Joshua M. Liao, MD, MSc

 Physician leaders represent diverse career interests, clinical specialties, and leadership types. Despite the perceived value of their clinical perspectives, little is known about how physician leaders balance patient care and leadership responsibilities or how that balance varies by clinical specialty or leadership type.&ensp;We conducted what is to our knowledge the first survey evaluating physician leaders’ perspectives about these issues.

 Web-based survey administered September 2017 to February 2018 among physician leaders from the 22 health systems cited in the 2016-2018 U.S. News & World Report Best Hospitals Honor Rolls.

 Respondents were asked questions regarding their participation in patient care. We described our findings using percentages and χ

 tests to compare categorical variables across leadership type (executive, educational, clinical) and clinical specialty (procedural, nonprocedural, supportive).

 Of 447 leaders contacted, 53% responded to our survey. Of those, 84% reported some degree of participation in patient care (69%, 90%, and 85% of executive, educational, and clinical leaders, respectively; 

&thinsp;=&thinsp;.001); most (74%) spent no more than a quarter of their time on patient care, and they often achieved a balance that they deemed optimal (74%). Proceduralists were more likely to spend over a quarter of their time on patient care and less likely to achieve an optimal balance.

 Although most physician leaders engage in some degree of patient care, the balance that they achieve varies by clinical specialty and leadership type. These findings provide insight for health care organizations seeking to engage and optimize physician leadership amid ongoing health care transformation.

The American Journal of Accountable Care. 2020;8(2):26-31

American health care continues to undergo significant transformation. Changes in health policy

; consolidation among providers, payers, and other stakeholders

 have placed an emphasis on accountability in health care delivery. These changes underscore the potential value of physician leadership,

 which has been associated with improvements in operational efficiency,

 These dynamics have led to increased organizational interest in physicians with leadership skills

 and growing numbers of physicians seeking leadership training.

Importantly, physicians pursue leadership careers for different reasons

: Some seek administrative opportunities (eg, health system medical director) whereas others desire leadership in specific clinical (eg, service line chief) or academic (eg, department chair) areas. Variation also exists in each of these categories. For instance, some medical directors focus on specific projects or topic areas (eg, a certain hospital unit, an infection control program) whereas others focus on topics that cut across teams and units (eg, value-based care, population health).

Different leadership paths require different skill sets.

 For instance, medical directors of clinical units benefit from change management and process improvement skills needed to drive daily operations. Physicians with leadership in cross-cutting topics such as population health must be proficient in policy analysis, data synthesis, and change management.

Despite this diversity, a common thread is that physicians’ first-hand patient care experience lends them unique leadership perspective

 that can be highly valuable to themselves and their organizations. For example, a physician who maintains an active clinical practice may have greater credibility among clinicians whom they lead, or a physician can inform organizational contracting using their clinical perspective to balance financial and operational considerations. Conversely, the time and energy needed to maintain a clinical practice can siphon attention away from leadership work, with impacts on administrative capacity and potential leadership efficacy.

 All physician leaders face the task of balancing clinical and leadership responsibilities.

Despite these dynamics and the possibility that they vary by type of leadership role and clinical specialty, little is known about physician leaders’ perspectives on balancing clinical and leadership responsibilities. Therefore, we conducted what is to our knowledge the first survey capturing these perspectives.

We conducted a web-based survey and followed approaches used in prior work by sampling physician leaders from the 22 hospitals cited at least once in the 

Best Hospitals Honor Roll from 2016 to 2018.

 For each institution, we reviewed online content descriptions of its executive leadership teams and respective departmental websites to identify the names and contact information of the individuals who possessed a medical degree (MD or DO) and filled a position in 1 of the following categories of leadership types: executive (CEOs, vice presidents, and other health system executives), educational (medical school deans and academic department chairs), and clinical (internal medicine division or clinical service line chiefs). Division chiefs were limited to internal medicine division chiefs to promote consistency in use of title and scope of leadership responsibilities. Where online leadership information was limited (1 hospital), we followed an approach used in prior work by initiating email outreach to identify all eligible leaders.

 Individuals filling multiple leadership roles were assigned to 1 category (executive, if relevant, followed by academic and clinical, in that order). Retirees were excluded. This yielded a sample of 447 potential participants (average of 20.3 leaders per institution).

Respondents were asked what amount of time they currently spend on direct patient care, defined as serving as a physician of record or consultant on a clinical service (eAppendix A [

]). They were also asked about the optimal amount of time that they believed someone in their leadership position should spend on direct patient care to be an effective leader; the minimum amount of time someone in their clinical specialty needs to spend on direct patient care to be a safe, effective clinician; and whether they would increase or decrease their participation in patient care. Physicians participating in patient care were asked if it influences their performance in their leadership role and, if so, how. Those not currently involved in direct patient care were asked why they no longer practice. Additional questions confirmed leaders’ leadership type, clinical specialty, and years in clinical practice.

After pretesting among 32 physician leaders (which led to the addition of 1 question about number of years participating in patient care), the survey was sent to eligible respondents between September 19, 2017, and February 5, 2018. Recipients received up to 6 reminders to complete the survey. The protocol was deemed exempt by the University of Pennsylvania Institutional Review Board (protocol No. 827375). Respondents were not financially compensated for their participation.

Leaders’ clinical specialties were categorized according to the nature of their primary patient care responsibilities as procedural (obstetrics-gynecology, ophthalmology, surgery, urology), nonprocedural (emergency medicine, dermatology, family medicine, internal medicine, neurology, pediatrics, physical medicine and rehabilitation, psychiatry), or supportive (anesthesiology, pathology, radiology, radiation oncology).

We used several definitions to describe respondents’ perceptions about balance between clinical and leadership responsibilities. We defined balance as optimal (those spending an amount on patient care equivalent to the amount they deemed optimal from a leadership standpoint) or nonoptimal (all other situations). Among the latter group, we identified individuals for whom clinical burden (spending more time on patient care than was optimal from a leadership standpoint) contributed to nonoptimal balance. Additionally, we defined the feasibility of balancing leadership and clinical responsibilities as infeasible (if the optimal amount of time on patient care from a leadership perspective was less than the amount needed to maintain clinical competence) or feasible (all other situations). We used χ

 tests to compare categorical variables. All tests of significance were 2-tailed and deemed significant at α&thinsp;=&thinsp;.05. All analyses were performed using Stata version 15.1 (StataCorp).

Of 447 eligible respondents, 53% returned complete (n&thinsp;=&thinsp;233) or partial (n = 4) surveys. Nineteen percent of respondents were executive leaders, 58% were educational leaders, and 23% were clinical leaders. Executive leaders were more likely to come from nonprocedural clinical specialties (72% nonprocedural, 12% procedural, 16% supportive) relative to educational leaders (38% nonprocedural, 38% procedural, 24% supportive). Clinical leaders were primarily nonprocedural (90% nonprocedural vs 10% procedural and 0% supportive) (

&thinsp;<&thinsp;.001). Compared with nonrespondents, respondents did not differ with respect to gender, geographic distribution, leadership type, or clinical specialty (eAppendix B).

Overall, 84% of physicians reported participating in direct patient care. The majority (96%) reported that doing so somewhat or greatly improved their performance as leaders. Respondents noted a number of ways in which this occurred, including increased credibility among those they lead (98%) and insight into “frontline” issues (96%) (eAppendix C). Only 3% of physician leaders believed that direct patient care somewhat diminished their performance, citing reasons such as decreased time for leadership responsibilities. Of respondents not participating in direct patient care, the most commonly endorsed reason was “insufficient time or energy to be an effective clinician” (78%). None reported expectations from leadership as a reason for not participating in patient care.

Balancing Clinical and Leadership Responsibilities

Among physicians participating in direct patient care, most reported spending no more than a quarter of their time on it (74%) and that spending less than a quarter of their time was optimal from a leadership standpoint (80%). The majority (74%) reported achieving an optimal balance, with 15% citing clinical burden as contributing to nonoptimal balance. Only 4% reported that balance between clinical and leadership responsibilities was infeasible.

Perspectives varied by leadership type. Overall, executive leaders were less likely to participate in direct patient care (69%) relative to educational (90%) and clinical (85%) leaders (

). Among respondents participating in clinical care, executive leaders were also less likely to spend more than a quarter of their time on patient care or to believe that spending over a quarter of their time on patient care was optimal from a leadership standpoint (

). In contrast, rates of optimal balance or clinical burden and the reported feasibility of balancing clinical and leadership responsibilities did not vary by leadership type.

Participation in direct patient care varied by clinical specialty, ranging from 98% of leaders in procedural specialties to 82% of leaders in nonprocedural specialties and 76% of leaders in supportive specialties (

&thinsp;=&thinsp;.002) (Figure). The amount of and perceptions about time spent on patient care also varied by specialty type (Table). With regard to balance between clinical and leadership responsibilities, leaders in procedural specialties were least likely to achieve optimal balance (61.0% vs 78.4% and 82.1%; 

&thinsp;=&thinsp;.028) and most likely to report clinical burden (28.8% vs 9.9% and 7.1%; 

&thinsp;=&thinsp;.002) relative to leaders from nonprocedural and supportive specialties, respectively.

To our knowledge, this study is the first to document physician leader perspectives about the balance between their clinical and leadership responsibilities. It has 2 key takeaways.

First, our results suggest that many physicians serving a range of leadership roles find it feasible to balance clinical and leadership responsibilities. That many leaders believed patient care aided them in fulfilling their leadership responsibilities is informative to both physician leaders and organizations seeking to foster physician leadership.

 For these groups, it can be instructive to recognize that participation in patient care may be hampered more by insufficient time rather than external pressures or expectations.

Second, our findings suggest that fostering balance among physician leaders’ clinical and leadership responsibilities is not a one-size-fits-all task. In particular, it is relevant that perspectives and features of balance varied across leadership type and clinical specialty.

Poor balance—for instance, through infeasibility or the presence of clinical burden&mdash;can complicate physicians’ abilities to effectively meet either clinical or leadership responsibilities, much less both simultaneously. The fact that the extent and nature of imbalance can vary is exemplified by our finding that leaders from procedural specialties were more likely to report nonoptimal balance and clinical burden compared with leaders from other specialties.

Organizations can use insights about variation in the extent and nature of imbalance to tailor responsibilities and expectations for different types of leaders. For instance, organizations may require greater participation in patient care among clinical leaders, for whom clinical practice has more immediate relevance, than for executive leaders, whose primary responsibilities are often nonclinical (eg, emphasis on finance or operations

) and more removed from those of frontline clinicians. That perceptions about the feasibility of achieving balance did not vary by clinical specialty or leadership type is reassuring and underscores the ability of physician leaders from a range of clinical specialties and leadership types to achieve optimal balance.

First, the generalizability of our findings is limited by the 53% response rate. Second, although our study was descriptive in design and did not evaluate for associations between leadership behaviors and outcomes, the results represent useful early evidence that can be built upon in future work. Third, our sample of leaders may not be representative of the full breadth of physician leadership (eg, it may not capture mid-level leaders or those in other divisions not directly sampled in our study) or representative of physician leaders in all hospitals or health systems. However, we followed prior approaches in sampling leaders across a consistent set of leadership types among a group of institutions recognized for excellence across a set of clinical measures and outcomes.

 Fourth, we were unable to evaluate the presence and extent of institutional requirements, expectations, and minimum standards for physician leaders regarding patient care responsibilities. These factors should be evaluated in future work. Fifth, our study assessed self-reported perspectives among physicians but not other factors that should be studied in future research, including perspectives among those in nonleadership roles or objective measures of success (eg, staff retention, operational performance).

Our study provides important early evidence about physician leaders’ practices and perspectives balancing clinical and leadership responsibilities. Although most engage in some degree of direct patient care, what kind of balance they achieve varies by clinical specialty and leadership type. Collectively, our findings provide context and insight for health care organizations seeking to engage physician leaders from various backgrounds and optimize the value of their clinical perspectives amid ongoing health care transformation.

 Department of Medicine, Perelman School of Medicine, University of Pennsylvania (JWM, JAS), Philadelphia, PA; Institute for Health Policy, Management, and Evaluation, University of Toronto (ASD), Toronto, Ontario, Canada; Department of Medicine, University of Toronto (ASD), Toronto, Ontario, Canada; Department of Medicine, Sinai Health System and University Health Network (ASD), Toronto, Ontario, Canada; Department of Medicine, and Value and Systems Science Lab, University of Washington School of Medicine (JML), Seattle, WA.

 The authors report 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 (JWM, ASD, JAS, JML); acquisition of data (JWM, ASD); analysis and interpretation of data (JWM, ASD, JAS, JML); drafting of the manuscript (JWM, JML); critical revision of the manuscript for important intellectual content (JWM, ASD, JAS, JML); statistical analysis (JWM); provision of study materials or patients (JWM); administrative, technical, or logistic support (JWM); and supervision (JML).

 John W. Morgan, MD, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Blockley Hall, 13th Floor, 423 Guardian Dr, Philadelphia, PA 19104. Email: john.morgan@pennmedicine.upenn.edu.

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Articles

Although most physician leaders from 22 organizations saw patients and felt that it improved their leadership performance, their perceptions of the optimal balance of clinical and leadership responsibilities varied.

Physician Leaders’ Perspectives About Balancing Clinical and Leadership Responsibilities

As a broadly defined care delivery strategy, care management can improve outcomes but has yielded variable results, particularly within value-based payment models.

One contributing factor is that care management encompasses different types of activities, functions, and goals.

A framework categorizing care management as disease management, utilization management, and/or health care navigation interventions can help providers and payers invest in, implement, and reap benefits from care management programs.

Emphasis on care management has become ubiquitous in the era of value-based payment. At the vanguard of the movement, policy makers such as Medicare have emphasized care management via a variety of initiatives, ranging from payment models that encourage longitudinal care management

 to billing codes that reimburse clinicians for coordinating the care of patients who have chronic conditions.

 Hospitals and physician groups increasingly view care management as a key area for investment and as a strategy for succeeding in a value-based environment,

 and there have been isolated reports of success within value-based payment models.

However, despite widespread enthusiasm, complex care management and coordination activities are not associated with differences in quality, utilization, or cost outcomes in prominent value-based payment models such as the Medicare Shared Savings Program (MSSP).

 One potential driver is the variability in how care management programs are defined and implemented. For instance, a survey of individuals leading care management programs demonstrated such a wide range of roles, program characteristics, patient selection methods, and measurement strategies that researchers faced challenges when attempting to classify programs.

In light of this variation, it is important for policy makers and clinicians to clearly define care management in order to evaluate its impact on patient care. Doing so is vital because care management is not a monolithic concept, but rather one that encompasses several distinct types of activities: those related to clinical conditions, health care utilization, and patient experience and access. Although these types of activities need not be mutually exclusive or at odds with each other, failing to distinguish between them when implementing care management programs carries risks.

Organizations may invest in programs that emphasize one activity while expecting the benefits of another, creating misalignment among organizational goals, program investments, and eventual results. For example, care management programs that emphasize disease management may improve quality performance (eg, increasing adherence to guideline-concordant processes for a given disease) while worsening cost performance by increasing utilization

 (eg, if patients who were previously nonadherent to guideline-concordant care begin receiving more of it).

Consequently, organizations that build disease management—heavy programs expecting them to drive performance in total costs of care reforms, such as accountable care organizations, may fail to see return on investment and arrive at the conclusion that “care management” does not work. This dynamic may exist in the MSSP, in which clinical condition–focused management initiatives have failed to contribute to cost savings.

 For patients, the end result of confusing the functions, benefits, and risks of different care management activities is that some individuals may receive care management services they do not need, while others do not receive services that they do need.

To address this issue and support organizational efforts to engage and succeed in value-based care, we offer a care management taxonomy based on the distinct activities of managing clinical disease (hereafter, 

), containing health care utilization (hereafter, 

), and improving patients’ navigation through the health care system (hereafter, 

). We contrast these 3 activities by focusing on differences in function, target populations, requisite competencies, and key risks and limitations (

Care management programs focused on disease management predate the era of value-based care.

 These programs target patients with chronic conditions, using medical evidence to create processes that improve patients’ disease self-management via steps such as medication adherence and lifestyle or behavioral changes (eg, related to diet and exercise).

The main function of disease management initiatives is to drive greater use of evidence- or guideline-based care. In turn, the requisite competencies for this type of care management activity consist primarily of the ability to translate clinical knowledge into care processes and engage patients in their own care (eg, via motivational interviewing, self-management support). From the perspective of organizational performance goals, this type of program can align with value-based care delivery by improving disease-specific metric performance. However, there is a dearth of evidence that disease management programs lead to appreciable reductions in total costs of care.

 Because disease management programs emphasize evidence- or guideline-based medicine, they are also limited by the lack of medical evidence in many areas of clinical care.

Another limitation of disease management programs is that they are not designed to address nonclinical determinants of clinical, quality, and cost outcomes. For example, hyperglycemia and hypoglycemia in insulin-dependent patients with diabetes can result from food insecurity—an issue that cannot be addressed by clinical strategies such as insulin titration. The clinical focus of these care management programs excludes social and other determinants of health.

Like disease management, utilization management is not a new concept. However, interest in these programs has increased significantly as more clinicians and organizations have gained the ability to collect utilization information (eg, through advances in data capture via the electronic health record and interoperability via admission/discharge/transfer, or ADT, messaging) and the incentives to reduce utilization under value-based payment and delivery reforms. Rather than maximizing guideline-concordant care, the core main function of this care management activity is to reduce unnecessary health care utilization, particularly high-cost utilization associated with emergency department (ED), hospital, and postacute care facility care.

Given this focus, utilization management programs target patients at risk for high utilization (sometimes called “super-utilizers”) and emphasize core competencies such as data analytics and robust clinical triage capabilities, which can be used to identify and intervene in the care of super-utilizers. The specific strategy for triage can vary, with some organizations embedding care managers within their primary care infrastructure to reduce utilization related to ambulatory care—sensitive conditions,

 whereas others station utilization managers in EDs to more directly curb inappropriate hospitalization.

The major limitation of utilization management programs is the risk of inadvertently deterring appropriate care. No clinical triage processes are perfect, and it can be challenging to prospectively determine when ED or acute hospital care is medically necessary. Moreover, these programs do not inherently distinguish between clinical and social drivers of utilization. As organizations seek to discern that for themselves, underemphasis on social drivers can lead to disappointing results, while overemphasis on super-utilizer patients can create underinvestment in programs targeted to average- or low-risk individuals—interventions that have similar if not greater ability to curb unnecessary utilization.

 Finally, although patient experience is a key element of value-based care, organizations that heavily emphasize utilization management may be perceived as “gatekeepers” that lack patient-centered processes.

As a method for delivering patient-centered care, health care navigation has received increased attention in the era of value-based payment. Organizations have created new roles for “health navigators”

 or “health coaches” who focus on helping to remove structural barriers for patients who have difficulties in accessing and/or coordinating care.

 As another example of health care navigation, primary care clinics have enabled direct referrals to community-based programs to address adverse social determinants of health.

 By improving individuals’ experience and/or ability to access care, navigation-focused care management programs can support success in value-based payment arrangements via greater patient engagement and continuity.

However, because navigation seeks to address individualized barriers to care, there are also risks to broad implementation within value-based payment initiatives. In reducing barriers to care, organizations may spur utilization that unintentionally counteracts efforts to manage costs of care. The potential benefits from patient navigation and engagement may also be undercut by features of payment model design. For instance, most heavily emphasize quality and cost outcomes over patient experience outcomes, reducing the degree to which improved navigation is reflected in payment model performance.

As a broadly defined care delivery strategy, care management can improve outcomes. However, the results to date have been variable, particularly within value-based payment models. One way to improve the design, implementation, and potential benefits of care management programs is to utilize a framework that distinguishes among different types of activities, functions, and goals encompassed by the concept of care management.

 Department of Medicine (LMM, JML) and Value and Systems Science Lab (LMM, JML), University of Washington School of Medicine, Seattle, WA; Leonard Davis Institute of Health Economics, University of Pennsylvania (JML), Philadelphia, PA.

 Concept and design (LMM, JML); drafting of the manuscript (LMM); critical revision of the manuscript for important intellectual content (LMM, JML); administrative, technical, or logistic support (LMM); and supervision (JML).

Leah M. Marcotte, MD, Department of Medicine, University of Washington, 1959 NE Pacific St, Seattle, WA 98105. Email: leahmar@uw.edu.

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To support effective care management programs in the context of value-based care, we propose a framework categorizing care management as disease management, utilization management, and care navigation interventions.

What We Talk About When We Talk About Care Management

The American Journal of Accountable Care. 2020;8(1):3-5

Over the past decade, accountable care organizations (ACOs) have expanded across payers, including Medicare, Medicaid, and commercial insurers. Participation among provider organizations has also increased over time, to the point where companies have emerged with the sole purpose of helping health systems succeed in prominent ACOs, such as the Medicare Shared Savings Program.

Although ACOs all possess a set of core features that define the payment model, differences across payer types and patient populations mean that no single strategy will be effective for all types of ACOs. Provider organizations would be best served considering and participating in ACOs after they have considered these differences and their implications for care delivery initiatives that can support ACO success. In this article, we leverage our perspective as physician leaders in an integrated delivery system that participates in multiple ACOs and discuss 3 factors—clinical complexity of ACO populations, social complexity of ACO populations, and ACO network configuration&mdash;to advance the discourse about payment model strategy and performance.

Certain ACO strategies are more or less likely to be successful based on the clinical complexity of the covered population. For instance, approximately two-thirds of Medicare beneficiaries have at least 2 chronic conditions,

 whereas the majority of beneficiaries in many commercial patient populations have no chronic medical diagnoses. This difference poses significant implications for how an ACO participant organization might approach 2 crucial types of activities: assessing patients’ clinical risk (ie, risk capture) and using risk information to implement care management services (ie, risk-stratified care management).

For Medicare beneficiaries, many high-cost conditions as defined by CMS’ Hierarchical Condition Categories (HCC) model are chronic and will remain stable year over year. As a result, providers can implement risk-capture activities within Medicare ACOs via approaches such as clinical decision support within the electronic health record to populate past diagnoses and prompt clinicians to affirm or update them.

In contrast, the lower chronic disease burden among beneficiaries in most commercial insurance plans undercuts the potential benefit of such approaches in commercial ACOs. In particular, the high-cost conditions for these patients, as defined by the HHS HCC model, will be acute (eg, trauma) and therefore less likely to be stable over time (ie, less likely to be relevant in even the next calendar year). Therefore, using clinical decision support prompts based on historical diagnoses can create more “noise” than “signal,” thus causing workflow inefficiencies for clinicians.

This logic also carries implications for risk-stratified care management within ACOs and, in particular, activities directed at high-cost patients. Differences in the clinical complexity of different ACO populations exacerbate a well-established issue with implementing risk-stratified care management: that there is inherent instability in high-cost populations, with individuals cycling in and out of these populations year to year.

Given this dynamic, care management interventions will adopt a different form within Medicare populations (eg, heavy focus on self-management of multiple chronic conditions) versus commercial populations (eg, preventive services to avoid catastrophic events such as motor vehicle accidents). Without these distinctions, provider organizations in ACOs may not achieve anticipated benefits from care management programs because of variation across different ACO populations.

Social factors play an outsized role in determining many health outcomes, serving as a larger driver than even healthcare factors.

 In turn, the extent of an ACO population’s social complexity carries major implications for provider organizations’ payment model strategy and performance.

For instance, because of their predictable coverage over an extended period, Medicare fee-for-service populations tend to be relatively stable in composition. In turn, condition-based care management can be used within Medicare ACOs to deliver guideline-concordant services that not only improve outcomes but also address utilization and costs as core ACO metrics. In contrast, this approach may be less effective in populations who are less stable over time and/or marked by higher social complexity, such as those in Medicaid. Many Medicaid beneficiaries have high costs as a result of social determinants (eg, housing and/or food insecurity) rather than or in addition to clinical determinants (eg, suboptimal medication titration). Delivering clinical interventions aimed at disease management fails to address nonhealthcare root causes of utilization and costs.

The extent of a population’s social complexity may determine how patients access care and, in turn, how organizations implement interventions to perform in ACOs. For example, comprehensive primary care—which focuses on activities such as chronic and acute care management, care coordination, and care continuity&mdash;has been cited as a critical strategy to cost containment within ACOs.

 However, the value of this approach is based on the assumption that patients’ primary healthcare access point is via a comprehensive and often brick-and-mortar primary care infrastructure. Although this may be true for certain groups, such as older Medicare populations, it may not be for others.

For instance, it may not be the norm for employed, less socially complex patients in commercial populations to access care in this way, raising the potential for organizations in commercial ACOs to better meet patient needs via technological approaches such as telemedicine, which can expand access while circumventing some costs of physical locations altogether. As another example, populations with high social complexity frequently access nonemergent care via the emergency department. Consequently, ACOs may be better off investing in fast-track triage and colocated urgent care and primary care facilities rather than comprehensive primary care or telemedicine infrastructure.

Just as ACO strategy should be dictated in part by differences in patients’ clinical and social complexity, it will also likely differ as a result of which providers are delivering care to patients (ie, the ACO network configuration). One size does not fit all because of differences in the networks that are needed in different ACOs.

For instance, network configuration can influence provider organizations’ approaches to managing clinical referrals among different types of clinicians—a core ACO strategy for maintaining a stable, engaged patient population and addressing their utilization, quality, and costs.

 For Medicare patients with multiple chronic conditions, ACOs may require strong networks of primary and subspecialty care within which patients can be referred and comanaged.

In contrast, for commercial populations with less need for tight primary-subspecialty coordination, it may be more strategic for ACO networks to ensure inclusion of providers who are delivering occupation-aligned services (eg, physical therapy providers for labor workers, on-site services that can be accessed at the site of work). Given the extent to which some Medicaid patients receive care from emergency departments, organizations interested in Medicaid ACOs would be well served by carefully considering whether and how to include freestanding and hospital-related sites within their networks.

Differences in network configuration can also affect organizational care standardization activities within ACOs. As methods for reducing unwarranted care variation, clinical pathways can be a promising strategy to implement within ACOs.

 However, whereas ACOs with networks emphasizing primary care providers may elect to develop and implement pathways around prevalent chronic conditions encountered in primary care (eg, diabetes, hypertension), ACOs with networks encompassing quaternary care sites may opt to instead prioritize subspecialty pathways.

Although several core features define ACOs as a payment model, several differences (eg, clinical and social complexity of patient populations, ACO network configuration) highlight why specific strategies may have variable effectiveness in different types of ACOs. Provider organizations would be well served by accounting for these issues as they consider ACO participation.

Department of Medicine, University of Washington School of Medicine (LMM, JML), Seattle, WA; Value and System Science Lab (LMM, JML), Seattle, WA; Leonard Davis Institute of Health Economics, University of Pennsylvania (JML), Philadelphia, PA.

Concept and design (LMM, JML); drafting of the manuscript (LMM); critical revision of the manuscript for important intellectual content (LMM, JML); administrative, technical, or logistic support (LMM); and supervision (JML).

Leah M. Marcotte, MD, Department of Medicine, University of Washington School of Medicine, 1107 NE 45th St, Ste 355, Seattle, WA 98105. Email: leahmar@uw.edu.

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Differences in patients’ clinical and social complexity and accountable care organization (ACO) network configuration highlight why specific strategies may have variable effectiveness in different types of ACOs.

One Size Will Not Fit All: Factors That Drive Strategy in Accountable Care Organizations

 To describe the extent of and longitudinal changes in physician practice variation with respect to implant costs, institutional postacute care (PAC) provider utilization, and total episode payments, as well as to evaluate the association between physician volume and quality and these outcomes.

We combined claims and internal hospital cost data for

34 physicians responsible for 3614 joint replacement episodes under bundled payment at Baptist Health System (BHS). Multilevel multivariable generalized linear models were employed and the intraclass correlation (ICC) was used to quantify between-physician variation.

 There was significant between-physician variation in implant costs, institutional PAC provider utilization, and total episode payments not explained by observable variables (

<.001 for all). Over 5 years, the ICC decreased from 0.26 to 0.06, 0.15 to 0.13, and 0.12 to 0.10 for implant costs, institutional PAC provider utilization, and total episode payments, respectively, but differences were not statistically significant. Both higher physician case volume and quality were associated with decreased total episode payments and institutional PAC provider utilization, but not with changes in implant costs.

practice variation was observed under bundled payment at BHS

and decreased to a greater degree for implant costs than institutional PAC provider utilization or total episode payments. Institutional PAC provider utilization and total episode payments were associated with physician volume and quality. Although some organizational strategies achieve gains by reducing physician practice variation, variation reduction is not an absolute requisite for success under bundled payment.

Amid the proliferation of orthopedic bundles, organizations can benefit from understanding whether strategies must reduce physician practice variation in order to succeed. Analyzing the experience of a long-standing participant in Medicare orthopedic joint replacement bundles, we found that although some strategies achieve gains by reducing physician practice variation, variation reduction is not an absolute requisite for success under bundled payment.

There was significant physician practice variation in implant costs, institutional postacute care (PAC) provider utilization, and total episode payments.

Over time, physician practice variation decreased to a greater degree for implant costs than for institutional PAC provider utilization or total episode payments.

To increase value and address substantial cost and quality variation in care, CMS has rapidly expanded orthopedic bundled payment initiatives. By receiving a single “bundled” amount for an entire episode of care, hospitals and physicians are accountable for quality and costs under bundled payment.

After early success bundling acute care among a small group of providers in the voluntary Acute Care Episode (ACE) demonstration,

 CMS extended its focus across the care continuum. In 2012, it launched the Bundled Payments for Care Improvement (BPCI) initiative,

This study demonstrates that variation reduction is an important, but not requisite, component of organizational success under orthopedic bundled payment.

Author | Joshua M. Liao, MD, MSc

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