A major challenge for leaders of hospital medicine programs is determining appropriate staffing levels. Specifically, every hospitalist leader must answer the following question:
- What is the correct number of physician staff needed to meet the requirements of the work environment?
The Board of Directors of the Society of Hospital Medicine (SHM) asked the Benchmarks Committee to prepare a “white paper” on this subject. The Committee discussed hospitalist staffing and agreed that there is no simple formula or process for answering the question cited above. Instead, the Committee decided to prepare a paper that outlines the issues and suggests best practices for determining appropriate hospitalist staffing levels. A member of the Benchmarks Committee, Gale Ashbrener, Sr., Performance Consultant, Kaiser Permanente-Hawaii, has prepared a model for hospitalist staffing in her organization, and her work is the basis of this document.
NOTE: Most of the examples used in this document are from Kaiser-Hawaii. As such, the numbers cited are reflective of that particular organizational environment (i.e., a group model HMO). Readers should focus on the concepts and processes that are presented, recognizing that the numbers may be different for their environment.
Overview of the Issues
A process or simplistic model for determining the appropriate level of hospitalist staffing is summarized in Figure 1.
Staffing is driven by demand: how many and what types of patients will the program expect to see in the upcoming year? Demand can then be converted to work: the tasks that the hospital medicine program must perform in order to treat these patients (the model must also quantify non-patient work). Once the total amount of work is described and quantified, the capacity of a hospitalist must be defined (e.g., in annual work hours). Then the number of hospitalists required to complete the projected work load can be computed.
The best practices for projecting patient demand are summarized in Box 1.
Hospitalist leaders should involve key stakeholders in the information gathering process. This helps establish the foundation for buy-in of the model down the road. You may want to pull together members of the hospitalist team and/or hospital administration to brainstorm on factors that may affect patient demand for inpatient services. At this point, keep an open mind for all considerations.
It is also critical to perform a comprehensive analysis of historical inpatient data. The analysis should examine all medical admissions at the hospital and specifically, in detail, those admissions cared for by the hospital medicine program. This analysis must look beyond the number of admissions and average length of stay (LOS). Several key characteristics of the hospitalized patients should be evaluated: age, diagnosis/severity, payer, and referring physician.
- Age: There are significant differences in inpatient utilization by age categories. It is important to further segment the “senior” Medicare (over age 65) population into several subgroups. Figure 2 (page 49) is based on data from Kaiser Permanente-Hawaii. As expected, there is a major difference in hospital utilization between the under age 65 population (15.9 admissions and 84 days per 1000) and the over age 65 population (167.9 admissions and 1,090 days per 1000). However, the differences within the Medicare subgroups are also substantial. For example, compare utilization by the population that is 65-69 years old (96.0 admissions and 621 days per 1000) with the population that is over age 85 (358.2 admissions and 2,111 days per 1000):
- Diagnoses/severity: There are acknowledged differences in LOS based on the patient’s reason for admission and many ways to characterize the reason of admission, including diagnosis and diagnostics-related groups (DRGs). Furthermore, patients with co-morbidities clearly require more coordination and patient management. There are several proprietary grouping methodologies that characterize the severity and intensity of an inpatient case, which include an assessment of co-morbidities. In analyzing historical data, the hospitalist leader should select a scheme that is used within the institution while minimizing the number of categories.
- Payer: In analyzing inpatient demand, it is also important to have an understanding of historical differences by payer (including uninsured patients). Health plans (or Medicaid programs) that are increasing or decreasing in size could affect the number of patients seen by a hospital medicine program.
- Referring physician: Community physicians (primary care, specialists, and surgeons) are a major source of inpatient cases for hospital medicine programs. It is important to analyze the historical impact of specific physicians or group practices on the patient load of the hospital medicine program.