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  • Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice

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General practice / Family practice
Original research
Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice
  1. Beate S Müller1,
  2. Lorenz Uhlmann2,
  3. Peter Ihle3,
  4. Christian Stock2,
  5. Fiona von Buedingen1,
  6. Martin Beyer1,
  7. Ferdinand M Gerlach1,
  8. Rafael Perera4,
  9. Jose Maria Valderas5,
  10. Paul Glasziou6,
  11. Marjan van den Akker1,7,
  12. Christiane Muth1
  1. 1Institute of General Practice, Goethe University Frankfurt, Frankfurt am Main, Hessen, Germany
  2. 2Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Baden-Württemberg, Germany
  3. 3PMV Research Group, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Nordrhein-Westfalen, Germany
  4. 4Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, Oxfordshire, UK
  5. 5APEx Collaboration for Academic Primary Care, University of Exeter Medical School, Exeter, Devon, UK
  6. 6Centre for Research in Evidence-Based Practice, Faculty of Health Sciences and Medicine, Bond University, Gold Coast, Queensland, Australia
  7. 7Department of Family Medicine, School CAPHRI, Maastricht University, Maastricht, Limburg, The Netherlands
  1. Correspondence to Dr Beate S Müller; b.mueller{at}allgemeinmedizin.uni-frankfurt.de

Abstract

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.

  • primary care
  • therapeutics
  • geriatric medicine
  • health services administration & management
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjopen-2020-039747

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    Footnotes

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    • Contributors MB, FMG and CM designed the study. PI, LU and CS analysed the data. BSM, LU, PI, CS, FvB, MB, FMG, RP, JMV, PG, MvdA and CM contributed to the interpretation of the data. CM and BM drafted the manuscript and all authors revised it and subsequent versions of the manuscript critically for important intellectual content. All authors approved the version to be submitted for publication. LU, CS and CM had full access to all data and are responsible for the integrity and the accuracy of the data analysis.

    • Funding This study was supported by the German Statutory Healthcare Insurance Company Techniker Krankenkasse.

    • Competing interests FMG, BSM, MB and CM received grants from the German Statutory Healthcare Insurance Company Techniker Krankenkasse during the course of the study. CS has been employed by Boehringer Ingelheim GmbH & Co KG since October 2019.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement The data sets generated and analysed in the current study are not publicly available, as further analyses are ongoing.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.