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A stakeholder-inclusive conceptual framework for modeling routinely collected health data for therapeutic decision-making illustrated by means of multistate models.

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Title: A stakeholder-inclusive conceptual framework for modeling routinely collected health data for therapeutic decision-making illustrated by means of multistate models.
Authors: Pfaffenlehner M; Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany. michelle.pfaffenlehner@uniklinik-freiburg.de.; Freiburg Center for Data Analysis, Modeling and AI, University of Freiburg, Freiburg, Germany. michelle.pfaffenlehner@uniklinik-freiburg.de., Dreßing A; Department of Neurology and Clinical Neuroscience, Medical Center, Faculty of Medicine, University of Freiburg, University of Freiburg, Freiburg, Germany.; Freiburg Brain Imaging Center, Faculty of Medicine, Medical Center, University of Freiburg, University of Freiburg, Freiburg, Germany., Knoerzer D; Roche Pharma AG, Grenzach, Germany., Wagner M; Stiftung Deutsche Schlaganfall-Hilfe, Gütersloh, Germany., Heuschmann P; Institute for Medical Data Sciences, University Hospital Würzburg, Würzburg, Germany.; Institute for Clinical Epidemiology and Biometry, University Würzburg, Würzburg, Germany., Scherag A; Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany.; Center for Clinical Studies, Jena University Hospital - Friedrich Schiller University Jena, Jena, Germany., Binder H; Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.; Freiburg Center for Data Analysis, Modeling and AI, University of Freiburg, Freiburg, Germany., Binder N; Freiburg Center for Data Analysis, Modeling and AI, University of Freiburg, Freiburg, Germany.; Institute of General Practice/Family Medicine, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
Corporate Authors: EVA4MII project
Source: BMC medical research methodology [BMC Med Res Methodol] 2026 Jul 14; Vol. 26 (1). Date of Electronic Publication: 2026 Jul 14.
Publication Type: Journal Article
Language: English
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE
Imprint Name(s): Original Publication: London : BioMed Central, [2001-
MeSH Terms: Clinical Decision-Making*/methods , Data Collection*/methods , Data Collection*/statistics & numerical data , Stakeholder Participation*, Outcome Assessment, Health Care/methods ; Outcome Assessment, Health Care/statistics & numerical data ; Humans ; Decision Making ; Reproducibility of Results ; Patient Advocacy
Abstract: Background: Routinely collected health data are increasingly used to generate real-world evidence for therapeutic decision-making. Their use, however, depends on the expectations of multiple stakeholders. Clinicians require clinically interpretable analyses, pharmaceutical stakeholders need robust evidence on effectiveness and safety, patient advocacy groups emphasize transparency, privacy, and meaningful outcome measures, and statisticians focus on bias control, reproducibility, and methodological rigor. Without explicit consideration of these perspectives, analyses risk being fragmented, misaligned with end-user needs, or lacking transparency. Aligning these perspectives early in the design of routine data analyses therefore remains a central challenge.
Methods: We developed a stakeholder-inclusive conceptual framework for modeling routine health data, through expert panel discussions, an interdisciplinary workshop and targeted literature examples. The synthesis focused on four stakeholder perspectives: clinicians, pharmaceutical industry, patient advocates, and statisticians. To illustrate how stakeholder priorities can be translated into analytical strategies, we reviewed selected applications of multistate models (MSMs) in routine health data settings.
Results: The conceptual framework links stakeholder-specific priorities, methodological requirements and identifies shared needs for analyses that are clinically meaningful, transparent, reproducible, and able to represent patient pathways, intermediate events, treatment trajectories, disease progression, safety outcomes, and patient-reported measures. While the framework is intended to be applicable across various analytical approaches MSMs are used here to illustrate how these diverse requirements can be operationalized in practice. They can capture longitudinal health processes, competing events, recurrent or intermediate states, and state-specific outcomes while retaining an interpretable graphical structure, and the reviewed examples show their applicability across different research questions using routine health data. Beyond specific methodological choices, clinical research relies fundamentally on statistical expertise. The framework also highlights that the statistician's role varies with the complexity of the research question, ranging from consultation on standard analyses to adaptation or development of advanced methods.
Conclusions: The stakeholder-inclusive framework provides methodological guidance for designing analyses of routine health data that are clinically meaningful, scientifically rigorous, and socially acceptable. By aligning the research question with the intended perspective from the beginning, it supports more robust and transparent evidence generation, with multistate models serving as a flexible tool to operationalize this integration.
(© 2026. The Author(s).)
Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: Peter Heuschmann reports research grants from the German Federal Ministry of Research, Technology and Space for the conduct of the study; he reports research grants from the German Federal Ministry of Research, Technology and Space, German Research Foundation, Federal Joint Committee (G-BA) within the Innovationfond, German Cancer Aid, German Heart Foundation, Bavarian State, European Union, Robert Koch Institute, University Hospital Heidelberg (within RASUNOA-prime; supported by an unrestricted research grant to the University Hospital Heidelberg from Bayer, BMS, Boehringer-Ingelheim, Daiichi Sankyo), outside the submitted work. The remaining authors have nothing to disclose.
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Contributed Indexing: Keywords: Conceptual framework; Decision-making; Multistate models; Real-world evidence; Routine data; Stakeholder perspectives
Entry Date(s): Date Created: 20260713 Date Completed: 20260714 Latest Revision: 20260726
Update Code: 20260726
PubMed Central ID: PMC13366620
DOI: 10.1186/s12874-026-02946-6
PMID: 42443777
Database: MEDLINE
Description
ISSN:1471-2288
DOI:10.1186/s12874-026-02946-6