White Paper: Primary Care Empanelment
As healthcare providers move toward population health management, patient empanelment has been raised as a priority for all healthcare systems, networks, and individual providers. Health Care Futures has drafted a short white paper to level set the facts of empanelment, assess empanelment methodologies, and profile potential options for inclusion within a physician compensation construct.
The objective of empanelment is to match a patient with the resources (e.g., Physicians, Nurse Practitioners, Physician Assistants, etc.) needed to receive the best quality medical care and improve patient experience. Providing integrated and seamless patient centered quality care is an essential building block for effective population health management allowing providers to maximize use of their license, match resource intensity with appropriate care management needs, and afford confidence among providers in their ability to manage performance and potentially insurance risk.
The Growing Role of Empanelment
There is a growing acknowledgment on the need for patients to have a relationship with a primary care physician (PCP). A strong patient to doctor relationship is critical to provide effective and responsive care teams and establish a trust-based rapport. Research suggests that this connection improves communication, diagnosis and overall patient satisfaction.
A properly empaneled provider enables the practice of proactive, rather than reactive medicine. Time savings from effectively matching supply (a physician’s capacity) and demand (care provided) will enable a review of all healthcare needs and address preventive measures and chronic illness interventions for any given patient.
The patient/physician relationship created through empanelment will also drive cost savings. A strong relationship with a PCP provides an understanding of the medical needs for each individual patient. This allows quicker visits, elimination of redundant tests, the ability for virtual treatment, among other cost saving efforts that will help alleviate constant time and cost pressure providers face. Additionally, there is greater financial liability associated with the at riskpatient population. For this reason, a priority of patient attribution is to ensure all risk based lives are assigned to a primary care provider.
Implications to Providers
Empanelment can provide new insights into a patient population. Demand factors such as visit rate, electronic communication, medication requests, etc. will outline the health of a given population and allow symmetry between the supply of providers and demands of patients. Acuity is a critical element of empanelment and is directly incorporated through demand analysis.
Empanelment can be thought of as the foundation of an effective Patient Centered Medical Home (PCMH) and is a necessary step to unlock the benefits of a PCMH. The transparency created from empanelment will allow individual providers and health systems to better recognize the work at hand. This newfound clarity can help one more effectively manage their panel, find efficiencies within provider teams, and ensure they are operating with the capacity needed to provide quality care.
Accurate empanelment will identify gaps in resources and create transparency in understanding physician capacity. Through empanelment, health systems can equitably distribute workloads and improve staffing decisions using analytics. This allows health systems to better identify to whom new patients should be attributed and how to integrate new patients without long wait times or suboptimal care. In other words, access and recruitment will be more effectively managed by having an empanelment process that accurately matches anticipated demand with available provider capacity.
Empanelment is built on the pillar that every patient should be attributed to a provider, whether that is a physician, NP, or PA. A challenge faced by all health systems as they attribute patients is how to define active versus inactive patients. The time windows from which patient encounters are tracked vary amongst providers and trade organizations. Many arguments exist for what is the most appropriate time window. For example, the Medical Group Management Association (MGMA) recommends an 18-month time frame, but various health systems have implemented 12- and 24-month encounter windows out of fear that an 18-month time frame will over/under state panels. Every organization will inherently have variation in panel size due to differences in attribution methodologies and patient populations. These variations can create challenges when benchmarking to other health systems or national statistics.
Industry Trends and Approaches to Empanelment
Patient attribution is the first step of empanelment and can take many forms. Attribution methodologies range from simple matching processes to complex algorithms. The Four Cut Method (See Exhibit One) of patient attribution is a common starting point for providers. The Four Cut Method is a thoughtful and established methodology. Mark Murray MD is credited with this attribution methodology and it has been widely adopted, including by the Medical Group Management Association (MGMA) in their annual cost and production survey. Despite these benefits, the Four Cut Method is not a one size fits all solution and can be thought of as a starting point rather than a destination. Regardless of the attribution methodology selected, physician feedback and input are necessary as the process evolves to meet the needs of all stakeholders.
|Steps to Patient Attribution – Four Cut Method|
|1||Patients who have seen only one provider for all visits are assigned to that provider|
|2||Patients who have seen more than one provider are assigned to the provider they have seen most often|
|3||The remaining patients who have seen multiple providers the same number of times are assigned to the provider who performed their most recent physical or health check|
|4||Any remaining patients who have seen multiple providers the same number of times but have not had a sentinel exam are assigned to the provider they saw last|
A key tenet of empanelment is that it’s a continuous process. Panel size should constantly be evaluated, updated, and evolving. If not treated as a living process many of the insights and benefits of empanelment will be lost. An example of panel size calculations (non-risk adjusted) compared to attribution methodologies is shown below.
|Panel Size:||MGMA||Case Study #1||Case Study #2||Case Study #3|
|Median Primary Care Panel Size:||1,701||~1,200||~1,900||~1,500|
|1) Four Cut Method over 18 months (See Exhibit 1)||1) Assign all patients in a risk-based product
2) 12 month look back (Four Cut Method)
3) 18 month look back
|1)Four Cut Method with a 12 month look back||
As discussed, variations in panel size will inevitably exist amongst physicians. Demographics, patient acuity, and many other causes will impact the amount of time it takes a physician to appropriately care for a population of patients. To account for these causes, some providers
incorporate a risk adjustment factor into panel calculations. Adjustment factors can take many forms and are highly dependent on the population at hand. Adjustment factors can span well beyond traditional demographic based risk metrics, such as socioeconomic and psychosocial influences.
Potential risk metrics, including traditional productivity standards (wRVUs), may only moderately correlate with physician work. For this reason, the implementation of a risk factor should be a thoughtfully researched and derived through an iterative testing process.
An example of an often used risk adjustment factor is CMS’s Hierarchal Condition Categories (HCC Score). HCC Scores are numeric risk adjustors that incorporate
diagnoses, age, gender, and demographic data. These scores attempt to help normalize a physician’s patient population for the amount of care that will likely be required. The impact of incorporating HCC Scores into any panel data is highly variable on the population, but research has shown risk burden multipliers as high as 1.4. In other words, a panel of 1,000 would equate to a risk adjusted panel of 1,400.
A contrasting risk evaluator is the Charlson Comorbidity Index (Charlson Scores). Charlson scores measure the presence of chronic diseases in a patient. The Charlson index contains nineteen classifications of comorbidities, with each classification assigned a different weight. Similar to HCC scores this weight represents risk burden and is used as a multiplier for adjusting panel size.
A third and less complex example of evaluating risk burden is to only analyze age and gender. Exhibit three (produced by Mark Murray and Associates LLC) provides a simple summary of proposed weights for an age and sex adjusted panel.
All three of these methodologies will be positively correlated to one another, but will produce different results. Risk metrics should not be viewed as mutually exclusive, often a blend of normalized risk metrics is compiled into one adjustment factor for a given population. For these reasons extensive testing is pertinent before any metric is incorporated into a risk stratification methodology.
Options for including Panel Size within a Physician Compensation Framework
As the nature of physician work evolves, it is important to maintain a link between the work a physician does day-to-day and how a physician is compensated. To that end, health systems have begun exploring compensation frameworks that include population health management principles as compensable events. Health Care Futures has documented the changing landscape of physician compensation in a separate white paper that outlines how empanelment can be incorporated in to a compensation construct. This white paper can be accessed by contacting any member of the Health Care Futures team.
Case Study – St. Luke’s Health System
As St. Luke’s Health System (St. Luke’s), an Idaho based not-for profit health system, entered into a system wide physician compensation redesign, physician and administrative leaders quickly realized the importance of patient empanelment for primary care providers. As the health care environment transitions from volume to value, St. Luke’s identified patient empanelment as the mechanism to reflect new definitions of work across all primary care providers (family medicine, internal medicine, and pediatrics). Health Care Futures teamed with WhiteCloud Analytics to help St. Luke’s navigate the implementation of patient empanelment as a compensable event.
The first step for St. Luke’s to incorporate patient empanelment into a compensation construct was to identify a core team of physician and system administrators (Empanelment Sponsor Team) to be charged with defining a system wide approach to patient empanelment. In tandem with WhiteCloud Analytics, an assessment of information technology resources and capabilities available to St. Luke’s was completed as the first step in developing an empanelment process. Equipped with an understanding of the system’s IT infrastructure, the Empanelment Sponsor Team developed a customized approach to the Four Cut method to attribute all St. Luke’s patients to a primary care provider. Given the challenges of identifying active versus inactive patients, St. Luke’s attribution process is updated monthly and transparently communicated to providers through a performance management platform designed by WhiteCloud Analytics.
Variations in the size of provider panels was quickly identified and affirmed the need for a risk adjustment factor. Providers realized all patients are not created equally and the work required for a physician to appropriately care for a population of patients will vary with demographics and patient complexity. To account for these causes, St. Luke’s again teamed with Health Care Futures and WhiteCloud Analytics to create a home-grown risk adjustment calculator. This risk adjustment incorporates for age, gender, chronic disease burden, and previous year utilization. Under this risk adjustment concept, two separate frameworks are used by St. Luke’s to risk stratify patient panels. One framework is tailored to adult primary care providers, while the second is specific to pediatrics. It’s important to note that the concept of risk adjustment is the same for all providers, but the specific measures incorporated into a risk adjustment approach differ between pediatricians and adult primary care providers.
Exhibit 4: St. Luke’s Risk Adjustment Concept
After a series of iterations and extensive testing, the Empanelment Sponsor Team now had a well vetted patient attribution and risk adjustment methodology and St. Luke’s was enabled to compare risk adjusted panels across providers and further patient empanelment as a compensable event. Given that the patient attribution and risk adjustment concept is unique to St. Luke’s, an internal perspective was maintained when incorporating panel management into compensation constructs. In other words, providers were compensated based on the size of their panel relative to peer providers at St. Luke’s rather than an external benchmark.
By incorporating patient empanelment in their compensation plan, St. Luke’s now has a direct means to recognize and reward the emerging definition of work for Primary Care Providers. At the outset, a relatively small component of compensation is tied to patient empanelment as the transition from historical production-based compensation models to an at-risk performance compensation model is not a small undertaking and physician support is critical for success. By the way of their system wide compensation redesign, St. Luke’s has adopted an evergreen compensation model that will evolve with the external environment. As traditional measures of production and compensation (wRVUs) continue to be devalued the percentage of compensation tied to panel management will increase.
The rigor of the empanelment Sponsor Team in developing such a strong process has opened a new lens to how St. Luke’s matches resources with demand and establishes a foundation from which St. Luke’s can evolve with population health initiatives. The system has gained a new perspective on how to best manage physician supply and demand while advancing the quality of patient care and experience. Likewise, a direct link to compensation has driven physician engagement and responsibility of their panels furthering the initiatives of proactive medicine and population health management.
Empanelment can be a meaningful tool for health care providers to advance Triple Aim objectives and as we move towards population health management the role of panels will likely only increase with maturation of team-based care. The objectives of empanelment are simple, but the process requires dedicated attention for effective implementation.
Health Care Futures recommends that organizations spend time to assure the empanelment approach is thoughtfully analyzed and aligned with the system’s strategy. The undertaking of empanelment is not small in the work effort required or the return generated for health Systems. To extent required, third party resources may be a complimentary means to navigating the process of implementation.
The benefits of unlocking patient empanelment are tremendous, but require dedication and physician support in development. To that end an understanding of IT resources, physician leadership, and internal capabilities is a required first step of the empanelment process.
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