Those who came to Miami, Florida, for the second live meeting of the ACO and Emerging Healthcare Delivery Coalition voiced these favorable assessments and more about their experience, which was shared among 50 attendees at the Marriott Biscayne Bay on October 16 and 17, 2014.

But if a single word could capture the response, it would be “opportunity.” The value of this gathering, as with the first one in May, will last well beyond the conclusion of the sessions. Small workshops and networking allowed members from a diverse group of accountable care organizations (ACOs)—large and small, new and well established&mdash;to share ideas, make connections, and perhaps form partnerships that will prove valuable in changing times. Learning together and learning from one another&mdash;both are reasons 

 created the Coalition, which has grown to more than 130 members in less than a year.

Typical meetings in healthcare involve only health plan leaders, or only IT people, or only providers. 

’s ACO Coalition stands apart because it puts everyone in the same room to share perspectives—in some cases, for the first time. “Feedback from our participants has been tremendous,” said Brian Haug, president of AJMC and event host. “Our meeting provides a rare opportunity for healthcare leaders from different parts of the system to come together. These exchanges are where meaningful change can occur.”

“Tell us something we don’t know about you.”

With that introduction, moderator Leonard Fromer, MD, FAAFP, executive medical director of Group Practice Forum, set in motion each speaker’s presentation or panelist’s contribution, giving the room a sense of openness and informality despite the remarkable level of expertise present.

Among those taking part were Ira Klein, MD, MBA, FACP, chief medical officer, National Accounts Clinical Sales and Strategy, Aetna; Thomas Graf, MD, and Eric Newman, MD, both with Geisinger Health System; John Jesser, MBA, of LiveHealth Online at WellPoint; and Krista Drobac, who within a month of the meeting would form Sirona Strategies as the new home of the Alliance for Connected Care.

Based on feedback from prior sessions, many of the presentations and workshops in Miami concerned technology and data: how to collect it, how to use it, who owns it, and whether the data points being gathered are even the right ones. Fromer worked to put both speakers and panelists at ease, laying the groundwork for the workshops that would follow.

By October, some participants were starting to see results of interventions for patients with chronic conditions, which were required under the 2010 Affordable Care Act (ACA), and they were ready to start framing their own definitions for the term “population health.”

As speaker Bruce Bagley, MD, FAAFP, president and CEO of TransforMED, said, “Population health is code for identifying the 5 to 7% of people who are costing the most money and figuring out what to do.”

Bagley and other speakers said achieving this requires a reengineering of the primary care practice, including a concentrated effort to take certain tasks off the plates of primary care physicians (PCPs), not only for the purpose of focusing their attention on atrisk patients, but also to improve their quality of life. “We have to redesign the system so we don’t burn out the people trying to do good work,” he said.

As Fromer noted later on, the common denominator of the many stakeholders is “measurement.” All things—perhaps too many things&mdash;are being measured, but ACOs are in the midst of figuring out how to cope with that situation. A multitude of challenges exist in making the massive transition from a volume-based payment model to one based on value, Fromer said, but ACOs are starting to meet them.

“The biggest idea, or output, I think, was revolving around real movement in achieving better triple-aim results, and scores, for patients we take care of in ACO settings,” he said.

Among the challenges ACOs face is the need to improve healthcare measures despite a shortage of PCPs. The patient population is aging, yet many patients, especially those who are still working, are busier than ever. Drobac presented opportunities that could come with expanded use of telehealth, which would involve more virtual appointments via Web-based technology.

More than 14,000 Medicare patients tried telehealth in 2013, Drobac said, and data show that those who tried it overwhelmingly liked it. Yet regulatory limits on telehealth have curtailed its ability to boost access to care for rural Americans, those with disabilities, or employees who don’t want to lose time from work.

As Drobac explained, current constraints limit the ability of ACOs to receive Medicare reimbursement for telehealth encounters, even though evidence of its effectiveness justifies payment. Meanwhile, resistance from some state medical associations to changes that would allow physicians to practice outside their home state have also limited telehealth’s growth.

Momentum for telehealth is building with the arrival of “wearable” healthcare technology, which Drobac said consumers have embraced. “The opportunity is ripe right now,” she said.

The heart of the gathering—and a favorite of attendees, based on feedback&mdash;were small workshops gathering a dozen participants each, lasting roughly a half hour, which allowed for a rapid exchange of ideas. Topics were tied to the material in main presentations, but the looser format seemed more like a seminar; here, participants learned more about and from each other.

Kelly Conroy of Triple Aim Development Group, West Palm Beach, Florida, began a session on financial incentives by describing the ACO landscape in her state. There are many organizations that are technically competitors, she said, but the staffs do not “feel like we [are] in competition.” Participants shared the lessons they’ve learned so far. Success of ACOs must be “outcome-driven,” and there must be a focus on developing good incentive structures that are fair and targeted toward those participants who have truly made changes in their practices. The worst thing to do, participants said, is to “give a big check” to physicians who have failed to change poor behavior. If an ACO wants to reward the best performers, data to determine who performs well will have to be collected at the ACO level.

Taking the time to track individual physician performance will likely prove worthwhile: many participants said that doctors are highly competitive with one another and will change their behavior if they know how their performance ranks within the ACO.

 The group spent some time discussing physician “citizenship,” also called “physicianship.” Measures of physicianship include, for example, how willing the doctor is to be part of a practice team, or to cover a shift for another doctor etc. There was some discussion about how this would relate to the ability to improve patient satisfaction ratings.

Attendees offered ideas to persuade physicians to participate in committee work that will be needed for the transition to value-based care, including financial incentives. One metric to track—and one which must be rewarded&mdash;is noting which doctors are willing to stay late at a practice to see a patient who would otherwise head to the emergency department. To build this willingness, one speaker said, the ACO must be sure that if the doctor stays, there are also specialists on call to consult, imaging services available, etc.

Patient engagement continues to be a challenge. Participants discussed the importance of engaging PCPs first, because unless that happens, “We have no chance to engage the patient.” Throughout the meeting, the need to engage PCPs, and the difficulty this presents, came up repeatedly.

 Drobac led this session, which began with the observation that the focus on Big Data in healthcare IT should perhaps be a focus on gathering the right data; some attendees wondered whether the data points typically gathered in an electronic health record always make sense. When there are too many “bells and whistles,” medical practitioners who are trying to use the data can be overwhelmed.

ACOs are still working to figure out what data are needed to properly run their organizations without asking so much that doctors feel bombarded. Requests from pharmaceutical companies complicate matters, with varying requests from each. As ACOs step into specialty pharmacy, they are greeted with all the data requirements for post marketing research, which is required by the FDA. Meeting these requests, and sharing data to achieve desired outcomes, have to be balanced with HIPAA requirements.

A key test is ensuring that data can be gathered in the course of normal work flow; staff, software, and procedures must be properly coordinated so that data are not being pulled from records after the fact.

The world of Big Data in healthcare is still unfolding, and many policy questions remain unsettled. Who pays for data gathering? Who owns the data? Once questions of how to share are resolved, how much do you share? Are the answers the same for practices owned by an ACO compared with those that are only affiliated? Drobac asked whether there should be a Choosing Wisely for data, referring to the well-regarded American Board of Internal Medicine initiative that seeks to reduce wasteful, harmful practices across medical specialties.

Friday’s sessions exemplified the valuable professional opportunities offered by the ACO Coalition: Graf, chief medical officer for population health and longitudinal care service lines at Geisinger, first gave a detailed keynote address outlining one of the best known models for value-based care. Then, he led one of the small workshops on the patient experience, a wide-ranging discussion that took turns into such details as workers’ compensation.

Geisinger, which operates throughout central Pennsylvania, uses technology and automation to help providers cover much of wellness care; the more a patient suffers from chronic conditions or comorbidities, the more “hands-on” the model becomes. The model offers a variety of settings for patients to receive primary care treatment. Great emphasis is placed on collecting data and teaching office staff to use it, Graf said, so the PCP has 2 core functions: handling complex medical decision making, and maintaining patient relationships.

In the process, Geisinger has not only shown profitable results—Graf pointed to data showing return on investment is $1.70 for every $1 put into the system&mdash;but healthcare measures have also improved sharply over 8 years. For example, more patients with diabetes are receiving vaccinations; more are at goal for blood pressure, cholesterol, and glycated hemoglobin; and more are documented nonsmokers.

“We’ve moved from providing great care one patient at a time, to great care 1 patient at a time to an entire population,” Graf said.

When ACOs were created by the ACA, they were intended to do more than simply provide insurance coverage. ACOs are vehicles designed to keep track of patients’ healthcare experiences, and to reward those entities that provide the better ones. Thus, if ACOs work as designed, even though they seek healthcare savings, they should not give doctors or hospitals incentives to cut corners or deny care, which was the complaint about the health maintenance organizations (HMOs) of the 1990s.

Quality of care and patient satisfaction measures exist alongside savings—the so-called “triple aim.” Putting these patient-centered measures on equal footing with financial performance is a meaningful break from past efforts, according to speakers and participants at the meeting who took part in 1990s reform efforts. Twenty years ago, HMOs formed to aggregate risk without a clear understanding of how to take on that risk. Today’s efforts are not just about managing risk, in contrast to the 1990s when some patients were left out of networks or denied coverage.

Effective ACOs have the ability to engage PCPs, especially by helping them make positive changes in the way they run their practices. Helping physicians free up their time and better deploy staff in both care and decision making should, in time, improve the bottom line and the quality of life for PCPs, who are in short supply. But first, PCPs have to be firmly convinced that ACOs are for their benefit.

“Without primary care engagement, we are simply spinning our wheels,” said Richard Lubicella, MS, MBA, the CEO of Accountable Care Options, LLC, a Florida ACO. “The primary care physicians will engage the patients for you if they are engaged.”

Thus, future ACO Coalition topics will include patient incentives to select PCPs, as well as the challenge of “attribution,” which is the matter of deciding which patients are assigned to the ACO in the first place.

To learn more about the ACO and Emerging Healthcare Coalition, contact ACO_Coaltion@ajmc.com or visit http://www.ajmc.com/acocoalition.

 Mary K. Caffrey is the managing editor of the Evidence-Based series at 

 Mary K. Caffrey, 666 Plainsboro Rd, Suite 300, Plainsboro, NJ 08536. E-mail: 

Articles

As the ACO and Emerging Healthcare Delivery Coalition gather in Miami, results are coming in, and it's time to figure out just what to measure.

For ACOs Large and Small, Sharing Ideas With an Open Mind

 Evidence-based preventive care is vastly underutilized in the United States, but is necessary to decrease morbidity and mortality. Personalization is essential for successful preventive care implementation. We developed and tested the feasibility of a new program for providing personalized and patient-centered preventive care in a busy, urban ambulatory clinic. We designed our program to be compatible with emerging care models, including the patient-centered medical home model, and to be applicable to diverse pointof- care settings.

: Pilot-study program with matched controls.

 Participants were 73 nonpregnant adult clinic patients with 73 matched controls from Bellevue Medical Center Ambulatory Care Clinic with the greatest estimated benefit from improvements in adherence to evidence-based preventive care. We used a validated mathematical model based on US Preventive Services Task Force recommendations to quantify and rank the estimated amount of health benefit that would arise from improved adherence to each preventive care guideline. We communicated these personalized estimates graphically to patients. Finally, we engaged the patient in a shared decision making process in which the patient identified which preventive health goals he aimed to achieve, and we set particular action steps to be taken before the next visit that were congruent with these goals.

 The program appeared feasible in a busy urban clinic, with no major workflow disruptions and qualitative acceptability to patients and practitioners. There was a trend towards increased life expectancy for program versus control patients by 12.0 months compared with 6.7 months (

 = .07), and program participants experienced greater improvements in smoking cessation (

 It appears feasible to implement a program that enhances personalized and patient-centered preventive care at a busy urban primary care clinic, and that may be associated with improved health outcomes.Although preventable morbidity and mortality in the United States is substantive, evidence-based preventive care is underutilized, as seen in the underutilization of the 60 distinct services recommended by the US Preventive Services Task Force (USPSTF).

 For example, only 48% of patients are screened for colorectal cancer, 40% of qualified patients take aspirin, and 28% of patients receive help to quit smoking.

 Further, health disparities are worsened due to unequal distribution of preventive care.

These preventive care deficits may arise partially from limited time for clinicians and patients to address relevant issues.

 Additionally, recommendations for the best patient-centered care

 will sometimes differ from patient to patient, adding further complexity. For example, a general clinical quality metric may encourage tight blood sugar control for a frail 80-year-old female with diabetes, when in practice, for her particular situation, this recommendation might cause more harm than benefit or conflict with her preferences.

It is increasingly appreciated that while primary care should become more personalized and patient-centered, time constraints may oppose these goals. Therefore, our objective was to develop and test the feasibility of a new program for providing personalized and patient-centered preventive care in a busy urban ambulatory clinic. We designed our program to be compatible with emerging care models, including the patient-centered medical home model, and to be applicable to diverse point-of-care settings.

Our program was constructed around the following framework: 1) identify patients who could most benefit from improvements in adherence to preventive care; 2) use a validated mathematical model

 to quantify and rank the estimated health benefit from improved adherence to each USPSTF guideline, personalizing estimates based on risk factors and medical history; 3) communicate this information in a manner reflecting insights from risk communication studies

 on patients with low literacy and numeracy; 4) perform shared decision making so the patient chooses preventive health goals aligned with his preferences (for example, lose 30 pounds); and 5) designate action steps to reach those goals (for example, use 9-inch dinner plates rather than larger ones to make food portions fill the plate and visually seem larger).

We employed this framework at Bellevue Medical Center, a safety net center in New York City, New York, with an extremely diverse population: the breakdown is 45% Hispanic; 40% African American, African, or Caribbean; and 10% Asian American; and patients can receive on-demand medical interpretation in 17 languages including Fukinese, Bengali, and Haitian Creole. The Adult Primary Care Center (APCC) at Bellevue has busy clinician loads, complex patients in great need of preventive care, and a recent designation as a patient-centered medical home. Our program supplemented rather than substituted for normally scheduled primary care visits, and was coordinated with these visits whenever possible. It began in May 2012, with intent to pilot for 15 months (3 months enrollment, 12 months follow-up) until August 2013. However, because of the 3-month disruption of operations from Superstorm Sandy, recruitment was extended until November 2013.

Identifying patients who could benefit most from improvements in preventive care

We employed a Markov model that estimates the differences in life expectancy with and without preventive guideline implementation.

 The model is able to consider the impact of all preventive guidelines rated as “A” or “B” by the USPSTF that are applicable to a particular patient, and estimates downstream effects on mortality that are personalized based on an individual’s demographics and risk-factor profile. Its design is described in more detail elsewhere.

Patients with 1 or more years of potential life expectancy gain (approximately 20% of APCC outpatients) were invited to participate in a quality improvement program intended to personalize and patient-center their care. Patients met this inclusion criterion if they had 1 or more of the following attributes: body mass index >30, hypertension, tobacco use, alcohol dependency, cardiovascular disease but not taking aspirin, or a strong family history of breast cancer. Most patients were prescreened for eligibility using electronic medical records (EMRs). We excluded patients with dominant comorbidities like active cancer or advanced renal disease. The program was endorsed by most primary care providers (PCPs) practicing at the site.

Communicating information in a manner informed by risk communication literature

To ensure that patients had adequate time to understand the personalized information and to make shared decisions, each visit lasted 40 to 60 minutes, split between a nurse practitioner (NP) session and a health coach (HC) session, with oversight from a physician (MD). Scheduled patient visits were monthly for the first 3 months, and then every 3 months for a total duration of 12 months. Additionally, contact was attempted at biweekly intervals between visits by phone call or postcard (for patients without reliable phone numbers). At the initial visit, the NP obtained a full health history. Data were inputted into the mathematical model, and the NP discussed that patient’s personalized results with the aid of a patient-friendly graph that prioritized recommendations and the correlated potential gains in life-years (

), and was developed with a risk-communication expert (author AF).

Engaging the patient in a shared decision-making process The patient and NP engaged in shared decision making

 to decide which health recommendations the patient would work on for the next visit. The NP facilitated implementation of these recommendations, including medication adjustments, ordering screening exams, and specialty referrals if needed.

The HC session immediately followed the NP session, aiming to set specific goals and action steps corresponding to the health recommendations endorsed during the NP session. Motivational interviewing techniques were again used, and the patient ended the visit with clear, specific goals. Each patient could designate 1 or more goals. These goals were written, laminated, and presented in a leather binder to add gravitas and symbols of appreciation. Other important educational materials and resources were provided to the patient, such as recommendations of healthy foods, logs to record their food choices, and lists of gyms near their residence. A copy of the patient’s graph was left in their PCP’s mailbox, and EMR notes were documented by the NP and HC.

At follow-up visits, the patient’s goal achievement (or lack thereof) was updated into the model along with their new vital signs, lab work, screenings, and medication changes that occurred since their last visit. If the patient made improvements to their health since the last visit, a smiley-face image was visible on the graph (Figure), symbolizing their accomplishments. Updated reports were provided to the patient’s PCP.

Because our program of personalized and patient-centered care was a quality improvement project rather than extramurally funded research, we did not employ validated measures or systematic transcripts to assess feasibility. Instead, we sought to note whether there were (1) disruptions to clinician or to clinic workflow, (2) subjective acceptance of the program by patients, and (3) subjective acceptance of the program by PCPs.

Although we did not have sufficient statistical power to detect clinically significant differences in process or outcome measures, we did seek to identify trends in these measures. Accordingly, we prespecified a control group of patients who also met program inclusion criteria and expressed interest in attending, but who were unable to attend because of scheduling constraints. Each control patient was matched with an intervention patient based on their date of clinic initiation so they would have a similar duration of follow-up, and similarly timed exposure to the 3-month service disruption caused by Superstorm Sandy.

For the 73 patients enrolled in the program, the median follow-up was 9 months. Their mean age was 54.6 years, 60.3% were female, and they were ethnically diverse: 23.2% black (African American), 10.6% white (non-Hispanic), 47.1% Hispanic (non-black), and 14.7% Asian. Of all patients, 38.4% attended only 1 visit; 16.4%, 2 visits; 16.4%, 3 visits; 8.2%, 4 visits; and 20.5% had 5 or more visits. The most prevalent preventive care goals were reducing obesity (76.7%, N = 56), reducing hypertension (74%, N = 57), diabetes control (47.0%, N = 35), lipid control (38.4%, N = 28), and tobacco cessation (9.6%, N = 7).

There was generally a positive response from patients and PCPs. Only 2 of 12 PCPs opted out of involvement, anecdotally concerned about loss of professional autonomy regarding management of their patients. Work flow disruption issues were minimal because program personnel scheduled visits around the PCP schedule. Patients were proud of their charts and folders and returned with them at follow-up visits.

Motivational interviewing and shared decision making were well received, with those patients motivated to take the most responsibility for their own care making the greatest improvements. For example, after the first program visit of a 40-year-old female of Mexican descent with borderline diabetes and non-alcoholic fatty liver disease, shared decisions resulted in goals directed at reducing obesity, managing hyperlipidemia, and consuming a healthier diet, with an estimated 4 years, 3 months potential gain in life expectancy. She has since lost 32 pounds and has controlled her hyperlipidemia through dietary changes. Her glycated hemoglobin and liver function tests are now normal. She feels well and energetic, and has added an estimated 4 years, 1 month to her life expectancy. She states, “My grandfather was sick with diabetes and I don’t want this disease in my life, so I worked so hard to control and change my diet through this clinic so that I won’t get diabetes or have problems again with fatty liver. I’m not watching my food because I want to lose pounds or be a Barbie [doll]—I’m doing it for my health in the future. When I first came here I ate heavy food every day, and now when I eat heavy food I don’t like it and I notice the difference.”

Although this pilot study has insufficient power to detect clinically significant improvements in outcomes, we observed positive trends. Compared with control patients, program patients had a similar distribution of preventive care objectives and burdens (

). Participants extended their life expectancy by an additional 5.3 months compared with the control group (

 = .07), and they had increased rates of smoking cessation (

We have implemented a program personalizing and patient-centering care at a busy urban clinic, and our experience suggests the approach is feasible. Our program not only provides personalized information, but patient-centers the decision making to promote active participation in setting and prioritizing health goals.

Prior to program initiation, many clinicians and health policy experts warned us that it would be infeasible to construct a program requiring 40- to 60-minute office visits. We have demonstrated that these predictions were incorrect. Furthermore, we note that the same activities could be accomplished more cost-effectively through additional task shifting: clinic staff could obtain vital signs and utilize routine questionnaires to get results to input into the mathematical model, and a health navigator could coordinate specialty appointments and resolve other logistical burdens (potentially saving 10 minutes each of NP time and HC time). In other words, what was a 60-minute visit divided between NP and HC with MD supervision could be transformed into a visit with those 60 minutes allocated more efficiently and less expensively by task shifting to lesser-skilled personnel: 5 to 10 minutes technician time, 20 minutes NP time, 20 minutes HC time, and 10 to 15 minutes navigator time. Also of note, any program that achieves and sustains a life expectancy increase of 5.3 months would offer favorable value if its additional expenditures (including downstream costs) are lower than $44,000 per patient per year,

which appears to greatly exceed the costs of our program.

Because program visits were longer than PCP visits, we were unable to discern how much of the improvement in performance was simply due to additional time spent with patients. Future work should allow us to do so. Additionally, while we lacked prespecified quantitative feasibility measures, such as time/motion studies and satisfaction surveys (a situation common to other quality improvement projects), we were able to identify a control group that was closely matched to the participants, and thereby may have avoided overestimation of health benefit because of selection bias or regression to the mean.

We have developed and implemented a program to enhance personalized and patient-centered preventive care at a busy urban primary care clinic. It appears to be feasible and well accepted by patients and practitioners.

 Institutional funds from the New York University Department of Population Health.

 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.

 Melanie Applegate, MSN, FNP, NYU School of Medicine, Department of Population Health, 550 First Ave, VZ30, 6th Fl, 628V, New York, NY 10016. Phone: (646) 501-2554. Fax: (646) 501-2706. E-mail: 

1. Published recommendations. 2004. US Preventive Services Task Force website. http://www.uspreventiveservicestaskforce.org/BrowseRec/Index. Accessed December 2, 2014.

2. Tai-Seale M, McGuire TG, Zhang W. Time allocation in primary care office visits.Health Serv Res. 2007;42(5):1871-1894.

3. Yarnall KS, Pollak KI, Østbye T, Krause KM, Michener JL. Primary care: is there enough time for prevention? Am J Public Health. 2003;93(4):635-641.

4. National Commission on Prevention Priorities/Partnership for Prevention. Preventive Care: A National Profile on Use, Disparities, and Health Benefits. Washington, DC: Partnership for Prevention; 2007:1-43.

5. Maciosek MV, Coffield AB, Edwards NM, Flottemesch TJ, Goodman MJ, Solberg LI. Priorities among effective clinical preventive services: results of a systematic review and analysis. Am J Prev Med. 2006;31(1):52-61.

6. Robinson JH, Callister LC, Berry JA, Dearing KA. Patient-centered care and adherence: definitions and applications to improve outcomes. J Am Acad Nurse Pract. 2008;20(12):600-607.

7. Braithwaite RS, Fiellin D, Justice AC. The payoff time: a flexible framework to help clinicians decide when patients with comorbid disease are not likely to benefit from practice guidelines. Med Care. 2009;47(6):610-617.

8. Braithwaite RS. Can life expectancy and QALYs be improved by a framework for deciding whether to apply clinical guidelines to patients with severe comorbid disease? Med Decis Making. 2011;31(4):582-595.

9. Taksler GB, Keshner M, Fagerlin A, Hajizadeh N, Braithwaite RS. Personalized estimates of benefit from preventive care guidelines: a proof of concept. Ann Intern Med. 2013;159(3):161-168.

10. Andrulis DP, Brach C. Integrating literacy, culture and language to improve health care quality for diverse populations. Am J Health Behav. 2007;31(suppl 1):S122-S133.

11. Epstein RM, Alper BS, Quill TE. Communicating evidence for participatory decision making. JAMA. 2004;291(19):2359-2366.

12. Emmons KM, Rollnick S. Motivational interviewing in health care settings. opportunities and limitations. Am J Prev Med. 2001;20(1):68-74.

13. Braithwaite RS, Meltzer DO, King JT Jr, Leslie D, Roberts MS. What does the value of modern medicine say about the $50,000 per quality-adjusted life-year decision rule? Med Care. 2008:46(4):349-356.

The American Journal of Accountable Care

Program that enhances personalized and patient-centered preventive care at a busy inner-city primary care clinic may be associated with improved health outcomes.

Pilot-Testing a New Program for Providing Personalized and Patient-Centered Preventive Care

To test a novel model of primary care designed to improve healthcare outcomes.

 We used literature searches, data analytics, and interviews with high-performing physicians to create the Accountable Primary Care Model. We enhanced the “4 Cs” Primary Care Model (first contact; comprehensive care; continuous care; coordinated care) with the addition of 5 more Cs: physician credibility, collaborative learning, cost-effectiveness, capacity expansion, and career satisfaction. Then, using a retrospective quasi-experimental design, we compared 3 years of outcomes data from members in a Medicare Advantage plan in a virtually integrated delivery system with relevant benchmarks, including matched patients in fee-for-service Medicare.

The Medicare Advantage health plan averaged 29,556 members with costs that were 58.93% of those in fee-for-service Medicare. Spending was shifted when appropriate from inpatient to outpatient settings and from specialists to primary care physicians. After allocating $80 per member per month for primary care costs, the health plan had medical cost ratios from 2010 to 2012 averaging 72.7% before surplus distribution. Member benefits were the best in the market, evidenced by the average maximum out-of-pocket expense limit of $1875. The next best plans averaged $2800. The health plan was rated 4.5 stars each year by CMS for quality, patient experience, access to care, and care process metrics. Of the primary care physicians surveyed, 90.2% would probably or definitely recommend this plan to another physician. About 91.4% of specialists surveyed were satisfied or very satisfied with this plan.

 The Accountable Primary Care Model offers improved clinical outcomes, cost, and patient satisfaction—the Triple Aim formulated by the Institute for Healthcare Improvement&mdash;along with the additional aim of physician satisfaction. It is the Triple Aim Plus One.

Volume-based reimbursement has limited the deployment of the Institute of Medicine/Starfield’s Primary Care Model (including the 4 Cs: first contact; comprehensive care; continuous care; coordinated care)

 despite its better healthcare outcomes at lower costs and validation of an assessment tool.

 Emerging evidence from controlled trials of the Patient Centered Medical Home (PCMH) model 3 to 5 years post implementation shows that it has produced little, if any, savings in the total cost of care. For example, Friedberg et al published a controlled trial 3 years after implementation of the PCMH for 39,559 patients in a multi-payer environment and found no total cost savings.

 Analysis of the retrospective study by Flottemesch et al reveals that a 10% increase in the Patient Practice Connections Readiness Survey (a proxy for medical home-ness) correlates with a 0.35% reduction in total annual costs of care for 58,391 patients with diabetes during years 3 through 5 post implementation.

 Wang et al found no significant changes in total medical costs during the third year post implementation of the PCMH in 1891 patients with diabetes.

 Furthermore, none of these studies includes the cost of supporting the PCMH, estimated to be $148,347 to $163,347 annually per primary care physician (PCP).

To enable physician transformation to accountability, Lumeris developed the Accountable Primary Care (APC) Model. Lumeris is a company that designs, builds, operates, measures, and optimizes value-based care models. This model embraces the 4 columns (Cs), or pillars, that support the Institute of Medicine/Starfield Primary Care Model,

 and contributes 5 additional Cs. The goal of this model is to foster the Institute for Healthcare Improvement’s Triple Aim of improved clinical outcomes, cost, and patient satisfaction, along with the additional aim of physician satisfaction—it is the Triple Aim

The APC Model is built on the Lumeris data analytics department’s multivariate regression analysis of relationships between 23 hypothesized variables and the medical cost ratio to discover critical success factors. We also contracted with the Olin School of Business at Washington University in St. Louis for an independent discovery of critical success factors. They utilized multivariate regression analysis to identify the 13 most important independent variables that impacted cost/revenue ratios at the PCP level. They then used forecast error variance decomposition of 2010 data to validate the model they generated from 2009 data. In addition, in 2012, the primary author of this manuscript interviewed 10 high-performing PCPs and hospitalists with more than 200 years of collective experience in diverse settings such as medical groups, independent practice associations, and a physician-hospital organization. The high-performing physicians were identified based on Lumeris internal data analytics focusing on population health quality metrics, patient satisfaction, and costs of care. During the same time period, this author performed Google Scholar searches of the grey and medical literature about topics and synonyms related to the 9Cs. He then searched the references in, and the articles citing, each study, as appropriate. After obtaining full text copies of the 1377 articles that passed initial screening, he reviewed each, analyzed the key findings, and integrated them into coherent themes. All of this information informed the development of the APC model as we utilized qualitative interpretative analyses to discover larger meaning and theory.

The APC Model has 4 levels. Level 0 is no PCP engagement, or the absence of accountability; PCPs are paid one-off for piecework. Levels 1, 2, and 3 represent low, medium, and high PCP engagement, respectively. Organizations may progress through these levels sequentially. Some organizations will have aspects of more than 1 level of the model implemented at the same time. Each level is implemented through a playbook that includes granular and specific actions for 8 different actors—the types being: administrator; analyst; care manager; chief medical officer; office staff (registered nurse, medical assistant); primary care physician/ nurse practitioner/physician assistant; population health manager; and regional medical director&mdash;and roles in the healthcare system by day, week, month, and quarter.

 refers to the patient’s initial entry point into the healthcare system. When new health or medical needs arise, it is usually optimal for the first contact to be with the PCP. In a nationally representative sample of more than 20,000 episodes of care, episodes that began with PCP visits, as opposed to some other source of care in the system, were ultimately 53% less costly. Controlling for emergency department (ED) visits, health status, sociodemographics, and other relevant variables did not materially change this cost differential.

 means PCPs offer a large range of services across the spectrum of patient care needs, for all but the most uncommon problems. With the APC Model, office visits for older or more complex patients are usually scheduled for 30 minutes to proactively address both manifest and latent issues. Longer visits also enable compliant documentation and accurate diagnosis coding for comprehensive health risk status assessments. These assessments enable claims-enhanced, data-driven collaborative population management, as well as appropriate risk-adjusted revenue assignment in Medicare Advantage (MA) and many accountable care organizations, Medicaid, and state insurance exchange programs.

C3: Continuous, longitudinal, person-focused care

 means that PCPs and patients work together in the context of longstanding relationships to reach mutual decisions that transcend episodic care. Accountable PCPs tend to follow their patients across care settings as they attend to their care in hospitals, nursing homes, and hospices. Person-focused care includes discussing expectations, discerning preferences, setting priorities, and engaging with family, as well as the usual personalized prevention, screening, and advance care planning.

 is widely admired but narrowly understood and practiced in the United States. Transitions to and from EDs, inpatient facilities, and skilled nursing facilities are obvious high-stakes care coordination opportunities. Half of Medicare beneficiaries have 5 or more chronic conditions.

 And every referral to a specialist—with accompanying requirements for information transfers, medication reconciliations, and adjustments to the patient’s overall care plan&mdash; may be viewed as a type of care transition. Accountable PCPs, those practicing at the top of their professional training and providing comprehensive primary care, decrease the number of care coordination events as they enhance patient convenience.

primary care earns patients’ trust in the PCP’s competence, beneficence, and professionalism. The strategic significance of this high level of trust is manifest as patients are willing to place confidence in PCP recommendations that may run contrary to their expectations or apparent wishes. Credibility is needed to counter the prevailing currents of Internet-driven consumerism and supply-sensitive care, which tend to undermine PCPs’ authority as they promote patient-specific and individually designed care agendas. PCPs earn credibility with patients primarily by providing the first 4 Cs, but also by honoring patients’ perspectives with active listening and respectful explanations, and by their professionalism in providing excellent customer service.

One accountable PCP said that without credibility, physicians are nothing but referral clerks. Patients who do not trust their PCPs often want their care from specialists, even for health problems within the realm of primary care.

 requires cooperation across institutional roles, organizational boundaries, and care settings. Both PCPs and the integrators

 of the healthcare system (often the payer or hospital) make important contributions. Payers contribute clinical and claims data transparency aggregated from across the continuum of care. Clinicians perform the work of augmenting this shared, actionable longitudinal information with their own patient data. Clinicians' knowledge of their patients is complementary to payers'. It is more nuanced (as it includes patients' current preferences) but incomplete in its breadth. The system integrator typically funds the analytics, while clinicians engage with the resulting rules-based clinical decision support messages. These 2 parties also take accountability for various tasks and responsibilities in collaborative population management, built on a foundation of collaborative learning and trust.

 naturally results from the other Cs, but it is enhanced by proactive, intentional PCP-led efforts. These are empowered by important infrastructure items that help dedicated care teams succeed: educational programs, care management, clinical quality and cost data sharing, opportunity analyses, and clinical decision support from the integrator. Cost-effective care is the embodiment of the Triple Aim 

One, as it optimizes the trade offs among population health, patient experience, and cost for each healthcare decision. Most of the time, cost-effective care is based on the 5 Rs derived from Lean manufacturing: right diagnosis, right care, right place, right provider, and right time.

While payers have an important role in cost-effective care, individualized decisions weighing trade offs and patient preferences are best made by physician-led care teams, in conjunction with patients and their families. Collaborative payers have the responsibility to provide vital integrated clinical and claims data with cost transparency. They also have the incentives and resources available to sift through the medical literature to identify evidence-based, fiscally responsible and, whenever possible, individualized clinical decision support messages and deliver them as close to the point of care as possible. These activities support the practices and processes by which PCPs can bend the cost curve.

 is a requirement for the APC Model, because it causes dramatic shifts of care from specialists to PCPs and from hospitals to the outpatient setting. The requisite primary care can be estimated as the number of patients in a PCP panel multiplied by the expansive responsibilities articulated in C1 through C7 that must be managed by PCP-led teams in order to progress toward the Triple Aim 

The collapsing interest in primary care among recent medical school graduates demands reinvention of the fee-for-service model.

PCP productivity expansion is the best solution for this impending crisis. A number of approaches—including e-mail visits, team- or pod-based care, and the use of nurse practitioners and other clinicians in appropriate situations&mdash;promise to narrow or even eliminate the PCP-to-future-needs gap.

 C9: Career satisfaction is markedly low among PCPs in the United States, with 36% saying they are dissatisfied with their careers—a rate 2 to 3 times higher than in Western European countries.

Career satisfaction is dependent on nonmonetary as well as monetary considerations. For example, pediatrics is among the lowest paid specialties, but pediatricians have one of the highest work-life balance self-ratings of all specialties.

Career satisfaction is directly related to issues such as meaning, control, order, work-life balance, and remuneration. Lumeris internally articulated the physician satisfaction (fourth aim) as “Triple Aim Plus One” in 2009. Other thought leaders, including Wallace,

and the Institute for Healthcare Improvement have proposed this fourth aim.

Suggested metrics for the 9 Cs are presented in 

After creating the APC Model, we looked back at its performance in an MA plan with a PCP gatekeeper model. All 3 levels of the APC model are represented by various PCP organizations in the outcomes data. The health plan had 25,423 members 65 years and older in 2010, 30,091 in 2011, and 33,155 in 2012. These members were matched to Medicare beneficiaries of the same county, age, and gender from a 5% Medicare fee-for-service (FFS) population limited data set each year.

The populations were intentionally not risk-adjusted by diagnosis codes, to eliminate any possible impact of more thorough diagnosis coding in the MA plan. In this analysis the MA plan’s contracted hospital rates were normalized to 100% of Medicare allowable. In a typical contract, the payer was allocated 15% of the total revenue to cover its costs. PCPs received 80% of the shareback (distribution of surplus) in global risk contracts. The percentage of shareback that was directly linked to performance on quality and process metrics increased over the 3-year period. By 2012, this percentage was typically 25% of the PCP’s 80% shareback. Approximately 1400 specialists contracted with the health plan. They were paid 110% of Medicare rates to compensate for their added work collaborating with PCPs. They were assured that they would receive more referrals with better documentation from PCPs if they provided high-value care. The plan contracted with 22 hospitals, of which 7 were independent and 15 were in 3 hospital systems. The provider profiles for 2010 to 2012 were similar.

Two cohorts were defined for comparison. The APC Model cohort consisted of all members of the Essence Healthcare plan who were 65 years and older. The 5% FFS sample consisted of a sample of Medicare FFS data matched for age, gender, and county. Claims data for the 2 cohorts were analyzed for each of the 3 years.

During calendar years 2010 through 2012, an MA plan (Essence Healthcare, #H2610) in Missouri and southern Illinois had costs that averaged 58.93% of a matched FFS Medicare cohort adjusted for age, gender, and county (

 contrasts this APC Model health plan with the matched FFS population for calendar years 2010, 2011, and 2012. Each cohort was divided into 10 deciles based on total costs of care for each member of the cohorts. Each year was considered to be independent of the other 2.

 is an analysis based on classifying claims into 1 of 10 groups. The number of claims in each group (not the costs of care) were compared. Note that the reductions in costs in Figure 1 were greater in the higher-cost deciles than in the lower-cost deciles, reflecting some influence of expenditures on preventive services.

While the number of accountable PCP visits is 197% of the fee-for-service unmanaged control group, this underestimates the increase in primary care services because it does not account for the longer duration of many of these PCP visits and many APC model services (eg, virtual visits) that are not reimbursable in the FFS remuneration system and therefore not billed. This is offset by the 67% decrease in the total number of specialist claims. Acute hospital bed days were 50% lower and skilled nursing facility days 64% lower. Occupational, physical, and speech therapy were 89% lower, and outpatient radiology 71% lower than FFS. The APC model simultaneously increased the number of preventive service claims by 1400%.

 by CMS in 2012, 2013, and 2014 based partially on 2011, 2012, and 2013 Health Care Effectiveness Data and Information Set (HEDIS)/Star quality metrics for patient care delivered in 2010, 2011, and 2012, along with patient experience, access to care, and care process metrics. The top 19% to 30% of MA plans nationally are 4.5 or 5 Stars each year.

Of note, the plan was rated at 5 Stars in the Consumer Assessment of Health Plans member survey questions C24 (getting needed care) and C28 (health plan quality) for each of these years.

In 2011 DSS Research performed a survey of PCPs contracted with this MA plan; the response rate was 44%. Of the 102 PCP respondents, 90.2% would definitely or probably recommend this MA Health plan to another physician. At the 95% confidence level, this is significantly higher than the national average (83.8%, n = 4529).30 In 2010, DSS Research performed a survey of specialists contracted with this MA plan; the response rate was 19.4%. About 91.4% of the 169 specialist respondents were satisfied or very satisfied with this plan. At the 95% confidence level, this is significantly higher than the national average (88.9%, n = 5810).

If the PCPs were paid $80 per member per month (PMPM)31—twice the FFS Medicare remuneration&mdash;and hospital contracts were normalized to 100% of Medicare, the MA plan would have medical cost ratios of 73.4% in 2010, 72.2% in 2011, and 72.5% in 2012, before surplus distribution. These low medical cost ratios occurred despite having the most generous member benefits, as measured by maximum out-of-pocket expenses (which were $1875, while the next lowest were $2800, looking at plans from 2010 to 2012), of any zero-premium-dollar MA health maintenance organization in its market.

As seen in Figure 2, the profound redistributions of medical services from hospitals and skilled nursing facilities to the outpatient setting, and from specialists to PCPs, are at the heart of the APC Model. Specialists are empowered to practice at the top of their training, as the APC model frees them from many routine follow-up visits and basic care that is provided by PCPs. The overall result is improvement in outcomes from both providers. These changes are consistent with Landon and Roberts’ vision for specialty care under global payment systems.

The 5-Star member survey ratings for access to care and quality of care suggest that the APC Model reins in supply-sensitive care

and increases preventive care services while maintaining quality and patient satisfaction. C1 through C9, but especially C5, produce these changes.

Other models of care can be analyzed through the lens of the 9 Cs. The Direct Primary Care Medical Home concept developed by Qliance Medical Management Inc can include all of the 9 Cs except for C6.

 The APC Model has greater emphasis on C5 and C7, but both care models include longer visits, a greater range of primary care office services, substantially more revenue for primary care, and virtual visits. The savings generated by the APC model provide the enhanced funding for primary care that is required from patients through the age-related monthly fees of the Direct Primary Care model. This enables the APC model to serve patients of all socioeconomic strata, since it provides the most generous benefits in the market in a zero-dollar-premium MA plan. Financial outcomes of the Direct Primary Care model are unknown.

The Primary Care Model defined C1-4, but these expansions of primary care are less substantially emphasized in the Medical Home and Wagner's Chronic Care models (

). The Medical Home as deployed today is an important building block for the transition from volume to value, but it does not go far enough. Care coordination fees typically ranging from $3 to $15 PMPM don’t cover the costs of practice reengineering and primary care expansion. PCP expenses in the APC model are estimated to be $80 PMPM—twice the typical Medicare FFS compensation&mdash;for a Medicare population, consistent with Goroll’s model of comprehensive payment for comprehensive adult primary care.

Several additional models of primary care include some of the 9 Cs. The Collaborative Care Model developed by Aetna and NovaHealth is focused mostly on C6, utilizing payer-sponsored care managers.

Its encouraging outcomes were limited to 750 members of 1 Independent Physician Association. ThedaCare’s Collaborative Care Units are a redesign of inpatient care that has lowered costs of inpatient care by 25% and improved quality metrics.

Thedacare also reported improvements in outpatient quality.

Their model incorporates C6 and C7. The CareMore model includes retraining hospitalists into extensivists, who provide hospitalist care and follow these patients in the office for a visit or two before releasing them back to the care of their PCPs.

The extensivists effectively coordinate care transitions (C4) and expand PCP capacity (C8). This model lowered inpatient utilization, length of stay, and readmissions, but overall financial outcomes are not available. HealthCare Partners Medical Group developed a care model that targets highneed patients at risk of hospitalization using multidisciplinary care teams and Homecare Teams. They bring high-risk conditions under control and return the patients to care with their PCPs. The organization’s Medicare patients use 800 acute hospital days per 1000 people per year. While their model is focused on team care rather than PCPs, they nonetheless utilize parts of C1, C2, C4, C6, C7, and C8.

Limited information is available about Boeing/Regence’s pilot study of the Intensive Outpatient Care Program, which included C4, C6, C7, and C8 to reduce the costs of care by 20% while improving quality in the sickest quintile of the population.

The New Model of Family Medicine was developed by the American Academy of Family Physicians and TransforMED. The model promotes all the Cs except C5 and C7, but it is not very granular and lacks published outcomes.

 The Institute of Medicine’s 10 New Rules for 21st Century Health Care include C1, C3, C4, C6, and C7, but the plan lacks detailed recommendations and outcomes.

Dartmouth Clinical Microsystems offers a well-established, dynamic, customizable approach to systems improvement, rather than a specific model of care.

 Implementations in primary care may utilize Wagner’s Chronic Care Model and include C1 through C4, and C8.

 We could not identify any published systematic reviews or meta-analyses of Clinical Microsystems’ cost and quality outcomes in primary care.

This study has several limitations. The APC model was partially derived from some physicians participating in the testing of the same model. In addition, the model was tested retrospectively in a single health plan in 1 market. It is also unclear to what extent the health plan’s gatekeeper model and PCP compensation through shared global risk contracts with quality incentives contributed to the outcomes, above and beyond the APC Model itself. The APC Model is designed for scalable implementations and various levels of the model are being deployed in multiple markets, but these independent outcomes data are not yet available.

The demonstrated strength of the APC Model is its extension of the proven Primary Care Model and the strong support for C5 through C9 in the medical literature. Note that this performance was not obtained within an Integrated Delivery System. The contracted PCPs came from medical groups, a Physician Hospital Organization and several Independent Physician Associations of varying cohesiveness. This improves the likelihood that the model may be replicable outside an Integrated Delivery System. The APC Model fosters the transition from volume- to value-based care by parsing it into 3 levels or steps. This model is completely consistent with the vision for healthcare reform articulated by Mostashari, Sanghavi, and McClellan.

The 2011 Medical Home provides building blocks for better healthcare. The 9 Cs of the APC Model extend the Medical Home model as they provide an empirical, programmatic road map for physician-led teams that invigorates the practice of high-value primary care medicine.

The APC Model enables a win-win-win system for patients, providers, and payers. All 3 benefit from improved patient satisfaction, higher-quality care, and lower costs of care. Collectively, the framework of the 9 Cs of the APC Model offers new hope for our beleaguered healthcare system, and for primary care in particular. Based on these results in a 4.5-Star MA plan, it is possible to utilize the 9 Cs to progress toward the Triple Aim 

 We thank Bart Hamilton, PhD, Tat Chan, PhD, and their colleagues at the Olin School of Business, Washington University in St. Louis, for their contribution to the analytical foundation of the APC model. We thank DSS Research for performing and providing the physician satisfaction survey research.

All authors are employees and shareholders of Essence Group Holdings Company. This includes Lumeris, which provides services to Essence Healthcare, the health plan in this study. Essence Group Holdings Company funded and had a role in the collection of data. This information was previously presented at the Patient Centered Primary Care Collaborative Conference on October 14, 2013, Bethesda, MD; and the 4th Annual Accountable Care Organization Congress on November 5, 2013, Los Angeles, CA.

Thomas D. Doerr, MD, c/o Lumeris, 13900 Riverport Dr, St. Louis, MO 63043. E-mail: 

1. Institute of Medicine. A Manpower Policy for Primary Health Care: Report of a Study. Washington, DC: National Academies Press; 1978.

2. Starfield, Barbara. Primary Care: Concept, Evaluation and Policy. New York: Oxford University Press; 1992.

3. Shi L, Starfield B, Xu J. Validating the adult primary care assessment tool. J Fam Pract. 2001;50(2):161-175.

4. Friedberg MW, Schneider EC, Rosenthal MB, Volpp KG, Werner RM. Association between participation in a multipayer medical home intervention and changes in quality, utilization and costs of care. JAMA. 2014;311(8):815-825.

5. Flottemesch TJ, Anderson LH, Solberg LI, Fontaine P, Asche SE. Patient-centered medical home cost reductions limited to complex patients. Am J Manag Care. 2012;18(11):677-686. [Notes: Analysis consisted of recalculations of Table 5 to combine the three cohorts, with weighting for the differing numbers of patients in each.]

The new Accountable Primary Care Model delivers Triple Aim-like outcomes. This model is empirical, measurable, programmatic, scalable, and transplantable.

The Accountable Primary Care Model: Beyond Medical Home 2.0

 Despite the rise of new value-based payment models as mechanisms to engage physicians in healthcare reform, there is currently limited physician participation in these new models. Little is known about specific physician perspectives on the direction of US healthcare under the Affordable Care Act (ACA) and the National Quality Strategy. Awareness of these perspectives is crucial for the development of strategies to support physician engagement with healthcare reform.

The aim of this study was to explore physician perceptions about the provisions of the ACA as it pertains to the concepts of value, quality, and cost.

 This study synthesized insights from 3 quantitative and qualitative datasets to explore physician perceptions from 2011 to 2014.

 (A) analysis of 5 nationwide, online surveys that were fielded to 90,563 Medscape physician members across 25 specialty areas to assess compensation, number of hours worked, practice changes resulting from healthcare reform, and adaptations to the new healthcare environment; (B) Analysis of key themes in commentary in Medscape articles published online (January 2013 to March 2014) that focused on the implementation of new models of care linked to the ACA; and (C) sentiment analysis of 790 unstructured, free-text, Internet-based comments posted online by physicians who read the 8 most popular articles posted on the Medscape platform from January 2013 to March 2014 that focused on quality improvement in healthcare and value-based reimbursement. Results: We identified, among physicians, 5 areas of friction related to healthcare reform that are associated with the transition to new models of value-based reimbursement and that potentially pose barriers to physician engagement in healthcare reform.

 Physician engagement in healthcare reform is largely being incentivized via pay-for-performance models and metrics. There is currently little evidence that health systems have sustainable plans to engage physicians beyond performance incentives. Targeted physician engagement strategies—continuing medical education, for instance&mdash;have been shown to be drivers of healthcare transformation. This study identifies key areas for targeted education that can help build skills to drive greater adoption of new models of more affordable healthcare delivery.

The 2010 Affordable Care Act (ACA) makes copious reference to the concept of value,

 which the Institute for Healthcare Improvement considers a function of the triple aim of quality, satisfaction, and, notably, cost. Indeed, healthcare affordability is 1 of the 6 priorities of the National Quality Strategy (NQS), which the Agency for Healthcare Research and Quality launched in 2011 as a comprehensive framework to guide efforts to improve and measure quality. Hospitals have already been participating in this quality rubric through exposure to value-based purchasing and the CMS Readmission Reductions Program,

 through which hospitals suffer economic penalties for excess readmissions. Now, the NQS priority of affordability is being extended to physicians via new healthcare delivery models, metrics-driven payment systems, and value-based reimbursement.

Change management leaders suggest that 4 elements are necessary for organizational transformation to occur, including: 1) skills to succeed, 2) role models, 3) compelling reasons for change, and, importantly, 4) reinforcing mechanisms for engagement.

In the context of healthcare reform, many value-based payment and delivery models serve as reinforcing mechanisms and as recognition by payers of the importance of physician engagement.

 Such delivery and payment models include accountable care organizations (ACOs), Patient Centered Medical Homes, Medicare Advantage, Meaningful Use (MU), and the Physician Quality Reporting System (PQRS) tied to CMS’s value-based payment modifier (VBPM). Commercial payers such as Aetna, Cigna, and UnitedHealthcare, as well as many state Medicaid agencies, are launching similar programs, and they are slowly becoming universal. By 2017, for example, some form of value- based payment system will be in place for all physicians taking Medicare reimbursement.

Despite the function of these new payment models as engagement/reinforcing mechanisms, there is currently limited physician participation in new models of delivery; there is also lower-than-anticipated data reporting for reimbursement programs.

 Although ACOs have increased in number, currently only approximately a quarter of physicians are in ACOs.

 Similarly, CMS reporting trends show that although participation in PQRS has grown from 17% in 2007 (then known as Physician Quality Reporting Initiative), only one-third of eligible professionals in 2010 reported performance metrics.

The success of new healthcare delivery models is dependent on the active participation of physicians. As such, it is important to examine reasons for low physician engagement.

Although trade surveys and discussion in trade publications suggest unease among physicians about healthcare reform,

 little is known about specific physician perspectives on the direction of US healthcare under the ACA and the NQS. Therefore, the aim of this analysis was to explore physician perceptions about the provisions of the ACA as they pertain to the concepts of value, quality, and cost.

) is an open-access online publication that receives more than 1.5 million physician visits per month. Medscape’s readership represents about 60% of total AMA-active physicians, as well as a large proportion of physicians who are not members of the AMA. One section, titled The Business of Medicine, publishes analysis, interviews experts, summarizes commentary, and provides a forum for physicians and providers to discuss the evolving business of medicine landscape. Insights were synthesized from the following 3 datasets:

(A) Between 2011 and 2014, 5 nationwide online surveys were fielded via a third party to Medscape physician members across 25 specialty areas to assess compensation, number of hours worked, practice changes resulting from healthcare reform, and adaptations to the new healthcare environment. Analysis focused on 90,563 completed surveys, and self-reported survey data were used to rank physician compensation by specialty.

(B) The Medscape editorial team and one of this paper’s authors (Wright) identified key themes in commentary in Medscape articles published online (January 2013 to March 2014) that focused on the implementation of new models of care linked to the ACA.

(C) We conducted a sentiment analysis of 790 unstructured, free-text, Internet-based comments posted online by physicians who read the most popular healthcare quality improvement and value-based reimbursement articles posted on the Medscape platform from January 2013 to March 2014. Sentiment analysis extracts and analyzes attitudinal information from sources as varied as articles, blog postings, e-mails, call-center notes, and survey responses. Sentiments refer to private, subjective states that individuals share publicly via social media and other accessible sites, which contain emotive elements and represent moral evaluations that have a bearing on behaviors and norms.

Based on an analysis of Medscape Business of Medicine data, we identify 5 specific areas of friction for the success of payment reform efforts.

December 2014

For ACOs Large and Small, Sharing Ideas With an Open Mind

Pilot-Testing a New Program for Providing Personalized and Patient-Centered Preventive Care

The Accountable Primary Care Model: Beyond Medical Home 2.0

Areas of Addressable Friction for the Adoption of Greater Healthcare Affordability: Insights from US Physicians

Sustainable Lifelines: Supporting Integrated Behavioral Health Services for Children and Adolescents in the Accountable Care Era

The 2014 Elections and the Future of Medicaid

Ensuring the Integrity and Transparency of Public Reports: How a Possible Oversight Model Could Benefit Healthcare

Telehealth: An Important Tool in Achieving the Goals of the ACO Program and Why Restrictions Should Be Lifted in Final ACO Rule

Finally: CMS to Address Allowing Hospitals More Say in Selecting Post Acute Care Providers

Slowing in Healthcare Costs: Hold the Celebration