Anesthesiologists typically initiate an assessment in the immediate preoperative period, focused on management of the airway, physiologic parameters, and choice of anesthetic. Given the growing complexity of medical issues in the surgical patient, the preoperative assessment may need to be initiated weeks to months prior to surgery. Early evaluation allows time to implement required interventions, optimize medical conditions, adjust medications, and collaborate with the surgical team.

Most studies of Preoperative clinics are in the Anesthesiology literature.1 Anesthesia‐run Preoperative clinics have demonstrated a reduction in surgical cancellations and length of stay (LOS).2 Auerbach and colleagues found medical consultation to have inconsistent effects on quality of care in surgical patients, but consultations occurred, at the earliest, 1 day prior to surgery.3 A randomized trial, performed at the Pittsburgh Veterans Administration (VA) medical center using an outpatient Internal Medicine Preoperative clinic, demonstrated a shortening of preoperative LOS but no change in total LOS, and increased use of consultants. However, there were reduced numbers of unnecessary admissions, defined as patients who were discharged without having had surgery.4 An analysis of a population‐based administrative database found that voluntary preoperative consultations were associated with a significant, albeit small, increase in mortality. Although this study used a matched cohort, the unmatched cohort that underwent consultation was higher risk; also, selection bias was possible, as the reasons for initial consultation were unknown.5

Historically, the Preoperative clinic at VA Greater Los Angeles Healthcare System (VAGLAHS) was supervised by the Department of Anesthesiology. In July 2004, the Preoperative clinic was restructured with Hospitalist oversight. The Anesthesia staff continued to evaluate all surgical patients, but did so only on the day of surgery, and after the patient was deemed an acceptable risk by the Preoperative clinic.

We undertook this study to measure the institutional impact of the addition of a Hospitalist‐run Preoperative clinic to our standard practice. The VA is an ideal setting, given the closed system with reliable longitudinal data. The VA electronic medical record also allows for comprehensive calculations of clinical covariants and outcomes.

MATERIALS AND METHODS

RESULTS

Table 1 describes the demographics and clinical characteristics of the patients evaluated in the Preoperative clinic. Number of surgeries performed in Periods A and B were 3568 and 3337, respectively, with an average of 1.3 surgeries per patient for both periods. The most common surgical specialties were Ophthalmology, Orthopedics, Urology, and General Surgery. The average ages of patients in Periods A and B were 63.9 and 61.4 years, respectively (P < 0.0001). The patients were predominantly male. ASA classifications were similar in the 2 periods, with over 60% of patients having an ASA score of 3 or higher.

Table 2 presents the selected preoperative resource utilization. Less than 3% of patients referred to the Preoperative clinic were referred for Cardiology consultation during both time periods. However, during Period A, some patients required multiple Cardiology referrals resulting in 85 referrals in Period A and 64 referrals in Period B. In contrast, Preoperative clinic providers ordered more cardiac studies in Period B than in Period A (P = 0.012). There was a significant increase in the number of patients on perioperative beta blockers, with 26% in Period A and 33% in Period B (P < 0.0001). Although there was no significant difference in the number of same‐day surgical cancellations between the 2 periods, there was a trend towards a reduction of cancellations for medically avoidable reasons, 34 (8.5%) and 18 (4.9%) cases during Periods A and B, respectively (P = 0.065).

Table 3 describes the clinical characteristics, inpatient LOS, and inpatient mortality for the surgical inpatients assessed in the Preoperative clinic. There were 1101 patients with 1200 inpatient surgeries in Period A, and 1126 patients with 1245 inpatient surgeries in Period B. The mean ages were 63.3 and 61.4 years in Periods A and B, respectively (P = 0.0004). More than 90% of patients were male. Over 62% of patients had ASA scores of 3 or higher in both periods. Both mean and median LOS was reduced in Period B. Results from the mixed‐effects regression model indicated no age and gender effects. ASA classification was significantly associated with LOS (P < 0.0001). There were reductions in LOS from Period A to Period B across all ASA classifications, however, the levels of reduction were different among them (ie, significant interaction effect, P = 0.0005). Patients who were ASA 3 or higher had a significantly shorter LOS in Period B as compared to those in Period A (P < 0.0001).

The LOS on the Cardiothoracic services was also evaluated. No significant difference in LOS was observed between the 2 periods (average LOS of 18 days) after adjusting for the patients' age and ASA score.

Inpatient mortality was reduced in Period B, from 14 cases (1.27%) to 4 cases (0.36%) (P = 0.0158). No patients who were ASA 2 or less died. Deaths in each period were evenly split between ASA categories 3 and 4 (Table 3). Subgroup analysis on inpatient deaths showed no age effect, but a significant period effect (odds ratio [OR] = 3.13, 95% confidence interval [CI]: 1.019.73 for Periods A vs B; P = 0.0488) and ASA status effect (OR = 0.06, 95% CI: 0.020.16 for ASA severe vs life‐threatening; P < 0.0001).

DISCUSSION

The addition of a Hospitalist‐run, medical Preoperative clinic was associated with more perioperative beta blocker use, shortened LOS, and lower mortality rates for our veteran patients undergoing noncardiac surgery. Such LOS reduction was not apparent in our internal control of cardiothoracic surgery patients or in the VA National Surgical Quality Improvement Program (NSQIP), a national representative sample of a similar patient population. While median unadjusted LOS in the VA NSQIP did not change over the same time periods, surgical mortality rates decreased, but by a smaller magnitude (15%) than seen in our study. While mortality in our study was reduced, the absolute numbers are relatively small. However, a subgroup analysis accounting for age and ASA score demonstrated a reduction in mortality.

As multiple structure and process changes were made in the Preoperative program, it is not definitively known which specific factor or factors could have affected inpatient surgical care. The Preoperative clinic evaluation was a one‐time consult, but included recommendations for perioperative management, including medication adjustments and infrequent suggestions for perioperative consultation. The decision to follow such recommendations was voluntary on the part of the surgical team. Alternatively, preoperative optimization may have played a role. By performing a multisystem evaluation with evidence‐based protocols, we possibly identified patients that were at increased risk of perioperative harm, and were able to intervene or recommend deferral of the procedure. This could have resulted in better surgical candidate selection with fewer postoperative complications, especially among patients with significant medical comorbidities.

Better patient selection is also suggested by a trend toward fewer same‐day cancellations for medically avoidable reasons during Period B. The distinction between medical versus patient‐related causes and avoidable versus unavoidable causes may be imprecise; however, the same Anesthesia staff assigned the categories over both periods and therefore any possible inconsistencies should have averaged out.

Increased usage of perioperative beta blockers may also have contributed to reduced mortality rates. We anticipated that more patients in Period B would be placed on perioperative beta blockers, given the guidelines in place at the time. More recently, the evidence for perioperative beta blockade has been further refined,16, 17 but during study Periods A and B, it was considered best practice for wider patient populations.

Fewer repeat referrals to Cardiology clinic and more cardiac testing were ordered by the Preoperative clinic providers during Period B. Ordering cardiac studies from Preoperative clinic and referring only when guideline‐driven could have streamlined the evaluation process and prevented the need for repeat referrals. We expect the number of stress tests and Cardiology consultations to have decreased even more in recent years as the 2007 ACC/AHA guidelines further emphasize medical optimization and de‐emphasize cardiac testing and prophylactic revascularization prior to surgery.18

Our results suggest that similar healthcare systems may benefit from adding medical expertise to their preoperative clinical operations. As the LOS reduction was most noticeable in patients with higher ASA scores, the largest impact would likely be with healthcare environments with medically complex patients and variable access to primary care. The shortage of primary care physicians and the increase in chronic disease burden in the US population may cause more patients to present to a surgeon in a nonoptimized condition. Arguably, such clinics could be supervised by any discipline that is familiar with the perioperative literature, chronic disease management, and postoperative inpatient care. Other options include clinics in which Anesthesiologists jointly collaborate with Hospitalists19 or General Internists with expertise in perioperative management.

Our study has many limitations. The VA has a largely male population and an electronic medical record, and thus results are not generalizable. Patients were younger in Period B than in Period A; however, the 2‐ to 3‐year difference might not be clinically significant, and the standard deviation was wide in both groups. This study is a retrospective observational study, and thus we cannot identify the specific processes that could have lead to any associated outcomes. There was no ideal contemporaneous control group, but examination of trends in cardiothoracic surgery at our institution and the national VA database does not reveal changes of this magnitude. Unforeseen biases could have resulted in upcoding of ASA scores by the mid‐level providers. Beta blocker usage was determined by patients prescribed beta blockers perioperatively, and did not exclude those on the medication prior to presentation. However, the significant increase in usage in Period B points to an increase in prescriptions originating from the Preoperative clinic. We do not have a breakdown of postoperative days in the intensive care unit (ICU) or ward settings, or the readmission rates. Thus, a true cost‐effectiveness analysis cannot be done. However, the reduction in postoperative LOS and decline in same‐day cancellations suggests that our institution benefited to some degree. Since the mid‐level providers were present prior to the change from Anesthesia to Hospitalist leadership, the only cost of the intervention was the hiring of a Hospitalist. However, the change freed an Anesthesiologist to work in the operating room or procedure suite. We do not have precise data regarding the number of surgeries delayed or canceled by the Preoperative clinic, but surgical workload was similar between both periods. Hopefully future studies will include richer data to minimize study limitations.

CONCLUSION

The addition of a Hospitalist‐run, medical Preoperative clinic was associated with improvements in perioperative processes and outcomes. Postoperative LOS was reduced in the sickest patients, as was inpatient mortality. Perioperative beta blocker use was increased. Adding Hospitalist expertise to preoperative clinical operations may be a viable model to improve perioperative care.

Anesthesiologists typically initiate an assessment in the immediate preoperative period, focused on management of the airway, physiologic parameters, and choice of anesthetic. Given the growing complexity of medical issues in the surgical patient, the preoperative assessment may need to be initiated weeks to months prior to surgery. Early evaluation allows time to implement required interventions, optimize medical conditions, adjust medications, and collaborate with the surgical team.

Most studies of Preoperative clinics are in the Anesthesiology literature.1 Anesthesia‐run Preoperative clinics have demonstrated a reduction in surgical cancellations and length of stay (LOS).2 Auerbach and colleagues found medical consultation to have inconsistent effects on quality of care in surgical patients, but consultations occurred, at the earliest, 1 day prior to surgery.3 A randomized trial, performed at the Pittsburgh Veterans Administration (VA) medical center using an outpatient Internal Medicine Preoperative clinic, demonstrated a shortening of preoperative LOS but no change in total LOS, and increased use of consultants. However, there were reduced numbers of unnecessary admissions, defined as patients who were discharged without having had surgery.4 An analysis of a population‐based administrative database found that voluntary preoperative consultations were associated with a significant, albeit small, increase in mortality. Although this study used a matched cohort, the unmatched cohort that underwent consultation was higher risk; also, selection bias was possible, as the reasons for initial consultation were unknown.5

Historically, the Preoperative clinic at VA Greater Los Angeles Healthcare System (VAGLAHS) was supervised by the Department of Anesthesiology. In July 2004, the Preoperative clinic was restructured with Hospitalist oversight. The Anesthesia staff continued to evaluate all surgical patients, but did so only on the day of surgery, and after the patient was deemed an acceptable risk by the Preoperative clinic.

We undertook this study to measure the institutional impact of the addition of a Hospitalist‐run Preoperative clinic to our standard practice. The VA is an ideal setting, given the closed system with reliable longitudinal data. The VA electronic medical record also allows for comprehensive calculations of clinical covariants and outcomes.

MATERIALS AND METHODS

RESULTS

Table 1 describes the demographics and clinical characteristics of the patients evaluated in the Preoperative clinic. Number of surgeries performed in Periods A and B were 3568 and 3337, respectively, with an average of 1.3 surgeries per patient for both periods. The most common surgical specialties were Ophthalmology, Orthopedics, Urology, and General Surgery. The average ages of patients in Periods A and B were 63.9 and 61.4 years, respectively (P < 0.0001). The patients were predominantly male. ASA classifications were similar in the 2 periods, with over 60% of patients having an ASA score of 3 or higher.

Table 2 presents the selected preoperative resource utilization. Less than 3% of patients referred to the Preoperative clinic were referred for Cardiology consultation during both time periods. However, during Period A, some patients required multiple Cardiology referrals resulting in 85 referrals in Period A and 64 referrals in Period B. In contrast, Preoperative clinic providers ordered more cardiac studies in Period B than in Period A (P = 0.012). There was a significant increase in the number of patients on perioperative beta blockers, with 26% in Period A and 33% in Period B (P < 0.0001). Although there was no significant difference in the number of same‐day surgical cancellations between the 2 periods, there was a trend towards a reduction of cancellations for medically avoidable reasons, 34 (8.5%) and 18 (4.9%) cases during Periods A and B, respectively (P = 0.065).

Table 3 describes the clinical characteristics, inpatient LOS, and inpatient mortality for the surgical inpatients assessed in the Preoperative clinic. There were 1101 patients with 1200 inpatient surgeries in Period A, and 1126 patients with 1245 inpatient surgeries in Period B. The mean ages were 63.3 and 61.4 years in Periods A and B, respectively (P = 0.0004). More than 90% of patients were male. Over 62% of patients had ASA scores of 3 or higher in both periods. Both mean and median LOS was reduced in Period B. Results from the mixed‐effects regression model indicated no age and gender effects. ASA classification was significantly associated with LOS (P < 0.0001). There were reductions in LOS from Period A to Period B across all ASA classifications, however, the levels of reduction were different among them (ie, significant interaction effect, P = 0.0005). Patients who were ASA 3 or higher had a significantly shorter LOS in Period B as compared to those in Period A (P < 0.0001).

The LOS on the Cardiothoracic services was also evaluated. No significant difference in LOS was observed between the 2 periods (average LOS of 18 days) after adjusting for the patients' age and ASA score.

Inpatient mortality was reduced in Period B, from 14 cases (1.27%) to 4 cases (0.36%) (P = 0.0158). No patients who were ASA 2 or less died. Deaths in each period were evenly split between ASA categories 3 and 4 (Table 3). Subgroup analysis on inpatient deaths showed no age effect, but a significant period effect (odds ratio [OR] = 3.13, 95% confidence interval [CI]: 1.019.73 for Periods A vs B; P = 0.0488) and ASA status effect (OR = 0.06, 95% CI: 0.020.16 for ASA severe vs life‐threatening; P < 0.0001).

DISCUSSION

The addition of a Hospitalist‐run, medical Preoperative clinic was associated with more perioperative beta blocker use, shortened LOS, and lower mortality rates for our veteran patients undergoing noncardiac surgery. Such LOS reduction was not apparent in our internal control of cardiothoracic surgery patients or in the VA National Surgical Quality Improvement Program (NSQIP), a national representative sample of a similar patient population. While median unadjusted LOS in the VA NSQIP did not change over the same time periods, surgical mortality rates decreased, but by a smaller magnitude (15%) than seen in our study. While mortality in our study was reduced, the absolute numbers are relatively small. However, a subgroup analysis accounting for age and ASA score demonstrated a reduction in mortality.

As multiple structure and process changes were made in the Preoperative program, it is not definitively known which specific factor or factors could have affected inpatient surgical care. The Preoperative clinic evaluation was a one‐time consult, but included recommendations for perioperative management, including medication adjustments and infrequent suggestions for perioperative consultation. The decision to follow such recommendations was voluntary on the part of the surgical team. Alternatively, preoperative optimization may have played a role. By performing a multisystem evaluation with evidence‐based protocols, we possibly identified patients that were at increased risk of perioperative harm, and were able to intervene or recommend deferral of the procedure. This could have resulted in better surgical candidate selection with fewer postoperative complications, especially among patients with significant medical comorbidities.

Better patient selection is also suggested by a trend toward fewer same‐day cancellations for medically avoidable reasons during Period B. The distinction between medical versus patient‐related causes and avoidable versus unavoidable causes may be imprecise; however, the same Anesthesia staff assigned the categories over both periods and therefore any possible inconsistencies should have averaged out.

Increased usage of perioperative beta blockers may also have contributed to reduced mortality rates. We anticipated that more patients in Period B would be placed on perioperative beta blockers, given the guidelines in place at the time. More recently, the evidence for perioperative beta blockade has been further refined,16, 17 but during study Periods A and B, it was considered best practice for wider patient populations.

Fewer repeat referrals to Cardiology clinic and more cardiac testing were ordered by the Preoperative clinic providers during Period B. Ordering cardiac studies from Preoperative clinic and referring only when guideline‐driven could have streamlined the evaluation process and prevented the need for repeat referrals. We expect the number of stress tests and Cardiology consultations to have decreased even more in recent years as the 2007 ACC/AHA guidelines further emphasize medical optimization and de‐emphasize cardiac testing and prophylactic revascularization prior to surgery.18

Our results suggest that similar healthcare systems may benefit from adding medical expertise to their preoperative clinical operations. As the LOS reduction was most noticeable in patients with higher ASA scores, the largest impact would likely be with healthcare environments with medically complex patients and variable access to primary care. The shortage of primary care physicians and the increase in chronic disease burden in the US population may cause more patients to present to a surgeon in a nonoptimized condition. Arguably, such clinics could be supervised by any discipline that is familiar with the perioperative literature, chronic disease management, and postoperative inpatient care. Other options include clinics in which Anesthesiologists jointly collaborate with Hospitalists19 or General Internists with expertise in perioperative management.

Our study has many limitations. The VA has a largely male population and an electronic medical record, and thus results are not generalizable. Patients were younger in Period B than in Period A; however, the 2‐ to 3‐year difference might not be clinically significant, and the standard deviation was wide in both groups. This study is a retrospective observational study, and thus we cannot identify the specific processes that could have lead to any associated outcomes. There was no ideal contemporaneous control group, but examination of trends in cardiothoracic surgery at our institution and the national VA database does not reveal changes of this magnitude. Unforeseen biases could have resulted in upcoding of ASA scores by the mid‐level providers. Beta blocker usage was determined by patients prescribed beta blockers perioperatively, and did not exclude those on the medication prior to presentation. However, the significant increase in usage in Period B points to an increase in prescriptions originating from the Preoperative clinic. We do not have a breakdown of postoperative days in the intensive care unit (ICU) or ward settings, or the readmission rates. Thus, a true cost‐effectiveness analysis cannot be done. However, the reduction in postoperative LOS and decline in same‐day cancellations suggests that our institution benefited to some degree. Since the mid‐level providers were present prior to the change from Anesthesia to Hospitalist leadership, the only cost of the intervention was the hiring of a Hospitalist. However, the change freed an Anesthesiologist to work in the operating room or procedure suite. We do not have precise data regarding the number of surgeries delayed or canceled by the Preoperative clinic, but surgical workload was similar between both periods. Hopefully future studies will include richer data to minimize study limitations.

CONCLUSION

The addition of a Hospitalist‐run, medical Preoperative clinic was associated with improvements in perioperative processes and outcomes. Postoperative LOS was reduced in the sickest patients, as was inpatient mortality. Perioperative beta blocker use was increased. Adding Hospitalist expertise to preoperative clinical operations may be a viable model to improve perioperative care.

Anesthesiologists typically initiate an assessment in the immediate preoperative period, focused on management of the airway, physiologic parameters, and choice of anesthetic. Given the growing complexity of medical issues in the surgical patient, the preoperative assessment may need to be initiated weeks to months prior to surgery. Early evaluation allows time to implement required interventions, optimize medical conditions, adjust medications, and collaborate with the surgical team.

Most studies of Preoperative clinics are in the Anesthesiology literature.1 Anesthesia‐run Preoperative clinics have demonstrated a reduction in surgical cancellations and length of stay (LOS).2 Auerbach and colleagues found medical consultation to have inconsistent effects on quality of care in surgical patients, but consultations occurred, at the earliest, 1 day prior to surgery.3 A randomized trial, performed at the Pittsburgh Veterans Administration (VA) medical center using an outpatient Internal Medicine Preoperative clinic, demonstrated a shortening of preoperative LOS but no change in total LOS, and increased use of consultants. However, there were reduced numbers of unnecessary admissions, defined as patients who were discharged without having had surgery.4 An analysis of a population‐based administrative database found that voluntary preoperative consultations were associated with a significant, albeit small, increase in mortality. Although this study used a matched cohort, the unmatched cohort that underwent consultation was higher risk; also, selection bias was possible, as the reasons for initial consultation were unknown.5

Historically, the Preoperative clinic at VA Greater Los Angeles Healthcare System (VAGLAHS) was supervised by the Department of Anesthesiology. In July 2004, the Preoperative clinic was restructured with Hospitalist oversight. The Anesthesia staff continued to evaluate all surgical patients, but did so only on the day of surgery, and after the patient was deemed an acceptable risk by the Preoperative clinic.

We undertook this study to measure the institutional impact of the addition of a Hospitalist‐run Preoperative clinic to our standard practice. The VA is an ideal setting, given the closed system with reliable longitudinal data. The VA electronic medical record also allows for comprehensive calculations of clinical covariants and outcomes.

MATERIALS AND METHODS

RESULTS

Table 1 describes the demographics and clinical characteristics of the patients evaluated in the Preoperative clinic. Number of surgeries performed in Periods A and B were 3568 and 3337, respectively, with an average of 1.3 surgeries per patient for both periods. The most common surgical specialties were Ophthalmology, Orthopedics, Urology, and General Surgery. The average ages of patients in Periods A and B were 63.9 and 61.4 years, respectively (P < 0.0001). The patients were predominantly male. ASA classifications were similar in the 2 periods, with over 60% of patients having an ASA score of 3 or higher.

Table 2 presents the selected preoperative resource utilization. Less than 3% of patients referred to the Preoperative clinic were referred for Cardiology consultation during both time periods. However, during Period A, some patients required multiple Cardiology referrals resulting in 85 referrals in Period A and 64 referrals in Period B. In contrast, Preoperative clinic providers ordered more cardiac studies in Period B than in Period A (P = 0.012). There was a significant increase in the number of patients on perioperative beta blockers, with 26% in Period A and 33% in Period B (P < 0.0001). Although there was no significant difference in the number of same‐day surgical cancellations between the 2 periods, there was a trend towards a reduction of cancellations for medically avoidable reasons, 34 (8.5%) and 18 (4.9%) cases during Periods A and B, respectively (P = 0.065).

Table 3 describes the clinical characteristics, inpatient LOS, and inpatient mortality for the surgical inpatients assessed in the Preoperative clinic. There were 1101 patients with 1200 inpatient surgeries in Period A, and 1126 patients with 1245 inpatient surgeries in Period B. The mean ages were 63.3 and 61.4 years in Periods A and B, respectively (P = 0.0004). More than 90% of patients were male. Over 62% of patients had ASA scores of 3 or higher in both periods. Both mean and median LOS was reduced in Period B. Results from the mixed‐effects regression model indicated no age and gender effects. ASA classification was significantly associated with LOS (P < 0.0001). There were reductions in LOS from Period A to Period B across all ASA classifications, however, the levels of reduction were different among them (ie, significant interaction effect, P = 0.0005). Patients who were ASA 3 or higher had a significantly shorter LOS in Period B as compared to those in Period A (P < 0.0001).

The LOS on the Cardiothoracic services was also evaluated. No significant difference in LOS was observed between the 2 periods (average LOS of 18 days) after adjusting for the patients' age and ASA score.

Inpatient mortality was reduced in Period B, from 14 cases (1.27%) to 4 cases (0.36%) (P = 0.0158). No patients who were ASA 2 or less died. Deaths in each period were evenly split between ASA categories 3 and 4 (Table 3). Subgroup analysis on inpatient deaths showed no age effect, but a significant period effect (odds ratio [OR] = 3.13, 95% confidence interval [CI]: 1.019.73 for Periods A vs B; P = 0.0488) and ASA status effect (OR = 0.06, 95% CI: 0.020.16 for ASA severe vs life‐threatening; P < 0.0001).

DISCUSSION

The addition of a Hospitalist‐run, medical Preoperative clinic was associated with more perioperative beta blocker use, shortened LOS, and lower mortality rates for our veteran patients undergoing noncardiac surgery. Such LOS reduction was not apparent in our internal control of cardiothoracic surgery patients or in the VA National Surgical Quality Improvement Program (NSQIP), a national representative sample of a similar patient population. While median unadjusted LOS in the VA NSQIP did not change over the same time periods, surgical mortality rates decreased, but by a smaller magnitude (15%) than seen in our study. While mortality in our study was reduced, the absolute numbers are relatively small. However, a subgroup analysis accounting for age and ASA score demonstrated a reduction in mortality.

As multiple structure and process changes were made in the Preoperative program, it is not definitively known which specific factor or factors could have affected inpatient surgical care. The Preoperative clinic evaluation was a one‐time consult, but included recommendations for perioperative management, including medication adjustments and infrequent suggestions for perioperative consultation. The decision to follow such recommendations was voluntary on the part of the surgical team. Alternatively, preoperative optimization may have played a role. By performing a multisystem evaluation with evidence‐based protocols, we possibly identified patients that were at increased risk of perioperative harm, and were able to intervene or recommend deferral of the procedure. This could have resulted in better surgical candidate selection with fewer postoperative complications, especially among patients with significant medical comorbidities.

Better patient selection is also suggested by a trend toward fewer same‐day cancellations for medically avoidable reasons during Period B. The distinction between medical versus patient‐related causes and avoidable versus unavoidable causes may be imprecise; however, the same Anesthesia staff assigned the categories over both periods and therefore any possible inconsistencies should have averaged out.

Increased usage of perioperative beta blockers may also have contributed to reduced mortality rates. We anticipated that more patients in Period B would be placed on perioperative beta blockers, given the guidelines in place at the time. More recently, the evidence for perioperative beta blockade has been further refined,16, 17 but during study Periods A and B, it was considered best practice for wider patient populations.

Fewer repeat referrals to Cardiology clinic and more cardiac testing were ordered by the Preoperative clinic providers during Period B. Ordering cardiac studies from Preoperative clinic and referring only when guideline‐driven could have streamlined the evaluation process and prevented the need for repeat referrals. We expect the number of stress tests and Cardiology consultations to have decreased even more in recent years as the 2007 ACC/AHA guidelines further emphasize medical optimization and de‐emphasize cardiac testing and prophylactic revascularization prior to surgery.18

Our results suggest that similar healthcare systems may benefit from adding medical expertise to their preoperative clinical operations. As the LOS reduction was most noticeable in patients with higher ASA scores, the largest impact would likely be with healthcare environments with medically complex patients and variable access to primary care. The shortage of primary care physicians and the increase in chronic disease burden in the US population may cause more patients to present to a surgeon in a nonoptimized condition. Arguably, such clinics could be supervised by any discipline that is familiar with the perioperative literature, chronic disease management, and postoperative inpatient care. Other options include clinics in which Anesthesiologists jointly collaborate with Hospitalists19 or General Internists with expertise in perioperative management.

Our study has many limitations. The VA has a largely male population and an electronic medical record, and thus results are not generalizable. Patients were younger in Period B than in Period A; however, the 2‐ to 3‐year difference might not be clinically significant, and the standard deviation was wide in both groups. This study is a retrospective observational study, and thus we cannot identify the specific processes that could have lead to any associated outcomes. There was no ideal contemporaneous control group, but examination of trends in cardiothoracic surgery at our institution and the national VA database does not reveal changes of this magnitude. Unforeseen biases could have resulted in upcoding of ASA scores by the mid‐level providers. Beta blocker usage was determined by patients prescribed beta blockers perioperatively, and did not exclude those on the medication prior to presentation. However, the significant increase in usage in Period B points to an increase in prescriptions originating from the Preoperative clinic. We do not have a breakdown of postoperative days in the intensive care unit (ICU) or ward settings, or the readmission rates. Thus, a true cost‐effectiveness analysis cannot be done. However, the reduction in postoperative LOS and decline in same‐day cancellations suggests that our institution benefited to some degree. Since the mid‐level providers were present prior to the change from Anesthesia to Hospitalist leadership, the only cost of the intervention was the hiring of a Hospitalist. However, the change freed an Anesthesiologist to work in the operating room or procedure suite. We do not have precise data regarding the number of surgeries delayed or canceled by the Preoperative clinic, but surgical workload was similar between both periods. Hopefully future studies will include richer data to minimize study limitations.

CONCLUSION

The addition of a Hospitalist‐run, medical Preoperative clinic was associated with improvements in perioperative processes and outcomes. Postoperative LOS was reduced in the sickest patients, as was inpatient mortality. Perioperative beta blocker use was increased. Adding Hospitalist expertise to preoperative clinical operations may be a viable model to improve perioperative care.

Perioperative myocardial infarction (PMI) often remains unrecognized with higher mortality in the aged.13 Perioperative ischemic symptoms are often masked by analgesia, sedation, and transient and subtle electrocardiographic (ECG) changes. Postoperative troponin measurement is not routinely done for PMI diagnosis. Hip fracture surgery is the most common non‐cardiac surgical procedure in the elderly, with limited data on clinical presentation of PMI.46 Moreover, the elderly are significantly underrepresented in clinical studies.7 We therefore examined the clinical presentation of PMI and its outcomes among elderly patients admitted for hip fracture repair.

METHODS

RESULTS

In the cohort of 1212 with hip fracture surgeries, 167 (13.8%) cases of PMI occurred in the first 7 days, of which 153 (92%) occurred within the first 48 hours. A total of 334 controls were matched with 167 cases of PMI. Table 1 summarizes the demographic characteristics of the study participants. Of the patients with PMI, 25.2% experienced symptoms of ischemia; 7% reported chest pain, and 12% reported dyspnea. Only 22.8% of patients with PMI had ECG changes consistent with ischemia. ST elevation MI was present in 7.2% patients. PMI patients had a lower mean hemoglobin compared to the patients without PMI (8.9 mg/dL vs 9.4 mg/dL, P < 0.001). Median length of stay (LOS) in the hospital was higher among patients who experienced PMI (11.6 vs 7.4 days, P < 0.001). Overall in‐hospital mortality was 5.6%. There were 24 deaths (14.4%) in the PMI group compared to 4 (1.2%) in‐hospital deaths in patients without PMI (P < 0.001). A total of 473 (94%) patients survived to discharge. At 30‐day follow‐up, there were 29 (17.4%) deaths in the PMI group and 14 (4.2%) deaths in non‐PMI group. During the follow‐up for 1 year, there were 143 (29%) deaths: PMI 66 (39.5%) and 77 (23%) non‐PMI group (P < 0.01).

Table 2 describes the risk factors associated with PMI in‐hospital, 30‐day, and 1‐year mortality. Risk factors for PMI were coronary artery disease (CAD) (odds ratio [OR], 3.5; confidence interval [CI], 2.25.6), and serum creatinine >2 mg/dL (OR, 2.4; CI, 1.34.4). Risk factors for in‐hospital mortality were age 8589 (OR, 5.3; CI, 1.617.7), age 90 (OR, 8.9; CI, 2.630.8), PMI (OR 15.1; CI, 4.648.8), male gender (OR 5.8; CI, 2.215.2), dyspnea (OR 5.4; CI, 1.816.9), and hemoglobin <8.0 gm/dL (OR, 3.5; CI, 1.29.9). PMI was a strong predictor for 30‐day mortality (hazard ratio [HR], 4.3; CI, 2.18.9). Risk factors for 1‐year mortality were: age 90 (HR, 2.0; CI, 1.43.1), male gender (HR, 2.1; CI, 1.53.0), and PMI (HR, 1.9; CI, 1.42.7). Figures 1 and 2 describe the Kaplan‐Meier survival curves for patients with and without PMI.

Figure 1

Figure 2

DISCUSSION

We report the high incidence of PMI (13.8%) in the cohort of 1212 elderly patients (mean age 85 years) undergoing hip fracture surgery. Most PMI events (92%) occurred within the first 48 hours of surgery. Most of the events (75%) were asymptomatic. Elderly patients with PMI had an increased hospital LOS by 4.2 days, with high in‐hospital mortality (13.8%), 30‐day mortality (17.4%), and 1‐year mortality (39.5%).

Most of the PMI patients were identified with cardiac biomarkers on the basis of universal definition of MI within the first 48 hours. Although universal definition of MI does not define PMI as a separate type, PMI shares common pathophysiological pathways of Type 1 MI (primary coronary event) and Type 2 MI (myocardial oxygen supplydemand imbalance). Postoperative tachycardia, hemodynamic instability, anemia, and hypoxemia may initiate pathways causing more Type 2 MI. Our study highlights the continued need for active surveillance of clinical symptoms, postoperative ECG monitoring for STT changes, and utilizing cardiac troponin in older postoperative patients to improve diagnostic accuracy of PMI.

The current study has higher asymptomatic PMI events when compared to a study of Devereaux et al.11 The current study had an older population undergoing urgent hip fracture surgery, with a higher burden of CAD (60%) and renal failure (20%) with serum creatinine >2 gm/dL (see Supporting Information, Appendix 1, in the online version of this article). Older age and a higher burden of these risk factors may explain the higher incidence of PMI in the current study. Perioperative liberal use of analgesics in hip fracture surgery may explain more asymptomatic patients.

In light of the recently published FOCUS12 trial, an important finding from our study is that postoperative anemia among elderly (<8.0 gm/dL) is associated with a 3.5‐fold increased in‐hospital mortality. It is critical to maintain perioperative hemoglobin above 8.0 gm/dL in very elderly patients, due to asymptomatic presentation of PMI.

In the current study, PMI is associated with a 15‐fold increased risk of in‐hospital death and a 4.3‐fold increased risk of 30‐day mortality in the elderly. Advanced age (85 years) is a well known strong predictor of initial hospital admission and death in elderly patients after outpatient surgery.13 Furthermore, the odds for an in‐hospital death increase by 70% for each 10‐year increase in age.14 Therefore, early detection of silent PMI among at‐risk elderly patients by cardiac biomarkers may help in optimization of cardiac pharmacotherapy known to decrease short‐ and long‐term mortality.

There are limitations inherent to the retrospective design and methodology. Data collection was done through the year 2002. CK was used for the period that spans from 1988 to mid‐2000. Troponin was used from 2000 to 2002. Statin use was not analyzed for lack of significant data. Limited use of beta‐blockers (15%) and angiotensin‐converting‐enzyme (ACE) inhibitors (25%) may also contribute to higher events (see Supporting Information, Appendix 1, in the online version of this article).

CONCLUSIONS

Elderly patients have a higher incidence of PMI and mortality after hip fracture surgery than what guidelines indicate. The majority of the elderly patients with PMI did not experience ischemic symptoms and required cardiac biomarkers for diagnosis. The results of our study support the measurement of troponin in postoperative elderly patients for the diagnosis of PMI to implement in‐hospital preventive strategies to reduce PMI‐associated mortality.

Perioperative myocardial infarction (PMI) often remains unrecognized with higher mortality in the aged.13 Perioperative ischemic symptoms are often masked by analgesia, sedation, and transient and subtle electrocardiographic (ECG) changes. Postoperative troponin measurement is not routinely done for PMI diagnosis. Hip fracture surgery is the most common non‐cardiac surgical procedure in the elderly, with limited data on clinical presentation of PMI.46 Moreover, the elderly are significantly underrepresented in clinical studies.7 We therefore examined the clinical presentation of PMI and its outcomes among elderly patients admitted for hip fracture repair.

METHODS

RESULTS

In the cohort of 1212 with hip fracture surgeries, 167 (13.8%) cases of PMI occurred in the first 7 days, of which 153 (92%) occurred within the first 48 hours. A total of 334 controls were matched with 167 cases of PMI. Table 1 summarizes the demographic characteristics of the study participants. Of the patients with PMI, 25.2% experienced symptoms of ischemia; 7% reported chest pain, and 12% reported dyspnea. Only 22.8% of patients with PMI had ECG changes consistent with ischemia. ST elevation MI was present in 7.2% patients. PMI patients had a lower mean hemoglobin compared to the patients without PMI (8.9 mg/dL vs 9.4 mg/dL, P < 0.001). Median length of stay (LOS) in the hospital was higher among patients who experienced PMI (11.6 vs 7.4 days, P < 0.001). Overall in‐hospital mortality was 5.6%. There were 24 deaths (14.4%) in the PMI group compared to 4 (1.2%) in‐hospital deaths in patients without PMI (P < 0.001). A total of 473 (94%) patients survived to discharge. At 30‐day follow‐up, there were 29 (17.4%) deaths in the PMI group and 14 (4.2%) deaths in non‐PMI group. During the follow‐up for 1 year, there were 143 (29%) deaths: PMI 66 (39.5%) and 77 (23%) non‐PMI group (P < 0.01).

Table 2 describes the risk factors associated with PMI in‐hospital, 30‐day, and 1‐year mortality. Risk factors for PMI were coronary artery disease (CAD) (odds ratio [OR], 3.5; confidence interval [CI], 2.25.6), and serum creatinine >2 mg/dL (OR, 2.4; CI, 1.34.4). Risk factors for in‐hospital mortality were age 8589 (OR, 5.3; CI, 1.617.7), age 90 (OR, 8.9; CI, 2.630.8), PMI (OR 15.1; CI, 4.648.8), male gender (OR 5.8; CI, 2.215.2), dyspnea (OR 5.4; CI, 1.816.9), and hemoglobin <8.0 gm/dL (OR, 3.5; CI, 1.29.9). PMI was a strong predictor for 30‐day mortality (hazard ratio [HR], 4.3; CI, 2.18.9). Risk factors for 1‐year mortality were: age 90 (HR, 2.0; CI, 1.43.1), male gender (HR, 2.1; CI, 1.53.0), and PMI (HR, 1.9; CI, 1.42.7). Figures 1 and 2 describe the Kaplan‐Meier survival curves for patients with and without PMI.

Figure 1

Figure 2

DISCUSSION

We report the high incidence of PMI (13.8%) in the cohort of 1212 elderly patients (mean age 85 years) undergoing hip fracture surgery. Most PMI events (92%) occurred within the first 48 hours of surgery. Most of the events (75%) were asymptomatic. Elderly patients with PMI had an increased hospital LOS by 4.2 days, with high in‐hospital mortality (13.8%), 30‐day mortality (17.4%), and 1‐year mortality (39.5%).

Most of the PMI patients were identified with cardiac biomarkers on the basis of universal definition of MI within the first 48 hours. Although universal definition of MI does not define PMI as a separate type, PMI shares common pathophysiological pathways of Type 1 MI (primary coronary event) and Type 2 MI (myocardial oxygen supplydemand imbalance). Postoperative tachycardia, hemodynamic instability, anemia, and hypoxemia may initiate pathways causing more Type 2 MI. Our study highlights the continued need for active surveillance of clinical symptoms, postoperative ECG monitoring for STT changes, and utilizing cardiac troponin in older postoperative patients to improve diagnostic accuracy of PMI.

The current study has higher asymptomatic PMI events when compared to a study of Devereaux et al.11 The current study had an older population undergoing urgent hip fracture surgery, with a higher burden of CAD (60%) and renal failure (20%) with serum creatinine >2 gm/dL (see Supporting Information, Appendix 1, in the online version of this article). Older age and a higher burden of these risk factors may explain the higher incidence of PMI in the current study. Perioperative liberal use of analgesics in hip fracture surgery may explain more asymptomatic patients.

In light of the recently published FOCUS12 trial, an important finding from our study is that postoperative anemia among elderly (<8.0 gm/dL) is associated with a 3.5‐fold increased in‐hospital mortality. It is critical to maintain perioperative hemoglobin above 8.0 gm/dL in very elderly patients, due to asymptomatic presentation of PMI.

In the current study, PMI is associated with a 15‐fold increased risk of in‐hospital death and a 4.3‐fold increased risk of 30‐day mortality in the elderly. Advanced age (85 years) is a well known strong predictor of initial hospital admission and death in elderly patients after outpatient surgery.13 Furthermore, the odds for an in‐hospital death increase by 70% for each 10‐year increase in age.14 Therefore, early detection of silent PMI among at‐risk elderly patients by cardiac biomarkers may help in optimization of cardiac pharmacotherapy known to decrease short‐ and long‐term mortality.

There are limitations inherent to the retrospective design and methodology. Data collection was done through the year 2002. CK was used for the period that spans from 1988 to mid‐2000. Troponin was used from 2000 to 2002. Statin use was not analyzed for lack of significant data. Limited use of beta‐blockers (15%) and angiotensin‐converting‐enzyme (ACE) inhibitors (25%) may also contribute to higher events (see Supporting Information, Appendix 1, in the online version of this article).

CONCLUSIONS

Elderly patients have a higher incidence of PMI and mortality after hip fracture surgery than what guidelines indicate. The majority of the elderly patients with PMI did not experience ischemic symptoms and required cardiac biomarkers for diagnosis. The results of our study support the measurement of troponin in postoperative elderly patients for the diagnosis of PMI to implement in‐hospital preventive strategies to reduce PMI‐associated mortality.

Perioperative myocardial infarction (PMI) often remains unrecognized with higher mortality in the aged.13 Perioperative ischemic symptoms are often masked by analgesia, sedation, and transient and subtle electrocardiographic (ECG) changes. Postoperative troponin measurement is not routinely done for PMI diagnosis. Hip fracture surgery is the most common non‐cardiac surgical procedure in the elderly, with limited data on clinical presentation of PMI.46 Moreover, the elderly are significantly underrepresented in clinical studies.7 We therefore examined the clinical presentation of PMI and its outcomes among elderly patients admitted for hip fracture repair.

METHODS

RESULTS

In the cohort of 1212 with hip fracture surgeries, 167 (13.8%) cases of PMI occurred in the first 7 days, of which 153 (92%) occurred within the first 48 hours. A total of 334 controls were matched with 167 cases of PMI. Table 1 summarizes the demographic characteristics of the study participants. Of the patients with PMI, 25.2% experienced symptoms of ischemia; 7% reported chest pain, and 12% reported dyspnea. Only 22.8% of patients with PMI had ECG changes consistent with ischemia. ST elevation MI was present in 7.2% patients. PMI patients had a lower mean hemoglobin compared to the patients without PMI (8.9 mg/dL vs 9.4 mg/dL, P < 0.001). Median length of stay (LOS) in the hospital was higher among patients who experienced PMI (11.6 vs 7.4 days, P < 0.001). Overall in‐hospital mortality was 5.6%. There were 24 deaths (14.4%) in the PMI group compared to 4 (1.2%) in‐hospital deaths in patients without PMI (P < 0.001). A total of 473 (94%) patients survived to discharge. At 30‐day follow‐up, there were 29 (17.4%) deaths in the PMI group and 14 (4.2%) deaths in non‐PMI group. During the follow‐up for 1 year, there were 143 (29%) deaths: PMI 66 (39.5%) and 77 (23%) non‐PMI group (P < 0.01).

Table 2 describes the risk factors associated with PMI in‐hospital, 30‐day, and 1‐year mortality. Risk factors for PMI were coronary artery disease (CAD) (odds ratio [OR], 3.5; confidence interval [CI], 2.25.6), and serum creatinine >2 mg/dL (OR, 2.4; CI, 1.34.4). Risk factors for in‐hospital mortality were age 8589 (OR, 5.3; CI, 1.617.7), age 90 (OR, 8.9; CI, 2.630.8), PMI (OR 15.1; CI, 4.648.8), male gender (OR 5.8; CI, 2.215.2), dyspnea (OR 5.4; CI, 1.816.9), and hemoglobin <8.0 gm/dL (OR, 3.5; CI, 1.29.9). PMI was a strong predictor for 30‐day mortality (hazard ratio [HR], 4.3; CI, 2.18.9). Risk factors for 1‐year mortality were: age 90 (HR, 2.0; CI, 1.43.1), male gender (HR, 2.1; CI, 1.53.0), and PMI (HR, 1.9; CI, 1.42.7). Figures 1 and 2 describe the Kaplan‐Meier survival curves for patients with and without PMI.

Figure 1

Figure 2

DISCUSSION

We report the high incidence of PMI (13.8%) in the cohort of 1212 elderly patients (mean age 85 years) undergoing hip fracture surgery. Most PMI events (92%) occurred within the first 48 hours of surgery. Most of the events (75%) were asymptomatic. Elderly patients with PMI had an increased hospital LOS by 4.2 days, with high in‐hospital mortality (13.8%), 30‐day mortality (17.4%), and 1‐year mortality (39.5%).

Most of the PMI patients were identified with cardiac biomarkers on the basis of universal definition of MI within the first 48 hours. Although universal definition of MI does not define PMI as a separate type, PMI shares common pathophysiological pathways of Type 1 MI (primary coronary event) and Type 2 MI (myocardial oxygen supplydemand imbalance). Postoperative tachycardia, hemodynamic instability, anemia, and hypoxemia may initiate pathways causing more Type 2 MI. Our study highlights the continued need for active surveillance of clinical symptoms, postoperative ECG monitoring for STT changes, and utilizing cardiac troponin in older postoperative patients to improve diagnostic accuracy of PMI.

The current study has higher asymptomatic PMI events when compared to a study of Devereaux et al.11 The current study had an older population undergoing urgent hip fracture surgery, with a higher burden of CAD (60%) and renal failure (20%) with serum creatinine >2 gm/dL (see Supporting Information, Appendix 1, in the online version of this article). Older age and a higher burden of these risk factors may explain the higher incidence of PMI in the current study. Perioperative liberal use of analgesics in hip fracture surgery may explain more asymptomatic patients.

In light of the recently published FOCUS12 trial, an important finding from our study is that postoperative anemia among elderly (<8.0 gm/dL) is associated with a 3.5‐fold increased in‐hospital mortality. It is critical to maintain perioperative hemoglobin above 8.0 gm/dL in very elderly patients, due to asymptomatic presentation of PMI.

In the current study, PMI is associated with a 15‐fold increased risk of in‐hospital death and a 4.3‐fold increased risk of 30‐day mortality in the elderly. Advanced age (85 years) is a well known strong predictor of initial hospital admission and death in elderly patients after outpatient surgery.13 Furthermore, the odds for an in‐hospital death increase by 70% for each 10‐year increase in age.14 Therefore, early detection of silent PMI among at‐risk elderly patients by cardiac biomarkers may help in optimization of cardiac pharmacotherapy known to decrease short‐ and long‐term mortality.

There are limitations inherent to the retrospective design and methodology. Data collection was done through the year 2002. CK was used for the period that spans from 1988 to mid‐2000. Troponin was used from 2000 to 2002. Statin use was not analyzed for lack of significant data. Limited use of beta‐blockers (15%) and angiotensin‐converting‐enzyme (ACE) inhibitors (25%) may also contribute to higher events (see Supporting Information, Appendix 1, in the online version of this article).

CONCLUSIONS

Elderly patients have a higher incidence of PMI and mortality after hip fracture surgery than what guidelines indicate. The majority of the elderly patients with PMI did not experience ischemic symptoms and required cardiac biomarkers for diagnosis. The results of our study support the measurement of troponin in postoperative elderly patients for the diagnosis of PMI to implement in‐hospital preventive strategies to reduce PMI‐associated mortality.