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Background: Data on resource use are frequently required for healthcare assessments. Studies on healthcare utilization (HCU) in individuals with mental disorders have analyzed both self-reports and administrative data. Source of data may affect the quality of analysis and compromise the accuracy of results. We sought to ascertain the degree of agreement between self-reports and statutory health insurance (SHI) fund claims data from patients with mental disorders., Methods: Claims data from six German SHI and self-reports were obtained along with a cost-effectiveness analysis performed as a part of a controlled prospective multicenter cohort study conducted in 18 psychiatric hospitals in Germany (PsychCare), including patients with pre-defined psychiatric disorders. Self-reports were collected using the German adaption of the Client Sociodemographic and Service Receipt Inventory (CSSRI) questionnaire with a 6-month recall period. Data linkage was performed using a unique pseudonymized identifier. Missing responses were coded as non-use for all analyses. HCU was calculated for inpatient and outpatient care, day-care services, home treatment, and pharmaceuticals. Concordance was measured using Cohen's Kappa (κ) and intraclass correlation coefficient (ICC). Regression approaches were used to investigate the effect of independent variables on the agreements., Results: In total 274 participants (mean age 47.8 [SD = 14.2] years; 47.08% women) were included in the analysis. No significant differences were observed between the linked and unlinked patients in terms of baseline characteristics. Total agreements values were 63.9% (κ = 0.03; PABAK = 0.28) for outpatient contacts, 69.3% (κ = 0.25; PABAK = 0.39) for medication use, 81.0% (κ = 0.56; PABAK = 0.62) for inpatient days and 86.1% (κ = 0.67; PABAK = 0.72) for day-care services. There was varied quantitative agreement between data sources, with the poorest agreement for outpatient care (ICC [95% CI] = 0.22 [0.10-0.33]) and the best for psychiatric day-care services (ICC [95% CI] = 0.72 [0.66-0.78]). Marital status and time since first treatment positively affected the chance of agreement on utilization of outpatient services., Conclusions: Although there were high levels of absolute agreement, the measures of concordance between administrative records and self-reports were generally minimal to moderate. Healthcare investigations should consider using linked or at least different data sources to estimate HCU for specific utilization areas, where unbiased information can be expected., Trial Registration: This study was part of the multi-center controlled PsychCare trial (German Clinical Trials Register No. DRKS00022535; Date of registration: 2020-10-02)., (© 2023. The Author(s).)

Background: With its digital health application (DiGA)-system, Germany is considered one of Europe's pioneers in the field of evidence-based digital health. Incorporating DiGA into standard medical care must be based on evidence-based success factors; however, a comprehensive overview of the evidence required of scientific studies for their approval is lacking., Objective: The study aims to, (1) identify specific requirements defined by the Federal Institute for Drugs and Medical Devices (German: Bundesinstitut für Arzneimittel- und Medizinprodukte; BfArM) to design adequate studies, proving a positive healthcare effect, and (2) to assess the evidence given for applications permanently listed in the DiGA directory., Methods: A multi-step approach was used: (1) identification of the evidence requirements for applications permanently listed in the DiGA directory, (2) identification of the evidence available supporting them., Results: All DiGA permanently listed in the DiGA directory (13 applications) are included in the formal analysis. Most DiGA addressed mental health (n = 7), and can be prescribed for one or two indications (n = 10). All permanently listed DiGA have demonstrated their positive healthcare effect through a medical benefit, and most of them provide evidence for one defined primary endpoint. All DiGA manufacturers conducted a randomized controlled trial., Discussion: It is striking that- although patient-relevant structural and procedural improvements show high potential for improving care, especially in terms of processes - all DiGA have provided a positive care effect via a medical benefit. Although BfArM accepts study designs with a lower level of evidence for the proof of a positive healthcare effect, all manufacturers conducted a study with a high level of evidence., Conclusion: The results of this analysis indicate that permanently listed DiGA meet higher standards than required by the guideline., (© 2023. The Author(s).)

Background: Data on the burden of community-acquired pneumonia (CAP) and health-care related costs in patients with cancer is scarce. We aimed to estimate the CAP incidence rate, mortality, and healthcare-related costs of CAP patients with different cancer subtypes in Germany., Methods: We used German health claims data of a representative sample of 4 million subjects to conduct cohort studies in patients with a new diagnosis of lung, hematological, breast, gastro-intestinal tract and renal/urinary-tract cancer and a comparator cohort without cancer between 2011 and 2015. CAP cases were identified in both the hospital and ambulatory care setting. Crude and age- and sex-standardized incidence rates (sIR) of CAP and mortality after CAP were calculated. To compare the health care-related costs of cancer patients with and without a diagnosis of CAP, a propensity-score (PS) matched control group was created., Results: The study population comprised of 89,007 patients with cancer. In lung cancer patients, the sIR was increased 21-fold compared to the control cohort. For the other cancer subtypes, the sIR was increased 4.3-fold (hematological malignancies) to 1.7-fold (breast cancer) compared to the control cohort. The 30-day mortality in CAP cases was highest in lung cancer patients with 20.0% and ranged from 7.2 to 18.5% in CAP cases with other cancer subtypes. The highest costs were observed in CAP cases with hematological malignancies with 28,969 € (SD 37,142 €) and the lowest in patients with renal/urinary tract cancer with 17,432 € (SD 19,579 €). The absolute difference in the mean overall costs between CAP cases and controls without CAP ranged from 4,111€ to 9,826€, depending on the cancer type. CAP-related costs were predominantly triggered by substantially elevated hospital costs in CAP cases., Conclusions: The incidence rate of CAP and related mortality is high in patients with cancer with strong variations by cancer subtype. Furthermore, CAP in cancer patients is associated with substantial direct excess costs.