This paper is in the following e-collection/theme issue:

Letters to the Editor (39) Patient-Reported Outcome Measures (PROMs) (275) Diabetes Self-Management (463)

Published on in Vol 24, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36876, first published .
Challenges in Measuring What Matters to Patients With Diabetes. Comment on “Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review”

Challenges in Measuring What Matters to Patients With Diabetes. Comment on “Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review”

Challenges in Measuring What Matters to Patients With Diabetes. Comment on “Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review”

Authors of this article:

Femke Rutters1 Author Orcid Image ;   Ellen Elsman1 Author Orcid Image ;   Lenka Groeneveld1 Author Orcid Image ;   Marlous Langendoen-Gort1 Author Orcid Image ;   Lidwine Mokkink1 Author Orcid Image ;   Caroline Terwee1 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

    Letter to the Editor

    Department of Epidemiology and Data Science, Amsterdam University Medical Centre, Location Vrije Universiteit Amsterdam, Amsterdam, Netherlands

    Corresponding Author:

    Femke Rutters, PhD

    Department of Epidemiology and Data Science

    Amsterdam University Medical Centre, Location Vrije Universiteit Amsterdam

    De Boelelaan 1089a

    Amsterdam, 1081 HV

    Netherlands

    Phone: 31 204445860

    Email: f.rutters@amsterdamumc.nl



    We would like to respond to Wee et al’s paper, “Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review” [1]. We appreciate the herculean effort undertaken to summarize all diabetes-related patient-reported outcome measures (PROMs). However, we have some concerns.

    First, despite the large amount of identified PROMs (N=238), there are still many PROMs missing [1]. In our systematic review of PROMs measuring health-related quality of life (HRQOL) in people with type 2 diabetes (currently under review), which was performed in the same time period and using the same databases, we identified 116 HRQOL PROMS. Of these, >50 were missing in Wee et al’s review [1]. Missing PROMs include, for example, the National Diabetes Register Survey [2], which in our review showed the best content validity. We think this incompleteness is due to a lack of alternative search strategies, such as checking references. We were surprised that the authors [1] identified no papers through hand-searching, while about one-fourth of the included papers in our review were identified through reference checking.

    Second, the authors [1] used the COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) methodology to summarize the evidence on the quality (measurement properties) of the PROMs. However, contrary to the COSMIN guidelines, the quality of the PROMs was not rated for each PROM subscale separately, even though measurement properties can vary among subscales.

    The limitations of this review [1] underscore the problematic status of PROMs in diabetes: there is no consensus on what doctors and scientists want to measure, and it is unclear what is most relevant to measure. The content of the existing PROMs is very heterogeneous; there are too many PROMs out there and many are of questionable validity. This hinders value-based health care and limits the value of PROMs when attempting to determine which treatment works most optimally. More awareness is needed, supported by recent initiatives on developing core outcome sets for people with diabetes [3-5]. We should start using those core outcome sets in our research and care for people with diabetes.

    In conclusion, there is still a need for a high-quality systematic overview of all available PROMs for people with diabetes, with emphasis on the constructs being measured, and a comprehensive evidence synthesis of the measurement properties of all (subscales of) PROMs. This would allow researchers and doctors working with people with diabetes to make informed choices on which PROMs to use for value-based health care.

    Conflicts of Interest

    None declared.

    1. Wee PJL, Kwan YH, Loh DHF, Phang JK, Puar TH, Ostbye T, et al. Measurement Properties of Patient-Reported Outcome Measures for Diabetes: Systematic Review. J Med Internet Res 2021 Aug 13;23(8):e25002 [FREE Full text] [CrossRef] [Medline]
    2. Svedbo Engström M, Leksell J, Johansson UB, Eeg-Olofsson K, Borg S, Palaszewski B, et al. A disease-specific questionnaire for measuring patient-reported outcomes and experiences in the Swedish National Diabetes Register: Development and evaluation of content validity, face validity, and test-retest reliability. Patient Educ Couns 2018 Jan;101(1):139-146. [CrossRef] [Medline]
    3. Dodd S, Harman N, Taske N, Minchin M, Tan T, Williamson PR. Core outcome sets through the healthcare ecosystem: the case of type 2 diabetes mellitus. Trials 2020 Jun 25;21(1):570 [FREE Full text] [CrossRef] [Medline]
    4. Harman NL, Wilding JPH, Curry D, Harris J, Logue J, Pemberton RJ, SCORE-IT Study Team. Selecting Core Outcomes for Randomised Effectiveness trials In Type 2 diabetes (SCORE-IT): a patient and healthcare professional consensus on a core outcome set for type 2 diabetes. BMJ Open Diabetes Res Care 2019 Dec;7(1):e000700 [FREE Full text] [CrossRef] [Medline]
    5. Patient-centered outcome measures: Diabetes. ICHOM Connect. 2019.   URL: https://connect.ichom.org/standard-sets/diabetes/ [accessed 2022-03-25]

    ‎
    COSMIN: Consensus-Based Standards for the Selection of Health Measurement Instruments
    HRQOL: health-related quality of life
    PROM: patient-reported outcome measure

    Edited by T Leung; This is a non–peer-reviewed article. submitted 31.01.22; accepted 21.03.22; published 31.03.22

    Copyright

    ©Femke Rutters, Ellen Elsman, Lenka Groeneveld, Marlous Langendoen-Gort, Lidwine Mokkink, Caroline Terwee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.03.2022.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.