and Productivity at Community Health Centers

Transcription

1 Many Paths to Primary Care: Flexible Staffing and Productivity at Community Health Centers Leighton Ku, Bianca Frogner, Erika Steinmetz & Polly Pittman Funded by HRSA cooperative agreement to the GW Health Workforce Research Center Preliminary and Not for Citation Thanks for Office of Data and Quality, BPHC, HRSA for access to UDS data 1

2 Transforming Primary Care Practice Pending shortage of primary care physicians and quality improvement efforts will require expanded use of non-physician clinicians in team-based care. Community health centers (CHCs) have been doing this for many years. CHCs in medically underserved areas. Often had adjust due to problems hiring and retaining primary care physicians, while maintaining quality of care. CHC experience is instructive for other group practices. Number of physicians in CHCs comparable to general medical practice size. Difference is use of non-physician staff. 2

3 Medical Staffing and Productivity it Key issue in staffing is productivity: how staffing affects the number of medical visits and revenue. Productivity usually based on # visits (or patients) per physician (or advanced practice clinician). Other staff are not counted. But in typical visit a medical asst may take vitals, doctor may evaluate and diagnose, and nurse might draw blood or provide education. From joint productivity i basis, we could say MD produces 75% of visit, med asst 10% and nurse 15%, together th creating 1.0 visit. it 3

4 Data Sources 2012 Uniform Data System (UDS). Annual reports from 1191 CHCs about staffing, patients, visits, diagnoses, insurance coverage, etc. Four types of medical staff ff(in FTEs): Physicians (MDs, DOs), Advanced Practice Staff (NPs, PAs, CNWs), Nurses (RNs, LPNs, LVNs), Other Medical Staff (e.g., medical assts., lab staff, etc.) Weight visits by diagnosis, to account for variable complexity of care 4

5 Basics of CHC Medical Staffing Medical staff excludes behavioral, dental, vision, enabling, and administrative/it staff. Average medical staff size = 45. Median = 27. Staff Type Physicians Advanced Practice Staff Nurses Other Medical Staff Avg. # of Medical Staff Avg. % of Medical Staff 19% 18% 26% 37% Used cluster analysis to identify four clusters of CHCs with different staffing patterns 5

6 Medical Staff Composition in Community Health Centers: Overall and for the Four Staffing Clusters 100% Four Staffing Clusters Per rcent of To otal Medica al Staff 80% 60% 40% 20% % Other Medical %N Nurses % Mid-Level % Physicians 0% OVERALL "Typical" High Advanced Practice High Nurse High Other Medical Staff n=1, n=421 n=44 n=295 n=431 Source: 2012 Uniform Data System 6

7 Staffing Clusters Differ in Size "Typical" High Advanced Practice Total # Med Staff High Nurse # Wtd Visits (1000s) High Other Medical

8 Average Productivity (Mean Weighted Visits per FTE Staff) Is Similar Across Clusters "Typical" 1,071 High Advanced Practice 1,261 High Nurse 1,223 High Other Medical 1,091 8

9 Location and Caseload Differences "Typical" 15% 37% 36% 52% High Advanced Practice High Nurse 15% 14% 29% 33% 36% 32% 39% 47% % Urban % Pts Uninsured % Pts Medicaid % Pts Limited English High Other Medical 23% 42% 35% 67% 9

10 Marginal Productivity by Staff and Cluster: # Additional Weighted Visits per Staff Person Physicians Advanced Practice Staff Nurses Other Medical Staff Overall CHCs 2994** 1584** ** Typical 3370** 1546** High Adv Practice 2761** 2287* High Nurse 2086** ** 357 High Other Medical Staff 2923** 1664** ** * p <.01, ** p <.001 Based on OLS regression with no constant and with robust standard errors: Wgtd visits = b1*phys + b2*advpr + b3*nurse + b4*othmed 10

11 More on Marginal Productivity Physicians have highest marginal productivity but all types of staff contribute. Marginal productivity levels vary across the different cluster types Nurse productivity is higher in High Nurse clusters. Similar for AP staff in High Adv Prac clusters and other medical in High Other clusters. Indicates CHCs flexibly modify staff roles and productivity depending on who is on staff. Ambiguous roles of nurses and other medical staff may be due to high hlevel lof substitution. i 11

12 CHC Level State County Level Factors Associated with CHC Staffing % Physicians % Adv Prac % Nurses % Oth Med Rural index Physician density Advanced ++ practice density Nurse density + - % popn poor - + Full NP scope Partial NP scope # medical pts - % pts uninsured % pts Medicaid % pts LEP Based on OLS regression with robust standard errors 12

13 Limitations of Study We know number of staff, but not what they do, nor how they interact to provide care. Requires finer-grained case studies. Do not know how different staffing affects quality of care, although CHCs generally provide good quality care. Potential misclassification of staff. Some medical staff may primarily be administrative or non- medical functions (e.g., running WIC clinic). Weighting may not accurately reflect complexity of care 13

14 Conclusions Medical practices can use more non-physician staff to increase visits, although physicians contribute most to productivity. All medical staff contribute to productivity. No clear optimal staffing pattern. Productivity seems similar across different staffing patterns. Staffing related to environmental factors, such as availability of staff, urban/rural locale and scope of practice laws and caseload characteristics. i Could be applicable to broader set of group practices in the U.S. 14