The hospitalist care model as described by Drs Robert Wachter and Lee Goldman in 1996 has seen rapid growth in terms of the number of hospitalists and the number of hospitals served by hospitalists' groups in North America.16 Hospitalists were initially defined as physicians who spend a minimum of 25% to 50% of their time caring for inpatients.7 The Society of Hospital Medicine later identified hospitalists as physicians whose primary professional focus is the general medical care of hospitalized patients. Their activities include patient care, teaching, research, and leadership related to hospital care.7, 8

Previous study results have consistently demonstrated that hospitalists may decrease overall cost and length of stay (LOS) for patients without compromising clinical outcomes.912

Like many countries around the world, tertiary hospitals in the Singapore health system grapple with the challenges of providing highly subspecialized care to patients who at the same time requires general medical care for multiple complex comorbidities. Unlike the United States, the shortage of generalists in Singapore's hospitals is partly historical, due to the fact that its health system was developed based on the British health system. Under this model of care, family doctors or general practitioners (GP) do not have a tradition of attending to their patients after they are admitted to the hospital. Care of patient is handed over to hospital specialist on admission. In the interest of improving patient care amidst increasing fragmentation of care due to subspecialization, Singapore General Hospital (SGH) developed a hospitalist care model that is adapted to the health system of Singapore.13 The hospital conducted an extensive study of the hospitalist care model which included study visits to the hospitalist programs at the Calgary Health Region in Canada and the University of California, San Francisco, CA, in the United States.14

The aim of this study was to assess the clinical outcomes of the adapted hospitalist program which uses family physicians as generalists in the hospital and compare this with the traditional model of using specialists to provide general medical care in the Singapore General Hospital. The care outcome indicators we used were hospital LOS, 30 day all‐cause readmissions, mortality, and cost of care.

Methods

Results

A total of 3493 patients met the inclusion/exclusion criteria, in which 601 patients were under the care of hospitalists. The demographic and clinical characteristics of all patients are shown in Table 1. There were no differences in age (67.0 20.4 vs. 66.1 19.8 years, P= 0.311) and ethnic group (P= 0.253) between patients cared for by hospitalists and nonhospitalists. Patients cared for by hospitalists were less likely to be admitted to ICU (0.5% vs. 2.5%, P= 0.002) than patients cared for by nonhospitalists. There were similar CCI grades between patients cared for by hospitalists and nonhospitalists (P= 0.872). Patients cared for by hospitalists had similar numbers of organ failures as compared to patients cared for by nonhospitalists.

Discussion

We found that patients cared for by hospitalists had shorter hospital LOS (reduced by 0.9 days), and reduced cost (reduced by $250), compared with that of patients cared for by nonhospitalists. This occurred without any compromise of the clinical outcomes as measured by hospital mortality and 30‐day all‐cause unscheduled readmission. The mortality rates were 4.0%(hospitalist) and 5.3%(nonhospitalist). The difference was not statistically significant (P= 0.187). The differences in hospital LOS and cost still existed even after adjustment for age, gender, ethnic group, ICU admission, CCI, and the numbers of organ failure.

Our findings are consistent with previous reports of reduced hospital LOS and hospitalization costs in patients cared for by hospitalists in the United States.2730

Several explanations have been proposed for the favorable results. First, hospitalists' accessibility and holistic approach to the multiple problems of individual patients provide a more coordinated response to the patient's changing needs during the hospital stay. Second, studies had suggested that better coordination of care by hospitalist results in a lower use of resources and fewer specialist consultations.31 Reduced patients hospital LOS and cost may lead to an overall reduction in total revenue to the hospital, resulting in an advantage to the patients and a disadvantage to the hospital. However, this reduction in total revenue may have been partially offset by an increase in the number of patients receiving hospital care services.32 Third, fewer patients in the hospitalists group had an ICU stay and this could be another reason for an increased chance of earlier discharge from the hospital.33 The reduced LOS still existed even after adjustment for ICU admission and other factors. The total number of patients with ICU admissions was small in both groups and did not make a difference to the outcome measures used in our study. The use of ICU is significantly higher by the nonhospitalist group. It is unlikely that the difference was due to severity of illness on admission because the admitting physicians at the emergency department do not specify whether patients are to be managed by hospitalists or nonhospitalists. Assignment of the patient to the 2 groups was based only on the availability of bed at the time of admission. There is a possibility that the difference had occurred by chance due to the small number of patients requiring ICU admission. Discussion of end of life care issues and palliation as an option is known to result in lowered utilization of ICU.34 There is a possibility that hospitalists are more likely to engage the patient and family in end of life care discussions although this would require further studies to confirm. Finally, hospitalists might be more effective in navigating the complex environment of the hospital and might develop greater clinical expertise as a result of repeated experience in caring for patients in a similar setting.35 All these favorable factors were present in our adapted hospitalist care model.

While some studies of hospitalist care have shown reduced LOS without reduction of cost, our results showed significant reduction in the cost of care ($250, P= 0.001) for patient who are managed under the hospitalist program. The differences lie mainly in the cost of treatment and facilities. There were no significant differences in the cost of investigations and drugs.

There were several limitations in our study. Although hospital discharge data had numerous advantages including reliability and extensive use in various analyses in health services and health policy research,36 the dataset was administrative in nature and was not created specifically for our study. The hospital discharge data was also at risk of coding errors and omissions of important diagnoses and complications, which may affect the disease complexity estimates.37 In our study this was partly mitigated by the quality control processes instituted by the hospital and government agencies that use this data for planning and health care financing purposes. As all the data came from a single hospital, there was less risk of coding discrepancies and nonuniformity in calculating hospitalization costs. Our study was retrospective and observational in nature. Nevertheless we did use a number of statistical methods and analyses to minimize the risk of bias. Underlying differences in the patient populations of the 2 comparison groups led us to rely heavily on multivariate analysis and adjustment to minimize confounding factors. Nevertheless it is still possible that factors not included in administrative data might still exist as unmeasured confounders.28 In the period of study, we did not identify significant changes in the process of care for the patients apart from the introduction of the adapted hospitalist care model. This study was done in a single hospital. The hospital is an acute tertiary hospital. It is also a teaching hospital with affiliation to 2 medical schools (Duke‐NUS Graduate Medical School and Yong Loo Lin School of Medicine). The results might not be generalizable to other hospitals with different characteristics. Finally, this study was limited to information concerning in‐hospital deaths, and we did not have data that would have allowed us to detect differences in deaths that occurred after discharge. Similarly, we could only assess readmissions within our hospital. We do not know how frequently patients were admitted to other hospitals, a potential problem in all research of this type reported to date.30

In conclusion, our study showed that the hospitalist care model can be adapted to work in health systems outside North America with favorable outcomes. Our adapted hospitalist care model using family physicians as generalists in the hospital was associated with improvements in areas of LOS and cost reductions. There were no difference in mortality and readmissions. In health systems where hospital and primary care providers are historically divided, the deployment of family physicians as hospitalist may have the additional benefit of bridging the gap and support care continuity across the entire spectrum of care settings for patients.

The hospitalist care model as described by Drs Robert Wachter and Lee Goldman in 1996 has seen rapid growth in terms of the number of hospitalists and the number of hospitals served by hospitalists' groups in North America.16 Hospitalists were initially defined as physicians who spend a minimum of 25% to 50% of their time caring for inpatients.7 The Society of Hospital Medicine later identified hospitalists as physicians whose primary professional focus is the general medical care of hospitalized patients. Their activities include patient care, teaching, research, and leadership related to hospital care.7, 8

Previous study results have consistently demonstrated that hospitalists may decrease overall cost and length of stay (LOS) for patients without compromising clinical outcomes.912

Like many countries around the world, tertiary hospitals in the Singapore health system grapple with the challenges of providing highly subspecialized care to patients who at the same time requires general medical care for multiple complex comorbidities. Unlike the United States, the shortage of generalists in Singapore's hospitals is partly historical, due to the fact that its health system was developed based on the British health system. Under this model of care, family doctors or general practitioners (GP) do not have a tradition of attending to their patients after they are admitted to the hospital. Care of patient is handed over to hospital specialist on admission. In the interest of improving patient care amidst increasing fragmentation of care due to subspecialization, Singapore General Hospital (SGH) developed a hospitalist care model that is adapted to the health system of Singapore.13 The hospital conducted an extensive study of the hospitalist care model which included study visits to the hospitalist programs at the Calgary Health Region in Canada and the University of California, San Francisco, CA, in the United States.14

The aim of this study was to assess the clinical outcomes of the adapted hospitalist program which uses family physicians as generalists in the hospital and compare this with the traditional model of using specialists to provide general medical care in the Singapore General Hospital. The care outcome indicators we used were hospital LOS, 30 day all‐cause readmissions, mortality, and cost of care.

Methods

Results

A total of 3493 patients met the inclusion/exclusion criteria, in which 601 patients were under the care of hospitalists. The demographic and clinical characteristics of all patients are shown in Table 1. There were no differences in age (67.0 20.4 vs. 66.1 19.8 years, P= 0.311) and ethnic group (P= 0.253) between patients cared for by hospitalists and nonhospitalists. Patients cared for by hospitalists were less likely to be admitted to ICU (0.5% vs. 2.5%, P= 0.002) than patients cared for by nonhospitalists. There were similar CCI grades between patients cared for by hospitalists and nonhospitalists (P= 0.872). Patients cared for by hospitalists had similar numbers of organ failures as compared to patients cared for by nonhospitalists.

Discussion

We found that patients cared for by hospitalists had shorter hospital LOS (reduced by 0.9 days), and reduced cost (reduced by $250), compared with that of patients cared for by nonhospitalists. This occurred without any compromise of the clinical outcomes as measured by hospital mortality and 30‐day all‐cause unscheduled readmission. The mortality rates were 4.0%(hospitalist) and 5.3%(nonhospitalist). The difference was not statistically significant (P= 0.187). The differences in hospital LOS and cost still existed even after adjustment for age, gender, ethnic group, ICU admission, CCI, and the numbers of organ failure.

Our findings are consistent with previous reports of reduced hospital LOS and hospitalization costs in patients cared for by hospitalists in the United States.2730

Several explanations have been proposed for the favorable results. First, hospitalists' accessibility and holistic approach to the multiple problems of individual patients provide a more coordinated response to the patient's changing needs during the hospital stay. Second, studies had suggested that better coordination of care by hospitalist results in a lower use of resources and fewer specialist consultations.31 Reduced patients hospital LOS and cost may lead to an overall reduction in total revenue to the hospital, resulting in an advantage to the patients and a disadvantage to the hospital. However, this reduction in total revenue may have been partially offset by an increase in the number of patients receiving hospital care services.32 Third, fewer patients in the hospitalists group had an ICU stay and this could be another reason for an increased chance of earlier discharge from the hospital.33 The reduced LOS still existed even after adjustment for ICU admission and other factors. The total number of patients with ICU admissions was small in both groups and did not make a difference to the outcome measures used in our study. The use of ICU is significantly higher by the nonhospitalist group. It is unlikely that the difference was due to severity of illness on admission because the admitting physicians at the emergency department do not specify whether patients are to be managed by hospitalists or nonhospitalists. Assignment of the patient to the 2 groups was based only on the availability of bed at the time of admission. There is a possibility that the difference had occurred by chance due to the small number of patients requiring ICU admission. Discussion of end of life care issues and palliation as an option is known to result in lowered utilization of ICU.34 There is a possibility that hospitalists are more likely to engage the patient and family in end of life care discussions although this would require further studies to confirm. Finally, hospitalists might be more effective in navigating the complex environment of the hospital and might develop greater clinical expertise as a result of repeated experience in caring for patients in a similar setting.35 All these favorable factors were present in our adapted hospitalist care model.

While some studies of hospitalist care have shown reduced LOS without reduction of cost, our results showed significant reduction in the cost of care ($250, P= 0.001) for patient who are managed under the hospitalist program. The differences lie mainly in the cost of treatment and facilities. There were no significant differences in the cost of investigations and drugs.

There were several limitations in our study. Although hospital discharge data had numerous advantages including reliability and extensive use in various analyses in health services and health policy research,36 the dataset was administrative in nature and was not created specifically for our study. The hospital discharge data was also at risk of coding errors and omissions of important diagnoses and complications, which may affect the disease complexity estimates.37 In our study this was partly mitigated by the quality control processes instituted by the hospital and government agencies that use this data for planning and health care financing purposes. As all the data came from a single hospital, there was less risk of coding discrepancies and nonuniformity in calculating hospitalization costs. Our study was retrospective and observational in nature. Nevertheless we did use a number of statistical methods and analyses to minimize the risk of bias. Underlying differences in the patient populations of the 2 comparison groups led us to rely heavily on multivariate analysis and adjustment to minimize confounding factors. Nevertheless it is still possible that factors not included in administrative data might still exist as unmeasured confounders.28 In the period of study, we did not identify significant changes in the process of care for the patients apart from the introduction of the adapted hospitalist care model. This study was done in a single hospital. The hospital is an acute tertiary hospital. It is also a teaching hospital with affiliation to 2 medical schools (Duke‐NUS Graduate Medical School and Yong Loo Lin School of Medicine). The results might not be generalizable to other hospitals with different characteristics. Finally, this study was limited to information concerning in‐hospital deaths, and we did not have data that would have allowed us to detect differences in deaths that occurred after discharge. Similarly, we could only assess readmissions within our hospital. We do not know how frequently patients were admitted to other hospitals, a potential problem in all research of this type reported to date.30

In conclusion, our study showed that the hospitalist care model can be adapted to work in health systems outside North America with favorable outcomes. Our adapted hospitalist care model using family physicians as generalists in the hospital was associated with improvements in areas of LOS and cost reductions. There were no difference in mortality and readmissions. In health systems where hospital and primary care providers are historically divided, the deployment of family physicians as hospitalist may have the additional benefit of bridging the gap and support care continuity across the entire spectrum of care settings for patients.

The hospitalist care model as described by Drs Robert Wachter and Lee Goldman in 1996 has seen rapid growth in terms of the number of hospitalists and the number of hospitals served by hospitalists' groups in North America.16 Hospitalists were initially defined as physicians who spend a minimum of 25% to 50% of their time caring for inpatients.7 The Society of Hospital Medicine later identified hospitalists as physicians whose primary professional focus is the general medical care of hospitalized patients. Their activities include patient care, teaching, research, and leadership related to hospital care.7, 8

Previous study results have consistently demonstrated that hospitalists may decrease overall cost and length of stay (LOS) for patients without compromising clinical outcomes.912

Like many countries around the world, tertiary hospitals in the Singapore health system grapple with the challenges of providing highly subspecialized care to patients who at the same time requires general medical care for multiple complex comorbidities. Unlike the United States, the shortage of generalists in Singapore's hospitals is partly historical, due to the fact that its health system was developed based on the British health system. Under this model of care, family doctors or general practitioners (GP) do not have a tradition of attending to their patients after they are admitted to the hospital. Care of patient is handed over to hospital specialist on admission. In the interest of improving patient care amidst increasing fragmentation of care due to subspecialization, Singapore General Hospital (SGH) developed a hospitalist care model that is adapted to the health system of Singapore.13 The hospital conducted an extensive study of the hospitalist care model which included study visits to the hospitalist programs at the Calgary Health Region in Canada and the University of California, San Francisco, CA, in the United States.14

The aim of this study was to assess the clinical outcomes of the adapted hospitalist program which uses family physicians as generalists in the hospital and compare this with the traditional model of using specialists to provide general medical care in the Singapore General Hospital. The care outcome indicators we used were hospital LOS, 30 day all‐cause readmissions, mortality, and cost of care.

Methods

Results

A total of 3493 patients met the inclusion/exclusion criteria, in which 601 patients were under the care of hospitalists. The demographic and clinical characteristics of all patients are shown in Table 1. There were no differences in age (67.0 20.4 vs. 66.1 19.8 years, P= 0.311) and ethnic group (P= 0.253) between patients cared for by hospitalists and nonhospitalists. Patients cared for by hospitalists were less likely to be admitted to ICU (0.5% vs. 2.5%, P= 0.002) than patients cared for by nonhospitalists. There were similar CCI grades between patients cared for by hospitalists and nonhospitalists (P= 0.872). Patients cared for by hospitalists had similar numbers of organ failures as compared to patients cared for by nonhospitalists.

Discussion

We found that patients cared for by hospitalists had shorter hospital LOS (reduced by 0.9 days), and reduced cost (reduced by $250), compared with that of patients cared for by nonhospitalists. This occurred without any compromise of the clinical outcomes as measured by hospital mortality and 30‐day all‐cause unscheduled readmission. The mortality rates were 4.0%(hospitalist) and 5.3%(nonhospitalist). The difference was not statistically significant (P= 0.187). The differences in hospital LOS and cost still existed even after adjustment for age, gender, ethnic group, ICU admission, CCI, and the numbers of organ failure.

Our findings are consistent with previous reports of reduced hospital LOS and hospitalization costs in patients cared for by hospitalists in the United States.2730

Several explanations have been proposed for the favorable results. First, hospitalists' accessibility and holistic approach to the multiple problems of individual patients provide a more coordinated response to the patient's changing needs during the hospital stay. Second, studies had suggested that better coordination of care by hospitalist results in a lower use of resources and fewer specialist consultations.31 Reduced patients hospital LOS and cost may lead to an overall reduction in total revenue to the hospital, resulting in an advantage to the patients and a disadvantage to the hospital. However, this reduction in total revenue may have been partially offset by an increase in the number of patients receiving hospital care services.32 Third, fewer patients in the hospitalists group had an ICU stay and this could be another reason for an increased chance of earlier discharge from the hospital.33 The reduced LOS still existed even after adjustment for ICU admission and other factors. The total number of patients with ICU admissions was small in both groups and did not make a difference to the outcome measures used in our study. The use of ICU is significantly higher by the nonhospitalist group. It is unlikely that the difference was due to severity of illness on admission because the admitting physicians at the emergency department do not specify whether patients are to be managed by hospitalists or nonhospitalists. Assignment of the patient to the 2 groups was based only on the availability of bed at the time of admission. There is a possibility that the difference had occurred by chance due to the small number of patients requiring ICU admission. Discussion of end of life care issues and palliation as an option is known to result in lowered utilization of ICU.34 There is a possibility that hospitalists are more likely to engage the patient and family in end of life care discussions although this would require further studies to confirm. Finally, hospitalists might be more effective in navigating the complex environment of the hospital and might develop greater clinical expertise as a result of repeated experience in caring for patients in a similar setting.35 All these favorable factors were present in our adapted hospitalist care model.

While some studies of hospitalist care have shown reduced LOS without reduction of cost, our results showed significant reduction in the cost of care ($250, P= 0.001) for patient who are managed under the hospitalist program. The differences lie mainly in the cost of treatment and facilities. There were no significant differences in the cost of investigations and drugs.

There were several limitations in our study. Although hospital discharge data had numerous advantages including reliability and extensive use in various analyses in health services and health policy research,36 the dataset was administrative in nature and was not created specifically for our study. The hospital discharge data was also at risk of coding errors and omissions of important diagnoses and complications, which may affect the disease complexity estimates.37 In our study this was partly mitigated by the quality control processes instituted by the hospital and government agencies that use this data for planning and health care financing purposes. As all the data came from a single hospital, there was less risk of coding discrepancies and nonuniformity in calculating hospitalization costs. Our study was retrospective and observational in nature. Nevertheless we did use a number of statistical methods and analyses to minimize the risk of bias. Underlying differences in the patient populations of the 2 comparison groups led us to rely heavily on multivariate analysis and adjustment to minimize confounding factors. Nevertheless it is still possible that factors not included in administrative data might still exist as unmeasured confounders.28 In the period of study, we did not identify significant changes in the process of care for the patients apart from the introduction of the adapted hospitalist care model. This study was done in a single hospital. The hospital is an acute tertiary hospital. It is also a teaching hospital with affiliation to 2 medical schools (Duke‐NUS Graduate Medical School and Yong Loo Lin School of Medicine). The results might not be generalizable to other hospitals with different characteristics. Finally, this study was limited to information concerning in‐hospital deaths, and we did not have data that would have allowed us to detect differences in deaths that occurred after discharge. Similarly, we could only assess readmissions within our hospital. We do not know how frequently patients were admitted to other hospitals, a potential problem in all research of this type reported to date.30

In conclusion, our study showed that the hospitalist care model can be adapted to work in health systems outside North America with favorable outcomes. Our adapted hospitalist care model using family physicians as generalists in the hospital was associated with improvements in areas of LOS and cost reductions. There were no difference in mortality and readmissions. In health systems where hospital and primary care providers are historically divided, the deployment of family physicians as hospitalist may have the additional benefit of bridging the gap and support care continuity across the entire spectrum of care settings for patients.

If you wish to receive credit for this activity, which beginson the next page, please refer to the website: www.blackwellpublishing.com/cme.

Accreditation and Designation Statement

Blackwell Futura Media Services designates this educational activity for a 1 AMA PRA Category 1 Credit. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Blackwell Futura Media Services is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Educational Objectives

Upon completion of this educational activity, participants will be better able to:

• Identify the approximate 30‐day readmission rate of Medicare patient hospitalized initially for pneumonia.

• Distinguish which variables were accounted and unaccounted for in the development of a pneumonia readmission model.

Continuous participation in the Journal of Hospital Medicine CME program will enable learners to be better able to:

• Interpret clinical guidelines and their applications for higher quality and more efficient care for all hospitalized patients.

• Describe the standard of care for common illnesses and conditions treated in the hospital; such as pneumonia, COPD exacerbation, acute coronary syndrome, HF exacerbation, glycemic control, venous thromboembolic disease, stroke, etc.

• Discuss evidence‐based recommendations involving transitions of care, including the hospital discharge process.

• Gain insights into the roles of hospitalists as medical educators, researchers, medical ethicists, palliative care providers, and hospital‐based geriatricians.

• Incorporate best practices for hospitalist administration, including quality improvement, patient safety, practice management, leadership, and demonstrating hospitalist value.

• Identify evidence‐based best practices and trends for both adult and pediatric hospital medicine.

Instructions on Receiving Credit

For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity during the valid credit period that is noted on the title page.

Follow these steps to earn credit:

• Log on to www.blackwellpublishing.com/cme.

• Read the target audience, learning objectives, and author disclosures.

• Read the article in print or online format.

• Reflect on the article.

• Access the CME Exam, and choose the best answer to each question.

• Complete the required evaluation component of the activity.

If you wish to receive credit for this activity, which beginson the next page, please refer to the website: www.blackwellpublishing.com/cme.

Accreditation and Designation Statement

Blackwell Futura Media Services designates this educational activity for a 1 AMA PRA Category 1 Credit. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Blackwell Futura Media Services is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Educational Objectives

Upon completion of this educational activity, participants will be better able to:

• Identify the approximate 30‐day readmission rate of Medicare patient hospitalized initially for pneumonia.

• Distinguish which variables were accounted and unaccounted for in the development of a pneumonia readmission model.

Continuous participation in the Journal of Hospital Medicine CME program will enable learners to be better able to:

• Interpret clinical guidelines and their applications for higher quality and more efficient care for all hospitalized patients.

• Describe the standard of care for common illnesses and conditions treated in the hospital; such as pneumonia, COPD exacerbation, acute coronary syndrome, HF exacerbation, glycemic control, venous thromboembolic disease, stroke, etc.

• Discuss evidence‐based recommendations involving transitions of care, including the hospital discharge process.

• Gain insights into the roles of hospitalists as medical educators, researchers, medical ethicists, palliative care providers, and hospital‐based geriatricians.

• Incorporate best practices for hospitalist administration, including quality improvement, patient safety, practice management, leadership, and demonstrating hospitalist value.

• Identify evidence‐based best practices and trends for both adult and pediatric hospital medicine.

Instructions on Receiving Credit

For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity during the valid credit period that is noted on the title page.

Follow these steps to earn credit:

• Log on to www.blackwellpublishing.com/cme.

• Read the target audience, learning objectives, and author disclosures.

• Read the article in print or online format.

• Reflect on the article.

• Access the CME Exam, and choose the best answer to each question.

• Complete the required evaluation component of the activity.

If you wish to receive credit for this activity, which beginson the next page, please refer to the website: www.blackwellpublishing.com/cme.

Accreditation and Designation Statement

Blackwell Futura Media Services designates this educational activity for a 1 AMA PRA Category 1 Credit. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Blackwell Futura Media Services is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Educational Objectives

Upon completion of this educational activity, participants will be better able to:

• Identify the approximate 30‐day readmission rate of Medicare patient hospitalized initially for pneumonia.

• Distinguish which variables were accounted and unaccounted for in the development of a pneumonia readmission model.

Continuous participation in the Journal of Hospital Medicine CME program will enable learners to be better able to:

• Interpret clinical guidelines and their applications for higher quality and more efficient care for all hospitalized patients.

• Describe the standard of care for common illnesses and conditions treated in the hospital; such as pneumonia, COPD exacerbation, acute coronary syndrome, HF exacerbation, glycemic control, venous thromboembolic disease, stroke, etc.

• Discuss evidence‐based recommendations involving transitions of care, including the hospital discharge process.

• Gain insights into the roles of hospitalists as medical educators, researchers, medical ethicists, palliative care providers, and hospital‐based geriatricians.

• Incorporate best practices for hospitalist administration, including quality improvement, patient safety, practice management, leadership, and demonstrating hospitalist value.

• Identify evidence‐based best practices and trends for both adult and pediatric hospital medicine.

Instructions on Receiving Credit

For information on applicability and acceptance of continuing medical education credit for this activity, please consult your professional licensing board.

This activity is designed to be completed within the time designated on the title page; physicians should claim only those credits that reflect the time actually spent in the activity. To successfully earn credit, participants must complete the activity during the valid credit period that is noted on the title page.

Follow these steps to earn credit:

• Log on to www.blackwellpublishing.com/cme.

• Read the target audience, learning objectives, and author disclosures.

• Read the article in print or online format.

• Reflect on the article.

• Access the CME Exam, and choose the best answer to each question.

• Complete the required evaluation component of the activity.

Hyperkalemia is a common and potentially life‐threatening problem encountered in many clinical settings. The incidence of hyperkalemia in hospitalized patients has been estimated to be between 1% and 10% in the United States each year.16 Medications are thought to contribute to the development of hyperkalemia in 35% to 75% of hospitalized patients.12, 9 Medications known to cause hyperkalemia include angiotensin‐converting enzyme (ACE) inhibitors, angiotensin II receptor antagonists (ARBs), potassium‐sparing diuretics, nonsteroidal anti‐inflammatory drugs (NSAIDs), potassium supplements, and antibiotics such as trimethoprim/sulfamethoxazole. Patients with hyperkalemia may develop neuromuscular symptoms such as fatigue, muscle weakness, tingling, numbness, and cramping. The most deleterious effect of hyperkalemia is cardiac toxicity, including life‐threatening arrhythmias.3, 711

Sodium polystyrene sulfonate (SPS) or Kayexalate is a cation‐exchange resin that is commonly employed to lower total body potassium in patients with mild to moderate hyperkalemia.1214 It removes potassium from the gut in exchange for sodium. SPS can be given orally or as an enema. When given orally, it is commonly administered with sorbitol to promote diarrhea. The onset of action is within 1 to 2 hours and lasts approximately 4 to 6 hours. The recommended average daily dose is 15 gm to 60 gm given as a single dose or in divided doses. An in vitro study indicated that each gram of resin binds to approximately 3.1 mEq of potassium.14 However, the majority of the exchange capacity is utilized for cations other than potassium. Therefore, the in vivo exchange capacity is thought to be no greater than 1 mEq of potassium per gram of resin.

There are conflicting data regarding the effectiveness of exchange resins.1, 13 In 1998, Guy‐Kapral et al.15 found that a 30‐gm dose of SPS failed to lower serum potassium concentration in end‐stage renal disease patients who were normokalemic. In contrast, Flinn et al.16 demonstrated effective lowering of serum potassium over a period of several days in which repeated doses of SPS were given to hyperkalemic patients. Moreover, in another study, serum potassium concentration was reduced by 1.0 mEq/L in 24 hours.17 However, this study was limited since subjects also received other potassium‐lowering agents such as insulin/glucose or sodium bicarbonate.

In 2004, Mikrut and Brockmiller‐Sell18 studied the dose response between SPS and serum potassium concentration. Their data demonstrated an average reduction in potassium concentration of approximately 1 mmol/L and 1.48 mmol/L following a 30 gm and a 60 gm dose of SPS, respectively. However, the study was small (n = 39) and only evaluated 2 dosages. In clinical practice, there is wide variability in SPS dosing. Furthermore, studies assessing the effects of different doses of SPS are lacking. Often, the dose chosen is dependent on comorbid conditions, concomitant medications and provider experience in treating hyperkalemia. The aim of our study was to examine the single‐dose effect of SPS on potassium concentration in hospitalized, hyperkalemic patients and to compare the potassium lowering effects of SPS doses commonly used.

Methods

Results

Clinical Outcome

A total of 115 patients (94%) achieved normalization of potassium concentration with a single dose of SPS. The mean SPS dose given was 31.84 13.58 gm. The changes in mean electrolyte values for all patients are shown in Table 2. The mean reduction in potassium concentration was 0.99 0.51 mmol/L (P < 0.0001). The follow‐up potassium concentration was obtained on an average of 10 hours after administration of SPS. The mean reduction in calcium concentration was 0.07 0.53 mg/dL (P = 0.13). Further, the mean reduction in sodium concentration was 0.09 3.33 mg/dL (P = 0.004). Figure 1 depicts the change in serum potassium concentration in each of the SPS dosage groups. The mean change in potassium concentrations compared to baseline was statistically significant in all dosage groups. The mean reduction in potassium concentration achieved statistical significance between the 15 gm and 60 gm groups (P < 0.05) and between the 30 gm and 60 gm groups (P < 0.05) (Table 3). To adjust for the potential covariate effects in these group mean comparisons, we further calculated the LSMEAN. Table 3 presents the least square mean changes in serum potassium concentration in each of the SPS dosage groups. As shown in Table 4, the least square mean changes in potassium concentrations compared to the baseline were also statistically significant in all dosage groups. These group differences remain significant, even after the adjustment by the baseline variables.

Figure 1

Table 2.Summary of Changes in Electrolytes

Electrolytes	Pre‐SPS	Post‐SPS	Mean Change	P Value
Abbreviation: SPS, sodium polystyrene sulfonate.
K+(mmol/L)	5.57 0.35	4.59 0.46	0.99 0.51	<0.0001
Ca2+(mg/dL)	8.54 0.81	8.46 0.64	0.07 0.53	0.13
Na+(mmol/L)	136.7 4.66	137.6 4.65	0.89 3.33	0.004

Table 3.Group Comparisons for Least Square Means of Potassium Reduction for the Dose Effect

Dose (gm)	Difference Between Means	CI for Difference Between Means
NOTE: Least square means (LSMEAN) are calculated using a ANCOVA model with Potassium Reduction as the outcome, the SPS dosage groups as the main categorical independent variable and the baseline characteristics in Table 1 as the covariates. The least square means are group means after having controlled for covariates (that is, they are the predicted group means, predicted at the population mean values of the covariates in the model). Tukey's method for multiple comparisons is used to adjust confidence limits for the differences of LS‐means. Abbreviations: ANCOVA, analysis of covariance; CI, confidence interval. * Statistically significant results.
15‐30	0.13	0.43, 0.16
15‐45	0.27	0.66, 0.11
15‐60*	0.64	1.09, 0.19
30‐45	0.14	0.48, 0.20
30‐60*	0.50	0.91, 0.10
45‐60	0.36	0.82, 0.10

Table 4.Least Square Means (LSMEAN) of Potassium Reduction, After Adjustment by the Baseline Variables in Table 1

SPS Dose	LSMEAN of Potassium Reduction	95% Confidence Limits
NOTE: Least square means (LSMEAN) are calculated using an ANCOVA model with potassium reduction as the outcome, the SPS dosage groups as the main categorical independent variable and the baseline characteristics in Table 1 as the covariates. The least square means are group means after having controlled for covariates (that is, they are the predicted group means, predicted at the population mean values of the covariates in the model). Abbreviations: ANCOVA, analysis of covariance; SPS, sodium polystyrene sulfonate.
15 gm	0.676566	0.119091	1.234041
30 gm	0.808860	0.260418	1.357302
45 gm	0.951205	0.431039	1.471371
60 gm	1.313806	0.718793	1.908818

Discussion

In this study, we retrospectively examined inpatients who received a single dose of SPS for the treatment of hyperkalemia. In addition, we established a possible dose response relationship in the treatment of mild to moderate hyperkalemia with SPS monotherapy. Our data revealed that 94% of patients achieved normalization of serum potassium concentration with a single dose of SPS. None of the patients experienced hypokalemia as a result of SPS administration. Moreover, when compared to the work by Mikrut and Brockmiller‐Sell,18 we found a similar reduction in serum potassium associated with the 30 gm (0.95 mmol/L vs. 1 mmol/L) and 60 gm (1.40 vs. 1.48 mEq/L) doses of SPS.

As expected, patients with higher serum potassium concentrations received higher SPS doses. Our data illustrated a possible direct, dose‐response relationship between the SPS dose and the reduction in serum potassium concentration. All of the dosage groups produced a statistically significant reduction in potassium concentrations compared to baseline. Moreover, a statistically significant difference was found in the 60 gm group when compared to the 15 gm and 30 gm groups. The mean increase change in sodium of 0.89 3.33 mmol/L was found to be statistically significant (P = 0.004) but not felt to be clinically relevant. The mean change in calcium concentration of 0.07 0.53 was not statistically significant (P = 0.13).

As with any retrospective chart review, incomplete documentation limits data collection. This may have led to an underestimation of the presence of ARF or other risk factors for hyperkalemia at the time of the event. We excluded patients who received other treatment for hyperkalemia in order to truly assess the effects of SPS on potassium concentration. However, we did not account for all potential confounding variables that are likely to affect potassium concentration such as acid‐base status and glycemic control at the time of the hyperkalemic episode. Also, dietary intake of potassium was not ascertained. Absence of a control group is also a limitation of the study, as it does not allow for complete causality to be established. The sample size, although significantly larger than previous studies, was small especially in regards to the subset analysis. Results cannot be generalized to women since the sample of females was very small or to those who were excluded from the analysis by design. Finally, this study evaluated hospitalized patients and direct extrapolation of the results to outpatient settings should be done cautiously, particularly in light of nutritional considerations.

Our study demonstrates a possible dose‐response relationship in lowering potassium concentrations with SPS. The data presented in this paper can be used to develop a potential dosing guideline for the use of SPS in the clinical management of hyperkalemia in a variety of clinical settings. It provides a basis for a much needed prospective study to finalize a dosing scheme for the use of SPS. Having a dosing scheme would serve as a resource for determining what dose of SPS to give for varying degrees of hyperkalemia while being mindful that individual responses to potassium lowering effect of SPS might be variable.

Hyperkalemia is a common and potentially life‐threatening problem encountered in many clinical settings. The incidence of hyperkalemia in hospitalized patients has been estimated to be between 1% and 10% in the United States each year.16 Medications are thought to contribute to the development of hyperkalemia in 35% to 75% of hospitalized patients.12, 9 Medications known to cause hyperkalemia include angiotensin‐converting enzyme (ACE) inhibitors, angiotensin II receptor antagonists (ARBs), potassium‐sparing diuretics, nonsteroidal anti‐inflammatory drugs (NSAIDs), potassium supplements, and antibiotics such as trimethoprim/sulfamethoxazole. Patients with hyperkalemia may develop neuromuscular symptoms such as fatigue, muscle weakness, tingling, numbness, and cramping. The most deleterious effect of hyperkalemia is cardiac toxicity, including life‐threatening arrhythmias.3, 711

Sodium polystyrene sulfonate (SPS) or Kayexalate is a cation‐exchange resin that is commonly employed to lower total body potassium in patients with mild to moderate hyperkalemia.1214 It removes potassium from the gut in exchange for sodium. SPS can be given orally or as an enema. When given orally, it is commonly administered with sorbitol to promote diarrhea. The onset of action is within 1 to 2 hours and lasts approximately 4 to 6 hours. The recommended average daily dose is 15 gm to 60 gm given as a single dose or in divided doses. An in vitro study indicated that each gram of resin binds to approximately 3.1 mEq of potassium.14 However, the majority of the exchange capacity is utilized for cations other than potassium. Therefore, the in vivo exchange capacity is thought to be no greater than 1 mEq of potassium per gram of resin.

There are conflicting data regarding the effectiveness of exchange resins.1, 13 In 1998, Guy‐Kapral et al.15 found that a 30‐gm dose of SPS failed to lower serum potassium concentration in end‐stage renal disease patients who were normokalemic. In contrast, Flinn et al.16 demonstrated effective lowering of serum potassium over a period of several days in which repeated doses of SPS were given to hyperkalemic patients. Moreover, in another study, serum potassium concentration was reduced by 1.0 mEq/L in 24 hours.17 However, this study was limited since subjects also received other potassium‐lowering agents such as insulin/glucose or sodium bicarbonate.

In 2004, Mikrut and Brockmiller‐Sell18 studied the dose response between SPS and serum potassium concentration. Their data demonstrated an average reduction in potassium concentration of approximately 1 mmol/L and 1.48 mmol/L following a 30 gm and a 60 gm dose of SPS, respectively. However, the study was small (n = 39) and only evaluated 2 dosages. In clinical practice, there is wide variability in SPS dosing. Furthermore, studies assessing the effects of different doses of SPS are lacking. Often, the dose chosen is dependent on comorbid conditions, concomitant medications and provider experience in treating hyperkalemia. The aim of our study was to examine the single‐dose effect of SPS on potassium concentration in hospitalized, hyperkalemic patients and to compare the potassium lowering effects of SPS doses commonly used.

Methods

Results

Clinical Outcome

A total of 115 patients (94%) achieved normalization of potassium concentration with a single dose of SPS. The mean SPS dose given was 31.84 13.58 gm. The changes in mean electrolyte values for all patients are shown in Table 2. The mean reduction in potassium concentration was 0.99 0.51 mmol/L (P < 0.0001). The follow‐up potassium concentration was obtained on an average of 10 hours after administration of SPS. The mean reduction in calcium concentration was 0.07 0.53 mg/dL (P = 0.13). Further, the mean reduction in sodium concentration was 0.09 3.33 mg/dL (P = 0.004). Figure 1 depicts the change in serum potassium concentration in each of the SPS dosage groups. The mean change in potassium concentrations compared to baseline was statistically significant in all dosage groups. The mean reduction in potassium concentration achieved statistical significance between the 15 gm and 60 gm groups (P < 0.05) and between the 30 gm and 60 gm groups (P < 0.05) (Table 3). To adjust for the potential covariate effects in these group mean comparisons, we further calculated the LSMEAN. Table 3 presents the least square mean changes in serum potassium concentration in each of the SPS dosage groups. As shown in Table 4, the least square mean changes in potassium concentrations compared to the baseline were also statistically significant in all dosage groups. These group differences remain significant, even after the adjustment by the baseline variables.

Figure 1

Table 2.Summary of Changes in Electrolytes

Electrolytes	Pre‐SPS	Post‐SPS	Mean Change	P Value
Abbreviation: SPS, sodium polystyrene sulfonate.
K+(mmol/L)	5.57 0.35	4.59 0.46	0.99 0.51	<0.0001
Ca2+(mg/dL)	8.54 0.81	8.46 0.64	0.07 0.53	0.13
Na+(mmol/L)	136.7 4.66	137.6 4.65	0.89 3.33	0.004

Table 3.Group Comparisons for Least Square Means of Potassium Reduction for the Dose Effect

Dose (gm)	Difference Between Means	CI for Difference Between Means
NOTE: Least square means (LSMEAN) are calculated using a ANCOVA model with Potassium Reduction as the outcome, the SPS dosage groups as the main categorical independent variable and the baseline characteristics in Table 1 as the covariates. The least square means are group means after having controlled for covariates (that is, they are the predicted group means, predicted at the population mean values of the covariates in the model). Tukey's method for multiple comparisons is used to adjust confidence limits for the differences of LS‐means. Abbreviations: ANCOVA, analysis of covariance; CI, confidence interval. * Statistically significant results.
15‐30	0.13	0.43, 0.16
15‐45	0.27	0.66, 0.11
15‐60*	0.64	1.09, 0.19
30‐45	0.14	0.48, 0.20
30‐60*	0.50	0.91, 0.10
45‐60	0.36	0.82, 0.10

Table 4.Least Square Means (LSMEAN) of Potassium Reduction, After Adjustment by the Baseline Variables in Table 1

SPS Dose	LSMEAN of Potassium Reduction	95% Confidence Limits
NOTE: Least square means (LSMEAN) are calculated using an ANCOVA model with potassium reduction as the outcome, the SPS dosage groups as the main categorical independent variable and the baseline characteristics in Table 1 as the covariates. The least square means are group means after having controlled for covariates (that is, they are the predicted group means, predicted at the population mean values of the covariates in the model). Abbreviations: ANCOVA, analysis of covariance; SPS, sodium polystyrene sulfonate.
15 gm	0.676566	0.119091	1.234041
30 gm	0.808860	0.260418	1.357302
45 gm	0.951205	0.431039	1.471371
60 gm	1.313806	0.718793	1.908818

Discussion

In this study, we retrospectively examined inpatients who received a single dose of SPS for the treatment of hyperkalemia. In addition, we established a possible dose response relationship in the treatment of mild to moderate hyperkalemia with SPS monotherapy. Our data revealed that 94% of patients achieved normalization of serum potassium concentration with a single dose of SPS. None of the patients experienced hypokalemia as a result of SPS administration. Moreover, when compared to the work by Mikrut and Brockmiller‐Sell,18 we found a similar reduction in serum potassium associated with the 30 gm (0.95 mmol/L vs. 1 mmol/L) and 60 gm (1.40 vs. 1.48 mEq/L) doses of SPS.

As expected, patients with higher serum potassium concentrations received higher SPS doses. Our data illustrated a possible direct, dose‐response relationship between the SPS dose and the reduction in serum potassium concentration. All of the dosage groups produced a statistically significant reduction in potassium concentrations compared to baseline. Moreover, a statistically significant difference was found in the 60 gm group when compared to the 15 gm and 30 gm groups. The mean increase change in sodium of 0.89 3.33 mmol/L was found to be statistically significant (P = 0.004) but not felt to be clinically relevant. The mean change in calcium concentration of 0.07 0.53 was not statistically significant (P = 0.13).

As with any retrospective chart review, incomplete documentation limits data collection. This may have led to an underestimation of the presence of ARF or other risk factors for hyperkalemia at the time of the event. We excluded patients who received other treatment for hyperkalemia in order to truly assess the effects of SPS on potassium concentration. However, we did not account for all potential confounding variables that are likely to affect potassium concentration such as acid‐base status and glycemic control at the time of the hyperkalemic episode. Also, dietary intake of potassium was not ascertained. Absence of a control group is also a limitation of the study, as it does not allow for complete causality to be established. The sample size, although significantly larger than previous studies, was small especially in regards to the subset analysis. Results cannot be generalized to women since the sample of females was very small or to those who were excluded from the analysis by design. Finally, this study evaluated hospitalized patients and direct extrapolation of the results to outpatient settings should be done cautiously, particularly in light of nutritional considerations.

Our study demonstrates a possible dose‐response relationship in lowering potassium concentrations with SPS. The data presented in this paper can be used to develop a potential dosing guideline for the use of SPS in the clinical management of hyperkalemia in a variety of clinical settings. It provides a basis for a much needed prospective study to finalize a dosing scheme for the use of SPS. Having a dosing scheme would serve as a resource for determining what dose of SPS to give for varying degrees of hyperkalemia while being mindful that individual responses to potassium lowering effect of SPS might be variable.

Hyperkalemia is a common and potentially life‐threatening problem encountered in many clinical settings. The incidence of hyperkalemia in hospitalized patients has been estimated to be between 1% and 10% in the United States each year.16 Medications are thought to contribute to the development of hyperkalemia in 35% to 75% of hospitalized patients.12, 9 Medications known to cause hyperkalemia include angiotensin‐converting enzyme (ACE) inhibitors, angiotensin II receptor antagonists (ARBs), potassium‐sparing diuretics, nonsteroidal anti‐inflammatory drugs (NSAIDs), potassium supplements, and antibiotics such as trimethoprim/sulfamethoxazole. Patients with hyperkalemia may develop neuromuscular symptoms such as fatigue, muscle weakness, tingling, numbness, and cramping. The most deleterious effect of hyperkalemia is cardiac toxicity, including life‐threatening arrhythmias.3, 711

Sodium polystyrene sulfonate (SPS) or Kayexalate is a cation‐exchange resin that is commonly employed to lower total body potassium in patients with mild to moderate hyperkalemia.1214 It removes potassium from the gut in exchange for sodium. SPS can be given orally or as an enema. When given orally, it is commonly administered with sorbitol to promote diarrhea. The onset of action is within 1 to 2 hours and lasts approximately 4 to 6 hours. The recommended average daily dose is 15 gm to 60 gm given as a single dose or in divided doses. An in vitro study indicated that each gram of resin binds to approximately 3.1 mEq of potassium.14 However, the majority of the exchange capacity is utilized for cations other than potassium. Therefore, the in vivo exchange capacity is thought to be no greater than 1 mEq of potassium per gram of resin.

There are conflicting data regarding the effectiveness of exchange resins.1, 13 In 1998, Guy‐Kapral et al.15 found that a 30‐gm dose of SPS failed to lower serum potassium concentration in end‐stage renal disease patients who were normokalemic. In contrast, Flinn et al.16 demonstrated effective lowering of serum potassium over a period of several days in which repeated doses of SPS were given to hyperkalemic patients. Moreover, in another study, serum potassium concentration was reduced by 1.0 mEq/L in 24 hours.17 However, this study was limited since subjects also received other potassium‐lowering agents such as insulin/glucose or sodium bicarbonate.

In 2004, Mikrut and Brockmiller‐Sell18 studied the dose response between SPS and serum potassium concentration. Their data demonstrated an average reduction in potassium concentration of approximately 1 mmol/L and 1.48 mmol/L following a 30 gm and a 60 gm dose of SPS, respectively. However, the study was small (n = 39) and only evaluated 2 dosages. In clinical practice, there is wide variability in SPS dosing. Furthermore, studies assessing the effects of different doses of SPS are lacking. Often, the dose chosen is dependent on comorbid conditions, concomitant medications and provider experience in treating hyperkalemia. The aim of our study was to examine the single‐dose effect of SPS on potassium concentration in hospitalized, hyperkalemic patients and to compare the potassium lowering effects of SPS doses commonly used.

Methods

Results

Clinical Outcome

A total of 115 patients (94%) achieved normalization of potassium concentration with a single dose of SPS. The mean SPS dose given was 31.84 13.58 gm. The changes in mean electrolyte values for all patients are shown in Table 2. The mean reduction in potassium concentration was 0.99 0.51 mmol/L (P < 0.0001). The follow‐up potassium concentration was obtained on an average of 10 hours after administration of SPS. The mean reduction in calcium concentration was 0.07 0.53 mg/dL (P = 0.13). Further, the mean reduction in sodium concentration was 0.09 3.33 mg/dL (P = 0.004). Figure 1 depicts the change in serum potassium concentration in each of the SPS dosage groups. The mean change in potassium concentrations compared to baseline was statistically significant in all dosage groups. The mean reduction in potassium concentration achieved statistical significance between the 15 gm and 60 gm groups (P < 0.05) and between the 30 gm and 60 gm groups (P < 0.05) (Table 3). To adjust for the potential covariate effects in these group mean comparisons, we further calculated the LSMEAN. Table 3 presents the least square mean changes in serum potassium concentration in each of the SPS dosage groups. As shown in Table 4, the least square mean changes in potassium concentrations compared to the baseline were also statistically significant in all dosage groups. These group differences remain significant, even after the adjustment by the baseline variables.

Figure 1

Table 2.Summary of Changes in Electrolytes

Electrolytes	Pre‐SPS	Post‐SPS	Mean Change	P Value
Abbreviation: SPS, sodium polystyrene sulfonate.
K+(mmol/L)	5.57 0.35	4.59 0.46	0.99 0.51	<0.0001
Ca2+(mg/dL)	8.54 0.81	8.46 0.64	0.07 0.53	0.13
Na+(mmol/L)	136.7 4.66	137.6 4.65	0.89 3.33	0.004

Table 3.Group Comparisons for Least Square Means of Potassium Reduction for the Dose Effect

Dose (gm)	Difference Between Means	CI for Difference Between Means
NOTE: Least square means (LSMEAN) are calculated using a ANCOVA model with Potassium Reduction as the outcome, the SPS dosage groups as the main categorical independent variable and the baseline characteristics in Table 1 as the covariates. The least square means are group means after having controlled for covariates (that is, they are the predicted group means, predicted at the population mean values of the covariates in the model). Tukey's method for multiple comparisons is used to adjust confidence limits for the differences of LS‐means. Abbreviations: ANCOVA, analysis of covariance; CI, confidence interval. * Statistically significant results.
15‐30	0.13	0.43, 0.16
15‐45	0.27	0.66, 0.11
15‐60*	0.64	1.09, 0.19
30‐45	0.14	0.48, 0.20
30‐60*	0.50	0.91, 0.10
45‐60	0.36	0.82, 0.10

Table 4.Least Square Means (LSMEAN) of Potassium Reduction, After Adjustment by the Baseline Variables in Table 1

SPS Dose	LSMEAN of Potassium Reduction	95% Confidence Limits
NOTE: Least square means (LSMEAN) are calculated using an ANCOVA model with potassium reduction as the outcome, the SPS dosage groups as the main categorical independent variable and the baseline characteristics in Table 1 as the covariates. The least square means are group means after having controlled for covariates (that is, they are the predicted group means, predicted at the population mean values of the covariates in the model). Abbreviations: ANCOVA, analysis of covariance; SPS, sodium polystyrene sulfonate.
15 gm	0.676566	0.119091	1.234041
30 gm	0.808860	0.260418	1.357302
45 gm	0.951205	0.431039	1.471371
60 gm	1.313806	0.718793	1.908818

Discussion

In this study, we retrospectively examined inpatients who received a single dose of SPS for the treatment of hyperkalemia. In addition, we established a possible dose response relationship in the treatment of mild to moderate hyperkalemia with SPS monotherapy. Our data revealed that 94% of patients achieved normalization of serum potassium concentration with a single dose of SPS. None of the patients experienced hypokalemia as a result of SPS administration. Moreover, when compared to the work by Mikrut and Brockmiller‐Sell,18 we found a similar reduction in serum potassium associated with the 30 gm (0.95 mmol/L vs. 1 mmol/L) and 60 gm (1.40 vs. 1.48 mEq/L) doses of SPS.

As expected, patients with higher serum potassium concentrations received higher SPS doses. Our data illustrated a possible direct, dose‐response relationship between the SPS dose and the reduction in serum potassium concentration. All of the dosage groups produced a statistically significant reduction in potassium concentrations compared to baseline. Moreover, a statistically significant difference was found in the 60 gm group when compared to the 15 gm and 30 gm groups. The mean increase change in sodium of 0.89 3.33 mmol/L was found to be statistically significant (P = 0.004) but not felt to be clinically relevant. The mean change in calcium concentration of 0.07 0.53 was not statistically significant (P = 0.13).

As with any retrospective chart review, incomplete documentation limits data collection. This may have led to an underestimation of the presence of ARF or other risk factors for hyperkalemia at the time of the event. We excluded patients who received other treatment for hyperkalemia in order to truly assess the effects of SPS on potassium concentration. However, we did not account for all potential confounding variables that are likely to affect potassium concentration such as acid‐base status and glycemic control at the time of the hyperkalemic episode. Also, dietary intake of potassium was not ascertained. Absence of a control group is also a limitation of the study, as it does not allow for complete causality to be established. The sample size, although significantly larger than previous studies, was small especially in regards to the subset analysis. Results cannot be generalized to women since the sample of females was very small or to those who were excluded from the analysis by design. Finally, this study evaluated hospitalized patients and direct extrapolation of the results to outpatient settings should be done cautiously, particularly in light of nutritional considerations.

Our study demonstrates a possible dose‐response relationship in lowering potassium concentrations with SPS. The data presented in this paper can be used to develop a potential dosing guideline for the use of SPS in the clinical management of hyperkalemia in a variety of clinical settings. It provides a basis for a much needed prospective study to finalize a dosing scheme for the use of SPS. Having a dosing scheme would serve as a resource for determining what dose of SPS to give for varying degrees of hyperkalemia while being mindful that individual responses to potassium lowering effect of SPS might be variable.

The growth of hospitalists nationally continues at an unprecedented pace.1 In academic medical centers, the development of hospital medicine groups either as independent divisions or as part of divisions of general internal medicine (DGIM) reflects this trend. Drivers for growth in the academic setting include housestaff work hour restrictions, increased need for oversight on teaching services, development of nonhousestaff services, surgical comanagement, and greater emphasis on efficiency, quality, and safety.26 These drivers have created tremendous opportunities for hospitalists, but the rapid growth has also created challenges to achieving traditional academic success.7, 8

While hospitalists feel the traditional academic pressures to produce new knowledge and teach, the extraordinary need to expand clinical services has resulted in a young hospitalist workforce, with most lacking fellowship training. At the same time, there are few senior mentors available. Taken together, many academic hospital medicine (AHM) programs find themselves populated by large cadres of junior faculty without the support, training, and mentoring they need to succeed in a faculty career.9 For hospital medicine groups, the risk to faculty recruitment, retention, productivity, and morale is high.

In this article, we describe the development and implementation of a multifaceted Faculty Development (FD) program whose goal was to provide our faculty with clinical, educational, leadership, and scholarly skills that would promote academic output and foster work satisfaction.

Methods

Results

Seven faculty participated in the inaugural program. We compared their scholarly output and experiences (6 faculty completed the survey; 87% response rate) with that of 11 more senior faculty who completed the comparison survey. Of note, the response rate of the comparison group was 69% (5 faculty who departed from our division during the previous 2 years were not surveyed). New faculty were surveyed at the start of the academic year with the follow‐up survey completed the following June. The more senior faculty completed the survey once at the same time as the baseline survey for the new faculty. All new faculty participated in each of the Core Seminars, the Teaching Course, the required number of Coaching sessions, and the observed teaching activity. We did not track their attendance at Divisional activities such as Grand Rounds or the Lunch Seminars.

Overall, the FD programmatic offerings were rated highly by new faculty (on a scale of 1 [lowest] to 5 [highest] for a global rating of each FD activity): Core Seminars 4.83 0.41, Coaching Program 4.5 0.84, Teaching Course 4.5 0.55, Grand Rounds 4.83 0.41, and Lunch Seminars 4.5 0.84. Table 2, which compares responses to a series of end of the year statements posed to new faculty, highlights notable differences in their level of comfort with specific skills and resource awareness. Given the small sample size, statistical significance was not calculated. Table 3 illustrates similar comparisons focused on academic output, which demonstrate that new faculty gave more talks to trainees, had greater involvement in hospital committees, more actively participated in quality and safety projects, and submitted more abstracts to regional or national meetings. New faculty also responded differently to which part of the FD program was most influential with 1 suggesting the Coaching Program, 2 the Core Seminars, 2 the entire program efforts, and 1 did not specify.

Table 4 illustrates comparison responses to a series of directed statements. New faculty all reported greater degrees of satisfaction overall, measured by the above responses, compared to previous faculty.

Discussion

We implemented an FD program to foster the academic development of new faculty, and to mitigate the effects of growing clinical demands and a rapid group expansion on our academic mission. The impact of the program was measured by increased work satisfaction and academic output in first year faculty, greater self‐reported comfort in a variety of skills and knowledge of resources, and an improvement in our sense of purpose behind our academic mission. Though the program is only in its second year, we believe the model is of value for other AHM groups, and perhaps even nonacademic groups, all of whom may use such an investment in their hospitalists as a method to improve recruitment, job satisfaction, and retention.

Reviewing our program's first year suggests there were at least 3 keys to our success. First, we benefited tremendously from the time spent crafting a vision for the program and relying heavily on input from the target audience of junior faculty. Moreover, we made every effort to leverage existing resources (eg, using faculty who already taught about a given topic) and time commitments (eg, reshaping our existing Monday lunch meeting). Finally, we increasingly used our FD venues to connect and build networks with colleagues outside our division and within the hospital. This was a deliberate effort to create opportunities for individual faculty to be exposed to and collaborate with nonhospitalists for academic output.

Our research has some limitations, most notably the small sample size in evaluating the program for statistical significance, and the incomplete survey return rates. However, the results were quite consistent and the nonresponses of departed faculty would tend to bias our results toward the null. We also acknowledge the possibility of other confounding factors (eg, changes in clinical compensation models) that may have played a role, although compensation changes were relatively minor during the period studied and faculty did attribute many of the benefits in job satisfaction and skill building to the FD program itself.

Hospital medicine is an unusual field in that there is low barrier to entry and exit. Providers can change jobs without having to say goodbye to a large panel of patients, and in the continued mismatch between available positions and hospitalists, alternative positions can easily and quickly be found if they are dissatisfied.17 In the academic arena, even as hospitalists are hired to fill clinical gaps, they still have to perform under more traditional academic rules in order to be promoted and receive the support and kudos of colleagues and trainees. For both these reasons, early nurturing and socialization is critical to retention and academic success. While some opportunities for FD will be offered by national organizations,18 groups also have local responsibilities to support, mentor, and develop their junior faculty. Not only is such support crucial for the junior faculty themselves, but in our young field, the mentored very quickly become the mentors. Our decision to invest in both mentees and mentors reinforced the importance of mentorship for academic success and retention while planting the seeds for continued success and growth.1923 A recent study suggested that the environment for mentoring may be as important as the mentoring itself, a finding we did not specifically measure, but would support based our anecdotal experiences.24 This orientation toward future needs and creating the right milieu is crucial because demands for continued hospitalist growth are likely to remain.

Moving into year 2 of our FD program and reflecting on the lessons learned from year 1, we've adopted the same multifaceted approach with only minor adjustments to the curriculum, greater expansion of faculty involved in teaching and coaching, and a continued focus on building a sense of community around our academic mission. For the Core Seminars, we moved away from the 3 half‐day sessions and chose to host 2‐hour sessions every other month. This allowed for the same curriculum to be delivered but was much easier to logistically orchestrate. It also had the intended effect of bringing the new faculty together more regularly. In addition, we created dedicated sessions in preparation for our national meeting to allow faculty to bring abstract submissions for review and later, posters and oral presentations for feedback. These added sessions came partly as a suggestion from new faculty in our first year program, and seemed to further energize junior faculty around converting their projects into scholarship. Finally, we continue to further develop coaching and mentoring relationships in our division, partly a result of successful new facultycoach pairings.

In conclusion, our FD program had a noted impact on our new faculty and had a meaningful impact on our division in terms of camaraderie and cohesion, a shared commitment to an academic mission, and a mechanism for recruitment and retention. We hope our practical description for development and implementation of an FD program, including our specific tools, are useful to other groups considering such an initiative.

The growth of hospitalists nationally continues at an unprecedented pace.1 In academic medical centers, the development of hospital medicine groups either as independent divisions or as part of divisions of general internal medicine (DGIM) reflects this trend. Drivers for growth in the academic setting include housestaff work hour restrictions, increased need for oversight on teaching services, development of nonhousestaff services, surgical comanagement, and greater emphasis on efficiency, quality, and safety.26 These drivers have created tremendous opportunities for hospitalists, but the rapid growth has also created challenges to achieving traditional academic success.7, 8

While hospitalists feel the traditional academic pressures to produce new knowledge and teach, the extraordinary need to expand clinical services has resulted in a young hospitalist workforce, with most lacking fellowship training. At the same time, there are few senior mentors available. Taken together, many academic hospital medicine (AHM) programs find themselves populated by large cadres of junior faculty without the support, training, and mentoring they need to succeed in a faculty career.9 For hospital medicine groups, the risk to faculty recruitment, retention, productivity, and morale is high.

In this article, we describe the development and implementation of a multifaceted Faculty Development (FD) program whose goal was to provide our faculty with clinical, educational, leadership, and scholarly skills that would promote academic output and foster work satisfaction.

Methods

Results

Seven faculty participated in the inaugural program. We compared their scholarly output and experiences (6 faculty completed the survey; 87% response rate) with that of 11 more senior faculty who completed the comparison survey. Of note, the response rate of the comparison group was 69% (5 faculty who departed from our division during the previous 2 years were not surveyed). New faculty were surveyed at the start of the academic year with the follow‐up survey completed the following June. The more senior faculty completed the survey once at the same time as the baseline survey for the new faculty. All new faculty participated in each of the Core Seminars, the Teaching Course, the required number of Coaching sessions, and the observed teaching activity. We did not track their attendance at Divisional activities such as Grand Rounds or the Lunch Seminars.

Overall, the FD programmatic offerings were rated highly by new faculty (on a scale of 1 [lowest] to 5 [highest] for a global rating of each FD activity): Core Seminars 4.83 0.41, Coaching Program 4.5 0.84, Teaching Course 4.5 0.55, Grand Rounds 4.83 0.41, and Lunch Seminars 4.5 0.84. Table 2, which compares responses to a series of end of the year statements posed to new faculty, highlights notable differences in their level of comfort with specific skills and resource awareness. Given the small sample size, statistical significance was not calculated. Table 3 illustrates similar comparisons focused on academic output, which demonstrate that new faculty gave more talks to trainees, had greater involvement in hospital committees, more actively participated in quality and safety projects, and submitted more abstracts to regional or national meetings. New faculty also responded differently to which part of the FD program was most influential with 1 suggesting the Coaching Program, 2 the Core Seminars, 2 the entire program efforts, and 1 did not specify.

Table 4 illustrates comparison responses to a series of directed statements. New faculty all reported greater degrees of satisfaction overall, measured by the above responses, compared to previous faculty.

Discussion

We implemented an FD program to foster the academic development of new faculty, and to mitigate the effects of growing clinical demands and a rapid group expansion on our academic mission. The impact of the program was measured by increased work satisfaction and academic output in first year faculty, greater self‐reported comfort in a variety of skills and knowledge of resources, and an improvement in our sense of purpose behind our academic mission. Though the program is only in its second year, we believe the model is of value for other AHM groups, and perhaps even nonacademic groups, all of whom may use such an investment in their hospitalists as a method to improve recruitment, job satisfaction, and retention.

Reviewing our program's first year suggests there were at least 3 keys to our success. First, we benefited tremendously from the time spent crafting a vision for the program and relying heavily on input from the target audience of junior faculty. Moreover, we made every effort to leverage existing resources (eg, using faculty who already taught about a given topic) and time commitments (eg, reshaping our existing Monday lunch meeting). Finally, we increasingly used our FD venues to connect and build networks with colleagues outside our division and within the hospital. This was a deliberate effort to create opportunities for individual faculty to be exposed to and collaborate with nonhospitalists for academic output.

Our research has some limitations, most notably the small sample size in evaluating the program for statistical significance, and the incomplete survey return rates. However, the results were quite consistent and the nonresponses of departed faculty would tend to bias our results toward the null. We also acknowledge the possibility of other confounding factors (eg, changes in clinical compensation models) that may have played a role, although compensation changes were relatively minor during the period studied and faculty did attribute many of the benefits in job satisfaction and skill building to the FD program itself.

Hospital medicine is an unusual field in that there is low barrier to entry and exit. Providers can change jobs without having to say goodbye to a large panel of patients, and in the continued mismatch between available positions and hospitalists, alternative positions can easily and quickly be found if they are dissatisfied.17 In the academic arena, even as hospitalists are hired to fill clinical gaps, they still have to perform under more traditional academic rules in order to be promoted and receive the support and kudos of colleagues and trainees. For both these reasons, early nurturing and socialization is critical to retention and academic success. While some opportunities for FD will be offered by national organizations,18 groups also have local responsibilities to support, mentor, and develop their junior faculty. Not only is such support crucial for the junior faculty themselves, but in our young field, the mentored very quickly become the mentors. Our decision to invest in both mentees and mentors reinforced the importance of mentorship for academic success and retention while planting the seeds for continued success and growth.1923 A recent study suggested that the environment for mentoring may be as important as the mentoring itself, a finding we did not specifically measure, but would support based our anecdotal experiences.24 This orientation toward future needs and creating the right milieu is crucial because demands for continued hospitalist growth are likely to remain.

Moving into year 2 of our FD program and reflecting on the lessons learned from year 1, we've adopted the same multifaceted approach with only minor adjustments to the curriculum, greater expansion of faculty involved in teaching and coaching, and a continued focus on building a sense of community around our academic mission. For the Core Seminars, we moved away from the 3 half‐day sessions and chose to host 2‐hour sessions every other month. This allowed for the same curriculum to be delivered but was much easier to logistically orchestrate. It also had the intended effect of bringing the new faculty together more regularly. In addition, we created dedicated sessions in preparation for our national meeting to allow faculty to bring abstract submissions for review and later, posters and oral presentations for feedback. These added sessions came partly as a suggestion from new faculty in our first year program, and seemed to further energize junior faculty around converting their projects into scholarship. Finally, we continue to further develop coaching and mentoring relationships in our division, partly a result of successful new facultycoach pairings.

In conclusion, our FD program had a noted impact on our new faculty and had a meaningful impact on our division in terms of camaraderie and cohesion, a shared commitment to an academic mission, and a mechanism for recruitment and retention. We hope our practical description for development and implementation of an FD program, including our specific tools, are useful to other groups considering such an initiative.

The growth of hospitalists nationally continues at an unprecedented pace.1 In academic medical centers, the development of hospital medicine groups either as independent divisions or as part of divisions of general internal medicine (DGIM) reflects this trend. Drivers for growth in the academic setting include housestaff work hour restrictions, increased need for oversight on teaching services, development of nonhousestaff services, surgical comanagement, and greater emphasis on efficiency, quality, and safety.26 These drivers have created tremendous opportunities for hospitalists, but the rapid growth has also created challenges to achieving traditional academic success.7, 8

While hospitalists feel the traditional academic pressures to produce new knowledge and teach, the extraordinary need to expand clinical services has resulted in a young hospitalist workforce, with most lacking fellowship training. At the same time, there are few senior mentors available. Taken together, many academic hospital medicine (AHM) programs find themselves populated by large cadres of junior faculty without the support, training, and mentoring they need to succeed in a faculty career.9 For hospital medicine groups, the risk to faculty recruitment, retention, productivity, and morale is high.

In this article, we describe the development and implementation of a multifaceted Faculty Development (FD) program whose goal was to provide our faculty with clinical, educational, leadership, and scholarly skills that would promote academic output and foster work satisfaction.

Methods

Results

Seven faculty participated in the inaugural program. We compared their scholarly output and experiences (6 faculty completed the survey; 87% response rate) with that of 11 more senior faculty who completed the comparison survey. Of note, the response rate of the comparison group was 69% (5 faculty who departed from our division during the previous 2 years were not surveyed). New faculty were surveyed at the start of the academic year with the follow‐up survey completed the following June. The more senior faculty completed the survey once at the same time as the baseline survey for the new faculty. All new faculty participated in each of the Core Seminars, the Teaching Course, the required number of Coaching sessions, and the observed teaching activity. We did not track their attendance at Divisional activities such as Grand Rounds or the Lunch Seminars.

Overall, the FD programmatic offerings were rated highly by new faculty (on a scale of 1 [lowest] to 5 [highest] for a global rating of each FD activity): Core Seminars 4.83 0.41, Coaching Program 4.5 0.84, Teaching Course 4.5 0.55, Grand Rounds 4.83 0.41, and Lunch Seminars 4.5 0.84. Table 2, which compares responses to a series of end of the year statements posed to new faculty, highlights notable differences in their level of comfort with specific skills and resource awareness. Given the small sample size, statistical significance was not calculated. Table 3 illustrates similar comparisons focused on academic output, which demonstrate that new faculty gave more talks to trainees, had greater involvement in hospital committees, more actively participated in quality and safety projects, and submitted more abstracts to regional or national meetings. New faculty also responded differently to which part of the FD program was most influential with 1 suggesting the Coaching Program, 2 the Core Seminars, 2 the entire program efforts, and 1 did not specify.

Table 4 illustrates comparison responses to a series of directed statements. New faculty all reported greater degrees of satisfaction overall, measured by the above responses, compared to previous faculty.

Discussion

We implemented an FD program to foster the academic development of new faculty, and to mitigate the effects of growing clinical demands and a rapid group expansion on our academic mission. The impact of the program was measured by increased work satisfaction and academic output in first year faculty, greater self‐reported comfort in a variety of skills and knowledge of resources, and an improvement in our sense of purpose behind our academic mission. Though the program is only in its second year, we believe the model is of value for other AHM groups, and perhaps even nonacademic groups, all of whom may use such an investment in their hospitalists as a method to improve recruitment, job satisfaction, and retention.

Reviewing our program's first year suggests there were at least 3 keys to our success. First, we benefited tremendously from the time spent crafting a vision for the program and relying heavily on input from the target audience of junior faculty. Moreover, we made every effort to leverage existing resources (eg, using faculty who already taught about a given topic) and time commitments (eg, reshaping our existing Monday lunch meeting). Finally, we increasingly used our FD venues to connect and build networks with colleagues outside our division and within the hospital. This was a deliberate effort to create opportunities for individual faculty to be exposed to and collaborate with nonhospitalists for academic output.

Our research has some limitations, most notably the small sample size in evaluating the program for statistical significance, and the incomplete survey return rates. However, the results were quite consistent and the nonresponses of departed faculty would tend to bias our results toward the null. We also acknowledge the possibility of other confounding factors (eg, changes in clinical compensation models) that may have played a role, although compensation changes were relatively minor during the period studied and faculty did attribute many of the benefits in job satisfaction and skill building to the FD program itself.

Hospital medicine is an unusual field in that there is low barrier to entry and exit. Providers can change jobs without having to say goodbye to a large panel of patients, and in the continued mismatch between available positions and hospitalists, alternative positions can easily and quickly be found if they are dissatisfied.17 In the academic arena, even as hospitalists are hired to fill clinical gaps, they still have to perform under more traditional academic rules in order to be promoted and receive the support and kudos of colleagues and trainees. For both these reasons, early nurturing and socialization is critical to retention and academic success. While some opportunities for FD will be offered by national organizations,18 groups also have local responsibilities to support, mentor, and develop their junior faculty. Not only is such support crucial for the junior faculty themselves, but in our young field, the mentored very quickly become the mentors. Our decision to invest in both mentees and mentors reinforced the importance of mentorship for academic success and retention while planting the seeds for continued success and growth.1923 A recent study suggested that the environment for mentoring may be as important as the mentoring itself, a finding we did not specifically measure, but would support based our anecdotal experiences.24 This orientation toward future needs and creating the right milieu is crucial because demands for continued hospitalist growth are likely to remain.

Moving into year 2 of our FD program and reflecting on the lessons learned from year 1, we've adopted the same multifaceted approach with only minor adjustments to the curriculum, greater expansion of faculty involved in teaching and coaching, and a continued focus on building a sense of community around our academic mission. For the Core Seminars, we moved away from the 3 half‐day sessions and chose to host 2‐hour sessions every other month. This allowed for the same curriculum to be delivered but was much easier to logistically orchestrate. It also had the intended effect of bringing the new faculty together more regularly. In addition, we created dedicated sessions in preparation for our national meeting to allow faculty to bring abstract submissions for review and later, posters and oral presentations for feedback. These added sessions came partly as a suggestion from new faculty in our first year program, and seemed to further energize junior faculty around converting their projects into scholarship. Finally, we continue to further develop coaching and mentoring relationships in our division, partly a result of successful new facultycoach pairings.

In conclusion, our FD program had a noted impact on our new faculty and had a meaningful impact on our division in terms of camaraderie and cohesion, a shared commitment to an academic mission, and a mechanism for recruitment and retention. We hope our practical description for development and implementation of an FD program, including our specific tools, are useful to other groups considering such an initiative.