ABSTRACT
<p><b>BACKGROUND</b>China began to implement the national medical and health system and public hospital reforms in 2009 and 2012, respectively. Anhui Province is one of the four pilot provinces, and the medical reform measures received wide attention nationwide. The effectiveness of the above reform needs to get attention. This study aimed to master the efficiency and productivity of county-level public hospitals based on the data envelopment analysis (DEA) model and Malmquist index in Anhui, China, and then provide improvement measures for the future hospital development.</p><p><b>METHODS</b>We chose 12 country-level hospitals based on geographical distribution and the economic development level in Anhui Province. Relevant data that were collected in the field and then sorted were provided by the administrative departments of the hospitals. DEA models were used to calculate the dynamic efficiency and Malmquist index factors for the 12 institutions.</p><p><b>RESULTS</b>During 2010-2015, the overall average relative service efficiency of 12 county-level public hospitals was 0.926, and the number of hospitals achieved an effective DEA for each year from 2010 to 2015 was 4, 6, 7, 7, 6, and 8, respectively, as measured using DEA. During this same period, the average overall production efficiency was 0.983, and the total productivity factor had declined. The overall production efficiency of five hospitals was >1, and the rest are <1 between 2010 and 2015.</p><p><b>CONCLUSIONS</b>In 2010-2015, the relative service efficiency of 12 county-level public hospitals in Anhui Province showed a decreasing trend, and the service efficiency of each hospital changed. In the past 6 years, although some hospitals have been effective, the efficiency of the county-level public hospitals in Anhui Province has not improved significantly, and the total factor productivity has not been effectively improved. County-level public hospitals need to combine their own reality to find their own deficiencies.</p>
ABSTRACT
<p><b>BACKGROUND</b>The self-consciousness and practicality of preferentially prescribed essential medicines (EMs) are not high enough in county hospitals. The purposes of this study were to use the information-motivation-behavioral skills (IMB) model to identify the predictors of essential medicines prescribing behavior (EMPB) among doctors and to examine the association between demographic variables, IMB, and EMPB.</p><p><b>METHODS</b>A cross-sectional study was carried out to assess predictive relationships among demographic variables and IMB model variables using an anonymous questionnaire administered in nine county hospitals of Anhui province. A structural equation model was constructed for the IMB model to test the instruments using analysis of moment structures 17.0.</p><p><b>RESULTS</b>A total of 732 participants completed the survey. The average age of the participants was 37.7 ± 8.9 years old (range: 22-67 years old). The correct rate of information was 90.64%. The average scores of the motivation and behavioral skills were 45.46 ± 7.34 (hundred mark system: 75.77) and 19.92 ± 3.44 (hundred mark system: 79.68), respectively. Approximately half (50.8%) of respondents reported that the proportion of EM prescription was below 60%. The final revised model indicated a good fit to the data (χ2 /df = 4.146, goodness of fit index = 0.948, comparative fit index = 0.938, root mean square error of approximation = 0.066). More work experience (β = 0.153, P < 0.001) and behavioral skills (β = 0.449, P < 0.001) predicted more EMPB. Higher income predicted less information (β = -0.197, P < 0.001) and motivation (β = -0.204, P < 0.001). Behavioral skills were positively predicted by information (β = 0.135, P < 0.001) and motivation (β = 0.742, P < 0.001).</p><p><b>CONCLUSION</b>The present study predicted some factors of EMPB, and specified the relationships among the model variables. The utilization rate of EM was not high enough. Motivation and behavior skills were crucial factors affecting EMPB. The influence of demographic variables, such as income and work experience, on EMPB should be fully appreciated. Comprehensive intervention measures should be implemented from multiple perspectives.</p>