"I must, and I can live with that": a thematic analysis of patients' perspectives on polypharmacy and a digital decision support system for GPs.

BACKGROUND: To investigate patients' perspectives on polypharmacy and the use of a digital decision support system to assist general practitioners (GPs) in performing medication reviews. METHODS: Qualitative interviews with patients or informal caregivers recruited from participants in a cluster-randomized controlled clinical trial (cRCT). The interviews were transcribed verbatim and analyzed using thematic analysis. RESULTS: We conducted 13 interviews and identified the following seven themes: the patients successfully integrated medication use in their everyday lives, used medication plans, had both good and bad personal experiences with their drugs, regarded their healthcare providers as the main source of medication-related information, discussed medication changes with their GPs, had trusting relationships with them, and viewed the use of digital decision support tools for medication reviews positively. No unwanted adverse effects were reported. CONCLUSIONS: Despite drug-related problems, patients appeared to cope well with their medications. They also trusted their GPs, despite acknowledging polypharmacy to be a complex field for them. The use of a digital support system was appreciated and linked to the hope that reasons for selecting specific medication regimens would become more comprehensible. Further research with a more diverse sampling might add more patient perspectives. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03430336 . Registered on February 6, 2018.

Anthropometrical differences between suicide and other non-natural death circumstances: an autopsy study.

BACKGROUND: In international epidemiological studies, associations between suicides and body height, or body mass index (BMI) were found. Because of the recently growing number of suicides in Germany, a closer look on different anthropometric measures of suicide victims autopsied at the Institute of Forensic Medicine of the Goethe-University in Frankfurt/Main, Germany, was taken. METHOD: A retrospective analysis of 1,271 non-natural death cases autopsied between 2006 and 2010 was performed. A total of 566 other than suicide (control group) and 245 suicide cases (study group) with a given body height and weight aged between 18 and 96 years were examined. RESULTS: Body mass indices of the 18-59-year-old male and 60-79-year-old female suicide victims were significantly lower. Old-aged women who committed suicide exhibited beside a significant lower body mass a significantly slender body shape measured as smaller pelvic circumference, waist circumference, and waist-to-tallness ratio. Self-poisoning was by far the leading suicide method in both genders. The victims of the suicide method hanging were the youngest on average, and this method was most common in the male underweight and female lightly normal weight BMI categories, whereas old, overweight, and obese men killed themselves predominantly with firearms. CONCLUSION: The analysis showed that body measures of suicide cases in comparison to other non-natural death circumstance cases differ. For criminal procedural reasons, all suicide cases should be autopsied. But high autopsy rates are also needed for scientific research and to ensure a high level of patient safety.

[The QR code in society, economy and medicine--fields of application, options and chances]. / Der QR Code in Gesellschaft, Wirtschaft und Medizin--Anwendungsbeispiele, Möglichkeiten und Chancen.

2D codes like the QR Code ("Quick Response") are becoming more and more common in society and medicine. The application spectrum and benefits in medicine and other fields are described. 2D codes can be created free of charge on any computer with internet access without any previous knowledge. The codes can be easily used in publications, presentations, on business cards and posters. Editors choose between contact details, text or a hyperlink as information behind the code. At expert conferences, linkage by QR Code allows the audience to download presentations and posters quickly. The documents obtained can then be saved, printed, processed etc. Fast access to stored data in the internet makes it possible to integrate additional and explanatory multilingual videos into medical posters. In this context, a combination of different technologies (printed handout, QR Code and screen) may be reasonable.

Predicting hospital admissions from individual patient data (IPD): an applied example to explore key elements driving external validity.

OBJECTIVE: To explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients. STUDY DESIGN AND SETTING: Using individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV). RESULTS: Prior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions. CONCLUSIONS: Predictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully. TRIAL REGISTRATION NUMBER: PROSPERO id: CRD42018088129.

Effectiveness of the application of an electronic medication management support system in patients with polypharmacy in general practice: a study protocol of cluster-randomised controlled trial (AdAM).

INTRODUCTION: Clinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy. METHODS AND ANALYSIS: Planned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter. SCOPE: general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients. POPULATION: patients (≥18 years) with polypharmacy (≥5 prescriptions). SAMPLE SIZE: initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved. INTERVENTION: complex intervention eMMa. FOLLOW-UP: at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa. OUTCOMES: primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse. STATISTICAL ANALYSIS: primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints. ETHICS AND DISSEMINATION: Trial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences. TRIAL REGISTRATION: NCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

Predicting negative health outcomes in older general practice patients with chronic illness: Rationale and development of the PROPERmed harmonized individual participant data database.

The prevalence of multimorbidity and polypharmacy increases significantly with age and are associated with negative health consequences. However, most current interventions to optimize medication have failed to show significant effects on patient-relevant outcomes. This may be due to ineffectiveness of interventions themselves but may also reflect other factors: insufficient sample sizes, heterogeneity of population. To address this issue, the international PROPERmed collaboration was set up to obtain/synthesize individual participant data (IPD) from five cluster-randomized trials. The trials took place in Germany and The Netherlands and aimed to optimize medication in older general practice patients with chronic illness. PROPERmed is the first database of IPD to be drawn from multiple trials in this patient population and setting. It offers the opportunity to derive prognostic models with increased statistical power for prediction of patient-relevant outcomes resulting from the interplay of multimorbidity and polypharmacy. This may help patients from this heterogeneous group to be stratified according to risk and enable clinicians to identify patients that are likely to benefit most from resource/time-intensive interventions. The aim of this manuscript is to describe the rationale behind PROPERmed collaboration, characteristics of the included studies/participants, development of the harmonized IPD database and challenges faced during this process.

A prognostic model predicted deterioration in health-related quality of life in older patients with multimorbidity and polypharmacy.

OBJECTIVES: To develop and validate a prognostic model to predict deterioration in health-related quality of life (dHRQoL) in older general practice patients with at least one chronic condition and one chronic prescription. STUDY DESIGN AND SETTING: We used individual participant data from five cluster-randomized trials conducted in the Netherlands and Germany to predict dHRQoL, defined as a decrease in EQ-5D-3 L index score of ≥5% after 6-month follow-up in logistic regression models with stratified intercepts to account for between-study heterogeneity. The model was validated internally and by using internal-external cross-validation (IECV). RESULTS: In 3,582 patients with complete data, of whom 1,046 (29.2%) showed deterioration in HRQoL, and 12/87 variables were selected that were related to single (chronic) conditions, inappropriate medication, medication underuse, functional status, well-being, and HRQoL. Bootstrap internal validation showed a C-statistic of 0.71 (0.69 to 0.72) and a calibration slope of 0.88 (0.78 to 0.98). In the IECV loop, the model provided a pooled C-statistic of 0.68 (0.65 to 0.70) and calibration-in-the-large of 0 (-0.13 to 0.13). HRQoL/functionality had the strongest prognostic value. CONCLUSION: The model performed well in terms of discrimination, calibration, and generalizability and might help clinicians identify older patients at high risk of dHRQoL. REGISTRATION: PROSPERO ID: CRD42018088129.