Implementing Exercise = Medicine in routine clinical care; needs for an online tool and key decisions for implementation of Exercise = Medicine within two Dutch academic hospitals

PIE M Consortium, Adrie Bouma*, Femke van Nassau, Joske Nauta, Leonie L. Krops, Hidde van der Ploeg, Evert Verhagen, Lucas van der Woude, Helco van Keeken, Rienk Dekker

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

1 Citaat (Scopus)
55 Downloads (Pure)


Background There is much evidence to implement physical activity interventions for medical reasons in healthcare settings. However, the prescription of physical activity as a treatment, referring to as 'Exercise is Medicine' (E = M) is currently mostly absent in routine hospital care in The Netherlands. To support E = M prescription by clinicians in hospitals, this study aimed: (1) to develop an E = M-tool for physical activity advice and referrals to facilitate the E = M prescription in hospital settings; and (2) to provide an E = M decision guide on key decisions for implementation to prepare for E = M prescription in hospital care. Methods A mixed method design was used employing a questionnaire and face-to-face interviews with clinicians, lifestyle coaches and hospital managers, a patient panel and stakeholders to assess the needs regarding an E = M-tool and key decisions for implementation of E = M. Based on the needs assessment, a digital E = M-tool was developed. The key decisions informed the development of an E = M decision guide. Results An online supportive tool for E = M was developed for two academic hospitals. Based on the needs assessment, linked to the different patients' electronic medical records and tailored to the two local settings (University Medical Center Groningen, Amsterdam University Medical Centers). The E = M-tool existed of a tool algorithm, including patient characteristics assessed with a digital questionnaire (age, gender, PA, BMI, medical diagnosis, motivation to change physical activity and preference to discuss physical activity with their doctor) set against norm values. The digital E = M-tool provided an individual E = M-prescription for patients and referral options to local PA interventions in- and outside the hospital. An E = M decision guide was developed to support the implementation of E = M prescription in hospital care. Conclusions This study provided insight into E = M-tool development and the E = M decision-making to support E = M prescription and facilitate tailoring towards local E = M treatment options, using strong stakeholder participation. Outcomes may serve as an example for other decision support guides and interventions aimed at E = M implementation.

Originele taal-2English
Aantal pagina's15
TijdschriftBMC Medical Informatics and Decision Making
Nummer van het tijdschrift1
StatusPublished - 22-sep.-2022

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