Sanjula Jain, PhD

Sanjula Jain, PhD, is a health economist and Adjunct Assistant Professor at The Johns Hopkins University School of Medicine.

Much of the national conversation in recent months has focused on the need to quickly contain and heal the US health economy in response to the coronavirus disease 2019 (COVID-19) crisis. The incoming Biden administration and 117th Congress will be challenged to move beyond the crisis, which will require a laser focus on getting as many Americans vaccinated as quickly as possible and funding a multi-trillion-dollar economic relief package.

The shift from crisis response to durable recovery will emphasize the intersectional forces we contend our national leaders must manage in the years and decade ahead. While some of the intersectional forces of change playing out in US health care are in fact cyclical, we believe that much of what is unfolding is secular. As with any significant crisis, the first-order impact of COVID-19 has been an acceleration of these secular forces already underway.

Digitization, Democratic Reform, and Demographics

Over the last decade, 3 secular forces of change have been in play: digitization, democratic reform, and demographics. We believe they will cause the decade to be viewed as one of the most consequential for US health care in the post–World War II era.

As the Great Recession unfolded in the late 2000s and early 2010s, the Obama-era federal stimulus package included tens of billions of dollars for the 

. The Meaningful Use regulations it spawned drove pervasive electronic health record (EHR) adoption. The second- and third-order impacts of that digitization have been profound. And yet, as COVID-19 unfolded, our information technology systems were a complicated patchwork that left public health officials without the data needed to match critical provider supply with shifting pandemic demand.

The Democratic-led Affordable Care Act was a second force of change. Among its key provisions, the legislation extended Medicaid to nonelderly adults with incomes up to 138% of the federal poverty line. As unemployment exploded in the first half of 2020, 

. States like Oklahoma have already expanded Medicaid, with others inching toward expansion, creating a de facto single-payer framework for all 50 states. The pandemic exposed the importance of ensuring that our health and care infrastructure extends to Americans in every zip code from the urban core to rural communities.

Third, in 2011, the first Baby Boomers turned 65, making 10,000 seniors eligible for Medicare each day. The demographic shift means the number of Medicare enrollees will double in the next 20 years. COVID-19 has been particularly tough on the elderly and reinforced the need for us to think about new technologies like teleservices as a more meaningful part of the care continuum.

In the context of these major secular forces of change, we believe COVID-19 exposed a set of  new questions that must be part of the ongoing national conversation around how US health care should operate in emergent and nonemergent times alike. We believe the transition to the 117th Congress under the new Biden administration is the right time to frame them.

1. How do we build flex capacity into our payment models?

Prior to COVID-19, the federal government had been incentivizing health systems to cut down on more expensive acute care, primarily through programs designed to limit readmissions to the hospital. Thus began the deconstruction of the traditional brick-and-mortal model of care delivery.

The transition away from an asset-intense model was challenged when the influx of patients with COVID-19 exceeded available beds. The major hot spots had no choice but to immediately scale up both their physical and virtual treatment capacity. Illustratively, NewYork-Presbyterian at the outbreak epicenter expanded from 

 to accommodate the surge of COVID-19 patients not covered by current payment incentives. Yet, it was clear that in addition to flexing the use of physical capacity, the home as a venue was trumpeted as nonemergent patients preferred the comfort of home to exposure risk in a health facility. Although providers were initially 

 adoption to meet demand, CMS eventually removed financial barriers through 

 incentivizing expanded use of digital modalities.

Broad-based change in the payment model will be required to accommodate flexibility in acute supply during times of crisis. The current model, which is designed to limit physical capacity, should allow providers to scale care delivery mechanisms up and down to include both bed supply and digital platforms. But how do you build an organization that has a level of resiliency and flexibility because of the unknowns associated with it? Ultimately, developing a core competency in quickly flexing our care delivery infrastructure will need to be part of how we define future payment models.

2. How do we achieve a reliable health care supply chain?

The sophistication of the US health care supply chain has long lagged behind other industries. With incentives to cut costs, most essential supplies from pharmaceuticals to personal protective equipment have increasingly been produced outside the United States to secure the least expensive option. COVID-19 brought the nation’s supply chain to its breaking point, both in terms of quality and availability, with supplies critical to the health of US citizens fully dependent on other countries with their own outbreaks to manage.

In effort to increase reliability, health system CEOs agree that we have no choice but to minimize our dependency on a foreign supply chain. If we are going to be ready for the next hurricane or pandemic, we have to make tradeoffs on price to balance “just in time” inventory and increase domestic production.

Going forward, we will need to build a reliable supply chain that can support a national infrastructure for healthcare. Similar to how 9/11 prompted the government to define and prioritize critical areas underlying US safety, we will need to adequately invest in and protect the life-saving supplies deemed critical to the health and well-being of US citizens. To ensure reliability, we must consider health care as part of national security and build strategies comparable to how we manage our national defense assets.

3. How do we leverage real-time data infrastructure?

Some 10 years after the passage of the HITECH Act, the pervasiveness of readily available and increasingly precise clinical data and analytical tools such as artificial intelligence are changing the face of medicine. Even well before COVID-19, the sophistication of digitized information was beginning to provide greater depth of understanding and treatment of diseases specific to individual patients.

But as we saw from the onset of COVID-19, we did not have time to pull disparate databases together to examine the effects of the disease on the individual. “Real-time” or concurrent data are necessary to monitor a patient when the course of the disease is uncertain. With notable regional variation in spread of the disease, more robust national data architecture would have been invaluable in developing more precise projections and response strategies.

As clinical data become more useful, health systems, which are frequently the central collection and processing entity, see the data as a core asset with value to improve diagnosis and treatment for an individual. Hand in hand with value to the individual is the value of aggregated data to not only the health system but also leaders across the nation. The establishment of a national data infrastructure holds the promise to help track spread and surge, understand underlying chronic conditions, and advance new treatment protocols to more effectively manage health at the population level.

The use of personal health information as a critical component of national surveillance will dually magnify the role of clinical data as a national security asset and individual concerns for data privacy. This balance will be at the heart of political debate, health policy development, and provider engagement over the decade of the 2020s.

As we headed into the 2020 election season, 

that the third year of the Trump presidency had “seen the largest degree of political polarization in any presidential year. Eighty-two percentage points separated Republicans' (89%) and Democrats' (7%) average job approval ratings of President Donald Trump.” As COVID-19 has surged across the nation, this gap has been evident in public sentiment on topics from crisis response to economic reopening.

The strategic opportunity sitting with the new Biden administration is building a shared factual view of how US health care must operate in times of crisis and calm alike. COVID-19 not only accelerated a set of secular forces already playing out in US health care, but it also exposed critical gaps that must be more fully addressed by the next round of nonpartisan reform.

We need a true “system” of health and care. It must be able to provide flex capacity in time of pandemic response, be supported by a domestic supply chain that can provide front-line caregivers the resources they need to safely care for critically ill patients, and leverage the promise of digitization to allow leaders to effectively manage supply and demand as hotspots emerge across our large and diverse country.

Speed of decision-making must be part of system-level thinking around these 3 areas. Whereas decision velocity in Washington slowed over the course of the 2010s, the 2020s demand a different model. The best leaders understand the intersectional forces of change that are unfolding and craft holistic system-level strategies to influence them. They have a compelling vision for the future state of the health economy that looks far different than today. They have the ability to build the coalitions required to move us toward it.

Articles

The incoming Biden administration will be challenged to address flex capacity, the supply chain, and real-time data as we transition from coronavirus disease 2019 (COVID-19) response to durable recovery.  

Contributor: 3 Key Questions for the Biden Administration and the 117th Congress Coming Out of the COVID-19 Crisis

Medicare’s Merit-based Incentive Payment System and other value-based payment systems hold providers accountable for population-level measures that are driven by many factors, including those beyond the providers’ direct control (eg, psychosocial stressors, environmental hazards). In this commentary, we identify and illustrate this misalignment of accountability and capability at the individual clinician level and at the provider organization level, which can hinder population health improvement. We also envision the roles of administrators and frontline clinicians amid a new culture of shared accountability and rigorous evaluation, with the potential to accelerate advances in population health care delivery.

The American Journal of Accountable Care. 2019;7(1):28-30

The healthcare system’s ongoing transition from fragmented care and volume-based payment toward coordinated population healthcare and value-based payment has been slow. This transition has been hampered by the misalignment of measurement and accountability systems with population health care delivery goals. The Institute of Medicine report 

For the Public’s Health: The Role of Measurement in Action and Accountability

 articulated that a well-functioning accountability system for improving health must identify bodies “with a clear charge to accomplish particular steps toward health goals.”

 Current efforts to improve population health have been stymied significantly because it is not clear which entities—within the healthcare system or across the broader public health system&mdash;have such a charge and in what contexts.

When identifying where accountability for achieving population health goals should lie, a natural first choice is the individual clinician, given the importance of physicians, nurse practitioners, and other frontline clinicians in determining patients’ care pathways. Consequently, current value-based payment systems often integrate performance measures that hold the individual clinician accountable for patient outcomes. This is problematic, however, as these outcomes are often affected by numerous factors, many of which are beyond the clinician’s direct control.

To illustrate, Medicare’s Merit-based Incentive Payment System (MIPS) holds clinicians accountable for care practices such as major depressive disorder prevention and antidepressant medication management. Clinicians may reasonably be expected to screen patients for depression and administer Patient Health Questionnaire-9 (PHQ-9) evaluations to help reduce the percentage of patients remaining on antidepressant medications after a designated time period. However, the population-level impact of these efforts is likely to be small, whereas the potential impact could be much greater with better-coordinated, collective efforts—those integrating both medical and nonmedical actors&mdash;to manage the underlying psychosocial stressors and complex, multifactorial processes that drive depressive symptoms.

(PHM) embodies the vision of achieving population health improvement by these means. Coordinated, multifaceted PHM interventions may include established models of chronic disease prevention and care management, as well as new collaboration with social services, improving the physical environment and safety, engaging in community education and outreach, and addressing food insecurity and other sequelae of poverty. Significant economies of scale are needed to efficiently perform most PHM interventions, such as geographic analysis of community-level health hazards and other sophisticated measurement and reporting functions,

 which require substantial investments in information technology and big data analytics. Moreover, it is beyond the training of most clinicians to prioritize, coordinate, and execute such multidimensional initiatives effectively. For both reasons, such outcomes-based MIPS measures place too much accountability on the individual clinician and thus may be ineffective in improving population health.

This misalignment is increasingly recognized among thought leaders, payers, and policy makers, as reflected in proposed redesigns of MIPS

 and the growing interest in new value-based payment models such as Accountable Health Communities, which emphasize managing attributed populations collectively.

 Provider organizations have begun to demonstrate how they may leverage their greater economies of scale to advance PHM goals, including through hospital leadership and shared services agreements among groups of smaller organizations.

Still, skeptics worry that provider organizations are just as unprepared as individual clinicians for the challenges of implementing effective PHM interventions. Doing so may require undertaking tasks far removed from traditional modes of medical care, such as forging and maintaining relationships with social services agencies and other public health institutions across communities. Indeed, few healthcare provider organizations—let alone individual providers&mdash;have demonstrated the ability to undertake them effectively.

Provider organizations have also experienced challenges effectively coordinating PHM interventions internally. The system-level measures used to determine payments within value-based contracts (eg, use of certified electronic health record technology, diabetes screening rate) hinge on the actions of the system’s individual clinicians. For example, if an organization leverages its big data capabilities to microtarget screening interventions to a high-risk patient subgroup, the individual clinician must still identify the patient in his or her exam room as high risk and perform the screening. Yet, rarely have provider organizations’ leadership effectively articulated how their clinician employees benefit when the organization’s PHM initiatives are executed faithfully or made substantial efforts to cultivate buy-in and engender a culture of collaboration among clinicians and staff in support of PHM. Perhaps more importantly, provider organizations’ leaders typically have not passed along to or shared with clinician employees the financial incentives the organization faces under value-based contracts, nor have they provided organizational or financial guardrails to ease clinician employees’ transitions into population health—oriented delivery and payment models.

 Although provider organizations are indeed starting to build in PHM-oriented performance bonuses for their clinicians, the predominant compensation structures remain salary based or productivity driven, unlinked to population health improvement. Thus, although payment systems mislay accountability when focused on the individual clinician, it is unclear whether population health will improve when accountability for PHM rests with the provider organization instead.

Individual clinicians and provider organizations each have important roles to play in improving population health care delivery: principally, in executing the organization’s PHM initiatives and in formulating and resourcing these initiatives, respectively. It is incumbent on administrators and frontline clinicians alike to understand these roles and coordinate the organization’s care delivery priorities together.

 Internally, such coordination must include, for employed clinicians, negotiated internal compensation models that align with the terms of the organization’s various payer contracts. Externally, provider organizations must coordinate with payers to negotiate payment contract incentives that can be easily passed along to or shared with their employed clinicians. Respecifying MIPS quality measures so that they focus on individual clinicians’ activities (eg, administering PHQ-9 evaluations) rather than downstream outcomes (eg, antidepressant medication management) represents one federal opportunity to foster providers’ internal coordination in this way. Provider organizations may also work with local payers to facilitate partnership agreements between network providers and entities (eg, social services) that can enhance their PHM initiatives’ capabilities and scale. Importantly, these arrangements must evolve over time with the community’s PHM efforts and as all involved parties identify opportunities to improve their effectiveness.

Robust scientific evaluations and evidence-building efforts are critical for overcoming barriers to improving PHM efforts, especially considering that it remains unknown what the most effective models of delivering population health are and how to apportion accountability for them. Given the multifaceted nature of the psychosocial determinants of population health, in most communities it may be critical that payers and other organizations traditionally ancillary to the healthcare industry (eg, employers, municipal health departments) participate in community-level deliberations to define the community’s population health goals, formulate plans and economic incentives for achieving them, and evaluate efforts. MIPS could foster this by modifying its Improvement Activities list to include, among other potential options, substantial (eg, 25%) representation from these community entities on the provider organization’s board or documentation of referrals and coordinated handoffs of underserved patients to local social services programs for nutrition or housing support. Moreover, each community must conduct its own evaluations, as coordinated PHM is a local endeavor. For instance, the set of organizations needed at the table to support achieving a particular population health goal may vary with the community’s sociodemographic and environmental characteristics and with the evolution of community organizations as they take on new roles and build up the “capacity to undertake the required activities”

Throughout the course of a community’s innovation, intervention, evaluation, and evolution, effective PHM will accelerate when the coordinated networks of the community’s partner organizations expand and each partner is held accountable more precisely for achieving what it is capable of achieving in the interest of improving the population’s health. MIPS and other value-based payment systems will continue to significantly inform how shared accountability is defined, incentivized, and implemented in many communities. It is important that they do so deliberately, for until shared accountability is realized, our efforts to realize meaningful gains in population health will continue to lag.

 Rollins School of Public Health, Emory University (ASW), Atlanta, GA; The Health Management Academy (SJ), Washington, DC.

 Dr Wilk is employed by Emory University, which engages in population health management efforts through Emory Healthcare, and owns stock as a minority shareholder in United Health Group. Dr Jain is employed by The Health Management Academy, which is a network of delivery systems.

 Concept and design (ASW, SJ); analysis and interpretation of data (SJ); drafting of the manuscript (ASW, SJ); critical revision of the manuscript for important intellectual content (ASW, SJ); and administrative, technical, or logistic support (ASW, SJ).

 Adam S. Wilk, PhD, Rollins School of Public Health, Emory University, 1518 Clifton Rd, Atlanta, GA 30322. Email: adam.s.wilk@emory.edu.

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Current population health efforts have been hampered by the misalignment of accountability. Thus, population health management will improve when shared accountability among stakeholders is achieved.

Effective Population Health Care Delivery Under Medicare’s Merit-based Incentive Payment System: Realigning Accountability With Capability

While most payers have been slow to embrace models that would incentivize value-based care delivery, providers have a unique opportunity to take the lead in this endeavor.&ensp;We examine best practices to develop a Population Health Care Delivery Model (PHCDM) to guide delivery systems as they design and pilot population health programs across the continuum of patient care and to facilitate their coordination with individual clinicians.

 A systematic review of observational studies and health system case studies was conducted.&ensp;We examined the effectiveness of population health—oriented programs and specific quality improvement initiatives in improving the health outcomes of patient populations across the continuum of care. Our assessment was primarily focused on the structural and design features of successful programs.

We find that population health improvement is a result of (1) prevention and well care and (2) disease management initiatives that are both patient-centered and population-oriented in structure. We identified differences in care delivery objectives as the severity of disease increases across the patient care continuum. The corresponding PHCDM presents a framework for providers to systematically pilot and evaluate population healthcare programs.

The delivery system—clinician partnership is essential to coordinating evidence-based practices across the care continuum and, as a result, strengthening relationships with payers to further incentivize population healthcare delivery.

There is growing recognition that paying for the delivery of high-quality, efficient healthcare is necessary to improve population health. Such value-based payment systems place a growing amount of revenue at risk for clinicians, although most continue to practice in care models developed under fee-for-service incentives. This asymmetry has raised concerns among clinicians about these systems’ implications for patient care, reporting requirements, and payment levels.

 The concurrent shift toward increased employment of physicians in large delivery systems

 may reflect, in part, clinicians looking to their delivery systems to help navigate the complexity of value-based payment systems. 

At the core of these emerging payment models is the expectation that care providers must be accountable for the health outcomes of entire patient populations across the continuum of care. Delivery systems must be reoriented to achieve these aims. At times, this work will be inexact, challenging, and even conflicted when other health system stakeholders’ responses to the system’s new population health objectives are asynchronous or askew with the providers’ efforts. Alternately, the pace of advancement toward population health management will accelerate if the delivery system’s efforts are supported by robust payment systems that are developed in collaboration with payers and reward incremental progress toward value-based care objectives. Although most payers have been slow to fully embrace alternative payment models (APMs) that would strongly incentivize value-based care delivery and promote population health, providers have a unique opportunity to take the lead in this endeavor.

Delivery systems are uniquely positioned both to help clinicians adapt to new payment regimes and to lead the way in developing and evaluating new models of population healthcare delivery. Delivery systems can play key roles in innovation, infrastructure investment, measurement, and contracting, as well as provide strategic direction and leadership in this enterprise. However, a delivery system’s investments and reorientation toward system-level functions

 could lead to diminished emphasis on patient-centeredness in care at the individual level. To ensure that patient care is not compromised, the delivery system must engage and collaborate with all stakeholders, particularly clinicians, and reflect their priorities in their new population healthcare delivery models.

 This system—clinician partnership is essential to coordinating evidence-based practices across all silos of the care continuum and strengthening relationships with payers to incentivize population healthcare delivery.

Balancing Population-Centered Care and Patient-Centered Care

It is a long-established ethic of the individual clinician to focus intently and autonomously on the individual patient in the exam room and deliver optimal patient-centered care in accordance with the patient’s preferences and needs.

 Likewise, each delivery system’s approach to delivering high-value population health must be unique to the needs of the population it serves. Where these approaches are successful, it will be in no small part because individual clinicians are effective in their new roles as executors of the delivery system’s population health initiatives and resources. However, individual clinicians may view these tasks as in conflict with their traditional patient-centered care delivery approaches, occupying time and resources that should be devoted to the patient’s immediate needs in the exam room. Hence, clinicians depend on the delivery system to recognize how they are being pulled in these 2 different directions and set reasonable expectations as they grow accustomed to their dual roles. Balancing these expectations requires the system to be diligent in monitoring clinician deviations from evidence-based recommended care practices and distinguish systematically between appropriate variation (eg, due to high-acuity complex patient needs) and avoidable variation in practice.

Ideally, clinicians’ care delivery models and the delivery system’s strategy are well-coordinated to ensure that the patient population receives efficient population-centered care while individual patients continue to receive effective patient-centered care. In this paper, we present a new framework, the Population Health Care Delivery Model (PHCDM) (

), to guide delivery systems as they design, pilot, and implement population health programs across the continuum of patient care and to facilitate their coordination with individual clinicians. The care continuum, as patients experience it, is useful for framing the objectives of a population health—oriented system in a way that recognizes the individual clinician’s autonomy and patient-centered perspective. In the following sections, we explain the aspirational goals of the PHCDM, rather than specific recommended tasks, recognizing that the effective delivery of population health requires nuanced approaches tailored to the needs of different patient populations. We also delineate new terms of collaboration between the delivery system and the front-line clinician within this framework.

As the delivery system embarks upon population health management, it must first obtain complete and timely information about the population’s health needs and preferences. To do this, the system must work with clinicians, public health agencies, and community organizations to acquire and review disparate data sources. These sources may include risk assessments, surveys, electronic health records (EHRs), and claims data, which can be used to conduct integrated data analyses to classify (1) populations with elevated risks of adverse outcomes and (2) populations for whom population health programs have the greatest potential for improving outcomes. Performing this analytic exercise affords the delivery system the capacity to provide clinicians with key information for realigning and implementing targeted evidence-based initiatives. This data platform is crucial for measuring progress and conducting self-evaluations of the system’s population health initiatives, which will be invaluable in gaining buy-in and financial support from local community agencies and health plans.

The Population Health Care Delivery Model

If the goals of population health are to be realized, the focus must extend beyond the traditional clinical setting to reduce the incidence and prevalence of disease. Accordingly, prevention and wellness efforts must address both clinical risk factors and social determinants (eg, physical environment) that cause or exacerbate illnesses.

 Traditionally, clinicians have provided limited preventive care, focusing instead on diagnostics and postdiagnosis patient care.

 The delivery system needs to invest more in primary and secondary prevention, facilitating clinicians’ prediagnosis delivery of care.

Additionally, the system must establish and coordinate care teams. This is particularly necessary because physicians often have limited bandwidth to prescribe, let alone provide, recommended preventive services.

 Systems may consider emulating Maine’s Primary Care Medical Home Pilot or Vermont’s Blueprint for Health in their use of the Community Health Team (CHT)

 structure, which includes care coordinators, nutritionists, behavioral and mental health specialists, nurses and nurse practitioners, and social, public health, and community health workers. Relative to established care delivery models, it is more efficient and cost-saving for the delivery system to identify prevention priorities and for physicians to manage CHT teams to carry out screenings and other well-care tasks (eg, breast self-examination education, creatinine screening for chronic kidney disease).

 Although the composition of care teams will vary with the needs of specific patient populations, careful consideration should be given to the competencies and capacity of the team for delivering targeted prevention strategies.

The delivery system should evaluate and monitor its patient population’s environment and identify potential risks for triggering certain conditions well before diagnosis. Systems can do so following the model tested by the CDC, which uses claims data and geospatial analytics to identify local hot spots for high-risk conditions, such as diabetes.

 Others use DNA sequencing to pinpoint individuals with genetic predispositions that warrant early intervention. Evidence suggests genetic screenings are comparable in costs to traditional screening activities and may yield more specific clinical insights, particularly for diagnosis of common cancers (eg, cervical, colorectal, breast).

 Beyond clinical information, the system should also integrate social determinant factors. Such initiatives may include obtaining data from local police departments and school districts to account for behavioral risk factors.

 Risk stratification efforts can indicate priority areas and opportunities for collaboration with community and public health organizations, potentially including delivery system partnerships with organizations such as the Occupational Safety and Health Administration or local housing coalitions to mitigate risks in the work and home environments (eg, to reduce mold and lead exposure).

 Because primary prevention activities diverge the most from traditional disease management, delivery systems should consider leveraging federal APMs (eg, Accountable Health Communities) and local or state funding

 to pilot strategies for aligning community and clinical services to address the health and social needs of patient populations.

Secondary prevention programs rooted in the Chronic Care Model are generally effective in detecting disease in early states and preventing further disease progression.

 To slow the growth of many conditions, the delivery system should increase screening rates for individuals with high-risk clinical indicators, such as obesity, hypertension, and high blood glucose levels. Lifestyle modification programs like the Diabetes Prevention Program (DPP) can substantially reduce the risk of many chronic conditions.

 The DPP model alone has been shown to reduce the risk of developing diabetes by more than 50% among adults with prediabetes. As the DPP expands as a covered benefit for Medicare beneficiaries,

 with a likely ripple effect on private health plans, delivery systems should strongly consider leveraging similar evidence-based programs and other social services

 as cost-saving strategies for improving health outcomes. Determinations to implement such interventions may be most easily made in communities where population turnover is relatively low, as any savings would be more likely to accrue to the investing delivery system. In higher-turnover communities, rigorous evaluations accounting for local conditions may be needed to demonstrate cost-effectiveness.

Upon diagnosis, the delivery system’s objective should be to coordinate health services to maximize patient function in a manner that avoids further health deterioration and onset of comorbid conditions. The system can provide care teams with information technology tools to assign patients individual risk scores using pharmacy data, for example, to help clinicians track the likelihood of future hospitalizations and prioritize preventive services accordingly.

 These preventive actions may be as simple as administering routine flu shots and other immunizations to prevent further complications. Moreover, following the lead of the Vermont Chronic Care Initiative,

 the delivery system must facilitate ways to complement the care team’s prescribed regimens with medication therapy management, motivational coaching, health literacy, and self-management skill-building to increase patient adherence and engagement. Clinicians will likely need to draw upon primary prevention resources and other community resources to provide patients with additional self-care support, such as smoking cessation and healthy cooking workshops.

Although the delivery system may define its population health priorities, the individual clinician will ultimately execute the corresponding initiatives. For instance, the delivery system may suggest cost-effective, conservative therapy options, as through decision support tools, and the clinician is expected to select from among them. However, the clinician may have important insights that lead them to recommend a different, less conservative therapy for a given patient. It is appropriate for the delivery system to enable and support such deviations when justified, even when they run counter to the delivery system’s established protocol. Emory Healthcare’s sepsis protocol is one such model of an effective collaborative intervention. Emory’s EHR system includes a “trigger” algorithm that uses patients’ vital signs to alert clinicians when a patient may be septic. The trigger provides the care team with several diagnostic options (eg, urine tests) to scan for infection. If the care team determines that the patient is septic, then the EHR will prompt the care team leader—often the physician&mdash;with a recommended evidence-based order set. In this model, the delivery system attempts to make delivering population healthcare less of an encumbrance by equipping clinicians with treatment suggestions based on real-time data analysis. Ultimately, however, the system allows the clinician to decide what orders are best for the individual patient.

The delivery system should further support clinicians by taking steps to maximize access to prescribed therapies. This may involve addressing barriers in patient transportation, finances, and noncompliance. Likewise, shared decision-making tools provided by the delivery system, such as patient dashboards and other technology-enabled devices for evaluating patient symptoms and care plan adherence, can assist clinicians in maintaining strong communication with patients and tracking their health needs.

After setting their initial treatment plans, clinicians should focus on minimizing exacerbation of established conditions and recalibrating treatment plans as needed. Quality evaluations (eg, Six Sigma) should prompt care teams and the delivery system to jointly devise both patient- and population-level interventions to address any identified gaps in treatment.

 Clinicians can evaluate treatment appropriateness and effectiveness using quality measures in conjunction with physical examinations and patient-reported feedback. These patient-level measures should be integrated into delivery system performance measurement systems and analyzed to ensure that all interventions and initiatives are, in fact, improving population health outcomes.

As conditions become more advanced and complications arise, patients will require regular follow-up care. Both the delivery system and care team should look to identify potential “breakdown” points in maintenance therapies for ongoing conditions and minimize risks that could trigger acute care episodes. The intent is to manage the population with low-intensity care management and fewer clinician interactions while preventing escalations in care. Banner Health has undertaken this approach through a unique partnership with Philips, using telehealth software to remotely monitor patient vitals using biometric sensors and identifying patients at risk for acute flare-ups.

 For patients facing severe conditions that will likely necessitate hospice or other long-term care services, and for those who do not respond to efforts to mitigate risks of more frequent exacerbations, the care team should consider initiating end-of-life education and planning conversations to re-establish the patient’s preferences.

Concerted efforts must also be made to institute systemwide processes to provide seamless transitional care across settings, including the patient’s home. Delivery systems should leverage dedicated personnel to manage patient flow (eg, case managers) and technological tools to track transitions between and within care facilities. For instance, Christiana Care Health System created its own CareLink system to improve its traditional discharge process by streamlining tasks such as medication reconciliation between pre- and post hospitalization.

 For most patients, routine clinical follow-ups or telehealth consults will be sufficient post discharge. For more complex patients, systems may consider extending care to the patient’s home using community paramedicine services in addition to contracting with home health agencies. Community paramedics can help reduce nonemergent hospital readmissions by following up with recently discharged patients, assessing the home environment, helping patients comply with discharge instructions, and transporting patients to more appropriate care settings (eg, urgent care centers).

 As the patient’s condition progresses to more advanced stages, the focus should shift to providing more comfort and palliative care, rather than preventive or active treatment. The delivery system should consider reconstituting the patient’s care team to include more coaching, therapeutic guidance, and pain management providers to reduce patient isolation, stress, and discomfort. To this extent, it is important for the system and its clinicians to continue addressing the psychosocial and home needs of these complex patients. The University of Wisconsin’s commitment to delivering high-quality palliative care is reflected in its provision of theater-style workshops for clinicians facilitating end-of-life conversations with patients.

 Similar communication and skills training programs should be offered by all delivery systems, distinguishing between primary care and specialist approaches as appropriate.

 Incorporating additional social aspects of palliative care—a focus on emotional well-being, caregiver burdens, and bereavement&mdash;can also be a valuable complement to the broader goals of population health care delivery.

Transition toward a population health orientation will be smoother in areas where payers have adopted contracts and incentives that are well aligned with the delivery system’s new goals and priorities. The challenge, however, is that the uncertainty of investment return (as in the case of populations with high rates of turnover) deters payers from taking on significant risk.

 Given this dynamic, the delivery system must consider modifying its internal compensation structure to align clinician payment with value-based care delivery, as well as leveraging outcome data from phase 1 and phase 2 pilots to demonstrate feasibility to health plans. The delivery system must provide proof of concept that it can in fact bend the cost curve while delivering high-quality care. Recognizing this is an ambitious endeavor, some delivery systems will be more effective in obtaining buy-in from payers and their clinicians if they demonstrate quality and financial gains after implementing more feasible medical care—focused population health interventions first. For systems in less mature markets, this suggests that care teams may have to focus more on phase 2 of the PHCDM to create immediate efficiency gains through better management of chronic conditions, transitions in care gaps, and reducing high-cost unexplained variations before investing in phase 1 strategies with a longer time horizon for return on investment. As delivery systems gradually build up their organizational capacity for value-based care and navigate both phases of the PHCDM, payers, both public and private, will increasingly provide financial support in tandem.

Population health management is a fundamental transformation of how healthcare is delivered. This shift requires the delivery system to embrace the principles of a learning system

 to improve the health of the population while allowing clinicians the flexibility to address the unique needs of patients. The delivery system depends on a dedicated team of healthcare professionals across the care continuum to execute population health initiatives precisely. Moreover, these clinicians must also deliver care insightfully by communicating with leadership about situations in which interventions systematically impede effective patient care and, in parallel, offering solutions that allow the system to further its population health improvement goals. Thus, delivery of high-value care requires delivery systems to coordinate both population-centered care and patient-centered care.

Although there is no standardized approach for how population health practices should be integrated into clinical operations, the PHCDM offers a framework for delivery systems to better understand and execute the objectives of delivering population health—oriented and patient-centered care jointly throughout the course of a patient’s care experience.

The Health Management Academy (SJ), Alexandria, VA; Department of Health Policy and Management, Rollins School of Public Health, Emory University (ASW, KET), Atlanta, GA; Emory Healthcare (SPH), Atlanta, GA.

 Dr Jain contributed to this work as part of doctoral training at Emory University prior to employment with The Health Management Academy. Dr Wilk reports employment with the Rollins School of Public Health, which is affiliated with Emory Healthcare, which is engaged in population health management activities. Dr Thorpe reports board membership for LHC Group and chairman responsibilities for the Partnership to Fight Disease. The remaining author reports no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Concept and design (SJ, ASW, KET, SPH); acquisition of data (SJ); analysis and interpretation of data (SJ, ASW); drafting of the manuscript (SJ, ASW, KET, SPH); critical revision of the manuscript for important intellectual content (SJ, ASW, KET, SPH); administrative, technical, or logistic support (SJ); and supervision (ASW, KET).

Sanjula Jain, PhD, The Health Management Academy, 515 Wythe St, Alexandria, VA 22314. Email: sanjula@hmacademy.com.

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The Population Health Care Delivery Model presents delivery systems with a framework for developing, piloting, and implementing population health programs across the continuum of care.

Sanjula Jain, PhD

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