The goal of population health management is to use data-driven, patient-centric solutions to improve community health and patient satisfaction while reducing costs.
But the value generated by PHM solutions is both qualitative and quantitative, making return on investment difficult to determine. Consequently, when creating a strategy for PHM, health care leaders face challenges in identifying the right mix of services that best addresses the needs of their communities.
To aid in strategy development, organizations should understand the types of PHM solutions available. How and which options will be put in place, how their value can be quantified and how a program may be affected by future developments should be evaluated in the context of the organization’s overall strategic objectives. I have outlined six types of PHM strategies:
Education is a key component of many PHM strategies. Delivering information during clinical sessions is a cornerstone of the patient-provider experience. Education encourages patients to be more active participants in their health care, which improves outcomes. Patient satisfaction can also be improved. Since patient satisfaction metrics will soon be a component of reimbursement, health care organizations have even more incentive to use education to develop positive, fruitful relationships with the members of their community.
Quantifying education’s direct impact on health improvement, however, is difficult. Organizations may be challenged to justify directing significant resources to educational programs. Fortunately, funding options for education may be on the upswing. For instance, Medicare is now reimbursing providers for the time they spend discussing end-of-life decisions with patients. Because studies suggest that low education levels have a direct relationship to poorer health outcomes, health care organizations should be strong advocates for, and potentially recipients of, funding for any programs that seek to improve a community’s level of education.
Preventive health management measures are discrete, low-cost activities that directly improve community health. Vaccinations are a prime example. Vaccination figures can be tracked with a high degree of accuracy, and vaccination programs have a strong value proposition. Nonetheless, recent concerns about the safety of some vaccinations, particularly in relation to autism, make continued education necessary.
Other preventive measures include the use of over-the-counter medications that have a proven track record of improving health outcomes. Examples include the ingestion of calcium supplements to reduce risk of osteoporosis and daily doses of aspirin to help prevent heart disease. Unfortunately, adherence to medication regimens is extremely difficult to track, which makes it hard to quantify their value. Again, reinforcement of medication recommendations through education can improve their effectiveness.
Predictive programs use big data analytics to identify health trends and at-risk populations. Analytics can help determine which sector of a community is predisposed to a certain disease and can track patient activities and environmental circumstances that may be contributing factors. However, if not implemented effectively, big data analytics can be a costly investment that does not provide the incremental value needed to develop effective PHM programs. Big data must be used to create actionable initiatives, not just sophisticated reporting.
Sometimes bigger is not better. Most health care organizations have strong historical ties to their communities and possess a solid understanding of local health care issues. In these cases, big data analytics can work if it is deployed on a directed scale to drill down into one or two areas of concern. This approach may be a more cost-effective way to use powerful tools to generate the best results.
Diagnostic measures are used to identify disease early enough to enable effective treatment. Diagnostic mammographies and colonoscopies fall into this category. Diagnostic testing is moderately expensive because many tests may be done on an individual before identifying any sign of disease. In fact, some patients undergo a lifetime of tests and never develop a disease. Organizations must remember that the return-on-investment calculation for diagnostic testing includes all tests, whether they identify a patient’s disease and prevent its further escalation or not.
Given the shift from fee-for-service toward outcomes-based reimbursement, some diagnostic tests may not be covered as part of value-based care or bundled payment arrangements. As a result, organizations may see a reduction in testing. Additionally, research has continued to refine the rates of recommended diagnostic testing. Recently, the American Cancer Society reduced its recommended screening rates for mammographies. While reductions in unnecessary testing can save resources and reduce patient inconvenience, organizations should ensure that the right levels of testing are in place to maximize disease prevention.
Interventional programs are high-cost initiatives that can generate positive, quantifiable rewards. A typical interventional program will use case managers, clinicians and family members to proactively manage a group of patients with similar risk factors for disease. For example, tracking water retention rates for patients with a high risk of heart attack can help prevent a life-threatening episode or can quickly mobilize treatment protocols should one occur. While the benefits of interventional programs are great, the cost to implement them must be calculated using a methodology similar to that employed for diagnostic programs. Costs for managing all patients, whether they experience an episode or not, must be included in the evaluation.
Fortunately, technological advances are creating more effective and less expensive ways for patients and caregivers to communicate: biometric monitoring devices, apps for patient engagement and telemedicine. Using these new technologies may help significantly lower the cost of interventional programs.
Advances in gene mapping are enabling scientists and clinicians to identify an individual’s predisposition for certain diseases. Programs can be developed to modify patient behavior, expedite early diagnosis and take proactive measures to reduce overall risk. One extreme example of how genetic testing can affect patient behavior relates to patients who test positive for the breast cancer susceptibility gene. Concern over the development of an early and aggressive form of breast cancer motivates some of these patients to undergo voluntary double mastectomies.
While some consider the knowledge gleaned from genetic testing to be exciting and revelatory, others consider it unnecessary and invasive. Some have concerns that the data collected from these tests may result in the recommendation of overly aggressive clinical regimes. Nonetheless, acceptance of genetic testing will likely increase as younger patients, many of whom are comfortable sharing personal information, participate in programs. In all cases, practitioners should employ the highest levels of ethical behavior, respect and compassion when deciding how this information may be collected, used and stored.
Population health management programs have the potential to bring positive change to the health care field. With thoughtful, strategic investments, organizations can channel their resources to programs that engage patients and improve outcomes in their communities.
Janis Powers, MBA, M.Arch., is the director of Powers Enterprises LLC in Austin, Texas.