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Clinical Trial Details — Status: Withdrawn

Administrative data

NCT number NCT05541120
Other study ID # 00000
Secondary ID
Status Withdrawn
Phase N/A
First received
Last updated
Start date October 18, 2022
Est. completion date August 31, 2026

Study information

Verified date February 2023
Source MaineHealth
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial 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.


Description:

Effect of Remote Patient Monitoring and Patient Education on Patient Activation and Glycemic Control in Individuals with Type 2 Diabetes Summary ABSTRACT In 2021, the MaineHealth Telehealth team was awarded a five-year, $1.7 million "Evidence-Based Telehealth Network Program" grant (EB TNPG) from Health Resources and Services Administration (HRSA). This grant is aimed at improving patient access to educational and management services for patients with type 2 diabetes in the rural Maine primary care setting by implementing RPM. The RPM devices will be used to transmit a participant's home point-of-care blood glucose values directly into MaineHealth's electronic medical record in real time. While there is strong evidence for diabetes self-management programs such as Living Well with Diabetes, the importance of patient engagement in clinical outcomes, the validity of the Patient Activation Measure (PAM-13®) survey to measure patient activation, and the overall efficacy of remote patient monitoring, there have been no randomized controlled trials looking at patient activation in remote patient monitoring in this important patient group. The investigators aim to address this in this study by conducting a randomized controlled trial of the use of RPM among rural patients with poorly controlled type 2 diabetes. The control group will have usual primary care provider care, including patient self-management tools, while the intervention group will have usual care + RPM. The investigators hypothesize that participation in RPM will be associated with decreases in HbA1c, increases in patient activation as measured by PAM-13® survey, and that increases in patient activation will be associated with decreases in HbA1c. STUDY PROCESS The study will be conducted over 5 years, and participants will be enrolled on a continuous rolling basis, with 70 total RPM kits available at any one time from a 3rd party vendor, Health Recovery Solutions (HRS). The maximum total number of participants the study can accommodate is 700, with 350 participants in each arm. The study team hopes for total enrollment as close to 700 as possible, but understands that total enrollment may be significantly less than 700. Point-of-care blood glucose values from the RPM study arm will flow into MaineHealth's electronic medical record (Epic) in real time. Every other week, the values will be reviewed by a clinical pharmacist with expertise in diabetes management. If an intervention or adjustment in the patient's regimen is indicated, the pharmacist will reach out to the Primary Care Provider (PCP) team to make this recommendation. The RPM intervention for each participant will be 6 months, at which point HRS will collect the RPM electronic tablet, and the PAM-13® survey will be administered. At 9 months after enrollment, the third HbA1c value will be collected from the electronic medical record, and the third administration of PAM-13® will take place. The PAM-13® survey will be administered through one of two methods 1) REDCap electronic form, the link for which will be sent to the participant by email, or 2) by telephone, administered by the Study Coordinator. Recruitment of participants will continue through the early part of 2026. Data will be analyzed during spring and summer of 2026, and the grant's end date is August 31, 2026. This study has been approved by MaineHealth's IRB as of Aug 5, 2022.


Recruitment information / eligibility

Status Withdrawn
Enrollment 0
Est. completion date August 31, 2026
Est. primary completion date June 30, 2026
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - 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) Exclusion Criteria: - 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

Study Design


Related Conditions & MeSH terms


Intervention

Device:
Remote Patient Monitoring
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.

Locations

Country Name City State
United States PenBay Medical Center Rockport Maine

Sponsors (3)

Lead Sponsor Collaborator
Tracy Jalbuena MD Health Resources and Services Administration (HRSA), MaineHealth

Country where clinical trial is conducted

United States, 

References & Publications (53)

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Fowles JB, Terry P, Xi M, Hibbard J, Bloom CT, Harvey L. Measuring self-management of patients' and employees' health: further validation of the Patient Activation Measure (PAM) based on its relation to employee characteristics. Patient Educ Couns. 2009 Oct;77(1):116-22. doi: 10.1016/j.pec.2009.02.018. Epub 2009 Apr 7. — View Citation

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Greene J, Hibbard JH. Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes. J Gen Intern Med. 2012 May;27(5):520-6. doi: 10.1007/s11606-011-1931-2. — View Citation

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Hellstrom 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. — View Citation

Hibbard 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. — View Citation

Hibbard 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. — View Citation

Hibbard 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. — View Citation

Hibbard 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. — View Citation

Hibbard 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. — View Citation

Hibbard JH. Using systematic measurement to target consumer activation strategies. Med Care Res Rev. 2009 Feb;66(1 Suppl):9S-27S. doi: 10.1177/1077558708326969. Epub 2008 Dec 3. — View Citation

Hosseinzadeh 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. — View Citation

Kinney 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. — View Citation

Kosar 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. — View Citation

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McDonnell ME. Telemedicine in Complex Diabetes Management. Curr Diab Rep. 2018 May 24;18(7):42. doi: 10.1007/s11892-018-1015-3. — View Citation

Melby 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. — View Citation

Michaud 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. — View Citation

Michaud TL, Siahpush M, Schwab RJ, Eiland LA, DeVany M, Hansen G, Slachetka TS, Boilesen E, Tak HJ, Wilson FA, Wang H, Pagan JA, Su D. Remote Patient Monitoring and Clinical Outcomes for Postdischarge Patients with Type 2 Diabetes. Popul Health Manag. 2018 Oct;21(5):387-394. doi: 10.1089/pop.2017.0175. Epub 2018 Mar 27. — View Citation

Moljord IE, Lara-Cabrera ML, Perestelo-Perez L, Rivero-Santana A, Eriksen L, Linaker OM. Psychometric properties of the Patient Activation Measure-13 among out-patients waiting for mental health treatment: A validation study in Norway. Patient Educ Couns. 2015 Nov;98(11):1410-7. doi: 10.1016/j.pec.2015.06.009. Epub 2015 Jun 23. — View Citation

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* Note: There are 53 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Mean HbA1c% Average glycated hemoglobin 6 months after enrollment
Primary Mean HbA1c% Average glycated hemoglobin 9 months after enrollment
Primary Mean change in HbA1c% Average change in percentage of HbA1c from baseline to 6 months after enrollment 6 months after enrollment
Primary Mean change in HbA1c% Average change in percentage of HbA1c from baseline to 9 months after enrollment 9 months after enrollment
Primary Percentage of participants in each group who have HbA1c < 7% Percentage of participants in each group with HbA1c < 7% 6 months after enrollment
Primary Percentage of participants in each group who have HbA1c < 7% Percentage of participants in each group with HbA1c < 7% 9 months after enrollment
Secondary PAM-13 at 6 months after enrollment PAM-13 Patient Activation Measure Survey
Unabbreviated scale title: Patient Activation Measure 13-Item Survey Minimum value: 0 Maximum value: 100 Higher values are associated with better health outcomes
6 months after enrollment
Secondary PAM-13 at 9 months after enrollment PAM-13 Patient Activation Measure Survey
PAM-13 Patient Activation Measure Survey
Unabbreviated scale title: Patient Activation Measure 13-Item Survey Minimum value: 0 Maximum value: 100 Higher values are associated with better health outcomes
9 months after enrollment
Secondary Mean change in PAM-13 at 6 months Average change in PAM-13 Patient Activation Measure Survey score from baseline to 6 months after enrollment
Unabbreviated scale title: Patient Activation Measure 13-Item Survey Minimum value: 0 Maximum value: 100 Higher values are associated with better health outcomes
6 months after enrollment
Secondary Mean change in PAM-13 at 9 months Average change in PAM-13 Patient Activation Measure Survey score from baseline to 9 months after enrollment
Unabbreviated scale title: Patient Activation Measure 13-Item Survey Minimum value: 0 Maximum value: 100 Higher values are associated with better health outcomes
9 months after enrollment
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