Predictive modeling to identify potential participants of a disease management program hypertension.

BACKGROUND: Based on the premise of limited health-care resources, decision-makers pursue to allocate disease management programs (DMP) more targeted. METHODS: Based on routine data from a private health insurance company, a prediction model was developed to estimate the individual risk for future in-patient stays of patients eligible for a DMP Hypertension. The database included anonymous claims data of 38,284 policyholders with a diagnosis in the year 2013. A cutoff point of ≥70% was used for selecting candidates with a risk for future hospitalization. Using a logistic regression model, we estimated the model's prognostic power, the occurrence of clinical events, and the resource use. RESULTS: Overall, the final model shows acceptable prognostic power (detection rate = 64.3%; sensitivity = 68.7%; positive predictive value (PPV) = 64.1%, area under the curve (AUC) = 0.72). The comparison between the selected hypothetical DMP-group with a predicted (LOH) ≥70% showed additional costs of about 69% for the DMP-group compared to insure with a LOH <70%. CONCLUSION: The predictive analytical approach may identify potential DMP participants with a high risk of increased health services utilization and in-patient stays.

[Patient-oriented healthcare programs. Concepts and practical experience in the field of chronic heart failure]. / Patientenzentrierte Gesundheitsprogramme. Konzeption und praktische Erfahrungen am Beispiel der Indikation chronische Herzinsuffizenz.

Disease management programs (DMP) have been recently introduced in the German statutory healthcare sector by federal law. These compulsory programs are aimed at enhancing guideline-based treatment by primary care physicians. Based on a systematic analysis of disease models and deficits in healthcare delivery, patient-oriented DMP offer an alternative approach. Their standardized services include care calls, written educational material, reminder systems, health reports, and optional telemetric monitoring. As an example of this approach, the medical results of 151 patients participating in a comprehensive chronic heart failure (CHF) program were evaluated. Within the observation period of 12 months, the number of patients receiving appropriate prescriptions (ACE inhibitors, diuretics, or beta blockers) rose significantly. In many patients there was a remission of CHF key symptoms (leg edema, shortness of breath, dizziness). The daily weight monitoring was particularly appreciated by the patients. For further development of patient-oriented DMP in the German healthcare system, it will be crucial that financial savings can be convincingly demonstrated besides the clinical benefits. These include quality of life, particularly for those chronic conditions in which patient self-management has a large impact on disease course.

Germany's disease management program: improving outcomes in congestive heart failure.

Hospital admissions among patients with congestive heart failure (CHF) are a major contributor to health care costs. A comprehensive disease management program for CHF was developed for private and statutory health insurance companies in order to improve health outcomes and reduce rehospitalization rates and costs. The program comprises care calls, written training material, telemetric monitoring, and health reports. Currently, 909 members from six insurance companies are enrolled. Routine evaluation, based on medical data warehouse software, demonstrates benefits in terms of improved health outcomes and processes of care. Economical evaluation of claims data indicates significant cost savings in a pre/post study design.