The global healthcare ecosystem is under immense pressure to deliver improved patient outcomes under increasing budget constraints. While many stakeholders struggle with similar issues, they meet those issues with differing priorities depending on where in the world one lives, and which perspective is used to view these major shifts. This has never been more apparent than during the current COVID-19 pandemic when even the most well-equipped and funded healthcare systems are teetering toward the edge as they deal with an influx of patients all at the same time.
Simultaneously, the complexity of day-to-day healthcare decision-making continues to intensify. Innovative treatments with curative potential based on precision/personalized medicine have become a reality. However, these cutting-edge therapies complicate the value-determination process of patients, payers and society, and accordingly, the healthcare budget planning process. The increasingly complex innovative treatment options, combined with the growing focus on healthcare equity and optimizing outcomes along with the encouragement for increased access to healthcare services by the World Health Organization present a challenging combination of issues for decision makers.
In order to meet challenges in each country, definitions of value will need to include multiple perspectives and local contexts, while new approaches to managing affordability should be considered, too. Additionally, a strengthening of existing approaches to healthcare evaluation and the development of new approaches that balance scientific and deliberative processes may provide both further rigor and transparency in decision-making with a focus on providing the best outcomes for the most people.
Health economics and outcomes research (HEOR) provides a framework that can clearly define healthcare issues and generate and assemble the relevant evidence to inform and guide healthcare-related decision-making in this constantly evolving space. It entails providing and evaluating a range of economics and outcomes data in health and healthcare, showing how decision alternatives impact outcomes and influence stakeholders, with the intention to guide healthcare-related investment decisions, inform behaviors of key stakeholders, evaluate outcomes and measure quality within the healthcare system. Health economics and outcomes research is the confluence of two fields that work together to provide powerful data and insights for healthcare decision makers.
Multidisciplinary HEOR experts understand that outcomes research combined with health economics provides vital information and tools to healthcare decision makers from the intervention to the healthcare system level. While both health economics and outcomes research can be performed in isolation, the synergy of combining the right data (outcomes research) with thoughtful (health) economic analyses based on multiple stakeholder perspectives ensures that even complex healthcare questions can be evaluated rationally.
Value-based healthcare evaluation—including value-based insurance design and pricing—learning healthcare systems, and an increased emphasis on placing patients at the center of healthcare decisions are putting more focus on the confluence of HEOR as a key evidence-generation player.
Paying for value requires first defining what value is and to whom that value matters (what perspective), measuring the care delivered in real time and feeding that information back into the system so adjustments can be made to incentivize and reimburse high-value care appropriately. Methods developed over the past three decades compare the clinical, economic and humanistic impact of alternative treatments and provide the basis for addressing evolving challenges, including personalized medicine, curative therapies and aging populations. New methods will need to take a holistic view in terms of time horizon, societal benefit and opportunity cost. Health economics and outcomes research experts and methods are often the vanguard of healthcare evaluations with dynamic, innovative methods to address the constantly changing environment.
The rise of big data and a focus on artificial intelligence mean that healthcare data are becoming more abundant and diverse, useful and able to impact healthcare decisions in real time. The promise and power of healthcare data can be realized with real-time insights to drive change in treatment, measure quality and enable efficient and cost-effective healthcare delivery. However, much of the data content is in unstructured form (e.g., physician notes in electronic medical records), and natural language processing has yet to be widely applied and effective at extracting content. Expertise in deep-learning methods as well as knowledge of traditional outcomes research methods and good practices will be key to delivering on the promise of big data to improve health outcomes. Data scientists are often collaborators with HEOR experts, and many of the methods cross over with actuarial science, biostatistics and data science, psychology and economic methods. Many of the good practices in these and other areas of data analytics are informed by good practices that were developed in the field.
Genetic data, including data from companion diagnostics, and the need for interoperability to link disparate data sets together, will exponentially increase the size of data sets and the visualization to detect and analyze trends. The proliferating digitization of healthcare data and algorithms that can rapidly discover—virtually at the time of collection—actionable trends, while measuring outcomes in meaningful ways, will increase the applicability and impact of HEOR methods. This significant trend will allow learning healthcare systems to come to the forefront.
The health economics and outcomes research framework can also help ensure more systematic yet customizable approaches to healthcare evaluation in different parts of the world. There is massive variation in decision-making capacity across regions highlighted by the backdrop of fiscal challenges in the low- and middle-income countries. The regions often most in need of decision-making tools have limited resources or capacity to develop and execute these types of analyses. These regions require revision of the mindset when developing optics, methods and communications strategies regarding evidence-based decision-making, for example, by applying the transparency, accountability, participation, integrity, and capacity framework.
The ability to make informed decisions closer to real time is becoming paramount, as we see in the experience of the pandemic. Currently we can only guess about which treatments for COVID may work, how many people are actually infected, and whether sheltering in place is worth the devastating cost to our world economy. All of these data points and more are required to make the best-informed decisions to maximize health and consequent economic outcomes.
Currently we have access to the greatest world-wide natural experiment in comparative public health systems. By working with leaders in the field, we can ensure that we understand how the healthcare system can best serve the patient/consumer, constituent populations, society and the world at large, to improve healthcare decisions and outcomes globally, in both the current environment and beyond.
The views and opinions expressed in this content or by commenters are those of the author and do not necessarily reflect the official policy or position of HIMSS or its affiliates.
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