Practitioner productivity and the product content of medical care in publicly supported health centers

Soc Sci Med. 1994 Mar;38(5):733-48. doi: 10.1016/0277-9536(94)90464-2.


The productivity-patient care content relationship in general practice and primary health care has never been a popular topic among medical practitioners. Yet the time a physician spends with patients or the number of patients treated in a fixed time interval would appear to be a critical factor in the content of this care. While current research has demonstrated a clear effect with respect to psychosocial care, the evidence with respect to technical care remains equivocal. The purpose of this study is to assess how physician production--measured as the number of patients seen per hour--affects the technical care performance of preventive and well care in 6 major patient management areas. The analysis uses data collected from 15 publicly supported, primary care centers in Pennsylvania, U.S.A. The care received by 1424 patients over a seven month period (4695 medical encounters) is reflected in the analysis; the work of 64 full time physicians is also represented. Using both linear and piecewise regression techniques, the analysis uncovered evidence that production levels do influence the performance of medical care procedures. The strength, direction and functional form of the relationship, however, depends upon the specific medical component under scrutiny. The impact of encounters per hour is especially telling for the provision of medical history items and preventive care directed at the female patients. The implications of these findings are discussed and inferences about the physician style dynamics which might link productivity and consultation content are presented.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Community Health Centers / statistics & numerical data*
  • Efficiency*
  • Female
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Pennsylvania
  • Physicians, Family / statistics & numerical data*
  • Primary Health Care / statistics & numerical data*
  • Public Health Administration / statistics & numerical data*
  • Regression Analysis
  • Time and Motion Studies