Insights of the medical income categories studied

PxNo not only had a positively significant level correlated to TMI but also held a consistent quality in the simultaneous quantile regression of both data sets. PxNo can be tracked easily through the computerized patient number generator system in the clinic that is visible and renewed daily so that I suggest PxNo be the best real-time index to estimate physicians’ daily income performance before running a monthly financial income sheet. In contrast, the insignificant results of TCI in data set 1 (TCI was excluded in the final evaluation of data set 1), TCI demonstrated a significant

relationship with TMI of data set 2, first-year income for new-arrived physicians. With regards to APF, in the quantile regression of data set 1, the impact on TMI moved from positive to negative, which was in accordance with the reimbursement policy NHI executes to control the number of patients a physician sees per time slot. In order to encourage physicians to focus on their professional practice and relationship with patients NHI sets up income threshold to the reimbursements as APF, the general scale of patient number to see any one physician followed as under 50, 51 to 70, and more than 70. Although in the long term EXAM presented a significant relationship with TMI of data set 1, both the empirical results of data set 1 and 2 suggested EXAM had small

percentage impacts on the three income groups. Considering empirical results of both data sets in quantile regression, TAO showed a consistent quality of positive influence in TMI among three income groups. TAO in the clinic is regarded as either high NHI reimbursement services or higher payments received as out of pocket payments, which generates a better cash flow for the clinic, compared with NHI reimbursement payments, as well. So far, on average, TAO only accounts for 12% toward the clinic’s total income (Figure). It reflects the general habits as well as impression of patients using ED room services when any of TAO is required. In addition it also implies that the clinic may need a broader public promotion about the medical services it offers, especially in the category of TAO, to the patients in the community. Another interesting result I observed in the study was the impact on quality shift from positive to negative in the quantile regression of both data sets that DRUG likely caused a reduction in TMI especially in the upper income group. The results coincided with NHI’s policy that intends to cut down on the prescription of drug medications.

6.4. Alternative health care market development

When I focused on the empirical results of both data sets, as was my expectation before running the statistical work, NHIr showed the most significant impacts on TMI in both baseline and quantile regression. As I mentioned in the introduction, as the

financial deficit of NHI has increased, so the clinic was reimbursed less per year when the services provided by the clinic are equal compared to years before. Maintaining the role as a community medical service provider in the NHI system, the clinic has offered every enrollee increased solutions on both sides of the health equation; the physicians catered their services to patients in search of cures for his/her diseases, but they’ve also offered a growing number of preventative side medical care options such as access to professionally trained nutritionists and sports medicine practitioners. The foremost goal

in all of this is bringing people in the community to a healthier way of living, so be it on the side of cure or prevention. By maintaining a different approach to health care and a perspective as a community health care provider, compared with other clinics in the NHI system, the clinic has been able to create a competitive advantage. By providing quality care in the cases of chronic disease and in the management of acute symptoms for patients, including novel prevention care options, it’s been able to create additional income in the health care market, as is. At the same time, this value added into the market, in addition to what the NHI already affords, has created premiums for both the clinic and physicians; the ultimate goal of this is to extend the health care market by improving internal efficiency, all the while leading more people in the community to better overall health.

With respect to the practical and daily management of a health clinic, this study was carried out utilizing a retrospective method. Lacking a prospective design and an

original data set for manipulation, I was unable to arrange data set 1 and 2 with exactly identical physicians under the same time period. Although some results were proved in the routine operation, it would still take more prospective researches to further confirm the conclusions.

APF 39%

EXAM TAO 9%

12%

DRUG 23%

Other 17%

Figure: Medical Services pie chart depicts the proportion of TMI generated by various clinical services

Table 1

Definitions, means, and standard deviations of the variables.

Variable Definition Mean, and SD Source

Primary: Data set 1 Data set 2

TMI Total monthly income generated per physician prior to

salary being paid. Mean = 12.03, SD = 1.24 Mean = 11.60, SD = 0.99 HIS

Demographic:    

TPEb Dichotomus variable that was coded one if the physician

was born in Taipei. Mean = 0.28, SD = 0.45 Mean = 0.44, SD = 0.50 HRMS

GED Dichotomus variable that was coded one for the male physicinas.

NA Mean = 0.59, SD = 0.49 HRMS

PuMS Trichotomus variable that was coded one when the physician graduated from a public medical school.

Mean = 0.28, SD = 0.25 Mean = 0.24, SD = 0.43 HRMS

MMS Trichotomus variable that was coded one when the physician graduated from a military medical school. When the physician graduated from a private medical school, PuMed and MMS were both coded zero.

Mean = 0.45, SD = 0.50 Mean = 0.18, SD = 0.38 HRMS

InMed Trichotomus variable that was coded one for the physicians of internal medicine.

Mean = 0.24, SD = 0.43 Mean =0.21, SD = 0.40 HRMS

SuMed Trichotomus variable that was coded one for the physicians of surgery medicine. For physicians with other specialties than internal and surgery medicine, both InMed and SuMed were coded zero.

Mean = 0.17, SD = 0.38 Mean = 0.24, SD = 0.42 HRMS

LR Dichotomus variable that was coded one if the physician registered his/her license under the clinic.

Mean = 0.34, SD = 0.48 Mean = 0.47, SD = 0.50 HRMS

AGE Age of the physician in the designated month. Mean = 3.93, SD = 0.21 Mean = 3.87, SD = 0.20 HRMS

cWM Cumultative working months a physician had worked in the clinic by the designated month.

Mean = 3.77, SD = 0.69 Mean = 0.98, SD = 0.59 HRMS

fCPT Internal competition factor that describes the level of competition for a physician in his/her division; the ratio of competition shifts and the total shifts in the same division.

Mean = -0.43, SD = 0.39 NA HRMS

Income-related:  

TCI Total monthly income generated by all the physicians in the clinic.

NA Mean = 16.27, SD = 0.13 HIS

APF The monthly sum of attending physician fees incurred per patient visit that were either reimbursed by NHI or paid out of patient's pocket.

Mean = 10.72, SD = 1.50 Mean = 10.43, SD = 1.16 HIS

EXAM The monthly sum of payments of lab and radiographic tests prescribed for patients that were either reimbursed by NHI or paid out of patients' pocket.

Mean = 8.41, SD = 3.38 Mean = 8.15, SD = 3.11 HIS

TAO The monthly sum of payments of local treatments and clinic operations executed for patients that were either reimbursed by NHI or paid out of patients' pocket.

Mean = 7.31, SD = 4.12 Mean = 6.42, SD = 4.43 HIS

DRUG The monthly sum of medication fees prescribed for patients that were either reimbursed by NHI or paid out of patient's pocket.

Mean = 10.17, SD = 1.76 Mean = 9.62, SD = 1.37 HIS

NHIr Total monthly income reimbursed by NHI for every physician.

Mean = 11.71, SD = 1.26 Mean = 11.25, SD 0.98 HIS PxNo Total monthly number of patients attended to by every

physician. Mean = 5.89, SD = 1.12 Mean = 5.53, SD = 1.03 HIS

NOTE: HIS denotes hospital information system and HRMS denotes human resource management system.

Table2

Demographic multivariante regression and quantile regression analyses of total monthly income (TMI) for twenty-nine physicians.

Variable Baseline Simultaneous quantile regression bootstrap (1000) SEs

q25 q50 q75