Ten-Year Evaluation of the Population-Based Integrated Health Care System "Gesundes Kinzigtal"

Abstract

Background: The population-based integrated health care system called "Gesundes Kinzigtal" (Integrierte Versorgung Gesundes Kinzigtal, IVGK) was initiated more than 10 years ago in the Kinzig River Valley region, which is located in the Black Forest in the German state of Baden-Württemberg. IVGK is intended to optimize health care while maximizing cost-effectiveness. It consists of programs for promoting health and for enabling cooperation among service providers, as well as of a shared-savings contract that has enabled resources to be saved every year. The goal of the present study was to investigate trends in the quality of care provided by IVGK over the past ten years in comparison to conventional care.

Methods: This is a non-randomized observational study with a control-group design (Kinzig River Valley versus 13 structurally comparable control regions), employing data collected by AOK, a large statutory health-insurance provider in Germany, over the period 2006-2015. Quality assessment was conducted with the aid of a set of indicators, developed by the authors, that was based exclusively on claims data. The statistical analysis of the trends in these indicators over time was conducted with preset criteria for the relevance of any observed changes, as well as preset mechanisms of controlling for confounding factors.

Results: For 88 of the 101 evaluable indicators, no relevant difference was seen between the trend over time in the region of the intervention and the average trend in the control regions. Relevant differences in favor of the IVGK were observed for six indicators, and negatively divergent trends compared to the controls were observed for seven indicators. In the main summarizing statistical analysis, no positive or negative difference was found between the Kinzig River Valley and the other regions with respect to trends in the health-care indicators over time.

Conclusion: An evaluation based on 101 indicators derived from health-insurance data did not reveal any improvement of the quality of care by IVGK and the totality of the programs that were implemented under it. However, under the conditions of the shared-savings contract, no relevant diminution in the quality of care was observed over a period of 10 years either, compared with structurally similar control regions without an integrated care model.

Figure 1

Temporal trends of two indicators showing a relevant difference in a comparison of the Kinzig River Valley (KT) region with the control regions a) An example of a positive trend in KT: heart failure (indicator 1.3)—Prescription of anti-inflammatory drugs: moderately positive hint b) An example of a negative trend in KT: myocardial infarction (indicator 14.1)—ACE inhibitors/ARBs for left ventricular dysfunction: moderately negative hint ACE, angiotensin converting enzyme; ARB, angiotensin II receptor blocker; KT, Kinzig River Valley; BW, Baden-Württemberg

Figure 2

Summarizing result of the indicator analysis. Representation of the evidence for the summary statistic S_hint with a two-sided p-value under the null hypothesis that S_hint in the Kinzig River Valley region is equal to the mean in the control regions KT, Kinzigtal; S_hint, total points for “positive hints” and “negative hints” (Table 3, eTable 4, eMethods)

eFigure 1

Estimation of the trend difference between intervention region and control regions. The Figure shows the results regarding the trend difference for all directed indicators; to ensure uniform presentation across indicators, these were re-coded in such a way that a numerically positive trend difference always means an advantage for the Kinzig River Valley region compared to the control regions (“directed trend difference”). The individual indicators are plotted on the x-axis; the y-axis shows the re-coded differences in trend estimates between the Kinzig River Valley and the control regions with a 95% confidence interval. The result was sorted according to the size of the re-coded trend difference.

eFigure 4

Mortality: change in deaths per 100 insured persons over 5 years Bell curve showing the variance in trends in the control regions

eFigure 5a

Proportion of patients with uncomplicated cystitis that were prescribed fluoroquinolones and/or cephalosporins as first-line antibiotics

eFigure 5b

Proportion of patients with uncomplicated cystitis that were prescribed fluoroquinolones and/or cephalosporins as first-line antibiotics

eFigure 5c

Proportion of patients with uncomplicated cystitis that were prescribed fluoroquinolones and/or cephalosporins as first-line antibiotics

eFigure 6a

Proportion of urinary tract infection patients that were prescribed reserve antibiotics* in the previous 12 months a) Prevalence of treatment with reserve antibiotics

eFigure 6b

Proportion of urinary tract infection patients that were prescribed reserve antibiotics* in the previous 12 months b) Change in treatment prevalence over 5 years; bell curve showing the variance in trends in the control regions

eFigure 6c

Proportion of urinary tract infection patients that were prescribed reserve antibiotics* in the previous 12 months c) The forest plot shows the change in the prevalence of treatment with reserve antibiotics in patients with urinary tract infection

eFigure 7a

Overall evidence for summary statistic S_diff and summary statistic S_IzI a) Representation of the overall evidence for the summary statistic S_diff with a two-sided p-value under the null hypothesis that S_diff in the Kinzig River Valley region is equal to the mean in the control regions

eFigure 7b

Overall evidence for summary statistic S_diff and summary statistic S_IzI b) Overall evidence for the summary statistic S_IzI; the dotted reference lines relate to the properties of absolute z-scores.*