MSmonitor-plus program and video calling care (MPVC) for multidisciplinary care and self-management in multiple sclerosis: study protocol of a single-center randomized, parallel-group, open label, non-inferiority trial

M Hoving, P J Jongen, S M A A Evers, M A Edens, E M P E Zeinstra, M Hoving, P J Jongen, S M A A Evers, M A Edens, E M P E Zeinstra

Abstract

Background: We designed a new multi-modal version of the MSmonitor, called the MSmonitor-Plus and Video calling Care (MPVC), a self-management and education program with e-health interventions that combines frequent use of specific questionnaires with video calling in treating multiple sclerosis (MS) patients.

Objective: To assess the effectiveness, cost-effectiveness and feasibility of MPVC compared to care as usual (CAU), with the goal of achieving equal or better quality of life for MS patients and their partners/informal caregivers. Our hypothesis is that by using MPVC, monitoring will become more efficient, that patients' self-efficacy, quality of life, and adherence to treatment will improve, and that they will be able to live their lives more autonomously.

Methods: A randomized, parallel-group, open label, non-inferiority trial will be conducted to compare MPVC with CAU in MS patients and their partners/informal caregivers. A total of 208 patients will be included with follow-up measurements for 2 years (at baseline and every 3 months). One hundred four patients will be randomized to MPVC and 104 patients to CAU. Partners/informal caregivers of both groups will be asked to participate. The study will consist of three parts: 1) a clinical effectiveness study, 2) an economic evaluation, and 3) a process evaluation. The primary outcome relates to equal or improved disease-specific physical and mental quality of life of the MS patients. Secondary outcomes relate to self-efficacy, efficiency, cost-effectiveness, autonomy, satisfaction with the care provided, and quality of life of partners/informal caregivers.

Discussion: The idea behind using MPVC is that MS patients will gain more insight into the individual course of the disease and get a better grip on their symptoms. This knowledge should increase their autonomy, give patients more control of their condition and enable them to better and proactively interact with health care professionals. As the consulting process becomes more efficient with the use of MPVC, MS-related problems could be detected earlier, enabling earlier multidisciplinary care, treatment or modification of the treatment. This could have a positive effect on the quality of life for both the MS patient and his/her partner/informal caregiver, reducing health and social costs.

Trial registration: NCT05242731 Clinical Trials.gov. Date of registration: 16 February 2022 retrospectively registered.

Keywords: MSmonitor; MSmonitor-plus; Multiple sclerosis; Quality of life.

Conflict of interest statement

The author(s) declared no potential conflicts of interest with respect to the research.

Dr. P.J. Jongen had received honoraria from Bayer Netherlands for consultancy activities. Dr. E.M.P.E. Zeinstra has received honoraria in connection with studies, teaching, and advisory boards from: Biogen, Genzyme, Merck, Novartis, Roche and Teva.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Flow chart of the study

References

    1. Ziemssen T. Multiple sclerosis beyond EDSS: depression and fatigue. J Neurol Sci. 2009;277(Suppl 1):37.
    1. Kip M, Zimmermann A. Krankheitsbild multiple sklerose. Weißbuch multiple Sklerose. Berlin, Heidelberg: Springer; 2016. pp. 1–12.
    1. Soelberg Sorensen P, Giovannoni G, Montalban X, Thalheim C, Zaratin P, Comi G. The multiple sclerosis care unit. Mult Scler. 2019;25(5):627–636.
    1. Hobart J, Bowen A, Pepper G, Crofts H, Eberhard L, Berger T, et al. International consensus on quality standards for brain health-focused care in multiple sclerosis. Mult Scler. 2019;25(13):1809–1818.
    1. Ziemssen T, Thomas K. Treatment optimization in multiple sclerosis: how do we apply emerging evidence? Expert Rev Clin Immunol. 2017;13(6):509–511.
    1. Baltaxe E, Czypionka T, Kraus M, Reiss M, Askildsen JE, Grenkovic R, et al. Digital health transformation of integrated Care in Europe: overarching analysis of 17 integrated care programs. J Med Internet Res. 2019;21(9):e14956.
    1. Kraus S, Schiavone F, Pluzhnikova A, Invernizzi AC. Digital transformation in healthcare: analyzing the current state-of-research. J Bus Res. 2021;123:557–567.
    1. Ghosh K, Dohan M, Veldandi H. Digital transformation strategies for healthcare providers: perspectives from senior leadership. 2018.
    1. Gopal G, Suter-Crazzolara C, Toldo L, Eberhardt W. Digital transformation in healthcare - architectures of present and future information technologies. Clin Chem Lab Med. 2019;57(3):328–335.
    1. Freedman MS, Devonshire V, Duquette P, Giacomini PS, Giuliani F, Levin MC, et al. Treatment optimization in multiple sclerosis: Canadian MS working group recommendations. Can J Neurol Sci. 2020;47(4):437–455.
    1. Harding K, Williams O, Willis M, Hrastelj J, Rimmer A, Joseph F, et al. Clinical outcomes of escalation vs early intensive disease-modifying therapy in patients with multiple sclerosis. JAMA Neurol. 2019;76(5):536–541.
    1. Van den Bulck SA, Hermens R, Slegers K, Vandenberghe B, Goderis G, Vankrunkelsven P. Designing a patient portal for patient-centered care: cross-sectional survey. J Med Internet Res. 2018;20(10):e269.
    1. Haase R, Wunderlich M, Dillenseger A, Kern R, Akgün K, Ziemssen T. Improving multiple sclerosis management and collecting safety information in the real world: the MSDS3D software approach. Expert Opin Drug Saf. 2018;17(4):369–378.
    1. Isernia S, Pagliari C, Jonsdottir J, Castiglioni C, Gindri P, Gramigna C, et al. Efficiency and patient-reported outcome measures from clinic to home: the human empowerment aging and disability program for digital-health rehabilitation. Front Neurol. 2019;10:1206.
    1. Neter E, Brainin E. eHealth literacy: a marker for" digital divide" in health information. Rev Health Care. 2012;3(3):145–151.
    1. Wapenaar J. Personeelstekort deze zomer nijpender dan ooit. Nursing. 2019;25(7):10–12.
    1. Kidd T, Carey N, Mold F, Westwood S, Miklaucich M, Konstantara E, et al. A systematic review of the effectiveness of self-management interventions in people with multiple sclerosis at improving depression, anxiety and quality of life. PLoS One. 2017;12(10):e0185931.
    1. Taylor SJ, Pinnock H, Epiphaniou E, Pearce G, Parke HL, Schwappach A, et al. A rapid synthesis of the evidence on interventions supporting self-management for people with long-term conditions: PRISMS–practical systematic review of self-management support for long-term conditions. 2015.
    1. Jongen PJ, Sinnige LG, van Geel BM, Verheul F, Verhagen WI, van der Kruijk RA, et al. The interactive web-based program MSmonitor for self-management and multidisciplinary care in multiple sclerosis: concept, content, and pilot results. Patient Pref Adher. 2015;9:1741.
    1. Jongen PJ, Sinnige LG, van Geel BM, Verheul F, Verhagen WI, van der Kruijk RA, et al. The interactive web-based program MSmonitor for self-management and multidisciplinary care in multiple sclerosis: utilization and valuation by patients. Patient Prefer Adher. 2016;10:243–250.
    1. Jongen PJ, Ter Veen G, Lemmens W, Donders R, van Noort E, Zeinstra E. The interactive web-based program msmonitor for self-management and multidisciplinary care in persons with multiple sclerosis: quasi-experimental study of short-term effects on patient empowerment. J Med Internet Res. 2020;22(3):e14297.
    1. Curavista. MSmonitor. 2022; Available at: . Accessed 25 Aug 2022.
    1. Beterdichtbij. 2022; Available at: . Accessed 25 May 2022.
    1. Microsoft. Microsoft teams. 2022; Available at: . Accessed 29 July 2022.
    1. Bohn Stafleu vL. Continu in verbinding met de patiënt. Skipr. 2019;12(11):19.
    1. Wapenaar J. Merendeel verpleegkundigen positief over e-health. Nursing. 2019;25(12):10–11.
    1. Jongen PJ, Blok BF, Heesakkers JP, Heerings M, Lemmens WA, Donders R. Simplified scoring of the actionable 8-item screening questionnaire for neurogenic bladder overactivity in multiple sclerosis: a comparative analysis of test performance at different cut-off points. BMC Urol. 2015;15(1):1–6.
    1. Bonniaud V, Parratte B, Amarenco G, Jackowski D, Didier J, Guyatt G. Measuring quality of life in multiple sclerosis patients with urinary disorders using the Qualiveen questionnaire. Arch Phys Med Rehabil. 2004;85(8):1317–1323.
    1. Vercoulen J, Alberts M, Bleijenberg G. De checklist individuele spankracht (CIS) Gedragstherapie. 1999;32(131):6.
    1. Wynia K, Middel B, Van Dijk JP, De Ruiter H, De Keyser J, Reijneveld SA. The multiple sclerosis impact profile (MSIP). Development and testing psychometric properties of an ICF-based health measure. Disabil Rehabil. 2008;30(4):261–274.
    1. Hobart J, Lamping D, Fitzpatrick R, Riazi A, Thompson A. The multiple sclerosis impact scale (MSIS-29) a new patient-based outcome measure. Brain. 2001;124(5):962–973.
    1. Krogh K, Christensen P, Sabroe S, Laurberg S. Neurogenic bowel dysfunction score. Spinal Cord. 2006;44(10):625–631.
    1. Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the hospital anxiety and depression scale: an updated literature review. J Psychosom Res. 2002;52(2):69–77.
    1. Noordhoff TC, Scheepe JR, t Hoen LA, Sluis TA, Blok BF. The multiple sclerosis intimacy and sexuality questionnaire (MSISQ-15): validation of the Dutch version in patients with multiple sclerosis and spinal cord injury. Neurourol Urodyn. 2018;37(8):2867–2874.
    1. Cella DF, Dineen K, Arnason B, Reder A, Webster KA, Karabatsos G, et al. Validation of the functional assessment of multiple sclerosis quality of life instrument. Neurology. 1996;47(1):129–139.
    1. Van Noort E, Kasteleyn MJ, Jongen P, Veen H, Chavannes NH. Feasibility of online risk-based monitoring by patients: the Natalizumab case. Mult Scler J. 2017;23:925–926.
    1. Groenenboom J. De inbedding van online zelfmanagementdagboeken in het zorgproces van multiple Sclerose patiënten. 2013.
    1. Ponds R, Van Boxtel M, Jolles J. De cognitive failure questionnaire als maat voor subjectief cognitief functioneren. Tijdschrift voor neuropsychologie. 2006;2:37–45.
    1. Badia X, Monserrat S, Roset M, Herdman M. Feasibility, validity and test–retest reliability of scaling methods for health states: the visual analogue scale and the time trade-off. Qual Life Res. 1999;8(4):303–310.
    1. Devlin NJ, Brooks R. EQ-5D and the EuroQol group: past, present and future. Appl Health Econ Health Policy. 2017;15(2):127–137.
    1. Al-Aqeel SA, AlAujan SS, Almazrou SH. The Institute for Medical Technology Assessment Productivity Cost Questionnaire (iPCQ) and the medical consumption questionnaire (iMCQ): translation and cognitive debriefing of the Arabic version. Int J Environ Res Public Health. 2021;18(14):7232.
    1. Cardol M, de Haan RJ, van den Bos Geertrudis AM, de Jong BA, de Groot IJ. The development of a handicap assessment questionnaire: the impact on participation and autonomy (IPA) Clin Rehabil. 1999;13(5):411–419.
    1. Rigby SA, Domenech C, Thornton EW, Tedman S, Young CA. Development and validation of a self-efficacy measure for people with multiple sclerosis: the multiple sclerosis self-efficacy scale. Mult Scler J. 2003;9(1):73–81.
    1. Battersby MW, Ask A, Reece MM, Markwick MJ, Collins JP. The Partners in Health scale: the development and psychometric properties of a generic assessment scale for chronic condition self-management. Austr J Prim Health. 2003;9(3):41–52.
    1. Petkov J, Harvey P, Battersby M. The internal consistency and construct validity of the partners in health scale: validation of a patient rated chronic condition self-management measure. Qual Life Res. 2010;19(7):1079–1085.
    1. Isala. Patient satisfaction questionnaire Isala. 2019; Available at: . Accessed 26 Aug 2022.
    1. Jongen PJ, Heerings M, Lemmens WA, Donders R, van der Zande A, van Noort E, et al. A prospective web-based patient-centred interactive study of long-term disabilities, disabilities perception and health-related quality of life in patients with multiple sclerosis in the Netherlands: the Dutch multiple sclerosis study protocol. BMC Neurol. 2015;15:128–120.
    1. Vickrey B, Hays RD, Harooni R, Myers LW, Ellison GW. A health-related quality of life measure for multiple sclerosis. Qual Life Res. 1995;4(3):187–206.
    1. Vickrey BG, Hays RD, Genovese BJ, Myers LW, Ellison GW. Comparison of a generic to disease-targeted health-related quality-of-life measures for multiple sclerosis. J Clin Epidemiol. 1997;50(5):557–569.
    1. Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the economic evaluation of health care programmes. Oxford University Press; 2015.
    1. Thorn JC, Coast J, Cohen D, Hollingworth W, Knapp M, Noble SM, et al. Resource-use measurement based on patient recall: issues and challenges for economic evaluation. Appl Health Econ Health Policy. 2013;11(3):155–161.
    1. Drost R, Paulus A, Ruwaard D, Evers S. Handleiding intersectorale kosten en baten van (preventieve) interventies. Maastricht: Maastricht University, Faculty of Health, medicine and life sciences CAPHRI, School for Public Health and Primary Care Care, Department of Health Services; 2014.
    1. Hakkaart-van Roijen L, Van der Linden N, Bouwmans C, Kanters T, Tan SS. Kostenhandleiding. Methodologie van kostenonderzoek en referentieprijzen voor economische evaluaties in de gezondheidszorg in opdracht van Zorginstituut Nederland Geactualiseerde versie. 2015. pp. 12–64.
    1. Saunders RP, Evans MH, Joshi P. Developing a process-evaluation plan for assessing health promotion program implementation: a how-to guide. Health Promot Pract. 2005;6(2):134–147.
    1. Versteegh MM, Vermeulen KM, Evers SM, De Wit GA, Prenger R, Stolk EA. Dutch tariff for the five-level version of EQ-5D. Value Health. 2016;19(4):343–352.
    1. van Volksgezondheid M. En sport W. Zinnige Zorg-systematisch doorlichten van het basispakket-over ons-Zorginstituut Nederland. 2016.
    1. Manca A, Hawkins N, Sculpher MJ. Estimating mean QALYs in trial-based cost-effectiveness analysis: the importance of controlling for baseline utility. Health Econ. 2005;14(5):487–496.
    1. Thompson SG, Barber JA. How should cost data in pragmatic randomised trials be analysed? BMJ. 2000;320(7243):1197–1200.
    1. Ramsey SD, Willke RJ, Glick H, Reed SD, Augustovski F, Jonsson B, et al. Cost-effectiveness analysis alongside clinical trials II—an ISPOR good research practices task force report. Value Health. 2015;18(2):161–172.
    1. van Volksgezondheid M. En sport W. Spoed moet goed-indicatoren en normen voor 6 spoedzorgindicaties-rapport-Zorginstituut Nederland. 2015.
    1. Briggs A, Sculpher M, Buxton M. Uncertainty in the economic evaluation of health care technologies: the role of sensitivity analysis. Health Econ. 1994;3(2):95–104.

Source: PubMed

スポンサーと協力者

医学的状態

薬物療法

3
購読する