Seven-Day Schedule Could Improve Hospital Quality, Capacity

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A new study evaluating outcomes for hospitals participating in the American Heart Association’s Get with the Guidelines program found no correlation between high performance on adhering to measures and care standards for acute myocardial infarction and for heart failure despite overlap between the sets of care processes (J Am Coll Cardio. 2011;58:637-644).

A total of 400,000 heart patients were studied, and 283 participating hospitals were stratified into thirds based on their adherence to core quality measures for each disease, with the upper third labeled superior in performance. Lead author Tracy Wang, MD, MHS, MSc, of the Duke Clinical Research Institute in Durham, N.C., and colleagues found that superior performance for only one of the two diseases led to such end-result outcomes as in-hospital mortality that were no better than for hospitals that were not high performers for either condition. But hospitals with superior performance for both conditions had lower in-hospital mortality rates.

“Perhaps quality is more than just following checklists,” Dr. Wang says. “There’s something special about these high-performing hospitals across the board, with better QI, perhaps a little more investment in infrastructure for quality.”

This result, Dr. Wang says, should give ammunition for hospitalists and other physicians to go to their hospital administrators to request more investment in quality improvement overall, not just for specific conditions.

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A new study evaluating outcomes for hospitals participating in the American Heart Association’s Get with the Guidelines program found no correlation between high performance on adhering to measures and care standards for acute myocardial infarction and for heart failure despite overlap between the sets of care processes (J Am Coll Cardio. 2011;58:637-644).

A total of 400,000 heart patients were studied, and 283 participating hospitals were stratified into thirds based on their adherence to core quality measures for each disease, with the upper third labeled superior in performance. Lead author Tracy Wang, MD, MHS, MSc, of the Duke Clinical Research Institute in Durham, N.C., and colleagues found that superior performance for only one of the two diseases led to such end-result outcomes as in-hospital mortality that were no better than for hospitals that were not high performers for either condition. But hospitals with superior performance for both conditions had lower in-hospital mortality rates.

“Perhaps quality is more than just following checklists,” Dr. Wang says. “There’s something special about these high-performing hospitals across the board, with better QI, perhaps a little more investment in infrastructure for quality.”

This result, Dr. Wang says, should give ammunition for hospitalists and other physicians to go to their hospital administrators to request more investment in quality improvement overall, not just for specific conditions.

A new study evaluating outcomes for hospitals participating in the American Heart Association’s Get with the Guidelines program found no correlation between high performance on adhering to measures and care standards for acute myocardial infarction and for heart failure despite overlap between the sets of care processes (J Am Coll Cardio. 2011;58:637-644).

A total of 400,000 heart patients were studied, and 283 participating hospitals were stratified into thirds based on their adherence to core quality measures for each disease, with the upper third labeled superior in performance. Lead author Tracy Wang, MD, MHS, MSc, of the Duke Clinical Research Institute in Durham, N.C., and colleagues found that superior performance for only one of the two diseases led to such end-result outcomes as in-hospital mortality that were no better than for hospitals that were not high performers for either condition. But hospitals with superior performance for both conditions had lower in-hospital mortality rates.

“Perhaps quality is more than just following checklists,” Dr. Wang says. “There’s something special about these high-performing hospitals across the board, with better QI, perhaps a little more investment in infrastructure for quality.”

This result, Dr. Wang says, should give ammunition for hospitalists and other physicians to go to their hospital administrators to request more investment in quality improvement overall, not just for specific conditions.

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Intermountain Risk Score Could Help Heart Failure Cases

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A risk measurement model created by the Heart Institute at Intermountain Medical Center in Murray, Utah, may one day be a familiar tool to HM groups.

Known as the Intermountain Risk Score (http://intermountainhealthcare.org/IMRS/), the tool uses 15 parameters culled from complete blood counts (CBC) and the basic metabolic profile (BMP) to determine risk. The model, which is free, was used to stratify mortality risk in heart failure patients receiving an internal cardioverter defibrillator (ICD) in a paper presented in September at the 15th annual scientific meeting of the Heart Failure Society of America.

The report found that mortality at one-year post-ICD was 2.4%, 11.8%, and 28.2% for the low-, moderate-, and high-risk groups, respectively. And while the study was narrow in its topic, Benjamin Horne, PhD, director of cardiovascular and genetic epidemiology at the institute, says its application to a multitude of inpatient settings is a natural evolution for the tool.

“One of the things about the innovation of this risk score is the lab tests are so common already,” Dr. Horne says. “They are so familiar to physicians. They’ve been around for decades. What no one had realized before is they had additional risk information contained within them.”

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A risk measurement model created by the Heart Institute at Intermountain Medical Center in Murray, Utah, may one day be a familiar tool to HM groups.

Known as the Intermountain Risk Score (http://intermountainhealthcare.org/IMRS/), the tool uses 15 parameters culled from complete blood counts (CBC) and the basic metabolic profile (BMP) to determine risk. The model, which is free, was used to stratify mortality risk in heart failure patients receiving an internal cardioverter defibrillator (ICD) in a paper presented in September at the 15th annual scientific meeting of the Heart Failure Society of America.

The report found that mortality at one-year post-ICD was 2.4%, 11.8%, and 28.2% for the low-, moderate-, and high-risk groups, respectively. And while the study was narrow in its topic, Benjamin Horne, PhD, director of cardiovascular and genetic epidemiology at the institute, says its application to a multitude of inpatient settings is a natural evolution for the tool.

“One of the things about the innovation of this risk score is the lab tests are so common already,” Dr. Horne says. “They are so familiar to physicians. They’ve been around for decades. What no one had realized before is they had additional risk information contained within them.”

A risk measurement model created by the Heart Institute at Intermountain Medical Center in Murray, Utah, may one day be a familiar tool to HM groups.

Known as the Intermountain Risk Score (http://intermountainhealthcare.org/IMRS/), the tool uses 15 parameters culled from complete blood counts (CBC) and the basic metabolic profile (BMP) to determine risk. The model, which is free, was used to stratify mortality risk in heart failure patients receiving an internal cardioverter defibrillator (ICD) in a paper presented in September at the 15th annual scientific meeting of the Heart Failure Society of America.

The report found that mortality at one-year post-ICD was 2.4%, 11.8%, and 28.2% for the low-, moderate-, and high-risk groups, respectively. And while the study was narrow in its topic, Benjamin Horne, PhD, director of cardiovascular and genetic epidemiology at the institute, says its application to a multitude of inpatient settings is a natural evolution for the tool.

“One of the things about the innovation of this risk score is the lab tests are so common already,” Dr. Horne says. “They are so familiar to physicians. They’ve been around for decades. What no one had realized before is they had additional risk information contained within them.”

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Pediatric HM Literature

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Pediatric HM Literature

Clinical question: What is the efficacy of dexamethasone in mechanically ventilated children younger than two years of age with respiratory syncytial virus (RSV) lower respiratory tract infections?

Background: Although RSV typically causes self-limited respiratory tract disease with stable and low mortality rates, a small proportion of infants will have severe lower respiratory tract disease requiring mechanical ventilation. The authors previously found no evidence of a benefit of corticosteroids in these infants, but post-hoc analysis suggested a benefit in infants with mild oxygenation abnormalities.

Study design: International, multicenter, randomized, double-blind, placebo-controlled trial.

Setting: Twelve ICUs in Europe.

Synopsis: All patients <2 years of age with RSV-positive bronchiolitis requiring mechanical ventilation were eligible if they had not received corticosteroids in the previous two weeks. Patients were categorized as having either mild or severe oxygenation abnormalities based on their arterial partial pressure of oxygen/fractional inspired oxygen concentration and/or mean airway pressure. The primary outcome measure was duration of mechanical ventilation, and the trial was stopped after interim analysis of 89 patients in the mild oxygenation abnormalities arm revealed insufficient power to detect a >20% difference between the groups if the planned number of 128 patients were ultimately enrolled.

Fifty-six patients were enrolled in the severe oxygenation abnormalities arm. For both groups, there were no differences in either the duration of mechanical ventilation or secondary outcomes, such as length of stay or duration of supplemental oxygen, between intervention and control patients.

This well-designed study adds to an established body of literature painting a clear picture of the inefficacy of corticosteroids in infants with bronchiolitis, with or without severe disease. Although enrollment was slow and ultimately the trial was prematurely terminated, the randomization resulted in almost perfectly matched groups, which likely strengthens the findings despite the small sample size.

Bottom line: Corticosteroids should not be administered to critically ill children with bronchiolitis.

Citation: Van Woensel JB, Vyas H, et al. Dexamethasone in children mechanically ventilated for lower respiratory tract infection caused by respiratory syncytial virus: a randomized controlled trial. Crit Care Med. 2011;39(7):1779-1783.

Reviewed by Pediatric Editor Mark Shen, MD, FHM, medical director of hospital medicine at Dell Children’s Medical Center, Austin, Texas.

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Clinical question: What is the efficacy of dexamethasone in mechanically ventilated children younger than two years of age with respiratory syncytial virus (RSV) lower respiratory tract infections?

Background: Although RSV typically causes self-limited respiratory tract disease with stable and low mortality rates, a small proportion of infants will have severe lower respiratory tract disease requiring mechanical ventilation. The authors previously found no evidence of a benefit of corticosteroids in these infants, but post-hoc analysis suggested a benefit in infants with mild oxygenation abnormalities.

Study design: International, multicenter, randomized, double-blind, placebo-controlled trial.

Setting: Twelve ICUs in Europe.

Synopsis: All patients <2 years of age with RSV-positive bronchiolitis requiring mechanical ventilation were eligible if they had not received corticosteroids in the previous two weeks. Patients were categorized as having either mild or severe oxygenation abnormalities based on their arterial partial pressure of oxygen/fractional inspired oxygen concentration and/or mean airway pressure. The primary outcome measure was duration of mechanical ventilation, and the trial was stopped after interim analysis of 89 patients in the mild oxygenation abnormalities arm revealed insufficient power to detect a >20% difference between the groups if the planned number of 128 patients were ultimately enrolled.

Fifty-six patients were enrolled in the severe oxygenation abnormalities arm. For both groups, there were no differences in either the duration of mechanical ventilation or secondary outcomes, such as length of stay or duration of supplemental oxygen, between intervention and control patients.

This well-designed study adds to an established body of literature painting a clear picture of the inefficacy of corticosteroids in infants with bronchiolitis, with or without severe disease. Although enrollment was slow and ultimately the trial was prematurely terminated, the randomization resulted in almost perfectly matched groups, which likely strengthens the findings despite the small sample size.

Bottom line: Corticosteroids should not be administered to critically ill children with bronchiolitis.

Citation: Van Woensel JB, Vyas H, et al. Dexamethasone in children mechanically ventilated for lower respiratory tract infection caused by respiratory syncytial virus: a randomized controlled trial. Crit Care Med. 2011;39(7):1779-1783.

Reviewed by Pediatric Editor Mark Shen, MD, FHM, medical director of hospital medicine at Dell Children’s Medical Center, Austin, Texas.

Clinical question: What is the efficacy of dexamethasone in mechanically ventilated children younger than two years of age with respiratory syncytial virus (RSV) lower respiratory tract infections?

Background: Although RSV typically causes self-limited respiratory tract disease with stable and low mortality rates, a small proportion of infants will have severe lower respiratory tract disease requiring mechanical ventilation. The authors previously found no evidence of a benefit of corticosteroids in these infants, but post-hoc analysis suggested a benefit in infants with mild oxygenation abnormalities.

Study design: International, multicenter, randomized, double-blind, placebo-controlled trial.

Setting: Twelve ICUs in Europe.

Synopsis: All patients <2 years of age with RSV-positive bronchiolitis requiring mechanical ventilation were eligible if they had not received corticosteroids in the previous two weeks. Patients were categorized as having either mild or severe oxygenation abnormalities based on their arterial partial pressure of oxygen/fractional inspired oxygen concentration and/or mean airway pressure. The primary outcome measure was duration of mechanical ventilation, and the trial was stopped after interim analysis of 89 patients in the mild oxygenation abnormalities arm revealed insufficient power to detect a >20% difference between the groups if the planned number of 128 patients were ultimately enrolled.

Fifty-six patients were enrolled in the severe oxygenation abnormalities arm. For both groups, there were no differences in either the duration of mechanical ventilation or secondary outcomes, such as length of stay or duration of supplemental oxygen, between intervention and control patients.

This well-designed study adds to an established body of literature painting a clear picture of the inefficacy of corticosteroids in infants with bronchiolitis, with or without severe disease. Although enrollment was slow and ultimately the trial was prematurely terminated, the randomization resulted in almost perfectly matched groups, which likely strengthens the findings despite the small sample size.

Bottom line: Corticosteroids should not be administered to critically ill children with bronchiolitis.

Citation: Van Woensel JB, Vyas H, et al. Dexamethasone in children mechanically ventilated for lower respiratory tract infection caused by respiratory syncytial virus: a randomized controlled trial. Crit Care Med. 2011;39(7):1779-1783.

Reviewed by Pediatric Editor Mark Shen, MD, FHM, medical director of hospital medicine at Dell Children’s Medical Center, Austin, Texas.

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Workplace Violence at Hospitals

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Risk factors of workplace violence at hospitals in Japan

Patients and their relatives exposed to mental stress caused by hospitalization or illness might use violence against healthcare staff. Previous surveys reported that healthcare staff experience more workplace violence than other industry workers.13 Workplace violence by patients or their relatives may cause psychological problems or somatic effects on healthcare staff, such as losing self‐respect, depression, post‐traumatic stress disorder, stomachache, headache, or insomnia. Because those effects might lead to higher than usual turnovers of healthcare staff at a hospital, and interfere with high‐quality healthcare services, workplace violence at healthcare settings became a global concern; a lot of studies investigating those circumstances mainly were conducted in developed countries.415 Those studies revealed that the psychiatric ward, the emergency room, or the long‐term care facilities were the high‐risk areas of workplace violence; the incidence rate of physical aggression in the past year ranged from 3% to 35%; and the incidence rate of verbal abuse in the past year ranged from 26% to 64%. But the overall circumstances are still unclear, because most of the subjects in those studies were limited to nurses or some departments, such as the psychiatric ward or the emergency room. There might be other professions or departments with higher risk of workplace violence.

The aim of this study was to investigate the incidence of workplace violence and the attributes of healthcare staff, such as profession, age, gender, departments, and so on, who are at high risk of experiencing workplace violence.

METHODS

A questionnaire‐based, anonymous, and self‐administered cross‐sectional survey was conducted at 19 hospitals in Japan from January to December 2009. Among the 19 hospitals, 8 hospitals had less than 200 beds, 7 hospitals had 200 to 500 beds for acute care, and 4 hospitals had more than 500 beds for acute care. Thirteen of 19 hospitals were teaching hospitals. Eight out of 19 hospitals were located in urban areas. The characteristics of the 19 hospitals are shown in Table 4 of Supporting Appendix (in the online version of this article). The questionnaires were distributed to all 11,095 healthcare staff with a sealed reply envelope, and were collected anonymously using a collection box at each hospital.

The questionnaire contained questions about workplace violence, the work environment, and other topics. This study classifies workplace violence into physical aggression, verbal abuse, and sexual harassment. The respondents were requested to reply in regard to their experiences with each of these 3 types of workplace violence by patients or their relatives, over the past year. In this article, only those 3 questions and some background information of respondents were used for analysis. The race of patients and medical staff was not investigated because Japan is a racially homogeneous nation, and more than 99% of the population is Asian.

Logistic regression analysis with forced entry of all variables to examine the effect of attributes of healthcare staff to workplace violence was used. In this analysis, random effects of each hospital or area were not taken into account. All analyses were performed using SPSS 18.0 (SPSS, Inc, Chicago, IL), and P < 0.05 was used to determine significance.

In this study, workplace violence was defined as an event that was subjectively recognized by healthcare staff as violence caused by patients or their relatives. The violence among healthcare staff was excluded.

RESULTS

The response rate was 79.1% (8711/11,095). Among the 8771 respondents, 36.4% experienced workplace violence by patients or their relatives over the past year; 15.9% experienced physical aggressions, 29.8% experienced verbal abuse, and 9.9% experienced sexual harassment. Table 1 provides characteristics of the respondents; Table 2 shows the proportion of victims for workplace violence.

Characteristics of Respondents
  No. of Respondents
n(%)*
  • Abbreviations: CCU, cardiac care unit; ICU, intensive care unit; NICU, neonatal intensive care unit.

  • Proportion of respondents among the total population.

  • Physicians usually do not belong to 1 section, but are included in the physicians' department.

No. of beds in their hospital<200 beds1298(14.8)
200‐500 beds3041(34.7)
500 beds or more4432(50.5)
SectionGeneral ward2377(27.1)
Administration department989(11.3)
Outpatient department675(7.7)
Physicians' department610(7.0)
Dietary department435(5.0)
Long‐term care ward331(3.8)
Rehabilitation department318(3.6)
Critical care center, ICU, or CCU306(3.5)
Obstetrics and gynecology ward, perinatal ward, or NICU287(3.3)
Clinical laboratory or physiology department266(3.0)
Operation department264(3.0)
Pharmaceutical department209(2.4)
Pediatric ward203(2.3)
Radiology department197(2.2)
Dialysis department104(1.2)
Psychiatric ward56(0.6)
Others1144(13.0)
ProfessionNurse4298(49.0)
Clerk1208(13.8)
Doctor610(7.0)
Nursing aide or care worker585(6.7)
Technician547(6.2)
Dietician or cook435(5.0)
Therapist313(3.6)
Pharmacist183(2.1)
Others592(6.7)
Years of experience in their own specialty or profession<5 yr3497(39.9)
6‐10 yr1618(18.4)
11‐15 yr1041(11.9)
16‐20 yr761(8.7)
21 yr or more1218(13.9)
Not reported636(7.3)
Working hours per week<20 hr640(7.3)
20‐40 hr1720(19.6)
40‐60 hr4638(52.9)
60 hr or more655(7.5)
Not reported1118(12.7)
GenderMale1941(22.1)
Female6272(71.5)
Not reported558(6.4)
Direct interaction or contact with patientsHaving those contacts7227(82.4)
Not having those contacts1001(11.4)
Not reported543(6.2)
Total 8771(100.0)
Proportion of Victims for Workplace Violence
  No. of RespondentsPhysical Aggression ExperienceVerbal Abuse ExperienceSexual Harassment ExperienceExperience of at Least 1 of the 3 Kinds of Violence
  nn(%)*n(%)*n(%)*n(%)*
No. of beds in their hospital<200 beds1298244(18.8)306(23.6)109(8.4)413(31.8)
200‐500 beds3041503(16.5)971(31.9)354(11.6)1173(38.6)
500 beds or more4432645(14.6)1338(30.2)406(9.2)1606(36.2)
SectionPsychiatric ward5633(58.9)37(66.1)8(14.3)42(75.0)
General ward2377852(35.8)1057(44.5)536(22.5)1371(57.7)
Dialysis department1045(4.8)44(42.3)24(23.1)55(52.9)
Critical care center, ICU, or CCU30690(29.4)108(35.3)41(13.4)151(49.3)
Long‐term care ward331108(32.6)109(32.9)38(11.5)157(47.4)
Outpatient department67547(7.0)268(39.7)44(6.5)292(43.3)
Physicians' department61033(5.4)193(31.6)6(1.0)203(33.3)
Pediatric ward20323(11.3)50(24.6)13(6.4)62(30.5)
Rehabilitation department31853(16.7)70(22.0)31(9.7)96(30.2)
Administration department98910(1.0)247(25.0)16(1.6)251(25.4)
Clinical radiology department19711(5.6)40(20.3)2(1.0)48(24.4)
Operation department26411(4.2)38(14.4)9(3.4)43(16.3)
Clinical laboratory or physiology department2664(1.5)37(13.9)9(3.4)43(16.2)
Obstetrics and gynecology ward, perinatal ward, or NICU2873(1.0)26(9.1)2(0.7)28(9.8)
Dietary department4357(1.6)39(9.0)8(1.8)42(9.7)
Pharmaceutical department2091(0.5)15(7.2)5(2.4)19(9.1)
Others1144101(8.8)237(20.7)77(6.7)289(25.3)
ProfessionNurse42981150(26.8)1694(39.4)729(17.0)2155(50.1)
Doctor61033(5.4)193(31.6)6(1.0)203(33.3)
Nursing aide or care worker585104(17.8)151(25.8)39(6.7)191(32.6)
Therapist31353(16.9)71(22.7)31(9.9)96(30.7)
Clerk120815(1.2)311(25.7)23(1.9)314(26.0)
Technician54715(2.7)79(14.4)19(3.5)97(17.7)
Dietician or cook4357(1.6)38(8.7)8(1.8)41(9.4)
Pharmacist1830(0.0)13(7.1)5(2.7)17(9.3)
Others59215(2.5)65(11.0)9(1.5)78(13.2)
Years of experience in their own specialty or profession<5 yr3497527(15.1)919(26.3)384(11.0)1183(33.8)
6‐10 yr1618316(19.5)510(31.5)183(11.3)636(39.3)
11‐15 yr1041210(20.2)350(33.6)125(12.0)421(40.4)
16‐20 yr761111(14.6)253(33.2)58(7.6)294(38.6)
21 yr or more1218160(13.1)422(34.6)85(7.0)475(39.0)
Not reported63668(10.7)161(25.3)34(5.3)183(28.8)
Working hours per week<20 hr64050(7.8)148(23.1)39(6.1)173(27.0)
20‐40 hr1720234(13.6)473(27.5)157(9.1)583(33.9)
40‐60 hr4638798(17.2)1424(30.7)498(10.7)1726(37.2)
60 hr or more655103(15.7)242(36.9)50(7.6)279(42.6)
Not reported1118207(18.5)328(29.3)125(11.2)431(38.6)
GenderMale1941185(9.5)471(24.3)77(4.0)529(27.3)
 Female62721137(18.1)2004(32.0)752(12.0)2494(39.8)
 Not reported55870(12.5)140(25.1)40(7.2)169(30.3)
Direct interaction or contact with patientsHaving those contacts72271325(18.3)2395(33.1)834(11.5)2945(40.7)
Not having those contacts100117(1.7)100(10.0)7(0.7)107(10.7)
Not reported54350(9.2)120(22.1)28(5.2)140(25.8)
Total 87711392(15.9)2615(29.8)869(9.9)3192(36.4)

Because of missing values, 6654 out of 8771 (75.9%) replies were used for the logistic regression analysis. Nagelkerke R2 for physical aggression was 0.33, for verbal abuse was 0.16, for sexual harassment was 0.23, and for at least one of the above types of violence was 0.23. The proportions of respondents, who had experienced each type of workplace violence, were not significantly different among the replies with missing data and with the effective data actually used.

Factors Associated With Higher Risk of Violence

Adjusted odds ratios of physical aggression were significantly high in general wards, psychiatric wards, critical care centers/emntensive care units (ICU)/cardiac care units (CCU), and long‐term care wards; and for nurses, nursing aides/care workers; for longer working hours; and for direct interaction with patients (Table 3).

Odds Ratio of Workplace Violence by Patients or Relatives
  Physical AggressionVerbal AbuseSexual HarassmentAt Least 1 of the 3 Kinds of Violence
  POdds Ratio (95%Cl)POdds Ratio (95%Cl)POdds Ratio (95%Cl)POdds Ratio (95%Cl)
  • Abbreviations: CCU, cardiac care unit; ICU, intensive care unit; NICU, neonatal intensive care unit.

  • P < 0.05.

  • Odds ratio of pharmaceutical department against physical aggression was not calculated because no staff experienced physical aggressions in the data set.

  • In order to avoid multicollinearity, Pharmacist and Dietician or cook were included in Others because they are correlated to the Pharmaceutical department and the Dietary department, respectively.

No. of beds in their hospital<200 beds 1.00  1.00  1.00  1.00 
200‐500 beds0.510.90(0.67‐1.22)<0.01*1.64(1.30‐2.07)0.191.27(0.89‐1.80)<0.01*1.45(1.16‐1.81)
500 beds or more0.02*0.69(0.51‐0.94)<0.01*1.57(1.24‐1.98)0.490.88(0.62‐1.26)0.01*1.32(1.06‐1.65)
SectionPhysicians' department 1.00  1.00  1.00  1.00 
Psychiatric ward<0.01*9.28(4.39‐19.62)<0.01*3.33(1.65‐6.70)0.690.80(0.27‐2.40)<0.01*4.55(2.07‐1.02)
Long‐term care ward<0.01*2.48(1.55‐3.96)<0.01*1.90(1.27‐2.86)0.651.15(0.63‐2.09)<0.01*2.20(1.50‐3.24)
General ward<0.01*3.00(2.18‐4.13)<0.01*1.73(1.36‐2.21)<0.01*1.89(1.32‐2.69)<0.01*1.98(1.57‐2.51)
Dialysis department0.02*0.32(0.12‐0.83)0.04*1.65(1.02‐2.66)0.01*2.21(1.23‐3.97)0.02*1.81(1.12‐2.92)
Critical care center, ICU, or CCU<0.01*2.44(1.60‐3.74)0.491.13(0.79‐1.61)0.561.17(0.70‐1.94)0.04*1.43(1.01‐2.01)
Administration department0.220.55(0.21‐1.44)0.071.38(0.98‐1.93)0.290.64(0.27‐1.48)0.071.37(0.98‐1.91)
Clinical radiology department0.531.42(0.48‐4.21)0.511.21(0.69‐2.12)0.02*0.17(0.04‐0.78)0.571.17(0.69‐1.98)
Rehabilitation department0.930.93(0.18‐4.77)0.881.08(0.42‐2.80)0.821.22(0.22‐6.79)0.771.14(0.46‐2.85)
Outpatient department<0.01*0.41(0.26‐0.65)0.03*1.35(1.02‐1.78)0.02*0.56(0.35‐0.90)0.401.12(0.86‐1.47)
Dietary department0.331.94(0.51‐7.35)0.661.13(0.65‐1.99)0.851.13(0.30‐4.26)0.841.06(0.61‐1.82)
Clinical laboratory or physiology department0.400.53(0.12‐2.34)0.851.06(0.59‐1.89)0.210.52(0.18‐1.45)0.870.96(0.55‐1.65)
Pediatric ward0.270.72(0.41‐1.29)0.080.69(0.45‐1.05)0.02*0.43(0.21‐0.90)0.03*0.65(0.43‐0.97)
Pharmaceutical department   0.050.52(0.26‐1.01)0.711.26(0.36‐4.38)0.140.63(0.34‐1.17)
Operation department<0.01*0.24(0.12‐0.48)<0.01*0.36(0.23‐0.55)<0.01*0.21(0.09‐0.48)<0.01*0.27(0.18‐0.41)
Obstetrics and gynecology ward, perinatal ward, or NICU<0.01*0.04(0.01‐0.18)<0.01*0.19(0.12‐0.32)<0.01*0.02(0.00‐0.18)<0.01*0.14(0.08‐0.22)
ProfessionDoctor 1.00  1.00  1.00 <0.01*1.00 
Nurse<0.01*4.09(2.41‐6.95)0.161.27(0.91‐1.76)<0.01*11.64(4.38‐30.90) 1.64(1.19‐2.26)
Therapist0.104.03(0.76‐21.28)0.830.90(0.34‐2.39)0.05*7.11(1.02‐49.3)0.831.11(0.43‐2.83)
Nursing aide or care worker0.03*1.95(1.07‐3.55)0.090.71(0.47‐1.05)<0.01*4.66(1.63‐13.31)0.190.77(0.53‐1.14)
Clerk0.03*0.36(0.14‐0.90)0.270.80(0.54‐1.19)0.172.26(0.70‐7.27)0.090.72(0.49‐1.06)
Technician0.270.55(0.19‐1.60)<0.01*0.37(0.22‐0.61)<0.01*6.92(2.20‐21.76)<0.01*0.46(0.28‐0.74)
Others<0.01*0.21(0.08‐0.57)<0.01*0.39(0.25‐0.60)0.242.14(0.60‐7.63)<0.01*0.39(0.25‐0.59)
Years of experience in their own specialty or profession<5 yr 1.00  1.00  1.00  1.00 
6‐10 yr<0.01*1.42(1.17‐1.72)0.01*1.22(1.05‐1.42)0.840.98(0.78‐1.22)0.01*1.22(1.05‐1.42)
11‐15 yr<0.01*1.64(1.31‐2.05)<0.01*1.45(1.22‐1.73)0.301.14(0.89‐1.47)<0.01*1.35(1.13‐1.60)
16‐20 yr0.301.16(0.88‐1.52)<0.01*1.47(1.21‐1.79)0.090.75(0.54‐1.04)<0.01*1.34(1.10‐1.63)
21 yr or more0.581.07(0.84‐1.37)<0.01*1.65(1.39‐1.96)<0.01*0.63(0.47‐0.85)<0.01*1.38(1.16‐1.64)
Working hours per week<20 hr 1.00  1.00  1.00  1.00 
20‐40 hr0.04*1.49(1.01‐2.19)0.521.08(0.85‐1.39)0.121.40(0.91‐2.15)0.101.23(0.96‐1.56)
40‐60 hr<0.01*1.80(1.25‐2.58)0.03*1.28(1.02‐1.60)0.05*1.50(1.00‐2.24)<0.01*1.39(1.11‐1.74)
60 hr or more<0.01*2.14(1.37‐3.34)<0.01*1.62(1.21‐2.17)0.141.49(0.88‐2.50)<0.01*1.90(1.43‐2.54)
Gender(Female vs male)0.690.95(0.76‐1.20)0.161.12(0.95‐1.32)<0.01*1.59(1.18‐2.12)0.01*1.22(1.05‐1.43)
Direct interaction or contact with patients(Constant and direct interaction with patients vs no interaction)0.02*2.17(1.11‐4.22)<0.01*2.46(1.87‐3.24)<0.01*6.80(2.43‐19.03)<0.01*2.58(1.97‐3.37)

Adjusted odds ratios of verbal abuse were significantly high in hospital with 200 beds or more, in general wards, psychiatric wards, long‐term care wards, outpatient departments, and dialysis departments; and for longer years of experience in their own specialty; for longer working hours; and for direct interaction with patients.

Adjusted odds ratios of sexual harassment were significantly high in general wards, and dialysis departments; for nurses, nursing aides/care workers, technicians, therapists; for females; and for direct interaction with patients.

Adjusted odds ratios for at least 1 of the 3 kinds of workplace violence were significantly high in hospitals with 200 beds or more, in general wards, psychiatric wards, critical care centers/ICU/CCU, long‐term care wards, and dialysis departments; for nurses; for longer years of experience in their own specialty; for longer working hours; for females; and for direct interaction with patients.

Factors Associated With Lower Risk of Violence

Adjusted odds ratios of physical aggression were significantly low in dialysis departments; outpatient departments; operation departments; obstetrics and gynecology wards, perinatal wards, or neonatal intensive care units (NICU); and for clerks.

Adjusted odds ratios of verbal abuse were significantly low in operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for technicians.

Adjusted odds ratios of sexual harassment were significantly low in clinical radiology departments; outpatient departments; pediatric wards; operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for longer years of experience in their own specialty.

Adjusted odds ratios for at least 1 of the 3 kinds of workplace violence were significantly low in pediatric wards; operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for technicians.

DISCUSSION

Among the healthcare staff, 36.4% experienced workplace violence by patients or their relatives over the past year; 15.9% experienced physical aggressions, 29.8% verbal abuse, and 9.9% sexual harassment. The risk factors of workplace violence identified in the present study were similar to those studies conducted not only in Japan, but also in Western countries. Though the target population was limited to Asians, our results can be applicable to other races, countries, and cultures.

Incidence of Workplace Violence

Most previous studies covered only specific professions at hospitals, such as nurses or critical care center staff, and there are only few multicenter studies covering entire sections and professions like this study.510, 1214 A Spanish study including about 8000 healthcare workers reported that 11% had experienced physical aggression, 64% had experienced threatening behavior, intimidation, or insults in the past year.11 The incidence of physical aggression was similar in both studies, but the incidence of verbal abuse was about twice as high as that of this study. The low response rate in the Spanish study (24%) might have contributed to a higher number of verbal abuse incidents, because those with experience of workplace violence would likely have answered the questionnaire. It is difficult to compare the incidence of workplace violence among different studies because the definitions of workplace violence differ widely. Ethnic culture might also affect the acknowledgement of workplace violence. The European NEXT study including about 30,000 nurses in 8 European countries reported a range of 10.4% incidence of workplace violence in the Netherlands, and 39.1% in France.10

Risk Factors of Physical Aggression

Previous studies reported that the prevalence of physical aggression is high in psychiatric wards, critical care centers, or long‐term care wards.1015 In these departments, patients with mental illness, postoperative delirium, or dementia are likely to be admitted.

Nurses and nursing aides are reported to be likely to experience physical aggression.3, 11, 15 Nurses and nursing aides have longer work hours with direct interaction with patients than other professions, and are considered to be at high risk of physical aggression.

Some studies, which did not examine influences by profession or department, reported that male was a risk factor for physical aggression and verbal abuse.6, 10, 11, 13 In this study though, the male gender was not associated with physical aggression or verbal abuse. Male nurses and nursing aides are likely to be assigned to high‐risk departments or to care for high‐risk patients. Gender may be confounded with variables such as profession or department.15

Longer work hours mean more frequent interaction with patients, and the risk for physical aggression might increase. Constant and direct interaction with patients is a risk factor, not only for physical aggression, but also for verbal abuse and sexual harassment.10

Risk Factors of Verbal Abuse

Previous studies reported that incidents of verbal abuse are high for nurses and nursing aides.15 Although in this study the proportion of verbal abuse was the highest in nurses (39.4%), adjusted odds ratio was not significant. Factors other than nurse profession, such as department and direct interaction with patients relating to the nurse profession, might be the higher risk factors for verbal abuse.

As reported in previous studies, psychiatric wards and long‐term care wards are risk factors of verbal abuse also in this study.10, 13, 15 Long waiting time at outpatient departments might increase the risk of verbal abuse.

Dialysis departments are at high risk of verbal abuse and sexual harassment. Compared to other outpatients, dialysis patients are forced to stay a long time in hospitals and there is, therefore, more interaction with nurses and technicians. The characteristic personality of dialysis patients, such as neuroticism or psychoticism, might also affect verbal abuse or sexual harassment.16

Because longer working hours mean more frequent interaction with patients, the risk of verbal abuse might increase.17 Managers with longer work experience might be at high risk for verbal abuse, because they often assume responsibility and take on the task of dealing with patients and their relevant complaints.11

Risk Factors of Sexual Harassment

Nurses are likely to experience sexual harassment because their public image seems to combine sexuality and maternalism.18 Nursing aides, technicians, and therapists also experience sexual harassment. The common risk factor among those professions is the direct contact with the patient's body during the patient's transfer. A lot of studies reported that female gender is a risk factor of sexual harassment.17, 19

Safety Factors of Workplace Violence

Adjusted odds ratios of operation departments, and obstetrics and gynecology wards, perinatal wards, or NICU were common safety factors for each type of workplace violence. Usually, the patients in operation rooms cannot talk or move a finger carelessly during the surgery. The fact that there are no adult male patients in obstetrics and gynecology wards, perinatal wards, or NICU, might have an influence on lower occurrence of workplace violence in these areas.

Limitations

This study used a questionnaire survey asking about subjective experiences of workplace violence over the 1 year before the study. There is the possibility of recall bias, and the same incident recognized as workplace violence by one person might not have been recognized as such by another person, because sensitivity differs among respondents.

In some categories with fewer respondents, such as the pharmaceutical department, it might be difficult to examine the exact confidence intervals of odds ratio. Further study with increased respondents of those categories is needed to confirm the odds ratios and the confidence intervals.

The rates of victims or risk for workplace violence were considered to vary with the character of the residents of each area or policy of each hospital. Therefore, a further analysis with adjustment for those factors is needed.

CONCLUSIONS

This study reveals that a significant proportion of healthcare staff (36.4%) has experienced workplace violence over the 1 year before the study was conducted and suggests that workplace violence is a serious problem. The attributes of healthcare staff who are at risk of workplace violence could be identified for each type of workplace violence. The mechanisms and the countermeasures for each type of workplace violence at those high‐risk areas should be further investigated. Further studies are necessary to confirm whether these findings are applicable to different races and different countries with different cultures.

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References
  1. Home Office. Violence at Work: Findings From the 2002/2003 British Crime Survey. Available at: http://www.homeoffice.gov.uk/rds/pdfs2/rdsolr0404.pdf. Accessed November 10,2010.
  2. Saarela KL,Isotalus N.Workplace violence in Finland: high‐risk groups and preventive strategies.Am J Ind Med Suppl.1999;1:8081.
  3. Duhart DT.Violence in the Workplace 1993–99, National Crime Victimization Survey,Washington, DC:Bureau of Justice Statistics;2001:112.
  4. Johnson SL.International perspectives on workplace bullying among nurses: a review.Int Nurs Rev.2009;56(1):3440.
  5. Farrell GA,Bobrowski C,Bobrowski P.Scoping workplace aggression in nursing: findings from an Australian study.J Adv Nurs.2006;55(6):778787.
  6. Gacki‐Smith J,Juarez AM,Boyett L, et al.Violence against nurses working in US emergency departments.J Nurs Adm.2009;39(7–8):340349.
  7. Chen WC,Hwu HG,Wang JD.Hospital staff responses to workplace violence in a psychiatric hospital in Taiwan.Int J Occup Environ Health.2009;15(2):173179.
  8. All Japan Hospital Association. Research on actual conditions of risk management system and workplace violence at hospitals (Japanese). Available at: http://www.ajha.or.jp/voice/pdf/other/080422.pdf. Accessed November 10, 2010.
  9. Wada K,Yoshida K,Sato E, et al.The present situation and the countermeasure for verbal abuse and physical aggression of patients (Japanese).Japan Medical Journal.2007;4354:8184.
  10. Camerino D,Estryn‐Behar M,Conway PM, et al.Work‐related factors and violence among nursing staff in the European NEXT study: a longitudinal cohort study.Int J Nurs Stud.2008;45(1):3550.
  11. Gascón S,Martínez‐Jarreta B,González‐Andrade JF, et al.Aggression towards health care workers in Spain: a multi‐facility study to evaluate the distribution of growing violence among professionals, health facilities and departments.Int J Occup Environ Health.2009;15(1):2935.
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Patients and their relatives exposed to mental stress caused by hospitalization or illness might use violence against healthcare staff. Previous surveys reported that healthcare staff experience more workplace violence than other industry workers.13 Workplace violence by patients or their relatives may cause psychological problems or somatic effects on healthcare staff, such as losing self‐respect, depression, post‐traumatic stress disorder, stomachache, headache, or insomnia. Because those effects might lead to higher than usual turnovers of healthcare staff at a hospital, and interfere with high‐quality healthcare services, workplace violence at healthcare settings became a global concern; a lot of studies investigating those circumstances mainly were conducted in developed countries.415 Those studies revealed that the psychiatric ward, the emergency room, or the long‐term care facilities were the high‐risk areas of workplace violence; the incidence rate of physical aggression in the past year ranged from 3% to 35%; and the incidence rate of verbal abuse in the past year ranged from 26% to 64%. But the overall circumstances are still unclear, because most of the subjects in those studies were limited to nurses or some departments, such as the psychiatric ward or the emergency room. There might be other professions or departments with higher risk of workplace violence.

The aim of this study was to investigate the incidence of workplace violence and the attributes of healthcare staff, such as profession, age, gender, departments, and so on, who are at high risk of experiencing workplace violence.

METHODS

A questionnaire‐based, anonymous, and self‐administered cross‐sectional survey was conducted at 19 hospitals in Japan from January to December 2009. Among the 19 hospitals, 8 hospitals had less than 200 beds, 7 hospitals had 200 to 500 beds for acute care, and 4 hospitals had more than 500 beds for acute care. Thirteen of 19 hospitals were teaching hospitals. Eight out of 19 hospitals were located in urban areas. The characteristics of the 19 hospitals are shown in Table 4 of Supporting Appendix (in the online version of this article). The questionnaires were distributed to all 11,095 healthcare staff with a sealed reply envelope, and were collected anonymously using a collection box at each hospital.

The questionnaire contained questions about workplace violence, the work environment, and other topics. This study classifies workplace violence into physical aggression, verbal abuse, and sexual harassment. The respondents were requested to reply in regard to their experiences with each of these 3 types of workplace violence by patients or their relatives, over the past year. In this article, only those 3 questions and some background information of respondents were used for analysis. The race of patients and medical staff was not investigated because Japan is a racially homogeneous nation, and more than 99% of the population is Asian.

Logistic regression analysis with forced entry of all variables to examine the effect of attributes of healthcare staff to workplace violence was used. In this analysis, random effects of each hospital or area were not taken into account. All analyses were performed using SPSS 18.0 (SPSS, Inc, Chicago, IL), and P < 0.05 was used to determine significance.

In this study, workplace violence was defined as an event that was subjectively recognized by healthcare staff as violence caused by patients or their relatives. The violence among healthcare staff was excluded.

RESULTS

The response rate was 79.1% (8711/11,095). Among the 8771 respondents, 36.4% experienced workplace violence by patients or their relatives over the past year; 15.9% experienced physical aggressions, 29.8% experienced verbal abuse, and 9.9% experienced sexual harassment. Table 1 provides characteristics of the respondents; Table 2 shows the proportion of victims for workplace violence.

Characteristics of Respondents
  No. of Respondents
n(%)*
  • Abbreviations: CCU, cardiac care unit; ICU, intensive care unit; NICU, neonatal intensive care unit.

  • Proportion of respondents among the total population.

  • Physicians usually do not belong to 1 section, but are included in the physicians' department.

No. of beds in their hospital<200 beds1298(14.8)
200‐500 beds3041(34.7)
500 beds or more4432(50.5)
SectionGeneral ward2377(27.1)
Administration department989(11.3)
Outpatient department675(7.7)
Physicians' department610(7.0)
Dietary department435(5.0)
Long‐term care ward331(3.8)
Rehabilitation department318(3.6)
Critical care center, ICU, or CCU306(3.5)
Obstetrics and gynecology ward, perinatal ward, or NICU287(3.3)
Clinical laboratory or physiology department266(3.0)
Operation department264(3.0)
Pharmaceutical department209(2.4)
Pediatric ward203(2.3)
Radiology department197(2.2)
Dialysis department104(1.2)
Psychiatric ward56(0.6)
Others1144(13.0)
ProfessionNurse4298(49.0)
Clerk1208(13.8)
Doctor610(7.0)
Nursing aide or care worker585(6.7)
Technician547(6.2)
Dietician or cook435(5.0)
Therapist313(3.6)
Pharmacist183(2.1)
Others592(6.7)
Years of experience in their own specialty or profession<5 yr3497(39.9)
6‐10 yr1618(18.4)
11‐15 yr1041(11.9)
16‐20 yr761(8.7)
21 yr or more1218(13.9)
Not reported636(7.3)
Working hours per week<20 hr640(7.3)
20‐40 hr1720(19.6)
40‐60 hr4638(52.9)
60 hr or more655(7.5)
Not reported1118(12.7)
GenderMale1941(22.1)
Female6272(71.5)
Not reported558(6.4)
Direct interaction or contact with patientsHaving those contacts7227(82.4)
Not having those contacts1001(11.4)
Not reported543(6.2)
Total 8771(100.0)
Proportion of Victims for Workplace Violence
  No. of RespondentsPhysical Aggression ExperienceVerbal Abuse ExperienceSexual Harassment ExperienceExperience of at Least 1 of the 3 Kinds of Violence
  nn(%)*n(%)*n(%)*n(%)*
No. of beds in their hospital<200 beds1298244(18.8)306(23.6)109(8.4)413(31.8)
200‐500 beds3041503(16.5)971(31.9)354(11.6)1173(38.6)
500 beds or more4432645(14.6)1338(30.2)406(9.2)1606(36.2)
SectionPsychiatric ward5633(58.9)37(66.1)8(14.3)42(75.0)
General ward2377852(35.8)1057(44.5)536(22.5)1371(57.7)
Dialysis department1045(4.8)44(42.3)24(23.1)55(52.9)
Critical care center, ICU, or CCU30690(29.4)108(35.3)41(13.4)151(49.3)
Long‐term care ward331108(32.6)109(32.9)38(11.5)157(47.4)
Outpatient department67547(7.0)268(39.7)44(6.5)292(43.3)
Physicians' department61033(5.4)193(31.6)6(1.0)203(33.3)
Pediatric ward20323(11.3)50(24.6)13(6.4)62(30.5)
Rehabilitation department31853(16.7)70(22.0)31(9.7)96(30.2)
Administration department98910(1.0)247(25.0)16(1.6)251(25.4)
Clinical radiology department19711(5.6)40(20.3)2(1.0)48(24.4)
Operation department26411(4.2)38(14.4)9(3.4)43(16.3)
Clinical laboratory or physiology department2664(1.5)37(13.9)9(3.4)43(16.2)
Obstetrics and gynecology ward, perinatal ward, or NICU2873(1.0)26(9.1)2(0.7)28(9.8)
Dietary department4357(1.6)39(9.0)8(1.8)42(9.7)
Pharmaceutical department2091(0.5)15(7.2)5(2.4)19(9.1)
Others1144101(8.8)237(20.7)77(6.7)289(25.3)
ProfessionNurse42981150(26.8)1694(39.4)729(17.0)2155(50.1)
Doctor61033(5.4)193(31.6)6(1.0)203(33.3)
Nursing aide or care worker585104(17.8)151(25.8)39(6.7)191(32.6)
Therapist31353(16.9)71(22.7)31(9.9)96(30.7)
Clerk120815(1.2)311(25.7)23(1.9)314(26.0)
Technician54715(2.7)79(14.4)19(3.5)97(17.7)
Dietician or cook4357(1.6)38(8.7)8(1.8)41(9.4)
Pharmacist1830(0.0)13(7.1)5(2.7)17(9.3)
Others59215(2.5)65(11.0)9(1.5)78(13.2)
Years of experience in their own specialty or profession<5 yr3497527(15.1)919(26.3)384(11.0)1183(33.8)
6‐10 yr1618316(19.5)510(31.5)183(11.3)636(39.3)
11‐15 yr1041210(20.2)350(33.6)125(12.0)421(40.4)
16‐20 yr761111(14.6)253(33.2)58(7.6)294(38.6)
21 yr or more1218160(13.1)422(34.6)85(7.0)475(39.0)
Not reported63668(10.7)161(25.3)34(5.3)183(28.8)
Working hours per week<20 hr64050(7.8)148(23.1)39(6.1)173(27.0)
20‐40 hr1720234(13.6)473(27.5)157(9.1)583(33.9)
40‐60 hr4638798(17.2)1424(30.7)498(10.7)1726(37.2)
60 hr or more655103(15.7)242(36.9)50(7.6)279(42.6)
Not reported1118207(18.5)328(29.3)125(11.2)431(38.6)
GenderMale1941185(9.5)471(24.3)77(4.0)529(27.3)
 Female62721137(18.1)2004(32.0)752(12.0)2494(39.8)
 Not reported55870(12.5)140(25.1)40(7.2)169(30.3)
Direct interaction or contact with patientsHaving those contacts72271325(18.3)2395(33.1)834(11.5)2945(40.7)
Not having those contacts100117(1.7)100(10.0)7(0.7)107(10.7)
Not reported54350(9.2)120(22.1)28(5.2)140(25.8)
Total 87711392(15.9)2615(29.8)869(9.9)3192(36.4)

Because of missing values, 6654 out of 8771 (75.9%) replies were used for the logistic regression analysis. Nagelkerke R2 for physical aggression was 0.33, for verbal abuse was 0.16, for sexual harassment was 0.23, and for at least one of the above types of violence was 0.23. The proportions of respondents, who had experienced each type of workplace violence, were not significantly different among the replies with missing data and with the effective data actually used.

Factors Associated With Higher Risk of Violence

Adjusted odds ratios of physical aggression were significantly high in general wards, psychiatric wards, critical care centers/emntensive care units (ICU)/cardiac care units (CCU), and long‐term care wards; and for nurses, nursing aides/care workers; for longer working hours; and for direct interaction with patients (Table 3).

Odds Ratio of Workplace Violence by Patients or Relatives
  Physical AggressionVerbal AbuseSexual HarassmentAt Least 1 of the 3 Kinds of Violence
  POdds Ratio (95%Cl)POdds Ratio (95%Cl)POdds Ratio (95%Cl)POdds Ratio (95%Cl)
  • Abbreviations: CCU, cardiac care unit; ICU, intensive care unit; NICU, neonatal intensive care unit.

  • P < 0.05.

  • Odds ratio of pharmaceutical department against physical aggression was not calculated because no staff experienced physical aggressions in the data set.

  • In order to avoid multicollinearity, Pharmacist and Dietician or cook were included in Others because they are correlated to the Pharmaceutical department and the Dietary department, respectively.

No. of beds in their hospital<200 beds 1.00  1.00  1.00  1.00 
200‐500 beds0.510.90(0.67‐1.22)<0.01*1.64(1.30‐2.07)0.191.27(0.89‐1.80)<0.01*1.45(1.16‐1.81)
500 beds or more0.02*0.69(0.51‐0.94)<0.01*1.57(1.24‐1.98)0.490.88(0.62‐1.26)0.01*1.32(1.06‐1.65)
SectionPhysicians' department 1.00  1.00  1.00  1.00 
Psychiatric ward<0.01*9.28(4.39‐19.62)<0.01*3.33(1.65‐6.70)0.690.80(0.27‐2.40)<0.01*4.55(2.07‐1.02)
Long‐term care ward<0.01*2.48(1.55‐3.96)<0.01*1.90(1.27‐2.86)0.651.15(0.63‐2.09)<0.01*2.20(1.50‐3.24)
General ward<0.01*3.00(2.18‐4.13)<0.01*1.73(1.36‐2.21)<0.01*1.89(1.32‐2.69)<0.01*1.98(1.57‐2.51)
Dialysis department0.02*0.32(0.12‐0.83)0.04*1.65(1.02‐2.66)0.01*2.21(1.23‐3.97)0.02*1.81(1.12‐2.92)
Critical care center, ICU, or CCU<0.01*2.44(1.60‐3.74)0.491.13(0.79‐1.61)0.561.17(0.70‐1.94)0.04*1.43(1.01‐2.01)
Administration department0.220.55(0.21‐1.44)0.071.38(0.98‐1.93)0.290.64(0.27‐1.48)0.071.37(0.98‐1.91)
Clinical radiology department0.531.42(0.48‐4.21)0.511.21(0.69‐2.12)0.02*0.17(0.04‐0.78)0.571.17(0.69‐1.98)
Rehabilitation department0.930.93(0.18‐4.77)0.881.08(0.42‐2.80)0.821.22(0.22‐6.79)0.771.14(0.46‐2.85)
Outpatient department<0.01*0.41(0.26‐0.65)0.03*1.35(1.02‐1.78)0.02*0.56(0.35‐0.90)0.401.12(0.86‐1.47)
Dietary department0.331.94(0.51‐7.35)0.661.13(0.65‐1.99)0.851.13(0.30‐4.26)0.841.06(0.61‐1.82)
Clinical laboratory or physiology department0.400.53(0.12‐2.34)0.851.06(0.59‐1.89)0.210.52(0.18‐1.45)0.870.96(0.55‐1.65)
Pediatric ward0.270.72(0.41‐1.29)0.080.69(0.45‐1.05)0.02*0.43(0.21‐0.90)0.03*0.65(0.43‐0.97)
Pharmaceutical department   0.050.52(0.26‐1.01)0.711.26(0.36‐4.38)0.140.63(0.34‐1.17)
Operation department<0.01*0.24(0.12‐0.48)<0.01*0.36(0.23‐0.55)<0.01*0.21(0.09‐0.48)<0.01*0.27(0.18‐0.41)
Obstetrics and gynecology ward, perinatal ward, or NICU<0.01*0.04(0.01‐0.18)<0.01*0.19(0.12‐0.32)<0.01*0.02(0.00‐0.18)<0.01*0.14(0.08‐0.22)
ProfessionDoctor 1.00  1.00  1.00 <0.01*1.00 
Nurse<0.01*4.09(2.41‐6.95)0.161.27(0.91‐1.76)<0.01*11.64(4.38‐30.90) 1.64(1.19‐2.26)
Therapist0.104.03(0.76‐21.28)0.830.90(0.34‐2.39)0.05*7.11(1.02‐49.3)0.831.11(0.43‐2.83)
Nursing aide or care worker0.03*1.95(1.07‐3.55)0.090.71(0.47‐1.05)<0.01*4.66(1.63‐13.31)0.190.77(0.53‐1.14)
Clerk0.03*0.36(0.14‐0.90)0.270.80(0.54‐1.19)0.172.26(0.70‐7.27)0.090.72(0.49‐1.06)
Technician0.270.55(0.19‐1.60)<0.01*0.37(0.22‐0.61)<0.01*6.92(2.20‐21.76)<0.01*0.46(0.28‐0.74)
Others<0.01*0.21(0.08‐0.57)<0.01*0.39(0.25‐0.60)0.242.14(0.60‐7.63)<0.01*0.39(0.25‐0.59)
Years of experience in their own specialty or profession<5 yr 1.00  1.00  1.00  1.00 
6‐10 yr<0.01*1.42(1.17‐1.72)0.01*1.22(1.05‐1.42)0.840.98(0.78‐1.22)0.01*1.22(1.05‐1.42)
11‐15 yr<0.01*1.64(1.31‐2.05)<0.01*1.45(1.22‐1.73)0.301.14(0.89‐1.47)<0.01*1.35(1.13‐1.60)
16‐20 yr0.301.16(0.88‐1.52)<0.01*1.47(1.21‐1.79)0.090.75(0.54‐1.04)<0.01*1.34(1.10‐1.63)
21 yr or more0.581.07(0.84‐1.37)<0.01*1.65(1.39‐1.96)<0.01*0.63(0.47‐0.85)<0.01*1.38(1.16‐1.64)
Working hours per week<20 hr 1.00  1.00  1.00  1.00 
20‐40 hr0.04*1.49(1.01‐2.19)0.521.08(0.85‐1.39)0.121.40(0.91‐2.15)0.101.23(0.96‐1.56)
40‐60 hr<0.01*1.80(1.25‐2.58)0.03*1.28(1.02‐1.60)0.05*1.50(1.00‐2.24)<0.01*1.39(1.11‐1.74)
60 hr or more<0.01*2.14(1.37‐3.34)<0.01*1.62(1.21‐2.17)0.141.49(0.88‐2.50)<0.01*1.90(1.43‐2.54)
Gender(Female vs male)0.690.95(0.76‐1.20)0.161.12(0.95‐1.32)<0.01*1.59(1.18‐2.12)0.01*1.22(1.05‐1.43)
Direct interaction or contact with patients(Constant and direct interaction with patients vs no interaction)0.02*2.17(1.11‐4.22)<0.01*2.46(1.87‐3.24)<0.01*6.80(2.43‐19.03)<0.01*2.58(1.97‐3.37)

Adjusted odds ratios of verbal abuse were significantly high in hospital with 200 beds or more, in general wards, psychiatric wards, long‐term care wards, outpatient departments, and dialysis departments; and for longer years of experience in their own specialty; for longer working hours; and for direct interaction with patients.

Adjusted odds ratios of sexual harassment were significantly high in general wards, and dialysis departments; for nurses, nursing aides/care workers, technicians, therapists; for females; and for direct interaction with patients.

Adjusted odds ratios for at least 1 of the 3 kinds of workplace violence were significantly high in hospitals with 200 beds or more, in general wards, psychiatric wards, critical care centers/ICU/CCU, long‐term care wards, and dialysis departments; for nurses; for longer years of experience in their own specialty; for longer working hours; for females; and for direct interaction with patients.

Factors Associated With Lower Risk of Violence

Adjusted odds ratios of physical aggression were significantly low in dialysis departments; outpatient departments; operation departments; obstetrics and gynecology wards, perinatal wards, or neonatal intensive care units (NICU); and for clerks.

Adjusted odds ratios of verbal abuse were significantly low in operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for technicians.

Adjusted odds ratios of sexual harassment were significantly low in clinical radiology departments; outpatient departments; pediatric wards; operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for longer years of experience in their own specialty.

Adjusted odds ratios for at least 1 of the 3 kinds of workplace violence were significantly low in pediatric wards; operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for technicians.

DISCUSSION

Among the healthcare staff, 36.4% experienced workplace violence by patients or their relatives over the past year; 15.9% experienced physical aggressions, 29.8% verbal abuse, and 9.9% sexual harassment. The risk factors of workplace violence identified in the present study were similar to those studies conducted not only in Japan, but also in Western countries. Though the target population was limited to Asians, our results can be applicable to other races, countries, and cultures.

Incidence of Workplace Violence

Most previous studies covered only specific professions at hospitals, such as nurses or critical care center staff, and there are only few multicenter studies covering entire sections and professions like this study.510, 1214 A Spanish study including about 8000 healthcare workers reported that 11% had experienced physical aggression, 64% had experienced threatening behavior, intimidation, or insults in the past year.11 The incidence of physical aggression was similar in both studies, but the incidence of verbal abuse was about twice as high as that of this study. The low response rate in the Spanish study (24%) might have contributed to a higher number of verbal abuse incidents, because those with experience of workplace violence would likely have answered the questionnaire. It is difficult to compare the incidence of workplace violence among different studies because the definitions of workplace violence differ widely. Ethnic culture might also affect the acknowledgement of workplace violence. The European NEXT study including about 30,000 nurses in 8 European countries reported a range of 10.4% incidence of workplace violence in the Netherlands, and 39.1% in France.10

Risk Factors of Physical Aggression

Previous studies reported that the prevalence of physical aggression is high in psychiatric wards, critical care centers, or long‐term care wards.1015 In these departments, patients with mental illness, postoperative delirium, or dementia are likely to be admitted.

Nurses and nursing aides are reported to be likely to experience physical aggression.3, 11, 15 Nurses and nursing aides have longer work hours with direct interaction with patients than other professions, and are considered to be at high risk of physical aggression.

Some studies, which did not examine influences by profession or department, reported that male was a risk factor for physical aggression and verbal abuse.6, 10, 11, 13 In this study though, the male gender was not associated with physical aggression or verbal abuse. Male nurses and nursing aides are likely to be assigned to high‐risk departments or to care for high‐risk patients. Gender may be confounded with variables such as profession or department.15

Longer work hours mean more frequent interaction with patients, and the risk for physical aggression might increase. Constant and direct interaction with patients is a risk factor, not only for physical aggression, but also for verbal abuse and sexual harassment.10

Risk Factors of Verbal Abuse

Previous studies reported that incidents of verbal abuse are high for nurses and nursing aides.15 Although in this study the proportion of verbal abuse was the highest in nurses (39.4%), adjusted odds ratio was not significant. Factors other than nurse profession, such as department and direct interaction with patients relating to the nurse profession, might be the higher risk factors for verbal abuse.

As reported in previous studies, psychiatric wards and long‐term care wards are risk factors of verbal abuse also in this study.10, 13, 15 Long waiting time at outpatient departments might increase the risk of verbal abuse.

Dialysis departments are at high risk of verbal abuse and sexual harassment. Compared to other outpatients, dialysis patients are forced to stay a long time in hospitals and there is, therefore, more interaction with nurses and technicians. The characteristic personality of dialysis patients, such as neuroticism or psychoticism, might also affect verbal abuse or sexual harassment.16

Because longer working hours mean more frequent interaction with patients, the risk of verbal abuse might increase.17 Managers with longer work experience might be at high risk for verbal abuse, because they often assume responsibility and take on the task of dealing with patients and their relevant complaints.11

Risk Factors of Sexual Harassment

Nurses are likely to experience sexual harassment because their public image seems to combine sexuality and maternalism.18 Nursing aides, technicians, and therapists also experience sexual harassment. The common risk factor among those professions is the direct contact with the patient's body during the patient's transfer. A lot of studies reported that female gender is a risk factor of sexual harassment.17, 19

Safety Factors of Workplace Violence

Adjusted odds ratios of operation departments, and obstetrics and gynecology wards, perinatal wards, or NICU were common safety factors for each type of workplace violence. Usually, the patients in operation rooms cannot talk or move a finger carelessly during the surgery. The fact that there are no adult male patients in obstetrics and gynecology wards, perinatal wards, or NICU, might have an influence on lower occurrence of workplace violence in these areas.

Limitations

This study used a questionnaire survey asking about subjective experiences of workplace violence over the 1 year before the study. There is the possibility of recall bias, and the same incident recognized as workplace violence by one person might not have been recognized as such by another person, because sensitivity differs among respondents.

In some categories with fewer respondents, such as the pharmaceutical department, it might be difficult to examine the exact confidence intervals of odds ratio. Further study with increased respondents of those categories is needed to confirm the odds ratios and the confidence intervals.

The rates of victims or risk for workplace violence were considered to vary with the character of the residents of each area or policy of each hospital. Therefore, a further analysis with adjustment for those factors is needed.

CONCLUSIONS

This study reveals that a significant proportion of healthcare staff (36.4%) has experienced workplace violence over the 1 year before the study was conducted and suggests that workplace violence is a serious problem. The attributes of healthcare staff who are at risk of workplace violence could be identified for each type of workplace violence. The mechanisms and the countermeasures for each type of workplace violence at those high‐risk areas should be further investigated. Further studies are necessary to confirm whether these findings are applicable to different races and different countries with different cultures.

Patients and their relatives exposed to mental stress caused by hospitalization or illness might use violence against healthcare staff. Previous surveys reported that healthcare staff experience more workplace violence than other industry workers.13 Workplace violence by patients or their relatives may cause psychological problems or somatic effects on healthcare staff, such as losing self‐respect, depression, post‐traumatic stress disorder, stomachache, headache, or insomnia. Because those effects might lead to higher than usual turnovers of healthcare staff at a hospital, and interfere with high‐quality healthcare services, workplace violence at healthcare settings became a global concern; a lot of studies investigating those circumstances mainly were conducted in developed countries.415 Those studies revealed that the psychiatric ward, the emergency room, or the long‐term care facilities were the high‐risk areas of workplace violence; the incidence rate of physical aggression in the past year ranged from 3% to 35%; and the incidence rate of verbal abuse in the past year ranged from 26% to 64%. But the overall circumstances are still unclear, because most of the subjects in those studies were limited to nurses or some departments, such as the psychiatric ward or the emergency room. There might be other professions or departments with higher risk of workplace violence.

The aim of this study was to investigate the incidence of workplace violence and the attributes of healthcare staff, such as profession, age, gender, departments, and so on, who are at high risk of experiencing workplace violence.

METHODS

A questionnaire‐based, anonymous, and self‐administered cross‐sectional survey was conducted at 19 hospitals in Japan from January to December 2009. Among the 19 hospitals, 8 hospitals had less than 200 beds, 7 hospitals had 200 to 500 beds for acute care, and 4 hospitals had more than 500 beds for acute care. Thirteen of 19 hospitals were teaching hospitals. Eight out of 19 hospitals were located in urban areas. The characteristics of the 19 hospitals are shown in Table 4 of Supporting Appendix (in the online version of this article). The questionnaires were distributed to all 11,095 healthcare staff with a sealed reply envelope, and were collected anonymously using a collection box at each hospital.

The questionnaire contained questions about workplace violence, the work environment, and other topics. This study classifies workplace violence into physical aggression, verbal abuse, and sexual harassment. The respondents were requested to reply in regard to their experiences with each of these 3 types of workplace violence by patients or their relatives, over the past year. In this article, only those 3 questions and some background information of respondents were used for analysis. The race of patients and medical staff was not investigated because Japan is a racially homogeneous nation, and more than 99% of the population is Asian.

Logistic regression analysis with forced entry of all variables to examine the effect of attributes of healthcare staff to workplace violence was used. In this analysis, random effects of each hospital or area were not taken into account. All analyses were performed using SPSS 18.0 (SPSS, Inc, Chicago, IL), and P < 0.05 was used to determine significance.

In this study, workplace violence was defined as an event that was subjectively recognized by healthcare staff as violence caused by patients or their relatives. The violence among healthcare staff was excluded.

RESULTS

The response rate was 79.1% (8711/11,095). Among the 8771 respondents, 36.4% experienced workplace violence by patients or their relatives over the past year; 15.9% experienced physical aggressions, 29.8% experienced verbal abuse, and 9.9% experienced sexual harassment. Table 1 provides characteristics of the respondents; Table 2 shows the proportion of victims for workplace violence.

Characteristics of Respondents
  No. of Respondents
n(%)*
  • Abbreviations: CCU, cardiac care unit; ICU, intensive care unit; NICU, neonatal intensive care unit.

  • Proportion of respondents among the total population.

  • Physicians usually do not belong to 1 section, but are included in the physicians' department.

No. of beds in their hospital<200 beds1298(14.8)
200‐500 beds3041(34.7)
500 beds or more4432(50.5)
SectionGeneral ward2377(27.1)
Administration department989(11.3)
Outpatient department675(7.7)
Physicians' department610(7.0)
Dietary department435(5.0)
Long‐term care ward331(3.8)
Rehabilitation department318(3.6)
Critical care center, ICU, or CCU306(3.5)
Obstetrics and gynecology ward, perinatal ward, or NICU287(3.3)
Clinical laboratory or physiology department266(3.0)
Operation department264(3.0)
Pharmaceutical department209(2.4)
Pediatric ward203(2.3)
Radiology department197(2.2)
Dialysis department104(1.2)
Psychiatric ward56(0.6)
Others1144(13.0)
ProfessionNurse4298(49.0)
Clerk1208(13.8)
Doctor610(7.0)
Nursing aide or care worker585(6.7)
Technician547(6.2)
Dietician or cook435(5.0)
Therapist313(3.6)
Pharmacist183(2.1)
Others592(6.7)
Years of experience in their own specialty or profession<5 yr3497(39.9)
6‐10 yr1618(18.4)
11‐15 yr1041(11.9)
16‐20 yr761(8.7)
21 yr or more1218(13.9)
Not reported636(7.3)
Working hours per week<20 hr640(7.3)
20‐40 hr1720(19.6)
40‐60 hr4638(52.9)
60 hr or more655(7.5)
Not reported1118(12.7)
GenderMale1941(22.1)
Female6272(71.5)
Not reported558(6.4)
Direct interaction or contact with patientsHaving those contacts7227(82.4)
Not having those contacts1001(11.4)
Not reported543(6.2)
Total 8771(100.0)
Proportion of Victims for Workplace Violence
  No. of RespondentsPhysical Aggression ExperienceVerbal Abuse ExperienceSexual Harassment ExperienceExperience of at Least 1 of the 3 Kinds of Violence
  nn(%)*n(%)*n(%)*n(%)*
No. of beds in their hospital<200 beds1298244(18.8)306(23.6)109(8.4)413(31.8)
200‐500 beds3041503(16.5)971(31.9)354(11.6)1173(38.6)
500 beds or more4432645(14.6)1338(30.2)406(9.2)1606(36.2)
SectionPsychiatric ward5633(58.9)37(66.1)8(14.3)42(75.0)
General ward2377852(35.8)1057(44.5)536(22.5)1371(57.7)
Dialysis department1045(4.8)44(42.3)24(23.1)55(52.9)
Critical care center, ICU, or CCU30690(29.4)108(35.3)41(13.4)151(49.3)
Long‐term care ward331108(32.6)109(32.9)38(11.5)157(47.4)
Outpatient department67547(7.0)268(39.7)44(6.5)292(43.3)
Physicians' department61033(5.4)193(31.6)6(1.0)203(33.3)
Pediatric ward20323(11.3)50(24.6)13(6.4)62(30.5)
Rehabilitation department31853(16.7)70(22.0)31(9.7)96(30.2)
Administration department98910(1.0)247(25.0)16(1.6)251(25.4)
Clinical radiology department19711(5.6)40(20.3)2(1.0)48(24.4)
Operation department26411(4.2)38(14.4)9(3.4)43(16.3)
Clinical laboratory or physiology department2664(1.5)37(13.9)9(3.4)43(16.2)
Obstetrics and gynecology ward, perinatal ward, or NICU2873(1.0)26(9.1)2(0.7)28(9.8)
Dietary department4357(1.6)39(9.0)8(1.8)42(9.7)
Pharmaceutical department2091(0.5)15(7.2)5(2.4)19(9.1)
Others1144101(8.8)237(20.7)77(6.7)289(25.3)
ProfessionNurse42981150(26.8)1694(39.4)729(17.0)2155(50.1)
Doctor61033(5.4)193(31.6)6(1.0)203(33.3)
Nursing aide or care worker585104(17.8)151(25.8)39(6.7)191(32.6)
Therapist31353(16.9)71(22.7)31(9.9)96(30.7)
Clerk120815(1.2)311(25.7)23(1.9)314(26.0)
Technician54715(2.7)79(14.4)19(3.5)97(17.7)
Dietician or cook4357(1.6)38(8.7)8(1.8)41(9.4)
Pharmacist1830(0.0)13(7.1)5(2.7)17(9.3)
Others59215(2.5)65(11.0)9(1.5)78(13.2)
Years of experience in their own specialty or profession<5 yr3497527(15.1)919(26.3)384(11.0)1183(33.8)
6‐10 yr1618316(19.5)510(31.5)183(11.3)636(39.3)
11‐15 yr1041210(20.2)350(33.6)125(12.0)421(40.4)
16‐20 yr761111(14.6)253(33.2)58(7.6)294(38.6)
21 yr or more1218160(13.1)422(34.6)85(7.0)475(39.0)
Not reported63668(10.7)161(25.3)34(5.3)183(28.8)
Working hours per week<20 hr64050(7.8)148(23.1)39(6.1)173(27.0)
20‐40 hr1720234(13.6)473(27.5)157(9.1)583(33.9)
40‐60 hr4638798(17.2)1424(30.7)498(10.7)1726(37.2)
60 hr or more655103(15.7)242(36.9)50(7.6)279(42.6)
Not reported1118207(18.5)328(29.3)125(11.2)431(38.6)
GenderMale1941185(9.5)471(24.3)77(4.0)529(27.3)
 Female62721137(18.1)2004(32.0)752(12.0)2494(39.8)
 Not reported55870(12.5)140(25.1)40(7.2)169(30.3)
Direct interaction or contact with patientsHaving those contacts72271325(18.3)2395(33.1)834(11.5)2945(40.7)
Not having those contacts100117(1.7)100(10.0)7(0.7)107(10.7)
Not reported54350(9.2)120(22.1)28(5.2)140(25.8)
Total 87711392(15.9)2615(29.8)869(9.9)3192(36.4)

Because of missing values, 6654 out of 8771 (75.9%) replies were used for the logistic regression analysis. Nagelkerke R2 for physical aggression was 0.33, for verbal abuse was 0.16, for sexual harassment was 0.23, and for at least one of the above types of violence was 0.23. The proportions of respondents, who had experienced each type of workplace violence, were not significantly different among the replies with missing data and with the effective data actually used.

Factors Associated With Higher Risk of Violence

Adjusted odds ratios of physical aggression were significantly high in general wards, psychiatric wards, critical care centers/emntensive care units (ICU)/cardiac care units (CCU), and long‐term care wards; and for nurses, nursing aides/care workers; for longer working hours; and for direct interaction with patients (Table 3).

Odds Ratio of Workplace Violence by Patients or Relatives
  Physical AggressionVerbal AbuseSexual HarassmentAt Least 1 of the 3 Kinds of Violence
  POdds Ratio (95%Cl)POdds Ratio (95%Cl)POdds Ratio (95%Cl)POdds Ratio (95%Cl)
  • Abbreviations: CCU, cardiac care unit; ICU, intensive care unit; NICU, neonatal intensive care unit.

  • P < 0.05.

  • Odds ratio of pharmaceutical department against physical aggression was not calculated because no staff experienced physical aggressions in the data set.

  • In order to avoid multicollinearity, Pharmacist and Dietician or cook were included in Others because they are correlated to the Pharmaceutical department and the Dietary department, respectively.

No. of beds in their hospital<200 beds 1.00  1.00  1.00  1.00 
200‐500 beds0.510.90(0.67‐1.22)<0.01*1.64(1.30‐2.07)0.191.27(0.89‐1.80)<0.01*1.45(1.16‐1.81)
500 beds or more0.02*0.69(0.51‐0.94)<0.01*1.57(1.24‐1.98)0.490.88(0.62‐1.26)0.01*1.32(1.06‐1.65)
SectionPhysicians' department 1.00  1.00  1.00  1.00 
Psychiatric ward<0.01*9.28(4.39‐19.62)<0.01*3.33(1.65‐6.70)0.690.80(0.27‐2.40)<0.01*4.55(2.07‐1.02)
Long‐term care ward<0.01*2.48(1.55‐3.96)<0.01*1.90(1.27‐2.86)0.651.15(0.63‐2.09)<0.01*2.20(1.50‐3.24)
General ward<0.01*3.00(2.18‐4.13)<0.01*1.73(1.36‐2.21)<0.01*1.89(1.32‐2.69)<0.01*1.98(1.57‐2.51)
Dialysis department0.02*0.32(0.12‐0.83)0.04*1.65(1.02‐2.66)0.01*2.21(1.23‐3.97)0.02*1.81(1.12‐2.92)
Critical care center, ICU, or CCU<0.01*2.44(1.60‐3.74)0.491.13(0.79‐1.61)0.561.17(0.70‐1.94)0.04*1.43(1.01‐2.01)
Administration department0.220.55(0.21‐1.44)0.071.38(0.98‐1.93)0.290.64(0.27‐1.48)0.071.37(0.98‐1.91)
Clinical radiology department0.531.42(0.48‐4.21)0.511.21(0.69‐2.12)0.02*0.17(0.04‐0.78)0.571.17(0.69‐1.98)
Rehabilitation department0.930.93(0.18‐4.77)0.881.08(0.42‐2.80)0.821.22(0.22‐6.79)0.771.14(0.46‐2.85)
Outpatient department<0.01*0.41(0.26‐0.65)0.03*1.35(1.02‐1.78)0.02*0.56(0.35‐0.90)0.401.12(0.86‐1.47)
Dietary department0.331.94(0.51‐7.35)0.661.13(0.65‐1.99)0.851.13(0.30‐4.26)0.841.06(0.61‐1.82)
Clinical laboratory or physiology department0.400.53(0.12‐2.34)0.851.06(0.59‐1.89)0.210.52(0.18‐1.45)0.870.96(0.55‐1.65)
Pediatric ward0.270.72(0.41‐1.29)0.080.69(0.45‐1.05)0.02*0.43(0.21‐0.90)0.03*0.65(0.43‐0.97)
Pharmaceutical department   0.050.52(0.26‐1.01)0.711.26(0.36‐4.38)0.140.63(0.34‐1.17)
Operation department<0.01*0.24(0.12‐0.48)<0.01*0.36(0.23‐0.55)<0.01*0.21(0.09‐0.48)<0.01*0.27(0.18‐0.41)
Obstetrics and gynecology ward, perinatal ward, or NICU<0.01*0.04(0.01‐0.18)<0.01*0.19(0.12‐0.32)<0.01*0.02(0.00‐0.18)<0.01*0.14(0.08‐0.22)
ProfessionDoctor 1.00  1.00  1.00 <0.01*1.00 
Nurse<0.01*4.09(2.41‐6.95)0.161.27(0.91‐1.76)<0.01*11.64(4.38‐30.90) 1.64(1.19‐2.26)
Therapist0.104.03(0.76‐21.28)0.830.90(0.34‐2.39)0.05*7.11(1.02‐49.3)0.831.11(0.43‐2.83)
Nursing aide or care worker0.03*1.95(1.07‐3.55)0.090.71(0.47‐1.05)<0.01*4.66(1.63‐13.31)0.190.77(0.53‐1.14)
Clerk0.03*0.36(0.14‐0.90)0.270.80(0.54‐1.19)0.172.26(0.70‐7.27)0.090.72(0.49‐1.06)
Technician0.270.55(0.19‐1.60)<0.01*0.37(0.22‐0.61)<0.01*6.92(2.20‐21.76)<0.01*0.46(0.28‐0.74)
Others<0.01*0.21(0.08‐0.57)<0.01*0.39(0.25‐0.60)0.242.14(0.60‐7.63)<0.01*0.39(0.25‐0.59)
Years of experience in their own specialty or profession<5 yr 1.00  1.00  1.00  1.00 
6‐10 yr<0.01*1.42(1.17‐1.72)0.01*1.22(1.05‐1.42)0.840.98(0.78‐1.22)0.01*1.22(1.05‐1.42)
11‐15 yr<0.01*1.64(1.31‐2.05)<0.01*1.45(1.22‐1.73)0.301.14(0.89‐1.47)<0.01*1.35(1.13‐1.60)
16‐20 yr0.301.16(0.88‐1.52)<0.01*1.47(1.21‐1.79)0.090.75(0.54‐1.04)<0.01*1.34(1.10‐1.63)
21 yr or more0.581.07(0.84‐1.37)<0.01*1.65(1.39‐1.96)<0.01*0.63(0.47‐0.85)<0.01*1.38(1.16‐1.64)
Working hours per week<20 hr 1.00  1.00  1.00  1.00 
20‐40 hr0.04*1.49(1.01‐2.19)0.521.08(0.85‐1.39)0.121.40(0.91‐2.15)0.101.23(0.96‐1.56)
40‐60 hr<0.01*1.80(1.25‐2.58)0.03*1.28(1.02‐1.60)0.05*1.50(1.00‐2.24)<0.01*1.39(1.11‐1.74)
60 hr or more<0.01*2.14(1.37‐3.34)<0.01*1.62(1.21‐2.17)0.141.49(0.88‐2.50)<0.01*1.90(1.43‐2.54)
Gender(Female vs male)0.690.95(0.76‐1.20)0.161.12(0.95‐1.32)<0.01*1.59(1.18‐2.12)0.01*1.22(1.05‐1.43)
Direct interaction or contact with patients(Constant and direct interaction with patients vs no interaction)0.02*2.17(1.11‐4.22)<0.01*2.46(1.87‐3.24)<0.01*6.80(2.43‐19.03)<0.01*2.58(1.97‐3.37)

Adjusted odds ratios of verbal abuse were significantly high in hospital with 200 beds or more, in general wards, psychiatric wards, long‐term care wards, outpatient departments, and dialysis departments; and for longer years of experience in their own specialty; for longer working hours; and for direct interaction with patients.

Adjusted odds ratios of sexual harassment were significantly high in general wards, and dialysis departments; for nurses, nursing aides/care workers, technicians, therapists; for females; and for direct interaction with patients.

Adjusted odds ratios for at least 1 of the 3 kinds of workplace violence were significantly high in hospitals with 200 beds or more, in general wards, psychiatric wards, critical care centers/ICU/CCU, long‐term care wards, and dialysis departments; for nurses; for longer years of experience in their own specialty; for longer working hours; for females; and for direct interaction with patients.

Factors Associated With Lower Risk of Violence

Adjusted odds ratios of physical aggression were significantly low in dialysis departments; outpatient departments; operation departments; obstetrics and gynecology wards, perinatal wards, or neonatal intensive care units (NICU); and for clerks.

Adjusted odds ratios of verbal abuse were significantly low in operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for technicians.

Adjusted odds ratios of sexual harassment were significantly low in clinical radiology departments; outpatient departments; pediatric wards; operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for longer years of experience in their own specialty.

Adjusted odds ratios for at least 1 of the 3 kinds of workplace violence were significantly low in pediatric wards; operation departments; obstetrics and gynecology wards, perinatal wards, or NICU; and for technicians.

DISCUSSION

Among the healthcare staff, 36.4% experienced workplace violence by patients or their relatives over the past year; 15.9% experienced physical aggressions, 29.8% verbal abuse, and 9.9% sexual harassment. The risk factors of workplace violence identified in the present study were similar to those studies conducted not only in Japan, but also in Western countries. Though the target population was limited to Asians, our results can be applicable to other races, countries, and cultures.

Incidence of Workplace Violence

Most previous studies covered only specific professions at hospitals, such as nurses or critical care center staff, and there are only few multicenter studies covering entire sections and professions like this study.510, 1214 A Spanish study including about 8000 healthcare workers reported that 11% had experienced physical aggression, 64% had experienced threatening behavior, intimidation, or insults in the past year.11 The incidence of physical aggression was similar in both studies, but the incidence of verbal abuse was about twice as high as that of this study. The low response rate in the Spanish study (24%) might have contributed to a higher number of verbal abuse incidents, because those with experience of workplace violence would likely have answered the questionnaire. It is difficult to compare the incidence of workplace violence among different studies because the definitions of workplace violence differ widely. Ethnic culture might also affect the acknowledgement of workplace violence. The European NEXT study including about 30,000 nurses in 8 European countries reported a range of 10.4% incidence of workplace violence in the Netherlands, and 39.1% in France.10

Risk Factors of Physical Aggression

Previous studies reported that the prevalence of physical aggression is high in psychiatric wards, critical care centers, or long‐term care wards.1015 In these departments, patients with mental illness, postoperative delirium, or dementia are likely to be admitted.

Nurses and nursing aides are reported to be likely to experience physical aggression.3, 11, 15 Nurses and nursing aides have longer work hours with direct interaction with patients than other professions, and are considered to be at high risk of physical aggression.

Some studies, which did not examine influences by profession or department, reported that male was a risk factor for physical aggression and verbal abuse.6, 10, 11, 13 In this study though, the male gender was not associated with physical aggression or verbal abuse. Male nurses and nursing aides are likely to be assigned to high‐risk departments or to care for high‐risk patients. Gender may be confounded with variables such as profession or department.15

Longer work hours mean more frequent interaction with patients, and the risk for physical aggression might increase. Constant and direct interaction with patients is a risk factor, not only for physical aggression, but also for verbal abuse and sexual harassment.10

Risk Factors of Verbal Abuse

Previous studies reported that incidents of verbal abuse are high for nurses and nursing aides.15 Although in this study the proportion of verbal abuse was the highest in nurses (39.4%), adjusted odds ratio was not significant. Factors other than nurse profession, such as department and direct interaction with patients relating to the nurse profession, might be the higher risk factors for verbal abuse.

As reported in previous studies, psychiatric wards and long‐term care wards are risk factors of verbal abuse also in this study.10, 13, 15 Long waiting time at outpatient departments might increase the risk of verbal abuse.

Dialysis departments are at high risk of verbal abuse and sexual harassment. Compared to other outpatients, dialysis patients are forced to stay a long time in hospitals and there is, therefore, more interaction with nurses and technicians. The characteristic personality of dialysis patients, such as neuroticism or psychoticism, might also affect verbal abuse or sexual harassment.16

Because longer working hours mean more frequent interaction with patients, the risk of verbal abuse might increase.17 Managers with longer work experience might be at high risk for verbal abuse, because they often assume responsibility and take on the task of dealing with patients and their relevant complaints.11

Risk Factors of Sexual Harassment

Nurses are likely to experience sexual harassment because their public image seems to combine sexuality and maternalism.18 Nursing aides, technicians, and therapists also experience sexual harassment. The common risk factor among those professions is the direct contact with the patient's body during the patient's transfer. A lot of studies reported that female gender is a risk factor of sexual harassment.17, 19

Safety Factors of Workplace Violence

Adjusted odds ratios of operation departments, and obstetrics and gynecology wards, perinatal wards, or NICU were common safety factors for each type of workplace violence. Usually, the patients in operation rooms cannot talk or move a finger carelessly during the surgery. The fact that there are no adult male patients in obstetrics and gynecology wards, perinatal wards, or NICU, might have an influence on lower occurrence of workplace violence in these areas.

Limitations

This study used a questionnaire survey asking about subjective experiences of workplace violence over the 1 year before the study. There is the possibility of recall bias, and the same incident recognized as workplace violence by one person might not have been recognized as such by another person, because sensitivity differs among respondents.

In some categories with fewer respondents, such as the pharmaceutical department, it might be difficult to examine the exact confidence intervals of odds ratio. Further study with increased respondents of those categories is needed to confirm the odds ratios and the confidence intervals.

The rates of victims or risk for workplace violence were considered to vary with the character of the residents of each area or policy of each hospital. Therefore, a further analysis with adjustment for those factors is needed.

CONCLUSIONS

This study reveals that a significant proportion of healthcare staff (36.4%) has experienced workplace violence over the 1 year before the study was conducted and suggests that workplace violence is a serious problem. The attributes of healthcare staff who are at risk of workplace violence could be identified for each type of workplace violence. The mechanisms and the countermeasures for each type of workplace violence at those high‐risk areas should be further investigated. Further studies are necessary to confirm whether these findings are applicable to different races and different countries with different cultures.

References
  1. Home Office. Violence at Work: Findings From the 2002/2003 British Crime Survey. Available at: http://www.homeoffice.gov.uk/rds/pdfs2/rdsolr0404.pdf. Accessed November 10,2010.
  2. Saarela KL,Isotalus N.Workplace violence in Finland: high‐risk groups and preventive strategies.Am J Ind Med Suppl.1999;1:8081.
  3. Duhart DT.Violence in the Workplace 1993–99, National Crime Victimization Survey,Washington, DC:Bureau of Justice Statistics;2001:112.
  4. Johnson SL.International perspectives on workplace bullying among nurses: a review.Int Nurs Rev.2009;56(1):3440.
  5. Farrell GA,Bobrowski C,Bobrowski P.Scoping workplace aggression in nursing: findings from an Australian study.J Adv Nurs.2006;55(6):778787.
  6. Gacki‐Smith J,Juarez AM,Boyett L, et al.Violence against nurses working in US emergency departments.J Nurs Adm.2009;39(7–8):340349.
  7. Chen WC,Hwu HG,Wang JD.Hospital staff responses to workplace violence in a psychiatric hospital in Taiwan.Int J Occup Environ Health.2009;15(2):173179.
  8. All Japan Hospital Association. Research on actual conditions of risk management system and workplace violence at hospitals (Japanese). Available at: http://www.ajha.or.jp/voice/pdf/other/080422.pdf. Accessed November 10, 2010.
  9. Wada K,Yoshida K,Sato E, et al.The present situation and the countermeasure for verbal abuse and physical aggression of patients (Japanese).Japan Medical Journal.2007;4354:8184.
  10. Camerino D,Estryn‐Behar M,Conway PM, et al.Work‐related factors and violence among nursing staff in the European NEXT study: a longitudinal cohort study.Int J Nurs Stud.2008;45(1):3550.
  11. Gascón S,Martínez‐Jarreta B,González‐Andrade JF, et al.Aggression towards health care workers in Spain: a multi‐facility study to evaluate the distribution of growing violence among professionals, health facilities and departments.Int J Occup Environ Health.2009;15(1):2935.
  12. Office of Policy Planning, Japanese Nursing Association.Research on actual conditions of workplace violence at healthcare sector 2003 (Japanese).Survey Report of Japanese Nursing Association.2004;71:716.
  13. Shields M,Wilkins K.Factors related to on‐the‐job abuse of nurses by patients.Health Rep.2009;20(2):719.
  14. Gerberich SG,Church TR,McGovern PM, et al.Risk factors for work‐related assaults on nurses.Epidemiology.2005;16(5):704709.
  15. Kling RN,Yassi A,Smailes E, et al.Characterizing violence in health care in British Columbia.J Adv Nurs.2009;65(8):16551663.
  16. Koutsopoulou V,Theodosopoulou E,Vantsi E, et al.Personality dimensions of haemodialysis patients related to initial renal disease.EDTNA ERCA J.2002;28(1):2124.
  17. Koritsas S,Boyle M,Coles J.Factors associated with workplace violence in paramedics.Prehosp Disaster Med.2009;24(5):417421.
  18. Savage J.Sexuality. An uninvited guest.Nurs Times.1989;85(5):2528.
  19. Nagata‐Kobayashi S,Maeno T,Yoshizu M, et al.Universal problems during residency: abuse and harassment.Med Educ.2009;43(7):628636.
References
  1. Home Office. Violence at Work: Findings From the 2002/2003 British Crime Survey. Available at: http://www.homeoffice.gov.uk/rds/pdfs2/rdsolr0404.pdf. Accessed November 10,2010.
  2. Saarela KL,Isotalus N.Workplace violence in Finland: high‐risk groups and preventive strategies.Am J Ind Med Suppl.1999;1:8081.
  3. Duhart DT.Violence in the Workplace 1993–99, National Crime Victimization Survey,Washington, DC:Bureau of Justice Statistics;2001:112.
  4. Johnson SL.International perspectives on workplace bullying among nurses: a review.Int Nurs Rev.2009;56(1):3440.
  5. Farrell GA,Bobrowski C,Bobrowski P.Scoping workplace aggression in nursing: findings from an Australian study.J Adv Nurs.2006;55(6):778787.
  6. Gacki‐Smith J,Juarez AM,Boyett L, et al.Violence against nurses working in US emergency departments.J Nurs Adm.2009;39(7–8):340349.
  7. Chen WC,Hwu HG,Wang JD.Hospital staff responses to workplace violence in a psychiatric hospital in Taiwan.Int J Occup Environ Health.2009;15(2):173179.
  8. All Japan Hospital Association. Research on actual conditions of risk management system and workplace violence at hospitals (Japanese). Available at: http://www.ajha.or.jp/voice/pdf/other/080422.pdf. Accessed November 10, 2010.
  9. Wada K,Yoshida K,Sato E, et al.The present situation and the countermeasure for verbal abuse and physical aggression of patients (Japanese).Japan Medical Journal.2007;4354:8184.
  10. Camerino D,Estryn‐Behar M,Conway PM, et al.Work‐related factors and violence among nursing staff in the European NEXT study: a longitudinal cohort study.Int J Nurs Stud.2008;45(1):3550.
  11. Gascón S,Martínez‐Jarreta B,González‐Andrade JF, et al.Aggression towards health care workers in Spain: a multi‐facility study to evaluate the distribution of growing violence among professionals, health facilities and departments.Int J Occup Environ Health.2009;15(1):2935.
  12. Office of Policy Planning, Japanese Nursing Association.Research on actual conditions of workplace violence at healthcare sector 2003 (Japanese).Survey Report of Japanese Nursing Association.2004;71:716.
  13. Shields M,Wilkins K.Factors related to on‐the‐job abuse of nurses by patients.Health Rep.2009;20(2):719.
  14. Gerberich SG,Church TR,McGovern PM, et al.Risk factors for work‐related assaults on nurses.Epidemiology.2005;16(5):704709.
  15. Kling RN,Yassi A,Smailes E, et al.Characterizing violence in health care in British Columbia.J Adv Nurs.2009;65(8):16551663.
  16. Koutsopoulou V,Theodosopoulou E,Vantsi E, et al.Personality dimensions of haemodialysis patients related to initial renal disease.EDTNA ERCA J.2002;28(1):2124.
  17. Koritsas S,Boyle M,Coles J.Factors associated with workplace violence in paramedics.Prehosp Disaster Med.2009;24(5):417421.
  18. Savage J.Sexuality. An uninvited guest.Nurs Times.1989;85(5):2528.
  19. Nagata‐Kobayashi S,Maeno T,Yoshizu M, et al.Universal problems during residency: abuse and harassment.Med Educ.2009;43(7):628636.
Issue
Journal of Hospital Medicine - 7(2)
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Journal of Hospital Medicine - 7(2)
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Risk factors of workplace violence at hospitals in Japan
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Risk factors of workplace violence at hospitals in Japan
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Department of Social Medicine, Toho University School of Medicine, 5‐21‐16, Omori‐Nishi, Ota‐ku, Tokyo 143‐8540, Japan
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Economic Impact of Enoxaparin in Stroke

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Economic impact of enoxaparin versus unfractionated heparin for venous thromboembolism prophylaxis in patients with acute ischemic stroke: A hospital perspective of the PREVAIL trial

Venous thromboembolism (VTE), which encompasses both deep‐vein thrombosis (DVT) and pulmonary embolism (PE), is a major health problem in the United States and worldwide. It represents one of the most significant causes of morbidity and mortality with an estimated 300,000 VTE‐related deaths,1 and 300,000‐600,000 hospitalizations in the United States annually.2 Hospitalization for medical illness is associated with a similar proportion of VTE cases as hospitalization for surgery.3 Several groups of medical patients have been shown to be at an increased risk of VTE, including those with cancer, severe respiratory disease, acute infectious illness, heart failure, myocardial infarction, and acute ischemic stroke.47 Ischemic stroke patients represent approximately 4.6% of medical patients at high risk of VTE in US hospitals.8 The incidence of DVT in such patients has been reported to be as high as 75%9 and PE has been reported to be responsible for up to 25% of early deaths after stroke.10

Several studies have demonstrated the efficacy of unfractionated heparin (UFH) or a low‐molecular‐weight heparin (LMWH) in the prevention of VTE in stroke patients, and have demonstrated that LMWHs are at least as effective as UFH.1114 The open‐label, randomized Prevention of VTE after acute ischemic stroke with LMWH and UFH (PREVAIL) trial demonstrated that in patients with acute ischemic stroke, prophylaxis for 10 days with the LMWH enoxaparin reduces the risk of VTE by 43% compared with UFH (10.2% vs 18.1%, respectively; relative risk = 0.57; 95% confidence interval [CI] = 0.44‐0.76; P = 0.0001) without increasing the incidence of overall bleeding events (7.9% vs 8.1%, respectively; P = 0.83), or the composite of symptomatic intracranial and major extracranial hemorrhage (1% in each group; P = 0.23). There was, however, a slight but significant increase in major extracranial hemorrhage alone with enoxaparin (1% vs 0%; P = 0.015).14 Evidence‐based guidelines from the American College of Chest Physicians (ACCP) provide recommendations for appropriate thromboprophylaxis regimens for patients at risk of VTE.15 Thromboprophylaxis with UFH, LMWH, and, more recently, fondaparinux is recommended for medical patients admitted to hospital with congestive heart failure or severe respiratory disease, or those who are confined to bed and have one or more additional risk factors, including active cancer, previous VTE, or acute neurologic disease.15 Similarly, in the Eighth ACCP Clinical Practice Guidelines, low‐dose UFH or LMWH are recommended for VTE prevention in patients with ischemic stroke who have restricted mobility.16

VTE is also associated with a substantial economic burden on the healthcare system, costing an estimated $1.5 billion annually in the United States.17 Thromboprophylaxis has been shown to be a cost‐effective strategy in hospitalized medical patients. Prophylaxis with a LMWH has been shown to be more cost‐effective than UFH in these patients.1821

However, despite the clinical and economic benefits, prophylaxis is still commonly underused in medical patients.22, 23 In surgical patients, the Surgical Care Improvement Project (SCIP) focuses on reducing surgical complications, and has endorsed 2 measures: VTE‐1, relating to the proportion of patients for whom VTE prophylaxis is ordered; and VTE‐2, relating to those who receive the recommended regimen (www.MedQIC.org/SCIP). The call‐to‐action by the Office of the Surgeon General also urges a coordinated, multifaceted plan to reduce the disease burden of VTE in the United States.24 The Joint Commission and the National Quality Forum (NQF) have recently introduced a set of quality assurance measures within the National Consensus Standards for the Prevention and Care of Venous Thromboembolism project,25 with the specific goal of improving in‐hospital VTE assessment, diagnosis, prophylaxis, and treatment. The Agency for Healthcare Research and Quality has also published guidelines to help prevent hospital‐acquired VTE.26 Within each of these performance measures, the costs of thromboprophylaxis in different subtypes of patients may be of particular interest to healthcare decision‐makers.

The objective of the current study was to determine the economic impact, in terms of hospital costs, of enoxaparin compared with UFH for VTE prophylaxis after acute ischemic stroke. A decision‐analytic model was constructed using data from the PREVAIL study and historical inpatient data from a multi‐hospital database.

METHODS

In this study, the cost implications, from the hospital perspective, of VTE prophylaxis with enoxaparin or UFH in patients with acute ischemic stroke, were determined using a decision‐analytic model in TreeAge Pro Suite (TreeAge Software, Inc., Williamstown, MA, USA). The decision‐tree was based on 3 stages: (a) whether patients received enoxaparin or UFH; (b) how patients were classified according to their National Institutes of Health Stroke Scale (NIHSS) classification scores (<14 or 14); and (c) which clinical event each patient experienced, as defined per the PREVAIL trial (DVT, PE, intracranial hemorrhage, major extracranial hemorrhage, and minor extracranial hemorrhage) (Figure 1). The time horizon for the model was established at 90 days to mirror the length of follow‐up in the PREVAIL trial.

Figure 1
Decision‐analytic model. Abbreviations: NIHSS, National Institute of Health Stroke Scale.

Total hospital costs were calculated based on clinical event rates (from the PREVAIL trial) and the costs of each clinical event, which were calculated separately according to the descriptions below, and then inserted into the decision‐analytic model. The clinical event rates were calculated from the efficacy and safety endpoints collected in the PREVAIL trial, and included VTE events (DVT and PE) and bleeding events (intracranial hemorrhage, major extracranial hemorrhage, and minor extracranial hemorrhage). Details of the patient population, eligibility criteria, and treatment regimen have previously been published in full elsewhere.14, 27

The costs of clinical events during hospitalization were estimated using a multivariate cost‐evaluation model, based on mean hospital costs for the events in the (Premier Inc., Charlotte, NC, USA) multi‐hospital database, one of the largest US hospital clinical and economic databases. The data are received from over 600 hospitals, representing all geographical areas of the United States, a broad range of bed sizes, teaching and non‐teaching, and urban and rural facilities. This database contains detailed US inpatient care records of principal and secondary diagnoses, inpatient procedures, administered laboratory tests, dispensed drugs, and demographic information. The evaluation of hospital cost for each type of clinical event was conducted by i3 Innovus (Ingenix, Inc., Eden Prairie, MN, USA). Total hospital costs were cumulative from all events, so if patients experienced multiple clinical events, the costs of the events were additive. The cost for stroke treatment and management was not included because it is an inclusion criterion of the PREVAIL trial and, thus, all patients in the trial have such costs.

Default drug costs were taken from the 2008 US wholesalers' acquisition cost data. The default dosing schedule is based on information extracted from the PREVAIL trial: enoxaparin 40 mg (once‐daily) and UFH 5000 U (twice‐daily) for 10 days each ($25.97 and $2.97, respectively). A drug‐administration fee was added for each dose of either enoxaparin or UFH ($10 for each).19

The estimated hospital cost of clinical events, along with drug costs, were inserted into the decision‐analytic model in TreeAge Pro Suite to estimate the cost per discharge from the hospital perspective in patients with ischemic stroke receiving VTE prophylaxis with enoxaparin or UFH. An additional analysis was performed to investigate the costs and cost differences in patients with less severe stroke (NIHSS scores <14) and more severe stroke (NIHSS scores 14).

Sensitivity analyses were performed to examine the impact of varying the cost inputs on the total hospital cost of each treatment arm by 5%, 10%, 15%, 20%, 30%, and 40%, and the robustness in the difference in costs between the enoxaparin and UFH groups. Univariate (via tornado diagram in TreeAge Pro Suite) and multivariate (via Monte Carlo simulation in TreeAge Pro Suite) analyses were performed. For the univariate analysis, each clinical event cost was adjusted individually, increasing or decreasing by 5%, 10%, 15%, 20%, 30% and 40% while other parameters remained unchanged. For the Monte Carlo simulation (TreeAge Pro Suite), all the parameters were simultaneously varied in a random fashion, within a range of 5%, 10%, 15%, 20%, 30%, and 40% over 10,000 trials. The simulation adopted a gamma distribution assumption for input sampling for cost parameters and a beta distribution for the event probability parameters. The confidence intervals for the probability parameters were obtained from the PREVAIL trial. The differences between the enoxaparin and UFH treatment groups were plotted in a graph against the variation in costs of each clinical event.

RESULTS

The clinical VTE and bleeding event rates as collected from the PREVAIL trial are shown in Table 1. The hospital costs per clinical event are shown in Table 2. The most costly clinical event from the hospital perspective was intracranial hemorrhage at $4001, followed by major extracranial hemorrhage at $3534. The costs of DVT and PE were $3003 and $2143, respectively.

Clinical Event Rates and 95% CI From the PREVAIL Study
 Event Rate95% CI
  • Abbreviations: CI, confidence interval; NIHSS, National Institute of Health Stroke Scale; PREVAIL, prevention of VTE (venous thromboembolism) after acute ischemic stroke with LMWH (low‐molecular‐weight heparin) and UFH study; UFH, unfractionated heparin.

Enoxaparin (NIHSS <14)  
Deep‐vein thrombosis0.0810.05730.1048
Pulmonary embolism0.0020.000050.011
Intracranial hemorrhage0.003100.0074
Major extracranial hemorrhage0.004700.0099
Minor hemorrhage0.03720.0240.0549
Enoxaparin (NIHSS 14)  
Deep‐vein thrombosis0.16250.10530.2197
Pulmonary embolism000
Intracranial hemorrhage0.008600.0205
Major extracranial hemorrhage0.01720.04660.1198
Minor hemorrhage0.07760.04660.1198
UFH (NIHSS <14)  
Deep‐vein thrombosis0.13560.10540.1658
Pulmonary embolism0.0040.00050.0145
Intracranial hemorrhage0.003200.0077
Major extracranial hemorrhage000
Minor hemorrhage0.05140.03550.0719
UFH (NIHSS 14)  
Deep‐vein thrombosis0.29140.22410.3588
Pulmonary embolism0.02290.00630.0575
Intracranial hemorrhage0.0160.00040.0316
Major extracranial hemorrhage000
Minor hemorrhage0.0640.0370.1019
Hospital Cost Assumptions per Event
EventCost per Event ($)*
LikeliestMinimumMaximum
  • Total costs are based on rates of each event. Patients who experience multiple events are considered to have experienced each event independent of another event.

  • Following a gamma distribution.

Deep‐vein thrombosis3,0032,4023,604
Pulmonary embolism2,1431,7142,572
Intracranial hemorrhage4,0013,2014,801
Major extracranial hemorrhage3,5342,8274,241
Minor hemorrhage1,3221,0581,586
Enoxaparin cost per dose262131
Unfractionated heparin cost per dose324

The average hospital cost with enoxaparin, when taking into account the costs of VTE and bleeding, was lower than with UFH ($422 vs $662, respectively), with a net savings of $240 per patient if enoxaparin was used. The average drug costs, including drug‐administration costs, were higher in the enoxaparin group ($360) compared with the UFH group ($259; difference $101). Nevertheless, the total hospital cost when clinical events and drug costs were considered together, was lower with enoxaparin than UFH. The total hospital costs per patient were $782 in patients receiving prophylaxis with enoxaparin and $922 in patients receiving UFH. Thus, enoxaparin was associated with a total cost‐savings of $140 per patient (Figure 2).

Figure 2
Anticoagulant‐related cost per patient.

The cost estimates according to the stroke severity score (NIHSS scores <14 vs 14) are described in Table 3. The drug costs were consistent, regardless of stroke severity, for enoxaparin ($360) and for UFH ($259). However, in both treatment groups, the event costs were higher in patients with more severe stroke, compared with less severe stroke. For example, in the enoxaparin group, the event costs were $686 in patients with NIHSS scores 14 and $326 in patients with NIHSS scores <14. Nevertheless, the overall costs (event costs plus drug costs) were lower with enoxaparin compared with UFH, both in patients with less severe and more severe stroke. In fact, the total hospital cost‐savings were greater when enoxaparin was used instead of UFH in patients with more severe stroke (cost‐saving $287 if NIHSS score 14 vs $71 if NIHSS score <14) (Table 3).

Hospital Cost Consequences for Patients With National Institute of Health Stroke Scale Scores of <14 vs 14
 Enoxaparin ($)UFH ($)Difference ($ [UFHEnoxaparin])
  • Abbreviations: NIHSS, National Institute of Health Stroke Scale; UFH, unfractionated heparin.

  • Includes drug administration costs.

NIHSS score <14   
Mean event costs per patient326497171
Mean drug costs per patient*360259101
Total costs68575671
NIHSS score 14   
Mean event costs per patient6861,073387
Mean drug costs per patient*360259101
Total costs1,0461,332287

Multiple sensitivity analyses were performed. In the base case univariate sensitivity analysis, individual costs were adjusted by 20% (Table 4). If the cost of DVT increased by 20% (from $3003 to $3604) the difference between the enoxaparin and UFH groups was $187. When the cost of DVT was decreased by 20% to $2402, enoxaparin was still cost‐saving, with a difference of $94. For each of the individual cost parameters that were varied (DVT, PE, intracranial hemorrhage, major extracranial hemorrhage, and minor hemorrhage), enoxaparin was always less costly than UFH. Subsequent sensitivity analyses were performed (not shown) where cost parameters were varied by 5%, 10%, 15%, 30%, and 40%. Enoxaparin remained less costly than UFH in all cases.

Univariate Analysis of Hospital Costs per Clinical Event
EventBaseline Cost Input ($)+20% Cost Input ($)+20% Difference ($ [UFH Enoxaparin]) (% Change)20% Cost Input ($)20% Difference ($ [UFH Enoxaparin]) (% Change)
  • Abbreviations: UFH, unfractionated heparin.

Deep‐vein thrombosis3,0033,604187 (33)2,40294 (33)
Pulmonary embolism2,1432,572144 (2.5)1,714137 (2.5)
Intracranial hemorrhage4,0014,801142 (1.3)3,201138 (1.3)
Major extracranial hemorrhage3,5344,241134 (4.0)2,827146 (4.0)
Minor hemorrhage1,3221,586142 (1.3)1,058138 (1.3)

A multivariate analysis was performed using a Monte Carlo simulation in TreeAge Pro (Figure 3). When all parameters were varied simultaneously (by 5%, 10%, 15%, 20%, 30%, and 40%) and the differences in costs between the enoxaparin and UFH groups were measured and plotted, the mean (standard deviation) difference between enoxaparin and UFH prophylaxis was $140 ($79) (Figure 3). Figure 4 shows a graphical presentation of the sensitivity analysis results for event probabilities and costs. Differences in enoxaparin drug costs, hospital costs for DVT, and probability of DVT for patients on enoxaparin are the factors that have the greatest effect on the overall cost.

Figure 3
Sensitivity analysis using Monte Carlo simulation to detect cost differences between unfractionated heparin and enoxaparin.
Figure 4
Sensitivity analysis results summarized in a tornado diagram for event probabilities and costs (the range over which they were varied is given in parentheses). Differences in enoxaparin drug costs, hospital costs for DVT, and probability of DVT for patients on enoxaparin are the factors which have the greatest effect on the expected value. The value was 0 for the probability of MEH for patients with NIHSS <14 or ≥14 on UFH. Abbreviations: DVT, deep vein thrombosis, ICH, intracranial hemorrhage, MEH, major extracranial hemorrhage, MH, minor extracranial hemorrhage, NIHSS, National Institute of Health Stroke Scale, PE, pulmonary embolism, UFH, unfractionated heparin.

Finally, an additional scenario was performed using a published ratio of asymptomatic DVT to symptomatic VTE, due to the fact that not all VTE events in the real‐world present with symptoms prompting treatment. Quinlan et al. determined a ratio of asymptomatic DVT to symptomatic VTE of 5 for total hip replacement patients and of 21 for total knee replacement patients.28 Although derived from different patient populations who received different anticoagulants, we utilized the symptomatic event rates from the pooled studies to recalculate cost differences between enoxaparin and UFH in acute ischemic stroke. Using only symptomatic event rates, based on the 21:1 ratio in patients undergoing total knee replacement, the total cost for enoxaparin was $485 compared to $386 for UFH. Similar results were found based on the 5:1 ratio in patients with total hip replacement (enoxaparin $532 vs $472 for UFH). This was the only scenario where the higher drug cost of prophylaxis with enoxaparin was not completely offset by the reduction in events compared to UFH, likely due to the smaller difference in event rates once examining only symptomatic VTE.

DISCUSSION

This analysis demonstrates that, from the hospital perspective, enoxaparin 40 mg subcutaneously once‐daily is associated with lower total hospital costs and is more cost‐effective than twice‐daily UFH 5000 U subcutaneously for the prevention of VTE in patients with acute ischemic stroke. Despite higher drug‐acquisition costs, enoxaparin was associated with total cost‐savings of $140 per patient. This is due to the lower event rates with enoxaparin compared with UFH.

Previous studies, using hospital or payer information, have shown that VTE prophylaxis is more cost‐effective compared with no prophylaxis. In terms of the different VTE prophylaxis regimens, enoxaparin represents a more cost‐effective option in comparison with UFH19, 21, 2932 and also when compared with fondaparinux.21, 33 When comparing the results between different trials, it should be noted that previous analyses were mainly modeled on the Prophylaxis in Medical Patients with Enoxaparin (MEDENOX) study, which was performed in general medical patients and reported a VTE rate of 5.5%.6 However, patients with acute ischemic stroke are at a higher risk of VTE, with a 10% incidence of VTE reported in the PREVAIL study.14 Furthermore, twice‐daily rather than three‐timesdaily administration of UFH was used in the PREVAIL study, based on the current practice patterns seen during the PREVAIL trial design.

A recent retrospective analysis of transactional billing records demonstrated that, despite higher mean costs of anticoagulation therapy, the mean, total, adjusted direct hospital costs were lower with LMWH thromboprophylaxis compared with UFH ($7358 vs $8680, respectively; difference $1322; P < 0.001).21 A previous study by Burleigh and colleagues based on hospital discharge information extracted from both medical and surgical patients, has a sub‐analysis in patients with stroke. In these patients also, the total costs were lower for enoxaparin compared with UFH ($8608 vs $8911, respectively; difference $303).29 In the Burleigh study, drug costs and total discharge costs (eg, room and board, laboratory, and diagnostic imaging) were derived from drug charges and total charges, and were converted to estimated costs using cost‐to‐charge methods, so the absolute figures are not directly comparable with the current analysis.

This study adds to current literature by using data from a prospective study to analyze the hospital costs of VTE prophylaxis in stroke patients. The current study also provides a valuable cost‐analysis regarding a specific subgroup of medical patients at particularly high risk of VTE, and provides an economic comparison among stroke patients with NIHSS scores of <14 versus 14. In the PREVAIL study, despite a 2‐fold higher incidence of VTE in patients with more severe stroke (16.3% vs 8.3%), a similar reduction in VTE risk was observed with enoxaparin versus UFH in patients with NIHSS scores of 14 (odds ratio = 0.56; 95% CI = 0.37‐0.84; P = 0.0036) and <14 (odds ratio = 0.46; 95% CI = 0.27‐0.78; P = 0.0043).14 Enoxaparin was shown to be cost‐saving relative to UFH in both patient groups and, in particular, in patients with more severe stroke.

Potential limitations of the current analysis include the applicability of the figures obtained from the highly selected clinical trial population to real‐world clinical practice, and the fact that it is difficult to match cost estimates to trial data definitions. For example, this analysis was conducted with a comparator of twice‐daily UFH (as opposed to three‐timesdaily) which may be used in the real‐world setting and may have resulted in the increased number of events in the UFH group seen in the PREVAIL study. Due to a variety of differences between real‐world practice patterns and the PREVAIL clinical trial, we can only speculate as to the true cost‐consequences of utilizing enoxaparin versus UFH.

Furthermore, the original model did not include a sub‐analysis regarding the rates and, therefore, costs of proximal/symptomatic VTE. In the primary study of PREVAIL, the rates of symptomatic DVT were 1 in 666 patients (<1%) for enoxaparin and 4 in 669 patients (1%) for UFH, whereas the rates of proximal DVT were 30 in 666 patients (5%) and 64 in 669 patients (10%), respectively. Sensitivity analyses were performed to investigate the impact of lower rates of both DVT and PE (up to 40%), and the differences between groups were found to be robust. However, it is important to note that overall costs for both groups may have been increased through the inclusion of asymptomatic costs, with a more distinct separation of these costs making for a good follow‐up study. In a similar cost‐analysis we performed based on the PREVAIL study, which assessed the cost to the payer, we included an analysis of costs according to 3 different VTE definitions: the PREVAIL VTE definition (as in the current study); a definition of major VTE (PE, symptomatic DVT, and asymptomatic proximal DVT); and primary endpoints recommended by the European Medicines Agency Committee for Medicinal Products for Human Use for studies on VTE (proximal DVT, nonfatal PE, and all‐cause mortality). We found similar results irrespective of clinical event definitions.34 In an additional model scenario using a published ratio of asymptomatic DVT to symptomatic VTE,28 the higher drug cost of prophylaxis with enoxaparin was not completely offset by the reduction in events compared to UFH. This was likely due to the smaller difference in event rates once examining only symptomatic VTE. This scenario was limited by the fact that the ratio was derived from different patient populations receiving different anticoagulants than stroke patients.

In conclusion, data from this analysis adds to the evidence that, from the hospital perspective, the higher drug cost of enoxaparin is offset by the economic consequences of the events avoided as compared with UFH for the prevention of VTE following acute ischemic stroke, particularly in patients with severe stroke.

Acknowledgements

The authors thank Aylin Lee from I3 Innovus for her contribution to this study. The authors also acknowledge Min Chen for her assistance in statistical analysis, and Essy Mozaffari for his contribution to this study.

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References
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Venous thromboembolism (VTE), which encompasses both deep‐vein thrombosis (DVT) and pulmonary embolism (PE), is a major health problem in the United States and worldwide. It represents one of the most significant causes of morbidity and mortality with an estimated 300,000 VTE‐related deaths,1 and 300,000‐600,000 hospitalizations in the United States annually.2 Hospitalization for medical illness is associated with a similar proportion of VTE cases as hospitalization for surgery.3 Several groups of medical patients have been shown to be at an increased risk of VTE, including those with cancer, severe respiratory disease, acute infectious illness, heart failure, myocardial infarction, and acute ischemic stroke.47 Ischemic stroke patients represent approximately 4.6% of medical patients at high risk of VTE in US hospitals.8 The incidence of DVT in such patients has been reported to be as high as 75%9 and PE has been reported to be responsible for up to 25% of early deaths after stroke.10

Several studies have demonstrated the efficacy of unfractionated heparin (UFH) or a low‐molecular‐weight heparin (LMWH) in the prevention of VTE in stroke patients, and have demonstrated that LMWHs are at least as effective as UFH.1114 The open‐label, randomized Prevention of VTE after acute ischemic stroke with LMWH and UFH (PREVAIL) trial demonstrated that in patients with acute ischemic stroke, prophylaxis for 10 days with the LMWH enoxaparin reduces the risk of VTE by 43% compared with UFH (10.2% vs 18.1%, respectively; relative risk = 0.57; 95% confidence interval [CI] = 0.44‐0.76; P = 0.0001) without increasing the incidence of overall bleeding events (7.9% vs 8.1%, respectively; P = 0.83), or the composite of symptomatic intracranial and major extracranial hemorrhage (1% in each group; P = 0.23). There was, however, a slight but significant increase in major extracranial hemorrhage alone with enoxaparin (1% vs 0%; P = 0.015).14 Evidence‐based guidelines from the American College of Chest Physicians (ACCP) provide recommendations for appropriate thromboprophylaxis regimens for patients at risk of VTE.15 Thromboprophylaxis with UFH, LMWH, and, more recently, fondaparinux is recommended for medical patients admitted to hospital with congestive heart failure or severe respiratory disease, or those who are confined to bed and have one or more additional risk factors, including active cancer, previous VTE, or acute neurologic disease.15 Similarly, in the Eighth ACCP Clinical Practice Guidelines, low‐dose UFH or LMWH are recommended for VTE prevention in patients with ischemic stroke who have restricted mobility.16

VTE is also associated with a substantial economic burden on the healthcare system, costing an estimated $1.5 billion annually in the United States.17 Thromboprophylaxis has been shown to be a cost‐effective strategy in hospitalized medical patients. Prophylaxis with a LMWH has been shown to be more cost‐effective than UFH in these patients.1821

However, despite the clinical and economic benefits, prophylaxis is still commonly underused in medical patients.22, 23 In surgical patients, the Surgical Care Improvement Project (SCIP) focuses on reducing surgical complications, and has endorsed 2 measures: VTE‐1, relating to the proportion of patients for whom VTE prophylaxis is ordered; and VTE‐2, relating to those who receive the recommended regimen (www.MedQIC.org/SCIP). The call‐to‐action by the Office of the Surgeon General also urges a coordinated, multifaceted plan to reduce the disease burden of VTE in the United States.24 The Joint Commission and the National Quality Forum (NQF) have recently introduced a set of quality assurance measures within the National Consensus Standards for the Prevention and Care of Venous Thromboembolism project,25 with the specific goal of improving in‐hospital VTE assessment, diagnosis, prophylaxis, and treatment. The Agency for Healthcare Research and Quality has also published guidelines to help prevent hospital‐acquired VTE.26 Within each of these performance measures, the costs of thromboprophylaxis in different subtypes of patients may be of particular interest to healthcare decision‐makers.

The objective of the current study was to determine the economic impact, in terms of hospital costs, of enoxaparin compared with UFH for VTE prophylaxis after acute ischemic stroke. A decision‐analytic model was constructed using data from the PREVAIL study and historical inpatient data from a multi‐hospital database.

METHODS

In this study, the cost implications, from the hospital perspective, of VTE prophylaxis with enoxaparin or UFH in patients with acute ischemic stroke, were determined using a decision‐analytic model in TreeAge Pro Suite (TreeAge Software, Inc., Williamstown, MA, USA). The decision‐tree was based on 3 stages: (a) whether patients received enoxaparin or UFH; (b) how patients were classified according to their National Institutes of Health Stroke Scale (NIHSS) classification scores (<14 or 14); and (c) which clinical event each patient experienced, as defined per the PREVAIL trial (DVT, PE, intracranial hemorrhage, major extracranial hemorrhage, and minor extracranial hemorrhage) (Figure 1). The time horizon for the model was established at 90 days to mirror the length of follow‐up in the PREVAIL trial.

Figure 1
Decision‐analytic model. Abbreviations: NIHSS, National Institute of Health Stroke Scale.

Total hospital costs were calculated based on clinical event rates (from the PREVAIL trial) and the costs of each clinical event, which were calculated separately according to the descriptions below, and then inserted into the decision‐analytic model. The clinical event rates were calculated from the efficacy and safety endpoints collected in the PREVAIL trial, and included VTE events (DVT and PE) and bleeding events (intracranial hemorrhage, major extracranial hemorrhage, and minor extracranial hemorrhage). Details of the patient population, eligibility criteria, and treatment regimen have previously been published in full elsewhere.14, 27

The costs of clinical events during hospitalization were estimated using a multivariate cost‐evaluation model, based on mean hospital costs for the events in the (Premier Inc., Charlotte, NC, USA) multi‐hospital database, one of the largest US hospital clinical and economic databases. The data are received from over 600 hospitals, representing all geographical areas of the United States, a broad range of bed sizes, teaching and non‐teaching, and urban and rural facilities. This database contains detailed US inpatient care records of principal and secondary diagnoses, inpatient procedures, administered laboratory tests, dispensed drugs, and demographic information. The evaluation of hospital cost for each type of clinical event was conducted by i3 Innovus (Ingenix, Inc., Eden Prairie, MN, USA). Total hospital costs were cumulative from all events, so if patients experienced multiple clinical events, the costs of the events were additive. The cost for stroke treatment and management was not included because it is an inclusion criterion of the PREVAIL trial and, thus, all patients in the trial have such costs.

Default drug costs were taken from the 2008 US wholesalers' acquisition cost data. The default dosing schedule is based on information extracted from the PREVAIL trial: enoxaparin 40 mg (once‐daily) and UFH 5000 U (twice‐daily) for 10 days each ($25.97 and $2.97, respectively). A drug‐administration fee was added for each dose of either enoxaparin or UFH ($10 for each).19

The estimated hospital cost of clinical events, along with drug costs, were inserted into the decision‐analytic model in TreeAge Pro Suite to estimate the cost per discharge from the hospital perspective in patients with ischemic stroke receiving VTE prophylaxis with enoxaparin or UFH. An additional analysis was performed to investigate the costs and cost differences in patients with less severe stroke (NIHSS scores <14) and more severe stroke (NIHSS scores 14).

Sensitivity analyses were performed to examine the impact of varying the cost inputs on the total hospital cost of each treatment arm by 5%, 10%, 15%, 20%, 30%, and 40%, and the robustness in the difference in costs between the enoxaparin and UFH groups. Univariate (via tornado diagram in TreeAge Pro Suite) and multivariate (via Monte Carlo simulation in TreeAge Pro Suite) analyses were performed. For the univariate analysis, each clinical event cost was adjusted individually, increasing or decreasing by 5%, 10%, 15%, 20%, 30% and 40% while other parameters remained unchanged. For the Monte Carlo simulation (TreeAge Pro Suite), all the parameters were simultaneously varied in a random fashion, within a range of 5%, 10%, 15%, 20%, 30%, and 40% over 10,000 trials. The simulation adopted a gamma distribution assumption for input sampling for cost parameters and a beta distribution for the event probability parameters. The confidence intervals for the probability parameters were obtained from the PREVAIL trial. The differences between the enoxaparin and UFH treatment groups were plotted in a graph against the variation in costs of each clinical event.

RESULTS

The clinical VTE and bleeding event rates as collected from the PREVAIL trial are shown in Table 1. The hospital costs per clinical event are shown in Table 2. The most costly clinical event from the hospital perspective was intracranial hemorrhage at $4001, followed by major extracranial hemorrhage at $3534. The costs of DVT and PE were $3003 and $2143, respectively.

Clinical Event Rates and 95% CI From the PREVAIL Study
 Event Rate95% CI
  • Abbreviations: CI, confidence interval; NIHSS, National Institute of Health Stroke Scale; PREVAIL, prevention of VTE (venous thromboembolism) after acute ischemic stroke with LMWH (low‐molecular‐weight heparin) and UFH study; UFH, unfractionated heparin.

Enoxaparin (NIHSS <14)  
Deep‐vein thrombosis0.0810.05730.1048
Pulmonary embolism0.0020.000050.011
Intracranial hemorrhage0.003100.0074
Major extracranial hemorrhage0.004700.0099
Minor hemorrhage0.03720.0240.0549
Enoxaparin (NIHSS 14)  
Deep‐vein thrombosis0.16250.10530.2197
Pulmonary embolism000
Intracranial hemorrhage0.008600.0205
Major extracranial hemorrhage0.01720.04660.1198
Minor hemorrhage0.07760.04660.1198
UFH (NIHSS <14)  
Deep‐vein thrombosis0.13560.10540.1658
Pulmonary embolism0.0040.00050.0145
Intracranial hemorrhage0.003200.0077
Major extracranial hemorrhage000
Minor hemorrhage0.05140.03550.0719
UFH (NIHSS 14)  
Deep‐vein thrombosis0.29140.22410.3588
Pulmonary embolism0.02290.00630.0575
Intracranial hemorrhage0.0160.00040.0316
Major extracranial hemorrhage000
Minor hemorrhage0.0640.0370.1019
Hospital Cost Assumptions per Event
EventCost per Event ($)*
LikeliestMinimumMaximum
  • Total costs are based on rates of each event. Patients who experience multiple events are considered to have experienced each event independent of another event.

  • Following a gamma distribution.

Deep‐vein thrombosis3,0032,4023,604
Pulmonary embolism2,1431,7142,572
Intracranial hemorrhage4,0013,2014,801
Major extracranial hemorrhage3,5342,8274,241
Minor hemorrhage1,3221,0581,586
Enoxaparin cost per dose262131
Unfractionated heparin cost per dose324

The average hospital cost with enoxaparin, when taking into account the costs of VTE and bleeding, was lower than with UFH ($422 vs $662, respectively), with a net savings of $240 per patient if enoxaparin was used. The average drug costs, including drug‐administration costs, were higher in the enoxaparin group ($360) compared with the UFH group ($259; difference $101). Nevertheless, the total hospital cost when clinical events and drug costs were considered together, was lower with enoxaparin than UFH. The total hospital costs per patient were $782 in patients receiving prophylaxis with enoxaparin and $922 in patients receiving UFH. Thus, enoxaparin was associated with a total cost‐savings of $140 per patient (Figure 2).

Figure 2
Anticoagulant‐related cost per patient.

The cost estimates according to the stroke severity score (NIHSS scores <14 vs 14) are described in Table 3. The drug costs were consistent, regardless of stroke severity, for enoxaparin ($360) and for UFH ($259). However, in both treatment groups, the event costs were higher in patients with more severe stroke, compared with less severe stroke. For example, in the enoxaparin group, the event costs were $686 in patients with NIHSS scores 14 and $326 in patients with NIHSS scores <14. Nevertheless, the overall costs (event costs plus drug costs) were lower with enoxaparin compared with UFH, both in patients with less severe and more severe stroke. In fact, the total hospital cost‐savings were greater when enoxaparin was used instead of UFH in patients with more severe stroke (cost‐saving $287 if NIHSS score 14 vs $71 if NIHSS score <14) (Table 3).

Hospital Cost Consequences for Patients With National Institute of Health Stroke Scale Scores of <14 vs 14
 Enoxaparin ($)UFH ($)Difference ($ [UFHEnoxaparin])
  • Abbreviations: NIHSS, National Institute of Health Stroke Scale; UFH, unfractionated heparin.

  • Includes drug administration costs.

NIHSS score <14   
Mean event costs per patient326497171
Mean drug costs per patient*360259101
Total costs68575671
NIHSS score 14   
Mean event costs per patient6861,073387
Mean drug costs per patient*360259101
Total costs1,0461,332287

Multiple sensitivity analyses were performed. In the base case univariate sensitivity analysis, individual costs were adjusted by 20% (Table 4). If the cost of DVT increased by 20% (from $3003 to $3604) the difference between the enoxaparin and UFH groups was $187. When the cost of DVT was decreased by 20% to $2402, enoxaparin was still cost‐saving, with a difference of $94. For each of the individual cost parameters that were varied (DVT, PE, intracranial hemorrhage, major extracranial hemorrhage, and minor hemorrhage), enoxaparin was always less costly than UFH. Subsequent sensitivity analyses were performed (not shown) where cost parameters were varied by 5%, 10%, 15%, 30%, and 40%. Enoxaparin remained less costly than UFH in all cases.

Univariate Analysis of Hospital Costs per Clinical Event
EventBaseline Cost Input ($)+20% Cost Input ($)+20% Difference ($ [UFH Enoxaparin]) (% Change)20% Cost Input ($)20% Difference ($ [UFH Enoxaparin]) (% Change)
  • Abbreviations: UFH, unfractionated heparin.

Deep‐vein thrombosis3,0033,604187 (33)2,40294 (33)
Pulmonary embolism2,1432,572144 (2.5)1,714137 (2.5)
Intracranial hemorrhage4,0014,801142 (1.3)3,201138 (1.3)
Major extracranial hemorrhage3,5344,241134 (4.0)2,827146 (4.0)
Minor hemorrhage1,3221,586142 (1.3)1,058138 (1.3)

A multivariate analysis was performed using a Monte Carlo simulation in TreeAge Pro (Figure 3). When all parameters were varied simultaneously (by 5%, 10%, 15%, 20%, 30%, and 40%) and the differences in costs between the enoxaparin and UFH groups were measured and plotted, the mean (standard deviation) difference between enoxaparin and UFH prophylaxis was $140 ($79) (Figure 3). Figure 4 shows a graphical presentation of the sensitivity analysis results for event probabilities and costs. Differences in enoxaparin drug costs, hospital costs for DVT, and probability of DVT for patients on enoxaparin are the factors that have the greatest effect on the overall cost.

Figure 3
Sensitivity analysis using Monte Carlo simulation to detect cost differences between unfractionated heparin and enoxaparin.
Figure 4
Sensitivity analysis results summarized in a tornado diagram for event probabilities and costs (the range over which they were varied is given in parentheses). Differences in enoxaparin drug costs, hospital costs for DVT, and probability of DVT for patients on enoxaparin are the factors which have the greatest effect on the expected value. The value was 0 for the probability of MEH for patients with NIHSS <14 or ≥14 on UFH. Abbreviations: DVT, deep vein thrombosis, ICH, intracranial hemorrhage, MEH, major extracranial hemorrhage, MH, minor extracranial hemorrhage, NIHSS, National Institute of Health Stroke Scale, PE, pulmonary embolism, UFH, unfractionated heparin.

Finally, an additional scenario was performed using a published ratio of asymptomatic DVT to symptomatic VTE, due to the fact that not all VTE events in the real‐world present with symptoms prompting treatment. Quinlan et al. determined a ratio of asymptomatic DVT to symptomatic VTE of 5 for total hip replacement patients and of 21 for total knee replacement patients.28 Although derived from different patient populations who received different anticoagulants, we utilized the symptomatic event rates from the pooled studies to recalculate cost differences between enoxaparin and UFH in acute ischemic stroke. Using only symptomatic event rates, based on the 21:1 ratio in patients undergoing total knee replacement, the total cost for enoxaparin was $485 compared to $386 for UFH. Similar results were found based on the 5:1 ratio in patients with total hip replacement (enoxaparin $532 vs $472 for UFH). This was the only scenario where the higher drug cost of prophylaxis with enoxaparin was not completely offset by the reduction in events compared to UFH, likely due to the smaller difference in event rates once examining only symptomatic VTE.

DISCUSSION

This analysis demonstrates that, from the hospital perspective, enoxaparin 40 mg subcutaneously once‐daily is associated with lower total hospital costs and is more cost‐effective than twice‐daily UFH 5000 U subcutaneously for the prevention of VTE in patients with acute ischemic stroke. Despite higher drug‐acquisition costs, enoxaparin was associated with total cost‐savings of $140 per patient. This is due to the lower event rates with enoxaparin compared with UFH.

Previous studies, using hospital or payer information, have shown that VTE prophylaxis is more cost‐effective compared with no prophylaxis. In terms of the different VTE prophylaxis regimens, enoxaparin represents a more cost‐effective option in comparison with UFH19, 21, 2932 and also when compared with fondaparinux.21, 33 When comparing the results between different trials, it should be noted that previous analyses were mainly modeled on the Prophylaxis in Medical Patients with Enoxaparin (MEDENOX) study, which was performed in general medical patients and reported a VTE rate of 5.5%.6 However, patients with acute ischemic stroke are at a higher risk of VTE, with a 10% incidence of VTE reported in the PREVAIL study.14 Furthermore, twice‐daily rather than three‐timesdaily administration of UFH was used in the PREVAIL study, based on the current practice patterns seen during the PREVAIL trial design.

A recent retrospective analysis of transactional billing records demonstrated that, despite higher mean costs of anticoagulation therapy, the mean, total, adjusted direct hospital costs were lower with LMWH thromboprophylaxis compared with UFH ($7358 vs $8680, respectively; difference $1322; P < 0.001).21 A previous study by Burleigh and colleagues based on hospital discharge information extracted from both medical and surgical patients, has a sub‐analysis in patients with stroke. In these patients also, the total costs were lower for enoxaparin compared with UFH ($8608 vs $8911, respectively; difference $303).29 In the Burleigh study, drug costs and total discharge costs (eg, room and board, laboratory, and diagnostic imaging) were derived from drug charges and total charges, and were converted to estimated costs using cost‐to‐charge methods, so the absolute figures are not directly comparable with the current analysis.

This study adds to current literature by using data from a prospective study to analyze the hospital costs of VTE prophylaxis in stroke patients. The current study also provides a valuable cost‐analysis regarding a specific subgroup of medical patients at particularly high risk of VTE, and provides an economic comparison among stroke patients with NIHSS scores of <14 versus 14. In the PREVAIL study, despite a 2‐fold higher incidence of VTE in patients with more severe stroke (16.3% vs 8.3%), a similar reduction in VTE risk was observed with enoxaparin versus UFH in patients with NIHSS scores of 14 (odds ratio = 0.56; 95% CI = 0.37‐0.84; P = 0.0036) and <14 (odds ratio = 0.46; 95% CI = 0.27‐0.78; P = 0.0043).14 Enoxaparin was shown to be cost‐saving relative to UFH in both patient groups and, in particular, in patients with more severe stroke.

Potential limitations of the current analysis include the applicability of the figures obtained from the highly selected clinical trial population to real‐world clinical practice, and the fact that it is difficult to match cost estimates to trial data definitions. For example, this analysis was conducted with a comparator of twice‐daily UFH (as opposed to three‐timesdaily) which may be used in the real‐world setting and may have resulted in the increased number of events in the UFH group seen in the PREVAIL study. Due to a variety of differences between real‐world practice patterns and the PREVAIL clinical trial, we can only speculate as to the true cost‐consequences of utilizing enoxaparin versus UFH.

Furthermore, the original model did not include a sub‐analysis regarding the rates and, therefore, costs of proximal/symptomatic VTE. In the primary study of PREVAIL, the rates of symptomatic DVT were 1 in 666 patients (<1%) for enoxaparin and 4 in 669 patients (1%) for UFH, whereas the rates of proximal DVT were 30 in 666 patients (5%) and 64 in 669 patients (10%), respectively. Sensitivity analyses were performed to investigate the impact of lower rates of both DVT and PE (up to 40%), and the differences between groups were found to be robust. However, it is important to note that overall costs for both groups may have been increased through the inclusion of asymptomatic costs, with a more distinct separation of these costs making for a good follow‐up study. In a similar cost‐analysis we performed based on the PREVAIL study, which assessed the cost to the payer, we included an analysis of costs according to 3 different VTE definitions: the PREVAIL VTE definition (as in the current study); a definition of major VTE (PE, symptomatic DVT, and asymptomatic proximal DVT); and primary endpoints recommended by the European Medicines Agency Committee for Medicinal Products for Human Use for studies on VTE (proximal DVT, nonfatal PE, and all‐cause mortality). We found similar results irrespective of clinical event definitions.34 In an additional model scenario using a published ratio of asymptomatic DVT to symptomatic VTE,28 the higher drug cost of prophylaxis with enoxaparin was not completely offset by the reduction in events compared to UFH. This was likely due to the smaller difference in event rates once examining only symptomatic VTE. This scenario was limited by the fact that the ratio was derived from different patient populations receiving different anticoagulants than stroke patients.

In conclusion, data from this analysis adds to the evidence that, from the hospital perspective, the higher drug cost of enoxaparin is offset by the economic consequences of the events avoided as compared with UFH for the prevention of VTE following acute ischemic stroke, particularly in patients with severe stroke.

Acknowledgements

The authors thank Aylin Lee from I3 Innovus for her contribution to this study. The authors also acknowledge Min Chen for her assistance in statistical analysis, and Essy Mozaffari for his contribution to this study.

Venous thromboembolism (VTE), which encompasses both deep‐vein thrombosis (DVT) and pulmonary embolism (PE), is a major health problem in the United States and worldwide. It represents one of the most significant causes of morbidity and mortality with an estimated 300,000 VTE‐related deaths,1 and 300,000‐600,000 hospitalizations in the United States annually.2 Hospitalization for medical illness is associated with a similar proportion of VTE cases as hospitalization for surgery.3 Several groups of medical patients have been shown to be at an increased risk of VTE, including those with cancer, severe respiratory disease, acute infectious illness, heart failure, myocardial infarction, and acute ischemic stroke.47 Ischemic stroke patients represent approximately 4.6% of medical patients at high risk of VTE in US hospitals.8 The incidence of DVT in such patients has been reported to be as high as 75%9 and PE has been reported to be responsible for up to 25% of early deaths after stroke.10

Several studies have demonstrated the efficacy of unfractionated heparin (UFH) or a low‐molecular‐weight heparin (LMWH) in the prevention of VTE in stroke patients, and have demonstrated that LMWHs are at least as effective as UFH.1114 The open‐label, randomized Prevention of VTE after acute ischemic stroke with LMWH and UFH (PREVAIL) trial demonstrated that in patients with acute ischemic stroke, prophylaxis for 10 days with the LMWH enoxaparin reduces the risk of VTE by 43% compared with UFH (10.2% vs 18.1%, respectively; relative risk = 0.57; 95% confidence interval [CI] = 0.44‐0.76; P = 0.0001) without increasing the incidence of overall bleeding events (7.9% vs 8.1%, respectively; P = 0.83), or the composite of symptomatic intracranial and major extracranial hemorrhage (1% in each group; P = 0.23). There was, however, a slight but significant increase in major extracranial hemorrhage alone with enoxaparin (1% vs 0%; P = 0.015).14 Evidence‐based guidelines from the American College of Chest Physicians (ACCP) provide recommendations for appropriate thromboprophylaxis regimens for patients at risk of VTE.15 Thromboprophylaxis with UFH, LMWH, and, more recently, fondaparinux is recommended for medical patients admitted to hospital with congestive heart failure or severe respiratory disease, or those who are confined to bed and have one or more additional risk factors, including active cancer, previous VTE, or acute neurologic disease.15 Similarly, in the Eighth ACCP Clinical Practice Guidelines, low‐dose UFH or LMWH are recommended for VTE prevention in patients with ischemic stroke who have restricted mobility.16

VTE is also associated with a substantial economic burden on the healthcare system, costing an estimated $1.5 billion annually in the United States.17 Thromboprophylaxis has been shown to be a cost‐effective strategy in hospitalized medical patients. Prophylaxis with a LMWH has been shown to be more cost‐effective than UFH in these patients.1821

However, despite the clinical and economic benefits, prophylaxis is still commonly underused in medical patients.22, 23 In surgical patients, the Surgical Care Improvement Project (SCIP) focuses on reducing surgical complications, and has endorsed 2 measures: VTE‐1, relating to the proportion of patients for whom VTE prophylaxis is ordered; and VTE‐2, relating to those who receive the recommended regimen (www.MedQIC.org/SCIP). The call‐to‐action by the Office of the Surgeon General also urges a coordinated, multifaceted plan to reduce the disease burden of VTE in the United States.24 The Joint Commission and the National Quality Forum (NQF) have recently introduced a set of quality assurance measures within the National Consensus Standards for the Prevention and Care of Venous Thromboembolism project,25 with the specific goal of improving in‐hospital VTE assessment, diagnosis, prophylaxis, and treatment. The Agency for Healthcare Research and Quality has also published guidelines to help prevent hospital‐acquired VTE.26 Within each of these performance measures, the costs of thromboprophylaxis in different subtypes of patients may be of particular interest to healthcare decision‐makers.

The objective of the current study was to determine the economic impact, in terms of hospital costs, of enoxaparin compared with UFH for VTE prophylaxis after acute ischemic stroke. A decision‐analytic model was constructed using data from the PREVAIL study and historical inpatient data from a multi‐hospital database.

METHODS

In this study, the cost implications, from the hospital perspective, of VTE prophylaxis with enoxaparin or UFH in patients with acute ischemic stroke, were determined using a decision‐analytic model in TreeAge Pro Suite (TreeAge Software, Inc., Williamstown, MA, USA). The decision‐tree was based on 3 stages: (a) whether patients received enoxaparin or UFH; (b) how patients were classified according to their National Institutes of Health Stroke Scale (NIHSS) classification scores (<14 or 14); and (c) which clinical event each patient experienced, as defined per the PREVAIL trial (DVT, PE, intracranial hemorrhage, major extracranial hemorrhage, and minor extracranial hemorrhage) (Figure 1). The time horizon for the model was established at 90 days to mirror the length of follow‐up in the PREVAIL trial.

Figure 1
Decision‐analytic model. Abbreviations: NIHSS, National Institute of Health Stroke Scale.

Total hospital costs were calculated based on clinical event rates (from the PREVAIL trial) and the costs of each clinical event, which were calculated separately according to the descriptions below, and then inserted into the decision‐analytic model. The clinical event rates were calculated from the efficacy and safety endpoints collected in the PREVAIL trial, and included VTE events (DVT and PE) and bleeding events (intracranial hemorrhage, major extracranial hemorrhage, and minor extracranial hemorrhage). Details of the patient population, eligibility criteria, and treatment regimen have previously been published in full elsewhere.14, 27

The costs of clinical events during hospitalization were estimated using a multivariate cost‐evaluation model, based on mean hospital costs for the events in the (Premier Inc., Charlotte, NC, USA) multi‐hospital database, one of the largest US hospital clinical and economic databases. The data are received from over 600 hospitals, representing all geographical areas of the United States, a broad range of bed sizes, teaching and non‐teaching, and urban and rural facilities. This database contains detailed US inpatient care records of principal and secondary diagnoses, inpatient procedures, administered laboratory tests, dispensed drugs, and demographic information. The evaluation of hospital cost for each type of clinical event was conducted by i3 Innovus (Ingenix, Inc., Eden Prairie, MN, USA). Total hospital costs were cumulative from all events, so if patients experienced multiple clinical events, the costs of the events were additive. The cost for stroke treatment and management was not included because it is an inclusion criterion of the PREVAIL trial and, thus, all patients in the trial have such costs.

Default drug costs were taken from the 2008 US wholesalers' acquisition cost data. The default dosing schedule is based on information extracted from the PREVAIL trial: enoxaparin 40 mg (once‐daily) and UFH 5000 U (twice‐daily) for 10 days each ($25.97 and $2.97, respectively). A drug‐administration fee was added for each dose of either enoxaparin or UFH ($10 for each).19

The estimated hospital cost of clinical events, along with drug costs, were inserted into the decision‐analytic model in TreeAge Pro Suite to estimate the cost per discharge from the hospital perspective in patients with ischemic stroke receiving VTE prophylaxis with enoxaparin or UFH. An additional analysis was performed to investigate the costs and cost differences in patients with less severe stroke (NIHSS scores <14) and more severe stroke (NIHSS scores 14).

Sensitivity analyses were performed to examine the impact of varying the cost inputs on the total hospital cost of each treatment arm by 5%, 10%, 15%, 20%, 30%, and 40%, and the robustness in the difference in costs between the enoxaparin and UFH groups. Univariate (via tornado diagram in TreeAge Pro Suite) and multivariate (via Monte Carlo simulation in TreeAge Pro Suite) analyses were performed. For the univariate analysis, each clinical event cost was adjusted individually, increasing or decreasing by 5%, 10%, 15%, 20%, 30% and 40% while other parameters remained unchanged. For the Monte Carlo simulation (TreeAge Pro Suite), all the parameters were simultaneously varied in a random fashion, within a range of 5%, 10%, 15%, 20%, 30%, and 40% over 10,000 trials. The simulation adopted a gamma distribution assumption for input sampling for cost parameters and a beta distribution for the event probability parameters. The confidence intervals for the probability parameters were obtained from the PREVAIL trial. The differences between the enoxaparin and UFH treatment groups were plotted in a graph against the variation in costs of each clinical event.

RESULTS

The clinical VTE and bleeding event rates as collected from the PREVAIL trial are shown in Table 1. The hospital costs per clinical event are shown in Table 2. The most costly clinical event from the hospital perspective was intracranial hemorrhage at $4001, followed by major extracranial hemorrhage at $3534. The costs of DVT and PE were $3003 and $2143, respectively.

Clinical Event Rates and 95% CI From the PREVAIL Study
 Event Rate95% CI
  • Abbreviations: CI, confidence interval; NIHSS, National Institute of Health Stroke Scale; PREVAIL, prevention of VTE (venous thromboembolism) after acute ischemic stroke with LMWH (low‐molecular‐weight heparin) and UFH study; UFH, unfractionated heparin.

Enoxaparin (NIHSS <14)  
Deep‐vein thrombosis0.0810.05730.1048
Pulmonary embolism0.0020.000050.011
Intracranial hemorrhage0.003100.0074
Major extracranial hemorrhage0.004700.0099
Minor hemorrhage0.03720.0240.0549
Enoxaparin (NIHSS 14)  
Deep‐vein thrombosis0.16250.10530.2197
Pulmonary embolism000
Intracranial hemorrhage0.008600.0205
Major extracranial hemorrhage0.01720.04660.1198
Minor hemorrhage0.07760.04660.1198
UFH (NIHSS <14)  
Deep‐vein thrombosis0.13560.10540.1658
Pulmonary embolism0.0040.00050.0145
Intracranial hemorrhage0.003200.0077
Major extracranial hemorrhage000
Minor hemorrhage0.05140.03550.0719
UFH (NIHSS 14)  
Deep‐vein thrombosis0.29140.22410.3588
Pulmonary embolism0.02290.00630.0575
Intracranial hemorrhage0.0160.00040.0316
Major extracranial hemorrhage000
Minor hemorrhage0.0640.0370.1019
Hospital Cost Assumptions per Event
EventCost per Event ($)*
LikeliestMinimumMaximum
  • Total costs are based on rates of each event. Patients who experience multiple events are considered to have experienced each event independent of another event.

  • Following a gamma distribution.

Deep‐vein thrombosis3,0032,4023,604
Pulmonary embolism2,1431,7142,572
Intracranial hemorrhage4,0013,2014,801
Major extracranial hemorrhage3,5342,8274,241
Minor hemorrhage1,3221,0581,586
Enoxaparin cost per dose262131
Unfractionated heparin cost per dose324

The average hospital cost with enoxaparin, when taking into account the costs of VTE and bleeding, was lower than with UFH ($422 vs $662, respectively), with a net savings of $240 per patient if enoxaparin was used. The average drug costs, including drug‐administration costs, were higher in the enoxaparin group ($360) compared with the UFH group ($259; difference $101). Nevertheless, the total hospital cost when clinical events and drug costs were considered together, was lower with enoxaparin than UFH. The total hospital costs per patient were $782 in patients receiving prophylaxis with enoxaparin and $922 in patients receiving UFH. Thus, enoxaparin was associated with a total cost‐savings of $140 per patient (Figure 2).

Figure 2
Anticoagulant‐related cost per patient.

The cost estimates according to the stroke severity score (NIHSS scores <14 vs 14) are described in Table 3. The drug costs were consistent, regardless of stroke severity, for enoxaparin ($360) and for UFH ($259). However, in both treatment groups, the event costs were higher in patients with more severe stroke, compared with less severe stroke. For example, in the enoxaparin group, the event costs were $686 in patients with NIHSS scores 14 and $326 in patients with NIHSS scores <14. Nevertheless, the overall costs (event costs plus drug costs) were lower with enoxaparin compared with UFH, both in patients with less severe and more severe stroke. In fact, the total hospital cost‐savings were greater when enoxaparin was used instead of UFH in patients with more severe stroke (cost‐saving $287 if NIHSS score 14 vs $71 if NIHSS score <14) (Table 3).

Hospital Cost Consequences for Patients With National Institute of Health Stroke Scale Scores of <14 vs 14
 Enoxaparin ($)UFH ($)Difference ($ [UFHEnoxaparin])
  • Abbreviations: NIHSS, National Institute of Health Stroke Scale; UFH, unfractionated heparin.

  • Includes drug administration costs.

NIHSS score <14   
Mean event costs per patient326497171
Mean drug costs per patient*360259101
Total costs68575671
NIHSS score 14   
Mean event costs per patient6861,073387
Mean drug costs per patient*360259101
Total costs1,0461,332287

Multiple sensitivity analyses were performed. In the base case univariate sensitivity analysis, individual costs were adjusted by 20% (Table 4). If the cost of DVT increased by 20% (from $3003 to $3604) the difference between the enoxaparin and UFH groups was $187. When the cost of DVT was decreased by 20% to $2402, enoxaparin was still cost‐saving, with a difference of $94. For each of the individual cost parameters that were varied (DVT, PE, intracranial hemorrhage, major extracranial hemorrhage, and minor hemorrhage), enoxaparin was always less costly than UFH. Subsequent sensitivity analyses were performed (not shown) where cost parameters were varied by 5%, 10%, 15%, 30%, and 40%. Enoxaparin remained less costly than UFH in all cases.

Univariate Analysis of Hospital Costs per Clinical Event
EventBaseline Cost Input ($)+20% Cost Input ($)+20% Difference ($ [UFH Enoxaparin]) (% Change)20% Cost Input ($)20% Difference ($ [UFH Enoxaparin]) (% Change)
  • Abbreviations: UFH, unfractionated heparin.

Deep‐vein thrombosis3,0033,604187 (33)2,40294 (33)
Pulmonary embolism2,1432,572144 (2.5)1,714137 (2.5)
Intracranial hemorrhage4,0014,801142 (1.3)3,201138 (1.3)
Major extracranial hemorrhage3,5344,241134 (4.0)2,827146 (4.0)
Minor hemorrhage1,3221,586142 (1.3)1,058138 (1.3)

A multivariate analysis was performed using a Monte Carlo simulation in TreeAge Pro (Figure 3). When all parameters were varied simultaneously (by 5%, 10%, 15%, 20%, 30%, and 40%) and the differences in costs between the enoxaparin and UFH groups were measured and plotted, the mean (standard deviation) difference between enoxaparin and UFH prophylaxis was $140 ($79) (Figure 3). Figure 4 shows a graphical presentation of the sensitivity analysis results for event probabilities and costs. Differences in enoxaparin drug costs, hospital costs for DVT, and probability of DVT for patients on enoxaparin are the factors that have the greatest effect on the overall cost.

Figure 3
Sensitivity analysis using Monte Carlo simulation to detect cost differences between unfractionated heparin and enoxaparin.
Figure 4
Sensitivity analysis results summarized in a tornado diagram for event probabilities and costs (the range over which they were varied is given in parentheses). Differences in enoxaparin drug costs, hospital costs for DVT, and probability of DVT for patients on enoxaparin are the factors which have the greatest effect on the expected value. The value was 0 for the probability of MEH for patients with NIHSS <14 or ≥14 on UFH. Abbreviations: DVT, deep vein thrombosis, ICH, intracranial hemorrhage, MEH, major extracranial hemorrhage, MH, minor extracranial hemorrhage, NIHSS, National Institute of Health Stroke Scale, PE, pulmonary embolism, UFH, unfractionated heparin.

Finally, an additional scenario was performed using a published ratio of asymptomatic DVT to symptomatic VTE, due to the fact that not all VTE events in the real‐world present with symptoms prompting treatment. Quinlan et al. determined a ratio of asymptomatic DVT to symptomatic VTE of 5 for total hip replacement patients and of 21 for total knee replacement patients.28 Although derived from different patient populations who received different anticoagulants, we utilized the symptomatic event rates from the pooled studies to recalculate cost differences between enoxaparin and UFH in acute ischemic stroke. Using only symptomatic event rates, based on the 21:1 ratio in patients undergoing total knee replacement, the total cost for enoxaparin was $485 compared to $386 for UFH. Similar results were found based on the 5:1 ratio in patients with total hip replacement (enoxaparin $532 vs $472 for UFH). This was the only scenario where the higher drug cost of prophylaxis with enoxaparin was not completely offset by the reduction in events compared to UFH, likely due to the smaller difference in event rates once examining only symptomatic VTE.

DISCUSSION

This analysis demonstrates that, from the hospital perspective, enoxaparin 40 mg subcutaneously once‐daily is associated with lower total hospital costs and is more cost‐effective than twice‐daily UFH 5000 U subcutaneously for the prevention of VTE in patients with acute ischemic stroke. Despite higher drug‐acquisition costs, enoxaparin was associated with total cost‐savings of $140 per patient. This is due to the lower event rates with enoxaparin compared with UFH.

Previous studies, using hospital or payer information, have shown that VTE prophylaxis is more cost‐effective compared with no prophylaxis. In terms of the different VTE prophylaxis regimens, enoxaparin represents a more cost‐effective option in comparison with UFH19, 21, 2932 and also when compared with fondaparinux.21, 33 When comparing the results between different trials, it should be noted that previous analyses were mainly modeled on the Prophylaxis in Medical Patients with Enoxaparin (MEDENOX) study, which was performed in general medical patients and reported a VTE rate of 5.5%.6 However, patients with acute ischemic stroke are at a higher risk of VTE, with a 10% incidence of VTE reported in the PREVAIL study.14 Furthermore, twice‐daily rather than three‐timesdaily administration of UFH was used in the PREVAIL study, based on the current practice patterns seen during the PREVAIL trial design.

A recent retrospective analysis of transactional billing records demonstrated that, despite higher mean costs of anticoagulation therapy, the mean, total, adjusted direct hospital costs were lower with LMWH thromboprophylaxis compared with UFH ($7358 vs $8680, respectively; difference $1322; P < 0.001).21 A previous study by Burleigh and colleagues based on hospital discharge information extracted from both medical and surgical patients, has a sub‐analysis in patients with stroke. In these patients also, the total costs were lower for enoxaparin compared with UFH ($8608 vs $8911, respectively; difference $303).29 In the Burleigh study, drug costs and total discharge costs (eg, room and board, laboratory, and diagnostic imaging) were derived from drug charges and total charges, and were converted to estimated costs using cost‐to‐charge methods, so the absolute figures are not directly comparable with the current analysis.

This study adds to current literature by using data from a prospective study to analyze the hospital costs of VTE prophylaxis in stroke patients. The current study also provides a valuable cost‐analysis regarding a specific subgroup of medical patients at particularly high risk of VTE, and provides an economic comparison among stroke patients with NIHSS scores of <14 versus 14. In the PREVAIL study, despite a 2‐fold higher incidence of VTE in patients with more severe stroke (16.3% vs 8.3%), a similar reduction in VTE risk was observed with enoxaparin versus UFH in patients with NIHSS scores of 14 (odds ratio = 0.56; 95% CI = 0.37‐0.84; P = 0.0036) and <14 (odds ratio = 0.46; 95% CI = 0.27‐0.78; P = 0.0043).14 Enoxaparin was shown to be cost‐saving relative to UFH in both patient groups and, in particular, in patients with more severe stroke.

Potential limitations of the current analysis include the applicability of the figures obtained from the highly selected clinical trial population to real‐world clinical practice, and the fact that it is difficult to match cost estimates to trial data definitions. For example, this analysis was conducted with a comparator of twice‐daily UFH (as opposed to three‐timesdaily) which may be used in the real‐world setting and may have resulted in the increased number of events in the UFH group seen in the PREVAIL study. Due to a variety of differences between real‐world practice patterns and the PREVAIL clinical trial, we can only speculate as to the true cost‐consequences of utilizing enoxaparin versus UFH.

Furthermore, the original model did not include a sub‐analysis regarding the rates and, therefore, costs of proximal/symptomatic VTE. In the primary study of PREVAIL, the rates of symptomatic DVT were 1 in 666 patients (<1%) for enoxaparin and 4 in 669 patients (1%) for UFH, whereas the rates of proximal DVT were 30 in 666 patients (5%) and 64 in 669 patients (10%), respectively. Sensitivity analyses were performed to investigate the impact of lower rates of both DVT and PE (up to 40%), and the differences between groups were found to be robust. However, it is important to note that overall costs for both groups may have been increased through the inclusion of asymptomatic costs, with a more distinct separation of these costs making for a good follow‐up study. In a similar cost‐analysis we performed based on the PREVAIL study, which assessed the cost to the payer, we included an analysis of costs according to 3 different VTE definitions: the PREVAIL VTE definition (as in the current study); a definition of major VTE (PE, symptomatic DVT, and asymptomatic proximal DVT); and primary endpoints recommended by the European Medicines Agency Committee for Medicinal Products for Human Use for studies on VTE (proximal DVT, nonfatal PE, and all‐cause mortality). We found similar results irrespective of clinical event definitions.34 In an additional model scenario using a published ratio of asymptomatic DVT to symptomatic VTE,28 the higher drug cost of prophylaxis with enoxaparin was not completely offset by the reduction in events compared to UFH. This was likely due to the smaller difference in event rates once examining only symptomatic VTE. This scenario was limited by the fact that the ratio was derived from different patient populations receiving different anticoagulants than stroke patients.

In conclusion, data from this analysis adds to the evidence that, from the hospital perspective, the higher drug cost of enoxaparin is offset by the economic consequences of the events avoided as compared with UFH for the prevention of VTE following acute ischemic stroke, particularly in patients with severe stroke.

Acknowledgements

The authors thank Aylin Lee from I3 Innovus for her contribution to this study. The authors also acknowledge Min Chen for her assistance in statistical analysis, and Essy Mozaffari for his contribution to this study.

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  15. Geerts WH,Bergqvist D,Pineo GF, et al;for the American College of Chest Physicians.Prevention of venous thromboembolism: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines (8th ed).Chest.2008;133(6 suppl):381S453S.
  16. Albers GW,Amarenco P,Easton JD,Sacco RL,Teal P;for the American College of Chest Physicians.Antithrombotic and thrombolytic therapy for ischemic stroke: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines (8th ed).Chest.2008;133(6 suppl):630S669S.
  17. Spyropoulos AC,Hurley JS,Ciesla GN,de Lissovoy G.Management of acute proximal deep vein thrombosis: pharmacoeconomic evaluation of outpatient treatment with enoxaparin vs inpatient treatment with unfractionated heparin.Chest.2002;122:108114.
  18. de Lissovoy G,Subedi P.Economic evaluation of enoxaparin as prophylaxis against venous thromboembolism in seriously ill medical patients: a US perspective.Am J Manag Care.2002;8:10821088.
  19. McGarry LJ,Thompson D,Weinstein MC,Goldhaber SZ.Cost effectiveness of thromboprophylaxis with a low‐molecular‐weight heparin versus unfractionated heparin in acutely ill medical inpatients.Am J Manag Care.2004;10:632642.
  20. Schädlich PK,Kentsch M,Weber M, et al.Cost effectiveness of enoxaparin as prophylaxis against venous thromboembolic complications in acutely ill medical inpatients: modelling study from the hospital perspective in Germany.Pharmacoeconomics.2006;24:571591.
  21. Merli G,Ferrufino CP,Lin J,Hussein M,Battleman D.Hospital‐based costs associated with venous thromboembolism prophylaxis regimens.J Thromb Thrombolysis.2010;29:449458.
  22. Cohen AT,Tapson VF,Bergmann JF, et al;for the ENDORSE Investigators.Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross‐sectional study.Lancet.2008;371:387394.
  23. Tapson VF,Decousus H,Pini M, et al;for the IMPROVE Investigators.Venous thromboembolism prophylaxis in acutely ill hospitalized medical patients: findings from the International Medical Prevention Registry on Venous Thromboembolism.Chest.2007;132:936945.
  24. United States Department of Health August 2008. Available at: http://www.ahrq.gov/qual/vtguide/. Accessed August 18,2010.
  25. Sherman DG,Soltes S,Samuel R,Chibedi‐Deroche D.Enoxaparin versus unfractionated heparin in the prevention of venous thromboembolism after acute ischemic stroke: rationale, design, and methods of an open‐label, randomized, parallel‐group multicenter trial.J Stroke Cerebrovasc Dis.2005;14:95100.
  26. Quinlan DJ,Eikelboom JW,Dahl OE,Eriksson BI,Sidhu PS,Hirsh J.Association between asymptomatic deep vein thrombosis detected by venography and symptomatic venous thromboembolism in patients undergoing elective hip or knee surgery.J Thromb Haemost.2007;5:14381443.
  27. Burleigh E,Wang C,Foster D, et al.Thromboprophylaxis in medically ill patients at risk for venous thromboembolism.Am J Health Syst Pharm.2006;63(20 suppl 6):S23S29.
  28. Deitelzweig SB,Becker R,Lin J,Benner J.Comparison of the two‐year outcomes and costs of prophylaxis in medical patients at risk of venous thromboembolism.Thromb Haemost.2008;100:810820.
  29. de Lissovoy G,Yusen RD,Spiro TE,Krupski WC,Champion AH,Sorensen SV.Cost for inpatient care of venous thrombosis: a trial of enoxaparin vs standard heparin.Arch Intern Med.2000;160:31603165.
  30. Offord R,Lloyd AC,Anderson P,Bearne A.Economic evaluation of enoxaparin for the prevention of venous thromboembolism in acutely ill medical patients.Pharm World Sci.2004;26:214220.
  31. Merli G,Ferrufino C,Lin J,Hussein M,Battleman D.Total hospital‐based costs of enoxaparin or fondaparinux prophylaxis in patients at risk of venous thromboembolism [abstract]. Presented at the Chest 2008 Annual Meeting; October 25–30,2008; Philadelphia, PA.
  32. Pineo G,Lin J,Stern L,Subrahmanian T,Annemans L.Economic impact of enoxaparin after acute ischemic stroke based on PREVAIL.Clin Appl Thromb Hemost.2011;17:150157.
References
  1. Heit JA.Venous thromboembolism: disease burden, outcomes and risk factors.J Thromb Haemost.2005;3:16111617.
  2. Heit JA.The epidemiology of venous thromboembolism in the community: implications for prevention and management.J Thromb Thrombolysis.2006;21:2329.
  3. Heit JA,O'Fallon WM,Petterson TM, et al.Relative impact of risk factors for deep vein thrombosis and pulmonary embolism: a population‐based study.Arch Intern Med.2002;162:12451248.
  4. Heit JA,Silverstein MD,Mohr DN,Petterson TM,O'Fallon WM,Melton LJ.Risk factors for deep vein thrombosis and pulmonary embolism: a population‐based case‐control study.Arch Intern Med.2000;160:809815.
  5. Alikhan R,Cohen AT.A safety analysis of thromboprophylaxis in acute medical illness.Thromb Haemost.2003;89:590591.
  6. Samama MM,Dahl OE,Quinlan DJ,Mismetti P,Rosencher N.Quantification of risk factors for venous thromboembolism: a preliminary study for the development of a risk assessment tool.Haematologica.2003;88:14101421.
  7. Gregory PC,Kuhlemeier KV.Prevalence of venous thromboembolism in acute hemorrhagic and thromboembolic stroke.Am J Phys Med Rehabil.2003;82:364369.
  8. Amin A,Stemkowski S,Lin J,Yang G.Thromboprophylaxis rates in US medical centers: success or failure?J Thromb Haemost.2007;5:16101616.
  9. Davenport RJ,Dennis MS,Wellwood I,Warlow CP.Complications after acute stroke.Stroke.1996;27:415420.
  10. Kelly J,Rudd A,Lewis R,Hunt BJ.Venous thromboembolism after acute stroke.Stroke.2001;32:262267.
  11. Hillbom M,Erilä T,Sotaniemi K,Tatlisumak T,Sarna S,Kaste M.Enoxaparin vs heparin for prevention of deep‐vein thrombosis in acute ischaemic stroke: a randomized, double‐blind study.Acta Neurol Scand.2002;106:8492.
  12. Sandercock PA,Counsell C,Tseng MC.Low‐molecular‐weight heparins or heparinoids versus standard unfractionated heparin for acute ischaemic stroke.Cochrane Database Syst Rev.2008;(3):CD000119.
  13. Diener HC,Ringelstein EB,von Kummer R, et al;for the PROTECT Trial Group.Prophylaxis of thrombotic and embolic events in acute ischemic stroke with the low‐molecular‐weight heparin certoparin: results of the PROTECT Trial.Stroke.2006;37:139144.
  14. Sherman DG,Albers GW,Bladin C, et al;for the PREVAIL Investigators.The efficacy and safety of enoxaparin versus unfractionated heparin for the prevention of venous thromboembolism after acute ischaemic stroke (PREVAIL study): an open‐label randomised comparison.Lancet.2007;369:13471355.
  15. Geerts WH,Bergqvist D,Pineo GF, et al;for the American College of Chest Physicians.Prevention of venous thromboembolism: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines (8th ed).Chest.2008;133(6 suppl):381S453S.
  16. Albers GW,Amarenco P,Easton JD,Sacco RL,Teal P;for the American College of Chest Physicians.Antithrombotic and thrombolytic therapy for ischemic stroke: American College of Chest Physicians Evidence‐Based Clinical Practice Guidelines (8th ed).Chest.2008;133(6 suppl):630S669S.
  17. Spyropoulos AC,Hurley JS,Ciesla GN,de Lissovoy G.Management of acute proximal deep vein thrombosis: pharmacoeconomic evaluation of outpatient treatment with enoxaparin vs inpatient treatment with unfractionated heparin.Chest.2002;122:108114.
  18. de Lissovoy G,Subedi P.Economic evaluation of enoxaparin as prophylaxis against venous thromboembolism in seriously ill medical patients: a US perspective.Am J Manag Care.2002;8:10821088.
  19. McGarry LJ,Thompson D,Weinstein MC,Goldhaber SZ.Cost effectiveness of thromboprophylaxis with a low‐molecular‐weight heparin versus unfractionated heparin in acutely ill medical inpatients.Am J Manag Care.2004;10:632642.
  20. Schädlich PK,Kentsch M,Weber M, et al.Cost effectiveness of enoxaparin as prophylaxis against venous thromboembolic complications in acutely ill medical inpatients: modelling study from the hospital perspective in Germany.Pharmacoeconomics.2006;24:571591.
  21. Merli G,Ferrufino CP,Lin J,Hussein M,Battleman D.Hospital‐based costs associated with venous thromboembolism prophylaxis regimens.J Thromb Thrombolysis.2010;29:449458.
  22. Cohen AT,Tapson VF,Bergmann JF, et al;for the ENDORSE Investigators.Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross‐sectional study.Lancet.2008;371:387394.
  23. Tapson VF,Decousus H,Pini M, et al;for the IMPROVE Investigators.Venous thromboembolism prophylaxis in acutely ill hospitalized medical patients: findings from the International Medical Prevention Registry on Venous Thromboembolism.Chest.2007;132:936945.
  24. United States Department of Health August 2008. Available at: http://www.ahrq.gov/qual/vtguide/. Accessed August 18,2010.
  25. Sherman DG,Soltes S,Samuel R,Chibedi‐Deroche D.Enoxaparin versus unfractionated heparin in the prevention of venous thromboembolism after acute ischemic stroke: rationale, design, and methods of an open‐label, randomized, parallel‐group multicenter trial.J Stroke Cerebrovasc Dis.2005;14:95100.
  26. Quinlan DJ,Eikelboom JW,Dahl OE,Eriksson BI,Sidhu PS,Hirsh J.Association between asymptomatic deep vein thrombosis detected by venography and symptomatic venous thromboembolism in patients undergoing elective hip or knee surgery.J Thromb Haemost.2007;5:14381443.
  27. Burleigh E,Wang C,Foster D, et al.Thromboprophylaxis in medically ill patients at risk for venous thromboembolism.Am J Health Syst Pharm.2006;63(20 suppl 6):S23S29.
  28. Deitelzweig SB,Becker R,Lin J,Benner J.Comparison of the two‐year outcomes and costs of prophylaxis in medical patients at risk of venous thromboembolism.Thromb Haemost.2008;100:810820.
  29. de Lissovoy G,Yusen RD,Spiro TE,Krupski WC,Champion AH,Sorensen SV.Cost for inpatient care of venous thrombosis: a trial of enoxaparin vs standard heparin.Arch Intern Med.2000;160:31603165.
  30. Offord R,Lloyd AC,Anderson P,Bearne A.Economic evaluation of enoxaparin for the prevention of venous thromboembolism in acutely ill medical patients.Pharm World Sci.2004;26:214220.
  31. Merli G,Ferrufino C,Lin J,Hussein M,Battleman D.Total hospital‐based costs of enoxaparin or fondaparinux prophylaxis in patients at risk of venous thromboembolism [abstract]. Presented at the Chest 2008 Annual Meeting; October 25–30,2008; Philadelphia, PA.
  32. Pineo G,Lin J,Stern L,Subrahmanian T,Annemans L.Economic impact of enoxaparin after acute ischemic stroke based on PREVAIL.Clin Appl Thromb Hemost.2011;17:150157.
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Journal of Hospital Medicine - 7(3)
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Economic impact of enoxaparin versus unfractionated heparin for venous thromboembolism prophylaxis in patients with acute ischemic stroke: A hospital perspective of the PREVAIL trial
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Economic impact of enoxaparin versus unfractionated heparin for venous thromboembolism prophylaxis in patients with acute ischemic stroke: A hospital perspective of the PREVAIL trial
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Department of Medicine, University of Calgary, Room 905, North Tower Foothills Hospital, 1403‐29 St NW, Calgary, AB, Canada T2N 2T9
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Chief resident year as stepping stone to attending academic hospitalist

Academic hospitalists have multiple duties including direct patient care, hospital management, teaching, and scholarly productivity. We are frequently pulled in divergent directions, while attending to these responsibilities. Without a framework to manage these assorted tasks, we are at risk of subpar performance and career dissatisfaction. Alternatively, we often thrive in our roles as utility players when armed with a developed skill set. Our profession could benefit greatly from encouraging future academic hospitalists to obtain further training prior to starting as an attending. Although hospital medicine fellowship training exists, there are still relatively few programs available. A well‐crafted year spent as a chief medical resident (CMR) may be a viable alternative.

My year as CMR allowed me to develop the skills necessary for success as an academic hospitalist in a supportive setting, and has given me an advantage in accelerating my career. This experience provided me with important tools that my initial 3 years of internal medicine residency did not. Even during my final year of residency, I was focused mostly on obtaining medical knowledge, learning its clinical applications, and honing team leadership skills. My mind rarely trespassed into the broader concerns of quality improvement initiatives, educational enhancements, or hospital management issues. Although the American College of Graduate Medical Education (ACGME) core competencies are helping to better focus residents' attention to these more diverse aspects of healthcare, residents still spend the majority of their time providing direct patient care.1 Now in my fourth year as an attending academic hospitalist, I continue to appreciate how my chief experience provided the foundation for much of the work I perform today.

My motivations for becoming a CMR included a desire to spend more time teaching and learning medicine, and an interest in helping to improve the residency program itself. I did not appreciate how much of the job would be spent managing people, and evaluating systems of care within the hospital, while working closely with nurses and hospital administrators. However, the skills I learned while addressing those unexpected tasks are what continue to help me in my position as a multifaceted hospitalist today. CMRs have been described as middle managers, being pushed and pulled by the demands and requirements of the groups above, below and around them.2 Academic hospitalists who frequently wear administrative and educational hats are not dissimilar. Retrospectively, I realize how fortunate I was to be exposed to those aspects as a CMR, with many of the same responsibilities but without the full expectations of a more seasoned attending.

The most memorable interaction during my first day as junior ward attending was with a revered internist, himself a former CMR, who dryly commented, So, you're pretending now. It took me a moment to catch his play on words until he clarified, you are now a pre‐attending. The true meaning of this was elucidated over the next several weeks as I was expected to perform many of the same duties of a seasoned attending, but often had the sense that I was only pretending to be an attending and still had much to learn.

CMR positions vary in terms of clinical, educational, and administrative responsibilities. Moreover, many institutions mix inpatient and outpatient roles. My position was focused almost entirely on inpatient duties at a single hospital, which gave me an in‐depth and longitudinal view of how a hospital is managed. Like many other CMRs, much of my time was spent on educational activities, such as running morning report, preparing for chief of medicine rounds, coordinating noon teaching conferences, and spending time with the medical students. Administrative tasks included various institutional‐based meetings for student grading, educational review committees, and program scheduling. In addition, I spent 1 month as junior attending on a ward team. Many other programs' CMRs spend more time as junior attending; however, by offloading some of this ward service requirement, I feel fortunate to have had that time to use for my own scholarly activity and teaching/administrative opportunities. Perhaps unique to my CMR position, I also was involved with the daily running of the hospital by working with administrators to evaluate patient transfer requests and addressing provider work flow issues. These additional tasks provided an invaluable learning experience.

Organizing morning report, running physical diagnosis rounds, and preparing cases and speakers for Chair's Rounds allowed me to hone and expand my teaching skills in ways that 3 years of residency did not. Moreover, it put me in direct contact with an energetic, inspiring group of learners that challenged me to solidify my own medical knowledge. (Try explaining the delta‐delta equation to figure out if there are 2 metabolic processes going on, in front of a group of 20 residents, and you'll discover what I mean.) I quickly learned that the one doing the talking is the one doing the learning and changed my teaching style to better facilitate student learning. My bedside learning was further augmented by attending Masters' Rounds to which I owe my ongoing interests in physical diagnosis. Masters Rounds were given once a week by 2 master clinicians. It was only for chief residents and was directed at teaching us how to teach others the art of bedside physical diagnosis. The majority of physical exam teaching points I focus on today come from those sessions.

As chief, I felt like I had the pulse of the hospital at all times. Most of my mornings were spent on the wards floating between teams. I owe thanks to my predecessor who told me that the true sign of a good CMR was to never sit long enough in your chair to let it get warm. My office was located on the wards, between a team room and a double patient room. Aside from times when I was having confidential conversations with residents, the door was open. Nurses looking to vent, phlebotomists wanting to sit down, and attendings needing a break from their teams to get work done were common visitors. Administrative personnel were also frequent visitors, usually requesting me to disseminate new policies to the residents. Because of this, I learned to understand and better interact with the diverse group of people responsible for making a teaching hospital function. These are the same constituencies that I now sit down with on various committees to attempt to make my present hospital operate more smoothly.

Despite running morning report, attending rounds with teams, and developing plans for better patient flow, I had time for scholarly work and found easy mentorship. I was able to revive 2 projects I had started as a resident and bring them close to conclusion under the continued mentorship of my coinvestigators. Offers for career skill development were also abound, and I benefited greatly from one associate director's tutorials on preparing effective PowerPoint presentations. Another attending mentored me in student feedback skills, which have allowed me to become a much more effective educator. I was also able to model that mentorship and begin to build my own mentor relationships with my students. In fact, this mentorship has become one of the most fulfilling aspects of my job. I was fortunate to have that mentorship early on in my career, as similar mentorship becomes difficult to obtain once in an attending hospitalist position.3

In conclusion, although current internal medicine residency training provides intensive direct patient care experiences, it only allows glimpses into the other aspects of an academic hospitalist's job. Unfortunately, it does not adequately prepare one to begin this type of position with a full complement of skills. Only a minority of hospitalists pursue additional structured training directly after residency; the majority jump into hospitalist positions and opt for on‐the‐job training. While there is an early economic advantage to starting an attending position without delay, I believe that the skills learned during an additional year of dedicated training allow for a more meaningful work experience and, ultimately, a faster rise within the track of an academic hospitalist.

The tasks that residency programs and hospitals may give to CMRs provide fertile material for developing the skills necessary to become a productive academic hospitalist. I thrived on the multifaceted work of caring for a diverse group of patients, teaching different levels of learners, helping to manage various hospital systems, and better understanding the hospital as the sum of its parts. As noted above, this pre‐attending league gave me the exposure to more fully develop my academic hospitalist game in a supportive environment. A CMR year may be beneficial for residents entering any career in internal medicine; however, I believe it is most aptly suited as a stepping stone for future academic hospitalists. I strongly recommend that current residents interested in academic hospital medicine consider a CMR position, and encourage program directors to consider molding their inpatient CMR experiences to facilitate this. Moreover, unless fellowship training in hospital medicine becomes the norm, I propose that current academic hospitalists do more to closely court and usher these pretenders into our ranks.

Files
References
  1. Varkey P,Karlapudi S,Rose S,Nelson R,Warner M.A systems approach for implementing practice‐based learning and improvement and systems‐based practice in graduate medical education.Acad Med.2009;84(3):335339.
  2. Berg DN,Huot SJ.Middle manager role of the chief medical resident: an organizational psychologist's perspective.J Gen Intern Med.2007;22(12):17711774.
  3. Harrison R,Hunter AJ,Sharpe B,Auerbach AD.Survey of US academic hospitalist leaders about mentorship and academic activities in hospitalist groups.J Hosp Med.2011;6:59.
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Journal of Hospital Medicine - 6(9)
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Academic hospitalists have multiple duties including direct patient care, hospital management, teaching, and scholarly productivity. We are frequently pulled in divergent directions, while attending to these responsibilities. Without a framework to manage these assorted tasks, we are at risk of subpar performance and career dissatisfaction. Alternatively, we often thrive in our roles as utility players when armed with a developed skill set. Our profession could benefit greatly from encouraging future academic hospitalists to obtain further training prior to starting as an attending. Although hospital medicine fellowship training exists, there are still relatively few programs available. A well‐crafted year spent as a chief medical resident (CMR) may be a viable alternative.

My year as CMR allowed me to develop the skills necessary for success as an academic hospitalist in a supportive setting, and has given me an advantage in accelerating my career. This experience provided me with important tools that my initial 3 years of internal medicine residency did not. Even during my final year of residency, I was focused mostly on obtaining medical knowledge, learning its clinical applications, and honing team leadership skills. My mind rarely trespassed into the broader concerns of quality improvement initiatives, educational enhancements, or hospital management issues. Although the American College of Graduate Medical Education (ACGME) core competencies are helping to better focus residents' attention to these more diverse aspects of healthcare, residents still spend the majority of their time providing direct patient care.1 Now in my fourth year as an attending academic hospitalist, I continue to appreciate how my chief experience provided the foundation for much of the work I perform today.

My motivations for becoming a CMR included a desire to spend more time teaching and learning medicine, and an interest in helping to improve the residency program itself. I did not appreciate how much of the job would be spent managing people, and evaluating systems of care within the hospital, while working closely with nurses and hospital administrators. However, the skills I learned while addressing those unexpected tasks are what continue to help me in my position as a multifaceted hospitalist today. CMRs have been described as middle managers, being pushed and pulled by the demands and requirements of the groups above, below and around them.2 Academic hospitalists who frequently wear administrative and educational hats are not dissimilar. Retrospectively, I realize how fortunate I was to be exposed to those aspects as a CMR, with many of the same responsibilities but without the full expectations of a more seasoned attending.

The most memorable interaction during my first day as junior ward attending was with a revered internist, himself a former CMR, who dryly commented, So, you're pretending now. It took me a moment to catch his play on words until he clarified, you are now a pre‐attending. The true meaning of this was elucidated over the next several weeks as I was expected to perform many of the same duties of a seasoned attending, but often had the sense that I was only pretending to be an attending and still had much to learn.

CMR positions vary in terms of clinical, educational, and administrative responsibilities. Moreover, many institutions mix inpatient and outpatient roles. My position was focused almost entirely on inpatient duties at a single hospital, which gave me an in‐depth and longitudinal view of how a hospital is managed. Like many other CMRs, much of my time was spent on educational activities, such as running morning report, preparing for chief of medicine rounds, coordinating noon teaching conferences, and spending time with the medical students. Administrative tasks included various institutional‐based meetings for student grading, educational review committees, and program scheduling. In addition, I spent 1 month as junior attending on a ward team. Many other programs' CMRs spend more time as junior attending; however, by offloading some of this ward service requirement, I feel fortunate to have had that time to use for my own scholarly activity and teaching/administrative opportunities. Perhaps unique to my CMR position, I also was involved with the daily running of the hospital by working with administrators to evaluate patient transfer requests and addressing provider work flow issues. These additional tasks provided an invaluable learning experience.

Organizing morning report, running physical diagnosis rounds, and preparing cases and speakers for Chair's Rounds allowed me to hone and expand my teaching skills in ways that 3 years of residency did not. Moreover, it put me in direct contact with an energetic, inspiring group of learners that challenged me to solidify my own medical knowledge. (Try explaining the delta‐delta equation to figure out if there are 2 metabolic processes going on, in front of a group of 20 residents, and you'll discover what I mean.) I quickly learned that the one doing the talking is the one doing the learning and changed my teaching style to better facilitate student learning. My bedside learning was further augmented by attending Masters' Rounds to which I owe my ongoing interests in physical diagnosis. Masters Rounds were given once a week by 2 master clinicians. It was only for chief residents and was directed at teaching us how to teach others the art of bedside physical diagnosis. The majority of physical exam teaching points I focus on today come from those sessions.

As chief, I felt like I had the pulse of the hospital at all times. Most of my mornings were spent on the wards floating between teams. I owe thanks to my predecessor who told me that the true sign of a good CMR was to never sit long enough in your chair to let it get warm. My office was located on the wards, between a team room and a double patient room. Aside from times when I was having confidential conversations with residents, the door was open. Nurses looking to vent, phlebotomists wanting to sit down, and attendings needing a break from their teams to get work done were common visitors. Administrative personnel were also frequent visitors, usually requesting me to disseminate new policies to the residents. Because of this, I learned to understand and better interact with the diverse group of people responsible for making a teaching hospital function. These are the same constituencies that I now sit down with on various committees to attempt to make my present hospital operate more smoothly.

Despite running morning report, attending rounds with teams, and developing plans for better patient flow, I had time for scholarly work and found easy mentorship. I was able to revive 2 projects I had started as a resident and bring them close to conclusion under the continued mentorship of my coinvestigators. Offers for career skill development were also abound, and I benefited greatly from one associate director's tutorials on preparing effective PowerPoint presentations. Another attending mentored me in student feedback skills, which have allowed me to become a much more effective educator. I was also able to model that mentorship and begin to build my own mentor relationships with my students. In fact, this mentorship has become one of the most fulfilling aspects of my job. I was fortunate to have that mentorship early on in my career, as similar mentorship becomes difficult to obtain once in an attending hospitalist position.3

In conclusion, although current internal medicine residency training provides intensive direct patient care experiences, it only allows glimpses into the other aspects of an academic hospitalist's job. Unfortunately, it does not adequately prepare one to begin this type of position with a full complement of skills. Only a minority of hospitalists pursue additional structured training directly after residency; the majority jump into hospitalist positions and opt for on‐the‐job training. While there is an early economic advantage to starting an attending position without delay, I believe that the skills learned during an additional year of dedicated training allow for a more meaningful work experience and, ultimately, a faster rise within the track of an academic hospitalist.

The tasks that residency programs and hospitals may give to CMRs provide fertile material for developing the skills necessary to become a productive academic hospitalist. I thrived on the multifaceted work of caring for a diverse group of patients, teaching different levels of learners, helping to manage various hospital systems, and better understanding the hospital as the sum of its parts. As noted above, this pre‐attending league gave me the exposure to more fully develop my academic hospitalist game in a supportive environment. A CMR year may be beneficial for residents entering any career in internal medicine; however, I believe it is most aptly suited as a stepping stone for future academic hospitalists. I strongly recommend that current residents interested in academic hospital medicine consider a CMR position, and encourage program directors to consider molding their inpatient CMR experiences to facilitate this. Moreover, unless fellowship training in hospital medicine becomes the norm, I propose that current academic hospitalists do more to closely court and usher these pretenders into our ranks.

Academic hospitalists have multiple duties including direct patient care, hospital management, teaching, and scholarly productivity. We are frequently pulled in divergent directions, while attending to these responsibilities. Without a framework to manage these assorted tasks, we are at risk of subpar performance and career dissatisfaction. Alternatively, we often thrive in our roles as utility players when armed with a developed skill set. Our profession could benefit greatly from encouraging future academic hospitalists to obtain further training prior to starting as an attending. Although hospital medicine fellowship training exists, there are still relatively few programs available. A well‐crafted year spent as a chief medical resident (CMR) may be a viable alternative.

My year as CMR allowed me to develop the skills necessary for success as an academic hospitalist in a supportive setting, and has given me an advantage in accelerating my career. This experience provided me with important tools that my initial 3 years of internal medicine residency did not. Even during my final year of residency, I was focused mostly on obtaining medical knowledge, learning its clinical applications, and honing team leadership skills. My mind rarely trespassed into the broader concerns of quality improvement initiatives, educational enhancements, or hospital management issues. Although the American College of Graduate Medical Education (ACGME) core competencies are helping to better focus residents' attention to these more diverse aspects of healthcare, residents still spend the majority of their time providing direct patient care.1 Now in my fourth year as an attending academic hospitalist, I continue to appreciate how my chief experience provided the foundation for much of the work I perform today.

My motivations for becoming a CMR included a desire to spend more time teaching and learning medicine, and an interest in helping to improve the residency program itself. I did not appreciate how much of the job would be spent managing people, and evaluating systems of care within the hospital, while working closely with nurses and hospital administrators. However, the skills I learned while addressing those unexpected tasks are what continue to help me in my position as a multifaceted hospitalist today. CMRs have been described as middle managers, being pushed and pulled by the demands and requirements of the groups above, below and around them.2 Academic hospitalists who frequently wear administrative and educational hats are not dissimilar. Retrospectively, I realize how fortunate I was to be exposed to those aspects as a CMR, with many of the same responsibilities but without the full expectations of a more seasoned attending.

The most memorable interaction during my first day as junior ward attending was with a revered internist, himself a former CMR, who dryly commented, So, you're pretending now. It took me a moment to catch his play on words until he clarified, you are now a pre‐attending. The true meaning of this was elucidated over the next several weeks as I was expected to perform many of the same duties of a seasoned attending, but often had the sense that I was only pretending to be an attending and still had much to learn.

CMR positions vary in terms of clinical, educational, and administrative responsibilities. Moreover, many institutions mix inpatient and outpatient roles. My position was focused almost entirely on inpatient duties at a single hospital, which gave me an in‐depth and longitudinal view of how a hospital is managed. Like many other CMRs, much of my time was spent on educational activities, such as running morning report, preparing for chief of medicine rounds, coordinating noon teaching conferences, and spending time with the medical students. Administrative tasks included various institutional‐based meetings for student grading, educational review committees, and program scheduling. In addition, I spent 1 month as junior attending on a ward team. Many other programs' CMRs spend more time as junior attending; however, by offloading some of this ward service requirement, I feel fortunate to have had that time to use for my own scholarly activity and teaching/administrative opportunities. Perhaps unique to my CMR position, I also was involved with the daily running of the hospital by working with administrators to evaluate patient transfer requests and addressing provider work flow issues. These additional tasks provided an invaluable learning experience.

Organizing morning report, running physical diagnosis rounds, and preparing cases and speakers for Chair's Rounds allowed me to hone and expand my teaching skills in ways that 3 years of residency did not. Moreover, it put me in direct contact with an energetic, inspiring group of learners that challenged me to solidify my own medical knowledge. (Try explaining the delta‐delta equation to figure out if there are 2 metabolic processes going on, in front of a group of 20 residents, and you'll discover what I mean.) I quickly learned that the one doing the talking is the one doing the learning and changed my teaching style to better facilitate student learning. My bedside learning was further augmented by attending Masters' Rounds to which I owe my ongoing interests in physical diagnosis. Masters Rounds were given once a week by 2 master clinicians. It was only for chief residents and was directed at teaching us how to teach others the art of bedside physical diagnosis. The majority of physical exam teaching points I focus on today come from those sessions.

As chief, I felt like I had the pulse of the hospital at all times. Most of my mornings were spent on the wards floating between teams. I owe thanks to my predecessor who told me that the true sign of a good CMR was to never sit long enough in your chair to let it get warm. My office was located on the wards, between a team room and a double patient room. Aside from times when I was having confidential conversations with residents, the door was open. Nurses looking to vent, phlebotomists wanting to sit down, and attendings needing a break from their teams to get work done were common visitors. Administrative personnel were also frequent visitors, usually requesting me to disseminate new policies to the residents. Because of this, I learned to understand and better interact with the diverse group of people responsible for making a teaching hospital function. These are the same constituencies that I now sit down with on various committees to attempt to make my present hospital operate more smoothly.

Despite running morning report, attending rounds with teams, and developing plans for better patient flow, I had time for scholarly work and found easy mentorship. I was able to revive 2 projects I had started as a resident and bring them close to conclusion under the continued mentorship of my coinvestigators. Offers for career skill development were also abound, and I benefited greatly from one associate director's tutorials on preparing effective PowerPoint presentations. Another attending mentored me in student feedback skills, which have allowed me to become a much more effective educator. I was also able to model that mentorship and begin to build my own mentor relationships with my students. In fact, this mentorship has become one of the most fulfilling aspects of my job. I was fortunate to have that mentorship early on in my career, as similar mentorship becomes difficult to obtain once in an attending hospitalist position.3

In conclusion, although current internal medicine residency training provides intensive direct patient care experiences, it only allows glimpses into the other aspects of an academic hospitalist's job. Unfortunately, it does not adequately prepare one to begin this type of position with a full complement of skills. Only a minority of hospitalists pursue additional structured training directly after residency; the majority jump into hospitalist positions and opt for on‐the‐job training. While there is an early economic advantage to starting an attending position without delay, I believe that the skills learned during an additional year of dedicated training allow for a more meaningful work experience and, ultimately, a faster rise within the track of an academic hospitalist.

The tasks that residency programs and hospitals may give to CMRs provide fertile material for developing the skills necessary to become a productive academic hospitalist. I thrived on the multifaceted work of caring for a diverse group of patients, teaching different levels of learners, helping to manage various hospital systems, and better understanding the hospital as the sum of its parts. As noted above, this pre‐attending league gave me the exposure to more fully develop my academic hospitalist game in a supportive environment. A CMR year may be beneficial for residents entering any career in internal medicine; however, I believe it is most aptly suited as a stepping stone for future academic hospitalists. I strongly recommend that current residents interested in academic hospital medicine consider a CMR position, and encourage program directors to consider molding their inpatient CMR experiences to facilitate this. Moreover, unless fellowship training in hospital medicine becomes the norm, I propose that current academic hospitalists do more to closely court and usher these pretenders into our ranks.

References
  1. Varkey P,Karlapudi S,Rose S,Nelson R,Warner M.A systems approach for implementing practice‐based learning and improvement and systems‐based practice in graduate medical education.Acad Med.2009;84(3):335339.
  2. Berg DN,Huot SJ.Middle manager role of the chief medical resident: an organizational psychologist's perspective.J Gen Intern Med.2007;22(12):17711774.
  3. Harrison R,Hunter AJ,Sharpe B,Auerbach AD.Survey of US academic hospitalist leaders about mentorship and academic activities in hospitalist groups.J Hosp Med.2011;6:59.
References
  1. Varkey P,Karlapudi S,Rose S,Nelson R,Warner M.A systems approach for implementing practice‐based learning and improvement and systems‐based practice in graduate medical education.Acad Med.2009;84(3):335339.
  2. Berg DN,Huot SJ.Middle manager role of the chief medical resident: an organizational psychologist's perspective.J Gen Intern Med.2007;22(12):17711774.
  3. Harrison R,Hunter AJ,Sharpe B,Auerbach AD.Survey of US academic hospitalist leaders about mentorship and academic activities in hospitalist groups.J Hosp Med.2011;6:59.
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New Jersey Hospital Funds Care-Transitions “Coach”

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Robert Wood Johnson University Hospital in Hamilton, N.J., has partnered with Jewish Family and Children’s Services of Greater Mercer County to support care transitions for 350 chronically ill older patients. Patients will receive a transitions coach following hospital discharge for education, support, and encouragement to keep appointments with their physicians. This “coach” will develop a plan of care for the patient, making one hospital visit, one home visit, and three phone calls, says Joyce Schwarz, the hospital’s vice president of quality and the project’s director.

The hospital received a $300,000 grant under the New Jersey Health Initiative from the Robert Wood Johnson Foundation to use an evidence-based intervention to improve care transitions and reduce readmissions, acting as a bridge between hospital personnel and community physicians.

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Robert Wood Johnson University Hospital in Hamilton, N.J., has partnered with Jewish Family and Children’s Services of Greater Mercer County to support care transitions for 350 chronically ill older patients. Patients will receive a transitions coach following hospital discharge for education, support, and encouragement to keep appointments with their physicians. This “coach” will develop a plan of care for the patient, making one hospital visit, one home visit, and three phone calls, says Joyce Schwarz, the hospital’s vice president of quality and the project’s director.

The hospital received a $300,000 grant under the New Jersey Health Initiative from the Robert Wood Johnson Foundation to use an evidence-based intervention to improve care transitions and reduce readmissions, acting as a bridge between hospital personnel and community physicians.

Robert Wood Johnson University Hospital in Hamilton, N.J., has partnered with Jewish Family and Children’s Services of Greater Mercer County to support care transitions for 350 chronically ill older patients. Patients will receive a transitions coach following hospital discharge for education, support, and encouragement to keep appointments with their physicians. This “coach” will develop a plan of care for the patient, making one hospital visit, one home visit, and three phone calls, says Joyce Schwarz, the hospital’s vice president of quality and the project’s director.

The hospital received a $300,000 grant under the New Jersey Health Initiative from the Robert Wood Johnson Foundation to use an evidence-based intervention to improve care transitions and reduce readmissions, acting as a bridge between hospital personnel and community physicians.

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‘Smoothing’ Strategies in Children’s Hospitals Reduce Overcrowding

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A report published online May 24 in the Journal of Hospital Medicine found that smoothing inpatient occupancy and scheduled admissions in 39 children’s hospitals helped reduce midweek overcrowding. Evan S. Fieldston, MD, MBA, MSHP, of the University of Pennsylvania School of Medicine in Philadelphia and colleagues previously demonstrated occupancy variability and midweek crowding weekends (J Hosp Med. 2011;6:81-87). Strategies the team studied included controlling admissions when possible to achieve more level occupancy, with a mean of 2.6% of admissions moved to a different day of the week.

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A report published online May 24 in the Journal of Hospital Medicine found that smoothing inpatient occupancy and scheduled admissions in 39 children’s hospitals helped reduce midweek overcrowding. Evan S. Fieldston, MD, MBA, MSHP, of the University of Pennsylvania School of Medicine in Philadelphia and colleagues previously demonstrated occupancy variability and midweek crowding weekends (J Hosp Med. 2011;6:81-87). Strategies the team studied included controlling admissions when possible to achieve more level occupancy, with a mean of 2.6% of admissions moved to a different day of the week.

A report published online May 24 in the Journal of Hospital Medicine found that smoothing inpatient occupancy and scheduled admissions in 39 children’s hospitals helped reduce midweek overcrowding. Evan S. Fieldston, MD, MBA, MSHP, of the University of Pennsylvania School of Medicine in Philadelphia and colleagues previously demonstrated occupancy variability and midweek crowding weekends (J Hosp Med. 2011;6:81-87). Strategies the team studied included controlling admissions when possible to achieve more level occupancy, with a mean of 2.6% of admissions moved to a different day of the week.

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By the numbers - 0.5%

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The reduction President Obama has proposed to a formula used by the Independent Payment Advisory Board (IPAB), created last year by the Affordable Care Act to cut Medicare costs without affecting quality. The formula IPAB currently uses as a baseline for growth estimates is GDP per capita, plus 1%. The president has proposed to reduce that figure to GDP plus 0.5%. The lower threshold means IPAB will have deeper cuts to make. Accordingly, hospitalists are watching the proposal, as it could lower federal reimbursements as IPAB looks for ways to cut Medicare spending

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The reduction President Obama has proposed to a formula used by the Independent Payment Advisory Board (IPAB), created last year by the Affordable Care Act to cut Medicare costs without affecting quality. The formula IPAB currently uses as a baseline for growth estimates is GDP per capita, plus 1%. The president has proposed to reduce that figure to GDP plus 0.5%. The lower threshold means IPAB will have deeper cuts to make. Accordingly, hospitalists are watching the proposal, as it could lower federal reimbursements as IPAB looks for ways to cut Medicare spending

The reduction President Obama has proposed to a formula used by the Independent Payment Advisory Board (IPAB), created last year by the Affordable Care Act to cut Medicare costs without affecting quality. The formula IPAB currently uses as a baseline for growth estimates is GDP per capita, plus 1%. The president has proposed to reduce that figure to GDP plus 0.5%. The lower threshold means IPAB will have deeper cuts to make. Accordingly, hospitalists are watching the proposal, as it could lower federal reimbursements as IPAB looks for ways to cut Medicare spending

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“Teachback” Reduces Readmissions for CHF Patients

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A sking “teachback” questions to hospitalized chronic heart failure (CHF) patients at Lehigh Valley Health Network in Allentown, Pa., helps them better understand their condition, treatment, and post-discharge care—thereby impacting readmissions. In an abstract presented at HM11 in Dallas in May, CHF patients who received teachback had a 7.3% readmission rate in the first three months of 2011, compared with 9.7% for those who did not.

Teachback, according to hospitalist and lead author Michael Pistoria, DO, FACP, SFHM, represents “humble inquiry—the simple need and ability to ask patients: ‘Can you tell me what I said to you?’” The provider then needs to listen to the reply and confirm the understanding, he adds.

Lehigh Valley convened a multidisciplinary quality team to study transitions of care, with a subgroup focused on patient-caregiver education, Dr. Pistoria explains. “The first thing the patient-family caregiver education team looked at was how to identify the key learner,” he says. “We had assumed it was the patient, but that’s not always the person who needs to learn about managing the patient’s condition.”

The subgroup then developed a curriculum of questions to be asked sequentially over three days to test patients and their caregivers’ understanding of heart failure and need for reinforcement. These questions, drawing upon educational resources already used within the system, assess the key learner’s knowledge, attitudes about healthy behaviors, and how to incorporate those behaviors into effective self-care.

The teachback system was tested on a few patients, then disseminated to 1,400 nurses through Lehigh Valley’s professional e-learning network using a brief training video. “We learned that doing a good job of staff teaching is not enough, unless we go back and periodically revisit the issues and audit their performance,” Dr. Pistoria says. “In our system, starting with our nurses was the right approach. It’s important for everybody to take ownership of the initiative. It’s also important, from unit to unit, to ask the questions the same way.”

Subsequent analysis shows continued reductions in readmissions, Dr. Pistoria says. Lehigh Valley’s next targets for teachback are community-acquired pneumonia, myocardial infarction, hypoglycemia, COPD, and anti-coagulant treatment.

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A sking “teachback” questions to hospitalized chronic heart failure (CHF) patients at Lehigh Valley Health Network in Allentown, Pa., helps them better understand their condition, treatment, and post-discharge care—thereby impacting readmissions. In an abstract presented at HM11 in Dallas in May, CHF patients who received teachback had a 7.3% readmission rate in the first three months of 2011, compared with 9.7% for those who did not.

Teachback, according to hospitalist and lead author Michael Pistoria, DO, FACP, SFHM, represents “humble inquiry—the simple need and ability to ask patients: ‘Can you tell me what I said to you?’” The provider then needs to listen to the reply and confirm the understanding, he adds.

Lehigh Valley convened a multidisciplinary quality team to study transitions of care, with a subgroup focused on patient-caregiver education, Dr. Pistoria explains. “The first thing the patient-family caregiver education team looked at was how to identify the key learner,” he says. “We had assumed it was the patient, but that’s not always the person who needs to learn about managing the patient’s condition.”

The subgroup then developed a curriculum of questions to be asked sequentially over three days to test patients and their caregivers’ understanding of heart failure and need for reinforcement. These questions, drawing upon educational resources already used within the system, assess the key learner’s knowledge, attitudes about healthy behaviors, and how to incorporate those behaviors into effective self-care.

The teachback system was tested on a few patients, then disseminated to 1,400 nurses through Lehigh Valley’s professional e-learning network using a brief training video. “We learned that doing a good job of staff teaching is not enough, unless we go back and periodically revisit the issues and audit their performance,” Dr. Pistoria says. “In our system, starting with our nurses was the right approach. It’s important for everybody to take ownership of the initiative. It’s also important, from unit to unit, to ask the questions the same way.”

Subsequent analysis shows continued reductions in readmissions, Dr. Pistoria says. Lehigh Valley’s next targets for teachback are community-acquired pneumonia, myocardial infarction, hypoglycemia, COPD, and anti-coagulant treatment.

A sking “teachback” questions to hospitalized chronic heart failure (CHF) patients at Lehigh Valley Health Network in Allentown, Pa., helps them better understand their condition, treatment, and post-discharge care—thereby impacting readmissions. In an abstract presented at HM11 in Dallas in May, CHF patients who received teachback had a 7.3% readmission rate in the first three months of 2011, compared with 9.7% for those who did not.

Teachback, according to hospitalist and lead author Michael Pistoria, DO, FACP, SFHM, represents “humble inquiry—the simple need and ability to ask patients: ‘Can you tell me what I said to you?’” The provider then needs to listen to the reply and confirm the understanding, he adds.

Lehigh Valley convened a multidisciplinary quality team to study transitions of care, with a subgroup focused on patient-caregiver education, Dr. Pistoria explains. “The first thing the patient-family caregiver education team looked at was how to identify the key learner,” he says. “We had assumed it was the patient, but that’s not always the person who needs to learn about managing the patient’s condition.”

The subgroup then developed a curriculum of questions to be asked sequentially over three days to test patients and their caregivers’ understanding of heart failure and need for reinforcement. These questions, drawing upon educational resources already used within the system, assess the key learner’s knowledge, attitudes about healthy behaviors, and how to incorporate those behaviors into effective self-care.

The teachback system was tested on a few patients, then disseminated to 1,400 nurses through Lehigh Valley’s professional e-learning network using a brief training video. “We learned that doing a good job of staff teaching is not enough, unless we go back and periodically revisit the issues and audit their performance,” Dr. Pistoria says. “In our system, starting with our nurses was the right approach. It’s important for everybody to take ownership of the initiative. It’s also important, from unit to unit, to ask the questions the same way.”

Subsequent analysis shows continued reductions in readmissions, Dr. Pistoria says. Lehigh Valley’s next targets for teachback are community-acquired pneumonia, myocardial infarction, hypoglycemia, COPD, and anti-coagulant treatment.

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