| Literature DB >> 34670624 |
Martin Muddu1,2, Fred C Semitala3,4,5, Isaac Ssinabulya2,6,7, Simon P Kigozi8, Rebecca Ssennyonjo1, Florence Ayebare9, Rodgers Katwesigye1, Mary Mbuliro1, Isaac Kimera1, Chris T Longenecker10, Moses R Kamya1,2,6,8, Jeremy I Schwartz2,11, Anne R Katahoire9.
Abstract
BACKGROUND: Persons living with HIV (PLHIV) receiving antiretroviral therapy (ART) have a high prevalence of hypertension (HTN) and increased risk of mortality from cardiovascular diseases. HTN and HIV care integration is recommended in Uganda, though its implementation has lagged. In this study, we sought to analyze the HTN and HIV care cascades and explore barriers and facilitators of HTN/HIV integration within a large HIV clinic in urban Uganda.Entities:
Keywords: Barriers; COM-B; Facilitators; Hypertension and HIV integration; Uganda
Year: 2021 PMID: 34670624 PMCID: PMC8690902 DOI: 10.1186/s43058-021-00223-9
Source DB: PubMed Journal: Implement Sci Commun ISSN: 2662-2211
Taxonomy of mixed methods design for the study (adopted from Palinkas et al.)
| Element | Category | Definition |
|---|---|---|
| Sequential QUAN͢qual | Sequential collection and analysis of quantitative and qualitative data, beginning with quantitative data, for the primary purpose of determining the integrated HTN-HIV care cascades. | |
| Expansion | We used quantitative data to determine the performance/outcomes of integrated HTN-HIV care cascades and qualitative data to elucidate the barriers and facilitators of implementing integrated HTN-HIV care. | |
| Connecting the data | The qualitative data set built upon the quantitative data set. The quantitative data set determined the integrated HTN-HIV care cascades and identified the successes and performance gaps. The qualitative data set contextualized the quantitative data by exploring the perceived barriers and facilitators of integrated HTN-HIV care. |
Fig. 1The Capability, Opportunity, Motivation influences Behavior (COM-B) domains which revealed either barriers or facilitators of integrating HTN management into HIV care
Number and characteristics of participants for the qualitative study
| Data collection methods | Number and category of participants | Total participants | Female | Mean age ( |
|---|---|---|---|---|
| Focus group discussions (FGDs) for patients | Patients who had both HTN and HIV (4 FGDs) | 26 | 18 (69.0%) | 52.0 (± 9.5) |
| In-depth interviews (IDIs) for patients | Patients who had both HTN and HIV (6 IDIs) | 6 | 4 (66.7%) | 44.0 (± 9.8) |
| Key informant interviews (KIIs) for healthcare providers | Doctor | 2 | 1 (50.0%) | N/A |
| Nurse | 3 | 2 (66.7%) | N/A | |
| Clinical officer | 3 | 2 (66.7%) | N/A | |
| Pharmacy technician | 2 | 1 (50.0%) | N/A | |
| HIV/HTN counselor | 2 | 1 (50.0%) | N/A | |
| HIV/HTN peer educator | 1 | 1 (100%) | N/A | |
Baseline characteristics of the study participants
| Characteristic | Overall cohort ( | HIV ( | HIV and HTN ( | |
|---|---|---|---|---|
| Age, yrs | 40.7 ( | 39.4 ( | 44.7 ( | <0.001 |
| Age categories, yrs | <0.001 | |||
| 18 to 30 | 1983 (12.4%) | 1728 (14.3%) | 255 (6.6%) | |
| 31 to 50 | 11,458 (71.8%) | 8892 (73.7%) | 2566 (65.9%) | |
| Over 50 | 2411 (15.1%) | 1349 (11.2%) | 1062 (27.3%) | |
| Sex | <0.001 | |||
| Male | 5077 (31.8%) | 3521 (29.2%) | 1556 (40.0%) | |
| Female | 10,876 (68.2%) | 8540 (70.8%) | 2336 (60.0%) | |
| Baseline BP, mm Hg | ||||
| Systolic | 119.2 ( | 115.5 ( | 145.7 ( | <0.001 |
| Diastolic | 77.0 ( | 74.7 ( | 93.8 ( | <0.001 |
| Baseline ART regimen | <0.001 | |||
| TDF-3TC-EFV | 7258 (45.9%) | 5918 (49.7%) | 1340 (34.5%) | |
| AZT-3TC-NVP | 4227 (26.7%) | 2929 (24.6%) | 1298 (33.4%) | |
| AZT-3TC-EFV | 1801 (11.4%) | 1306 (11.0%) | 495 (12.7%) | |
| TDF-3TC-NVP | 1054 (6.7%) | 752 (6.3%) | 302 (7.8%) | |
| Others | 1470 (9.3%) | 1015 (8.5%) | 455 (11.7%) | |
| Duration on ART | <0.001 | |||
| < 2 years | 3638 (23.0%) | 2885 (24.2%) | 753 (19.4%) | |
| 2 to 5yrs | 5512 (34.9%) | 4453 (37.4%) | 1059 (27.2%) | |
| 5 to 10yrs | 5675 (35.9%) | 4004 (33.6%) | 1671 (43.0%) | |
| > 10yrs | 985 (6.2%) | 578 (4.9%) | 407 (10.5%) | |
| Baseline CD4 count | 365.3 ( | 365.9 ( | 363.6 ( | 0.674 |
| Baseline CD4 count by category | 0.162 | |||
| <50 | 2110 (13.2%) | 1610 (13.4%) | 500 (12.9%) | |
| 50–<100 | 1041 (6.5%) | 760 (6.3%) | 281 (7.2%) | |
| 100–<200 | 2123 (13.3%) | 1591 (13.2%) | 532 (13.7%) | |
| >200 | 10,657 (66.9%) | 8080 (67.1%) | 2577 (66.3%) | |
| Baseline BMI, | 0.130 | |||
| Underweight (<19.0) | 1221 (8.1%) | 887 (7.8%) | 334 (9.0%) | |
| Normal weight (19.0 to <25.0) | 6774 (44.9%) | 5122 (45.0%) | 1652 (44.6%) | |
| Overweight (25.0 to <30.0) | 4175 (27.7) | 3159 (27.8%) | 1016 (27.4%) | |
| Obese (≥30.0) | 2913 (19.3) | 2210 (19.4%) | 703 (19.0%) | |
Association between hypertension and sex, age, ART regiment, and duration on ART among PLHIV at the Mulago ISS clinic
| Risk factor | Univariate | Multi-variate | ||
|---|---|---|---|---|
| Odds ratio ( | Odds ratio ( | |||
| Male | ||||
| Female | 0.64 (0.59–0.68) | <0.001 | 0.65 (0.60–0.71) | <0.001 |
| 18–30 years | ||||
| 31–50 years | 7.32 (3.76–14.26) | <0.001 | 3.01 (1.51–6.01) | 0.002 |
| Over 50 years | 19.76 (10.11–38.64) | <0.001 | 7.08 (3.53–14.19) | <0.001 |
| TDF-3TC-EFV | ||||
| AZT-3TC-EFV | 1.65 (1.47–1.86) | <0.001 | 1.04 (0.91–1.20) | 0.557 |
| TDF-3TC-NVP | 1.74 (1.51–2.01) | <0.001 | 1.54 (1.31–1.81) | <0.001 |
| AZT-3TC-NVP | 1.92 (1.76–2.09) | <0.001 | 1.64 (1.47–1.83) | <0.001 |
| Other | 1.78 (1.57–2.01) | <0.001 | 1.31 (1.13–1.52) | <0.001 |
| <2 years | ||||
| 2 to 5 years | 0.91 (0.82–1.01) | 0.081 | 0.78 (0.70–0.87) | <0.001 |
| 5 to 10 years | 1.60 (1.45–1.76) | <0.001 | 0.99 (0.88–1.12) | 0.893 |
| >10 years | 2.70 (2.32–3.13) | <0.001 | 1.56 (1.30–1.87) | <0.001 |
Fig. 2Integrated hypertension-HIV care cascades at the Mulago ISS clinic. The proportions are the percentages of participants at each particular step of the cascade as compared to the previous cascade steps
Fig. 3Hypertension care cascade among PLHIV who were diagnosed with HTN at the Mulago ISS clinic. The proportions are the percentages of participants at each particular step of the cascade as compared to the previous cascade steps
Barriers and facilitators for integrated HTN/HIV care in the HIV clinic as related to the domains of COM-B model
| COM-B domain | Barriers | Facilitators |
|---|---|---|
| Patient lack of knowledge of HTN risk, complications, HTN-HIV drug interactions, and self-management | Healthcare providers have adequate knowledge of HTN screening | |
| Healthcare providers lack knowledge of treating HTN and HTN-HIV drug interactions | Healthcare providers and patients can leverage ART adherence support which is already being provided to PLHIV to provide adherence support for both HTN and HIV treatment | |
| Lack of monitoring indicators for HTN | ||
| There were no barriers in this domain | HTN/HIV peer educators and healthcare providers have adequate skills to screen for HTN among PLHIV | |
| Measuring BP is easy for most of the healthcare providers including HIV peer educators | ||
| Lack of simple evidence-based treatment protocol for HTN care | Availability of BP machines and staff to measure and record blood pressure | |
| Lack of on-site HTN medications despite demand from patients and providers | ||
| Cost of buying anti-hypertensive medicines is high; patients cannot afford | ||
| Inadequate maintenance of automated BP machines at the HIV clinic | ||
| Lack of data collection tools and databases for HTN care | ||
| HTN prescriptions are mainly done by doctors; limited task shifting to clinical officers and nurses | Patients are interested in being supported by PLHIV peer educators to improve adherence to HTN and HIV treatment | |
| Patients prioritize adherence to ART over HTN medications | Patients and healthcare providers have great interest in HTN/HIV integrated care | |
| Lack of performance targets and review of HTN care quality | There were no facilitators in this domain |