Using statutory health insurance data to evaluate non-response in a cross-sectional study on depression among patients with diabetes in Germany.

BACKGROUND: Low response rates do not indicate poor representativeness of study populations if non-response occurs completely at random. A non-response analysis can help to investigate whether non-response is a potential source for bias within a study. METHODS: A cross-sectional survey among a random sample of a health insurance population with diabetes (n = 3642, 58.9% male, mean age 65.7 years), assessing depression in diabetes, was conducted in 2013 in Germany. Health insurance data were available for responders and non-responders to assess non-response bias. The response rate was 51.1%. Odds ratios (ORs) for responses to the survey were calculated using logistic regression taking into consideration the depression diagnosis as well as age, sex, antihyperglycaemic medication, medication utilization, hospital admission and other comorbidities (from health insurance data). RESULTS: Responders and non-responders did not differ in the depression diagnosis [OR 0.99, confidence interval (CI) 0.82-1.2]. Regardless of age and sex, treatment with insulin only (OR 1.73, CI 1.36-2.21), treatment with oral antihyperglycaemic drugs (OAD) only (OR 1.77, CI 1.49-2.09), treatment with both insulin and OAD (OR 1.91, CI 1.51-2.43) and higher general medication utilization (1.29, 1.10-1.51) were associated with responding to the survey. CONCLUSION: We found differences in age, sex, diabetes treatment and medication utilization between responders and non-responders, which might bias the results. However, responders and non-responders did not differ in their depression status, which is the focus of the DiaDec study. Our analysis may serve as an example for conducting non-response analyses using health insurance data.

Healthcare provision, functional ability and quality of life after proximal femoral fracture - 'ProFem': Study protocol of a population-based, prospective study based on individually linked survey and statutory health insurance data.

INTRODUCTION: Proximal femoral fractures (PFF) are among the most frequent fractures in older people. However, the situation of people with a PFF after hospital discharge is poorly understood. Our aim is to (1) analyse healthcare provision, (2) examine clinical and patient-reported outcomes (PROs), (3) describe clinical and sociodemographic predictors of these and (4) develop an algorithm to identify subgroups with poor outcomes and a potential need for more intensive healthcare. METHODS AND ANALYSIS: This is a population-based prospective study based on individually linked survey and statutory health insurance (SHI) data. All people aged minimum 60 years who have been continuously insured with the AOK Rheinland/Hamburg and experience a PFF within 1 year will be consecutively included (SHI data analysis). Additionally, 700 people selected randomly from the study population will be consecutively invited to participate in the survey. Questionnaire data will be collected in the participants' private surroundings at 3, 6 and 12 months after hospital discharge. If the insured person considers themselves to be only partially or not at all able to take part in the survey, a proxy person will be interviewed where possible. SHI variables include healthcare provision, healthcare costs and clinical outcomes. Questionnaire variables include information on PROs, lifestyle characteristics and socioeconomic status. We will use multiple regression models to estimate healthcare processes and outcomes including mortality and cost, investigate predictors, perform non-responder analysis and develop an algorithm to identify vulnerable subgroups. ETHICS AND DISSEMINATION: The study was approved by the ethics committee of the Faculty of Medicine, Heinrich-Heine-University Düsseldorf (approval reference 6128R). All participants including proxies providing written and informed consent can withdraw from the study at any time. The study findings will be disseminated through scientific journals and public information. TRIAL REGISTRATION NUMBER: DRKS00012554.