The Impacts of the COVID-19 Pandemic on the Medical Expenditure Panel Survey.

The COVID-19 pandemic caused substantial disruptions in the field operations of all 3 major components of the Medical Expenditure Panel Survey (MEPS). The MEPS is widely used to study how policy changes and major shocks, such as the COVID-19 pandemic, affect insurance coverage, access, and preventive and other health care utilization and how these relate to population health. We describe how the MEPS program successfully responded to these challenges by reengineering field operations, including survey modes, to complete data collection and maintain data release schedules. The impact of the pandemic on response rates varied considerably across the MEPS. Investigations to date show little effect on the quality of data collected. However, lower response rates may reduce the statistical precision of some estimates. We also describe several enhancements made to the MEPS that will allow researchers to better understand the impact of the pandemic on US residents, employers, and the US health care system. (Am J Public Health. 2021;111(12):2157-2166. https://doi.org/10.2105/AJPH.2021.306534).

Use of prescriber requirements among US commercial health plans.

BACKGROUND: Prescriber requirements are a form of utilization management (UM) in which health plans require that a certain type of physician (eg, a rheumatologist) prescribe a drug. OBJECTIVE: To examine how a set of US commercial health plans impose prescriber requirements in their specialty drug coverage decisions. METHODS: We identified specialty drug coverage decisions from the Tufts Medical Center Specialty Drug Evidence and Coverage (SPEC) Database. SPEC includes coverage information issued by 17 large US commercial health plans. We categorized prescriber requirements as the following: (1) the drug must be prescribed in consultation, supervision, or coordination with a specialist; (2) the drug must be prescribed by a specialist (eg, a neurologist); or (3) the drug must be prescribed by a specialist with particular expertise (eg, a neurologist with expertise in spinal muscular atrophy). First, we examined how often each plan imposed prescriber requirements. Second, we determined the degree of specialization that plans required prescribing physicians to have. Third, we used Pearson's chi-square tests to examine the association between plans' use of prescriber requirements and the following drug characteristics: cancer treatment, orphan indication, pediatric indication, drug approved in the last year, black box warning, and self-administered formulation. RESULTS: Overall, health plans imposed prescriber requirements in 22.0% (1,844/8,383) of their coverage decisions, although the frequency that they did so varied (range: 0.8%-86.0%). Of prescriber requirements, 79.1% (1,459/1,844) required that the drug be prescribed in consultation, supervision, or coordination with a specialist; 18.3% (338/1,844) required that the drug be prescribed by a specialist; and 2.6% (47/1,844) required that the drug be prescribed by a specialist with particular expertise. Plans were more likely to impose prescriber requirements for drugs with the following characteristics: indicated for a pediatric population, black box warning, self-administered, and noncancer treatments (all P < 0.001). CONCLUSIONS: Health plans varied in the frequency that they imposed prescriber requirements in their specialty drug coverage decisions and with respect to the degree of specialization they required prescribing physicians to have. DISCLOSURES: This study was funded by the Center for the Evaluation of Value and Risk in Health at Tufts Medical Center. The center receives funding from a variety of sources, including government agencies, foundations, and pharmaceutical and device companies. The SPEC Database, which provided data for this study, is funded in part through a data subscription program to which a number of pharmaceutical companies subscribe. All authors are employed by the Center for the Evaluation of Value and Risk in Health. In addition, Chambers reports speaker fees from Astellas and consulting fees from Biogen and Lundbeck. The other authors have nothing to disclose. An earlier version of this study was presented as a poster at the AMCP 2021 Virtual Meeting, April 12-16, 2021.

Prospective validation of the Kaiser Permanente prostate cancer risk calculator in a contemporary, racially diverse, referral population.

PURPOSE: To prospectively validate a new prostate cancer risk calculator in a racially diverse population. MATERIALS AND METHODS: We recently developed, internally validated and published the Kaiser Permanente Prostate Cancer Risk Calculator. This study is a prospective validation of the calculator in a separate, referral population over a 21-month period. All patients were tested with a uniform PSA assay and a standardized systematic, ultrasound-guided biopsy scheme. We report on 3 calculator models: Model 1 included age, race, PSA, prior biopsy status, body mass index, and family history of prostate cancer; Model 2 added digital rectal exam to Model 1 variables; Model 3 added prostate volume to Model 2 variables. We considered three outcomes: high-grade disease (Gleason score ≥7), low-grade disease (Gleason score=6), and no cancer. Predictive discrimination and calibration were calculated. How each model might alter biopsy frequency and outcomes at various thresholds of risk was assessed. We compared the performance of our calculator with two other calculators. RESULTS: In 4178 patients (16.2% Asian, 11.3% African American, 13.5% Hispanic), cancer was found in 53%; 62% were Gleason score ≥7. Using a high-grade risk threshold for biopsy of ≥10%, Model 2 predictions would result in 9% of men avoiding a biopsy, while only missing 2% of high-grade cancers. At the same threshold, Model 3 predictions would result in 26% of men avoiding a biopsy, while only missing 5% of high-grade cancers. The c-statistics for Models 1, 2, and 3 to predict high-grade disease vs. low-grade or no cancer were 0.76, 0.79 and 0.85, respectively. The c-statistics for Models 1, 2, and 3 to predict any prostate cancer vs. no cancer were 0.70, 0.72 and 0.80, respectively. All models were well calibrated for all outcomes. Our Model 3 calculator had superior discrimination for high grade disease (c-statistic=0.85, 0.84-0.86) and any cancer (0.80, 0.79-0.82) compared to the PBCG calculator [(0.79, 0.78-0.80); 0.72 (0.70-0.73)] and the PCPT calculator [(0.75, 0.74-0.77); 0.69 (0.67-0.70)], respectively. In the high-grade cancer predicted risk range of 0-30%, our Model 2 was better calibrated than the PCPT and PBCG calculators. CONCLUSIONS: This validation of our calculator showed excellent performance characteristics.

Regulation of provider networks in response to COVID-19.

In public health insurance programs, federal and state regulators use network adequacy standards to ensure that health plans provide enrollees with adequate access to care. These standards are based on provider availability, anticipated enrollment, and patterns of care delivery. We anticipate that the coronavirus disease 2019 pandemic will have 3 main effects on provider networks and their regulation: enrollment changes, changes to the provider landscape, and changes to care delivery. Regulators will need to ensure that plans adjust their network size should there be increased enrollment or increased utilization caused by forgone care. Regulators will also require updated monitoring data and plan network data that reflect postpandemic provider availability. Telehealth will have a larger role in care delivery than in the prepandemic period, and regulators will need to adapt network standards to accommodate in-person and virtual care delivery.

Double-edged sword of federalism: variation in essential health benefits for mental health and substance use disorder coverage in states.

The Affordable Care Act requires all insurance plans sold on health insurance marketplaces and individual and small-group plans to cover 10 Essential Health Benefits (EHB), including behavioral health services. Instead of applying a uniform EHB plan design, the Department of Health and Human Services let states define their own EHB plan. This approach was seen as the best balance between flexibility and comprehensiveness, and assumed there would be little state-to-state variation. Limited federal oversight runs the risk of variation in EHB coverage definitions and requirements, as well as potential divergence from standardized medical guidelines. We analyzed 112 EHB documents from all states for behavioral health coverage in effect from 2012 to 2017. We find wide variation among states in their EHB plan required-coverage, and divergence between medical-practice guidelines and EHB plans. These results emphasize consideration of federated regulation over health insurance coverage standards. Federal flexibility in states benefit design nods to state-specific policymaking-processes and population needs. However, flexibility becomes problematic if it leads to inadequate coverage that reduces access to critical health care services. The EHBs demonstrate an incomplete effort to establish appropriate minimum standards of coverage for behavioral health services.

Partitioned Survival and State Transition Models for Healthcare Decision Making in Oncology: Where Are We Now?

OBJECTIVES: Partitioned survival models (PSMs) are routinely used to inform reimbursement decisions for oncology drugs. We discuss the appropriateness of PSMs compared to the most common alternative, state transition models (STMs). METHODS: In 2017, we published a National Institute for Health and Care Excellence (NICE) Technical Support Document (TSD 19) describing and critically reviewing PSMs. This article summarizes findings from TSD 19, reviews new evidence comparing PSMs and STMs, and reviews recent NICE appraisals to understand current practice. RESULTS: PSMs evaluate state membership differently from STMs and do not include a structural link between intermediate clinical endpoints (eg, disease progression) and survival. PSMs directly consider clinical trial endpoints and can be developed without access to individual patient data, but limit the scope for sensitivity analyses to explore clinical uncertainties in the extrapolation period. STMs facilitate these sensitivity analyses but require development of robust survival models for individual health-state transitions. Recent work has shown PSMs and STMs can produce substantively different survival extrapolations and that extrapolations from STMs are heavily influenced by specification of the underlying survival models. Recent NICE appraisals have not generally included both model types, reviewed individual clinical event data, or scrutinized life-years accrued in individual health states. CONCLUSIONS: The credibility of survival predictions from PSMs and STMs, including life-years accrued in individual health states, should be assessed using trial data on individual clinical events, external data, and expert opinion. STMs should be used alongside PSMs to support assessment of clinical uncertainties in the extrapolation period, such as uncertainty in post-progression survival.

A mixed-method comparison of physician-reported beliefs about and barriers to treatment with medications for opioid use disorder.

BACKGROUND: Evidence demonstrates that medications for treating opioid use disorder (MOUD) -namely buprenorphine, methadone, and extended-release naltrexone-are effective at treating opioid use disorder (OUD) and reducing associated harms. However, MOUDs are heavily underutilized, largely due to the under-supply of providers trained and willing to prescribe the medications. METHODS: To understand comparative beliefs about MOUD and barriers to MOUD, we conducted a mixed-methods study that involved focus group interviews and an online survey disseminated to a random group of licensed U.S. physicians, which oversampled physicians with a preexisting waiver to prescribe buprenorphine. Focus group results were analyzed using thematic analysis. Survey results were analyzed using descriptive and inferential statistical methods. RESULTS: Study findings suggest that physicians have higher perceptions of efficacy for methadone and buprenorphine than for extended-release naltrexone, including for patients with co-occurring mental health disorders. Insurance obstacles, such as prior authorization requirements, were the most commonly cited barrier to prescribing buprenorphine and extended-release naltrexone. Regulatory barriers, such as the training required to obtain a federal waiver to prescribe buprenorphine, were not considered significant barriers by many physicians to prescribing buprenorphine and naltrexone in office-based settings. Nor did physicians perceive diversion to be a prominent barrier to prescribing buprenorphine. In focus groups, physicians identified financial, logistical, and workforce barriers-such as a lack of addiction treatment specialists-as additional barriers to prescribing medications to treat OUD. CONCLUSIONS: Additional education is needed for physicians regarding the comparative efficacy of different OUD medications. Governmental policies should mandate full insurance coverage of and prohibit prior authorization requirements for OUD medications.

Public insurance expansions and mental health care availability.

OBJECTIVE: To provide new evidence on the effects of large-scale public health insurance expansions, associated with the Affordable Care Act (ACA), on the availability of specialty mental health care treatment in the United States. We measure availability with the probability that a provider accepts Medicaid. DATA SOURCE/STUDY SETTING: The National Mental Health Services Survey (N-MHSS) 2010-2018. STUDY DESIGN: A quasi-experimental differences-in-differences design using observational data. DATA COLLECTION: The N-MHSS provides administrative data on the universe of specialty mental health care providers in the United States. Response rates are above 90 percent in all years. Data cover 85 019 provider/year observations. PRINCIPAL FINDINGS: ACA-Medicaid expansion increases the probability that a provider accepts Medicaid by 1.69 percentage points, 95 percent confidence interval: [0.0017,0.0321], which corresponds to an increase from 87.27 percent pre-expansion to 90.27 percent postexpansion in expansion states or a 1.94 percent increase. We observe spillovers to Medicare, although this finding is sensitive to specification. CONCLUSIONS: This study provides evidence on the impact of ACA-Medicaid expansion on accepted forms of payment for specialty mental health care treatment. Findings suggest that expansion increases availability of providers who deliver valuable care for enrollees with severe mental illness. These findings may help policy makers reflecting on the future directions of the US health care delivery system.

Son preference, security concerns and crime against women: Expanding the public health discourse in India.

The phenomenon of son preference in India and the declining number of girls due to such a mindset has been an area of concern. While the Preconception and Prenatal Diagnostic Techniques Act and the Beti Bachao and Beti Padhao scheme have been the mainstay of the government's initiative to counter this reproductive injustice, recognizing son preference and crime against women as public health concern opens up a new vista to counter this injustice. This study has identified that the public health system needs to engage with the following aspects to counter the problem: counseling services to women and men around fertility choices; access/availability to contraceptive choices; engaging men and boys in developing a response against violence; gender-sensitive training and capacity building; access to sexual and reproductive rights awareness amongst girls, women, boys, and men; and health insurance for senior citizens.

Going the Extra Mile? How Provider Network Design Increases Consumer Travel Distance, Particularly for Rural Consumers.

CONTEXT: The practical accessibility to medical care facilitated by health insurance plans depends not just on the number of providers within their networks but also on distances consumers must travel to reach the providers. Long travel distances inconvenience almost all consumers and may substantially reduce choice and access to providers for some. METHODS: The authors assess mean and median travel distances to cardiac surgeons and pediatricians for participants in (1) plans offered through Covered California, (2) comparable commercial plans, and (3) unrestricted open-network plans. The authors repeat the analysis for higher-quality providers. FINDINGS: The authors find that in all areas, but especially in rural areas, Covered California plan subscribers must travel longer than subscribers in the comparable commercial plan; subscribers to either plan must travel substantially longer than consumers in open networks. Analysis of access to higher-quality providers show somewhat larger travel distances. Differences between ACA and commercial plans are generally substantively small. CONCLUSIONS: While network design adds travel distance for all consumers, this may be particularly challenging for transportation-disadvantaged populations. As distance is relevant to both health outcomes and the cost of obtaining care, this analysis provides the basis for more appropriate measures of network adequacy than those currently in use.

The Changing Health Insurance Coverage Landscape in the United States.

Changes in the health insurance coverage landscape in the United States during the past decade have important implications for receipt and affordability of cancer care. In this paper, we summarize evidence for the association between health insurance coverage and cancer prevention and treatment. We then discuss ongoing changes in health care coverage, including implementation of provisions of the Affordable Care Act, increasing prevalence of high-deductible health insurance plans, and factors that affect health care delivery, with a focus on vertical integration of hospitals and providers. We summarize the evidence for the effects of the changes in health coverage on care and discuss areas for future research with the goal of informing efforts to improve cancer care delivery and outcomes in the United States.

The Affordable Care Act's Medicaid Expansion and Impact Along the Cancer-Care Continuum: A Systematic Review.

BACKGROUND: Health reform and the merits of Medicaid expansion remain at the top of the legislative agenda, with growing evidence suggesting an impact on cancer care and outcomes. A systematic review was undertaken to assess the association between Medicaid expansion and the goals of the Patient Protection and Affordable Care Act in the context of cancer care. The purpose of this article is to summarize the currently published literature and to determine the effects of Medicaid expansion on outcomes during points along the cancer care continuum. METHODS: A systematic search for relevant studies was performed in the PubMed/MEDLINE, EMBASE, Scopus, and Cochrane databases. Three independent observers used an abstraction form to code outcomes and perform a quality and risk of bias assessment using predefined criteria. RESULTS: A total of 48 studies were identified. The most common outcomes assessed were the impact of Medicaid expansion on insurance coverage (23.4% of studies), followed by evaluation of racial and/or socioeconomic disparities (17.4%) and access to screening (14.5%). Medicaid expansion was associated with increases in coverage for cancer patients and survivors as well as reduced racial- and income-related disparities. CONCLUSIONS: Medicaid expansion has led to improved access to insurance coverage among cancer patients and survivors, particularly among low-income and minority populations. This review highlights important gaps in the existing oncology literature, including a lack of studies evaluating changes in treatment and access to end-of-life care following implementation of expansion.

Increasing health service access by expanding disease coverage and adding patient navigation: challenges for patient satisfaction.

BACKGROUND: Cancer control programs have added patient navigation to improve effectiveness in underserved populations, but research has yielded mixed results about their impact on patient satisfaction. This study focuses on three related research questions in a U.S. state cancer screening program before and after a redesign that added patient navigators and services for chronic illness: Did patient diversity increase; Did satisfaction levels improve; Did socioeconomic characteristics or perceived barriers explain improved satisfaction. METHODS: Representative statewide patient samples were surveyed by phone both before and after the program design. Measures included satisfaction with overall health care and specific services, as well as experience of eleven barriers to accessing health care and self-reported health and sociodemographic characteristics. Multiple regression analysis is used to identify independent effects. RESULTS: After the program redesign, the percentage of Hispanic and African American patients increased by more than 200% and satisfaction with overall health care quality rose significantly, but satisfaction with the program and with primary program staff declined. Sociodemographic characteristics explained the apparent program effects on overall satisfaction, but perceived barriers did not. Further analysis indicates that patients being seen for cancer risk were more satisfied if they had a patient navigator. CONCLUSIONS: Health care access can be improved and patient diversity increased in public health programs by adding patient navigators and delivering more holistic care. Effects on patient satisfaction vary with patient health needs, with those being seen for chronic illness likely to be less satisfied with their health care than those being seen for cancer risk. It is important to use appropriate comparison groups when evaluating the effect of program changes on patient satisfaction and to consider establishing appropriate satisfaction benchmarks for patients being seen for chronic illness.

The Secretary Shall . . . : Implementing the Affordable Care Act's Private Insurance Expansions.

The federal bureaucracy played a critical role in implementing most aspects of the Affordable Care Act's private insurance coverage expansion. Through brief case studies, the authors review three dimensions of this role: the development of the Center for Consumer Information and Insurance Oversight, rulemaking in the formulation of the essential health benefits package, and the implementation of the federal website. They relate these to themes in the public administration literature. Politics-both through state decisions and through continuing congressional action (and inaction)-pervaded the implementation process. The challenges of staffing and situating the new bureaucracy effectively changed vertical boundaries within the Department of Health and Human Services, with long-lasting consequences. Finally, the complex design of the policy itself made passage of the legislation easier but implementation much more difficult. Ultimately, however, implementation was remarkably successful, achieving improvements in coverage consistent with the Congressional Budget Office's projections.

Have the ACA's Exchanges Succeeded? It's Complicated.

The fight over health insurance exchanges epitomizes the rapid evolution of health reform politics in the decade since the passage of the Affordable Care Act (ACA). The ACA's drafters did not expect the exchanges to be contentious because they would expand private insurance coverage to low- and middle-income individuals who were increasingly unable to obtain employer-sponsored health insurance. Instead, exchanges became one of the primary fronts in the war over Obamacare. Have the exchanges been successful? The answer is not straightforward and requires a historical perspective through a federalism lens. What the ACA has accomplished has depended largely on whether states were invested in or resistant to implementation, as well as individual decisions by state leaders working with federal officials. Our account demonstrates that the states that have engaged with the ACA most consistently appear to have experienced greater exchange-related success. But each aspect of states' engagement with or resistance to the ACA must be counted to fully paint this picture, with significant variation among states. This variation should give pause to those considering next steps in health reform, because state variation can mean innovation and improvement but also lack of coverage, disparities, and diminished access to care.

Advanced Medical Care Program for the Rapid Introduction of Healthcare Technologies to the National Health Insurance System in Japan.

Japan's Advanced Medical Care Program (AMCP) seeks to facilitate patient access to promising healthcare technologies through National Health Insurance (NHI) coverage. This study aimed to examine AMCP's contribution to the accelerated introduction of new technologies through NHI coverage. AMCP-type B technologies registered May 2006-March 2019 were examined. To investigate the use of AMCP for NHI coverage, data from the AMCP website and from regulatory authority documents were used. Of 127 AMCP-type B technologies, 38 underwent final review. Fifteen technologies were successfully introduced into NHI coverage. Eight technologies introduced directly through the Advanced Medical Care Conference were related to medical devices. Other technologies, including drugs, required additional accelerated frameworks for market approval. A strategic approach with the careful selection of target therapeutic technologies and accelerated frameworks is key for the rapid introduction of medical technologies through AMCP.

Tailored HIV programmes and universal health coverage.

Improvements in geospatial health data and tailored human immunodeficiency virus (HIV) testing, prevention and treatment have led to greater microtargeting of the HIV response, based on location, risk, clinical status and disease burden. These approaches show promise for achieving control of the HIV epidemic. At the same time, United Nations Member States have committed to achieving broader health and development goals by 2030, including universal health coverage (UHC). HIV epidemic control will facilitate UHC by averting the need to commit ever-increasing resources to HIV services. Yet an overly targeted HIV response could also distort health systems, impede integration and potentially threaten broader health goals. We discuss current approaches to achieving both UHC and HIV epidemic control, noting potential areas of friction between disease-specific microtargeting and integrated health systems, and highlighting opportunities for convergence that could enhance both initiatives. Examples of these programmatic elements that could be better aligned include: improved information systems with unique identifiers to track and monitor individuals across health services and the life course; strengthened subnational data use; more accountable supply chains that supply a broad range of services; and strengthened community-based services and workforces. We argue that the response both to HIV and to broader health threats should use these areas of convergence to increase health systems efficiency and mitigate the harm of any potential decrease in health funding. Further investments in implementation and monitoring of these programme elements will be needed to make progress towards both UHC and HIV epidemic control.

Les améliorations des données sanitaires géospatiales et la personnalisation du dépistage, de la prévention et du traitement du virus de l'immunodéficience humaine (VIH) ont permis de développer le micro-ciblage de la réponse au VIH, en fonction du lieu, du risque, de la situation clinique et de la charge de morbidité. Ces approches sont prometteuses pour lutter contre l'épidémie de VIH. Dans le même temps, les États membres des Nations Unies se sont engagés à atteindre des objectifs plus larges de santé et de développement d'ici 2030, notamment la couverture sanitaire universelle. Cette dernière sera facilitée par la lutte contre l'épidémie de VIH, qui réduira la nécessité de consacrer toujours plus de ressources aux services liés au VIH. Cependant, une réponse au VIH trop ciblée pourrait également distordre les systèmes de santé, empêcher leur intégration et potentiellement nuire aux objectifs de santé plus vastes. Nous abordons ici les approches actuelles en matière de couverture sanitaire universelle et de lutte contre l'épidémie de VIH, en notant les points de friction potentiels entre un micro-ciblage spécifique à certaines maladies et des systèmes de santé intégrés, ainsi que les opportunités de convergence qui pourraient être bénéfiques aux deux initiatives. Parmi les éléments de programmes qui pourraient être mieux coordonnés, nous pouvons citer: l'amélioration des systèmes d'information avec des identifiants uniques permettant de suivre les personnes dans leur parcours de soins et tout au long de leur vie; la plus grande utilisation des données infranationales; la responsabilisation des chaînes d'approvisionnement qui fournissent un grand nombre de services; et le renforcement des services et des intervenants communautaires. Nous soutenons que la réponse au VIH et à d'autres menaces sanitaires devrait exploiter ces domaines de convergence pour accroître l'efficacité des systèmes de santé et atténuer le préjudice d'une éventuelle baisse des fonds alloués à la santé. Il sera nécessaire d'investir davantage dans la mise en œuvre et le suivi de ces éléments de programmes pour avancer, aussi bien vers la couverture sanitaire universelle que dans la lutte contre l'épidémie de VIH.

Las mejoras en los datos geoespaciales de salud y las pruebas, la prevención y el tratamiento adaptados al virus de la inmunodeficiencia humana (VIH) han conducido a una mayor focalización de la respuesta al VIH, basada en la ubicación, el riesgo, el estado clínico y la carga de la enfermedad. Estos enfoques son prometedores para lograr el control de la epidemia del VIH. Al mismo tiempo, los Estados Miembros de las Naciones Unidas se han comprometido a alcanzar objetivos de salud y desarrollo de mayor alcance para 2030, incluida la cobertura universal de salud (universal health coverage, UHC). El control de la epidemia del VIH facilitará la UHC porque evitará la necesidad de comprometer recursos cada vez mayores para los servicios del VIH. Sin embargo, una respuesta al VIH demasiado específica también podría distorsionar los sistemas de salud, impedir la integración y amenazar potencialmente los objetivos de salud de mayor alcance. Se discuten los enfoques actuales para lograr tanto la atención primaria de salud como el control de la epidemia del VIH, se señalan las posibles áreas de fricción entre la focalización específica de la enfermedad y los sistemas integrados de salud, y se destacan las oportunidades de convergencia que podrían mejorar ambas iniciativas. Entre los ejemplos de estos elementos programáticos que podrían alinearse mejor se incluyen: sistemas de información mejorados con identificadores únicos para hacer un seguimiento y monitoreo de las personas a través de los servicios de salud y el curso de la vida; el fortalecimiento del uso de datos a nivel subnacional; cadenas de suministro más responsables que proveen una amplia gama de servicios; y el fortalecimiento de los servicios en la comunidad y las fuerzas de trabajo. Se argumenta que la respuesta tanto al VIH como a las amenazas para la salud en general debe utilizar estas áreas de convergencia para aumentar la eficiencia de los sistemas de salud y mitigar el daño de cualquier posible disminución en la financiación de la salud. Se necesitarán más inversiones en la ejecución y el monitoreo de estos elementos del programa para avanzar tanto en el control de la epidemia de VIH como en la UHC.

Squaring the cube: Towards an operational model of optimal universal health coverage.

Universal Health Coverage (UHC) has become a key goal of health policy in many developing countries. However, implementing UHC poses tough policy choices about: what treatments to provide (the depth of coverage); to what proportion of the population (the breadth of coverage); at what price to patients (the height of coverage). This paper uses a theoretical mathematical programming model to derive analytically the optimal balance between the range of services provided and the proportion of the population covered under UHC, using the general principles of cost-effectiveness analysis. In contrast to most CEA, the model allows for variations in both the costs of provision and the social benefits of treatments, depending on the deprivation level of the population. We illustrate empirically the optimal trade-off between the size of the benefits package and the proportion of the population securing access to each treatment for a hypothetical East African country, based on WHO data on the costs and benefits of treatments at different coverage levels. We begin with a scenario allowing coverage levels to vary, then apply differential equity weights to the benefits of coverage, and finally illustrate a scenario where interventions are either provided at 95% coverage or not at all (as is usually done in health benefits package design) for comparison. The results present the optimal trade-off between the social benefits of pursuing full population coverage, at the expense of expanding the benefits package for 'easier to reach' populations.