midas+ executive insights: population health management

Population Health: Securing Data Assets and Assessing Organizational Readiness

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Midas+ Executive Insights Forum | May 2015

With Insights from Ashish Jha, MD, MPH K. T. Li Professor of International Health and Health Policy Harvard School of Public Health Professor of Medicine, Harvard Medical School Director, Harvard Global Health Institute



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Contents Acknowledgments ......................................................................................................................... 2

Executive Summary ...................................................................................................................... 4

Population Health: Securing Data Assets and Assessing Organizational Readiness................... 5

Introduction................................................................................................................................................ 5 Emerging Trends ....................................................................................................................................... 6 The Challenge ........................................................................................................................................... 6 The Method of Discovery .......................................................................................................................... 7 Results I: Securing Data Assets ............................................................................................................... 8

Medicare Advantage Group .................................................................................................................. 8 Medicaid Managed Care Group ............................................................................................................ 9 Commercial Managed Care Group ..................................................................................................... 10

Results II: Assessing the State of Readiness to Execute a PHM Strategy ............................................ 11 Conclusions and Areas for Future Inquiry ............................................................................................... 13 References .............................................................................................................................................. 14

Appendix: Tables ........................................................................................................................ 15

Table 1: Priority ranking of pre-defined list of PHM Interventions across all work groups: Medicare Advantage, Managed Medicaid, and Commercial Managed Care ......................................................... 16 Table 2: Priority ranking of pre-defined list of PHM Interventions summarized by three payer-defined segments of Medicare Advantage, Managed Medicaid, and Commercial Managed work groups. ........ 17 Table 3: Expanded List of PHM Technologies and Solution Capabilities ............................................. 18


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Acknowledgments The Midas+ Team would like to recognize and thank the following individuals for their generous gift of time and thought leadership in the development of this point of view.

Larry Allen, MD Chief Medical Officer Indiana University Goshen Hospital Goshen, IN Bryan J. Alsip, MD, MPH, FACPM EVP/CMO, University Health System San Antonio, TX Marcos Athanasoulis Chief Technology Officer Healthy Communities Institute Berkeley, CA Eliot Asyre Xerox Managing Director Health & Productivity Buck Consultants St. Louis, MO Nicolas Beard, MD International Healthcare Executive Seattle, WA Kathy Connolly Dir. Patient Safety Risk & Quality Strategy and Business Dev. ECRI Institute Charlotte, NC Joe Coughlin Dir. MIT AgeLab Boston, MA Frederocl (Rick) Curro, PhD PEARL Clinical Translational Network, NY Karen Dunning Director Care Coordination Operations Sutter Health, CA Carladenise Edwards, Ph.D. CSO, Alameda Health System, CA Todd Evenson VP Consulting & Data Solutions MGMA Englewood, CO

Gail Grant, MD Medical Director Cedars-Sinai Medical Center Los Angeles, CA Dave Graser CIO, VP, Ardent Health Services Nashville, TN Bill Hammock SVP Oliver Wyman Health & Life Sciences Practice Spring Hill, TN Deena Hannen, RN Corp Admin Director, Care Management Swedish Health Services Seattle, WA Gina Huhnke, MD Deaconess Health System, Chief Quality Officer Evansville, IN Ashish Jha, MD Professor of Health Policy Harvard School of Public Health Veterans Health Administration Boston, MA Kim Johns Chief Quality Officer Deaconess Health System Evansville, IN Shanna Johnson VP Clinical Quality Analytics and Improvement, Trinity Health Livonia, MI Takaji (Harry) Kittaka, MD Chief Transformation Officer Adena Health System, OH Cindy Klein VP & Chief Medical Information Officer United Surgical Partners International Addison, TX

Howard Landa, MD Chief Medical Information Officer Alameda Health System Oakland, CA Dan McCabe, MD Chief Executive Officer AZ Connected Care Tucson, AZ Kevin Moley U.S. Ambassador (Retired) Scottsdale, AZ Matt Nee VP InterSystems North American Sales Cambridge, MA William Peruzzi, MD Chief Medical Officer Alameda Health System Oakland, CA Scott Rabin Gen Mgr Xerox - Buck-Prin H&P Priv. Health Exchange Solutions Los Angeles, CA Florence Reinisch VP Strategy Healthy Communities Institute Berkeley, CA Steve Reynolds VP Market Management Xerox – GHS, NJ Gayle Sandhu Corporate Senior Director, Quality Insurance Scripps Health, San Diego, CA Jeff Selwyn, MD Medical Director AZ Connected Care Tucson, AZ Ann Shimek SVP Clinical Operations United Surgical Partners Intl. Addison, TX


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Gary Starnes AVP Systems Development, Integration & Architecture Ardent Health Services Nashville, TN Tamara StClaire, MBA, PhD Chief Innovation Officer Xerox Commercial Healthcare Sacramento, CA Lionel Tehini, President Cloud Applications & Strategic Services, Medhost Franklin, TN Juan Tovar, MD Physician Advisor for Utilization Scripps Health Management San Diego, CA Deryk Van Brunt, President Healthy Communities Institute Berkeley, CA Neil West, MD Chair, Catalina Foundation Tucson, AZ Scott Williamson Sr. National Accounts Manager InterSystems Cambridge, MA Terri Yancey, RN VP Case Management & Central Appeals Community Health Systems Franklin, TN David Yarger Chief Operating Officer AZ Connected Care Tucson, AZ Huiling Zhang, MD VP Strategic Analytics & Solutions Clinical Operations, Tenet Dallas, TX

Xerox Attendees Lesa Bailey Account Executive Midas+ Solutions Loveland, OH Brian Baker Account Executive Midas+ Solutions Denver, CO Jay Bar Sr VP Healthcare Provider Services Xerox New York, NY Denise DeMaio Account Executive Midas+ Solutions Raleigh, NC Lois Gillette, RN VP Product Design Midas+ Solutions Tucson, AZ Alycia James VP Care Performance Transformation Group Midas+ Solutions Wilmington, NC Linda Justice, RN Solutions Executive Midas+ Solutions Greenville, SC Jim Kirkendall VP Analytics Midas+ Solutions Tucson, AZ Chris Kuzniak, MD Medical Director Midas+ Solutions Atlanta, GA

Justin Lanning SVP, Managing Director Midas+, Healthcare Provider Solutions Tucson, AZ Karen LaRue VP Operations Midas+ Solutions Tucson, AZ Vicky Mahn-DiNicola, RN VP Market Research & Insights Midas+ Solutions Tucson, AZ Jeanine Martin VP Business Development Midas+ Solutions Nashville, TN Cori McDonald Account Executive Midas+ Solutions Sierra Vista, AZ Clayton Nicholas VP Products and Marketing Midas+ Solutions Nashville, TN Chris Peebles VP Information Technology Midas+ Solutions Tucson, AZ Kelly Rakowski Sr VP Healthcare Payer Services Xerox Milwaukee, WI Lynn Smith, RN Clinical Excellence Executive Midas+ Solutions Kansas City, MO David Williams VP Sales Xerox Provider Healthcare Atlanta, GA


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MIDAS+ EXECUTIVE INSIGHTS

Executive Summary Population Health Management (PHM) is quickly becoming one of the most talked about organizational strategies to achieve long-term financial viability for hospitals and healthcare systems reorganizing as ACOs. Health plans and employers are equally vested in PHM interventions as a means to improve health and control costs.

At the Midas+ Executive Insights forum, held on May 18, 2015 in Tucson, Arizona, over sixty executive healthcare leaders came together to discuss the ways in which PHM strategies are established. The first step in the process is to secure the data needed to stratify the population into meaningful segments. This is critical when identifying and prioritizing which interventions are best matched to the needs of the population. The next step is to ensure that the interventions are effective.

When polled at the beginning of the session, 15% of executives reported that their organizations were “already there” in terms of delivering a fully scaled PHM program, with an additional 30% reporting that they would achieve this target within the next two years. An additional 48% reported the journey towards PHM will likely take five to ten years to achieve.

The interventions required to execute a PHM strategy are varied, and require both community and provider assets. Executive participants were asked to review a list of 18 potential PHM interventions and identify which were already in place at most organizations, and which were “must have” vs. “nice to have” in the first 24 months of implementing a PHM strategy. Thirty-two percent of interventions were deemed as “already in place”, with 38% assigned into the “must have” category. Twenty percent of the interventions were considered “nice to have”, with the remaining 10% considered to be longer range or potentially unnecessary strategies. See Table 1 for a list of these interventions and their ranking.

The discussion groups also identified that there may be different levels of readiness to execute a PHM strategy, depending on the populations being targeted for PHM. Populations consisting largely of Medicare patients may require different interventions to address chronic and complex diseases, compared to a relatively healthier population that is covered under a commercial plan. Table 2 illustrates the differences in readiness between Medicare Advantage, Managed Medicaid and Commercial Managed populations.

The visionary leaders in this forum also identified 18 additional PHM interventions that may be useful to change disease trajectory and promote health. While several of these interventions require significant financial commitment and long-term planning to implement, such as predictive analytics, and the use of an integrated data warehouse spanning a community, many interventions identified were rooted in community and social settings outside of the traditional “bricks and mortar” of provider organizations. See Table 3 for a complete list of PHM interventions.

The emphasis on community-based intervention sets the stage for our next series of executive forums, to be held in Nashville on September 16-17, 2015; where we will be discussing the ways in which provider-based organizations can secure the right leadership to establish successful PHM strategies and create new community alliances needed to care for the populations they serve.


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MIDAS+ EXECUTIVE INSIGHTS

Population Health: Securing Data Assets and Assessing Organizational Readiness Today’s healthcare world is relentlessly focused on improving the health of populations. After all, it’s easier to decrease healthcare costs by creating a focus on wellness and prevention than it is to treat complex chronic disease. But to implement the right strategies that will align with the needs of a community, you must first understand the immediate and longer term risk of those you are serving.

Introduction

This paper is about the fundamentals of beginning the journey towards Population Health Management (PHM). Like any journey, knowing who is going along for the ride influences where you are going and how you are going to get there.

PHM is often an ambiguous term that can mean different things to the stakeholders that provide and manage care resources across the health continuum. While fundamentally rooted in public health and community services, health plans are adopting PHM strategies that not only involve contractual agreements with medical providers in order to shift the financial risk of covered populations; but are engaging directly with patients to coordinate services. Not surprising then, hospitals, physicians, and ACOs create additional PHM strategies from a provider-centric view in order to manage clinical and financial risks of patients for whom they are accountable.

Provider-based PHM strategies typically consist of aggressive care coordination interventions, including follow-up calls to patients following discharge, hospital, and community case management services, disease management programs, medication reconciliation processes, and utilization of provider-owned or managed post-acute care services. In addition, attempts to engage and incentivize medical providers to adopt standardized practice management protocols and care pathways that show promise in reducing cost of services are typical in provider-centric models of PHM.

The May 2015 Midas+ Executive Insights Forum was facilitated by Ashish Jha, MD, physician, healthcare policy researcher and advocate for the notion that an ounce of data is worth a thousand pounds of opinion.


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Emerging Trends

An emerging trend in provider-based PHM strategies is to leverage community-based resources, not only for promotion of wellness and prevention, but for care of the frail elderly and those with complex chronic diseases. Programs such as the American Heart, Lung, and Diabetes Associations may be used to educate and support patients with chronic disease. Community and neighborhood health coalitions and faith-based organizations are leveraged to conduct wellness clinics and health promotion activities, as well as to provide care to home-bound citizens in need of social support and transportation services.

In addition, new partnerships between hospital providers and other community assets are arising, including partnerships with retail pharmacies, emergency medical services, and public and private transportation services, to name a few. While traditional provider-centric business leaders might view these partnerships as “eating into our own bottom line”, many are quickly understanding that the financial benefits of delivering such services through existing and well-established infrastructures far outweigh the cost and time to recreate and sustain similar services. Plus, the added advantage of leveraging resources that are both convenient and simple for citizens to access promises increased consumer engagement in health-related behaviors that ultimately impact health outcomes.

The Challenge

One challenge with all of these PHM interventions, however, is to determine which ones are the most urgent for a given population, and how to prioritize efforts against limited financial resources. Even for provider-based PHM models, the answer will differ depending on one’s business position within the community. Multi-specialty provider groups may view this challenge from a narrower point of view than an ACO, which might wish to deliver a broader set of services.

In contrast, health plans and employers may focus services around contracted providers and services and create incentives for both providers and consumers to leverage “in-network” resources in order to limit utilization and reduce cost.

What all seem to agree on, however, is that in order to implement the right strategies to care for a population within a total or partial capitated “at-risk” model, it is first necessary to understand the baseline disease burden of the targeted population, including the potential outcome determinants of risk behaviors, demographics, and socioeconomic variables.

“Population Health Management is about the outcomes of a group of individuals and the distribution of the outcomes across the population; including the determinants of those outcomes – and then segmenting the population into more homogenous subgroups so that you can target your interventions on the things that you can potentially impact. There is no monolithic solution to this challenge”.

– Dr. Ashish Jha


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The Method of Discovery

By invitation, a group of approximately 55 healthcare leaders and executives from across the U.S, consisting of Chief Executive Officers, Chief Information Officers, Chief Medical Officers, as well as other senior leaders of analytics strategy, case management, quality improvement, payer, employer, community and vendor organizations, rallied around the conversation of PHM during a structured three-hour forum designed to explore the infrastructure issues needed to deploy a PHM strategy.

Participants were asked to convene around one of three business scenarios representing healthcare systems in the early stages of moving from a traditional fee-for-service model to the new frontier of full “at-risk” acute care delivery models.

In the attempt to segment the “at-risk” populations at the broadest level, three fictitious scenarios were created that might be typical in an ACO contract with a given health plan:

Medicare Advantage (representing senior citizens 65 and older, either in relatively good health or with one or more chronic conditions, including the frail elderly population)

Medicaid Managed Care (representing under-advantaged citizens less than 65 years with disabilities and including those with one or more chronic disease)

Commercial Managed Care (representing employed or economically advantaged citizens with relatively good health or with existing and new onset chronic disease)

All populations were assumed to have episodic acute care needs related and unrelated to any underlying chronic disease, as well as the need for palliative care and end-of-life services.

Participants were then asked to discuss methods for identifying the high-risk segments within each of their populations, including the identification of specific data assets needed to risk-stratify their at-risk populations.

Finally, participants were asked to classify a list of pre-identified PHM interventions to identify those most likely to already be in place at most health care organizations, and which interventions were “must haves” within 24 months of establishing the capitated agreement. Participants were also asked to identify which interventions would be “nice to have” within the next 24 months; as well as in the next three to five years. Additional interventions not included in the pre-defined list were invited, as well as comments about interventions that might be of little to no benefit in realizing their objectives.

Hear what executive participants said when asked:

When do you think your organization will be ready to deliver a fully scaled population health management program?

Already there 5/33 (15.2%)

Within 2 years 10/33 (30.3%)

Within 5 years 12/33 (36.4%)

Within 10 years 4/33 (12.1%)

Won’t get there 2/33 (6.0%)

See Acknowledgments on page 2-3 for a list of participants and their affiliations


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Results I: Securing Data Assets Below is a summary of the challenges of identifying the high-risk patients in each of the three population segments, and what data assets are generally needed to identify them. Comments that distinguished the three payer-based segments are highlighted below.

Medicare Advantage Group According to DAN MCCABE MD, who was instrumental in forming a moderate-sized ACO in the Southwest, during the initial phase of an ACO start up providers are heavily reliant on historical claims data to understand the utilization history of the patients for whom they are accountable. However, often this information isn’t available on day one. The health plan typically provides the ACO with a list of participants and the assigned provider or provider group attribution, but a comprehensive claims history to identify frequent utilizers of service may not be immediately available for all patients.

Additional data assets identified by the team include socioeconomic and demographic data, clinical data from the EMR (both ambulatory and hospital), and community health data that might be available, including assessments done in the home by community health workers to assess patient risk. Collecting basic information such as activities of daily living (ADLs), in-home medication adherence evaluations, and even depression and anxiety mood scale information would provide richer data that can later be used for segmenting the population. “Ideally we could have a health or risk profile for each patient, including their risk of falling at home”, said CARLADENISE EDWARDS, who went on to say that “of course all of this implies we will need a big data platform to create predictive analytics, but we also need basic feedback loops in place to track the effectiveness of provider interventions.”

“There may be gaps in the data initially, but the next thing we did was to contract with a vendor to help us risk stratify the population”, said SHANNA JOHNSON. For those organizations who are analyzing their own data, “it might also be important to bring in an epidemiology skill set to interpret the data findings”, said GAYLE SANDHU.

The group agreed that the next step in the risk stratification process is to get the information into meaningful and useful formats so that providers can begin implementing the right strategies. According to LARRY ALLEN, "we need to find the right balance between hi-tech and hi-touch”. In addition, it is important not to forget the intuitive clinical insights from providers, which may be helpful in identifying high-risk patients within a provider’s practice. “Just ask a provider who their high risk patients are and they can likely identify those individuals without sophisticated reports and analytics, said Allen.

“It is projected that as few as 10% of Medicare patients spend 50% of the resources. The problem is that this 10% is made up of many different segments of people, including those with disabilities, chronic disease and the frail elderly. We can further refine these three subgroups into those with acute conditions concurrent with chronic disease. The challenge then is to match the right interventions to the needs of each group. For example, a disease management program will do nothing for the frail elderly without chronic disease.

Plus we have to understand that for the 10% of patients that we deem high-risk based on historical utilization patterns, perhaps only 10% of those represent actual preventable spending [meaning patients admitted to acute care vs. ambulatory care settings].

There is also a portion of this group who will, in one to two years, exit our programs due to natural causes even if we would do nothing [referring to patients who die]. We suspect we will see different patterns in the Medicaid populations once additional research in this area has been conducted and published”.

– Dr. Ashish Jha


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Medicaid Managed Care Group The challenges in identifying patients within the population of Medicaid are compounded by the fact that this population tends to be extremely culturally diverse. According to WILLIAM PERUZZI MD, the issue is compounded by language barriers as well as diverse social determinants including gang-related behaviors [referring to injuries and trauma afflicted by both self and others], homelessness, and substance abuse. “In our community we have a large Asian population, where there are as many as 20 to 30 different languages spoken”, said Peruzzi. In addition, “social determinants such as coming from a single parent household, mental health issues, and educational factors [implying lower levels of health literacy] play a significant role in determining risk”, said Peruzzi.

Similar to the Medicare group, this group concluded that historical administrative claims data are useful to identify frequent utilizers of hospital and emergency department services, with one participant citing the work of Jeffrey Brenner on Hot Spotting to gain insights into root causes for frequent hospital visits (Benner, 2014).

“We are really making judgments on a different plane and according to different values”, said RICK CURRO, who went on to propose a change in traditional clinical encounters. “The objective would be to elevate and standardize the traditional provider-patient encounter to the level of a clinical study, by adding an audit trail to ensure best practice,” said Curro.

Another challenge cited by the group is the ability to track patients across the community. Patients in this group tend to be fairly mobile, so traditional hospital ADT and patient registration systems may not be sufficient to track patients over time. According to FLORENCE REINISCH, “It’s important that we understand the patterns of movement of these high risk populations over time and how they move from one risk segment to another”.

The group also cited the use of cell phone technologies as another potential data source. “In southern Ohio we care for an Appalachian community that tends to be economically depressed. However, it’s amazing that probably 99% of those we care for in the hospital have cell phones”, said TAKAJI KITTAKA MD.

While all agreed that having an integrated data warehouse and a standard set of predictive analytics to identify high-risk segments would be ideal, matching the needs of the population to the right interventions at the right time is what matters most. According to GARY STARNES, “Only a handful of places have all the needed technology solutions in place today. It may be that we don’t need a different set of analytics for this population, but rather a different set of interventions…it’s how we act on the information and how we deliver it that moves the dot”.

“No one is asking hospitals to fix society, but you can be a convening force to help move the needle within each of your communities”.

– Dr. Ashish Jha


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Commercial Managed Care Group The commercial managed care population typically consists of individuals 18 to 64 years of age who are actively working. This population is generally assumed to have some resources available to them for accessing and engaging with healthcare services, and includes newborn and pediatric populations as well as adults.

According to KAREN DUNNING, “It tends to be a fairly straightforward process to identify the obvious high-cost utilizers of services such as high-risk babies in NICUs, organ transplant patients, and trauma cases”. These populations may not require sophisticated PHM interventions, but rather more traditional case and utilization management approaches that are ubiquitous within the managed care space.

However, the need to “engage” this population is of particular importance, because their behaviors might be different from those of other populations. According to DAVID GRASER, “patients in the commercial group often feel invincible” and their motivation to change lifestyle and behaviors that impact long-term outcomes could actually be less than other groups, despite the fact that this group tends to be more sophisticated with technology access and utilization of technologies like patient portals and on-line health screening tools.

Because the outcomes resulting from lifestyle changes in this group are so long-term, it is important to determine which behavior changes have the greatest potential to impact long term outcomes and cost. Once those determinants are identified, the PHM interventions can be deployed with the long-range objective of changing the trajectory of actual and potential disease processes. To this end, “there is a tendency to focus on the more immediate cost reduction strategies tied to utilization of lower-cost services, such as generic prescriptions and “in-network” providers”, said HUILING ZHANG, MD.

There are also patients within the “relatively healthy” segment who have new or existing chronic diseases that require focused PHM strategies. These populations can be identified by historical claims and ambulatory clinical data, such as laboratory findings, BMI ratios, and medications. “The key is to project an “actuarial-like” analysis to predict which patients progress to more complex disease states”, said Graser.

Patient-reported outcomes may also be a valuable source of information to screen longitudinal risk factors, including employer-based screening to ensure employees have “skin in the game”. Incentivizing lifestyle change is personal and complex. According to DEENA HANNEN, “It’s hard to remember when I’m 40 that ‘I could lose my eyesight when I’m a 75 year old diabetic when the desert is sitting in front of me…but it’s easier to remember $200 less in premiums this year”.

“Much more research needs to be done across diverse populations in order to properly segment risk and understand what causes people to progress in and out of the risk segments. We should expect to see variation across various population segments and prepare for the fact that there is no single solution that will meet the needs of all populations and that organizations will have the difficult task of deciding which strategies to build into their PHM strategies, which will impact the most people. These decisions are ideally based on data rather than stakeholder opinion”.

– Dr. Ashish Jha


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Results II: Assessing the State of Readiness to Execute a PHM Strategy

The challenge identified by all three groups was the need to match the “right PHM resources at the right time and in the right place” to meet individual patient needs and impact disease trajectory. In this part of the work group exercise, participants were provided with a prepared list of 17 potential PHM inter-ventions and asked to classify them into one of five categories:

• Likely already in place in most integrated care settings

• Need to have in place in first 24 months of PHM strategy

• Nice to have in first 24 months of PHM strategy

• Defer for years 3-5 (important but not as urgent)

• Not sure strategy is needed or has significant benefit

The purpose of this exercise was to quantify how far along most provider-based organizations are today with creating the necessary infrastructure needed to support PHM strategies, and to identify potential gaps and needs for future success.

Overall, across all three payer-defined population segments for this exercise, 32% of the capabilities listed in the pre-defined list of PHM interventions were deemed by participants as “Likely already in place”, with an additional 38% classified as “Need to have in place in first 24 months”. Twenty percent of the PHM interventions were identified as “Nice to have in first 24 months”, with 8% deferred for future implementation in years three to five. Only 2% of the pre-defined PHM interventions were listed as “Not sure strategy is needed or has significant benefit”.

Table 1 describes the distribution of the responses for all three groups combined. Not surprisingly, the capability to track immunizations was predominate in the “Likely already in place” category, as this function was part of the initial minimum requirements of the Stage I electronic medical record (EMR) “Meaningful Use” incentive program.

The next largest intervention reported to be in place already was disease management. While this item was not explicitly defined for purposes of this exercise, it could be assumed that most integrated delivery systems and ACOs believe they already have this capability in place for chronic populations such as diabetes, cardiovascular, and lung disease. Further confirmation of this fact may be warranted in future research.

Patient-reported outcomes were predominately identified as a future capability in 3-5 years. However, given the emphasis on patient-reported outcomes by the National Quality Forum (NQF) and PCORI, this capability could shift to a more urgent requirement in the next 1-2 years.


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The least urgent capability on the pre-defined list of potential PHM interventions was genomic testing and Drug-DNA testing. Although viewed as a largely futuristic PHM strategy, current technology trends and market forces could also escalate the need for this capability in the future, especially in organizations whose PHM strategies are guided by retail influences that support low-cost genomic testing for the masses, such as 23andMe, Walgreens, Theranos and other emerging laboratory testing vendors in this space.

When examining the stages of readiness across the three payer segments, there were moderate differences among the three groups. Table 2 illustrates that the Medicare Advantage group collectively reported the fewest interventions “likely already in place” (26%) compared to the commercial group (44%). However, it should be noted that there were only 5 respondents in the commercial group, which elected to perform this exercise by group consensus in contrast to the other two work groups who performed the exercise as individuals. Further research to understand differences among the three payer segments is needed.

Nineteen additional interventions that were not part of the original prepared list were identified across the three work groups and are incorporated into a post-exercise PHM intervention list, which is displayed in Table 3. Of interest, 15 of the 19 additional interventions offered by work group participants were community-based vs. hospital- or provider-based interventions, bringing the total number of community-based capabilities to 18 of the 36 (50%) potential technology and service capabilities listed for PHM.1

Several of the low-cost community interventions offered by various work group participants included organized trips to the local Farmer’s Market to purchase organic foods or to parish nursing programs. When questioned by other participants with an IT or Medical background about how healthcare organizations could potentially partner with churches in the provision of care to frail elderly, KAREN DUNNING, a Director of Operations at Sutter Health, replied, “You probably already have these programs in place today – you just don’t know you do”.

This observation sheds light on the potentially untapped opportunities that may exist through more creative partnerships with community assets, including churches, local transportation services, hardware stores, restaurants, schools, and other organizations and businesses that are traditionally not viewed as being part of the medical treatment domain.

1 Within the context of this paper, community-based capabilities are defined as those interventions that are primarily conducted within a community setting and outside of the direct hospital-based or ambulatory medical care setting, regardless of the primary funding source. Table 3 designates the focus of the intervention as either provider- or community-based.


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Conclusions and Areas for Future Inquiry

The findings from this executive work group are two-fold. First, the data assets required to fully execute a PHM strategy are continuously evolving. The promise that advanced analytics brings is enormous; not only to segment populations into meaningful cohorts so that we can target our interventions, but to understand what causes people to shift across the various segments. The need to wait until all source data is available to answer these questions is not realistic, nor is it necessary. However, there is little doubt that more research needs to be conducted in order to understand the problems we are facing.

In addition, it is imperative that we begin to understand how to demonstrate a return on investment for the PHM interventions that are deployed. This is especially critical in order to justify long-term expenditures for costly interventions that are likely to require both technical and human resources to deploy.

The second finding is that greater emphasis needs to be placed on the inclusion of community assets when developing a PHM Strategy. The Medicare Advantage work group, which revealed this segment as having the least state of readiness, may indicate that mature PHM strategies for effective intervention with frail elderly and those with complex chronic disease are not yet fully realized by most healthcare organizations. This may be in part because many of the necessary PHM management interventions for these segments likely require a robust set of community-based services, many of which may not yet be in place in most provider-centric PHM models today.

A question that might be asked of leaders who are beginning their journey in PHM is how they will create the necessary infrastructure to scale an effective PHM strategy. This will require a major paradigm shift for most healthcare systems, where the hospital is viewed as the center of the strategy. Not only will hospital-based leaders need to establish community-based strategies, they will also need to ensure they have the right executive leaders in the C-Suite to inspire and create a new community alliance.

What attributes and skill sets are needed for these emerging leaders? Will they arise out of public health, nursing, or marketing domains? A recent was study conducted by the American Hospital Association and the Association for Community Health Improvement (December, 2013) that offers some insights into these questions. More than 1,198 hospitals were surveyed to examine trends in hospital-based population health infrastructure.


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What is clear from these findings is that no current standards exist for implementing PHM strategies. Furthermore, many health care organizations were found to be implementing their PHM interventions through part-time director or mid-level managers without direct engagement at the C-suite level. Healthcare organizations will have to secure new executive leaders with full-time accountability for the PHM strategy and with professional education and experience in the PHM field.

Though current population health leaders with dedicated accountabilities for PHM have extensive experience in healthcare, they tend to be fairly new to their positions and the field. Community health, health education, and community benefit are desirable backgrounds for new PHM executive leaders, while existing leaders should pursue education in community health needs assessments, healthy communities, and collaborative facilitation.

So how will hospital-based population health programs recalibrate their existing infrastructure to realize successful clinical outcomes and cost reduction strategies and evaluate their return on investment? These and other questions will be explored in our next Midas+ Executive Insights Forum to be held in Nashville, TN, on September 16-17, 2015.

For information on how to become part of the Midas+ Executive Insights Forum, to obtain permission to reprint, or for questions or comments about this manuscript, please direct your inquiries to the author, Vicky A. Mahn-DiNicola, RN, MS, CPHQ, VP Research and Market Insights, at [email protected].

References

Association for Community Health Improvement. (2013, December). Trends in hospital-based population health infrastructure: Results from an Association for Community Health Improvement and American Hospital Association survey. Chicago: Health Research & Educational Trust. Accessed June 16, 2015 at www.healthycommunities.org.

Benner, J. (2014, February). Robert Wood Johnson Foundation. A Revolutionary Approach to Improving Health Care Delivery. Accessed June 16, 2015 at http://www.rwjf.org/en/library/articles-and-news/2014/02/improving-management-of-health-care-superutilizers.html

mailto:[email protected]

http://www.healthycommunities.org/

http://www.rwjf.org/en/library/articles-and-news/2014/02/improving-management-of-health-care-superutilizers.html




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Appendix: Tables


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Table 1: Priority ranking of pre-defined list of PHM Interventions across all work groups: Medicare Advantage, Managed Medicaid, and Commercial Managed Care

Population Health Management

Technologies and Solution Capabilities

Likely to Already Be in Place

Need to Have

Next 24 Months

Nice to Have Next 24 Months

Defer for

Years 3-5

Not Sure Needed or

Minimal Value

Vaccination tracking with alerts and reminders 18 1 4 1 1

Disease management solutions for high risk complex and chronic disease

16 8 1 0 0

Hospital readmission reduction solutions 13 10 2 0 0

Patient portal for scheduling appointments and access to personal health information

12 5 6 1 0

Solutions to coordinate wellness checks and primary care visits

11 12 2 0 0

Solutions to coordinate care transitions planning and services post hospital discharge

11 11 2 1 0

Post-acute care services including home care and end-of-life care

11 11 2 1 0

Clinical risk assessment and segmentation of at risk population

11 13 1 0 0

Specialty care referral mechanisms 7 10 4 2 0

Integrated data warehouse for care continuum data 7 11 7 0 0

Community services to provide support groups, education and parish nursing

6 12 7 1 0

Medication reconciliation and evaluation of medication efficacy

6 17 2 0 0

Telehealth to treat patients virtually 2 7 11 5 0

Predictive analytics to support proactive and personalized care management

2 15 5 2 0

Email and e-visits with primary care providers 1 12 11 1 0

Solutions for capturing patient reported outcomes on mobile devices

0 5 14 5 0

Genomics and DNA-Drug Testing 0 2 2 14 7

TOTAL 134 162 83 34 8

PERCENTAGE 32% 38% 20% 8% 2%

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Table 2: Priority ranking of pre-defined list of PHM Interventions summarized by three payer-defined segments of Medicare Advantage, Managed Medicaid, and Commercial Managed work groups.

Population Health Management

Technologies and Solution Capabilities

Likely to Already Be in

Place

Need to Have Next 24 Months

Nice to Have Next 24 Months

Defer for Years 3-5

Not Sure Needed or

Minimal Value

Medicare Advantage 26% (35) 38% (51) 22% (30) 11% (15) 4% (5)

Managed Medicaid 31% (62) 41% (81) 21% (41) 7% (13) 2% (3)

Commercial Managed 44% (37) 35% (30) 14% (12) 7% (6) 0% (0)

TOTAL ACROSS ALL GROUPS 134 162 83 34 8

TOTAL PERCENTAGE ACROSS ALL GROUPS

32% 38% 20% 8% 2%

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Table 3: Expanded List of PHM Technologies and Solution Capabilities Additional capabilities added by executive participants displayed in bold italics

Focus: Capability:

Provider 1. Vaccination tracking with alerts and reminders

Provider 2. Disease management solutions for high risk complex and chronic disease

Provider 3. Hospital readmission reduction solutions

Provider 4. Patient portal for scheduling appointments and access to personal health information

Provider 5. Solutions to coordinate wellness checks and primary care visits

Provider 6. Solutions to coordinate care transitions planning and services post hospital discharge

Provider 7. Post-acute care services including home care and end-of-life care

Provider 8. Clinical risk assessment and segmentation of at risk population

Provider 9. Specialty care referral mechanisms

Provider 10. Integrated data warehouse for care continuum data

Community 11. Community services to provide support groups, education and parish nursing

Provider 12. Medication reconciliation and evaluation of medication efficacy

Community 13. Telehealth to treat patients virtually

Provider 14. Predictive analytics to support proactive and personalized care management

Provider 15. Email and e-visits with primary care providers

Community 16. Solutions for capturing patient reported outcomes on mobile devices

Provider 17. Genomics and DNA-Drug Testing

Provider 18. Multi-disciplinary care teams that cross boundaries of health care settings

Provider 19. Standardized care pathways or roadmaps to manage common conditions

Provider 20. Hot Spotting high utilizers of hospital and emergency department services

Provider 21. Predictive analytics to monitor disease trajectory of at risk populations

Community 22. Smartphone applications to monitor care following discharge

Community 23. Solutions to track address and contact information for enrollees across community

Community 24. Partnerships with minute clinics/retail pharmacies for episodic care management

Community 25. Longitudinal tracking of functional Activities of Daily Living (ADLs)

Community 26. Longitudinal tracking of depression and anxiety

Community 27. Expansion of data analytics at a county and state level with merger of census data

Community 28. Home monitoring systems with centralized monitoring of vital signs, weight, O2 status

Community 29. Employer-based wellness screening and health coaching

Community 30. Partnership with schools and universities to promote health, nutrition, exercise etc.

Community 31. Community nursing case management for chronic disease

Community 32. Community social services case management and monitoring tools for frail elderly

Community 33. Farmers market shopping program to support nutrition and whole foods consumption

Community 34. Partnership with local cab and transportations services

Community 35. Partnership with local emergency medical services (EMS)

Community 36. Partnerships with local hardware stores for installing bathtub skid protectors, hardware

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