Many days of researching on the topic of value of health and value in health care has resulted in a much deeper understanding in both concepts and the methodologies of measuring and valuing health in various research and practice settings. Potential knowledge gaps were revealed in the studies of health outcomes, health utilities, and health preferences.
Many findings and ideas were absorbed from research papers written by key opinion leaders in the field of economics, decision science, public health, and medical science. To make matters clear, I will begin by sharing my thoughts on the topics based on the original papers, and then discuss new ideas and my research topics in the context of the existing literature.
The first paper “What is Value in Health Care” was written by professor Michael E. Porter from Harvard Business School. He is a micro-economist who is most well-known for his studies in competition and business strategy. This article is published on New England Journal of Medicine 363, no. 26 (December 23, 2010): 2477–2481. Two framework papers that develop the concepts outlined in this article, “Value in Health Care” and “Measuring Health Outcomes,” are available through the hyperlinks.
What Is Value in Health Care?
In any field, improving performance and accountability depends on having a shared goal that unites the interests and activities of all stakeholders. In health care, however, stakeholders have myriad, often conflicting goals, including access to services, profitability, high quality, cost containment, safety, convenience, patient-centeredness, and satisfaction. Lack of clarity about goals has led to divergent approaches, gaming of the system, and slow progress in performance improvement.
Comments: This article started with the need of a shared goal for health care quality improvement and system reform to be successful and then pointed out the obstacles facing health care providers, payers, and policy-makers. For any type of optimization in economics or research in general, a target variable that reflects the interests of key stakeholders is required. Finding such a target variable that is measurable and agreeable to all stakeholders is the first challenge decision-makers must face. How to reach consensus on the measuring and valuing of health and evaluate the quality of health care thereby?
Achieving high value for patients must become the overarching goal of health care delivery, with value defined as the health outcomes achieved per dollar spent.1 This goal is what matters for patients and unites the interests of all actors in the system. If value improves, patients, payers, providers, and suppliers can all benefit while the economic sustainability of the health care system increases.
Value — neither an abstract ideal nor a code word for cost reduction — should define the framework for performance improvement in health care. Rigorous, disciplined measurement and improvement of value is the best way to drive system progress. Yet value in health care remains largely unmeasured and misunderstood.
Comments: Although the measuring of value in health care appears simple by its definition — the health outcomes achieved per dollar spent. The challenge is to select a list of indicators as health outcomes for a certain medical condition and measure them precisely – to say the least.
Value should always be defined around the customer, and in a well-functioning health care system, the creation of value for patients should determine the rewards for all other actors in the system. Since value depends on results, not inputs, value in health care is measured by the outcomes achieved, not the volume of services delivered, and shifting focus from volume to value is a central challenge. Nor is value measured by the process of care used; process measurement and improvement are important tactics but are no substitutes for measuring outcomes and costs.
Since value is defined as outcomes relative to costs, it encompasses efficiency. Cost reduction without regard to the outcomes achieved is dangerous and self-defeating, leading to false “savings” and potentially limiting effective care.
Comments: To create an efficient value-based health care system, it is important to reward all players involved based on value created for patients and society at large. It is also important not to create false “savings” through cost-reduction only without quality improvement. But unfortunately, measures of cost-containment have already been implemented in many parts of the world with focus only on Cost and no means to measure and control Outcomes.
Outcomes, the numerator of the value equation, are inherently condition-specific and multidimensional. For any medical condition, no single outcome captures the results of care. Cost, the equation’s denominator, refers to the total costs of the full cycle of care for the patient’s medical condition, not the cost of individual services. To reduce cost, the best approach is often to spend more on some services to reduce the need for others.
Comments: A straightforward example is that more spending on prevention and primary care could result in bigger savings on secondary care; increased spending on patient discharge management could reduce costs from re-hospitalization.
Health care delivery involves numerous organizational units, ranging from hospitals to physicians’ practices to units providing single services, but none of these reflect the boundaries within which value is truly created. The proper unit for measuring value should encompass all services or activities that jointly determine success in meeting a set of patient needs. These needs are determined by the patient’s medical condition, defined as an interrelated set of medical circumstances that are best addressed in an integrated way. The definition of a medical condition includes the most common associated conditions — meaning that care for diabetes, for example, must integrate care for conditions such as hypertension, renal disease, retinal disease, and vascular disease and that value should be measured for everything included in that care.1
Comments: the above statement simply says all costs associated with treating a medical condition should be included in the measuring of value. The value equation may be expressed by the following for condition X.
For primary and preventive care, value should be measured for defined patient groups with similar needs. Patient populations requiring different bundles of primary and preventive care services might include, for example, healthy children, healthy adults, patients with a single chronic disease, frail elderly people, and patients with multiple chronic conditions.
Comments: The value in prevention and primary care can be summarized by the improvements in health outcomes of patient / population group divided by the total cost of services provided. For example,
Care for a medical condition (or a patient population) usually involves multiple specialties and numerous interventions. Value for the patient is created by providers’ combined efforts over the full cycle of care. The benefits of any one intervention for ultimate outcomes will depend on the effectiveness of other interventions throughout the care cycle.
Accountability for value should be shared among the providers involved. Thus, rather than “focused factories” concentrating on narrow groups of interventions, we need integrated practice units that are accountable for the total care for a medical condition and its complications.
Because care activities are interdependent, value for patients is often revealed only over time and is manifested in longer-term outcomes such as sustainable recovery, need for ongoing interventions, or occurrences of treatment-induced illnesses.2The only way to accurately measure value, then, is to track patient outcomes and costs longitudinally.
For patients with multiple medical conditions, value should be measured for each condition, with the presence of the other conditions used for risk adjustment. This approach allows for relevant comparisons among patients’ results, including comparisons of providers’ ability to care for patients with complex conditions.
Comments: Having a shared goal for health care quality improvement creates another problem in practice. How do we separate the effect of each specialty and intervention involved along the entire care cycle of treating one medical condition? How do we measure to what extent each intervention has contributed to the overall quality improvement? What about latent effects and interdependency between interventions? Would the answers above work the same when co-morbidities were introduced?
The current organizational structure and information systems of health care delivery make it challenging to measure (and deliver) value. Thus, most providers fail to do so. Providers tend to measure only what they directly control in a particular intervention and what is easily measured, rather than what matters for outcomes. For example, current measures cover a single department (too narrow to be relevant to patients) or outcomes for a whole hospital, such as infection rates (too broad to be relevant to patients). Or they measure what is billed, even though current reimbursement practices are misaligned with value. Similarly, costs are measured for departments or billing units rather than for the full care cycle over which value is determined. Faulty organizational structure also helps explain why physicians fail to accept joint responsibility for outcomes, blaming lack of control over “outside” actors involved in care (even those in the same hospital) and patients’ compliance.
Comments: As a result, failure to “segregate” the shared value by specialties and interventions, and match value with reimbursement under current health care organizational structure have limited the benefits of quality improvement initiatives on patient outcomes.
The concept of quality has itself become a source of confusion. In practice, quality usually means adherence to evidence-based guidelines, and quality measurement focuses overwhelmingly on care processes. For example, of the 78 Healthcare Effectiveness Data and Information Set (HEDIS) measures for 2010, the most widely used quality-measurement system, all but 5 are clearly process measures, and none are true outcomes.3 Process measurement, though a useful internal strategy for health care institutions, is not a substitute for measuring outcomes. In any complex system, attempting to control behavior without measuring results will limit progress to incremental improvement. There is no substitute for measuring actual outcomes, whose principal purpose is not comparing providers but enabling innovations in care. Without such a feedback loop, providers lack the requisite information for learning and improving.
Measuring, reporting, and comparing outcomes are perhaps the most important steps toward rapidly improving outcomes and making good choices about reducing costs.4 Systematic, rigorous outcome measurement remains rare, but a growing number of examples of comprehensive outcome measurement provide evidence of its feasibility and impact.
Determining the group of relevant outcomes to measure for any medical condition (or patient population in the context of primary care) should follow several principles. Outcomes should include the health circumstances most relevant to patients. They should cover both near-term and longer-term health, addressing a period long enough to encompass the ultimate results of care. And outcome measurement should include sufficient measurement of risk factors or initial conditions to allow for risk adjustment.
For any condition or population, multiple outcomes collectively define success. The complexity of medicine means that competing outcomes (e.g., near-term safety versus long-term functionality) must often be weighed against each other.
Comments: In another article posted on The Health Care Blog, Paul Keckly, Managing director of the Navigant Center for Healthcare Research and Policy Analysis in the U.S. listed a number of buzz words that often “get thrown around” but “(were) rarely defined and measured consistently”. These include “Quality”, “Outcomes”, “Cost”, “Value”, among others. To understand the meaning of Value and Quality in health care, one must start with knowing the tiers of interdependent health outcomes as shown in Figure 1 from the original text. Consider it as one of the general approaches to measure outcomes.
The outcomes for any medical condition can be arrayed in a three-tiered hierarchy, in which the top tier is generally the most important and lower-tier outcomes involve a progression of results contingent on success at the higher tiers. Each tier of the framework contains two levels, each involving one or more distinct outcome dimensions. For each dimension, success is measured with the use of one or more specific metrics.
With some conditions, such as metastatic cancers, providers may have a limited effect on survival or other Tier 1 outcomes, but they can differentiate themselves in Tiers 2 and 3 by making care more timely, reducing discomfort, and minimizing recurrence.
Each medical condition (or population of primary care patients) will have its own outcome measures. Measurement efforts should begin with at least one outcome dimension at each tier, and ideally one at each level. As experience and available data infrastructure grow, the number of dimensions (and measures) can be expanded.
Improving one outcome dimension can benefit others. For example, more timely treatment can improve recovery. However, measurement can also make explicit the tradeoffs among outcome dimensions. For example, achieving more complete recovery may require more arduous treatment or confer a higher risk of complications. Mapping these tradeoffs, and seeking ways to reduce them, is an essential part of the care-innovation process.
Two examples are given below in Figure 2 to illustrate possible outcome dimensions for breast cancer and acute knee osteoarthritis requiring knee replacement.
Comments: In practice, the most common measures of outcomes include the first tier survival/mortality, the second tier hospital length of stay, and the third tier 30-day readmission rate.