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CompletedNCT05479097Updated Jul 16, 2024Results posted

Feasibility Study of a Novel mHealth Application to Enable Community Health Workers to Manage

An interventional study of Anti-Hypertensive in Hypertension, sponsored by University of Wisconsin, Madison. Completed at 1 site in Guatemala. Open to participants aged 18 Years to 99 Years. Per ClinicalTrials.gov, last updated 2024-07-16.

Sponsored by University of Wisconsin, Madison · Not applicable, Interventional, and Health services research

Phase
Not applicable
Study type
Interventional
Enrollment
32
Allocation
Non-randomized
Ages
18 Years to 99 Years
Sex
All
01

Study summary

This is a single group study assessing the feasibility of hypertension management by community health workers (CHWs) equipped with a mobile clinical decision support (CDS) application and working with remote physician supervision.

Read the detailed description

An estimated 1.13 billion people worldwide are currently living with hypertension, the leading preventable cause of death and disability. Two thirds of these patients live in low- and middle-income countries (LMIC). Treatment of hypertension has been found to be cost-effective in reducing morbidity and mortality across a broad range of settings. Despite this, less than 10% of patients with hypertension in LMIC have good control of their blood pressure. Health systems in LMIC, which are often focused on providing episodic care for acute illnesses and suffer from inadequate and poorly distributed health care infrastructure and workforce, are ill-equipped to address the rise in chronic non-communicable diseases (NCDs) such as hypertension. Governments and NGOs are increasingly turning to community health workers (CHWs) - lay people trained to carry out a variety of tasks and who often are from or have a close connection to the communities they serve - to help fill care gaps for hypertension and other NCDs in LMIC. In most cases, CHWs have played supportive (e.g. providing patient education) rather than direct care roles. While such programs have led to improved chronic disease outcomes, they still rely on clinic-based physicians, mid-level providers or nurses to directly provide medical management, and therefore do not address the essential problem of inadequate primary care infrastructure and workforce, particularly in rural areas. Overcoming this problem is key to reducing the growing burden of untreated hypertension in LMIC.

To solve this problem, the investigators are developing an innovative mobile application to assist CHWs in the treatment of hypertension in adults with remote physician supervision. This application is built on the widely-used CommCare platform and will provide clinical decision support (CDS) to CHWs based on protocols from the WHO and the International Society of Hypertension for antihypertensive medication initiation and titration, lifestyle counseling, and identification of patients requiring a higher level of care. The investigators will develop and test this approach in a rural area of Guatemala with poor primary care infrastructure and where the team has worked extensively in the past and has an ongoing collaboration with a local NGO, the San Lucas Mission, and affiliated CHWs. Through this collaboration, the investigators have developed and implemented a CHW-led rural diabetes program enabled by a CDS mobile application and have demonstrated that CHWs can safely and effectively manage diabetes using the application. The hypothesis is that the investigators will be able to adapt the model to hypertension management and are evaluating the feasibility of this approach with this pilot study.

02

Conditions studied

  • Hypertension

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In context

Hypertension

6,834 studies on the registry are indexed under Hypertension; 971 are open to participants now.

This study's enrollment of 32 is below the median of 90 across 5,095 interventional studies indexed under Hypertension.

Browse Hypertension studies →

Lead sponsor

University of Wisconsin, Madison is the lead sponsor of 1,182 studies on the registry; 180 are open to participants now.

Of its 156 completed or terminated interventional studies of FDA-regulated products, 118 (76%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 99 Years
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Greater than 18 years old
  • Diagnosed with hypertension
  • Blood pressure greater than or equal to 140/90 mm Hg OR
  • currently taking antihypertensive medication

Exclusion criteria

Exclusion Criteria:

  • Pregnancy
  • Severe comorbid condition(s) with life expectancy less than 1 year
05

Study design

Phase
Not applicable
Primary purpose
Health services research
Allocation
Non-randomized
Intervention model
Single group
Masking
None (open label)
Enrollment
32 participants (actual)

Interventions

  • DrugAnti-Hypertensive

    Based on information entered by the CHWs into the CommCare application designed for this study, the application will provide recommendations (and underlying rationale for these recommendations) for prescription of antihypertensives (amlodipine and/or losartan OR enalapril) and medications to reduce cardiovascular risk (aspirin and atorvastatin) if indicated, lifestyle modification, and referral to the supervising physician if indicated for potential complications of hypertension.

06

What researchers measure

Primary outcomes

  1. Change in Systolic Blood Pressure

    Difference in systolic blood pressure from baseline to 6 months

    Time frame: baseline, 6 months

  2. Difference in Diastolic Blood Pressure From Baseline to 6 Months

    Difference in diastolic blood pressure from baseline to 6 months

    Time frame: baseline, 6 months

  3. Change in the Proportion of Patients With Systolic Blood Pressure Less Than or Equal to 140

    Difference in the proportion of patients with systolic blood pressure less than or equal to 140 from baseline to 6 months

    Time frame: baseline, 6 months

  4. Change in the Proportion of Patients With Systolic Blood Pressure Less Than or Equal to Personalized Goal

    Difference in the proportion of patients with systolic blood pressure less than or equal to personalized goal from baseline to 6 months

    Time frame: baseline, 6 months

  5. Proportion of Visits for Which Both the CHW Conducting the Visit and the Physician Reviewing Post-visit Data Agreed With the Antihypertensive Recommendations Provided by the CDS Application

    This measure will be calculated as the proportion of visits for which both the CHW conducting the visit and the physician reviewing post-visit data agreed with the antihypertensive recommendations provided by the application.

    Time frame: 6 months

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Results

Posted Jul 16, 2024

Participant flow

Participant flow — Overall Study
MilestoneStudy Participants
Started32
Completed30
Not completed2
Withdrew: Withdrawal by subject2

Outcome measures

PrimaryChange in Systolic Blood Pressure

Difference in systolic blood pressure from baseline to 6 months

Time frame:
baseline, 6 months
Reported as:
Median · mmHg
Change in Systolic Blood Pressure
mmHgStudy Participants
Change in Systolic Blood Pressure-7.5 (-12.0 to -1.0)
Statistical analysis
  • Study Participants · Wilcoxon signed rank test · p = 0.03232 (A priori threshold for statistical significance was P \<0.05.) · Median difference (net): -7.5 · 95% CI -12.0 to -1.0Systolic blood pressure was not normally distributed in the study sample, so nonparametric analysis was used.
PrimaryDifference in Diastolic Blood Pressure From Baseline to 6 Months

Difference in diastolic blood pressure from baseline to 6 months

Time frame:
baseline, 6 months
Reported as:
Mean · mmHg
Difference in Diastolic Blood Pressure From Baseline to 6 Months
mmHgStudy Participants
Difference in Diastolic Blood Pressure From Baseline to 6 Months-3.1 (-6.1 to -0.1)
Statistical analysis
  • Study Participants · t-test, 2 sided · p = 0.045 (The a priori threshold for statistical significance was P \<0.05.) · Mean difference (net): -3.1 · 95% CI -6.1 to -0.1As diastolic blood pressure was normally distributed in our sample, we used a paired t-test to evaluate the mean difference in measurements.
PrimaryChange in the Proportion of Patients With Systolic Blood Pressure Less Than or Equal to 140

Difference in the proportion of patients with systolic blood pressure less than or equal to 140 from baseline to 6 months

Time frame:
baseline, 6 months
Reported as:
Count of participants · Participants
Change in the Proportion of Patients With Systolic Blood Pressure Less Than or Equal to 140
ParticipantsStudy Participants
Baseline systolic blood pressure control — Systolic blood pressure controlled (<=140 mmHg)21
Baseline systolic blood pressure control — Systolic blood pressure not controlled (>140 mmHg)9
Six month systolic blood pressure control — Systolic blood pressure controlled (<=140 mmHg)23
Six month systolic blood pressure control — Systolic blood pressure not controlled (>140 mmHg)7
Statistical analysis
  • Study Participants · McNemar · p = 0.7237 (The a priori threshold for statistical significance was P \<0.05)
PrimaryChange in the Proportion of Patients With Systolic Blood Pressure Less Than or Equal to Personalized Goal

Difference in the proportion of patients with systolic blood pressure less than or equal to personalized goal from baseline to 6 months

Time frame:
baseline, 6 months
Reported as:
Count of participants · Participants
Change in the Proportion of Patients With Systolic Blood Pressure Less Than or Equal to Personalized Goal
ParticipantsStudy Participants
Baseline — Systolic blood pressure less than or equal to personalized goal21
Baseline — Systolic blood pressure greater than personalized goal9
Six months — Systolic blood pressure less than or equal to personalized goal23
Six months — Systolic blood pressure greater than personalized goal7
Statistical analysis
  • Study Participants · McNemar · p = 0.7237 (The a priori threshold for statistical significance was P \<0.05)
PrimaryProportion of Visits for Which Both the CHW Conducting the Visit and the Physician Reviewing Post-visit Data Agreed With the Antihypertensive Recommendations Provided by the CDS Application

This measure will be calculated as the proportion of visits for which both the CHW conducting the visit and the physician reviewing post-visit data agreed with the antihypertensive recommendations provided by the application.

Time frame:
6 months
Reported as:
Count of units · Patient visits
Proportion of Visits for Which Both the CHW Conducting the Visit and the Physician Reviewing Post-visit Data Agreed With the Antihypertensive Recommendations Provided by the CDS Application
Patient visitsStudy Participants
Visits for which both CHW and physician agreed with medication recommendations202
Visits for which either the CHW or physician disagreed with medication recommendations7

Adverse events

Collected over Six months.. Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
Study Participants0/32 (0%)0/32 (0%)16/32 (50%)
Most frequent other events
Showing 10 of 16
Most frequent other events
EventStudy Participants
DyspepsiaGastrointestinal disorders5/32
Non-cardiac chest painGeneral disorders4/32
HyperglycemiaMetabolism and nutrition disorders2/32
DizzinessNervous system disorders2/32
HypotensionVascular disorders2/32
Alanine aminotransferase increasedInvestigations1/32
HeadacheNervous system disorders1/32
Sore throatRespiratory, thoracic and mediastinal disorders1/32
NauseaGastrointestinal disorders1/32
Gastroesophageal reflux diseaseGastrointestinal disorders1/32

Baseline characteristics

Age, Continuous
Age, Continuous(years)Study Participants
Mean59.0 ± 12.9
Sex: Female, Male
Sex: Female, Male(Participants)Study Participants
Female27
Male5
Ethnicity (NIH/OMB)
Ethnicity (NIH/OMB)(Participants)Study Participants
Hispanic or Latino32
Not Hispanic or Latino0
Unknown or Not Reported0
Race (NIH/OMB)
Race (NIH/OMB)(Participants)Study Participants
American Indian or Alaska Native32
Asian0
Native Hawaiian or Other Pacific Islander0
Black or African American0
White0
More than one race0
Unknown or Not Reported0
Region of Enrollment
Region of Enrollment(participants)Study Participants
Guatemala32
Systolic blood pressure
Systolic blood pressure(mmHg)Study Participants
Median132.0 (124.8 to 143.5)
Diastolic blood pressure
Diastolic blood pressure(mmHg)Study Participants
Mean80.8 ± 11.0
08

Study locations

1 site
  • San Lucas Mission
    San Lucas Tolimán, Departamento de Sololá 07013, Guatemala
09

References and documents

Publications

  • Mills KT, Bundy JD, Kelly TN, Reed JE, Kearney PM, Reynolds K, Chen J, He J. Global Disparities of Hypertension Prevalence and Control: A Systematic Analysis of Population-Based Studies From 90 Countries. Circulation. 2016 Aug 9;134(6):441-50. doi: 10.1161/CIRCULATIONAHA.115.018912. PubMed 27502908 ↗
  • Zhang D, Wang G, Joo H. A Systematic Review of Economic Evidence on Community Hypertension Interventions. Am J Prev Med. 2017 Dec;53(6S2):S121-S130. doi: 10.1016/j.amepre.2017.05.008. PubMed 29153113 ↗
  • Hunter DJ, Reddy KS. Noncommunicable diseases. N Engl J Med. 2013 Oct 3;369(14):1336-43. doi: 10.1056/NEJMra1109345. No abstract available. PubMed 24088093 ↗
  • Checkley W, Ghannem H, Irazola V, Kimaiyo S, Levitt NS, Miranda JJ, Niessen L, Prabhakaran D, Rabadan-Diehl C, Ramirez-Zea M, Rubinstein A, Sigamani A, Smith R, Tandon N, Wu Y, Xavier D, Yan LL; GRAND South Network, UnitedHealth Group/National Heart, Lung, and Blood Institute Centers of Excellence. Management of NCD in low- and middle-income countries. Glob Heart. 2014 Dec;9(4):431-43. doi: 10.1016/j.gheart.2014.11.003. PubMed 25592798 ↗
  • Vedanthan R, Bernabe-Ortiz A, Herasme OI, Joshi R, Lopez-Jaramillo P, Thrift AG, Webster J, Webster R, Yeates K, Gyamfi J, Ieremia M, Johnson C, Kamano JH, Lazo-Porras M, Limbani F, Liu P, McCready T, Miranda JJ, Mohan S, Ogedegbe O, Oldenburg B, Ovbiagele B, Owolabi M, Peiris D, Ponce-Lucero V, Praveen D, Pillay A, Schwalm JD, Tobe SW, Trieu K, Yusoff K, Fuster V. Innovative Approaches to Hypertension Control in Low- and Middle-Income Countries. Cardiol Clin. 2017 Feb;35(1):99-115. doi: 10.1016/j.ccl.2016.08.010. PubMed 27886793 ↗
  • Kim K, Choi JS, Choi E, Nieman CL, Joo JH, Lin FR, Gitlin LN, Han HR. Effects of Community-Based Health Worker Interventions to Improve Chronic Disease Management and Care Among Vulnerable Populations: A Systematic Review. Am J Public Health. 2016 Apr;106(4):e3-e28. doi: 10.2105/AJPH.2015.302987. Epub 2016 Feb 18. PubMed 26890177 ↗
  • Mishra SR, Neupane D, Preen D, Kallestrup P, Perry HB. Mitigation of non-communicable diseases in developing countries with community health workers. Global Health. 2015 Nov 10;11:43. doi: 10.1186/s12992-015-0129-5. PubMed 26555199 ↗
  • Khetan AK, Purushothaman R, Chami T, Hejjaji V, Madan Mohan SK, Josephson RA, Webel AR. The Effectiveness of Community Health Workers for CVD Prevention in LMIC. Glob Heart. 2017 Sep;12(3):233-243.e6. doi: 10.1016/j.gheart.2016.07.001. Epub 2016 Dec 16. PubMed 27993594 ↗
  • Svoronos T, Mjungu P, Dhadialla R, Luk R, Zue C, Jackson J, et al. CommCare: Automated quality improvement to strengthen community-based health. Weston: D-Tree International 2010
  • Unger T, Borghi C, Charchar F, Khan NA, Poulter NR, Prabhakaran D, Ramirez A, Schlaich M, Stergiou GS, Tomaszewski M, Wainford RD, Williams B, Schutte AE. 2020 International Society of Hypertension Global Hypertension Practice Guidelines. Hypertension. 2020 Jun;75(6):1334-1357. doi: 10.1161/HYPERTENSIONAHA.120.15026. Epub 2020 May 6. No abstract available. PubMed 32370572 ↗
  • Duffy S, Svenson J, Chavez A, Kelly M, Wise P. Empowering Community Health Workers With Mobile Technology to Treat Diabetes. Ann Fam Med. 2019 Mar;17(2):176. doi: 10.1370/afm.2361. No abstract available. PubMed 30858263 ↗
  • Duffy S, Norton D, Kelly M, Chavez A, Tun R, Ramirez MNG, Chen G, Wise P, Svenson J. Using Community Health Workers and a Smartphone Application to Improve Diabetes Control in Rural Guatemala. Glob Health Sci Pract. 2020 Dec 23;8(4):699-720. doi: 10.9745/GHSP-D-20-00076. Print 2020 Dec 23. PubMed 33361237 ↗
  • Duffy S, Chavez A, Arthur IS, Ortiz GL, Bermudez-Canete A, Nunez-Perez P, White E, Aguilar V, Aguirre J, Dang D, Perez Abaj CS, Letona Lopez YE, Tun R, Valley TM. Feasibility study of a novel mHealth clinical decision support application to enable community health workers to manage hypertension in rural Guatemala. J Glob Health. 2026 Jul 31;16:04232. doi: 10.7189/jogh.16.04232. PubMed 42533611 ↗

Study documents

  • Study protocol · Oct 2, 2023
  • Statistical analysis plan · Apr 12, 2022
  • Informed consent form · Jan 27, 2023

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jul 16, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT05479097
Responsible party
Sponsor
First posted
Jul 29, 2022
Start date
Feb 6, 2023
Primary completion
Aug 15, 2023
Completion
Dec 31, 2023
Results posted
Jul 16, 2024
Last update
Jul 16, 2024

Study contacts

Sean Duffy, MD
principal investigator · University of Wisconsin-Madison Department of Family Medicine and Community Health

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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