Wender Lin

Diabetes‐Specific or Generic Measures for Health‐Related Quality of Life? Evidence from Psychometric Validation of the D‐39 and SF‐36

OBJECTIVE There is a debate regarding the use of disease-specific versus generic instruments for health-related quality of life (HRQOL) measures. We tested the psychometric properties of HRQOL measures using the Diabetes-39 (D-39) and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). METHODS This was a cross-sectional study collecting data from 280 patients in Taiwan. Exploratory factor analysis was conducted to evaluate construct validity of the two instruments. Known-groups validity was examined using laboratory indicators (fasting, 2-hour postprandial plasma glucose, and hemoglobin A1c), presence of diabetic complications (retinopathy, nephropathy, neuropathy, diabetic foot disorder, cardiovascular and cerebrovascular disorders), and psychosocial variables (sense of well-being and self-reported diabetes severity). Overall discriminative power of the two instruments was evaluated using the C-statistic. RESULTS Three distinct factors were extracted through factor analysis. These factors tapped all subscales of the D-39, fourphysical subscales of the SF-36, and four mental subscales of the SF-36, respectively. Compared with the SF-36, the D-39 demonstrated superior known-groups validity for 2-hour postprandial plasma glucose groups but was inferior for complication groups. Compared with the SF-36, the D-39 discriminated better between self-reported severity known groups, but was inferior between well-being groups. In overall discriminative power, the D-39 discriminated better between laboratory known groups. The SF-36, however, was superior in discriminating between complication known groups. CONCLUSIONS For psychometric properties, the D-39 and the SF-36 were superior to each other in different regards. The combined use of a disease-specific instrument and a generic instrument may be a useful strategy for diabetes HRQOL assessment.

Continuity of diabetes care is associated with avoidable hospitalizations: evidence from Taiwan's National Health Insurance scheme

OBJECTIVE Taiwans health-care system allows patients to utilize specialty services without referrals by primary care providers. This discontinuity of care may lead to increases in future hospitalizations. This study aims to determine whether the discontinuity of care is associated with the risk of hospitalization. DESIGN A secondary data analysis based on a claim data of a nationally representative random sample of diabetic patients in Taiwan. A usual provider continuity (UPC) index was developed-a ratio of the visits to the physician that subjects most usually see relevant to diabetes care to the total physician visits relevant to diabetes care-to investigate its association with the risk of hospitalization. SETTING Taiwans National Health Insurance scheme from 1997 through 2002. PARTICIPANTS Totally 6476 diabetic patients. INTERVENTION(s) None. MAIN OUTCOME MEASURE(s) Diabetes-related short-term and long-term ambulatory care sensitive condition (ACSC) admissions. RESULTS Patients with ACSC admissions had significantly lower UPC scores compared with those without ACSC admissions. Using a Cox regression model that controlling for age, sex, severity of diabetes and the number of total visits, patients with low to medium continuity of care (UPC <0.75) were found to be significantly associated with increased risk of hospitalization as compared with patients with high continuity of care, especially for long-term ACSC admissions (relative risk: 1.336 [1.019-1.751]). CONCLUSIONS Higher continuity of care with usual providers for diabetic care is significantly associated with lower risk of future hospitalization for long-term diabetic complication admissions. To avoid future hospitalization, health policy stakeholders are encouraged to improve the continuity of care through strengthening the provider-patient relationships.

Development of a Risk-Adjusted Capitation Model Based on Principal Inpatient Diagnoses in Taiwan

BACKGROUND AND PURPOSE Taiwans 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 individuals 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 models 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 individuals 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 Taiwans risk-adjusted capitation model based on principal inpatient diagnoses has higher predictability on individuals future expenditure than its counterpart in the USA. This finding provides insight into not only the development of Taiwans diagnosis-based risk adjustment models but also the necessity of modification when applying foreign-developed risk adjustment models to the NHI.

Measuring inequality in physician distributions using spatially adjusted Gini coefficients.

Objective To measure inequality in physician distributions using Gini coefficient and spatially adjusted Gini coefficients. Design Measurements were based on the distribution of physician data from the Taiwan National Health Insurance Research Database (NHIRD) and population data from the Ministry of the Interior in Taiwan. Settings The distribution of population and physicians in Taiwan from 2001 to 2010. Participants This study considered 35 000 physicians who are registered in Taiwan. Main Outcome Measures To calculate the Gini coefficient and spatially adjusted Gini coefficients in Taiwan from 2001 to 2010. Results The Gini coefficient for each year, from 2001 to 2010, ranged from 0.5128 to 0.4692, while the spatially adjusted Gini coefficients based on travel time and travel distance ranged, respectively, from 0.4324 to 0.4066 and from 0.4408 to 0.4178. We found that, in each year, irrespective of the type of spatial adjustment, the spatially adjusted Gini coefficient was smaller than the Gini coefficient itself. Our empirical findings support that the Gini coefficient may overestimate the maldistribution of physicians. Conclusions Our simulations demonstrate that increasing the number of physicians in medium-sized cities (such as capitals of counties or provinces), and/or improving the transportation time between medium-sized cities and rural areas, could be feasible solutions to mitigate the problem of geographical maldistribution of physicians.