Are missed- and kept-visit measures capturing different aspects of retention in HIV primary care?

The literature recognizes six measures of retention in care, an integral component of the HIV Continuum of Care. Given prior research showing that different retention measures are differentially associated with HIV health outcomes (e.g., CD4 count and viral suppression), we hypothesized that different groups of people living with HIV (PLWH) would also have differential retention outcomes based on the retention measure applied. We conducted a cross-sectional analysis of multisite patient-level medical record data (n = 10,053) from six academically-affiliated HIV clinics using six different measures of retention. Principal component analysis indicated two distinct retention constructs: kept-visit-measures and missed-visit measures. Although black (compared to white) PLWH had significantly poorer retention on the three missed-visit measures, race was not significantly associated with any of the three kept-visit measures. Males performed significantly worse than females on all kept-visit measures, but sex differences were not observed for any missed-visit retention measures. IDU risk transmission group and younger age were associated with poorer retention on both missed- and kept-visit retention measures. Missed- and kept-visit measures may capture different aspects of retention, as indicated in the observed differential associations among race, sex, age, and risk transmission group. Multiple measures are needed to effectively assess retention across patient subgroups.

Evaluation of a computer-based and counseling support intervention to improve HIV patients' viral loads.

We sought to integrate a brief computer and counseling support intervention into the routine practices of HIV clinics and evaluate effects on patients' viral loads. The project targeted HIV patients in care whose viral loads exceeded 1000 copies/ml at the time of recruitment. Three HIV clinics initiated the intervention immediately, and three other HIV clinics delayed onset for 16 months and served as concurrent controls for evaluating outcomes. The intervention components included a brief computer-based intervention (CBI) focused on antiretroviral therapy adherence; health coaching from project counselors for participants whose viral loads did not improve after doing the CBI; and behavioral screening and palm cards with empowering messages available to all patients at intervention clinics regardless of viral load level. The analytic cohort included 982 patients at intervention clinics and 946 patients at control clinics. Viral loads were assessed at 270 days before recruitment, at time of recruitment, and +270 days later. Results indicated that both the control and intervention groups had significant reductions in viral load, ending with approximately the same viral level at +270 days. There was no evidence that the CBI or the targeted health coaching was responsible for the viral reduction in the intervention group. Results may stem partially from statistical regression to the mean in both groups. Also, clinical providers at control and intervention clinics may have taken action (e.g., conversations with patients, referrals to case managers, adherence counselors, mental health, substance use specialists) to help their patients reduce their viral loads. In conclusion, neither a brief computer-based nor targeted health coaching intervention reduced patients' viral loads beyond levels achieved with standard of care services available to patients at well-resourced HIV clinics.

Time spent with HIV viral load above 1500 copies/ml among patients in HIV care, 2000-2014.

OBJECTIVE: Sexual HIV transmission is more likely to occur when plasma HIV RNA level (viral load) exceeds 1500 copies/ml. We assessed the percentage of person-time spent with viral load above 1500 copies/ml (pPT >1500) among adults with HIV in care. DESIGN: Observational cohort in eight United States HIV clinics. METHODS: Participants had at least one HIV Outpatient Study (HOPS) clinic visit and at least two viral loads during 2000-2014. We assessed pPT above 1500 in time intervals between consecutive viral load pairs, overall and by ART status. Trends in pPT above 1500 and associations between pPT above 1500 and chosen baseline demographics and clinical characteristics were analyzed using generalized estimating equations. RESULTS: There were 5873 patients contributing 37 794 person-years; 86.0% person-years had prescribed ART, with increasing coverage over time. Over 2000-2014 pPT above 1500 was 24.2%, decreasing from 38.3% in 2000-2002 to 11.3% in 2012-2014. During observation time with ART prescribed, pPT above 1500 was 16.4% overall, decreasing from 29.9% in 2000-2002 to 8.0% in 2012-2014. pPT above 1500 was higher in patients less than 35 vs. at least 50 years old (31.5 vs. 15.6%), women vs. men (30.8 vs. 22.3%), and black vs. white and Latino/Hispanic patients (32.7 vs. 19.9 and 23.7%, respectively). Multivariable correlates of higher pPT above 1500 included no prescribed ART, being younger, non-Hispanic black vs. white, baseline viral load above 1500 copies/ml or lower CD4 count, and baseline public vs. private insurance. CONCLUSION: pPT above 1500 declined during 2000-2014. Results support decreasing HIV transmission risk from persons in HIV care over the last decade, and the need to focus interventions on patient groups more consistently viremic.

Gaps Up To 9 Months Between HIV Primary Care Visits Do Not Worsen Viral Load.

Current guidelines specify that visit intervals with viral monitoring should not exceed 6 months for HIV patients. Yet, gaps in care exceeding 6 months are common. In an observational cohort using US patients, we examined the association between gap length and changes in viral load status and sought to determine the length of the gap at which significant increases in viral load occur. We identified patients with gaps in care greater than 6 months from 6399 patients from six US HIV clinics. Gap strata were >6 to <7, 7 to <8, 8 to <9, 9 to <12, and ≥12 months, with viral load measurements matched to the opening and closing dates for the gaps. We examined visit gap lengths in association with two viral load measurements: continuous (log10 viral load at gap opening and closing) and dichotomous (whether patients initially suppressed but lost viral suppression by close of the care gap). Viral load increases were nonsignificant or modest when gap length was <9 months, corresponding to 10% or fewer patients who lost viral suppression. For gaps ≥12 months, there was a significant increase in viral load as well as a much larger loss of viral suppression (in 23% of patients). Detrimental effects on viral load after a care gap were greater in young patients, black patients, and those without private health insurance. On average, shorter gaps in care were not detrimental to patient viral load status. HIV primary care visit intervals of 6 to 9 months for select patients may be appropriate.

Do Persons Living with HIV Continue to Fill Prescriptions for Antiretroviral Drugs during a Gap in Care? Analysis of a Large Commercial Claims Database.

The significance of a gap in HIV care depends, at least partially, on whether patients continue to fill prescriptions for antiretroviral (ARV) drugs during the gap in care. We used a billing claims database to determine the proportion of persons who filled ≥1 prescription for ARV drugs during a gap in care (no clinic visit in >6 months). Persons were stratified into 3 groups: "never" (prescriptions never filled), "sometimes" (prescriptions filled >0%-<100% of months), and "always" (prescriptions filled monthly). Logistic regression analyses were conducted to determine factors associated with "never" filling ARV drugs. Of 14 308 persons, 69% (n = 9817), 13% (n = 1928), and 18% (n = 2563) "never," "sometimes," and "always" filled ARV drugs during the gap in care. Persons aged 18 to 29 years (odds ratio [OR] = 1.56, 95% confidence interval [CI] 1.39-1.74), women (OR = 1.67, CI 1.52-1.83), and persons from the Northeast region of the United States (OR = 1.86, CI 1.69-2.03) were more likely to never fill ARV drugs than persons aged ≥30 years, men, and persons outside the Northeast, respectively. Efforts should be made to minimize gaps in care, emphasize importance of therapy, and provide adherence support.

Reengagement in Care After a Gap in HIV Care Among a Population of Privately Insured Persons with HIV in the United States.

The HIV care continuum illustrates steps needed to reach HIV viral suppression, including retention in care. The continuum's retention measure does not account for gaps or reengagement in care and thus provides an incomplete picture of long-term engagement. We used a claims database to determine the proportion of privately insured persons with HIV who experienced a gap in care and subsequently reengaged between 2008 and 2012. A gap was defined as no office visit claim in >6 months and reengagement as ≥1 office visit claim after a gap. Cox proportional hazards models were conducted to determine factors associated with time to first gap and time to reengagement. Of 5142 persons in the study, 79% were males and median age was 46 years (range, 19-64 years). No race/ethnicity data were available. Thirty percent (n = 1555) experienced a gap. Median time to first gap was 15 months (IQR: 6-30). Median gap length was 3.2 months. Seventy percent with a gap reengaged; 22% reengaged more than once. Of 1086 patients who reengaged, 224 (21%) eventually had a terminal gap. Residence in the North Central region (HR 0.73, 95% CI 0.62-0.87) and having ≥1 Charlson comorbidities (HR 0.85, 95% CI 0.73-0.99) were associated with shorter time to reengagement. The majority who experienced a gap reengaged within a relatively short period and remained in the cohort at 60 months. However, 21% of those reengaging had a terminal gap by 60 months, which should alert providers to the eventual potential for loss to follow-up. The analysis was limited by inability to distinguish between HIV-specific and non-HIV-specific care visits.

Faster entry into HIV care among HIV-infected drug users who had been in drug-use treatment programs.

OBJECTIVE: We evaluated whether being in drug use treatment improves linkage to HIV medical care for HIV-infected drug users. We assessed whether an evidence-based intervention for linkage to care ['ARTAS'] works better for HIV-infected drug users who had been in drug use treatment than those who had not. DESIGN: Randomized trial. METHODS: 295 Participants in the Antiretroviral Treatment Access Study ['ARTAS'] trial were followed for time to first HIV medical care. Drug use (injected and non-injected drugs) in the last 30days and being in drug treatment in the last 12 months were assessed by audio-CASI. We used a proportional hazards model of time to care in drug users with and without drug treatment, adjusting for barriers to care, AIDS symptoms, and demographic factors. We tested whether drug treatment modified the intervention effect by using a drug use/drug treatment*intervention interaction term. RESULTS: Ninety-nine participants (30%) reported drug use in the 30days before enrollment. Fifty-three (18%) reported being in a drug treatment program in the last 12 months. Drug users reporting methadone maintenance became engaged in care in less than half the time of drug users without a treatment history [HR 2.97 (1.20, 6.21)]. The ARTAS intervention effect was significantly larger for drug users with a treatment history compared to drug users without a treatment history (AHR 5.40, [95% CI, 2.03-14.38]). CONCLUSIONS: Having been in drug treatment programs facilitated earlier entry into care among drug users diagnosed with HIV infection, and improved their response to the ARTAS linkage intervention.

Single Viral Load Measurements Overestimate Stable Viral Suppression Among HIV Patients in Care: Clinical and Public Health Implications.

BACKGROUND: The HIV continuum of care paradigm uses a single viral load test per patient to estimate the prevalence of viral suppression. We compared this single-value approach with approaches that used multiple viral load tests to examine the stability of suppression. METHODS: The retrospective analysis included HIV patients who had at least 2 viral load tests during a 12-month observation period. We assessed the (1) percent with suppressed viral load (<200 copies/mL) based on a single test during observation, (2) percent with suppressed viral loads on all tests during observation, (3) percent who maintained viral suppression among patients whose first observed viral load was suppressed, and (4) change in viral suppression status comparing first with last measurement occasions. Prevalence ratios compared demographic and clinical subgroups. RESULTS: Of 10,942 patients, 78.5% had a suppressed viral load based on a single test, whereas 65.9% were virally suppressed on all tests during observation. Of patients whose first observed viral load was suppressed, 87.5% were suppressed on all subsequent tests in the next 12 months. More patients exhibited improving status (13.3% went from unsuppressed to suppressed) than worsening status (5.6% went from suppressed to unsuppressed). Stable suppression was less likely among women, younger patients, black patients, those recently diagnosed with HIV, and those who missed ≥1 scheduled clinic visits. CONCLUSIONS: Using single viral load measurements overestimated the percent of HIV patients with stable suppressed viral load by 16% (relative difference). Targeted clinical interventions are needed to increase the percent of patients with stable suppression.

Assessing efficacy of a retention-in-care intervention among HIV patients with depression, anxiety, heavy alcohol consumption and illicit drug use.

OBJECTIVE: We evaluated whether heavy alcohol use, illicit drug use or high levels of anxiety, and depression symptoms were modifiers of the retention through enhanced personal contact intervention. The intervention had previously demonstrated overall efficacy in the parent study. DESIGN: Randomized trial. METHODS: A total of 1838 patients from six US HIV clinics were enrolled into a randomized trial in which intervention patients received an 'enhanced contact' protocol for 12 months. All participants completed an audio computer-assisted self-interview that measured depression and anxiety symptoms from the Brief Symptom Inventory, alcohol use from the Alcohol Use Disorders Identification Test-Consumption instrument, and drug use from the WHO (Alcohol, Smoking and Substance Involvement Screening Test) questions. The 12-month binary outcome was completing an HIV primary care visit in three consecutive 4-month intervals. The outcome was compared between intervention and standard of care patients within subgroups on the effect modifier variables using log-binomial regression models. RESULTS: Persons with high levels of anxiety or depression symptoms and those reporting illicit drug use, or heavy alcohol consumption had no response to the intervention. Patients without these 'higher risk' characteristics responded significantly to the intervention. Further analysis revealed higher risk patients were less likely to have successfully received the telephone contact component of the intervention. Among higher risk patients who did successfully receive this component, the intervention effect was significant. CONCLUSION: Our findings suggest that clinic-based retention-in-care interventions are able to have significant effects on HIV patients with common behavioral health issues, but the design of those interventions should assure successful delivery of intervention components to increase effectiveness.

Evaluating patterns in retention, continuation, gaps, and re-engagement in HIV care in a Medicaid-insured population, 2006-2012, United States.

We used the US-based MarketScan(®) Medicaid Multi-state Databases to determine the un-weighted proportion of publically insured persons with HIV that were retained, continued, and re-engaged in care. Persons were followed for up to 84 months. Cox proportional hazards models were conducted to determine factors associated with gaps in care. Of the 6463 HIV cases identified in 2006, 61% were retained during the first 24 months, and 53% continued in care through 78 months. Between 8% and 30% experienced a gap in care, and 59% of persons who experienced a gap in care later re-engaged in care. Persons with one or more Charlson co-morbidities (HR 0.72, 95% CI 0.64-0.81), ages 40-59 (0.79, 0.71-0.88), mental illness diagnosis (0.79, 0.72-0.87), hepatitis C co-infection (0.83, 0.75-0.93), and female sex (0.86, 0.78-0.94) were less likely to experience a gap in care. Between 27% and 38% of those not retained in care continued to receive HIV-related laboratory services. This Medicaid claims database combines features of both clinic visits-based and surveillance lab-based surrogate measures to give a more complete picture of engagement in care than single-facility-based studies.

The Contribution of Missed Clinic Visits to Disparities in HIV Viral Load Outcomes.

OBJECTIVES: We explored the contribution of missed primary HIV care visits ("no-show") to observed disparities in virological failure (VF) among Black persons and persons with injection drug use (IDU) history. METHODS: We used patient-level data from 6 academic clinics, before the Centers for Disease Control and Prevention and Health Resources and Services Administration Retention in Care intervention. We employed staged multivariable logistic regression and multivariable models stratified by no-show visit frequency to evaluate the association of sociodemographic factors with VF. We used multiple imputations to assign missing viral load values. RESULTS: Among 10 053 patients (mean age = 46 years; 35% female; 64% Black; 15% with IDU history), 31% experienced VF. Although Black patients and patients with IDU history were significantly more likely to experience VF in initial analyses, race and IDU parameter estimates were attenuated after sequential addition of no-show frequency. In stratified models, race and IDU were not statistically significantly associated with VF at any no-show level. CONCLUSIONS: Because missed clinic visits contributed to observed differences in viral load outcomes among Black and IDU patients, achieving an improved understanding of differential visit attendance is imperative to reducing disparities in HIV.

A Comparison of Methods for Analyzing Viral Load Data in Studies of HIV Patients.

HIV RNA viral load (VL) is a pivotal outcome variable in studies of HIV infected persons. We propose and investigate two frameworks for analyzing VL: (1) a single-measure VL (SMVL) per participant and (2) repeated measures of VL (RMVL) per participant. We compared these frameworks using a cohort of 720 HIV patients in care (4,679 post-enrollment VL measurements). The SMVL framework analyzes a single VL per participant, generally captured within a "window" of time. We analyzed three SMVL methods where the VL binary outcome is defined as suppressed or not suppressed. The omit-participant method uses a 8-month "window" (-6/+2 months) around month 24 to select the participant's VL closest to month 24 and removes participants from the analysis without a VL in the "window". The set-to-failure method expands on the omit-participant method by including participants without a VL within the "window" and analyzes them as not suppressed. The closest-VL method analyzes each participant's VL measurement closest to month 24. We investigated two RMVL methods: (1) repeat-binary classifies each VL measurement as suppressed or not suppressed and estimates the proportion of participants suppressed at month 24, and (2) repeat-continuous analyzes VL as a continuous variable to estimate the change in VL across time, and geometric mean (GM) VL and proportion of participants virally suppressed at month 24. Results indicated the RMVL methods have more precision than the SMVL methods, as evidenced by narrower confidence intervals for estimates of proportion suppressed and risk ratios (RR) comparing demographic strata. The repeat-continuous method had the most precision and provides more information than other considered methods. We generally recommend using the RMVL framework when there are repeated VL measurements per participant because it utilizes all available VL data, provides additional information, has more statistical power, and avoids the subjectivity of defining a "window."

Time above 1500 copies: a viral load measure for assessing transmission risk of HIV-positive patients in care.

OBJECTIVE: We examined HIV transmission potential of patients in care by analyzing the amount of person-time spent above a viral load threshold that increases risk for transmission. DESIGN: Observational cohort and supplemental data. METHODS: The cohort included HIV patients who received care at six HIV clinics in the United States, from 1 April 2009 to 31 March 2013, and had two or more viral load tests during this interval. Person-time (in days) above a viral load of 1500 copies/ml out of the total observation time was determined by inspecting consecutive pairs of viral load results and the time intervals between those pairs. The person-time rate ratios comparing demographic and clinical subgroups were estimated with Poisson regression. RESULTS: The cohort included 14 532 patients observed for a median of 1073 days with a median of nine viral load records. Ninety percent of the patients had been prescribed antiretroviral therapy. On average, viral load exceeded 1500 copies/ml during 23% of the patients' observation time (average of 84 days per year, per patient). Percentage of person-time above the threshold was higher among patients who had more than a fourth of their viral load pairs exceeding a 6-month interval (34% of observation time), patients not on antiretroviral therapy (58% of time), new/re-engaging patients (34% of time), patients 16-39 years of age (32% of time), and patients of black race (26% of time). CONCLUSION: HIV patients in care spent an average of nearly a quarter of their time with viral loads above 1500 copies/ml, higher among some subgroups, placing them at risk for potentially transmitting HIV to others.

Clinic-wide intervention lowers financial risk and improves revenue to HIV clinics through fewer missed primary care visits.

: We calculated the financial impact in 6 HIV clinics of a low-effort retention in care intervention involving brief motivational messages from providers, patient brochures, and posters. We used a linear regression model to calculate absolute changes in kept primary care visits from the preintervention year (2008-2009) to the intervention year (2009-2010). Revenue from patients' insurance was also assessed by clinic. Kept visits improved significantly in the intervention year versus the preintervention year (P < 0.0001). We found a net-positive effect on clinic revenue of +$24,000/year for an average-size clinic (7400 scheduled visits/year). We encourage HIV clinic administrators to consider implementing this low-effort intervention.

Estimating the cost of increasing retention in care for HIV-infected patients: results of the CDC/HRSA retention in care trial.

BACKGROUND: Retaining HIV patients in medical care promotes access to antiretroviral therapy, viral load suppression, and reduced HIV transmission to partners. We estimate the programmatic costs of a US multisite randomized controlled trial of an intervention to retain HIV patients in care. METHODS: Six academically affiliated HIV clinics randomized patients to intervention (enhanced personal contact with patients across time coupled with basic HIV education) and control [standard of care (SOC)] arms. Retention in care was defined as 4-month visit constancy, that is, at least 1 primary care visit in each 4-month interval over a 12-month period. We used microcosting methods to collect unit costs and measure the quantity of resources used to implement the intervention in each clinic. All fixed and variable labor and nonlabor costs of the intervention were included. RESULTS: Visit constancy was achieved by 45.7% (280/613) of patients in the SOC arm and by 55.8% (343/615) of patients in the intervention arm, representing an increase of 63 patients (relative improvement 22.1%; 95% confidence interval: 9% to 36%; P < 0.01). The total annual cost of the intervention at the 6 clinics was $241,565, the average cost per patient was $393, and the estimated cost per additional patient retained in care beyond SOC was $3834. CONCLUSIONS: Our analyses showed that a retention in care intervention consisting of enhanced personal contact coupled with basic HIV education may be delivered at fairly low cost. These results provide useful information for guiding decisions about planning or scaling-up retention in care interventions for HIV-infected patients.

GB Virus C (GBV-C) Infection in Hepatitis C Virus (HCV) Seropositive Women with or at Risk for HIV Infection.

BACKGROUND: GB virus C (GBV-C) may have a beneficial impact on HIV disease progression; however, the epidemiologic characteristics of this virus are not well characterized. Behavioral factors and gender may lead to differential rates of GBV-C infection; yet, studies have rarely addressed GBV-C infections in women or racial/ethnic minorities. Therefore, we evaluated GBV-C RNA prevalence and genotype distribution in a large prospective study of high-risk women in the US. RESULTS: 438 hepatitis C virus (HCV) seropositive women, including 306 HIV-infected and 132 HIV-uninfected women, from the HIV Epidemiologic Research Study were evaluated for GBV-C RNA. 347 (79.2%) women were GBV-C RNA negative, while 91 (20.8%) were GBV-C RNA positive. GBV-C positive women were younger than GBV-C negative women. Among 306 HIV-infected women, 70 (22.9%) women were HIV/GBV-C co-infected. Among HIV-infected women, the only significant difference between GBV-negative and GBV-positive women was age (mean 38.4 vs. 35.1 years; p<0.001). Median baseline CD4 cell counts and plasma HIV RNA levels were similar. The GBV-C genotypes were 1 (n = 31; 44.3%), 2 (n = 36; 51.4%), and 3 (n = 3; 4.3%). The distribution of GBV-C genotypes in co-infected women differed significantly by race/ethnicity. However, median CD4 cell counts and log10 HIV RNA levels did not differ by GBV-C genotype. GBV-C incidence was 2.7% over a median follow-up of 2.9 (IQR: 1.5, 4.9) years, while GBV-C clearance was 35.7% over a median follow-up of 2.44 (1.4, 3.5) years. 4 women switched genotypes. CONCLUSIONS: Age, injection drug use, a history of sex for money or drugs, and number of recent male sex partners were associated with GBV-C infection among all women in this analysis. However, CD4 cell count and HIV viral load of HIV/HCV/GBV-C co-infected women were not different although race was associated with GBV-C genotype.

Enhanced personal contact with HIV patients improves retention in primary care: a randomized trial in 6 US HIV clinics.

BACKGROUND: The aim of the study was to determine whether enhanced personal contact with human immunodeficiency virus (HIV)-infected patients across time improves retention in care compared with existing standard of care (SOC) practices, and whether brief skills training improves retention beyond enhanced contact. METHODS: The study, conducted at 6 HIV clinics in the United States, included 1838 patients with a recent history of inconsistent clinic attendance, and new patients. Each clinic randomized participants to 1 of 3 arms and continued to provide SOC practices to all enrollees: enhanced contact with interventionist (EC) (brief face-to-face meeting upon returning for care visit, interim visit call, appointment reminder calls, missed visit call); EC + skills (organization, problem solving, and communication skills); or SOC only. The intervention was delivered by project staff for 12 months following randomization. The outcomes during that 12-month period were (1) percentage of participants attending at least 1 primary care visit in 3 consecutive 4-month intervals (visit constancy), and (2) proportion of kept/scheduled primary care visits (visit adherence). RESULTS: Log-binomial risk ratios comparing intervention arms against the SOC arm demonstrated better outcomes in both the EC and EC + skills arms (visit constancy: risk ratio [RR], 1.22 [95% confidence interval {CI}, 1.09-1.36] and 1.22 [95% CI, 1.09-1.36], respectively; visit adherence: RR, 1.08 [95% CI, 1.05-1.11] and 1.06 [95% CI, 1.02-1.09], respectively; all Ps < .01). Intervention effects were observed in numerous patient subgroups, although they were lower in patients reporting unmet needs or illicit drug use. CONCLUSIONS: Enhanced contact with patients improved retention in HIV primary care compared with existing SOC practices. A brief patient skill-building component did not improve retention further. Additional intervention elements may be needed for patients reporting illicit drug use or who have unmet needs. CLINICAL TRIALS REGISTRATION: CDCHRSA9272007.

Shifting the paradigm: using HIV surveillance data as a foundation for improving HIV care and preventing HIV infection.

CONTEXT: Reducing HIV incidence in the United States and improving health outcomes for people living with HIV hinge on improving access to highly effective treatment and overcoming barriers to continuous treatment. Using laboratory tests routinely reported for HIV surveillance to monitor individuals' receipt of HIV care and contacting them to facilitate optimal care could help achieve these objectives. Historically, surveillance-based public health intervention with individuals for HIV control has been controversial because of concerns that risks to privacy and autonomy could outweigh benefits. But with the availability of lifesaving, transmission-interrupting treatment for HIV infection, some health departments have begun surveillance-based outreach to facilitate HIV medical care. METHODS: Guided by ethics frameworks, we explored the ethical arguments for changing the uses of HIV surveillance data. To identify ethical, procedural, and strategic considerations, we reviewed the activities of health departments that are using HIV surveillance data to contact persons identified as needing assistance with initiating or returning to care. FINDINGS: Although privacy concerns surrounding the uses of HIV surveillance data still exist, there are ethical concerns associated with not using HIV surveillance to maximize the benefits from HIV medical care and treatment. Early efforts to use surveillance data to facilitate optimal HIV medical care illustrate how the ethical burdens may vary depending on the local context and the specifics of implementation. Health departments laid the foundation for these activities by engaging stakeholders to gain their trust in sharing sensitive information; establishing or strengthening legal, policy and governance infrastructure; and developing communication and follow-up protocols that protect privacy. CONCLUSIONS: We describe a shift toward using HIV surveillance to facilitate optimal HIV care. Health departments should review the considerations outlined before implementing new uses of HIV surveillance data, and they should commit to an ongoing review of activities with the objective of balancing beneficence, respect for persons, and justice.

The association of clinical follow-up intervals in HIV-infected persons with viral suppression on subsequent viral suppression.

The recommendation for the frequency for routine clinical monitoring of persons with well-controlled HIV infection is based on evidence that relies on observed rather than intended follow-up intervals. We sought to determine if the scheduled follow-up interval is associated with subsequent virologic failure. Participants in this 6-clinic retrospective cohort study had an index clinic visit in 2008 and HIV viral load (VL) ≤400 c/mL. Univariate and multivariate tests evaluated if scheduling the next follow-up appointment at 3, 4, or 6 months predicted VL >400 c/mL at 12 months (VF). Among 2171 participants, 66%, 26%, and 8% were scheduled next follow-up visits at 3, 4, and 6 months, respectively. With missing 12-month VL considered VF, 25%, 25%, and 24% of persons scheduled at 3, 4, and 6 months had VF, respectively (p=0.95). Excluding persons with missing 12-month VL, 7.1%, 5.7%, and 4.5% had VF, respectively (p=0.35). Multivariable models yielded nonsignificant odds of VF by scheduled follow-up interval both when missing 12-month VL were considered VF and when persons with missing 12-month VL were excluded. We conclude that clinicians are able to make safe decisions extending follow-up intervals in persons with viral suppression, at least in the short-term.

Measuring retention in HIV care: the elusive gold standard.

BACKGROUND: Measuring retention in HIV primary care is complex, as care includes multiple visits scheduled at varying intervals over time. We evaluated 6 commonly used retention measures in predicting viral load (VL) suppression and the correlation among measures. METHODS: Clinic-wide patient-level data from 6 academic HIV clinics were used for 12 months preceding implementation of the Centers for Disease Control and Prevention/Health Resources and Services Administration (CDC/HRSA) retention in care intervention. Six retention measures were calculated for each patient based on scheduled primary HIV provider visits: count and dichotomous missed visits, visit adherence, 6-month gap, 4-month visit constancy, and the HRSA HIV/AIDS Bureau (HRSA HAB) retention measure. Spearman correlation coefficients and separate unadjusted logistic regression models compared retention measures with one another and with 12-month VL suppression, respectively. The discriminatory capacity of each measure was assessed with the c-statistic. RESULTS: Among 10,053 patients, 8235 (82%) had 12-month VL measures, with 6304 (77%) achieving suppression (VL <400 copies/mL). All 6 retention measures were significantly associated (P < 0.0001) with VL suppression (odds ratio; 95% CI, c-statistic): missed visit count (0.73; 0.71 to 0.75, 0.67), missed visit dichotomous (3.2; 2.8 to 3.6, 0.62), visit adherence (3.9; 3.5 to 4.3,0.69), gap (3.0; 2.6 to 3.3, 0.61), visit constancy (2.8; 2.5 to 3.0, 0.63), and HRSA HAB (3.8; 3.3 to 4.4, 0.59). Measures incorporating "no-show" visits were highly correlated (Spearman coefficient = 0.83-0.85), as were measures based solely on kept visits (Spearman coefficient = 0.72-0.77). Correlation coefficients were lower across these 2 groups of measures (range = 0.16-0.57). CONCLUSIONS: Six retention measures displayed a wide range of correlation with one another, yet each measure had significant association and modest discrimination for VL suppression. These data suggest there is no clear gold standard and that selection of a retention measure may be tailored to context.