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Strengthening Referral Networks for Management of Hypertension Across the Health System (STRENGTHS)

Strengthening Referral Networks for Management of Hypertension Across the Health System (STRENGTHS)

Status
UNKNOWN
Phases
Phase 3
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03543787
Acronym
STRENGTHS
Enrollment
1600
Registered
2018-06-01
Start date
2020-01-17
Completion date
2023-05-31
Last updated
2023-03-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hypertension

Keywords

Referral networks, low and middle income countries, PRECEDE-PROCEED, implementation research, hypertension, cardiovascular disease, process evaluation

Brief summary

STRENGTHS is a transdisciplinary implementation research study, guided by the PRECEDE-PROCEED framework, to address the challenge of improving hypertension control in low-resource settings. The investigators propose to test the hypothesis that referral networks strengthened by an integrated health information technology and peer support intervention will be effective and cost-effective in improving hypertension control among patients in western Kenya. The investigators hypothesise that the integrated Health information Technology and Peer Support intervention will facilitate seamless referral of hypertensive patients across the different levels of the health system compared to usual care, leading to improvement in blood pressure. If proven to be successful, STRENGTHS can serve as a model for improving referral of patients upstream and downstream in health systems worldwide.

Detailed description

Hypertension is a major risk factor for cardiovascular disease, and 80% of global mortality due to cardiovascular diseases occurs in low- and middle-income countries. In low income countries, lack of coordination between different levels of the health system threatens the ability to provide the care necessary to control hypertension and prevent cardiovascular disease related morbidity. Strong referral networks have improved health outcomes for chronic disease in a variety of settings. Health information technology and peer-based support are two strategies that have improved care coordination and clinical outcomes. However, their effectiveness in strengthening referral networks to improve blood pressure control and reduce cardiovascular disease risk in low-resource settings is unknown. The Academic Model Providing Access to Healthcare (AMPATH) partners with the Kenya Ministry of Health to provide care for non-communicable chronic diseases (NCDs), including hypertension at all levels of the health system. The Kenya Ministry of Health Sector Referral Strategy 2014-2018 calls for improving the referral system at every level of the health system. AMPATH has piloted both health information technology and peer support for NCDs, and both strategies are feasible in this setting. However, the impact of integrating Health information technology and peer support to strengthen referral networks for hypertension control is unknown. The proposal's objective is to utilise the PRECEDE-PROCEED framework to conduct trans-disciplinary, translational implementation research focused on strengthening referral networks for hypertension control. The central hypothesis is Health Information Technology integrated with peer support will be effective and cost-effective in strengthening referral networks, improving blood pressure control, and reducing cardiovascular risk among hypertensive patients in western Kenya. The investigators hypothesise that Health information technology(HIT) and peer support(PS) will synergistically address barriers to hypertension control at the patient, provider and health system levels. The investigators further hypothesise that changes in referral network characteristics may mediate the impact of the intervention on the primary outcome, and that baseline referral net-work characteristics may moderate the impact of the intervention. To test these hypotheses and achieve the overall objective, STRENGTHS has the following specific aims: Aim 1: Conduct a baseline needs and contextual assessment for implementing and integrating HIT and PS to strengthen referral networks for hypertension control, using a mixed-methods approach, including: observational process mapping and gap assessment; baseline referral network analysis; and qualitative methods to identify facilitators, barriers, contextual factors, and readiness for change. Sub-Aim 1.1: Use data from the aim 1 to develop a contextually and culturally appropriate intervention to strengthen referral networks for hypertension control using a participatory, iterative design process. Conduct pilot acceptability and feasibility testing of the intervention. Aim 2: Evaluate the effectiveness of HIT and PS for hypertension control by conducting a two-arm cluster randomized trial comparing: 1) usual care vs. 2) referral networks strengthened with an integrated HIT-PS intervention. The primary outcome will be one-year change in systolic blood pressure and a key secondary outcome will be cardiovascular risk reduction. Sub-Aim 2.1: Conduct mediation analysis to evaluate the influence of changes in referral network characteristics on intervention outcomes, and a moderation analysis to evaluate the influence of baseline referral net-work characteristics on the effectiveness of the intervention. Sub-Aim 2.2: Conduct a process evaluation using the Saunders framework, evaluating key implementation measures related to fidelity, dose delivered, dose received, recruitment, reach, and context. Aim 3: Evaluate the incremental cost-effectiveness of the intervention, in terms of costs per unit decrease in SBP, per percent change in CVD risk score, and per disability-adjusted life year (DALY) saved. This research project will add to the existing knowledge base on innovative and scalable strategies for strengthening referral networks to improve control of NCDs in lower-MICs. If proven to be effective, it has the potential to be a scalable model for other low-resource settings globally.

Interventions

COMBINATION_PRODUCTHealth IT and Peer Support Intervention

Health IT will support referral system by establishing 1) communication between healthcare providers and peer navigators 2) decision support for clinician to facilitate appropriate referrals 3) tracking of referred patients real-time 4) dashboards to monitor key evaluation metrics. Peer Support intervention: peer navigators at each level of the referral network will ensure 1) referral adherence by link clinicians and patients 2) health system navigation 3) psychosocial support: leverage their shared disease experience to help patients overcome barriers to health seeking behaviour.

Sponsors

Indiana University
CollaboratorOTHER
Duke University
CollaboratorOTHER
Icahn School of Medicine at Mount Sinai
CollaboratorOTHER
Purdue University
CollaboratorOTHER
University of Texas at Austin
CollaboratorOTHER
Moi University
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE

Intervention model description

PRECEDE-PROCEED implementation research framework; 2-arm cluster randomized controlled trial

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* \>= 18 yrs * Enrolled in AMPATH CDM Program * meet criteria for referral up or down the network * Patients with complicated hypertension meet criteria for referral up the network, defined as patients with hypertension who remain uncontrolled (SBP \>= 140 or DBP \>= 90) on 3 or more anti-hypertensive medications, who have signs or symptoms of end-organ damage, or who have suspected secondary causes of hypertension (age \<35 years, HIV, or pregnancy) * Patients with stable, uncomplicated hypertension meet criteria for referral down the network, defined as controlled BP (SBP \< 140 and DBP \< 90) for 3 or more consecutive visits and no evidence of new end-organ damage

Exclusion criteria

* acute illness requiring immediate medical attention * terminal illness * inability to provide informed consent

Design outcomes

Primary

MeasureTime frameDescription
Change in one year systolic blood pressure as measured in clinic1 yearThe systolic blood pressure at baseline will be compared to systolic blood after 1 year of follow up. Blood pressure measurements will be averaged from three successive readings taken every 5 minutes in clinic

Secondary

MeasureTime frameDescription
Change in one year overall Cardiovascular disease (CVD) QRISK2 score1 yearQRISK2 score is a computerised algorithm for predicting the ten-year risk of developing CVD events. The factors that enter into the calculation of the QRISK2 score include: Age 25-84 years, sex, ethnicity, smoking status, diabetes status, family history of coronary artery disease in first degree relatives below the age of 65 years, chronic kidney disease stages 4 and 5, atrial fibrillation, rheumatoid arthritis, cholesterol / high density lipoprotein ratio, systolic blood pressure, body mass index. A score of 10% or more suggest a 10% risk of primary CVD events in ten years and warrants intervention to reduce the risk. It's not used among patients who already have a heart attack or a stroke.
Mortality1 year follow upDeath at the end of the study
Hospitalisation1 year of follow upNumber of self-reported hospital admissions for hypertensive crises or heart failure among participants over one year follow up.
Change in number of CVD risk factors and behaviors as assessed using a standardised screening questionnaire1 yearBaseline risk factor profile compared to profile at 1 year of the various CVD risk factors as assessed using a standardised CVD risk factors and behaviours screening questionnaire
Self reported adherence to hypertension medication as assessed using the Morisky Medication adherence questionnaire1 yearTo assess changes in adherence to hypertension medications at one year from baseline as determined using the Morisky medication adherence questionnaire
Cardiovascular disease complications1 year follow upAny cardiovascular complications including Heart failure, Stroke and Acute myocardial infarction

Other

MeasureTime frameDescription
Referral network characteristics1 yearTo assess the referral densities within the healthcare system.
Referral proces characteristics1 yearTo assess referral completion rates within the healthcare system

Countries

Kenya

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Mar 2, 2026