The Office of Science and Data Policy is the departmental focal point for policy research, analysis, evaluation, and coordination of department-wide public health science policy and data policy activities and issues. The Office provides authoritative advice and analytical support to the ASPE and departmental leadership on public health science policy and data policy issues and initiatives, coordinates science and data policy issues of interagency scope within HHS, and manages interagency initiatives in science policy and data policy. The Office works closely with staff from across the Department on strategic plan development and implementation efforts. The Offices also carries out a program of policy research, analysis, evaluation, and data development in these issues.
The Office of Science and Data Policy includes several components:
Topic Areas:
- HHS Data Council
- Strategic Planning
- Regulatory Impact Analysis
- Information Quality Guidelines
- Prevention and wellness
- Public health systems and functions
- Food safety and nutrition
- Drugs and devices
- Tobacco control and prevention
- Biomedical research and development
- Economic analysis
- Emergency preparedness, response, and recovery
- Data and statistical policy
- Health disparities and vulnerable populations
- Health information technology
- Microsimulation
- Privacy policy
VIEW REPORTS:
Examining Consumer Responses to Calorie Information on Restaurant Menus in a Discrete Choice Experiment
The 2014 U.S. Food and Drug Administration (FDA) final rule, “Food Labeling: Nutrition Labeling of Standard Menu Items in Restaurants and Similar Retail Food Establishments,” requires information on the calorie content of food items to be clearly displayed on menus. This FDA menu labeling rule applies to restaurants and similar retail food establishments that are part of a chain with 20 or more locations doing business under the same name and offering for sale substantially the same menu items.
Costs and Benefits of Selected Policy Tools to Promote Drug Development
The development of new drugs and biologics is critical to ensuring that the U.S. population continues to enjoy improvements in quality and length of life. However, pharmaceutical companies must balance this imperative with the need to earn economic returns when making investment decisions. Some drugs, although desirable from a societal perspective, may have low expected revenues or associated development challenges, resulting in underinvestment from pharmaceutical companies.
Estimating Medical Costs for Regulatory Benefit-Cost Analysis: Conceptual Framework and Best Practices
The U.S. Department of Health and Human Services (HHS) is required to assess the benefits and costs of its major regulations prior to promulgation. To support these assessments, in 2016 HHS issued its Guidelines for Regulatory Impact Analyses, developed under the leadership of its Office of the Assistant Secretary for Planning and Evaluation and its Department-wide Analytics Team. When developing these Guidelines, the Analytics Team recognized that HHS analysts needed more detailed guidance on estimating the medical costs of illness.
Valuing Time in U.S. Department of Health and Human Services Regulatory Impact Analyses: Conceptual Framework and Best Practices
Executive Order 12866, as supplemented by Executive Orders 13563 and 13771, requires that most U.S. government agencies assess the costs, benefits, and other impacts of their major regulations before they are promulgated. Under the leadership of its Office of the Assistant Secretary for Planning and Evaluation, the U.S. Department of Health and Human Services’ (HHS’s) Department-wide Analytics Team recently finalized detailed guidelines for the conduct of HHS regulatory impact analyses.
Analysis Report: Understanding the Role of Partnerships in Medical Product Development
Partnerships involving public sector organizations, academia, non-profits, and pharmaceutical companies have demonstrated their potential for addressing unmet needs in medical product research and development (R&D). Effective partnerships can enhance access to innovation, reduce risk, manage costs, and may provide a means for steering R&D investment to address societal objectives. Over the past 20 years, changes in technology, public policy and the business environment have resulted in the emergence of new public-private partnership (PPP) models.
Final Report Volume I: Background Paper, Declining Response Rates in Federal Surveys: Trends and Implications
Over the last decade, survey response rates have been steadily declining, and this decline has raised concerns across the federal government regarding the quality and utility of national survey data. Response rates are commonly considered the most important indicator of the representativeness of a survey sample and overall data quality, and low response rates are viewed as evidence that a sample suffers from nonresponse bias.
Measurement of Interoperable Electronic Health Care Records Utilization
The objective of this project was to develop methods to measure the degree of interoperability as a result of data sharing and use between users of certified technologies who are eligible for Meaningful Use (MU) incentives and non-incentivized Trading Partners (TPs) using non-certified technologies.
Guidelines For Regulatory Impact Analysis
Regulatory impact analyses (RIAs) apply a well-established and widely-used framework for collecting, organizing, and evaluating data on the anticipated consequences of alternative policies. They help ensure that regulatory actions are justified and necessary to achieve social goals, and that these actions are implemented in the most efficient, least burdensome, and most cost-effective manner possible (OMB 2011a). To support these aims, RIAs include an assessment of the benefits and costs anticipated to result from a proposed regulatory action and from alternative policy options.
Guidelines For Regulatory Impact Analysis: A Primer
Regulatory impact analyses (RIAs) apply a well-established and widely-used framework for collecting, organizing, and evaluating data on the anticipated consequences of alternative policies. They help ensure that regulatory actions are justified and necessary to achieve social goals, and that these actions are implemented in the most efficient, least burdensome, and most cost-effective manner possible (OMB 2011a). To support these aims, RIAs include an assessment of the benefits and costs anticipated to result from a proposed regulatory action and from alternative policy options.
Study of Costs Associated with Community Activities under the Communities Putting Prevention to Work (CPPW) Initiative
The Centers for Disease Control and Prevention’s (CDC’s) Communities Putting Prevention to Work (CPPW) program funded 44 communities and states under the American Recovery and Reinvestment Act (ARRA) to implement community-based tobacco and obesity prevention interventions. As part of the larger evaluation of the program, we conducted a study of the implementation costs across all funded communities. In this report, we summarize findings from our analysis of the costs of CPPW across all of the ARRA-funded programs.
Observations on Trends in Prescription Drug Spending
Key findings • Expenditures on prescription drugs are rising and are projected to continue to rise faster than overall health spending thereby increasing this sector’s share of health care spending. • ASPE estimates that prescription drug spending in the United States was about $457 billion in 2015, or 16.7 percent of overall personal health care services. Of that $457 billion, $328 billion (71.9 percent) was for retail drugs and $128 billion (28.1 percent) was for non-retail drugs.
HHS Action Plan to Reduce Racial and Ethnic Health Disparities: Implementation Progress Report 2011-2014
ASPE REPORT HHS Action Plan to Reduce Racial and Ethnic Health Disparities: Implementation Progress Report 2011-2014 Novermber 2015 U.S. Dept. of Health and Human Services. Office of the Secretary. Office of the Assistant Secretary for Planning and Evaluation and Office of Minority Health About This Report
Valuing Utility Offsets to Regulations Affecting Addictive or Habitual Goods
Acknowledgements This paper was prepared for the Office of the Assistant Secretary for Planning and Evaluation (ASPE), U.S. Department of Health and Human Services (HHS), by David Cutler (Harvard University), Amber Jessup (ASPE/HHS), Donald Kenkel (Cornell University), and Martha Starr (U.S. Food and Drug Administration and American University). The contributions of Dr. Cutler and Dr. Kenkel were funded through subcontracts with Mathematica Policy Research. Amber Jessup is the HHS Project Manager.
Minimizing Disclosure Risk in HHS Open Data Initiatives
Federal agencies have a long history of releasing data to the public, and they also have a legal obligation to protect the confidentiality of the individuals and organizations from which the data were collected. Federal agencies have successfully balanced these two objectives for decades. With the new emphasis on expanding public access to federal data, coupled with the increasing availability of data from other sources, federal agencies are continuing to ensure that the combination of data already available and the data they are preparing to release does not enable the identification of individuals or other entities through what has been termed the "mosaic effect." The concept of a mosaic effect is derived from the mosaic theory of intelligence gathering, in which disparate pieces of information become significant when combined with other types of information. To gain more insight into the mosaic effect and its implications for the continued release of data to the public while minimizing the risk of disclosing personal information, the Office of the Assistant Secretary for Planning and Evaluation (ASPE) in the U.S. Department of Health and Human Services (HHS) contracted with Mathematica Policy Research to convene a technical expert panel (TEP), prepare background materials, and summarize what was learned from the panel discussion and the background research in a final report.
Examination of Clinical Trial Costs and Barriers for Drug Development
Pharmaceutical companies conduct clinical trials for many reasons. The most obvious goal of clinical trials is to demonstrate safety and efficacy to gain Food and Drug Administration (FDA) approval. FDA provides guidance to developers about what constitutes acceptable clinical trials and appropriate outcomes. Improving the drug development process, especially by conducting better (meaning providing more information on safety or efficacy) and faster clinical trials, can foster innovation in medical product development. The primary purposes of this study: 1) to better understand sponsors' strategies in the design and execution of clinical trials, 2) to identify factors that may delay, hinder, or lead to unsuccessfully completed trials, and 3) to develop an operational model of clinical trial decision-making to enable examination of what-if scenarios by end-users. This study models the decision-making process for a drug sponsor as a stylized decision tree that looks at the process for formulating a clinical trial from the point of view of an expected-revenue-maximizing sponsor in the face of uncertainty (or risk). The simplified clinical decision-making model incorporates the following considerations: Therapeutic area Potential market size/revenues for the drug Clinical stage Success probabilities by clinical stage In addition to identifying the costs of the clinical trials, the following barrier mitigation strategies were analyzed: Use of electronic health records (EHR) Looser trial enrollment restrictions Simplified clinical trial protocols and reduced amendments Reduced source data verification (SDV) Wider use of mobile technologies, including electronic data capture (EDC) Use of lower-cost facilities or at-home testing Priority Review/Priority Review vouchers Improvements in FDA review process efficiency and more frequent and timely interactions with FDA Overall, the therapeutic area with the highest clinical research burden across all phases is respiratory system ($115.3 million) followed by pain and anesthesia ($105.4 million) and oncology ($78.6 million) trials. Use of lower-cost facilities/in-home testing and wider use of mobile technologies appear to be most effective in reducing costs across therapeutic areas and trial phases. Use of lower-cost facilities and/or in-home testing can reduce per-trial costs by up to $0.8 million (16 percent) in Phase 1, $4.3 million (22 percent) in Phase 2, and $9.1 million (17 percent) in Phase 3, depending on therapeutic area.
Medicare Part B Reimbursement of Prescription Drugs
This ASPE Issue Brief describes how Medicare Part B reimburses the cost of prescription drugs administered in physician offices and hospital outpatient settings. It explains the changes made to the reimbursement system under the Medicare Prescription Drug, Improvement, and Modernization Act of 2003, summarizes the direct consequences of these changes, and presents analysis of drug price variation subsequent to these changes.
Analytical Framework for Examining the Value of Antibacterial Products
Antibacterial resistance is a growing global problem. At least 2 million people in the U.S. acquire serious infections with bacteria that are resistant to one or more of antibacterial drugs designed to treat it. Despite the potential of new antibacterial products to reduce the social burden associated with resistant infections, development of antibacterials has been limited by insufficient return to capital invested in development of these products. This study, conducted by ERG develops an analytical decision-tree model framework that can be used to assess the impacts of different possible market incentives on the private and social returns to product development of new antibacterial products. ERG evaluated the private and social returns associated with the development of antibacterial drugs for acute bacterial otitis media (ABOM), acute bacterial skin and skin structure infections (ABSSSI), community acquired bacterial pneumonia (CABP) complicated intra-abdominal infections (CIAI), complicated urinary tract infections (CUTI), hospital acquired/ventilator associated bacterial pneumonia (HABP/VABP); a new vaccine effective in preventing ABOM; and a new rapid point-of-care diagnostic designed to identify MRSA. For antibacterial drugs, the average private return ranges from -$4.5 million (HABP/VABP) to $37.4 million (CABP). The average social value for the development of antibacterial drugs, however, ranges from a low of $486.6 million (ABOM) to a high of $1.217 billion (HABP/VABP). The private and social value for a new ABOM vaccine was estimated at $515.1 million and $2.281 billion, respectively. Similarly, the private and social value for new rapid point-of-care diagnostic designed to identify methicillin-resistant Staphylococcus aureus (MRSA) that can cause serious infections is estimated at $329.0 million and $22.1 billion, respectively. The gap between the current private and social values of drug development suggests that incentives are desirable to stimulate the development of drugs to treat the six indications considered. It is also important to note that simultaneous institution of conservation mechanisms, such as education campaigns to promote prudent use, and other stewardship programs, are likely to alter the incentive levels identified in this study.
Rapid Evaluation Approaches for Complex Initiatives
This paper presents a comparative framework of rapid evaluation methods for projects of three levels of complexity: quality improvement methods for simple process improvement projects; rapid cycle evaluations for complicated organizational change programs, and systems-based rapid feedback methods for large-scale systems change or population change initiatives. The paper provides an example of each type of rapid evaluation and ends with a discussion of rapid evaluation principles appropriate for any level of complexity. The comparative framework is designed as a heuristic tool rather than a prescriptive how-to manual for assigning rapid evaluation methods to different projects.
Understanding Disparities in Persons with Multiple Chronic Conditions: Research Approaches and Datasets
Understanding how to provide better care for individuals with multiple chronic conditions (MCC) is a priority for the Department of Health and Human Services. Persons with MCC represent almost one-third of the U.S. population and account for two-thirds of health care spending, yet most research on chronic conditions focuses on single diseases. In response to this growing challenge, the Department of Health and Human Services (HHS) led the development of the Strategic Framework on Multiple Chronic Conditions, a roadmap for federal MCC priorities.
Understanding the High Prevalence of Low-Prevalence Chronic Disease Combinations: Databases and Methods for Research
Final White Paper Contract # HHSP2333700IT September 20, 2013 Prepared for: James Sorace, MD, MS Michael Millman, PhD Assistant Secretary for Planning and Evaluation U.S. Department of Health & Human Services 200 Independence Ave. S.W. Washington, DC 20201
Research Addressing the HHS Strategic Framework on Multiple Chronic Conditions
Understanding how to provide better care for individuals with multiple chronic conditions (MCC) is a priority for the Department of Health and Human Services. Persons with MCC represent almost one-third of the U.S. population and account for two-thirds of health care spending, yet most research on chronic conditions focuses on single diseases. In response to this growing challenge, the Department of Health and Human Services (HHS) led the development of the Strategic Framework on Multiple Chronic Conditions, a roadmap for federal MCC priorities.
The Feasibility of Using Electronic Health Data for Research on Small Populations
Background. Many small populations have distinctive health and health care needs but have been difficult to study in survey research. Objective. This report is part of a project funded by the Assistant Secretary for Planning and Evaluation to explore the feasibility of using electronic health record (EHR) and other electronic health data for research on small populations. The first part of the report illustrates the challenges and limitations of using existing federal surveys and federal claims databases for studying small populations. The second part explores the potential of the increasingly available EHR and other existing electronic health data to complement federal data sources, as well as potential next steps to demonstrate and improve the feasibility of using EHRs for research on small populations. Methods. We use four example small populations throughout the report to illustrate a range of health and health care needs and considerations for research: Asian subpopulations; lesbian, gay, bisexual, and transgender populations; rural populations; and adolescents with autism spectrum disorders. We conducted interviews with experts on the health, health care and research needs for these small populations, as well as with experts on current efforts to use EHR and other electronic health data for research. Findings are based on these interviews, literature, and feedback from a technical expert panel. Results. Challenges to studying small populations using federal survey data include their small size, uneven distribution, and lack of standardized ways to identify population members. The growing availability of EHR and other existing health information has the potential to help overcome some of these challenges, given a number of conditions are met to be able to use these data for research. These include technical, legal, and organizational conditions that each come with their own challenges. However, these challenges are being addressed by researchers around the country who have begun to use EHR and other electronic health data for research on small populations, particularly from organized delivery systems and research networks. Potential next steps may include improving data quality through validation studies and clinician engagement, development of research methods using a combination of data sources, efforts to improve the legal framework under which this type of research is regulated, and pilot studies on specific small populations. Conclusions. There is great potential for using EHR and other existing electronic health data to study small populations. As with federal survey data, EHR data may be better suited for some types of research than others, and the context within which the data was collected must be kept in mind. Secondary use of existing electronic health data is challenging traditional views of research methods, privacy, and research collaboration. To further tap the potential use of these data for research on small populations, the Department of Health and Human Services could work with stakeholders to identify and prioritize key next steps and the potential role that public and/or private funders can play.