Minimizing population health loss due to scarcity in OR capacity: validation of quality of life input

BMC Medical Research Methodology

Research

Eline Krijkamp¹  Guy Widdershoven²  Jan Busschbach³  C. René Leemans⁴  Kira S. van Hof⁵  Rob Baatenburg de Jong⁵  Anouk M.I.A. van Alphen⁵  Benjamin Y. Gravesteijn⁶  Hester Lingsma⁷  Henriëtte van der Horst⁸  Franck Asselman⁹  Leonie Baatenburg de Jong^1,10 

[1] Department of Epidemiology, Erasmus University Medical Center, currently employed by the Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, the Netherlands;Department of Ethics, Law and Humanities, Amsterdam University Medical Centres, Vrije Universiteit, Amsterdam, Netherlands;Department of Medical Psychology, Erasmus University Medical Center, Rotterdam, the Netherlands;Department of Otolaryngology – Head and Neck Surgery, Amsterdam University Medical Centres, Cancer Center Amsterdam, Vrije Universiteit, Amsterdam, Netherlands;Department of Otorhinolaryngology, Erasmus University Medical Center, Rotterdam, the Netherlands;Department of Otorhinolaryngology, Erasmus University Medical Center, Rotterdam, the Netherlands;Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands;Department of Obstetrics & Gynaecology, OLVG, Amsterdam, Netherlands;Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands;Department of general practice, Amsterdam University Medical Centers Vrije Universiteit, Amsterdam, Netherlands;Strategy & Innovation department, Amsterdam University Medical Centers, Amsterdam, the Netherlands;University of Amsterdam, Amsterdam, Netherlands;

关键词: Validation;    Value based health care;    Prioritization;    Surgery;    Decision modeling;    Quality of life;   

DOI  :  10.1186/s12874-022-01818-z

 received in 2022-01-26, accepted in 2022-12-09,  发布年份 2022

来源: Springer

【 摘 要 】

ObjectivesA previously developed decision model to prioritize surgical procedures in times of scarce surgical capacity used quality of life (QoL) primarily derived from experts in one center. These estimates are key input of the model, and might be more context-dependent than the other input parameters (age, survival). The aim of this study was to validate our model by replicating these QoL estimates.MethodsThe original study estimated QoL of patients in need of commonly performed procedures in live expert-panel meetings. This study replicated this procedure using a web-based Delphi approach in a different hospital. The new QoL scores were compared with the original scores using mixed effects linear regression. The ranking of surgical procedures based on combined QoL values from the validation and original study was compared to the ranking based solely on the original QoL values.ResultsThe overall mean difference in QoL estimates between the validation study and the original study was − 0.11 (95% CI:  -0.12 - -0.10). The model output (DALY/month delay) based on QoL data from both studies was similar to the model output based on the original data only: The Spearman’s correlation coefficient between the ranking of all procedures before and after including the new QoL estimates was 0.988.DiscussionEven though the new QoL estimates were systematically lower than the values from the original study, the ranking for urgency based on health loss per unit of time delay of procedures was consistent. This underscores the robustness and generalizability of the decision model for prioritization of surgical procedures.

【 授权许可】

CC BY   
© The Author(s) 2023

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