The efficiency of Thai’s psychiatric hospitals by data

Objective To identify the efficiency of 13 adult psychiatric hospitals under the MentalHealth Department.Materials and methods This retrospective research paper was collected data fromthe budget year 2008 consisting 5 input factors (personnel costs, operating cost fromgovernment budget, operating costs from hospital profit, number of beds, and number of hospitalofficials) and 4 output factors (number of outpatients, number of inpatients, length of stay,and a mean of relative weight of Diagnosis Related Group showing the complexity level oftreatment of each particular patient). Then these input and output data were analyzed by usingdata envelopment analysis (DEA) technique.Results The results, by constant return to scale (CRS) showed that 9 out of 13hospitals were on the overall efficiency frontier having an average CRS of 0.954. Variablereturn to scale (VRS) showed that there were 11 hospitals on the technical efficiency frontierwith an average VRS of 0.972.Conclusion There were 9 psychiatric hospitals having high overall efficiency and11 psychiatric hospitals having high technical efficiency. However, there were some limitationsin some specific areas in psychiatric hospitals.Key words : efficiency, data envelopment analysis (DEA) model, psychiatric hospital

Health Equity as a Human Right of the Highland People in Thailand

Research was conducted to compare health equity levels between three groups. These groups were compared using the benchmark of fairness. Multistage cluster sampling methods were used. The sample size for quantitative study included 789 subjects in 10 provinces and was strengthened by a qualitative component in the form of in-depth interviews. Data analysis utilized ANOVA and Post-hoc Turkey means. The counters for health equity were analyzed by z-scores.Results revealed a significant difference on 7 of the 9 factors (p \< .001). Comparative measurements on Efficiency and Quality of Care (p=.170) as well as Administrative efficiency (p=.227) were not significant. With regards to z score analysis Thai National Citizens were the highest scored (z=.3293), Hill tribe Thai national citizens were average scored (z=.0516) and Hill tribe stateless were the lowest scored (z=-.3885). The means to reduce the gap between groups from the expertise aimed 1) The Hill tribe stateless data base. 2) The health needs budget for The Hill tribe stateless. 3) Only one standard in all health care units. 4) The disfigured nationality laws to support the stateless hill tribe. 5) The decentralization to local government to provide health services.In conclusion, the government health care units service all groups health needs in Thailand. It is here suggested that the Thai government bridge the gap with consistent policy to reduce the gaps between groups in all directions.

Unit Cost for Primary Care: A Case Study at Primary Care Unit with Joint Costs between Municipality, Regional Hospital and University

OBJECTIVE: To study unit cost and cost recovery at primary care unit (Panpee and Naresuan PCUs) in fiscal year 2005.METHOD: This was descriptive retrospective research. Research tools included financial records of cost components including capital costs, labor costs and material costs. The top-down costing method was used and the costs were grouped based on primary care activities and divided into direct costs and indirect costs. A direct distribution method was used for allocating indirect cost and a straight-line method was used for cost depreciation. For each activity, the full cost was divided by the number of service to determine the unit cost.RESULTS: The unit costs at Panpee and Naresuan primary care units were as fellows: 134.6 baht and 143.2 baht for treatment, 415.2 baht and 117.4 baht for maternal and child care, 415.2 baht and 234.2 baht for family planning, 16.6 baht and 20.2 baht for school health care, 639.8 baht and 987.4 baht for home health care, and 103.5 baht and 61.7 baht for immunization. The cost recovery for Panpee and Naresuan primary care units were 181.6 % and 228.7%.CONCLUSION: These results should be taken into account for resource allocation and enhancing efficiency in practice for health promotion and prevention.