The contribution of comorbidities to mortality in hospitalized patients with heart failure.

BACKGROUND: Heart failure (HF) with reduced ejection fraction (HFrEF) has a worse prognosis than HF with preserved EF (HFpEF). The study aimed to evaluate whether different comorbidity profiles of HFrEF- and HFpEF-patients or HF-specific mechanisms contribute to a greater extent to this difference. METHODS: We linked data from two health insurances to data from a cardiology clinic hospital information system. Patients with a hospitalization with HF in 2005-2011, categorized as HFrEF (EF < 45%) or HFpEF (EF ≥ 45%), were propensity score (PS) matched to controls without HF on comorbidites and medication to assure similar comorbidity profiles of patients and their respective controls. The balance of the covariates in patients and controls was compared via the standardized difference (SDiff). Age-standardized 1-year mortality rates (MR) with 95% confidence intervals (CI) were calculated. RESULTS: 777 HFrEF-patients (1135 HFpEF-patients) were PS-matched to 3446 (4832) controls. Balance between patients and controls was largely achieved with a SDiff < 0.1 on most variables considered. The age-standardized 1-year MRs per 1000 persons in HFrEF-patients and controls were 267.8 (95% CI 175.9-359.8) and 86.1 (95% CI 70.0-102.3). MRs in HFpEF-patients and controls were 166.2 (95% CI 101.5-230.9) and 61.5 (95% CI 52.9-70.1). Thus, differences in MRs between patients and their controls were higher for HFrEF (181.7) than for HFpEF (104.7). CONCLUSIONS: Given the similar comorbidity profiles between HF-patients and controls, the higher difference in mortality rates between HFrEF-patients and controls points more to HF-specific mechanisms for these patients, whereas for HFpEF-patients a higher contribution of comorbidity is suggested by our results.

[Linkage of statutory health insurance data with those of a hospital information system: feasible, but also "useful"?]. / Verknüpfung von Routinedaten der Gesetzlichen Krankenversicherung mit Daten eines Krankenhausinformationssystems: Machbar, aber auch "nützlich"?

AIM: Administrative data are increasingly being linked with other data sources for research purposes in the field of epidemiology and health services research abroad. In Germany, the direct linkage of routine data of statutory health insurance (SHI) providers with other data sources is complicated due to strict data protection requirements. The aim of this analysis was to evaluate an indirect linkage of SHI routine data with data of a hospital information system (HIS). METHODS: The dataset comprised data from 2004 to 2010 from 2 sickness funds and one HIS. In both data sources, hospitalisations were restricted to admissions into one hospital with at least one diagnosis of heart failure. The 2 data sources were linked, in cases of the agreement of the admission and discharge dates, as well as the agreement of at least a certain percentage of diagnoses in HIS data when compared to SHI data (full coding depth). Based on the direct linkage using the pseudonymised insurance number as gold standard, the proposed linkage approach was evaluated by means of test statistics. Furthermore, the completeness of relevant information of the HIS was described. RESULTS: The dataset contained 3 731 hospitalisations from the HIS and 8 172 hospitalisations from the SHI routine data. The sensitivity of the linkage approach was 86.7% in the case of an agreement of at least 30% of the diagnoses and decreased to 41.7% in the case of 100% agreement in the diagnoses. The specificity was almost 100% at all studied cut-offs of agreement. Anthropometric measures and diagnostic information were available only for a small fraction of cases in the data of the HIS, whereas information on the health status and on laboratory information was comparatively complete. CONCLUSION: For the linkage of SHI routine data with complementary data sources, indirect linkage methods can be a valuable alternative in comparison to direct linkage, which is time-consuming with regard to planning and application. Since the proposed approach was used in a relatively small sample and a restricted patient population, a replication using nation-wide data without respective restrictions would require an extension of the algorithm. Furthermore, the large administrative effort seems questionable considering the comparatively high amount of missing values in interesting information in the HIS.

Evaluating methods for intersectoral comparison of quality of care. A routine data analysis of elective percutaneous coronary interventions.

OBJECTIVES: To compare the quality of care regarding the use of elective percutaneous coronary interventions (PCIs) in the inpatient and outpatient setting and to evaluate different methods of confounder control in this context. METHODS: Based on data of three statutory health insurances including more than nine million insurance members, a retrospective cohort study between 2005 and 2009 was conducted. The occurrence of myocardial infarction, stroke, further coronary intervention and death was ascertained following the first PCI in the study period, which was preceded by a one-year period without a PCI. A Cox proportional hazard model was used to assess the influence of the setting of the elective PCI on the risk for complications after the PCI for each outcome separately. Age, sex, the number of diseases of the Elixhauser comorbidity measure, past acute coronary syndrome, coronary artery disease, dyslipidemia, past stroke, past coronary artery bypass surgery and the year of the PCI were included as covariables. The analyses were repeated in a propensity score matched cohort as well as in inverse probability of treatment weighted analyses. RESULTS: The cohort comprised 4,269 patients with an outpatient PCI and 26,044 patients with an inpatient PCI. The majority of the analyses revealed no statistically significant effect of the setting of the PCI on the risk of myocardial infarction, stroke and further coronary interventions, whereas a reduced mortality risk was observed for outpatient PCIs. Similar results were obtained in the propensity score analyses. CONCLUSIONS: The analysis revealed that the adjusted risk for complications following an elective PCI is similar between the inpatient and the outpatient setting. For mortality the risk differed but this might be explained by residual or unmeasured confounding. The different methods applied in this study revealed mostly similar results. Since our study only covered one aspect of quality of care in the field of PCI and did not consider drug treatment in hospital or in the outpatient setting, further studies are needed which include these aspects.

[Use of routine data from statutory health insurances for federal health monitoring purposes]. / Nutzungsmöglichkeiten von Routinedaten der Gesetzlichen Krankenversicherung in der Gesundheitsberichterstattung des Bundes.

Federal health monitoring deals with the state of health and the health-related behavior of populations and is used to inform politics. To date, the routine data from statutory health insurances (SHI) have rarely been used for federal health monitoring purposes. SHI routine data enable analyses of disease frequency, risk factors, the course of the disease, the utilization of medical services, and mortality rates. The advantages offered by SHI routine data regarding federal health monitoring are the intersectoral perspective and the nearly complete absence of recall and selection bias in the respective population. Further, the large sample sizes and the continuous collection of the data allow reliable descriptions of the state of health of the insurants, even in cases of multiple stratification. These advantages have to be weighed against disadvantages linked to the claims nature of the data and the high administrative hurdles when requesting the use of SHI routine data. Particularly in view of the improved availability of data from all SHI insurants for research institutions in the context of the "health-care structure law", SHI routine data are an interesting data source for federal health monitoring purposes.