Faculty Bibliography

There are inefficiencies in current approaches to monitoring patients on antiretroviral therapy in sub-Saharan Africa. Patients typically attend clinics every 1 to 3 months for clinical assessment. The clinic costs are comparable with the costs of the drugs themselves and CD4 counts are measured every 6 months, but patients are rarely switched to second-line therapies. To ensure sustainability of treatment programmes, a transition to more cost-effective delivery of antiretroviral therapy is needed. In contrast to the CD4 count, measurement of the level of HIV RNA in plasma (the viral load) provides a direct measure of the current treatment effect. Viral-load-informed differentiated care is a means of tailoring care so that those with suppressed viral load visit the clinic less frequently and attention is focussed on those with unsuppressed viral load to promote adherence and timely switching to a second-line regimen. The most feasible approach to measuring viral load in many countries is to collect dried blood spot samples for testing in regional laboratories; however, there have been concerns over the sensitivity and specificity of this approach to define treatment failure and the delay in returning results to the clinic. We use modelling to synthesize evidence and evaluate the cost-effectiveness of viral-load-informed differentiated care, accounting for limitations of dried blood sample testing. We find that viral-load-informed differentiated care using dried blood sample testing is cost-effective and is a recommended strategy for patient monitoring, although further empirical evidence as the approach is rolled out would be of value. We also explore the potential benefits of point-of-care viral load tests that may become available in the future.This article has not been written or reviewed by Nature editors. Nature accepts no responsibility for the accuracy of the information provided.

OBJECTIVES: Attrition from care among HIV infected patients can lead to poor clinical outcomes. Our objective was to evaluate hypothetical interventions seeking to improve retention-in-care (RIC) for HIV-infected patients in East Africa, asking whether they could offer favorable value compared to earlier ART initiation. METHODS: We used a micro-simulation model to analyze two RIC focused strategies within an East African HIV treatment program--"risk reduction," defined as intervention(s) that decrease the risk of attrition from care; and "outreach," defined as interventions that find patients and relink them with care. We compared this to earlier ART treatment as a measure of the potential health benefits forgone (e.g., opportunity cost). RESULTS: Reducing attrition by 40% at an average cost of $10 per person remains a less efficient use of resources compared to ensuring full access to ART (cost- effectiveness ratio $1300 vs $3700) for ART eligible patients. An outreach intervention had limited clinical benefit in our simulation. If intervention costs are <$10 per person, however, an intervention able to achieve a 40% (or greater) reduction in attrition may be a cost-effective next implementation option following implementation of earlier ART treatment. CONCLUSIONS: Our results suggest that programs should consider retention focused programs once they have already achieved high degrees of ART coverage among eligible patients. It is important that decision makers understand the epidemiology and associated outcomes of those patients who are classified as lost to follow up in their systems prior to implementation in order to achieve the highest value.

BACKGROUND: The effects of antiretroviral treatment on the HIV epidemic are complex. HIV-infected individuals survive longer with treatment, but are less likely to transmit the disease. The standard coverage measure improves with the deaths of untreated individuals and does not consider the fact that some individuals may acquire the disease and die before receiving treatment, making it susceptible to overestimating the long-run performance of antiretroviral treatment programs. OBJECTIVE: The objective was to propose an alternative coverage definition to better measure the long-run performance of HIV treatment programs. METHODS: We introduced cumulative incidence-based coverage as an alternative to measure an HIV treatment program's success. To numerically compare the definitions, we extended a simulation model of HIV disease and treatment to represent a dynamic population that includes uninfected and HIV-infected individuals. Also, we estimated the additional resources required to implement various treatment policies in a resource-limited setting. RESULTS: In a synthetic population of 600,000 people of which 44,000 (7.6%) are infected, and eligible for treatment with a CD4 count of less than 500 cells/mm(3), assuming a World Health Organization (WHO)-defined coverage rate of 50% of eligible people, and treating these individuals with a single treatment regimen, the gap between the current WHO coverage definition and our proposed one is as much as 16% over a 10-year planning horizon. CONCLUSIONS: Cumulative incidence-based definition of coverage yields a more accurate representation of the long-run treatment success and along with the WHO and other definitions of coverage provides a better understanding of the HIV treatment progress.

BACKGROUND: Hospital care on weekends has been associated with delays in care, reduced quality, and poor clinical outcomes. OBJECTIVE: The purpose of this study was to evaluate the impact of a weekend hospital intervention on processes of care and clinical outcomes. The multifaceted intervention included expanded weekend diagnostic services, improved weekend discharge processes, and increased physician and care management services on weekends. DESIGN AND PATIENTS: This was an interrupted time series observational study of adult non-obstetric patients hospitalized at a single academic medical center between January 2011 and January 2014. The study included 18 months prior to and 19 months following the implementation of the intervention. Data were analyzed using segmented regression analysis with adjustment for confounders. MAIN MEASURES: The primary outcome was average length of stay. Secondary outcomes included percent of patients discharged on weekends, 30-day readmission rate, and in-hospital mortality rate. KEY RESULTS: The study included 57,163 hospitalizations. Following implementation of the intervention, average length of stay decreased by 13 % (95 % CI 10-15 %) and continued to decrease by 1 % (95 % CI 1-2 %) per month as compared to the underlying time trend. The proportion of weekend discharges increased by 12 % (95 % CI 2-22 %) at the time of the intervention and continued to increase by 2 % (95 % CI 1-3 %) per month thereafter. The intervention had no impact on readmissions or mortality. During the post-implementation period, the hospital was evacuated and closed for 2 months due to damage from Hurricane Sandy, and a new hospital-wide electronic health record was introduced. The contributions of these events to our findings are not known. We observed a lower inpatient census and found differences in patient characteristics, including higher rates of Medicaid insurance and comorbidities, in the post-Hurricane Sandy period as compared to the pre-Sandy period. CONCLUSIONS: The intervention was associated with a reduction in length of stay and an increase in weekend discharges. Our longitudinal study also illuminated the challenges of evaluating the effectiveness of a large-scale intervention in a real-world hospital setting.

BACKGROUND: In the current report, we ask if targeting a cognitive behavioral therapy (CBT)-based intervention aimed at reducing hazardous alcohol consumption to HIV-infected persons in East Africa would have a favorable value at costs that are feasible for scale-up. METHODS: Using a computer simulation to inform HIV prevention decisions in East Africa, we compared 4 different strategies for targeting a CBT intervention-(i) all HIV-infected persons attending clinic; (ii) only those patients in the pre-antiretroviral therapy (ART) stages of care; (iii) only those patients receiving ART; and (iv) only those patients with detectable viral loads (VLs) regardless of disease stage. We define targeting as screening for hazardous alcohol consumption (e.g., using the Alcohol Use Disorders Identification Test and offering the CBT intervention to those who screen positive). We compared these targeting strategies to a null strategy (no intervention) or a hypothetical scenario where an alcohol intervention was delivered to all adults regardless of HIV status. RESULTS: An intervention targeted to HIV-infected patients could prevent 18,000 new infections, add 46,000 quality-adjusted life years (QALYs), and yield an incremental cost-effectiveness ratio of $600/QALY compared to the null scenario. Narrowing the prioritized population to only HIV-infected patients in pre-ART phases of care results in 15,000 infections averted, the addition of 21,000 QALYs and would be cost-saving, while prioritizing based on an unsuppressed HIV-1 VL test results in 8,300 new infections averted, adds 6,000 additional QALYs, and would be cost-saving as well. CONCLUSIONS: Our results suggest that targeting a cognitive-based treatment aimed at reducing hazardous alcohol consumption to subgroups of HIV-infected patients provides favorable value in comparison with other beneficial strategies for HIV prevention and control in this region. It may even be cost-saving under certain circumstances.

OBJECTIVES: We sought to improve public health surveillance by using a geographic analysis of emergency department (ED) visits to determine local chronic disease prevalence. METHODS: Using an all-payer administrative database, we determined the proportion of unique ED patients with diabetes, hypertension, or asthma. We compared these rates to those determined by the New York City Community Health Survey. For diabetes prevalence, we also analyzed the fidelity of longitudinal estimates using logistic regression and determined disease burden within census tracts using geocoded addresses. RESULTS: We identified 4.4 million unique New York City adults visiting an ED between 2009 and 2012. When we compared our emergency sample to survey data, rates of neighborhood diabetes, hypertension, and asthma prevalence were similar (correlation coefficient = 0.86, 0.88, and 0.77, respectively). In addition, our method demonstrated less year-to-year scatter and identified significant variation of disease burden within neighborhoods among census tracts. CONCLUSIONS: Our method for determining chronic disease prevalence correlates with a validated health survey and may have higher reliability over time and greater granularity at a local level. Our findings can improve public health surveillance by identifying local variation of disease prevalence. (Am J Public Health. Published online ahead of print July 16, 2015: e1-e8. doi:10.2105/AJPH.2015.302679).