| Summary: | 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.
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