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In 2004, Germany introduced a program based on voluntary contracting to strengthen the role of general practice care in the healthcare system. Key components include structured management of chronic diseases, coordinated access to secondary care, data-driven quality improvement, computerized clinical decision-support, and capitation-based reimbursement. Our aim was to determine the long-term effects of this program on the risk of hospitalization of specific categories of high-risk patients. Based on insurance claims data, we conducted a longitudinal observational study from 2011 to 2018 in Baden-Wuerttemberg, Germany. Patients were assigned to one or more of four open cohorts (in 2011, elderly, n = 575,363; diabetes mellitus, n = 163,709; chronic heart failure, n = 82,513; coronary heart disease, n = 125,758). Adjusted for key patient characteristics, logistic regression models were used to compare the hospitalization risk of the enrolled patients (intervention group) with patients receiving usual primary care (control group). At the start of the study and throughout long-term follow-up, enrolled patients in the four cohorts had a lower risk of all-cause hospitalization and ambulatory, care-sensitive hospitalization. Among patients with chronic heart failure and coronary heart disease, the program was associated with significantly reduced risk of cardiovascular-related hospitalizations across the eight observed years. The effect of the program also increased over time. Over the longer term, the results indicate that strengthening primary care could be associated with a substantial reduction in hospital utilization among high-risk patients.
Since 2010, an intensified ambulatory cardiology care programme has been implemented in southern Germany. To improve patient management, the structure of cardiac disease management was improved, guideline-recommended care was supported, new ambulatory medical services and a morbidity-adapted reimbursement system were set up. Our aim was to determine the effects of this programme on the mortality and hospitalisation of enrolled patients with cardiac disorders. We conducted a comparative observational study in 2015 and 2016, based on insurance claims data. Overall, 13,404 enrolled patients with chronic heart failure (CHF) and 19,537 with coronary artery disease (CAD) were compared, respectively, to 8,776 and 16,696 patients that were receiving usual ambulatory cardiology care. Compared to the control group, patients enrolled in the programme had lower mortality (Hazard Ratio: 0.84; 95% CI: 0.77–0.91) and fewer all-cause hospitalisations (Rate Ratio: 0.94; 95% CI: 0.90–0.97). CHF-related hospitalisations in patients with CHF were also reduced (Rate Ratio: 0.76; 95% CI: 0.69–0.84). CAD patients showed a similar reduction in mortality rates (Hazard Ratio: 0.81; 95% CI: 0.76–0.88) and all-cause hospitalisation (Rate Ratio: 0.94; 95% CI: 0.91–0.97), but there was no effect on CAD-related hospitalisation. We conclude that intensified ambulatory care reduced mortality and hospitalisation in cardiology patients.
Background Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.
Methods Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.
Results Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.
Conclusions Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.
Background: Critical incident reporting systems (CIRS) can be an important tool for the identification of organisational safety needs and thus to improve patient safety. In German primary care, CIRS use is obligatory but remains rare. Studies on CIRS implementation in primary care are lacking, but those from secondary care recommend involving management personnel.
Objective: This project aimed to increase CIRS use in 69 practices belonging to a local practice network.
Methods: The intervention consisted of the provision of a web-based CIRS, accompanying measures to train practice teams in error management and CIRS, and the involvement of the network’s management. Three measurements were used: (1) number of incident reports and user access rates to the web-based CIRS were recorded, (2) staff were given a questionnaire addressing incident reporting, error management and safety climate and (3) qualitative reflection conferences were held with network management.
Results: Over 20 months, 17 critical incidents were reported to the web-based CIRS. The number of staff intending to report the next incident online decreased from 42% to 20% of participants. In contrast, the number of practices using an offline CIRS (eg, incident book) increased from 23% to 49% of practices. Practices also began proactively approaching network management for help with incidents. After project completion, participants scored higher in the patient safety climate factor ‘perception of causes of errors’. For many practices, the project provided the first contact with structured error management.
Conclusion: Specific measures to improve the use of CIRS in primary care should focus on network management and practice owners. Practices need basic training on safety culture and error management. Continuing, practices should implement an offline CIRS, before they can profit from the exchange of reports via web-based CIRS. It is crucial that practices receive feedback on incidents, and trained network management personnel can provide such support.