From Access to Engagement: Measuring Retention in Outpatient HIV Clinical Care

Mugavero, Michael J.; Davila, Jessica A.; Nevin, Christa R.; Giordano, Thomas P.

doi:10.1089/apc.2010.0086

Cited by 245 publications

(247 citation statements)

References 26 publications

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“…Researchers have assessed retention in care in a number of different ways. [21][22][23][24][25] These measures have their own strengths and weaknesses, 26 but none of them takes into account the fact that frequency of attendance is related to changes in treatment and health status and may also be affected by external forces or changes in clinic policy. In the UK, for example, guidelines at the time the REACH study was conducted indicated that patients should be seen within 2-4 weeks of starting ART and every 3-6 months for routine monitoring on ART if they were considered 'stable', with good adherence and an undetectable viral load.…”

Section: Chapter 1 Backgroundmentioning

confidence: 99%

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

Howarth

Apea

Michie

et al. 2017

Health Serv Deliv Res

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BackgroundAntiretroviral therapy (ART) benefits individuals living with human immunodeficiency virus (HIV) through reduced morbidity and mortality, and brings public health gains through a reduction in HIV transmission. People living with human immunodeficiency virus (PLWH) need to know their HIV status and engage in HIV care in order for these individual and public health benefits to be realised.ObjectiveTo explore, describe and understand HIV outpatient attendance in PLWH, in order to develop cost-effective interventions to optimise engagement in care.DesignA mixed-methods study incorporating secondary analysis of data from the UK Collaborative HIV Cohort (UK CHIC) study and primary data collection.MethodsPhase 1 – an engagement-in-care (EIC) algorithm was developed to categorise patients as in care or out of care for each month of follow-up. The algorithm was used in group-based trajectory analysis to examine patterns of attendance over time and of the association between the proportion of months in care before ART initiation and post-ART mortality and laboratory test costs. Phase 2 – a cross-sectional survey was conducted among patients attending seven London HIV clinics. Regular attenders (all appointments attended in past year), irregular attenders (one or more appointments missed in past year) and non-attenders (recent absence of ≥ 1 year) were recruited. A ‘retention risk tool’ was developed to identify those at risk of disengaging from care. Individual in-depth interviews and focus groups were conducted with PLWH. Phase 3 – key informant interviews were conducted with HIV service providers. Interventions were developed from the findings of phases 2 and 3.ResultsPlots from group-based trajectory analysis indicated that four trajectories best fitted the data. Higher EIC is associated with reduced mortality but the association between EIC before starting ART, and post-ART mortality [relative hazard (RH) per 10% increase in EIC 0.29, 95% confidence interval (CI) 0.18 to 0.47] was attenuated after adjustment for fixed covariates and post-ART cluster of differentiation 4 counts and viral loads (RH 0.74, 95% CI 0.42 to 1.30). Small differences were found in pre-ART EIC and the costs of post-ART lab tests. The final model for the retention risk tool included age at diagnosis, having children, recreational drug use, drug/alcohol dependency, insufficient money for basic needs and use of public transport to get to the clinic. Quantitative and qualitative data showed that a range of psychological, social and economic issues were associated with disengagement from care. The negative impact of stigma on attendance was highlighted. Interventions were proposed that support a holistic approach to care including peer support, address stigma by holding clinics in alternative locations and involve training staff to encourage attendance.ConclusionsThe study shows the adverse health impacts of disengaging from HIV care and demonstrates the importance of the wider health and social context in managing HIV effectively. Although phase 1 analysis was based on UK data, phases 2 and 3 were limited to London. The interventions proposed are supported by the data but their cost-effectiveness requires testing. Future research is needed to evaluate the interventions, to validate our retention risk tool across populations and settings, and to fully analyse the economic costs of disengaging from HIV care.FundingThe National Institute for Health Research Health Services and Delivery Research programme. The UK CHIC study is funded by the Medical Research Council UK (grant numbers G0000199, G0600337, G0900274 and M004236).

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Section: Chapter 1 Backgroundmentioning

confidence: 99%

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

Howarth

Apea

Michie

et al. 2017

Health Serv Deliv Res

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“…This not only leads to poor clinical outcomes among such individuals but can also lead to the development of antiviral drug resistance and contribute to the ongoing spread of HIV in the community [23] [24]. Furthermore, since the initial ART regimen offers the best chance of viral suppression, immunologic recovery, and clinical stability, it is imperative that individuals be quickly integrated into a medical system that meets their needs [25].…”

Section: Introductionmentioning

confidence: 99%

Loss to Follow-Up among a Group of Patients with HIV and Severe Mental Illness in South Africa

Furin¹,

Gripshover²,

Jeenah³

et al. 2014

WJA

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Background: Persons with HIV and severe mental illness face numerous barriers in antiretroviral treatment adherence. More information is needed on reasons for loss of follow-up in this population. Methods: A retrospective analysis was conducted on adult HIV patients with a history of mental illness enrolled at an urban HIV clinic in Johannesburg, South Africa who discontinued care. Results: 24.8% of adult patients in the clinic discontinued follow-up during the study period. Of those discontinuing follow-up, 48 were successfully traced by home visits. Among this group, 21 (43.8%) were not engaged in care, 12 (25.0%) had transferred care, 9 (18.8%) were deceased, 3 (6.2%) had relocated, and 3 (6.2%) were missing. Transportation costs and distance, conflicts with work/school schedule, and confusion regarding when to return were the most frequently cited reasons for discontinuing follow-up. Conclusions: Although almost 25% of patients were lost to follow up, overall rates of retention in care for these patients were similar to those seen in other HIV-infected populations and higher than those seen among patients with psychiatric disease. Tracing patients through home visits proved to be an effective means to confirm the magnitude of patients lost to follow up, ascertain their outcomes, and elucidate the reasons for discontinuing care.

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“…Laboratory data have been widely used as surrogate measures when data on primary care encounters are unavailable, as is often the case in large surveillance studies using public health laboratory data or cross-sectional population-based surveys that sample across defined geographic areas (e.g., county or state surveys). Such measures have been shown to be good indicators of initial or overall access to clinical HIV care (17), but there are no longitudinal data regarding concordance between measures of retention defined by HIV primary care encounters and those using surrogate laboratory measures (6,9,18,19).…”

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confidence: 99%

Laboratory Measures as Proxies for Primary Care Encounters: Implications for Quantifying Clinical Retention Among HIV-Infected Adults in North America

Rebeiro¹,

Althoff²,

Lau³

et al. 2015

Am. J. Epidemiol.

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Because of limitations in the availability of data on primary care encounters, patient retention in human immunodeficiency virus (HIV) care is often estimated using laboratory measurement dates as proxies for clinical encounters, leading to possible outcome misclassification. This study included 83,041 HIV-infected adults from 14 clinical cohorts in the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) who had ≥1 HIV primary care encounters during 2000-2010, contributing 468,816 person-years of follow-up. Encounter-based retention (R EB ) was defined as ≥2 encounters in a calendar year, ≥90 days apart. Laboratory-based retention (R LB ) was defined similarly, using the dates of CD4-positive cell counts or HIV-1 RNA measurements. Percentage of agreement and the κ statistic were used to characterize agreement between R LB and R EB . Logistic regression with generalized estimating equations and stabilized inverse-probability-of-selection weights was used to elucidate temporal trends and the discriminatory power of R LB as a predictor of R EB , accounting for age, sex, race/ethnicity, primary HIV risk factor, and cohort site as potential confounders. Both R EB and R LB increased from 2000 to 2010 (from 67% to 78% and from 65% to 77%, respectively), though R EB was higher than R LB throughout (P < 0.01). R LB agreed well with R EB (80%-86% agreement; κ = 0.55-0.62, P < 0.01) and had a strong, imperfect ability to discriminate between persons retained and not retained in care by R EB (C statistic: C = 0.81, P < 0.05). As a proxy for R EB , R LB had a sensitivity and specificity of 84% and 77%, respectively, with misclassification error of 18%. clinical encounters; clinical retention; HIV; laboratory measurements; measurement error; misclassification; proxies Abbreviations: AIDS, acquired immunodeficiency syndrome; CI, confidence interval; HIV, human immunodeficiency virus; HIV-1, HIV type 1; IDU, injection drug user; IPW, inverse-probability-of-selection weights; NA-ACCORD, North American AIDS Cohort Collaboration on Research and Design; ROC, receiver operating characteristic; ROR, ratio of odds ratios.Access to health care and its utilization for clinical monitoring in both healthy populations (for preventive care) and unhealthy populations (for treatment) are vital components of improving health outcomes. The reliable and ongoing use of clinical services by patients as part of disease management, or retention in care, is one such indicator of health-care utilization. Epidemiologic tools have long been recognized as being both available and useful for evaluation of evidence and formulation of policies for health services (1). With healthcare reform (e.g., the Affordable Care Act) removing barriers to linkage to care in the United States, an understanding of how people seek health care and are retained in care is likely to become increasingly valuable (2, 3). These questions speak to identifying disparities in our health-care system and may have a large impact on patient outcomes.The study of...

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From Access to Engagement: Measuring Retention in Outpatient HIV Clinical Care

Abstract: Engagement in HIV care is increasingly recognized as a crucial step in maximizing individual patient outcomes.

Cited by 245 publications

References 26 publications

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

REACH: a mixed-methods study to investigate the measurement, prediction and improvement of retention and engagement in outpatient HIV care

Loss to Follow-Up among a Group of Patients with HIV and Severe Mental Illness in South Africa

Laboratory Measures as Proxies for Primary Care Encounters: Implications for Quantifying Clinical Retention Among HIV-Infected Adults in North America

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