Exploring the Performance and Practice Patterns of Physician Teams in a Medical Center

• Main Authors: Chen, Long-Hong, 陳隆鴻
• Other Authors: Ray-E Chang
• Format: Others
• Language: zh-TW
• Published: 1997
• Online Access: http://ndltd.ncl.edu.tw/handle/30771061057534529013

碩士 === 國立臺灣大學 === 醫療機構管理研究所 === 85 === ABSTRACTHealth care expenditures continue to soar at an unsustainable rate of 7-10% annually all over the world. The governments recognize this imminent financial crisis if health care expenditures cannot be contained. In order to curb the rapid escalation of health care expenditures, measures of reform have been proposed and some are already implemented, e. g., case payment for some diagnoses. In the health care system, physicians make and control 80% of the resoure input decisions, so the inefficiency resulting from physician practice has a far greater impact on hospital financial status of hospital than the inefficiency from administration. It is known that practice patterns among physicians vary widely where the utilization rate of medical resources for a specific diagnosis can fluctuate by a factor of twenty within a hospital. Therefore, reducing costs and improving efficiency are the immediate challenges faced by hospital administrators.The purposes of the study are to identify the efficiencies and practice patterns of physician teams and to discuss the potential reasons. A two-part model provides a clear framework for understanding physician''s production process, but can also be used to analyze physician performance. Three issue arise when one attempts to scrutinize physician production. First, outputs produced are seldom homogeneous. Second, many different types of resources are consumed in the delivery of medical services. To provide accurate measurement of the consumption of medical resources is not an easy task. Finally, this medical care production process involves multiple inputs and outputs. Therefore, an appropriate evaluation tool that can accommodate the multiple input/ multiple output nature and is able to ascertain the efficiency of the practice is of necessity. So we use AP-DRG to adjust patient severity, accounting technique named activity-based costing to the costing of a complex production process provides a useful reference in defining the inputs of this complex medical service production and ratio efficiency games, a new technique combines DEA and game theory, to evaluate physician team performance.The hospital from which the study sample is collected is a medical center, affiliated with a medical school, with 1700 beds and 745 physicians. Out of these physicians, 310 of them are surgeons, and they practice in six major specialty, i.e., general surgery, orthopedics, obstetrics/gynecology, otorhinolaryngology, ophthalmology, and urology called form A to F. In order to have homogeneous production units, only surgeons are included in this study. Since this is a teaching hospital, physicians in the hospital practice in teams rather than individually. There are twenty-eight sub-specialty surgeon teams, and these teams form the sample of our study. Each team is regarded as a decision making unit. In this study, based on the nature of physician''s services rendered, we first classify physicians'' outputs into two categories: outpatient and inpatient services. The measure-ment of outpatient and inpatient services are the number of ambulatory visits and the weighted number of patients discharged, respectively. In this study, inputs used to produced medical services are classified based on the main activities of the hospital in providing patient care. These activities are ambulatory care, hospitalized care, test/examination, and surgery. The intensity of each activity is measured in physician team level by the number of hours used to provide ambulatory care, total number of patient days used for patients discharged, cost of test/ examination, and allocated cost of operating room. Since the last two items are measured in monetary unit, cost of test/ examination and allocated cost of operating room can be combined. Moreover, as physicians are employed, they should be considered one of the major resources used for providing medical services. The number of physicians in each team is used to measure this input. Eight physician teams are identified as efficient. The efficiency scores, called extended ratio efficient scores (e.r.e.s., hereafter efficiency score) At the specialty level, with the exception of specialty C, at least one physician team within each specialty is considered efficient. While specialty B has 60% of physician teams efficient, only 14% of the team in specialty A are efficient. Specialty B and E have an average efficiency score among the teams greater than one. This means that these two specialties'' practices in general are at least 20% more efficient than other specialties and at least 20% more efficient than other specialties. The average efficiency scores of specialty A, C, and D cluster around 0.83. However, specialty F has the lowest efficiency score of around 0.72. This means specialty F on average is at least 10% less efficient than other specialties and is in need of considerable improvement.From the input/output weight selection, practice pattern can be observed. Teams in specialty A primarily select the number of discharged patients and hours used for ambulatory care, which reveals that specialty A is an inpatient-oriented specialty. On the other hand, specialty C is a more outpatient-oriented specialty. Other specialties are more in balance between inpatient and outpatient services. The benchmark for physician teams in specialty A is A2, whose efficiency score is 1.71. The reason is that this team deals with many high severity patients and performs complex procedures. Therefore, the discharge patients are weighted considerably more. Comparing to team A2, other teams have relatively more physicians and retain patients too long with respect to patients'' severity, which causes them inefficient. These are potential areas for improvement. Teams in different specialties practice are able to obtain efficiency in various manners. With the results of this study, the inefficient physician teams are identified, and the teams can implement efficient practices to improve their performances and lower the costs of hospitals.