Evaluating the Implementation of the Diabetes Prevention Program in an Integrated Health System
NCT ID: NCT03249077
Last Updated: 2022-06-30
Study Results
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Basic Information
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COMPLETED
8198 participants
OBSERVATIONAL
2017-07-01
2021-04-15
Brief Summary
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Detailed Description
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Beginning in April 2018, the Centers for Medicare \& Medicaid Services (CMS) made a landmark decision to reimburse clinical and non-clinical settings for providing DPP to Medicare beneficiaries (i.e., Medicare DPP); this coverage is currently for in-person DPP only and not digital DPP.\[6,7\] CMS's decision to cover DPP among older adults with prediabetes further catapulted efforts within healthcare organizations to address the increasing number of individuals with diabetes receiving care in their facilities. However, few studies have examined the sustainability of providing DPP based on maintenance of the effect (i.e., long-term change in weight and HbA1c), healthcare costs, participant experience, and organizational support. In addition, attracting individuals to DPP and similar lifestyle change interventions remains a significant challenge and identifying useful approaches is important.\[8-11\] Lastly, whereas the effectiveness of in-person DPP is well-established, prior studies evaluating the effect of digital DPP identified positive outcomes but had significant methodological limitations, such as a single arm pre- / post-test design and participant-reported outcomes.\[12,13-19\]
In 2017 Kaiser Permanente Northwest (KPNW), a large, integrated health system serving Oregon and southwest Washington, began piloting both digital and in-person versions of DPP for its adult health plan members with prediabetes and obesity. The purpose of this mixed-methods, natural experiment is to evaluate this large health system initiative by assessing the effects of both digital and in-person DPP on change in weight and HbA1c, health behaviors, and psychosocial factors. Also, sustainability based on cost-effectiveness and patient and healthcare stakeholder perspectives will be examined.
KPNW patients eligible to participate in DPP (digital or in-person) will be identified and recruited using the electronic health record (EHR). Both the digital and in-person (group-based) DPP programs will be delivered over 12 months. Demographic and clinical data to be included in analyses will also be extracted from the EHR. Behavioral and psychosocial questionnaires will be administered to DPP enrollees and non-enrollees online using REDCap. Semi-structured qualitative interviews will be conducted with a subset of DPP enrollees and non-enrollees to understand reasons for enrollment and likes/dislikes about the program. Healthcare system providers and stakeholders will also be interviewed to capture factors related to sustainability of offering DPP within the health system.
For the primary analysis, investigators plan to model 12- and 24-month weight and HbA1c trajectories using a linear mixed effects model using time since baseline as the time axis. Because randomization is not feasible in this real-world implementation of DPP, propensity score adjustment will be used to control for potential confounding. Furthermore, investigators will conduct an economic evaluation over the 12-month follow-up period for both the digital and in-person DPP cohorts as well as over the 24-month period for the digital DPP cohort from the perspective of the health plan, following best practices,\[20\] and guided by previous economic analyses of DPP interventions.\[21-26\]
The mixed-methods, natural experiment design investigators will use to evaluate KPNW's implementation of digital and in-person DPP will build on existing evidence related to DPP effectiveness across the two delivery modes on change in weight and HbA1c over time. In addition, the cost-effectiveness analysis will determine the impact of digital and in-person DPP on return on investment for healthcare systems and sustainability of the program. Findings from our evaluation will therefore inform best practices for implementing and sustaining DPP within large healthcare systems.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Digital DPP enrolled
The DPP online program is a CDC-certified translation of the DPP lifestyle intervention delivered in an online small group format of 10-15 participants.
Digital DPP
The online DPP program is 12 months in duration with 16 core sessions delivered over 16-26 weeks and 6 maintenance sessions delivered over 6 months.
In-person DPP enrolled
In-person DPP participants will attend group sessions of \~20 participants in size at KPNW clinics. The group facilitator will use the CDC National DPP curriculum,
In-person DPP
The in-person DPP program is 12 months and consists of weekly sessions for the first 6 months and monthly sessions for the remaining 6 months.
DPP not enrolled (usual care)
Access to usual care services without restrictions.
DPP not enrolled
Access to usual care services without restrictions.
Interventions
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Digital DPP
The online DPP program is 12 months in duration with 16 core sessions delivered over 16-26 weeks and 6 maintenance sessions delivered over 6 months.
In-person DPP
The in-person DPP program is 12 months and consists of weekly sessions for the first 6 months and monthly sessions for the remaining 6 months.
DPP not enrolled
Access to usual care services without restrictions.
Eligibility Criteria
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Inclusion Criteria
2. BMI ≥ 30; and
3. HbA1c 5.7-6.4%.
Exclusion Criteria
19 Years
75 Years
ALL
No
Sponsors
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Kaiser Permanente
OTHER
Responsible Party
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Principal Investigators
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Stephanie L Fitzpatrick, PhD
Role: PRINCIPAL_INVESTIGATOR
Kaiser Permanente
Locations
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Kaiser Permanente Center for Health Research
Portland, Oregon, United States
Countries
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References
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American Diabetes Association. Economic Costs of Diabetes in the U.S. in 2017. Diabetes Care. 2018 May;41(5):917-928. doi: 10.2337/dci18-0007. Epub 2018 Mar 22.
Ackermann RT, Kenrik Duru O, Albu JB, Schmittdiel JA, Soumerai SB, Wharam JF, Ali MK, Mangione CM, Gregg EW; NEXT-D Study Group. Evaluating diabetes health policies using natural experiments: the natural experiments for translation in diabetes study. Am J Prev Med. 2015 Jun;48(6):747-54. doi: 10.1016/j.amepre.2014.12.010.
Ali MK, Wharam F, Kenrik Duru O, Schmittdiel J, Ackermann RT, Albu J, Ross-Degnan D, Hunter CM, Mangione C, Gregg EW; NEXT-D Study Group. Advancing Health Policy and Program Research in Diabetes: Findings from the Natural Experiments for Translation in Diabetes (NEXT-D) Network. Curr Diab Rep. 2018 Nov 20;18(12):146. doi: 10.1007/s11892-018-1112-3.
Chambers EC, Rehm CD, Correra J, Garcia LE, Marquez ME, Wylie-Rosett J, Parsons A. Factors in Placement and Enrollment of Primary Care Patients in YMCA's Diabetes Prevention Program, Bronx, New York, 2010-2015. Prev Chronic Dis. 2017 Mar 30;14:E28. doi: 10.5888/pcd14.160486.
Venkataramani M, Pollack CE, Yeh HC, Maruthur NM. Prevalence and Correlates of Diabetes Prevention Program Referral and Participation. Am J Prev Med. 2019 Mar;56(3):452-457. doi: 10.1016/j.amepre.2018.10.005. Epub 2019 Jan 17.
Ali MK, McKeever Bullard K, Imperatore G, Benoit SR, Rolka DB, Albright AL, Gregg EW. Reach and Use of Diabetes Prevention Services in the United States, 2016-2017. JAMA Netw Open. 2019 May 3;2(5):e193160. doi: 10.1001/jamanetworkopen.2019.3160.
Ackermann RT, O'Brien MJ. Evidence and Challenges for Translation and Population Impact of the Diabetes Prevention Program. Curr Diab Rep. 2020 Feb 20;20(3):9. doi: 10.1007/s11892-020-1293-4.
Moin T, Damschroder LJ, AuYoung M, Maciejewski ML, Havens K, Ertl K, Vasti E, Weinreb JE, Steinle NI, Billington CJ, Hughes M, Makki F, Youles B, Holleman RG, Kim HM, Kinsinger LS, Richardson CR. Results From a Trial of an Online Diabetes Prevention Program Intervention. Am J Prev Med. 2018 Nov;55(5):583-591. doi: 10.1016/j.amepre.2018.06.028. Epub 2018 Sep 24.
Sepah SC, Jiang L, Ellis RJ, McDermott K, Peters AL. Engagement and outcomes in a digital Diabetes Prevention Program: 3-year update. BMJ Open Diabetes Res Care. 2017 Sep 7;5(1):e000422. doi: 10.1136/bmjdrc-2017-000422. eCollection 2017.
Sepah SC, Jiang L, Peters AL. Long-term outcomes of a Web-based diabetes prevention program: 2-year results of a single-arm longitudinal study. J Med Internet Res. 2015 Apr 10;17(4):e92. doi: 10.2196/jmir.4052.
Kim SE, Castro Sweet CM, Cho E, Tsai J, Cousineau MR. Evaluation of a Digital Diabetes Prevention Program Adapted for Low-Income Patients, 2016-2018. Prev Chronic Dis. 2019 Nov 27;16:E155. doi: 10.5888/pcd16.190156.
Castro Sweet CM, Chiguluri V, Gumpina R, Abbott P, Madero EN, Payne M, Happe L, Matanich R, Renda A, Prewitt T. Outcomes of a Digital Health Program With Human Coaching for Diabetes Risk Reduction in a Medicare Population. J Aging Health. 2018 Jun;30(5):692-710. doi: 10.1177/0898264316688791. Epub 2017 Jan 24.
Chen F, Su W, Becker SH, Payne M, Castro Sweet CM, Peters AL, Dall TM. Clinical and Economic Impact of a Digital, Remotely-Delivered Intensive Behavioral Counseling Program on Medicare Beneficiaries at Risk for Diabetes and Cardiovascular Disease. PLoS One. 2016 Oct 5;11(10):e0163627. doi: 10.1371/journal.pone.0163627. eCollection 2016.
Lee PG, Damschroder LJ, Holleman R, Moin T, Richardson CR. Older Adults and Diabetes Prevention Programs in the Veterans Health Administration. Diabetes Care. 2018 Dec;41(12):2644-2647. doi: 10.2337/dc18-1141. Epub 2018 Oct 30.
Joiner KL, Nam S, Whittemore R. Lifestyle interventions based on the diabetes prevention program delivered via eHealth: A systematic review and meta-analysis. Prev Med. 2017 Jul;100:194-207. doi: 10.1016/j.ypmed.2017.04.033. Epub 2017 Apr 27.
Sanders GD, Neumann PJ, Basu A, Brock DW, Feeny D, Krahn M, Kuntz KM, Meltzer DO, Owens DK, Prosser LA, Salomon JA, Sculpher MJ, Trikalinos TA, Russell LB, Siegel JE, Ganiats TG. Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine. JAMA. 2016 Sep 13;316(10):1093-103. doi: 10.1001/jama.2016.12195.
Diabetes Prevention Program Research Group. Within-trial cost-effectiveness of lifestyle intervention or metformin for the primary prevention of type 2 diabetes. Diabetes Care. 2003 Sep;26(9):2518-23. doi: 10.2337/diacare.26.9.2518.
Diabetes Prevention Program Research Group. The 10-year cost-effectiveness of lifestyle intervention or metformin for diabetes prevention: an intent-to-treat analysis of the DPP/DPPOS. Diabetes Care. 2012 Apr;35(4):723-30. doi: 10.2337/dc11-1468.
Herman WH. The cost-effectiveness of diabetes prevention: results from the Diabetes Prevention Program and the Diabetes Prevention Program Outcomes Study. Clin Diabetes Endocrinol. 2015 Sep 2;1:9. doi: 10.1186/s40842-015-0009-1. eCollection 2015.
Hoerger TJ, Hicks KA, Sorensen SW, Herman WH, Ratner RE, Ackermann RT, Zhang P, Engelgau MM. Cost-effectiveness of screening for pre-diabetes among overweight and obese U.S. adults. Diabetes Care. 2007 Nov;30(11):2874-9. doi: 10.2337/dc07-0885. Epub 2007 Aug 13.
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Related Links
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Centers for Medicare \& Medicaid Services. Federal Register, Vol. 81, No. 136, July 15, 2016, Proposal Rules. Pages 46413-46418 Accessed 11/09/2016
Hinnant L, Razi S, Lewis R, et al. Evaluation of the Health Care Innovation Awards: Community Resource Planning, Prevention, and Monitoring Annual Report 2015. Awardee-Level Findings: YMCA of the USA. Accessed 11/09/2016
Other Identifiers
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