DiabetesNCT03249077
Evaluating the Implementation of the Diabetes Prevention Program in an Integrated Health System
An observational study of Diabetes, run by Kaiser Permanente at 1 site in United States.
Trial summary
In preparation for the roll out of the Medicare Diabetes Prevention Program (DPP) in 2018, Kaiser Permanente Northwest (KPNW), a large, integrated health care system, plans to pilot the implementation of DPP starting in April 2017. Read more about this study
- Who is it for?
- Ages 19 to 75 years
- Conditions the study is for
- Diabetes
- What is being tested?
- Digital DPP, In-person DPP and DPP not enrolled
- Type of treatment
- Lifestyle or therapy programme
- How many people
- 8,198 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Jul 2017to 15 Apr 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 19 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: KPNW adult members with prediabetes and obesity.
Who may be able to join
- Age 19-75
- BMI ≥ 30; and
- HbA1c 5.7-6.4%.
Who cannot join
- 1) Diagnosis of diabetes prior to the study's recruitment efforts
Trial locations and contacts
1 site in 1 country.
United States1 site
Kaiser Permanente Center for Health Research
Portland, Oregon, 97227
About this study
In preparation for the roll out of the Medicare Diabetes Prevention Program (DPP) in 2018, Kaiser Permanente Northwest (KPNW), a large, integrated health care system, plans to pilot the implementation of DPP starting in April 2017. Patients 19-75 years old at high risk for diabetes will be offered DPP online or DPP in-person. A pragmatic, rigorous, quantitative and qualitative evaluation will be conducted to compare patients enrolled in DPP (either online or in-person) to those not enrolled to better inform future implementation efforts of DPP within and outside of KPNW. This study is a natural experiment project.
Read the detailed description
The prevalence of prediabetes and obesity among U.S. adults age 40 and older is significant, with over 30% having prediabetes and over 40% having obesity.[1,2] Prediabetes and obesity increase the risk for diabetes, cardiovascular disease, and poor quality of life, and are responsible for substantial healthcare costs.[3] In response to the multi-level burden of prediabetes and obesity, there have been several efforts to prevent diabetes at the population level and reduce healthcare costs,[4,5] including national implementation and reimbursement of the successful Diabetes Prevention Program (DPP).
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
- Diabetes
- Being tested
- Digital DPP, In-person DPP, DPP not enrolled
- Keywords
- Prevention, Medicare
- Medical subject headings
- Diabetes Mellitus
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Digital DPPBehavioural
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 DPPBehavioural
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 enrolledOther
Access to usual care services without restrictions.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Behavioral: Digital DPP | |
| 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, Receives: Behavioral: In-person DPP | |
| DPP not enrolled (usual care) | Access to usual care services without restrictions. Receives: Other: DPP not enrolled |
What is being measured
The primary outcome is the main question the study is designed to answer.
Weight
Weight obtained from the electronic health record
Measured: Baseline through 12 months
Secondary outcomes (4)
HbA1c
HbA1c obtained from the electronic health record
Measured: Baseline through 12 months
Cost-effectiveness
Cost data will include: 1) medical care; and 2) the cost of intervention delivery, obtained from administrative and electronic health records.
Measured: Baseline through 12 months; and Baseline through 24 months (for digital DPP comparison to usual care only).
Weight (24-month for digital DPP)
Weight obtained from the electronic health record (for digital DPP comparison to usual care only)
Measured: Baseline through 24 months
HbA1c (24-month for digital DPP)
HbA1c obtained from the electronic health record (for digital DPP comparison to usual care only)
Measured: Basaeline through 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Aug 2017
- Study start1 Jul 2017
- Primary completion15 Apr 2021
- Study completion15 Apr 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (23)Papers the sponsor has linked to this study.
- Other trials for DiabetesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 8,198 participants (actual)
Sponsor and investigators
- Lead sponsor
- Kaiser Permanente
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Stephanie L Fitzpatrick, PhD, Principal investigator, Kaiser Permanente
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03249077
- Sponsor's protocol ID
- 1R01DK115237
- Status last verified
- Jun 2022
- First submitted
- 8 Aug 2017
- Last updated
- 30 Jun 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Gerstein HC, Santaguida P, Raina P, Morrison KM, Balion C, Hunt D, Yazdi H, Booker L. Annual incidence and relative risk of diabetes in people with various categories of dysglycemia: a systematic overview and meta-analysis of prospective studies. Diabetes Res Clin Pract. 2007 Dec;78(3):305-12. doi: 10.1016/j.diabres.2007.05.004. Epub 2007 Jun 29.
PubMed 17601626American 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.
PubMed 29567642Ackermann 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.
PubMed 25998925Ali 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.
PubMed 30456479Chambers 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.
PubMed 28358669Venkataramani 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.
PubMed 30661888Ali 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.
PubMed 31074808Ackermann 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.
PubMed 32080770Moin 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.
PubMed 30262149Sepah 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.
PubMed 28948027Sepah 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.
PubMed 25863515Kim 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.
PubMed 31775010Castro 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.
PubMed 28553807Chen 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.
PubMed 27706216Lee 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.
PubMed 30377187
Study at a glance
From the registry record, last updated by the sponsor on 30 Jun 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluating the Implementation of the Diabetes Prevention Program in an Integrated Health System
- ClinicalTrials.gov ID
- NCT03249077
- Acronym / sponsor ID
- 1R01DK115237
- Conditions
- Diabetes
- Keywords
- Prevention, Medicare
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 8,198 participants (actual)
- Lead sponsor
- Kaiser PermanenteUniversity, hospital or other
- Study start
- 1 Jul 2017 (actual)
- Primary completion
- 15 Apr 2021 (actual)
- Study completion
- 15 Apr 2021 (actual)
- First posted
- 15 Aug 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
In preparation for the roll out of the Medicare Diabetes Prevention Program (DPP) in 2018, Kaiser Permanente Northwest (KPNW), a large, integrated health care system, plans to pilot the implementation of DPP starting in April 2017. Patients 19-75 years old at high risk for diabetes will be offered DPP online or DPP in-person. A pragmatic, rigorous, quantitative and qualitative evaluation will be conducted to compare patients enrolled in DPP (either online or in-person) to those not enrolled to better inform future implementation efforts of DPP within and outside of KPNW. This study is a natural experiment project.
Detailed description
The prevalence of prediabetes and obesity among U.S. adults age 40 and older is significant, with over 30% having prediabetes and over 40% having obesity.[1,2] Prediabetes and obesity increase the risk for diabetes, cardiovascular disease, and poor quality of life, and are responsible for substantial healthcare costs.[3] In response to the multi-level burden of prediabetes and obesity, there have been several efforts to prevent diabetes at the population level and reduce healthcare costs,[4,5] including national implementation and reimbursement of the successful Diabetes Prevention Program (DPP).
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Digital DPP enrolled | – | Behavioral: Digital DPPThe DPP online program is a CDC-certified translation of the DPP lifestyle intervention delivered in an online small group format of 10-15 participants. |
| In-person DPP enrolled | – | Behavioral: In-person DPPIn-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, |
| DPP not enrolled (usual care) | – | Other: DPP not enrolledAccess to usual care services without restrictions. |
Who may qualify
- Ages
- 19 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- KPNW adult members with prediabetes and obesity.
Key inclusion criteria (3 listed)
- Age 19-75
- BMI ≥ 30; and
- HbA1c 5.7-6.4%.
Key exclusion criteria (1 listed)
- 1) Diagnosis of diabetes prior to the study's recruitment efforts
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Digital DPPThe 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. | Behavioural | Digital DPP enrolled |
| In-person DPPThe 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. | Behavioural | In-person DPP enrolled |
| DPP not enrolledAccess to usual care services without restrictions. | Other | DPP not enrolled (usual care) |
Primary outcome
Weight
Time frame: Baseline through 12 months
Weight obtained from the electronic health record
4 secondary outcomes
HbA1c
Time frame: Baseline through 12 months
Cost-effectiveness
Time frame: Baseline through 12 months; and Baseline through 24 months (for digital DPP comparison to usual care only).
Weight (24-month for digital DPP)
Time frame: Baseline through 24 months
HbA1c (24-month for digital DPP)
Time frame: Basaeline through 24 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Jun 2022.
- Background: PubMed 17601626Gerstein HC, Santaguida P, Raina P, Morrison KM, Balion C, Hunt D, Yazdi H, Booker L. Annual incidence and relative risk of diabetes in people with various categories of dysglycemia: a systematic overview and meta-analysis of prospective studies. Diabetes Res Clin Pract. 2007 Dec;78(3):305-12. doi: 10.1016/j.diabres.2007.05.004. Epub 2007 Jun 29.
- Background: PubMed 29567642American 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.
- Background: PubMed 25998925Ackermann 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.
- Background: PubMed 30456479Ali 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.
- Background: PubMed 28358669Chambers 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.
- Background: PubMed 30661888Venkataramani 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.
- Background: PubMed 31074808Ali 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.
- Background: PubMed 32080770Ackermann 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.
- Background: PubMed 30262149Moin 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.
- Background: PubMed 28948027Sepah 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.
- Background: PubMed 25863515Sepah 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.
- Background: PubMed 31775010Kim 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.
- Centers for Medicare \& Medicaid Services. Federal Register, Vol. 81, No. 136, July 15, 2016, Proposal Rules. Pages 46413-46418 Accessed 11/09/2016Link provided by the sponsor.
- 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 11/09/2016Link provided by the sponsor.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Stephanie L Fitzpatrick, PhD principal investigator
Kaiser Permanente
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabetes, run by Kaiser Permanente at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 30 Jun 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Weight (time frame: Baseline through 12 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03249077, which also lists 23 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Jun 2022.