Population Health Management: It Takes a Village

In the early 1970s, David Bowie released the song Changes telling the world to “turn and face the strange.” Easier said than done. We tend to like established routines. Yet, anyone who has been in the practice of medicine since the turn of the millennium has experienced ongoing, rapid change in the way care is delivered, reimbursed, and measured. Paper prescriptions to ePrescribing. Paper charts to eCharts. ICD-9 to ICD-10. Fee schedules to alternative payment models. It’s overwhelming.

Population health management (PHM) is one such area of change that promises to improve the health status of patients and communities. PHM can be traced as far back as World War II when Jerry Morris and Richard Titmuss analyzed variations of individual illnesses in relation to changing social situations (e.g., unemployment).[1] PHM has come a long way since then. As electronic health record (EHR) adoption accelerated under the CMS “Meaningful Use” incentive program, clinicians were challenged to think beyond the patient standing in front of them to management of all active patients for guideline adherence.

Twenty-first century technology is now beginning to blend payment with measureable health value management of patient populations, requiring pro-active PHM. More and more, alternative payment models (APMs) are requiring providers to think of PHM beyond their individual patient populations to community-wide consumers of their services; achieving an improved health status across the care continuum. Such advanced PHM requires a technically-enabled, longitudinal view of all patients for whom the community of providers is accountable. In other words, it takes a village.

Population Health Management (PHM) 2.0

PHM 2.0 aligns with the emerging risk-bearing reimbursement arrangements. These payment models are being sought by healthcare purchasers including payers, employers, and government entities such as CMS and state Medicaid agencies. Historically, risk has been born by these purchasers under a fee-for service (FFS) payment model with these payers focused on cost containment and management of healthcare resources. In contrast, advanced APMs share or shift risk to the provider community. APMs swing the purchaser’s focus to health management and outcomes-based measurement where calculated health value management determines provider revenue.

Health value is measured using what is known as the “Triple Aim” of lower costs, better care, and better delivery. CMS gauges qualitative and quantitative achievement of these 3 guiding principles using 6 national quality strategy domains, as follows:

Triple Aim, CMS National Quality Stategy Domain

Under APMs, coverage and cost are no longer the sole considerations to reimbursement. Community-based APMs will almost always link health value management back to some measure of the triple aim with a direct correlation between accomplishments and payment. Therefore, PHM of your assigned patients across the care continuum becomes an essential component to community-based risk-bearing economics.

Building Strong PHM Programs

PHM 2.0 seeks to shift care from episodic, reactive delivery to prescriptive, pro-active care. To succeed, there are three critical objectives to your population health management program: maintaining good health, managing chronic disease, and reducing health risk. Prevention and wellness are often achieved through process-oriented measures such as annual wellness visits, flu shots, cancer screenings, obesity counseling, etc. Adding a dedicated chronic disease management program that incorporates risk stratification and comorbid conditions can lead to further reduction in risk and long-term success.

Advanced APMs will pay providers a set amount for contractually defined services over an identified time period. This is known as population-based payment (PBP). Examples of PBP arrangements include accountable care organizations (ACO) and ACO look-alikes, bundled payments and other episode-based models, as well as condition-based and global capitation. Each of these programs ties payment to or adjusts payment based upon quality outcomes. PBP programs require strong PHM. This can be better realized by answering 4 questions with data-enabled information to obtain a full understanding of your plan’s patient panel for purposes of proactive management.

Question 1: Who are your patients?  Under risk-bearing payment arrangements, you must first know who is being attributed to your provider “village.” Attribution is the method used by the purchaser to determine provider responsibility for the costs and care of patients. The primary methods of attribution are patient self-attestation, claims, and plan assignment. The primary care provider (PCP) plays a pivotal role in patient attribution.

Patient self-attestation is accomplished during plan enrollment when a beneficiary selects a PCP. However, if the plan design is open access, payers may use claims to attribute members to a provider in the following order of priority:

  1. Prospective attribution:
    • Well visit in the previous 12 months; then look back 24 months
    • Medical E&M code in the previous 12 months; then look back 24 months
    • Prescription in the previous 12 months; then look back 24 months
    • Other medical procedures (PCP) in the previous 12 months; then look back 24 months
    • Selected specialists seen in the previous 24 months
  2. Remainder is unattributed and often assigned using a retrospective or “performance year” attribution methodology based on a patient’s utilization of services.

Some purchasers attributed all patients on a retrospective basis, while others – including CMS – use a hybrid method that starts with prospective assignment and ends with a final retrospective reconciliation at the end of a performance year.

Question 2: What is the current status of your patient population?  Once you understand the patients for whom you are accountable, you need to benchmark financial and clinical patient status. Financial benchmarking may be done using a total spend per beneficiary based on the previous year utilization. This financial benchmarking is commonly used in shared-savings accountable care APMs.

Clinical benchmarking is best achieved using health assessment. Health assessment can be done by analyzing claims, prescription and other payer-oriented data, but is greatly enhanced by conducting a current patient health status “checkup.” Often termed “health risk assessment,” a brief questionnaire of standardized queries is used to identify health status and help set care goals. Using structured responses can support your PHM program through advanced data analytics.

Question 3: Where do your patients fall when risk stratified?  Risk stratification provides a clearer picture on the health status for your patient population; and, adequacy of your PBP payment to care for these patients. Information obtained from a health risk assessment can help you better understand patient risk status so that you can prepare for the disease burden of your attributed patients, direct resources to close care gaps, and target improvements in care and health.

Stratification is usually done with risk scoring. Some patients will score as low or no risk, while others may be moderate or high risk. Leveraging stratification analytics and statistical modeling through only claims data only is a good start and commonly done by payers. Aligning predictive analytics available by using EHR data can help your provider community set population health goals. Moreover, it can identify those patients that need timely intervention.

Today, longitudinal views of patients typically leverage claims-related data. Precision of such modeling and analytics can be further enhanced by incorporating additional data such as found in electronic health record (EHR) data, wearables, and mobile device applications. Yet, market penetration of clinical data integration is around 5-20%, making it early in maturity.[2] A recent study compared population-based risk stratification modeling using data from claims vs. outpatient EHRs and found promising results, particularly in explaining lower variation in utilization-based outcomes.[3] Long-term, benefits from blend administrative claims and EHR data will lead to more accurate, actionable data.

Question 4: How will you intervene?  The intensity of intervention should align with the patient’s risk score. The higher the risk, the more intense the intervention effort. Yet, a well-rounded intervention program will touch each of the community’s patients at some level.

Based upon risk stratification, the intensity and form of intervention can be appropriately used. For example, low risk patients may be managed “on-demand” using nurse call lines; whereas, patients with well controlled diabetes may be managed through a standard disease management program. Lifestyle management may touch all patients using seat belt campaigns or smoking cessation programs. High risk interventions might work to manage those patients in jeopardy of developing conditions or needing care that could lead to devastating costs such as transplants or cancer.

In Summary

Health plans have been in the community-based risk management business for decades. As the payment paradigm moves risk to provider communities, the role of community-wide population health management becomes more essential to providers. This will be effective, but only if a strong PHM program is put in place. In so doing, providers are positioned to truly impact the health status of the very neighborhoods in which they practice.

[1] Szreter S. The Population Health Approach in Historical Perspective. American Journal of Public Health. 2003; 93(3):421-431.

[2] Holmes, Cribbs, Cole, Gartner, “Hype Cycle for U.S. Healthcare Payers, 2017,” July 14, 2017.

[3] Cite JHU article

Adele Allison
Director of Provider Innovation Strategies
DST Health Solutions, LLC
Birmingham, AL

Published on 10/30/17

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