Development of a risk-adjusted capitation model based on principal inpatient diagnoses in Taiwan.

BACKGROUND AND PURPOSE: Taiwan's National Health Insurance (NHI) program has considered the use of capitation payments to health care providers as a method for control of the rising costs of the system. The establishment of capitation payments usually requires the performance of risk adjustment. The purposes of this study were to develop a diagnosis-based risk adjustment model for the NHI and to evaluate its predictability. METHODS: Using a 2% random sample of 371,620 NHI enrollees, the authors developed a Taiwan version of the Principal Inpatient Diagnosis Cost Groups (TPIPDCGs) from 1996 claim records to predict an individual's expenditure in 1997. Weighted least squares regression models were built in an estimation sample (two-thirds of the study sample), and were cross-validated in a validation sample (the remaining one-third of the study sample). Predictive R2 and predictive ratios were used to evaluate the model's predictability. RESULTS: Only 7.88% of the study sample could be classified into 1 of the 16 TPIPDCGs. Combined with demographic variables, which alone could explain 3.7% of the variation in an individual's future expenditure, the risk adjustment model based on TPIPDCGs could explain 12.2% of expenditure variation. In addition, the finding that the predictive ratios of the TPIPDCG model approximated unity better than those of the demographic model in all subgroups indicates that the capitation payment as predicted by the TPIPDCG model for each subgroup would better correlate to the actual spending. CONCLUSION: Taiwan's risk-adjusted capitation model based on principal inpatient diagnoses has higher predictability on individual's future expenditure than its counterpart in the USA. This finding provides insight into not only the development of Taiwan's diagnosis-based risk adjustment models but also the necessity of modification when applying foreign-developed risk adjustment models to the NHI.     

Lecithin vesicles for topical delivery of diclofenac.

Skin penetration of topically applied diclofenac is important for the treatment of rheumatic diseases and actinic keratoses. We have studied the permeation of diclofenac across human cadaver epidermis in-vitro from four lecithin vesicle formulations and a few marketed semi-solid preparations. The lecithin vesicle formulations were prepared by dissolving the lipid contents (lecithin and sodium cholate) in a 1:1 mixture of methanol-chloroform, evaporating the solvents under vacuum, and hydrating the lipid layer with the drug solution in water or 10% ethanol. The vesicles were sonicated for 5 min to reduce the vesicle size and their size and Zeta potential were characterized. The cumulative amount and maximum flux of diclofenac was 69.7+/-40.3 micrograms and 4.77+/-3.16 micrograms/hcm(2) from lecithin vesicles containing sodium cholate and 10% ethanol, and is the highest of all formulations studied. The cumulative amount and mean maximum flux obtained from other formulations were in the range of 2.46+/-1.98-29.9+/-10.1 micrograms and 0.53+/-0.46-3.61+/-0.86 micrograms/hcm(2). Based on the results, lecithin vesicles of diclofenac appear to be advantageous for the topical delivery of diclofenac.     

Treatment of horizontal root‐fractured maxillary incisors – a case report

Abstract – Traumatic dental injuries often occur to the teeth and their supporting tissues and they are the main reasons for emergency visit to a dental clinic. Management of a fracture depends on its position and the extent of root involvement. Horizontal root fractures are not seen frequently and the treatment consists of reduction and long‐term rigid fixation of the coronal segment. The present case demonstrates the successful management of two horizontally fractured maxillary central incisors with a follow‐up period of 9 months.     

Working‐correlation‐structure identification in generalized estimating equations

Selecting an appropriate working correlation structure is pertinent to clustered data analysis using generalized estimating equations (GEE) because an inappropriate choice will lead to inefficient parameter estimation. We investigate the well‐known criterion of QIC for selecting a working correlation structure, and have found that performance of the QIC is deteriorated by a term that is theoretically independent of the correlation structures but has to be estimated with an error. This leads us to propose a correlation information criterion (CIC) that substantially improves the QIC performance. Extensive simulation studies indicate that the CIC has remarkable improvement in selecting the correct correlation structures. We also illustrate our findings using a data set from the Madras Longitudinal Schizophrenia Study. Copyright © 2008 John Wiley & Sons, Ltd.