Faculty Bibliography

Physicians engage in risk stratification as a normative part of their professional duties. Risk stratification has the potential to be beneficial in many ways, and implicit recognition of this potential benefit underlies its acceptance as a cornerstone of the medical profession. However, risk stratification also has the potential to be harmful. We argue that 'profiling' is a term that corresponds to risk stratification strategies in which there is concern that ethical harms exceed likely or proven benefits. In the case of risk stratification for health goals, this would occur most frequently if benefits were obtained by threats to justice, autonomy or privacy. We discuss implications of the potential overlap between risk stratification and profiling for researchers and for clinicians, and we consider whether there are salient characteristics that make a particular risk stratification algorithm more or less likely to overlap with profiling, such as whether the risk stratification algorithm is based on voluntary versus non-voluntary characteristics, based on causal versus non-causal characteristics, or based on signifiers of historical disadvantage. We also discuss the ethical challenges created when a risk stratification scheme helps all subgroups but some more than others, or when risk stratification harms some subgroups but benefits the aggregate group.

BACKGROUND: . Despite the benefits of the placebo-controlled trial design, it is limited by its inability to quantify total benefits and harms. Such trials, for example, are not designed to detect an intervention's placebo or nocebo effects, which if detected could alter the benefit-to-harm balance and change a decision to adopt or reject an intervention. OBJECTIVE: . In this article, we explore scenarios in which alternative experimental trial designs, which differ in the type of control used, influence expected value across a range of pretest assumptions and study sample sizes. METHOD: . We developed a decision model to compare 3 trial designs and their implications for decision making: 2-arm placebo-controlled trial ("placebo-control"), 2-arm intervention v. do nothing trial ("null-control"), and an innovative 3-arm trial design: intervention v. do nothing v. placebo trial ("novel design"). Four scenarios were explored regarding particular attributes of a hypothetical intervention: 1) all benefits and no harm, 2) no biological effect, 3) only biological effects, and 4) surreptitious harm (no biological benefit or nocebo effect). RESULTS: . Scenario 1: When sample sizes were very small, the null-control was preferred, but as sample sizes increased, expected value of all 3 designs converged. Scenario 2: The null-control was preferred regardless of sample size when the ratio of placebo to nocebo effect was >1; otherwise, the placebo-control was preferred. Scenario 3: When sample size was very small, the placebo-control was preferred when benefits outweighed harms, but the novel design was preferred when harms outweighed benefits. Scenario 4: The placebo-control was preferred when harms outweighed placebo benefits; otherwise, preference went to the null-control. LIMITATIONS: . Scenarios are hypothetical, study designs have not been tested in a real-world setting, blinding is not possible in all designs, and some may argue the novel design poses ethical concerns. CONCLUSIONS: . We identified scenarios in which alternative experimental study designs would confer greater expected value than the placebo-controlled trial design. The likelihood and prevalence of such situations warrant further study.

We analyzed temporal patterns of alcohol misuse, smoking, and depression among veterans in care to determine whether these conditions vary concordantly or sequentially. Using the Veterans Aging Cohort Study, harmful alcohol use (AUDIT-C >/= 4), current smoking, and depression (PHQ-9 >/= 8), were measured. In regression analyses, predictors included each outcome condition at baseline, the other two conditions in the same survey, the other two conditions in the immediately preceding survey, number of years since enrollment, and HIV status. We found that current smoking and depression were more common among HIV infected individuals. Harmful alcohol use was more common among uninfected individuals. Temporal analyses suggested a concurrent pattern: each condition was associated with the other two conditions (p < 0.03, OR 1.12-1.66) as well as with the prior presence of the same condition (p < 0.0001; OR 6.38-22.02). Smoking was associated with prior depression after controlling for current depression (OR 1.16; p = 0.003). In conclusion, alcohol misuse, smoking, and depression were temporally concordant and persistent, raising the question of whether they constitute a common syndrome in HIV infected patients and others with chronic diseases.

OBJECTIVES/OBJECTIVE:To improve individual health quality measures, which are associated with varying degrees of health benefit, and composite quality metrics, which weight individual measures identically. STUDY DESIGN/METHODS:We developed a health-weighted composite quality measure reflecting the total health benefit conferred by a health plan annually, using preventive care as a test case. METHODS:Using national disease prevalence, we simulated a hypothetical insurance panel of individuals aged 25 to 84 years. For each individual, we estimated the gain in life expectancy associated with 1 year of health system exposure to encourage adherence to major preventive care guidelines, controlling for patient characteristics (age, race, gender, comorbidity) and variation in individual adherence rates. This personalized gain in life expectancy was used to proxy for the amount of health benefit conferred by a health plan annually to its members, and formed weights in our health-weighted composite quality measure. We aggregated health benefits across the health insurance membership panel to analyze total health system performance. RESULTS:Our composite quality metric gave the highest weights to health plans that succeeded in implementing tobacco cessation and weight loss. One year of compliance with these goals was associated with 2 to 10 times as much health benefit as compliance with easier-to-follow preventive care services, such as mammography, aspirin, and antihypertensives. For example, for women aged 55 to 64 years, successful interventions to encourage weight loss were associated with 2.1 times the health benefit of blood pressure reduction and 3.9 times the health benefit of increasing adherence with screening mammography. CONCLUSIONS:A single health-weighted quality metric may inform measurement of total health system performance.

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.

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.