Archive for the ‘Risk Stratification’ Category

Guest Post: Lab Data is the Missing Link in Healthcare Risk Adjustment

June 19th, 2018 by Jason Bhan, MD

Data informing risk adjustment programs is critical under value-based healthcare reimbursement models.

For health plans, value-based care means a continuous need to innovate and improve their risk adjustment, clinical quality, and care management programs. Unless payers identify and receive the correct amount of reimbursement, it is difficult for them to invest appropriately into member care programs for better outcomes while remaining financially successful.

The data informing risk adjustment programs are critical, as they build the foundation for accurate member risk stratification. In that respect, those data sources are directly related to the correct amount of reimbursement payers receive and can invest in proactive care management. In other words, high-quality clinical data delivered quickly enough for a plan to get a member into a care management program early enough is important to the health of the member and the business. The approach leads to improved clinical outcomes and reduced costs in emergency room visits, hospitalizations and chronic condition management.

Lab Data: An Untapped Resource

To achieve such clinical granularity, at scale, plans can turn to diagnostics—or lab—data. Lab data drives approximately 70 percent of medical decisions and, unlike claims data, is available in near real-time. It also provides an unrivaled level of specificity for clinical conditions. When lab data is integrated into plans’ claims- and chart-based programs, it enables earlier, more comprehensive and accurate clinical insights to benefit care management of both existing and new members. Utilizing the same information that clinicians use to make decisions, within the same timeframe, provides a powerful and unique opportunity to intervene and impact a patient’s health.

What Can Lab Data Do for You?

Expanding and improving their clinical data supply with diagnostics data can help health plans to:

  • Provide historical insights on members where claims are unavailable to improve risk adjustment. For new enrollees, this enables the health plan to get new members into the appropriate care/disease management programs from day one.
  • Serve as an early detection system for care management of all enrollees. Plans can identify patients in need of additional or alternative therapy from lab data earlier than from any other data source. For existing members, the detailed results uncover needs that may have been overlooked based on a claims analysis alone.
  • Identify high-risk members for case management and provider interventions from lab data. Optimized risk adjustment aligns reimbursements to health status, enabling the plan to more heavily invest in member care programs.

Applying AI Solutions

When it comes to gaining actionable insights from diagnostics data, plans can benefit from partnering with healthcare artificial intelligence (AI) specialists in the field. Healthcare AI organizations use techniques such as machine learning and natural language processing—coupled with massive computational power—on big data sets, to make sense out of non-standard, complex, and heterogeneous data.

Healthcare AI, when applied to diagnostics clinical lab data, improves risk stratification by identifying diagnoses earlier in the year versus waiting for the claim or searching charts. Rich in clinical details, it presents a more complete picture of the member’s health. Better risk stratification leads to better care management programs; and successful programs have been shown to reduce costs by targeting those most likely to benefit and keeping intervention costs low.

Dr. Jason Bhan

About the Author: Jason Bhan, MD, is co-founder and Chief Medical Officer at Prognos, an innovator in applying AI to clinical lab diagnostics. More than half of the Prognos team is made of engineers, data scientists, and clinicians. Prognos aims to increase the usefulness of disparate healthcare data to better inform clinical decisions and ultimately improve patient outcomes.

10 Critical Care Coordination Model Elements for Medicaid Managed Care Members

May 17th, 2018 by Melanie Matthews

There are 10 critical elements of the care coordination model for Independent Health Care Plan (iCare) Medicaid managed care members, according to Lisa Holden, vice president of accountable care, iCare.

The first element and touchpoint for Medicaid managed care members is their care coordinator. “Every single one of our incoming SSI Medicaid members is assigned to a care coordinator,” Holden told participants in the May 2018 webinar, Medicaid Member Engagement: A Telephonic Care Coordination Relationship-Building Strategy, now available for replay. “That person is responsible for everything to do with that member’s coordination of care.”

Care coordinators are assigned to every Medicaid member and are responsible for engaging and coordinating member’s care needs.

“We want our care coordinators to make an initial phone call as early as a couple of days after the member is enrolled in our plan,” she said. “If the member is interested in having a conversation, we offer to conduct a health risk assessment. But if the timing isn’t right, then we offer to schedule another appointment. There’s no pressure except that we want them to feel engaged by us.”

Once completed, the health risk assessment forms the basis of an interdisciplinary individualized care plan created by the care coordinator with the member.

The care coordinator, who is a social worker by background, has access to a nurse, who is available for medically complex members, said Holden.

iCare also relies on health coaches. Health coaches are now teaming up with a care coordinator as much as, if not more than, the nurses are historically, Holden said.

“Our health coaches are literally assigned to work in the community to become very familiar with the resources that are available,” she added. “They are becoming steeped in the communities in which they serve. Each one is assigned to a neighborhood, and we’ve asked them, ‘Get to know the police. Get to know the fire. Get to know the food organizations and food pantries. Get to know the housing specialists in your area.'”

The health coaches also help the care coordinators locate difficult-to-contact members by being in the community as a boots on the ground force. They’re also focused on assessing and addressing social determinants of health.

“We really believe that health coaches are going to be the key to our success in this year and in years to come,” Holden explained.

In addition to the care coordinators, health coaches and nurses, the care coordination team includes two specialized positions…a trauma-informed intervention specialist and a mental health and substance abuse intervention specialist. “We brought those two specialties into this program for our Medicaid members because we know that there’s a high instance of behavioral health conditions, which usually has another diagnosis of alcohol and drug use, not always, but quite often. We wanted to have the team ready to engage the member,” said Holden.

Once the member is engaged, iCare’s care coordination team begins to identify unmet needs, she explained. “We want to know, ‘Is their life going well? Do they have appropriate medical care? Are they in a relationship with a primary care provider that they feel is co-respectful? Are they getting their answers to their questions?'”

To begin talking about medical needs, the care coordination team has to establish trust, said Holden. “We have to talk with the member in an honest way that reflects our respect for them and also engages them in order for them to tell us how they really feel.”

iCare uses the Patient Activation Measure tool to help identify where the member is in a spectrum of four different levels of activation. iCare then tailors its member engagement approach to build a trusting relationship and provide member education by recognizing where they are in their activation level.

Following up on preventive measures are key for the iCare care coordination model. Care coordinators reach out to members for care plan updates. The care plan has to be alive and very member-centric, said Holden. The health risk assessment is repeated each year and the care plan is updated based on those results.

iCare is also focusing on social determinants of health with the recognition that they impact a members’ health more than clinical care. Clinical care attributes to only about 20 percent of somebody’s health outcomes; the rest of that 80 percent is made up of by health behaviors, social and economic factors, and physical environment. “If we don’t get underneath those issues, we can ask for things to improve, but we’re going to see minimal success,” Holden added.

During the webinar, Holden also shared: how the care coordinators helps Medicaid members overcome barriers to care; seven rising risk/acuity identification tools; readmission prevention initiatives for high-risk patients; three programs aimed at reducing high emergency department utilization; and details on a Follow-to-Home program for members who are homeless. Holden also shared: details on language to use…and not to use…when engaging members; advice on the best time to connect with members by phone, such as time of day, specific days of the months; the role of the specialist interventionist compared to the care coordinator; and the background of iCare’s care coordinators and health coaches.

Click here to view the webinar today or order a DVD or CD of the conference proceedings.

Providers and ACO Data Analytics: Too Much Information Is Not Helpful

November 22nd, 2016 by Patricia Donovan
Add a different caption here.

Collaborative Health Systems believes the health data it distributes to its physicians should speak to the challenges providers see in the market.

As the largest sponsor of Medicare Shared Savings Program (MSSP) accountable care organizations (ACOs), Collaborative Health Systems (CHS) has learned a number of lessons about the integration of data analytics and technology. Here, Elena Tkachev, CHS director of ACO analytics, outlines three challenges her organization has faced in the rollout of health analytics to its provider base, and some CHS approaches to these hurdles.

What are some of the challenges we have identified, and some solutions? Number one is the availability and access to timely and accurate data. This has been a challenge for us. As an insurance company, we have a very strong expertise and access to the claims information Medicare provides to us, but we did face the challenge of incorporating electronic medical records (EMRs) into our data. We have been taking a phased approach, where we continue only adding and enhancing our data. If you are not at a point where you’re ready to consume everything, it doesn’t mean you should not do it until you have all the pieces together. It’s better to start with something and then you can grow from that point and improve it.

The second is related to the technology and capability—the ability to aggregate all this different data from different resources and have it be meaningful. For us, it’s really an investment in having strong technology data architect subject matter experts as well as the tools that can help us with that.

The third is display of meaningful results. This has been a challenge and we’ve reiterated it. Since I first started at CHS, the reports have drastically changed, because we learned from our providers that too much information is not helpful; just giving someone a spreadsheet with a lot of columns is not very useful.

Providers would rather see information summarized, and less is more. It’s really important to have information be very clear. The data needs to speak to the challenges the providers see in the market.

Source: Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results

http://hin.3dcartstores.com/Health-Analytics-in-Accountable-Care-Leveraging-Data-to-Transform-ACO-Performance-and-Results-_p_5185.html

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results documents the accomplishments of CHS’s 24 ACOs under the MSSP program, the crucial role of data analytics in CHS operations, and the many lessons learned as an early trailblazer in value-based care delivery.

HINfographic: The Rising Risk: Harvesting Population Health’s Low-Hanging Fruit

October 5th, 2016 by Melanie Matthews

Paramount to population health management success under risk-based contracts is strategic oversight of the ‘rising risk’—individuals with two or more unmanaged health conditions. One quarter of respondents to the 2016 Population Health Management survey by the Healthcare Intelligence Network zero in on their own ‘rising risk’ populations.

A new infographic by HIN examines the health risks served by population health management programs and how population health management services are delivered.

2016 Healthcare Benchmarks: Population Health Management2016 Healthcare Benchmarks: Population Health Management analyzes responses of more than 100 healthcare organizations to HIN’s third comprehensive industry survey on PHM trends administered in spring 2016. It delivers the latest metrics on current and future PHM initiatives, providing actionable data on the most effective PHM tools and workflows, risk identification strategies, communication and engagement tools, program delivery modalities, results and challenges, and much, much more.

2016 Healthcare Benchmarks: Population Health Management is supported with more than 50 graphs and tables and describes many successes respondents have achieved with a PHM approach. Participating organizations also weigh in on the sustainability of a population health management approach. Click here for more information.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Home Visits Validate Predictive Analytics and 10 More 2016 Risk Stratification Trends

August 30th, 2016 by Patricia Donovan

Assuring data integrity is the top challenge to health risk stratification, according to a July 2016 healthcare benchmarks survey.


Two key trends emerging from a July 2016 survey on Stratifying High-Risk Patients highlight the need to occasionally eschew sophisticated tools in favor of basic, face-to-face care coordination.

As one survey respondent noted, “A key element [of stratifying high-risk patients] is building a trusting face-to-face relationship with each patient, knowing what they want to work on, coaching them and activating them.”

The first learning gleaned from the survey’s 112 respondents is that, despite the prevalence of high-end risk predictors, algorithms and monitoring tools, clinicians must occasionally step into the patient’s world—that is, literally enter their home—in order to capture the individual’s total health picture.

Fifty-six percent of respondents make home visits to risk-stratified patients; a half dozen identified the home visit as its most successful intervention for risk-stratified populations.

That inside look at the patient environment illuminates data points an electronic health records (EHRs) might never bring to light, including socioeconomic factors like limited mobility that could prevent a patient from keeping a follow-up appointment.

“I never know until the moment I enter the home and actually see what the environment is like whether we correctly predicted the need for high intervention (and get a return on it),” commented one respondent.

The second trend in risk stratification is the emerging laser focus on ‘rising risk’ patients, an activity reported by 72 percent of respondents. This scrutiny of rising risk populations helps to prevention their migration to high-risk status, where complex and costly health episodes prevail.

Other data points identified by the 2016 Stratifying High-Risk Patients survey include the following:

  • Almost four-fifths of 2016 respondents have programs to stratify high-risk patients, and the infrastructures of more than half of these initiatives utilize clinical analytics, predictive algorithms, EHRs and other IT tools to manage care for high-risk patients.
  • The reigning health risk calculator continues to be the LACE tool (Length of stay, Acute admission, Charleston Comorbidity score, ED visits), used by 45 percent in 2016, versus 33 percent two years ago.
  • For more than a quarter of 2016 respondents, assuring data integrity remains a key challenge to risk prediction.
  • A case manager typically has primary responsibility for risk stratification, say 52 percent of respondents.
  • Diabetes is the most prevalent clinical condition among high-risk patients, say 47 percent.
  • At least 70 percent report reductions in hospitalizations and ER visits related to risk stratification efforts.
  • Improvement in the highly desirable metric of patient engagement is reported by 74 percent of respondents.

Click here to download an executive summary of survey results: Stratifying High-Risk Patients in 2016: As Risk Prediction Prevails, Industry Eyes Social Determinants, Rising Risk.

Health Coaching Success Metrics and 8 More Behavior Change Benchmarks

July 7th, 2016 by Patricia Donovan

Satisfied clients and participants on track for goal attainment are two hallmarks of a can't-lose coaching initiative.

Satisfied clients and participants on track for goal attainment are two hallmarks of a can’t-lose coaching initiative.

What are the hallmarks of a winning health coaching strategy? The answer depends on what’s being measured: the effectiveness of the individual coach, the participant’s progress, or overall program success.

That’s the feedback from 111 healthcare organizations responding to the 2016 Health Coaching Survey by the Healthcare Intelligence Network.

If you’re looking to measure the health coach’s success, then client satisfaction is the best indicator, say 27 percent of these respondents.

On the other hand, for a gauge of an individual’s progress, look to the participant’s goal attainment, report 78 percent.

This same metric—goal achievement—is also the best indicator of program success as a whole, agree 64 percent.

The May 2016 survey documented a number of other health coaching benchmarks, including the following:

  • Motivational interviewing is a coach’s top tactic to effect behavior change, say 83 percent.
  • All-important ‘face time’ with coaches is plentiful: 47 percent embed or co-locate health coaches at points of care, with most onsite coaching occurring in primary care offices (50 percent) or at employer work sites (50 percent).
  • Nine percent even embed health coaches in hospital emergency rooms.
  • While a majority focuses on coaching high-risk individuals with multiple chronic illnesses, 51 percent now extend eligibility for health coaching to individuals stratified as ‘rising risk.’
  • Nearly half of respondents—48 percent—offer health coaching to patients and health plan members with behavioral health diagnoses.
  • Reflecting the surge in telehealth, 12 percent of respondents offer video health coaching sessions to clients.

Download an executive summary of the 2016 Health Coaching survey.

2016 Population Health Management Snapshot: Most Interventions Telephonic and 9 More PHM Trends

May 19th, 2016 by Patricia Donovan

Most population health management interventions are conducted telephonically, according to HIN's latest PHM metrics.

The majority of outreach in the burgeoning field of population health management is delivered telephonically, according to 84 percent of respondents to an April 2016 Population Health Management (PHM) survey by the Healthcare Intelligence Network.

This third comprehensive PHM assessment also determined that data analytics use in population health management continues to rise, though more slowly than it did from 2012 to 2014, when EHR and registry use tripled.

Additionally, the survey found that 70 percent of respondents have committed to population health management, up from 56 percent in 2012. At the same time, many lament payor reluctance to cover essential PHM services like health coaching and group visits they see as critical to PHM success.

To accrue clinical and financial gains from PHM’s data-driven, risk-stratified care coordination approach, 90 percent provide chronic care management (CCM) services, a strategy that results in PHM ROI between 2:1 and 3:1 for 12 percent of these CCM adopters.

In condition-specific PHM metrics new for 2016, diabetes tops the list of health targets for PHM interventions, say 88 percent.

A health risk assessment (HRA) remains the primary instrument for identifying individuals for PHM interventions, say 70 percent, up from 64 percent in 2014.

Also paramount to PHM success under value-based healthcare reimbursement is strategic oversight of the ‘rising risk’— individuals with two or more unmanaged health conditions. One quarter of 2016 respondents focus PHM attention on their ‘rising risk’ populations, the April 2016 survey determined.

In recent years, population health management (PHM) has ranked as the healthcare space richest with opportunity, according to HIN’s annual industry trends snapshots.

Download an executive summary of 2016 Population Health Management survey results.

Horizon Episodes of Care Program Prototype for Value-Based Specialty Care and Reimbursement

April 21st, 2016 by Patricia Donovan

Horizon BCBS-NJ's Episodes of Care program engages specialists across a suite of nine episodes.

Imagine a value-based healthcare payment model in which the sole financial hazard to specialist providers is the risk of amassing additional revenue.

Further, envision a scenario in which these specialists are invited to design their payment program, from the model’s intent to key quality metrics.

Those are some highlights of Horizon Blue Cross Blue Shield of New Jersey’s Episodes of Care (EOC) program, a value-based model designed to focus specialists on the provision of quality- and value-based care across nine separate episodes, from joint replacement to hysterectomy to oncology.

Hailed as a national leader in advancing the episodes model as a prototype for value-based specialty care, Horizon is careful to distinguish its EOC program from a bundled payment initiative, for two key reasons.

“First, our EOC program is a quality-based program; it’s not only about the payment or payment structure,” explained Lili Brillstein, director of the Horizon Episodes of Care program during a recent webinar, Episodes of Care: Improving Clinical Outcomes and Reducing Total Cost of Care Through a Collaborative Payor-Provider Relationship.

Secondly, bundled payments typically refer to a prospective model in which a bundled amount of money is paid to a provider or group of providers in advance of services being delivered, while Horizon’s retrospective model pays providers after services have been provided.

The upside-only nature of Horizon’s retrospective model contributes to the program’s collaborative nature, Ms. Brillstein added. “If the metrics are met, savings are shared. If the metrics are not met, we’re not punishing our partners.”

There is other evidence of collaboration and of Horizon’s desire to see the providers succeed in the EOC program. One example is the payor’s use of case mix-adjusted budgets at the practice level rather than the prevalent member-specific risk-adjusted budgets. “This budgeting allows Horizon to create an opportunity for providers to move the needle [on a metric], and benefit from that. The opportunity for cost savings and shared savings also is dramatically improved.”

Another case in point is Horizon’s invitation to prospective providers to talk through the episode’s construct, intent and design prior to its launch.

Horizon’s engagement of providers in the EOC program has “changed the spirit of the relationships between the payor and the provider,” Ms. Brillstein noted. “It’s like nothing I’ve ever seen before. Our provider partners have become our ambassadors for the program.”

Select EOC results presented during the webinar indicated that outcomes are better for EOC partners—in the area of reduced readmissions, for example—than they are for physicians not in the EOC program.

Horizon expects to launch at least three more episodes in 2016, including a Crohn’s Disease episode that will take into account behavioral health services for those members. While the payor fully expects to move to a prospective model, it believes its current EOC model is preparing them for that eventuality, softening the transition from fee for service to prospective payments.

“[That transition] doesn’t just happen. You don’t sign the paper, and suddenly know what to do. It is an evolutionary transformative process,” concluded Ms. Brillstein.

Click here to listen to an interview with Lili Brillstein: Horizon BCBSNJ Episodes of Care: No-Risk Retrospective Model Paves Way for Value-Based Migration

CHS on Data Analytics in Accountable Care: “No Matter What Happens, This Change is Coming”

February 11th, 2016 by Patricia Donovan

Collaborative Health Systems, the largest sponsor of Medicare ACOs in the United States, recently rolled out an analytics and dashboard portal for its 3,200 providers.

Attention, please. Two aggressive milestones to migrate Medicare providers to value-based healthcare are on the horizon:

  • In 2016, CMS expects 30 percent of Medicare fee-for-service (FFS) reimbursement to be tied to alternative payment models such as accountable care and bundled payments.
  • Also this year, the federal payor wants 85 percent of Medicare FFS payments to be based upon quality metrics.

“If you are a provider, or working with providers who accept Medicare beneficiaries, it’s really important to know these changes are coming,” advises Elena Tkachev, director of ACO analytics for Collaborative Health Systems (CHS). “It will be the responsibility of physicians to participate in these payments because no matter what happens, this change is coming.”

Ms. Tkachev detailed the power of data analytics to drive CHS’s success in accountable care during Data Analytics in Accountable Care: Strategies and Case Studies, a January 2016 webinar from the Healthcare Intelligence Network now available for replay.

As the largest sponsor of Medicare Shared Savings Program (MSSP) ACOs in the United States, CHS has a firm handle on HHS’s value-based agenda. The organization manages 24 MSSP ACOs, nine of which generated savings of nearly $27 million in 2014, and one that has been accepted as a Next Generation ACO, the newest Medicare accountable care model.

And with CMS expectations for value-based reimbursement slated to rise over the next two years, expectations for data analytics to improve care and costs related to Medicare beneficiaries have never been higher.

“Today, physicians are being measured through claims and the clinical metrics on the population they serve. We see the main responsibility of analytics as providing simple access to actionable, timely and relevant information to help clinicians make better decisions, improve quality of care and enhance the patient experience.”

Despite the magnitude of its enterprise, CHS believes its future in accountable care rests upon its primary care physicians (PCPs), which it views as “quarterbacks of care” for its more than 280,000 Medicare beneficiaries.

To foster quality improvement, CHS equips PCPs with an arsenal of analytics capabilities. So that its 3,200 providers can tap into CHS’s massive storehouse of CMS, claims, lab, risk stratification and care coordination data collected on its 24 Medicare Shared Savings Program (MSSP) ACOs, the health system recently rolled out an analytics and dashboard portal.

These tools enable providers to monitor the aggregate health of their populations as well as their own performance, even giving providers the ability to track their own performance over time and contrast it with other clinicians’—a capability that pleases CHS’s more competitive physicians, Ms. Tkachev notes.

Frequent webinar training keeps provider analytics’ use sharp, and dashboard-generated reports and scorecards help physicians to monitor and enhance quality performance and improve patient outreach, Ms. Tkachev explained.

Despite its significant success, CHS still encounters the perennial challenges of access to timely and accurate data, aggregation abilities, and the display of meaningful results. Ms. Tkachev shared some CHS tactics to resolve these issues, including soliciting feedback on the tools from providers who use them.

Listen to an interview with Elena Tkachev on data analytic’s potential to drive annual wellness visits and boost beneficiary attribution.

Longitudinal Care Plans, Risk Scores Raise Patient Engagement for MSSP ACO’s Complex Population

October 6th, 2015 by Patricia Donovan

A top-performing MSSP in 2014, the Memorial Hermann ACO has successfully engaged its Complex Care population via a collaborative care coordination approach.

The Memorial Hermann ACO may have been one of 2014’s top-performing Medicare Shared Savings Programs (MSSPs), but the health system’s commitment to achieving quality outcomes was solidified more than eight years ago, when its own physicians asked for a clinically integrated physician network.

Memorial Hermann complied, developing a set of tools, training and care models to not only support the physicians but also reflect payors’ needs: chief among them, initiatives that could boost patient engagement.

Today, the Memorial Hermann ACO has a patient-centered care delivery strategy built on teamwork and collaboration. The Texas ACO is proud to point to a patient engagement rate of 74 percent for individuals enrolled in Complex Care, an initiative for individuals with long-term, multiple chronic conditions that has significantly reduced cost and hospital lengths of stay for participants.

This patient engagement measure represents members who consent to participate in the program and remain engaged for 30 days, explained Mary Folladori, RN, MSN, FACM, CMAC, system director of care management at Memorial Hermann Physician Network and ACO, during Care Coordination in an ACO: Managing the Population Health Continuum from Wellness to End-of-Life, a September 2015 webinar from the Healthcare Intelligence Network now available for replay.

Ms. Folladori provided an overview of the ACO’s care coordination strategy that in 2014 generated savings of nearly $53 million in the MSSP program, resulting in a health system payout of almost $23 million. The ACO’s performance earned Memorial Hermann a MSSP quality score of 88 percent.

Some high points from Memorial Hermann’s ACO strategy include the following:

  • Embedding of care coordinators into the ‘micro culture’ of a physician practice, its community and the members served by the practice;
  • Strategic use of a data warehouse to identify vulnerable members early and link them with needed health services;
  • Development of comprehensive risk scores derived from multiple sources for Complex Care patients; and
  • Creation of longitudinal care plans that follow Complex Care patients for up to 18 months and help to transition them back to a baseline level of functioning.

In wrapping up observations on Memorial Hermann’s quality-driven approach, Ms. Folladori quoted its CEO, Chris Lloyd: “The success that has been found within our ACO is deeply based on a collaborative approach to care. It has been cultivated over eight years with our commitment to clinical integration. We all strongly believe that without that strong clinically integrated physician network, without our physicians driving those quality outcomes, we would not have been as successful as we have.”

With so much emphasis on quality and outcomes, it’s no wonder participation today in the Memorial Hermann ACO is by invitation only—and only after a practice has passed an assessment.