The Costs of Health Protection: Economic Pearls from the APHA Meetings

What’s the price of protection from disease transmission? Public health’s long-standing responsibilities in disease investigation and control have taken center stage in recent weeks in response to concerns about Ebola transmission risks in the U.S. These responsibilities remain bread-and-butter work of America’s local and state public health agencies more than 150 years after John Snow famously used them to locate and contain the source of that London cholera outbreak. Although CDC stands front and center in coordinating the U.S. Ebola response, local and state agencies shoulder most of the actual effort in investigating suspected cases, tracing and monitoring contacts, maintaining records on investigation and control activities, and disseminating guidelines to physicians and other health professionals regarding response and mitigation protocols. These agencies also play critical roles in advising state and local policymakers regarding legal interventions for disease control (no small task in the case of Ebola), and in keeping the general public up to date and informed. Ebola is a very, VERY special case, but routine disease investigation work happens every day in every community across the U.S. as agencies investigate routine but costly risks such as suspected food-borne and water-borne illnesses, vaccine-preventable diseases, and sexually-transmitted infections.

Amazingly, we know very little about the resources required to perform this work effectively in a given community or state, and about the factors that influence these resource requirements. Without evidence about what it costs to do this work, and about the community characteristics that make this work more or less resource-intensive, there is no way of knowing whether society spends too much or too little on disease investigation activities, and whether we distribute these resources optimally and equitably across the U.S. based on disease risks and prevention opportunities.

This week’s APHA meetings in New Orleans finally gave us some answers about the prices we should be willing to pay for disease investigation and control. Early results from a series of studies funded through our Public Health Delivery and Cost Studies (DACS) were featured at this year’s meetings. One of these studies, led by Adam Atherly and colleagues in the Colorado Public Health PBRN and the University of Colorado, conducted detailed time studies of disease monitoring activities carried out in that state during 2014. Results show that the cost of disease monitoring starts at about $13,000 per year in the average community, and increases by about $400 per case detected but at a decreasing rate of growth – demonstrating large economies of scale. These findings tell us quite a bit about how we might design better funding models to ensure equitable disease investigation capabilities across the U.S., and how we might pool resources and expertise across sparsely populated and low-resource communities to achieve more cost-effective protections.

Another DACS study led by Lori Bilello and colleagues from the Florida PBRN and the University of Florida-Jacksonville, focused on the cost of disease control activities for sexually-transmitted infections. The most striking finding from this study is the sheer magnitude of cost variation across Florida’s local communities. My take on this study is that much of the cost variation reflects differences in the intensity of disease control activities implemented by Florida’s county health departments and their partner organizations, begging the question of whether more intensive activities provide health returns that justify their higher levels of investment. The Florida study also identifies differences in the efficiency of STI control activities, with some agencies lagging behind in the adoption of modern screening and diagnostic technologies that do not require costly and intrusive physical examinations. Donobedian’s law of “no measurement, no improvement” is clearly on display in Florida’s study, as well as in Kim Gearin’s study of community-level variation early childhood vaccination performance in Minnesota.

APHA showcased many other interesting studies on the economics of public health delivery (see our full list of RWJF-supported PHSSR studies presented at APHA this week). This work includes:

§ Our study to estimate the effects of Medicaid expansions on public health spending and service delivery (teaser figure below);

§ Our ongoing work to estimate the costs of supporting Foundational Public Health Capabilities as recommended recently by the Institute of Medicine;

§ Our analysis of geographic variation in implementing high-value public health services for chronic disease prevention, communicable disease control, and environmental health protection using data from the MPROVE study;

§ Our analysis of the early public health implications of Kentucky’s experience in implementing key provisions of the Affordable Care Act.

§ More work from the University of Washington ‘s Betty Bekemeier and colleagues in the Public Health Activities and Services Tracking Study (PHAST), showing links between local health department spending and rates of communicable disease.

Clearly, beignets and the Big Muddy were not the only attractions on the New Orleans riverfront this week (but the beignets were very good indeed).

Stay tuned to this blog and contact the National Coordinating Center for Public Health Services & Systems Research for more information on these or other studies about the economics of public health delivery. I invite you to comment on this blog, tweet at me, nudge me on linkedin, and follow my research archive.

Learning from Variation in ACA Implementation

Political scientists, economists, and other social scientists frequently exploit variation in the implementation and timing of policy initiatives in order to estimate impact and effectiveness. The Affordable Care Act (ACA) creates abundant opportunities for these types of variation studies and natural experiments that can help us learn which implementation strategies work best, for which population groups, and under what conditions.

Numerous ACA provisions give states, local governments, health care systems, and even individual providers broad discretion in deciding what to do under ACA and when to do it. Beyond the high-visibility state decisions concerning Medicaid expansions and health insurance exchange operations, states are making hundreds of other implementation decisions about strategies like insurance outreach and enrollment, provider network adequacy, multi-payer payment models, and initiatives to expand and integrate medical, public health, and social services delivery systems to improve population-wide health status. Hospitals and physicians get to decide when and how to try their luck at ACA-supported accountable care organizations (ACOs), patient-centered medical homes (PCMHs), and various forms of bundled-payment and shared-savings models. Insurers and employers are choosing whether and how to incorporate incentives for quality improvement and wellness into their health benefits designs. Public health and community-based organizations get to decide whether and how to compete for funding to implement policy, environmental, and system (PES) changes that promote health and prevent disease and injury with support from the ACA’s Prevention and Public Health Fund. Variation due to public-private discretion, competition and entrepreneurship abound within the ACA.

How do we harvest the potential knowledge and learning from this large-scale implementation variation? A meeting this week at the Brookings Institution in Washington DC focused on developing some key research strategies. One conclusion reached early on in the meeting: it is possible to capitalize on the fact that many, many research institutions have studies underway regarding ACA implementation and impact. RAND’s Health Reform Opinion Survey and COMPARE microsimulation model, the Urban Institute’s Health Reform Monitoring Survey, the University of Chicago’s ACA Scholar Practitioner Research Network, the Princeton University/RWJF State Health Reform Assistance Network, Georgetown’s Center on Health Insurance Reforms, Kaiser Family Foundation’s Health Reform Initiative, and many other fellow travelers have big studies underway regarding key elements of ACA. (This includes our PHSSR Center’s own studies of ACA’s effects on the U.S. public health system). These many individual studies create opportunities for harmonization, triangulation, data linkage and pooled analyses, meta-analyses and research synthesis.

What’s missing from the many “big data” ACA studies are clear pictures of what’s happening on the ground in individual states and communities – an ability to characterize the patterns of variation in implementation at more granular scales, and to determine how these patterns influence health care delivery and outcomes. The research community has yet to provide a clear understanding of how and why ACA implementation strategies vary across the U.S., and how these various strategies play out in different political, institutional, socioeconomic and cultural contexts.

To fully exploit the research opportunities presented by ACA implementation variation, researchers require the ability to be many places at the same time and observe what is happening on the ground in a variety of communities and practice settings. Researchers need the stamina and staying power to observe implementation processes continuously over time. And researchers need the versatility to employ mixed-method research approaches that productively combine (1) large amounts of qualitative data on implementation strategies collected from multiple perspectives and settings with (2) the array of large quantitative data sources that offer measures of provider and consumer behaviors, service delivery patterns, and related health and economic outcomes.

This is where the Brookings Institution’s Engelberg Center for Health Care Reform and their partners at the Rockefeller Institute of Government at SUNY and the Fels Institute of Government at the University of Pennsylvania come into play. Over the past year, scholars at these institutions have convened a multidisciplinary network of researchers across the U.S. who are well-positioned geographically and institutionally to observe ACA implementation strategies at granular levels in some 36 states. The researchers that comprise the ACA Implementation Research Network have access to multiple ACA decision-makers and key informants, multiple sources of secondary data, and a variety of supporting documents and records relevant to ACA implementation at state and local levels. Already, this network has completed a series of baseline studies of ACA implementation in a broad cross-section of states (for example see our report on ACA in Kentucky and similar reports for other states).

After demonstrating proof of concept through these baseline studies in individual states, the ACA Implementation Research Network is now embarking on a series of larger-scale, cross-cutting topics that involve collection and analysis of standardized data on ACA implementation across a large number of states. This first wave of cross-cutting studies target topics such as: (1) state information technology strategies and capacities to support ACA implementation; (2) consumer support and outreach strategies for insurance enrollment; (3) provider network composition among insurers participating in the state exchanges; (4) implementation strategies used in “oppositional states” where policy leaders oppose the ACA; and (5) state strategies for reforming health care and public health delivery systems. I hope to play a leading role in this last cross-cutting study, together with other colleagues in the PHSSR enterprise. Specifically, we hope to leverage studies that we already have underway concerning public health delivery system reform, and to leverage the strength of our public health practice-based research networks (PBRNs) across the U.S.

The ACA Implementation Research Network is strongly committed to engaging knowledge users in the design and implementation of its ACA research, and to disseminating findings rapidly and continuously to decision-makers in policy and practice settings. We are excited to be a part of this collaborative experiment in large-scale policy implementation field research, and we believe it will become a valuable source of knowledge and learning over time. Fellow travelers in public health economics and delivery system research will want to keep close tabs the progress of this new effort.

Northern Lights: Canadian Insight on Bridging Public Health and Health Care Delivery to Improve Population Health

The United States and Canada have long compared the relative performance of their medical care systems in order to identify pathways for improvement, but the public health systems of these two countries receive much less attention by scholars and pundits. Having spent the past few days meeting with some of the best public health minds and hands in Canada, I conclude that there is much to be learned about ways of improving the organization, financing and delivery of public health strategies in the U.S. through comparative research with Canadian models.

Canada’s system of universal health care financing and delivery formed incrementally during the 1940s through the 1980s, but its public health institutions developed quite independently following a much longer time path. The result – at least until relatively recently – was public health institutions that operated relatively autonomously from health care delivery institutions with separate funding streams, much like the U.S. experience. Over time, Canada’s provinces and territories have implemented various forms of regionalized health care delivery in an effort to pool resources and expertise for the purposes of improving quality, constraining costs, and reducing inequities in delivery. Over the past decade or so, many (but not all) provinces have transferred public health responsibilities and funding from municipal and provincial agencies to these regional health care delivery institutions, called regional health authorities. Provincial Ministries of Health have retained overall responsibilities for stewardship of their integrated regional health systems using the levers of funding, policy, monitoring and accountability. The provinces also administer some core public health functions centrally such as selected surveillance, epidemiology, and laboratory capabilities – much like many state public health agencies in the U.S.

Structurally, Canada’s integrated regional health authorities look and feel like advanced versions of the accountable care organization (ACO) models that are now taking shape in the U.S., at least in the more comprehensive and ambitious ACO models that endeavor to incorporate public health responsibilities into “totally accountable care” strategies. As such, Canada seems to offer Americans a unique opportunity to gaze into the future and anticipate some of the benefits and challenges associated with bridging public health and medical care delivery systems to improve population health.

Why am I so enthusiastic about the knowledge to be gained from US-Canadian comparative research on public health systems and services? In full disclosure, most of my knowledge derives from several days of intensive exchange with colleagues in the west coast province of British Columbia. BC has a diverse population of about 4.3 million, spread across a geographic area larger than Texas. Five regional health authorities operate in the province of BC, two of which serve the heavily urbanized population of greater Vancouver, with other authorities serving vast areas of sparsely populated rural and remote communities. In my couple of days in this province, I was able to gather intelligence on Canadian public health systems research and share insight from our U.S. based studies through a number of different venues, including:

§ Giving seminars for the BC Centre for Disease Control and the multi-institutional BC Population Health Network based in urban Vancouver, where some of the province’s best public health scientists and practitioners convene (slides here and here);

§ Speaking at the 141st meeting of the Health Officer’s Council of British Columbia held in suburban New Westminster and meeting with this fiercely independent group of public health physician leaders, many of whom function within the regional health authorities (slides here);

§ Jumping a seaplane over to the island city of Victoria to meet and lecture with the awe-inspiring intellectual leaders of public health systems research at the University of Victoria and their colleagues at collaborating institutions like the University of British Columbia, University of Toronto, and University of Saskatchewan (slides here);

§ Boarding the mothership at the Province of British Columbia Ministry of Health to meet with their Population and Public Health Division and speak as part of the Ministry’s research and policy rounds (slides here and here).

My conclusion from this whirlwind: the evidence, experiences, and ideas of this diverse Canadian providence are extremely relevant to our American experimentation with public health system transformation. Moreover, the other Canadian provinces beyond BC offer yet additional models of public health organization, financing, and delivery that are ripe for comparative analysis. Health systems researchers would be foolish not to harvest the rich opportunities for comparative public health delivery research spanning the American-Canadian border.

Fortunately, Canada already has a strong foundation of applied public health services and systems research (PHSSR) led by ongoing studies of researchers based at the University of Victoria. This group embarked on a large program of research known as the Core Public Health Functions Research Initiative in 2006, with the goal of elucidating the implementation and impact of BC’s multi-pronged strategies to improve the effectiveness of core public health functions across the province. This effort led to an even larger and geographically more expansive research program funded by the Canadian Institutes of Health Research (CIHR) beginning in 2009 and known as the Renewal of Public Health Services in BC and Ontario, which supports comparative research on the implementation and impact of core public health strategies across these two diverse provinces. The academic ringleaders of Canada’s PHSSR enterprise include Professor Marjorie McDonald, RN, PhD, who holds a chair in public health education and population intervention research at the School of Nursing, and Dr. Trevor Hancock, MB, MHSc, who is a professor and senior scholar in the School of Public Health and Social Policy and one of the founders of the international Healthy Cities/Healthy Communities movement.

These Canadian PHSSR researchers approach their work with the versatility and realism that only mixed-method investigations can achieve. And much like our U.S. based public health PBRNs, these scholars are firmly entrenched in the principles and practices of collaborative, practice-based research. Every study is led by a team of “knowledge users” firmly embedded in the real world of public health practice and policy, along with relevant academic researchers. Not coincidentally, this research group has produced some of its best work to date on studies of “Knowledge to Action” strategies that support the use of evidence in public health program development and implementation processes. Another defining feature of this team’s research it its strategic selection of specific public health practice domains to study as “exemplars” for how public health delivery systems function as a whole – a concept that is analogous to the long-standing use of tracer conditions in health services research. To date UVic’s exemplars have included healthy living strategies, food safety, unintentional injury prevention, and emergency preparedness.

To be sure, BC’s rich public health research environment is only partially attributable to its research universities like UVic and UBC. A large, diverse, and talented pool of scholars exists within the BC Ministry of Health and within regional health authorities like Frasier Health, many of whom have formal linkages and appointments with the surrounding universities. Epidemiologists, economists, sociologists, engineers, policy and legal scholars, biomedical scientists, and many other disciplines are represented among these “pracademics” who produce and publish top-shelf research alongside their operational and managerial responsibilities within the health system. Conducting applied research studies within the Ministry of Health and its regional health authorities appears to be far from a novel concept within the province of BC. A new Guiding Framework for Public Health in BC was released by the Ministry last year, which has begun to provide new focus for applied research and evaluation within the province.

My few days of immersion in BC public health research and reality left me with a few intriguing impressions that seem worthy of further exploration through comparative PHSSR and public health economics research, including the following:

§ Bringing public health and medical care delivery under a common organizational structure and global budget may not automatically and instantaneously result in integrated health systems that adopt a population health perspective and prioritize upstream, long-term strategies for disease prevention and health promotion. Challenges persist in balancing the resource needs and performance expectations of medical care and public health even in integrated regional structures. Our American ACOs need to learn from relevant Canadian models and experiences.

§ Governance and decision-making structures for public health vary in their composition and functioning across Canada as they do in the U.S. These structures appear highly influential in shaping public health strategy and implementation, and as such represent worthy mechanisms to study and understand.

§ Canada’s health system leaders and public health researchers are making enviable progress in integrating a health equity lens into their science, policy and practice. BC’s new First Nation’s Health Authority is one manifestation of this perspective that is worthy of special attention from researchers and policy analysts, particularly given its explicit emphasis on wellness and culture and its unique governance and decision-making structures. The U.S. PHSSR enterprise has not been particularly deliberate nor successful in incorporating the perspectives and experiences of Native American populations into its research, so this is an area that could benefit from Canadian leadership and expertise.

§ Canadian policy leaders and researchers continue to struggle with the underlying theory, methods and mechanics of defining and measuring core public health functions, their costs, and their health and economic value. These are challenges that American scholars and practitioners clearly share. For forward momentum, there appears to be some enthusiasm behind the idea of adapting some of our U.S. PHSSR methods and measures for deployment in the Canadian context, including our National Longitudinal Survey of Public Health Systems, our MPROVE measures of public health implementation, and our DACS cost estimation methods. Doing so would open up some extremely powerful opportunities for international comparative research.

I encourage fellow travelers in PHSSR and public health economics to look northward for inspiration and insight that can advance your own programs of research. Watch this blog for future posts on our progress in mobilizing Canadian-American comparative research on public health delivery systems.

Expanding Experiments in Public Health Delivery Systems

One of the most promising developments in health and social policy research these days is the renewed push for using experimental designs to determine the effectiveness and efficiency of programs, policies, and implementation strategies in real-world settings. Random-assignment studies have been the gold standard in medical research for more than a half-century now because of the strong internal validity they provide, but these types of study designs are much less frequently used to study non-clinical interventions. The time and monetary costs of trials, logistical barriers, legal and ethical concerns, and the problem of weak external validity have led many health services researchers and policy implementers to shy away from randomized designs in favor of purely observational and quasi-experimental studies. Those large and massively expensive social experiments conducted in the 1970s and 1980s – like the RAND Health Insurance Experiment, the Negative Income Tax Experiment, and the COMMIT Smoking Cessation Trial – are probably partly to blame for our more recent trial-reluctance, despite the extremely valuable evidence generated by some (but not all) of these costly studies.

What’s driving enthusiasm for experimentation now are the concepts of the pragmatic trial and the large simple trial in the context of promoting comparative effectiveness research (CER) and a learning health system. By relaxing some of the requirements of a traditional randomized double-blind placebo-controlled clinical trial, it becomes possible to implement trials in real-world settings reflecting realistic policy and program choices and alternatives, thereby dramatically improving external validity without sacrificing much internal validity. Pragmatic trial designs can also reduce the monetary and time costs required to produce new evidence, such as by using existing data sources and reporting systems to monitor health and economic outcomes both before and after research subjects and/or settings are randomized to alternatives. And of course, it’s not just individual “patients” who can be randomly assigned to “treatment” alternatives – with a low-cost pragmatic trial, it becomes possible to randomly assign work teams, organizations, multi-organizational collaboratives, and even entire communities to different ways of doing things and different levels of exposure.

Research funders like the Patient Centered Outcomes Research Institute (PCORI) are now actively encouraging the use of pragmatic trials, mostly in the context of studying specific therapeutic interventions and their clinical delivery systems. And groups like MIT’s Jameel Poverty Action Lab (JPAL) are actively organizing low-cost pragmatic trials on a variety of health and social program interventions centered on poverty reduction, mostly in developing countries but now more recently in the U.S. The Coalition for Evidence Based Policy and the White House itself are also major proponents of this approach in U.S. health and social policy research.

These developments suggest that the time is right for American public health agencies and their partners who implement public health programs and policies across the U.S. to expand their use of pragmatic experimental trials. Many of the programs, policies, and delivery system strategies used in public health to prevent disease and injury and promote health on a population-wide basis have inadequate evidence concerning their health and economic impact. This fact is partly responsible for ongoing political and policy controversies concerning the ACA’s Prevention and Public Health Fund. Moreover, public health delivery systems in the U.S. are undergoing significant changes in their organization, financing, and operations due to economic and policy imperatives triggered by health care reform and public finance constraints. In the face of these policy uncertainties and pressures for change, why not incorporate pragmatic trials into our public health decision-making and implementation processes?

State and local public health agencies often have considerable (though perhaps under-appreciated) discretion over key details concerning how programs and policies are implemented. What types and levels of staffing to use, where and how to locate programs, how to recruit and engage target populations, how to tailor approaches for specific subgroups of interest, what mechanisms to use for disseminating and communicating information, what duration, sequencing and timing of activities to implement, how to divide roles and responsibilities among collaborating organizations, what financing and payment mechanisms to use – to the extent that these ingredients plausibly influence the effectiveness and efficiency of public health strategies, they represent promising targets for experimentation. Moreover, public health agencies are awash in existing data sources from both active and passive surveillance systems and program reporting requirements that can be used to structure pragmatic trials.

Powerful examples of pragmatic trials organized in public health settings are becoming more numerous, providing proof-of-concept that it is possible and worthwhile to organize such experiments. For example, a group of after-school programs for children in the Chicago area organized a field experiment to test different informational and material incentives designed to improve children’s food choices in a USDA-supported free meal program, showing that the introduction of small material incentives increased the take-up of healthy snacks by more than 400%. Similarly, a trial that I posted about earlier this summer from the ARM meeting tested the cost-effectiveness of a novel strategy for boosting child vaccination rates using a reminder and recall (R&R) intervention delivered centrally by local health departments in collaboration with community-based primary care practices. That study found that the collaborative, health department-delivered R&R model outperformed a standard physician practice-based R&R model both in terms of vaccination rates and in terms of costs, clearly showing the value of collective action involving public health agencies and primary care practices. Most recently the Coalition for Evidence Based Policy announced 3 new studies that will receive funding through its competition for low-cost randomized controlled trials, and 2 of these studies involve public health programs and delivery systems. One study in Durham NC costing just $183,000 will examine the health and economic impact of a postnatal nurse home visiting program, and another study conducted by the federal OSHA agency costing just $153,000 will test the effectiveness of a novel randomized workplace safety inspection policy that randomly selects worksites to receive onsite federal worker safety inspections.

Our National Coordinating Center for PHSSR is working to help create the conditions and infrastructure necessary to support pragmatic trials and other strong research designs in U.S. public health delivery system settings. For example, we have launched Practice-Based Research Networks (PBRNs) in more than 30 states that bring together state and local public health agencies and university-based researchers into ongoing research collaborations for the purposes of studying variation, change, and innovation in public health delivery. With several years of history in collaborative research now under their belts, many of our PBRNs are now well-positioned to progress to pragmatic trial designs wherein a network’s participating local public health settings can be randomly assigned to pursue different implementation approaches. One such trial is already underway in our Kentucky PBRN to test the effects of cultural competency training for local public health workers. A growing base of experience now exists with implementing studies that involve multiple PBRNs in the U.S., bringing in a larger number and diversity of communities and public health settings into the study design. Moreover, we recently launched a series of natural experiment studies in public health settings that, while not randomized, are helping both public health researchers and practitioners use more advanced research design and analytic methodologies like propensity-score matching and instrumental-variables estimation to support causal inferences and address threats to internal validity.

On the data and measurement front, our Center is working with colleagues at the University of Washington and other partners to standardize the measurement approaches and data sources used in state and local public health settings, in order to make large-scale pragmatic trials even more possible. For example, our recent Multi-Network Practice and Outcome Variation Examination (MPROVE) study has been working with PBRNs in six states to develop and implement a standard set of measures of public health delivery involving chronic disease prevention, communicable disease control, and environmental health protection –many of which are constructed using existing, routine data systems at state and local levels. These MPROVE measures, maintained over time, can provide a powerful data platform for supporting pragmatic trials in many different programmatic areas ranging from obesity prevention to food-borne illness control. Our Center also works to construct and analyze longitudinally linked analytic data files from a variety of other sources, including NACCHO’s periodic National Profile census survey of local health departments, the Census Bureau’s Annual Surveys of State & Local Government Finance, and our own National Longitudinal Survey of Public Health Systems which has followed a national cohort of communities since 1998.

To be sure, experimental designs are neither appropriate nor feasible for answering all of the questions of interest in empirical public health economics and PHSSR. But there are certainly many opportunities for using trials in public health settings to produce valuable evidence that are currently unrealized. Using resources like PBRNs and our expanding set of PHSSR measures and data sources, it is possible to employ pragmatic randomized trial designs more frequently to generate strong evidence about what works best for whom in public health delivery. Rigor and relevance need not be mutually exclusive.

Better Living through Chemicals? Addressing Substitution Effects in Medicine and Public Health

An interesting new study published in next month’s Journal of Health Economics examines the moral hazard involved in prevention through pharmaceutical therapy, and it has implications for the ACA’s goals of population health improvement. A convincing body of research shows that the dramatic rise in statin use over the past two decades has improved cardiovascular health by reducing the incidence of high cholesterol, serious cardiac events like AMI, and mortality from cardiovascular disease. But do statin users slack off on their nutrition and physical activity, consistent with a substitution effect, possibly leading to other health problems? Or do statin users redouble their healthy living because the drugs increase life expectancy and therefore boost the value of investing in future health status, consistent with a complementary effect?

Robert Kaestner and colleagues use longitudinal data from the famous Framingham Heart Study to investigate these questions. Using data collected on people with moderate to high cholesterol both before and after the introduction of statins in the U.S. market (1991-2001), the researchers observe changes in health behaviors associated with statin use.

Naturally, this study faces considerable risks of bias due to unobserved confounding and endogeneity because people may initiate statins due to unobserved health shocks that also influence their subsequent health behaviors. The authors use one of my favorite techniques to mitigate this bias: fixed effects estimation with a novel instrumental-variables technique. The IVs used here reflect the gradual time trend in the availability and use of statins among people who eventually become users of the drug, capturing the presumably exogenous forces that influence the diffusion pattern of a new drug. And these IVs stand up to the usual tests of strength and excludability (well, mostly…).

Results indicate that statin use led to a small BMI increase and a larger increase in the probability of being obese, consistent with the substitution hypothesis. The effect on physical activity, however, was mixed, with women reducing and men increasing their activity levels in response to statin use. Smoking was not consistently responsive to statin use, but moderate alcohol use increased among males. The authors conclude that statins serve as a strong substitute for healthy dietary intake but not for exercise or other general health behaviors that have a weaker association with cholesterol levels.

Taken as a whole, these results provide another powerful reason for combining clinical and non-clinical approaches when attempting to promote health and prevent disease on a population-wide basis. One approach used in isolation may generate behavioral offsets and unintended consequences that slow progress toward larger population health goals. As a result, medicine and public health strategies applied together may have larger effects than either strategy acting alone – the true definition of synergy. The ACA includes provisions to facilitate and incentivize these types of combined strategies, but more research is needed to determine whether these provisions work as intended. This blog will track the progress of this research, so stay tuned.

The Comparative Effectiveness of Preparedness

The CDC’s anthrax event earlier this week provides a reason to reflect on the uncertainties and difficult policy choices involved in reducing the health risks posed by large-scale disasters. Modern societies face a complex and evolving mix of potential disasters, ranging from intentional acts of violence and terrorism, to uncontrolled viral pandemics, to the weather-produced emergencies fueled by climate change. A new paper from economists at the London School of Economics and MIT offers some useful insight into a critical but too-often obscured question in the preparedness field: how should governments decide which potential disasters to prevent and prepare for, and how much to invest in such strategies?

Ian Martin and Robert Pindyck’s paper shows that cost-benefit analysis of a single strategy to avert a catastrophe, considered in isolation, is unlikely to give us the correct answer about the health and economic value of pursuing that strategy. The policy interdependence of potential catastrophic events means that it is often not socially or economically optimal to avert all such events, even when an apparently cost-effective strategy is available for each hazard. To use preparedness speak, the optimal “all hazards” approach to risk mitigation may not, in fact, seek to avert all hazards.

A key reason for this result is that the existence of one hazard often increases the benefit of averting another hazard, due to the law of diminishing returns. For example, a policy to contain the threat of pandemic influenza will produce more social benefit when other hazards also threaten the population, like catastrophic flooding or industrial accidents. As these background or competing hazards diminish, so too does the value of averting the primary hazard. Martin and Pindyck’s theoretical analysis shows that, when seeking to avert multiple hazards, “the benefits are additive but the costs are multiplicative,” so policymakers should seek to identify the subset of hazard mitigation strategies that maximize net benefit to society.

In practice, identifying this optimal subset of hazard prevention and preparedness strategies can be difficult in the presence of many possible hazards and many ways of reducing risk, which vary across communities and population groups. To address these decision challenges, the authors point to a need for: (1) better measures of risk, vulnerability and resilience; and (2) more research on the effectiveness and cost of prevention and preparedness strategies.

Fortunately, initiatives such as the National Health Security Preparedness Index program are pushing on both fronts – for improved metrics and for expanded research – promising eventually to enable vast improvements in evidence-informed preparedness policy. And even though the CDC’s federal Preparedness and Emergency Response Research Centers Program is sunsetting, this initiative has spawned numerous lines of inquiry that are producing valuable evidence about the effectiveness of preparedness strategies (see for example work that Mary Davis and I have done with colleagues at UNC’s preparedness center to explicate the roles of local public health capabilities in producing preparedness). Some of the most promising recent progress in preparedness research is exploring what makes communities resilient to various types of hazards, and how to promote and reinforce such resilience. See for example Malcolm William’s latest research on this topic presented at last week’s AcademyHealth meeting.

Continued progress in these lines of inquiry will bring us closer to understanding the comparative effectiveness of preparedness: which combination of strategies produce the greatest net benefits, for which populations, and in which community contexts. This type of CER evidence is needed not just for treatment choices facing individual patients, but also for health policy choices facing populations.

Costs, Collective Actions and Crowd-Out in Public Health: New Evidence from ARM

AcademyHealth’s Annual Research Meeting (ARM) convened in San Diego this week to unleash the latest findings from a host of new health services research studies, many with a strong orientation toward economics and public health. I cannot begin to summarize all the great work from this meeting in a single post, so for now I will take a random thought-walk through a couple of the studies I found most striking. (Note: I will update this post in a few days with links to meeting slides once they are posted online).

Front of mind for me is the fascinating pragmatic randomized trial conducted in local health department settings by Allison Saville and her colleagues at the University of Colorado, Colorado Children’s Hospital and Colorado’s state health department. This trial tested the cost-effectiveness of a novel strategy for boosting child vaccination rates using a reminder and recall (R&R) intervention delivered centrally by local health departments in collaboration with community-based primary care practices. The study found that the collaborative, health department-delivered R&R model outperformed a standard physician practice-based R&R model both in terms of vaccination rates and in terms of costs, clearly showing the value of collective action involving public health agencies and primary care practices.

Another elegant study of vaccination practices was presented by LA County Health Department’s Ricardo Basurto-Davila and colleagues, focusing on the health and economic effects of school-based vaccination programs used during the 2009 H1N1 influenza outbreak. The researchers find that school-based strategies produced significantly higher child vaccination coverage rates than did traditional community-based and clinic-based vaccination programs. These higher rates of child coverage, however, came at the expense of coverage among adults 65 years of age and older. In fact, the cost reductions achieved by school-based vaccination programs were attributable mostly to the lower vaccination rates they produced among seniors, rather than to lower disease transmission rates among children. The findings suggest that public health agencies must carefully consider the characteristics of the outbreak and the population groups most at risk when choosing to use mass vaccination strategies for influenza.

Other economically interesting studies focused on food and diet-related public health risks. The University of Washington’s Betty Bekemeier linked financial data on local expenditures for food safety and sanitation with county-level surveillance data on the incidence of food-borne and water-borne diseases in two states over 8 years, finding that some of these diseases are less common in higher-spending communities. A very different study presented by Washington’s Davine Wright used a Markov model to estimate the cost-effectiveness of a school-based screening program designed to detect eating disorders in children, finding an attractive cost per QALY gained of about $57,000.

Penn’s famed behavioral economist and physician Kevin Volpp presented findings from two new trials that explored whether financial incentives tied to weight loss tend to crowd-out the intrinsic motivations people have to achieve a healthier weight. He finds that voluntary participants in randomized weight loss trials tend to have high levels of intrinsic motivation for weight loss at baseline, and that randomly assigned financial incentives do not erode these motivations significantly during the course of a trial. Money does not appear to crowd-out other forms of motivation in these studies.

The new study I presented at ARM this year examined financial crowd-out at a higher scale of operation − one that is particularly relevant now that 26 states are in the midst of implementing the ACA’s Medicaid expansions. Specifically, we asked: does growth in state Medicaid spending crowd out the ability of state governments to invest in other types of beneficial public health programs? And if so, what are the health consequences of such crowd-out? Using almost 20 years of data from 1993-2011, we find evidence of significant crowd-out, consistent with the federal matching formula that rewards states for Medicaid spending but does not provide commensurate incentives for other types of public health outlays. We project that, over time, this crowd-out phenomenon is large enough to result in elevated rates of preventable mortality, offsetting the mortality gains produced by expanded Medicaid coverage. (We were flattered for this work to receive designation as one of the “Best of ARM” studies and as such to receive critiques from noted health economists Steve Parente and Jack Needleman during the meeting).

And speaking of the best, UC-Berkeley’s Tim Brown received the AcademyHealth Article of the Year Award in Public Health Systems Research for his research examining the health effects attributable to public health spending by California’s local agencies. In a pair of recent analyses using careful panel data methods and instrumental-variables techniques, Tim finds sizable reductions in all-cause mortality and notable gains in self-reported health status among California counties that experience growth in per-capita local health department spending during 2001-2008. These studies add to a growing evidence base regarding the health and economic value of public health activities.

Equally importantly, these studies and the larger ARM meeting (including the Public Health Systems Research Interest Group meeting) showcase the value of investing in rigorous research designs and analytic methodologies to answer important questions about public health policy and practice. These studies show that creativity, persistence, and a deep commitment to inquiry and analysis can produce valuable public health knowledge, even when time, money and data are constrained.

Murky Data Undercut the ‘Underfunding’ Argument in Public Health

The Trust for America’s Health latest annual report on U.S. public health expenditures was released last week, reminding us that good data on this topic are so frustratingly elusive. Consistent with past years, the report concludes that the U.S. public health system is “chronically underfunded.” But the sad fact is that available data are woefully inadequate to support this conclusion with any reasonable level of confidence and empirical precision.

As noted in previous posts, a high degree of uncertainty surrounds our best estimates of governmental public health spending. Three basic questions of public finance go mostly unaddressed in public health:

1. How much does the nation currently spend on public health activities?

2. Who pays for these activities?

3. How are funds allocated and used across programs and population groups?

Without solid answers to these questions, it is impossible to make a strong case that public health is “underfunded” in the sense that current spending falls below a given threshold defined by objective measures of need, risk, or efficiency. Moreover, answering the basic public finance questions are necessary prerequisites for determining the health and economic value of investments in public health strategies. TFAH deserves credit for soldiering through this data desert, scraping information from public budget documents, websites, and interviews with public health officials. But these sources cannot yield the completeness, comparability and granularity of data needed for sound policy analysis and deliberation, much less for credible economic research and evaluation.

What makes this fiscal opacity even more frustrating is that mechanisms currently exist that could be employed to generate high-quality data on governmental public health spending: the U.S. Census Bureau’s annual Survey of Government Finances and the quinquennial Census of Governments. These mechanisms could be used to produce government-wide data on how much is spent on public health activities, who pays, and how funds are used. These mechanisms could be used to capture and analyze data on the incidence and level of spending in high-priority areas like tobacco prevention, obesity prevention, infectious disease control and food safety protection – information that could be combined with existing disease and risk surveillance data to help society make better decisions about where and how to deploy resources, and to help us learn faster what’s working and what’s not.

Of central importance, such data would fill in the many unknowns inherent in existing financial data captured from periodic surveys of state and local public health agencies, which are subject to the vagaries of how public health responsibilities are divvied up within state and local government bureaucracies, and how these bureaucracies keep their books. (Although their financial measures are imperfect, these periodic surveys are extremely valuable for conducting research on the implementation and impact of public health strategies, as my own studies and many others in the field of PHSSR illustrate).

Why aren’t public health expenditure data already regularly produced? Using the federal government’s existing governmental data collection mechanisms to produce better data on public health spending would probably require channeling some additional funding to the Census Bureau – a nontrivial but not insurmountable requirement. The larger challenge involves reaching consensus on what set of governmental activities should be defined and measured as public health responsibilities on a nationwide basis. This is a long-standing problem for the public health profession, which often relies on flexible and fuzzy conceptualizations of public health activity to build broad advocacy coalitions and to navigate ideological differences of opinion about the appropriate roles of government in the health policy arena. To counter this problem, a 2012 report by the Institute of Medicine recommended a national consensus process to identify a “minimum package” of public health services that should be available in all states and communities, and some work is now underway.

Many other social sectors benefit from regular flows of reliable financial data, including education, housing, criminal justice, and medical care. These data enhance research and evaluation, policy analysis and decision-making, managerial benchmarking and quality improvement, and governmental accountability and transparency. Maybe it is time to generate and use such data for public health.

How Did Massachusetts’ Health Reform Reduce Mortality?

An interesting new study of the 2006 Massachusetts health reform law adds to a growing body of evidence demonstrating that coverage expansions and related reforms help to improve overall health status. Specifically, this is the first study of the Massachusetts reform to suggest that its health effects are sufficiently large so as to be detectable at the population level, as reflected in the overall mortality rates for counties. These very encouraging results beg the question of how the results were achieved — which components of comprehensive reform are responsible for the drop in mortality?

The estimated 2.9% reduction in all-cause mortality represents a large and significant drop in deaths at the population level, particularly given the relatively short 5-year study period following health reform implementation. Chronic diseases are the main drivers of morbidity and mortality in the U.S., and most of these diseases chip away at our health over long periods of time, eventually causing death. Interventions that can make a dent in overall death rates in the space of just a few years are few and far between, and certainly worthy of attention (as I noted in a related commentary on this study).

The study authors focus on the expansion of health insurance coverage as the active ingredient in the Massachusetts law that is likely responsible for the drop in deaths. The results imply that for every 830 adults who gained insurance coverage, 1 death was prevented. However, I am not entirely convinced of this implication, and believe there could be more to the story of how Massachusetts lowered their mortality rates.

This study examines the population-level health effects of a health reform strategy that included not only insurance coverage expansions but also improvements in preventive services delivery and public health protections. Other elements of Massachusetts’ health reform strategy, such as reducing out-of-pocket costs for clinical preventive services and enhancing public health programs and infrastructure, may have contributed to the drop in mortality. For example, other studies have found large reductions in smoking prevalence and tobacco-associated health events among Massachusetts Medicaid recipients after the state added a comprehensive tobacco cessation benefit to its Medicaid program in 2006 as part of its health reform strategy. These preventive strategies and the resulting drop in tobacco exposure could plausibly explain some of the observed drop in mortality.

Importantly, the research design employed in this study cannot definitively attribute the mortality reductions to the gains in insurance coverage. The study uses county-level mortality data, so we cannot be sure that the people who gained coverage are the ones who experienced a reduction in their mortality risk (the classic ecological fallacy problem). The study hinges on comparing Massachusetts’ 14 counties to a statistically matched comparison group of counties outside the state, so with such a small number of intervention counties there is always the risk of systematic nonequivalence between the intervention and comparison counties—particularly when some of the covariates used for matching (like the baseline uninsured rate) are themselves subject to considerable sampling error.

Of course, other studies that have focused more narrowly on coverage expansions – such as the recent Oregon Medicaid experiment studies – have failed to find evidence of significant mortality reductions. Most of these studies use person-level rather than county-level analyses, so they are not able to detect population-level effects and they are not vulnerable to ecological fallacy. And the Oregon studies so far have been limited to shorter follow-up periods than the five years used in this latest Massachusetts study. Still, the mixed results from existing studies raise the possibility that insurance coverage by itself may not be sufficient to achieve large population-level health improvements. The mortality reductions found in Massachusetts may be attributable to the study’s population-level perspective, which captures the effects not only of insurance coverage expansion but also of other elements of reform. If so, combining coverage expansion with enhanced prevention and public health programming might just be the secret recipe for successful health reform.

These results provide encouraging news about the population-level health gains that ACA may produce. Before their 2006 reform, Massachusetts was already better off than most other U.S. states in terms of health insurance coverage and overall health status. Consequently, we might expect to see even larger health gains as similar reforms take hold in less-advantaged states. Of course, some of these less-advantaged states have chosen not to implement some of the ACA’s reforms to date – specifically the Medicaid coverage expansions. And the ACA’s prevention and public health programming has been scaled back considerably as a result of sequestration and decisions to use Prevention and Public Health Fund resources for other priorities. So, ACA’s population-level health effects remain uncertain and a very important target for ongoing study.

Publishing and Funding Research on Public Health Economics

For fellow travelers in public health economics, this post provides a quick update on resources for publishing and funding research on these topics. First, the publishing frontier: I am guest-editing an upcoming supplemental issue of the American Journal of Public Health devoted to the topic of advances in public health services and systems research (PHSSR). This issue is being developed with support provided by the Robert Wood Johnson Foundation and the U.S. Centers for Disease Control and Prevention. We are especially interested in studies examining health and economic consequences of organizational strategies, funding mechanisms, workforce models, policy/legal approaches, and health IT applications deployed in public health settings. The extended deadline for submitting manuscripts is May 15, 2014, and more information is available here.

Next, the funding frontier: I have recently added a page to this blog that highlights research funding opportunities relevant to public health economics. This page is far from a comprehensive inventory at this stage, but I will be building it over time as I have time.

Speaking of research funding, for those who may have missed it, an interesting item was included in the President’s FY2015 budget request submitted to Congress earlier this month. A $5 million request for public health systems research at the U.S. Centers for Disease Control and Prevention was included in the HHS budget request, as authorize by Section 4301 of the ACA. As the request explains: “CDC will undertake research that seeks to identify the economic and budgetary impacts of public health interventions; expand data on health care utilization and effectiveness; and inform how public health should evolve and public health and health care should collaborate as the health care delivery system transforms.” This blog will keep track of any research findings that flow from this federal initiative, should it be implemented.