Study Stopped
Lack of participants eligible for study
Effect of Remote Patient Monitoring and Patient Education on Patient Activation and Glycemic Control in Individuals With Type 2 Diabetes
1 other identifier
interventional
N/A
1 country
1
Brief Summary
This is a randomized controlled trial of the use of Remote Patient Monitoring (RPM) compared to usual care among rural patients with poorly controlled type 2 diabetes. Usual care is defined as participation in Living Well with Diabetes/Virtual Diabetes Self-Management Program and Primary Care Provider evaluation and management at the providers' discretion, including medication adjustment or interventions, and other types of interventions depending on clinical judgement.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
Started Oct 2022
Longer than P75 for not_applicable diabetes-mellitus-type-2
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 30, 2022
CompletedFirst Posted
Study publicly available on registry
September 15, 2022
CompletedStudy Start
First participant enrolled
October 18, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 30, 2026
ExpectedStudy Completion
Last participant's last visit for all outcomes
August 31, 2026
February 16, 2023
February 1, 2023
3.7 years
August 30, 2022
February 15, 2023
Conditions
Keywords
Outcome Measures
Primary Outcomes (6)
Mean HbA1c%
Average glycated hemoglobin
6 months after enrollment
Mean HbA1c%
Average glycated hemoglobin
9 months after enrollment
Mean change in HbA1c%
Average change in percentage of HbA1c from baseline to 6 months after enrollment
6 months after enrollment
Mean change in HbA1c%
Average change in percentage of HbA1c from baseline to 9 months after enrollment
9 months after enrollment
Percentage of participants in each group who have HbA1c < 7%
Percentage of participants in each group with HbA1c \< 7%
6 months after enrollment
Percentage of participants in each group who have HbA1c < 7%
Percentage of participants in each group with HbA1c \< 7%
9 months after enrollment
Secondary Outcomes (4)
PAM-13 at 6 months after enrollment
6 months after enrollment
PAM-13 at 9 months after enrollment
9 months after enrollment
Mean change in PAM-13 at 6 months
6 months after enrollment
Mean change in PAM-13 at 9 months
9 months after enrollment
Study Arms (2)
Living Well with Diabetes
NO INTERVENTIONUsual care is defined as participation in Living Well with Diabetes/Virtual Diabetes Self-Management Program, PCP evaluation and management, including medication adjustment or interventions, and other types of interventions depending on clinical judgement. This may include eConsults between the provider and a pharmacist, in-person visits between the provider and the patient, synchronous telemedicine visits between the provider and the patient, and synchronous telemedicine visits between the pharmacist and the patient.
Living Well with Diabetes + Remote Patient Monitoring
EXPERIMENTALRemote patient monitoring as the intervention is defined as a tablet and Bluetooth-enabled glucometer technology that collects point-of-care (POC) blood glucose data from a patient outside of a traditional clinical setting, and securely transmits this data to Epic for review and potential intervention.
Interventions
Remote patient monitoring as the intervention is defined as a tablet and Bluetooth-enabled glucometer technology that collects point-of-care (POC) blood glucose data from a patient outside of a traditional clinical setting, and securely transmits this data to Epic for review and potential intervention.
Eligibility Criteria
You may qualify if:
- Be enrolled in Living Well with Diabetes education program
- Have an HbA1c% ≥ 8 in the prior 6 months
- Be capable of providing consent
- Be adults (age 18 or over)
You may not qualify if:
- Primarily managed by endocrinology for their diabetes (\> 1 visit with endocrinology in the previous 12 months)
- Incarcerated
- PCP not at one of the 30 primary care practices listed (see attachment List of PCP Practices)
- Diagnosed with type 1 diabetes
- Candidate for continuous glucose monitoring, as defined by Centers for Medicare and Medicaid Services as using at least three insulin injections per day, any combination of types of insulins
- Pregnant
- Have previously participated in the Living Well with Diabetes/Virtual Diabetes Self-Management Program
- Have previously used a remote patient monitoring device for diabetes management
- Have a diagnosis of dementia or other clinical diagnosis that would impair participation capacity
- Currently participating in any other clinical trial regarding diabetes care or management
- Currently enrolled in hospice
- Currently residing in a long term care or rehabilitation facility
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Tracy Jalbuena MDlead
- MaineHealthcollaborator
- Health Resources and Services Administration (HRSA)collaborator
Study Sites (1)
PenBay Medical Center
Rockport, Maine, 04856, United States
Related Publications (53)
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PMID: 31543458BACKGROUNDAmerican 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.
PMID: 29567642BACKGROUNDAndersen JA, Scoggins D, Michaud T, Wan N, Wen M, Su D. Racial Disparities in Diabetes Management Outcomes: Evidence from a Remote Patient Monitoring Program for Type 2 Diabetic Patients. Telemed J E Health. 2021 Jan;27(1):55-61. doi: 10.1089/tmj.2019.0280. Epub 2020 Apr 17.
PMID: 32302521BACKGROUNDBahrom NH, Ramli AS, Isa MR, Baharudin N, Badlishah-Sham SF, Mohamed-Yassin MS, Abdul-Hamid H. Validity and reliability of the Patient Activation Measure(R) (PAM(R))-13 Malay version among patients with Metabolic Syndrome in primary care. Malays Fam Physician. 2020 Nov 10;15(3):22-34. eCollection 2020.
PMID: 33329860BACKGROUNDBomba F, Markwart H, Muhlan H, Menrath I, Ernst G, Thyen U, Schmidt S. Adaptation and validation of the German Patient Activation Measure for adolescents with chronic conditions in transitional care: PAM(R) 13 for Adolescents. Res Nurs Health. 2018 Feb;41(1):78-87. doi: 10.1002/nur.21831. Epub 2017 Dec 20.
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PMID: 31068494BACKGROUNDDieleman JL, Baral R, Birger M, Bui AL, Bulchis A, Chapin A, Hamavid H, Horst C, Johnson EK, Joseph J, Lavado R, Lomsadze L, Reynolds A, Squires E, Campbell M, DeCenso B, Dicker D, Flaxman AD, Gabert R, Highfill T, Naghavi M, Nightingale N, Templin T, Tobias MI, Vos T, Murray CJ. US Spending on Personal Health Care and Public Health, 1996-2013. JAMA. 2016 Dec 27;316(24):2627-2646. doi: 10.1001/jama.2016.16885.
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PMID: 22127797BACKGROUNDHaas L, Maryniuk M, Beck J, Cox CE, Duker P, Edwards L, Fisher EB, Hanson L, Kent D, Kolb L, McLaughlin S, Orzeck E, Piette JD, Rhinehart AS, Rothman R, Sklaroff S, Tomky D, Youssef G; 2012 Standards Revision Task Force. National standards for diabetes self-management education and support. Diabetes Care. 2014 Jan;37 Suppl 1(Suppl 1):S144-53. doi: 10.2337/dc14-S144. No abstract available.
PMID: 24357210BACKGROUNDHellstrom A, Kassaye Tessma M, Flink M, Dahlgren A, Schildmeijer K, Ekstedt M. Validation of the patient activation measure in patients at discharge from hospitals and at distance from hospital care in Sweden. BMC Public Health. 2019 Dec 19;19(1):1701. doi: 10.1186/s12889-019-8025-1.
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PMID: 19052169BACKGROUNDHibbard JH, Greene J. What the evidence shows about patient activation: better health outcomes and care experiences; fewer data on costs. Health Aff (Millwood). 2013 Feb;32(2):207-14. doi: 10.1377/hlthaff.2012.1061.
PMID: 23381511BACKGROUNDHibbard JH, Greene J, Shi Y, Mittler J, Scanlon D. Taking the long view: how well do patient activation scores predict outcomes four years later? Med Care Res Rev. 2015 Jun;72(3):324-37. doi: 10.1177/1077558715573871. Epub 2015 Feb 24.
PMID: 25716663BACKGROUNDHibbard JH, Mahoney ER, Stockard J, Tusler M. Development and testing of a short form of the patient activation measure. Health Serv Res. 2005 Dec;40(6 Pt 1):1918-30. doi: 10.1111/j.1475-6773.2005.00438.x.
PMID: 16336556BACKGROUNDHibbard JH, Stockard J, Mahoney ER, Tusler M. Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv Res. 2004 Aug;39(4 Pt 1):1005-26. doi: 10.1111/j.1475-6773.2004.00269.x.
PMID: 15230939BACKGROUNDHibbard JH, Tusler M. Assessing activation stage and employing a "next steps" approach to supporting patient self-management. J Ambul Care Manage. 2007 Jan-Mar;30(1):2-8. doi: 10.1097/00004479-200701000-00002.
PMID: 17170632BACKGROUNDHosseinzadeh H, Verma I, Gopaldasani V. Patient activation and Type 2 diabetes mellitus self-management: a systematic review and meta-analysis. Aust J Prim Health. 2020 Dec;26(6):431-442. doi: 10.1071/PY19204.
PMID: 33222755BACKGROUNDKinney RL, Lemon SC, Person SD, Pagoto SL, Saczynski JS. The association between patient activation and medication adherence, hospitalization, and emergency room utilization in patients with chronic illnesses: a systematic review. Patient Educ Couns. 2015 May;98(5):545-52. doi: 10.1016/j.pec.2015.02.005. Epub 2015 Feb 19.
PMID: 25744281BACKGROUNDKosar C, Besen DB. Adaptation of a patient activation measure (PAM) into Turkish: reliability and validity test. Afr Health Sci. 2019 Mar;19(1):1811-1820. doi: 10.4314/ahs.v19i1.58.
PMID: 31149012BACKGROUNDLee MK, Lee KH, Yoo SH, Park CY. Impact of initial active engagement in self-monitoring with a telemonitoring device on glycemic control among patients with type 2 diabetes. Sci Rep. 2017 Jun 20;7(1):3866. doi: 10.1038/s41598-017-03842-2.
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PMID: 29797292BACKGROUNDMelby K, Nygard M, Brobakken MF, Grawe RW, Guzey IC, Reitan SK, Vedul-Kjelsas E, Heggelund J, Lara-Cabrera ML. Test-Retest Reliability of the Patient Activation Measure-13 in Adults with Substance Use Disorders and Schizophrenia Spectrum Disorders. Int J Environ Res Public Health. 2021 Jan 29;18(3):1185. doi: 10.3390/ijerph18031185.
PMID: 33572717BACKGROUNDMichaud TL, Siahpush M, King KM, Ramos AK, Robbins RE, Schwab RJ, Clarke MA, Su D. Program completion and glycemic control in a remote patient monitoring program for diabetes management: Does gender matter? Diabetes Res Clin Pract. 2020 Jan;159:107944. doi: 10.1016/j.diabres.2019.107944. Epub 2019 Nov 23.
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PMID: 18363526BACKGROUND
Related Links
- Centers For Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health. BRFSS Prevalence \& Trend Data
- Centers for Medicare and Medicaid Services. DM-2 (NQF 0059): Diabetes: Hemoglobin A1c (HbA1c) Poor Control (\>9%).; 2019. Accessed January 20, 2022.
- International Diabetes Federation. IDF Diabetes Atlas. IDF Diabetes Atlas. Published 2021
- Lisa A. States with the biggest rural populations. Stacker. Published April 8, 2019.
- National Clinical Care Commission. Report to Congress on Leveraging Federal Programs to Prevent and Control Diabetes and Its Complications. Department of Health and Human Services; 2021. Accessed January 31, 2022.
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Tracy Jalbuena, MD
MaineHealth
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- NONE
- Purpose
- TREATMENT
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR INVESTIGATOR
- PI Title
- Clinical Lead for Telehealth
Study Record Dates
First Submitted
August 30, 2022
First Posted
September 15, 2022
Study Start
October 18, 2022
Primary Completion (Estimated)
June 30, 2026
Study Completion (Estimated)
August 31, 2026
Last Updated
February 16, 2023
Record last verified: 2023-02
Data Sharing
- IPD Sharing
- Will not share