A Pay-For-Performance Program In Taiwan Improved Care For Some Diabetes Patients, But Doctors May Have Excluded Sicker Ones

The role of foot self-care behavior on developing foot ulcers in diabetic patients with peripheral neuropathy: a prospective study

BACKGROUND

Although foot self-care behavior is viewed as beneficial for the prevention of diabetic foot ulceration, the effect of foot self-care behavior on the development of diabetic foot ulcer has received little empirical investigation.

OBJECTIVE

To explore the relationship between foot self-care practice and the development of diabetic foot ulcers among diabetic neuropathy patients in northern Taiwan.

METHODS

A longitudinal study was conducted at one medical center and one teaching hospital in northern Taiwan.

PARTICIPANTS

A total of 295 diabetic patients who lacked sensitivity to a monofilament were recruited. Five subjects did not provide follow-up data; thus, only the data of 290 subjects were analyzed. The mean age was 67.0 years, and 72.1% had six or fewer years of education.

METHODS

Data were collected by a modified version of the physical assessment portion of the Michigan Neuropathy Screening Instrument and the Diabetes Foot Self-Care Behavior Scale. Cox regression was used to analyze the predictive power of foot self-care behaviors.

RESULTS

A total of 29.3% (n=85) of diabetic neuropathy patients developed a diabetic foot ulcer by the one-year follow-up. The total score on the Diabetes Foot Self-Care Behavior Scale was significantly associated with the risk of developing foot ulcers (HR=1.04, 95% CI=1.01-1.07, p=0.004). After controlling for the demographic variables and the number of diabetic foot ulcer hospitalizations, however, the effect was non-significant (HR=1.03, 95% CI=1.00-1.06, p=0.061). Among the foot self-care behaviors, lotion-applying behavior was the only variable that significantly predicted the occurrence of diabetic foot ulcer, even after controlling for demographic variables and diabetic foot ulcer predictors (neuropathy severity, number of diabetic foot ulcer hospitalizations, insulin treatment, and peripheral vascular disease; HR=1.19, 95% CI=1.04-1.36, p=0.012).

CONCLUSIONS

Among patients with diabetic neuropathy, foot self-care practice may be insufficient to prevent the occurrence of diabetic foot ulcer. Instead, lotion-applying behavior predicted the occurrence of diabetic foot ulcers in diabetic patients with neuropathy. Further studies are needed to explore the mechanism of lotion-applying behavior as it relates to the occurrence of diabetic foot ulcer.

The ABCs of incentive-based treatment in health care: a behavior analytic framework to inform research and practice

Behavior plays an important role in health promotion. Exercise, smoking cessation, medication adherence, and other healthy behavior can help prevent, or even treat, some diseases. Consequently, interventions that promote healthy behavior have become increasingly common in health care settings. Many of these interventions award incentives contingent upon preventive health-related behavior. Incentive-based interventions vary considerably along several dimensions, including who is targeted in the intervention, which behavior is targeted, and what type of incentive is used. More research on the quantitative and qualitative features of many of these variables is still needed to inform treatment. However, extensive literature on basic and applied behavior analytic research is currently available to help guide the study and practice of incentive-based treatment in health care. In this integrated review, we discuss how behavior analytic research and theory can help treatment providers design and implement incentive-based interventions that promote healthy behavior.

Setting standards at the forefront of delivery system reform: aligning care coordination quality measures for multiple chronic conditions

The primary study objective is to assess how three major health reform care coordination initiatives (Accountable Care Organizations, Independence at Home, and Community-Based Care Transitions) measure concepts critical to care coordination for people with multiple chronic conditions. We find that there are major differences in quality measurement across these three large and politically important programs. Quality measures currently used or proposed for these new health reform-related programs addressing care coordination primarily capture continuity of care. Other key areas of care coordination, such as care transitions, patient-centeredness, and cross-cutting care across multiple conditions are infrequently addressed. The lack of a comprehensive and consistent measure set for care coordination will pose challenges for healthcare providers and policy makers who seek, respectively, to provide and reward well-coordinated care. In addition, this heterogeneity in measuring care coordination quality will generate new information, but will inhibit comparisons between these care coordination programs.

Performance profiling in primary care: does the choice of statistical model matter?

BACKGROUND

Profiling is increasingly being used to generate input for improvement efforts in health care. For these efforts to be successful, profiles must reflect true provider performance, requiring an appropriate statistical model. Sophisticated models are available to account for the specific features of performance data, but they may be difficult to use and explain to providers.

OBJECTIVE

To assess the influence of the statistical model on the performance profiles of primary care providers. Data Source. Administrative data (2006–2008) on 2.8 million members of a Dutch health insurer who were registered with 1 of 4396 general practitioners.

METHODS

Profiles are constructed for 6 quality measures and 5 resource use measures, controlling for differences in case mix. Models include ordinary least squares, generalized linear models, and multilevel models. Separately for each model, providers are ranked on z scores and classified as outlier if belonging to the 10% with the worst or best performance. The impact of the model is evaluated using the weighted kappa for rankings overall, percentage agreement on outlier designation, and changes in rankings over time.

RESULTS

Agreement among models was relatively high overall (kappa typically .0.85). Agreement on outlier designation was more variable and often below 80%, especially for high outliers. Rankings were more similar for processes than for outcomes and expenses. Agreement among annual rankings per model was low for all models.

CONCLUSIONS

Differences among models were relatively small, but the choice of statistical model did affect the rankings. In addition, most measures appear to be driven largely by chance, regardless of the model that is used. Profilers should pay careful attention to the choice of both the statistical model and the performance measures.