When historic floods struck the Baton Rouge area last month,

 Louisiana health officials were able to offer the working poor who fled their homes something they could not give to the musicians, waiters, and hotel maids left homeless by Hurricane Katrina 11 years ago: access to healthcare.

Just a few months ago, those left in the “coverage gap” after the US Supreme Court left Medicaid expansion up to the states would have been out of luck. But on July 1, 2016, Louisiana became the 31st state under the Affordable Care Act (ACA) to bring Medicaid to those earning up to 138% of the federal poverty level (FPL).

With a goal to enroll 375,000 in this population the first year, by August 24, 2016, the state had reached 289,742—past the three-fourths mark, according to an e-mail from Louisiana Department of Health (LDH) spokeswoman Samantha Faulkner. That means more than 11,000 individuals gained coverage through expansion in just the 2 weeks following an August 10, 2016, update

) in an interview that some flood victims had signed up in shelters.

Louisiana’s simplified enrollment process—which makes heavy use of data already on hand&mdash;has created a new model for states with no stomach for bureaucracy. By design, expansion is like flipping a switch. With limited effort for the enrollees, Louisiana is giving coverage to thousands of low-wage workers and self-employed contractors who drive the tourism economy. That is as it should be, according to Governor John Bel Edwards, who has traveled the state to emphasize that far from a handout, 70% of those gaining coverage are working folks, people “caught in a trap.”

To find those eligible, Louisiana has deployed longtime LDH staff into clinics and hospitals to capture potential enrollees at the point of care. And, in a move destined to be copied, state officials used data from the Supplemental Nutrition Assistance Program (SNAP) to identify families likely eligible. So far, according to Faulkner, this method accounts for 23,413 Medicaid certifications, although many involve more than 1 person.

Edwards’ decision to plow ahead with expansion amid a budget crisis has gained notice. In late August, he was named to Modern Healthcare’s “Top 100 Most Influential People in Healthcare,”

 at number 35—while a governor who is scaling back Medicaid expansion, Matt Bevin of Kentucky, came in at 89. Edwards calls expansion, “the easiest big decision I’ll ever make” and said work remains on delivery system and payment reform.

In June, Mary Caffrey, managing editor of the 

, visited New Orleans during the early days of enrollment to hear from providers and an advocate for safety net clinics about the promise of Medicaid expansion after a long wait and what it might mean for Louisiana.

It was mid-morning, and the Daughters of Charity Health Center on Carrollton Avenue was bright and busy. One of 9 centers the Catholic order operates across 25 miles, the Carrollton site, was bursting with patients, mostly women and children. In the waiting area for the optometry and dental clinics, there was not a chair to be had.

The Daughters have cared for New Orleans’ poor since before the Civil War,

 and today, 90% of the clinics’ patients earn less than 200% of the FPL, with 70% below the 100% mark.

 According to Daughters of Charity vice president and chief operating officer Frank Folino, 24% of the clinics

 so a sizable number of them might need to see the young woman tucked in a quiet corner who registers patients for Medicaid expansion, which was scheduled to take effect in a few weeks

Behind the young woman, separated by a partition, was a longtime employee from the state’s Medicaid office. Armed with digital application tools and a direct line to the state capital, he had been dispatched from LDH to handle Medicaid renewals and to speed eligibility for anyone who signs up at the Carrollton clinic. The idea is to integrate Medicaid enrollment right into the workflow, when patients are least likely to be lost. Although the numbers of these trained staff were still small in June, Faulkner said they were projected to grow to 100 at 80 sites.

There is much hope that Medicaid expansion has finally come to one of the country’s poorest states, but no one is blind to the challenges that remain. Those who have never had insurance must learn to use it, and there are questions on whether there will be enough primary care doctors for this new wave of patients. The governor himself has said that Medicaid payments to doctors must increase to ensure access over the long haul. And, according to Susan Todd, executive director of 504HealthNet, a health policy umbrella for 60 primary and behavioral healthcare sites in the New Orleans region,

 everyone must remember there will still be uninsured individuals after expansion

“This is right versus wrong, not right versus left,” Edwards said on the first day of enrollment (June 1, 2016) during a visit to University Medical Center (UMC), the $1.2-billion replacement for historic Charity Hospital, which served generations of New Orleans’ poor before it shuttered after Hurricane Katrina. “At the end of the day … we’re going to improve health outcomes. We want a better quality of life for our people. We want them to be happier, healthier, more productive people.”

When he campaigned last fall, Edwards promised Medicaid expansion knowing full well that a budget deficit awaited his arrival. He got expansion rolling with an executive order on January 12, 2016, his second day on the job.

 Weeks later, his administration announced the shortfall was worse than expected: this year

s $24.5 billion budget had a gap of $943 million, with a deficit of $2 billion looming for the fiscal year that started on July 1, 2016.

 Keeping his promise would take creativity, because the legislature would not pay for administrative help, even though expansion is projected to save $184 million.

“We didn’t get one additional dime from the state,” said Secretary of Health Rebekah Gee, MD, MPH, MS, in her June interview with 

That meant no money for new staff to figure out who was eligible—to say nothing of funds for education or advertising. So, Louisiana tapped eligibility data it already had, using rolls from existing Medicaid waivers and the SNAP data, a first among the states. Gee’s move to “outstation” the LDH Medicaid staffers&mdash;like the one at Daughters of Charity&mdash;counted as a piece of Louisiana’s 25% share of the administrative costs of enrollment (the federal government is paying 75%), according to information from state health officials.

With these steps, Edwards and Gee have rewritten the playbook for low-cost, low-bureaucracy Medicaid enrollment that is well-suited to expansion’s holdout states—places where poverty and chronic disease exceed the norm, along with resistance to government spending. And it’s all working. In the week before expansion coverage took effect, new or expanded benefits were already scheduled to reach more than 225,900 people at 100% to 138% of the FPL; these included families of 4 earning $33,564 or single adults earning $16,404, according to LDH data provided to 

 Thus, Louisiana enrolled 60% of its eligible population in less than a month; more than 186,800 of them were automatically signed up when enrollment opened on June 1, 2016.

A week into enrollment, Gee had the number of new Medicaid enrollees at her fingertips: 197,026 at that point. Most of them were transferred based on eligibility for 2 existing programs: 1) 61,000 enrollees who had limited primary care and behavioral health benefits through the Greater New Orleans Community Health Connection (GNOCHC)—a program funded in the aftermath of Hurricane Katrina that concluded when Medicaid began July 1, 2016&mdash;living in New Orleans and 3 parishes (counties) that make up the immediate suburbs; and 2) enrollees across the state with income levels just above traditional Medicaid who were receiving various family planning, contraception, and screening services under a separate Medicaid waiver.

Louisiana broke new ground with its use of SNAP eligibility rolls to quickly qualify individuals. Gee explained in the interview that SNAP clients received a notice letting them know of their likely Medicaid eligibility, along with 3 income-related questions. Clients could respond by phone, fax, e-mail, or regular mail. Within days, Gee said, the state Medicaid office had fielded 10,000 phone calls; over time, the state expects up to 105,000 people to enroll this way, because in the future, low-income families will be able to enroll in SNAP and Medicaid at the same time.

Louisiana hospitals, which went through a transformative relationship with the state’s charity care system under Edwards’ predecessor, Bobby Jindal, have greeted expansion warmly.

 It comes a year into the life of UMC, which was under construction before the Supreme Court ruled that Jindal could decline Medicaid expansion dollars.

Rachel Verville, system vice president for Revenue Cycle at LCMC Health—which operates 4 hospitals in the New Orleans area besides UMC&mdash;has seen Medicaid expansion in former posts in Massachusetts and New Hampshire, and is impressed with Louisiana’s innovation. “It’s very refreshing to use data that is already available,” she said in an interview with 

, adding that the automatic enrollment from GNOCHC (pronounced no-key) will allow a smooth transition for these patients.

Gee had to fill gaps to cover Louisiana’s share of administrative costs. With a background in academia, she tapped the Robert Wood Johnson Foundation, the Kaiser Family Foundation, and other sources. To promote expansion, Gee and Edwards toured the state, answering constituent questions and drawing free media coverage. “People want to know, ‘Is this real Medicaid?’ We’ve had some tears shedded,” Gee said. “We’ve had a lot of happy faces at these enrollment events.” What didn’t happen, based on interviews and media reports, are the computer glitches and downtime that plagued the ACA’s early days.

Grasping the magnitude of Louisiana’s expansion requires understanding of just how hard it was to get traditional Medicaid. According to data provided by Louisiana LDH, the previous income limit for parents and caretaker relatives (if a child 19 years or younger was at home) was 24% of the FPL for a family of 4—just $5820 a year, or $485 a month. Adults without children could not get coverage at all unless they qualified for disability.

Verville said there is excitement at the chance to change Louisiana’s healthcare story. “There are people who are going to have coverage, maybe for the first time in their lives,” she said. Gee also portrays Medicaid expansion as a piece of a larger picture, of raising not only the population’s healthcare profile, but its economic one as well. “It’s quite rewarding to participate in helping a population gain access to healthcare,” Verville said. For providers, “It opens a whole world of opportunity.”

It’s not that Louisiana doesn’t have a history of caring for the poor. The Daughters of Charity operated hospitals in New Orleans for more than a century, and Governor Huey P. Long expanded this system and created the Louisiana State University (LSU) Medical School. As the system evolved, in 1997, LSU took full control of the charity hospitals.

 Although care for the poor at the state’s charity hospitals was free, preventive and primary care networks were sparse. The divide perpetuated generations of separation between the poor, who went to the emergency department (ED) for most of their care, and the insured, who could see the doctor, the dentist, and specialists.

After the ACA passed, Louisiana readied itself for Medicaid expansion. However, when the US Supreme Court made expansion optional, to the dismay of healthcare leaders, Jindal refused to accept additional Medicaid funds. Instead, he ended the charity hospital system, pairing off most of the former state hospitals with private ones and offering state contracts to manage them.

 When the state capital, Baton Rouge, lost its charity hospital, another city ED was flooded with so many uninsured patients that it closed.

It’s little wonder, then, that CDC data show that Louisiana ranks poorly in rates of diabetes (10.4%)

CDC data from 2012, before the ACA took full effect, show Louisiana ranked second in cancer incidence (483.4 cases per 100,000 residents) behind Kentucky and third in deaths from cancer (190.5 per 100,000 residents) behind Kentucky and Mississippi.

s experience shows what is possible: after expansion, Kentucky cut its uninsured rate from 20.4% in late 2013 to 7.5% as of December 2015

According to Gallup, Louisiana retains one of the highest uninsured rates at 16.3%.

The stability for newly insured patients—not having to patch together services or drug coverage&mdash;will extend somewhat to hospitals and other providers. Ayame Dinkler, assistant vice president for Government Affairs and Strategy Development at LCMC Health, said that although public—private partnerships like UMC will still require support through state funding from the Governor and the legislature, Medicaid expansion will save the state a tremendous amount of money. “We can’t train the next generation of physicians without state funding,” Dinkler said.

New Orleans’ Transition to Primary Care 

Twenty years ago, after the Daughters of Charity sold its last hospital, the order created a holistic system of primary and behavioral healthcare across the New Orleans region, according to President and CEO Michael G. Griffin. Last year, the centers treated 40,000 patients and handled 107,000 primary and behavioral health visits. Concepts like the patient-centered medical home are not new here. “Our job is to keep you healthy,” Griffin said.

In the aftermath of Katrina, however, it became clear that the working poor, who lacked insurance, needed a different way to access primary and especially behavioral healthcare. Charity Hospital was gone, but as Todd explained, there was now an opportunity: a more complete network of community-based care could replace the bus rides and long waits in the ED. In 2007, Congress awarded a $100-million grant to help provide basic services to those with incomes above the Medicaid range. From those beginnings, GNOCHC emerged.

The GNOCHC parishes will have a head start on Medicaid expansion, Todd says. All the centers in 504HealthNet have electronic health records (EHRs), so there is baseline information for many Medicaid expansion patients. Expansion will mean improved benefits, access to dental care, and prescription drugs beyond the $4 formulary at Wal-Mart, she said. (For example, patients with diabetes will get coverage for insulin.) It also means staff will spend less time piecing together payments for prescriptions and to cover other operations. “There’s more stability,” Todd said. “They can go forward and not worry that we’re not going to have financing for this group of adults that we’ve been caring for.

There’s agreement that patients who have coverage are more likely to keep appointments and less likely to wait until a health problem is acute to seek care. Although GNOCHC patients may have less of a learning curve, Verville said that LCMC Health is preparing to work with managed care plans to teach the newly insured how to use their coverage—including the need to replace the ED with primary care. Since taking control of Interim LSU Hospital in 2013&mdash;which provided care until UMC opened last year&mdash;LCMC Health has produced a huge drop in the no-show rate in the clinic (from 62% to 22%) and an upward trend in patient satisfaction scores, which are now above 75%.

For both LCMC Health and Daughters of Charity, improved stability likely means a change in the “payer mix,” with a higher share of insured patients. Since 2013, LCMC Health has shifted the share of Medicaid patients from 42% to 34% in 2015, and the share of self-pay/indigent patients from 39% to 37%. The share of patients with commercial coverage has increased from 8% to 13% over the same period, and Medicare patients have increased from 11% to 16%.

Medicaid expansion will be a game changer for Daughters of Charity, says Folino, offering more resources to pour back into the mission. The current payer mix includes 55% of patients with Medicaid and 13% with commercial coverage, according to data provided in an e-mail. Folino said the average self-pay fee is $45 for an office visit compared with a Medicaid reimbursement of $135; he projects that 10% of the current uninsured patient base will enroll. This means Daughters of Charity will not only get increased revenue for these office visits, but these patients will also gain coverage for dental care and the center’s pharmacy.

Support for institutions is only part of the equation. Support for primary care physicians (PCPs) is important too, according to Pamela M. Wiseman, MD, associate professor of Clinical Family Medicine at LSU Health Sciences Center. Although she is “cautiously optimistic” about expansion, she has long been concerned about the number of PCPs in the pipeline, and wonders if there’s enough capacity to treat the newly insured. 

Wiseman points to data from the Robert Graham Center that projects Louisiana will need an additional 392 PCPs to meet demand through 2030.

 To make primary care attractive, Louisiana must fund more training positions and help young doctors with student debt, Wiseman said

The apparent popularity of Medicaid expansion in Louisiana is no guarantee that other Deep South states will follow—or even that expansion will survive where it exists. Kentucky’s Matt Bevin, a Republican who succeeded Democrat Steve Beshear, has proposed premium requirements, “lock outs” for nonpayment, and he would ask enrollees to earn dental and vision benefits. Enrollees would have to work or volunteer.

 In Arkansas, Republican Governor Asa Hutchinson used a procedural maneuver to protect the “private option” with some modifications; however, after enrollment numbers topped 300,000, some state legislators wanted cutbacks.

Louisiana’s neighbor to the east, Mississippi, rivals its rates of poverty and chronic disease, and in mid-August, the state’s physicians seemed to support a resolution supporting expansion. Except, at the last minute, they took the words “Medicaid expansion” out of the document for fear that would rile political leaders opposed to anything associated with “Obamacare.”

 in June that some uninsured patients from Mississippi visit New Orleans area clinics because they have nowhere else to go.

In Louisiana, there’s also the issue of getting more physicians to accept Medicaid. It is not clear yet how many physicians in each of Louisiana Medicaid’s 5 managed care plans will accept patients from this new group. According to the LDH website, that information will come directly from the plans.

Expansion will bring an opportunity to work on longer-range goals, like being able to bill for both primary and behavioral healthcare if they happen the same day, Todd said. Most of all, those involved say they look forward to moving the needle on core measures and health outcomes.

Amid her concerns, Wiseman remembers the patients she treated at her old clinic who lacked insurance and could not follow her to LSU Health. “Now, they can come see me.”

1. How public health has supported Louisiana flood victims. Public Health Newswire. http://www.publichealthnewswire.org/?p=15866. Published August 24, 2016. Accessed August 27, 2016.

2. Will Louisiana’s Medicaid expansion provide a model for other states? Georgia Health News website. http://www.georgiahealthnews.com/2016/06/louisianas-medicaid-expansion-provide-model-states/. Published June 20, 2016. Accessed June 25, 2016.

3. Healthy Louisiana enrollment tops 278,000. Louisiana Department of Health website. http://ldh.louisiana.gov/index.cfm/newsroom/detail/3928. Published August 10, 2016. Accessed August 24, 2016.

4. Gov. Edwards: Medicaid expansion will benefit people, state of Louisiana. WDSU-TV website. http://www.wdsu.com/news/local-news/new-orleans/gov-edwards-medicaid-expansion-will-benefit-people-state-of-louisiana/38751638. Published March 29, 2016. Accessed August 27, 2016.

Articles

The American Journal of Accountable Care

How does a state with almost no money launch Medicaid expansion? Louisiana health officials used data they already had, and in doing so, have created a model that could be used elsewhere.

In Louisiana, Necessity Breeds Innovation to Bring Medicaid Expansion

The current benchmark method used by Medicare Shared Saving Program (MSSP) accountable care organizations (ACOs) favors historically high-cost ACOs. To address this problem, the new Next Generation ACO model modifies the benchmarking methodology by incorporating regional and national relative efficiency discounts.  We analyzed the effect of a benchmark on ACO savings under the original benchmark and these 2 adjusted benchmarking techniques.

We simulated different benchmarking methodologies and their effects on ACO savings.

 Using 2012 to 2014 Medicare spending data and MSSP ACO performance data, we applied county-level and national-level benchmark adjustments following the Next Generation ACO benchmarking method. We implemented both adjustments simultaneously and varied the adjustment caps between 0% and 5% to observe how the adjustment magnitude would affect savings for each ACO. We computed the average change in the newly calculated saving rate and earned shared savings for each $1000 change of the original benchmark, adjusting for ACO characteristics.

The Next Generation benchmark adjustments can reduce the correlation between ACO earned savings and historical spending, but the proposed adjustment levels are not large enough. By simulating different adjustment levels, we conclude that a combined national and regional discount cap of 3.5% best removes the correlation between benchmark and MSSP ACO performance.

Under the current MSSP, a higher benchmark level is associated with a better chance to save and larger earned savings. Although the Next Generation ACO benchmark adjustment is effective, the adjustment should be larger to completely remove the correlation between prior performance and an ACO’s savings.

Medicare offers 3 main types of accountable care organization (ACO) programs: Pioneer ACOs, initiated in 2011; Medicare Shared Savings Program (MSSP), initiated in 2012; and Next Generation ACOs, initiated in 2016. The great majority of Medicare ACOs are MSSP ACOs; as of 2016, there are 434 active MSSP ACOs serving over 7.7 million Medicare beneficiaries, but only 9 Pioneer ACOs and 21 Next Generation ACOs.

MSSP ACOs earn shared savings if the realized spending is less than a required percentage, ranging from 2% to 3.9% of the target spending.

 This benchmark, which is established at the start of a 3-year period, adjusts for patient risk scores and increases annually following a national spending trend, but makes no adjustment based on the relative historic spending level. As a result, providers who have achieved cost efficiency may be discouraged from entering or continuing to participate in an ACO payment model due to its reliance on historical performance. Several previous studies show that under the current benchmarking methodology, ACOs that earned more savings were located in high spending regions and had high spending relative to other ACOs in the same region.

In an attempt to fix this problem, the new Next Generation ACO model modifies the benchmarking methodology by incorporating regional and national relative efficiency discounts, so ACOs that have already attained cost efficiency compared with their region will have a more favorable discount.

 The Next Generation ACO also includes a standard discount of 3% and an adjustment based on ACOs’ quality scores. Since the inclusion of the 3% standard discount would not affect the relationship between saving and benchmark, and the quality adjustment has a phase in period in which it is not active, these features are not included in our analysis.

We used 2012 to 2014 Medicare spending data and MSSP ACO performance data to analyze the effect of a benchmark on ACO savings under 3 benchmark schemes: current MSSP benchmark and 2 benchmarks following the Next Generation ACO model, one with regional adjustments and another with national spending adjustments. The light purple bars in the 

 (panel A) show that the higher the current benchmark level, the higher the ACO saving rates. The darker colored bars in the Figure (panel A) show that this positive relationship weakens when incorporating the benchmarking adjustments. However, the regional and national adjustment levels are not large enough to remove the correlation. By simulating different adjustment levels, we concluded that a combined national and regional discount cap of 3.5% best removes the correlation between benchmark and MSSP ACO performance.

MSSP ACO public use files, from 2012 to 2014, contain information on ACOs’ spending in the first 2 performance years, as well as characteristics of assigned beneficiaries, including county of residence, Medicare enrollment type, and risk score.

 We combined this data with county-level fee-for-service (FFS) Medicare expenditures to determine each ACO’s spending level relative to the national and region levels. Our final dataset contained 329 ACOs. We dropped ACOs that stopped participating in MSSP and Golden Life Healthcare LLC—an outlier with a 44% saving rate; including this outlier does not substantially change results.

Outcomes are 2 ACO-level saving measures: 1) saving rate, defined as benchmark expenditures minus actual expenditures as a percentage of benchmark expenditures; and 2) earned shared savings per capita, defined as per-capita shared savings for ACOs that simultaneously exceeded their minimum saving rate and met the program’s quality standard.

Following the Next Generation ACO benchmarking method, we create 2 adjusted benchmarks: 1) county-level efficiency adjustment and 2) national efficiency adjustment. Specifically, if an ACO’s risk-adjusted historical per-capita baseline is higher (or lower) than the risk-adjusted county-level FFS baseline, the ACO’s county-adjusted benchmark is equal to the original benchmark decreased (or increased) up to 1%. Similarly, if an ACO’s historical baseline is higher (or lower) than the national level, the national adjusted benchmark is equal to the original benchmark decreased (or increased) up to 0.5%. We separately analyzed whether either adjustment can remove the relationship between historical spending and savings. Separating regional and national adjustments allowed us to compare them explicitly.

We then implemented both adjustments simultaneously, as in the Next Generation ACO model, and varied the discount caps between 0% and 5% to observe how the adjustment magnitude affects savings for each ACO. We computed the average change in the newly calculated saving rate and earned shared savings per capita for each $1000 change of the original benchmark, adjusting for ACO characteristics, including number of beneficiaries served in the ACO, average county spending level, the ACO’s patient demographic and enrollment characteristics, starting date indicators, and year indicators. Through this simulation, we determined the discount levels that best remove the positive relationship between benchmark and performance.

The purple bars in the Figure show the average saving rates of all ACOs and average earned shared savings per capita among ACOs that achieved saving by decile of the original benchmark amount. The higher the benchmark level, the larger the savings, confirming that the level of the benchmark has a large effect on both the extensive margin (whether or not an ACO saves) and the intensive margin (how much an ACO saves).

Regional and National Efficiency Adjustments Are Somewhat Effective

We recalculated the saving rate and earned shared savings per capita for each ACO under the 2 adjusted benchmarks. The first adjusted benchmark takes into account only the regional efficiency adjustment, while the second benchmark takes into account only the national efficiency adjustment. The Figure (panel A) shows the average saving rate by decile of the original benchmark when the saving rate is calculated using the original and the 2 adjusted benchmarks. The Figure (panel B) presents the relationship between these benchmarks and earned shared savings per capita. Both adjustments slightly mitigate the correlation between the original benchmark and the recalculated outcomes. The regional efficiency adjustment is more effective than the national efficiency adjustment, but this seems to be caused by the larger magnitude of the regional adjustment. Under both adjusted benchmarks, the positive relationships between the recalculated outcomes and the original benchmark are still present.

Controlling for ACO characteristics, the correlation between the original benchmark and the saving rate was 0.14 (

 = .00). After incorporating the national and regional adjustments, the correlations decreased to 0.13 (

 = .02), respectively. All the evidence suggests that the adjustment level currently being used in the Next Generation ACO model is effective, but not large enough to remove the correlation between benchmark and ACO performance.

To see what level of adjustment best removes the correlation, we varied the discount caps of these 2 adjustments and displayed the average change in the newly calculated savings rate for each $1000 change of the original benchmark in the 

 (panel A) and newly calculated earned savings per capita in the Table (panel B). In the Table, both adjustments are implemented simultaneously. The darker cells correspond to scenarios with a stronger and more statistically significant relationship between recalculated outcomes and benchmarks, while the whiter cells indicate a weaker relationship with less statistical significance. At the current Next Generation ACO implementation level—1% cap for regional adjustment and 0.5% cap for national adjustment&mdash;an increase of $1000 in the original benchmark is related to a 0.52% increase in the savings rate and a $19.17 increase in earned savings per capita. This is not trivial, considering the average savings rate is 0.54% and the average shared savings per capita is $79.80 in our sample.

The analysis reveals that a combined national and regional discount cap of 3.5% best removes the correlation between benchmark and ACO performance under an ACO model. At this level, the absolute value of correlation is the smallest and is statistically insignificant. If the combined cap is too small, the program rewards ACOs with high benchmarks; if the combined cap is too large, the relationship becomes negative and saving becomes harder to achieve for high-benchmark ACOs. Finally, as shown from the diagonal shape of the white cells in the Table, both adjustments have similar effects on the correlation, and the combined adjustment level is more important than the relative size of each adjustment.

The benchmark calculation can greatly influence realized savings for ACOs. The current MSSP benchmark is set to be ACO-specific and is based on the prior 3 years’ performance in order to encourage participation from high-cost ACOs.

It is essential to have a program that gives all ACOs a fair chance to succeed. Under the current benchmark system, the incentives to join MSSP are weaker for ACOs with a lower benchmark, as it is harder for them to achieve savings. Under a 2-sided risk model, which MSSP was originally scheduled to transition to, the incentive to participate in an ACO program is even weaker because ACOs face a larger risk. Moreover, the current MSSP benchmark is scheduled to be recalculated every 3 years, so previous high-cost, high-performance providers will eventually have a low benchmark. Before the recalculation occurs, attrition may be the best choice for ACOs that would receive a low updated benchmark.

Our study explores 2 benchmark adjustments that are implemented in the Next Generation ACO model and designed to remove the relationship between the benchmark level and an ACO’s success. The regional efficiency adjustment makes savings harder to achieve for ACOs that are performing poorly in their region. Similarly, the national efficiency adjustment makes savings harder to achieve for ACOs that spent more than the national spending average in the current performance year, lowering the correlation between high-cost regions and MSSP success.

At the current Next Generation ACO adjustment level, both adjustments can partially remove the relationship between an ACO’s spending level and the realized savings. However, a stronger adjustment is needed to completely remove the correlation. Our analysis revealed that the level of the combined national and regional discount cap is more important and the respective level of each adjustment does not greatly affect results. It is not surprising that regional and national efficiency adjustments have similar effects, given that more than 80% of the ACOs are affected by these 2 adjustments in the same way: if an ACO spent more than the regional average, it is also more likely to have spent more than the national average. We recommend implementing a benchmark adjustment with a combined cap of 3.5%. At this level, the positive relationship between historical spending and savings is completely removed, making savings equally attainable for all ACOs, independent of their previous spending level.

In summary, the MSSP benchmark is calculated based on the ACO’s previous 3 years’ claims data, making savings hard to achieve for historically low-cost ACOs. We note that a higher benchmark level is associated with a better chance to save and larger earned savings per capita. We also show, when adjusting benchmarks using the adjustment methods in the Next Generation ACO model, that the relationship between benchmark and saving is weakened; however, a benchmark is still an important determinant of saving. We tested different levels of regional efficiency and national efficiency adjustments and determined that a combined adjustment cap of 3.5% best removes the positive relationship between benchmark and ACO performance. Although the Next Generation ACO benchmark adjustment is effective at reducing the correlation between prior poor performance and an ACO’s savings, the adjustment should be larger to completely remove the positive relationship.

Lulu Liu, MA, and Richard Svoboda, MA, made equal contributions to the article.

Department of Economics (LL, RS) and Department of Health Policy and Management (YZ), University of Pittsburgh, Pittsburgh, PA.

Yuting Zhang gratefully acknowledges funding from the Commonwealth Fund (Grant 20150380). The sponsors played no role in the study conduct, data analysis, or report.

The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Concept and design (LL, RS, YZ); acquisition of data (LL, RS, YZ); analysis and interpretation of data (LL, RS, YZ); drafting of the manuscript (LL, RS, YZ); critical revision of the manuscript for important intellectual content (LL, RS, YZ); statistical analysis (LL, RS); obtaining funding (YZ); administrative, technical, or logistic support (LL, RS, YZ); and supervision (YZ).

Yuting Zhang, PhD, Department of Health Policy and Management, University of Pittsburgh, 130 De Soto St, Crabtree Hall A664, Pittsburgh, PA 15261. E-mail:

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2. Methodology for determining shared savings and losses under the Medicare Shared Savings Program. CMS website. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/sharedsavingsprogram/Downloads/ACO_Methodology_Factsheet_ICN907405.pdf. Published April 2014. Accessed June 1, 2016.

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2012;366(19):e29. doi: 10.1056/NEJMp1202004.

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8. Aggregate expenditure and risk score data on assignable beneficiaries by county. CMS website. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/sharedsavingsprogram/Downloads/Assignable-Beneficiaries-by-County-for-CMS-1644-P.zip. Updated June 29, 2016. Accessed August 25, 2016.

The Medicare Shared Saving Program benchmark can be improved by following the example of Next Generation accountable care organizations, but with a larger adjustment level.

Using a Modified Next Generation ACO Benchmark Can Improve the MSSP

 Implementing “Lean” methodology as a way to build requisite skills, enhance collaboration, and eliminate complicated work patterns for positive outcomes (eg, lowered costs, improved patient wait times).

A Lean learning project, facilitated by a locally sourced Lean learning organization, is documented at an autonomous internal medicine practice with the goal of improving patient wait times throughout the practice. Lean learning principles are modified to accommodate ambulatory care settings. Barriers to physician and practice involvement are minimized to encourage physician and practice engagement.

Initial quantitative results showed improvement in patient flow through the practice and time/cost savings that will continue to accumulate over time. Qualitative results show greater change management skill and capacity, as well as awareness and appreciation of team members and collaborative work in this ambulatory care setting.

The increase in change management skill and capacity is critical to the success of transformation efforts in ambulatory care and finding ways to reduce barriers to direct physician involvement and physician practice involvement must remain high priority.

Transforming healthcare is a favorite topic in newspapers and professional journals, with the promise of reformed care delivery methods, improved quality, and patient satisfaction, while reducing overall costs.

 Achieving this Triple Aim in healthcare is essential to ensuring the long-term health of our population and the stability of the economy.

 There is consensus that the patient-centered medical home (PCMH) model of care holds the greatest potential as a road map for the transformation of clinical care; however, implementation of the PCMH model requires significant change to care delivery structure, culture, payment models, and traditional leadership. Ambulatory care settings currently incentivized to advance the PCMH model lack significant leadership and quality improvement (QI) capacity.

 Incentivizing practices to move forward with transformative efforts without prerequisite skills to manage change effectively is counterproductive and may be the reason more significant success has yet to be achieved. Extending the PCMH model into a robust and cooperative patient-centered medical community (PCMC) is the vision that must be achieved in order for sustainable and meaningful transformation to occur.

Impeding adoption of the PCMH model are complicated work patterns developed over years in response to extrinsic demands by the system, patients, and payers, as well as a lack of methodology to effectively manage change. Elimination of these complicated work patterns is a critical first step, and cannot be done without investing in change management, leadership, and QI skill development in autonomous ambulatory practices. These skills, robustly developed, render organizations capable of enduring transformation, rather than simply making brief problem-oriented adjustments. “Lean” methodology is a way to build requisite skills and eliminate complicated work patterns in a single initiative.

Northern Physicians Organization (NPO), in Traverse City, Michigan, believes that investment in the development of Lean thinking in autonomous practice settings is of prime importance to realizing the goals of transformation and quality care for patients. NPO is a physician-led provider organization representing over 500 physicians in northern Michigan, assisting practices of all sizes in the move from fee-for-service to fee-for-value. NPO believes the practices it represents are well suited to Lean methodology for QI, as Lean builds leadership and improvement skills in the individuals who perform the work through the entire vertical structure of the organization. NPO, in partnership with the Northwestern Michigan College (NMC) Training Services Department, is bringing Lean thinking to ambulatory office practices, and one project case study is described in this paper.

Thirlby Clinic is a 9-physician adult internal medicine practice in Traverse City, Michigan, which opted to pursue a Lean learning initiative at the encouragement of NPO. Although Lean is gaining momentum in healthcare, according to Heather Fraizer, PhD, of the NMC Training Services Department, the majority of Lean projects are initiated within large organizations and acute care facilities. These larger initiatives become less about transferring long-term skills and more about solving specific problems by reproducing institutional solutions. Thirlby Clinic’s business manager, Louise Kilmer, has been party to large institutional and system changes in her 40-year healthcare career. She believes that employee empowerment resulting from Lean is most beneficial to businesses like hers. Deb Schepperly, the clinical quality manager, was “sold on Lean principles,” as she believed, for the first time in many years, that changing the landscape of healthcare was possible.

With a Lean project on the agenda, the practice identified a physician champion in Peter Alvarado, MD. Physician champions are critical for healthcare change demonstrations,

yet they are often the most difficult element to secure. This lack of engagement is driven by many factors, including a deep sense of personal autonomy that frequently conflicts with principles of quality improvement, a culture of blame that can result if mistakes happen and priorities for quality seem at odds between the system and individual care perspectives.

 Physician support signals value and significance for the process to all team members in a powerful way. “The physician’s role is central, and the commitment and drive must come from the physician level.”

Dr Alvarado secured consensus that practice physicians would not impede the efforts of the team, despite varying levels of physician enthusiasm and readiness to participate. Leading by example and assisting the practice to implement change systematically and incrementally was Dr Alvarado’s strategy to allow Lean to spread through the practice culture.

A 10-person multidisciplinary team—formed with representation from physician, administrative, clerical, clinical, billing, and laboratory staff&mdash;was tasked with the broad goal of improving patient flow through the practice. This goal allowed the team to determine problems using Lean methodology, which, in turn, helped them to avoid anchoring to preexisting conceptualizations of problems and their origins.

With project roles, scope, and purpose clarified through a project charter, the team proceeded to an introductory simulation of how Lean could impact a different healthcare setting. The simulation brings team members together onto a “level playing field,” where individual team members’ positions or status in the practice is not important to the work they do in the simulation. Gayle Gwizdala, MD, the second participating physician, felt that this leveling effect was important for their team, as it created a true collaborative environment.

Dr Fraizer met with the team for 2-hour sessions, roughly every 2 weeks, following the simulation, accommodating shorter work periods that minimize disruption to patients and nonparticipating office staff, while remaining true to Lean principles of coaching teams where the work is performed. To analyze their current work process, the team created a value stream map (VSM) of each patient’s journey through the practice, with the task of improving patient wait times. VSM is a paper-and-pencil tool that helps teams to visualize and ultimately understand the flow of material and information as the patient moves through care (the “value stream”). The VSM takes into account not only the activity of the patient, but the management and information systems that support the process. The information gathered in this tedious but critical step represents more than just the assigning of time or collection of metrics. According to Dr Gwizdala, the mapping process results in a deep appreciation for the work of others on the team and for the rollover effect that process changes in one aspect of care have on other team members. This forging of interdisciplinary respect and team mentality was believed by both Dr Gwizdala and Ms Schepperly to be the biggest benefit to the VSM process.

Using the VSM and a multidisciplinary team, problems were identified in the process that create bottlenecks to patient flow. The team then quantitatively ranked these problems based on the impact that change would have on the value stream and how easily the problem might be solved. The ranking approach allowed priority problems to surface that decrease the value to the customer, while de-emphasizing totally disruptive, across-the-board change; Dr Fraizer refers to this as the sweet spot of change. The quantitative approach reduced individual perceptual and emotional biases and brought the team to consensus with greater efficiency, resulting in the identification of 4 clear problems that the team could focus on improving.

Work groups formed for each identified problem to develop solutions using rapid development plans, known as Plan/Do/Study/Act (PDSA) cycles with guidance from Dr Fraizer. Constant refinement of solutions kept the impact of change minimized. During this time in healthcare, where change fatigue is a real danger, Lean returns a sense of control to physicians and staff members.

Lean thinking continues to grow at Thirlby Clinic, and results are already evident. Tangible effects, both quantitative and qualitative, are further discussed in the context of the 4 identified problems:

1. Improve Scheduling Patient Appointment Availability

The clinic was not able to achieve the 30% availability of open access appointments as part of their PCMH functions in the past. This had been an elusive goal, with physicians expressing concern that open appointments would remain open and subsequently become lost income potential. Dr Alvarado was instrumental in securing a 15-minute open same-day care (SDC) appointment for every half-day worked from each of the clinic’s 9 providers. Previous attempts by administrators to make this change failed due to a lack of true buy-in by physicians. Late morning and afternoon appointments were typically kept open, although the physicians do control where open appointments are placed based on individual needs. Electronic scheduling software that tracks appointment openings, permits easy changes, and provides quantitative feedback to team members as the process is refined.

 One problem identified almost immediately was the absence of a clear definition or shared understanding of what constituted an SDC appointment. Some believed SDC appointments were to be used for acute care visits only, and were therefore usually booked a day or 2 in advance. The team developed a clear definition of the term and disseminated this definition to the entire practice. The clinic also stopped screening calls to see if appointments were deemed as “necessary,” instead employing the now-universal operational definition that an SDC appointment accommodates the patients’ needs. “It is needed by our patients and this is what matters. We don’t judge why our patients want a same-day appointment because we don’t live in their world,” summarized Deb Schepperly. Patients were educated about the changes through signs in the waiting and exam rooms, messages on the website, closed-circuit TV messages, and recorded telephone reception messages, as well as through direct discussion with office staff. Patients were happy to see their usual provider rather than being sent to urgent care.

The clinic now offers 20% SDC appointments and estimates that 6 minutes are saved per open appointment, largely due to the elimination of administrative coordination overhead between front staff and physician or clinician. With 12 open appointments per day, this equates to 72 minutes of time saved every day that can be repurposed. With the 20% SDC process standardized, Thirlby Clinic is moving forward to eventually meet the 30% SDC requirement. Physicians have found that open appointments are rarely unused, and so it paves the way for the practice to more easily increase the fraction of open-access appointments up to 30%. The team prioritized the value of the patient’s time, thereby generating substantial time savings for the practice and increasing patient satisfaction.

The work group assigned to apply the 5S (Sort, Straighten, Shine, Standardize, and Sustain) method to the common work areas took their task very seriously, and they were amazed at how many unneeded items cluttered their work and mental space. Minimizing disorder in an office environment by keeping the work area clean and organized minimizes interruptions; fewer unnecessary interruptions—which healthcare workers are prone to experiencing due to the inherently coordination-intensive type of work

—keeps providers’ mental reserves ready to tolerate and cope with the necessary disruptions that will occur.

 The work group liberally applied 5S to their own work environments, which quickly spread to staff members not directly involved in the project. Employee satisfaction increased, as did their productivity; the 5S improvements smoothed awkward work processes and increased employee pride and ownership in the office. These benefits, although challenging to quantify, were agreed to have increased productivity through minimized rework and employee retention over the long term. The clinic very conservatively estimated 30 seconds of savings per staff member per day, which seems trivial, but over the course of a month, and distributed across such a large practice, it equates to 4 hours of time available for any number of things that compete for attention in healthcare practice.

Medication refill requests; estimated at 40% of all incoming phone calls/faxes, represent a substantial time demand for the practice. The work group opted to take a 2-pronged approach, addressing patient education and physician ordering practices. The considerable scope of this change suggested the need for smaller group trials of possible solutions to minimize practice disruptions. Solutions were trialed with the 2 participating physicians before rolling out to the full practice. Signs and outgoing messages were used to remind patients about changes to the medication refill process. Physicians changed their renewal habits to ensure that stable medications were renewed for 1 year at a time and were reminded to do this using messages on their computers.

Over the course of 2 months, the clinical staff has noted a 25% to 35% reduction in phone calls and incoming faxes for the 2 providers who implemented the changes. Dr Alvarado took an additional step to reduce phone calls by ensuring that his patients had labs drawn in advance of their appointments. Although some additional work by the physician is necessary, the benefit is tremendous: patients appreciate having results at the time of their appointments and physicians appreciate having all the information required to develop treatment plans and coordinate care. The opportunity to discuss the results and the suggested treatment plan within a single visit allows the patient to ask questions and optimizes their participation in shared decision making. Patients value this time and note that it is a better quality of appointment.

With the reduction in phone calls, each of the 2 physicians estimated a 15-minute weekly time savings, and clinical/front office staff noted an hour of weekly time savings. Time savings for each of these represent increased capacity for additional work. Lisa Reed, a licensed practical nurse involved in the Lean project, stated, “I find myself at the end of a day and I know my work is done. I feel as though I am on top of what is happening instead of playing catch-up. It feels great!”

Formal metrics that document tangible time savings, continue to provide increasing momentum for providers who were initially skeptical. With the original Lean project complete, Dr Alvarado and Ms Schepperly continue to champion these changes to the remaining practice members. The standardization of processes across the practice is the next stage, although Dr Alvarado observed that the word standardization “can be a scary thing” for a physician. He went on to explain:

“In regards to standardization, physicians may find the concept of standardization a little scary or unsavory because they may feel that they lose autonomy or are relegated to practicing cookie cutter medicine. However, standardization often lessens the workload, decreases complexity, and is less onerous on staff. Once you get through the scariness of the unknown, very often standardization is better medicine and more efficient.”

4. Improve the Check-in Process, Increase Lab Function, and Decrease Documented Wait Times

In order to streamline the check-in process, the assigned work group implemented a patient kiosk in the waiting room that allows patients to check themselves in and update records, as needed. The team knew that a percentage of patients would never use the kiosk, and therefore, the manual check-in process could never be completely eliminated. On average, 110 patients are seen in the clinic daily; of these, 27% choose to use the kiosk. Each normal check-in occupies a front staff member for an average of 2 minutes, so kiosk check-in saves the practice about 60 minutes a day.

The team is still evaluating processes to improve efficient use of the lab. However, the team has recognized through analysis of the smaller PDSA trial for phone call reductions, that lab capacity would be a significant problem if performing lab draws in advance of appointments became standardized across all physicians in the practice. The implication of the process changes suggested by the PDSA trial kept the practice from making changes that could not be effectively implemented. Management of change and anticipation of the consequences of change is a key benefit of Lean methodology, particularly when implementing multidisciplinary team solutions.

Comparison of the pre-Lean VSM to the clinic’s current state is enlightening. Pre-Lean, patients were in the office for 1 hour, and 10 minutes of this was face-to-face time with the physician. Through the use of the collective changes noted previously, the average patient now spends 47 minutes in the office, but still receives 10 minutes of face-to-face time with the physician. Lean thinking then, reduced wasted time by 22%, while preserving physician—patient time—time tightly coupled to both patient and provider satisfaction.

 As the practice engages more physicians and staff members, further reductions in time waste and increased capacity to engage in activities that bring value and revenue into the practice are expected.

The benefits of Lean thinking are seen beyond the outcomes from specific work projects. Individual departments are now meeting specifically to focus on improvements, and employees are now engaged in the problem-solving process. There is greater overall awareness and discussion about change management; provider and provider/management meetings have time reserved to discuss changes happening within the organization. The common thread is that rather than having change thrust upon the practice, the full team has gained the necessary skills to continue the work of proactive management.

Lean is seeping into all aspects of Thirlby’s practice as team members are energized by their success, combined with newly acquired skills. As noted above, significant time savings resulted from the introduction of Lean methodology and will continue to accumulate with spread to the rest of the office. However, even a limited implementation of Lean methodology in the case study practice has resulted in notable effects on patient satisfaction, outcomes, and cost of care.

The biggest challenge to the Thirlby’s Lean effort was gaining active physician participation, which is a universal challenge recognized in the literature.

 The next step to increase Lean momentum in NPO’s practice base is to continue generating physician-to-physician opportunities to discuss and affirm the benefit of Lean initiatives. Direct physician endorsements are meaningful to other physicians; the knowledge that another physician has been able to manage and find benefit in change, is far more impactful than the same message delivered in any other way. In addition to engaging physicians and their practices in Lean transformation, NPO will continue to seek funding sources to assist practices in making this journey. According to Dr Alvarado, adoption of Lean methodology by practices will be facilitated by reducing financial barriers to participation.

Lean championship training—the extension of initial projects&mdash;more robustly develops Lean methodology in practice leaders, ultimately building a base of effective change agents that will become communities’ future healthcare leaders. NPO considers the adoption of Lean methodology strategically critical in its plans to support its member practices through transformation. NPO believes that by providing skill development opportunities and a plan for how change can happen, Lean methodology will provide foundational building blocks essential to success in this new era of healthcare. Without the fundamentals required to lead and manage change, forced transformation is wasteful and counterproductive.

A major obstacle to Lean adoption for physicians and practices is the time required for the learning process. An estimated 192 hours of time was spent by the 10 interdisciplinary team members between November 2014 and June 2015; however, this is gross time expenditure and the net time spent is considerably less. For example, the changed prescription renewal process alone resulted in an hour of time saved across the practice daily. With this single process change, the use of Lean thinking returned more than the time cost of the entire demonstration period, and furthermore, the benefit of change continues accumulating into the future. Thin financial margins—far from constituting an argument against change&mdash;are the primary reason to invest in skill development. Efficient change management is critical to survival during this time of transformation.

Practices in ambulatory care settings must remain operational during the learning process.  This ultimately limits the participation in any Lean learning experience to a fraction of the staff and providers any one time, thus challenging the spread of change throughout the rest of the organization. Lean learning however, develops not just a changed process for those that participate, but also the capacity, flexibility, and creativity required for meaningful and sustainable change to continue. This skill enhances the ability of practices to spread adoption, and, ultimately, changes the organizational culture, thereby moving once immovable attitudes.

Another limitation in the use of Lean learning in ambulatory care settings that are geographically remote is access to qualified Lean leaders and facilitated learning experiences. Lean experiences that are subsidized by outside sources can be rigidly imposed and contracted which can be prohibitive to ambulatory care settings and independently owned physician practices who require flexibility in order to participate. 

NPO’s investment in initial Lean learning, and its continued commitment to extended learning, demonstrates that practices can develop the skills and capacity required to effectively manage change and build on successes, extending the reach of transformative efforts while minimizing the risk of change.

Practice engagement in Lean results in far greater results than the use of tools and understanding of Lean terminology. Leadership skill and collaborative work habits create efficiency and even greater capacity to further transformation efforts. Future implications include the elimination of barriers to physician and practice involvement in Lean learning in the ambulatory care setting such as subsidizing costs and adaptation to time and physical restrictions.  Physician engagement may be the biggest future implication and need for development as the health system advances in the transformation from fee-for-service to fee-for-value. The involvement of physicians, the traditional leaders of healthcare and whose relationship with the patient are the basis of healthcare as a whole, is essential to the process. Physician engagement of other physicians is likely the best hope in moving this mark

Lack of time is a common argument against transformation, but tools that reduce time inefficiencies and develop change management skill are most likely to successfully overcome this argument. Efficiency translates into more time spent with patients working on their health, a greater capacity to succeed in change, and greater satisfaction for patients, physicians, and staff members. NPO believes that achieving the Triple Aim in healthcare is well within our reach, and is committed to empowering its members with Lean methodology, 1 physician and practice at a time.

Ms Nicolaou would like to acknowledge Dr Peter Alvarado, internist, Thirlby Clinic; Dr Heather Frazier, PhD, training specialist, Northwestern Michigan College, Training Services Department; and Deb Schepperly, clinical quality manager, Thirlby Clinic. The Thirlby team is grateful for the leadership and guidance of Dr Fraizer, whose contribution extended far beyond teaching methodology. Deb Schepperly commented that Dr Fraizer’s modelling of behavior and approach to coaching throughout the project imparted leadership skills and confidence to the team, allowing them carry on using Lean within the practice. Ms Nicolaou would like to thank the staff of NPO for being truly dedicated coworkers and the intellectual people that they are. Specifically, she would like to thank Marie, Kris, Ed, and her husband David for their mad editing skills and never ending drive for better healthcare.  

 Northern Physicians Organization, Traverse City, MI.

The author reports no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content; administrative, technical, or logistic support.

 Lisa M. Nicolaou, RN MSNI, Clinical Process Analyst, Northern Physicians Organization, 300 E Front St, Ste 240, Traverse City, MI 49684. E-mail: lnicolaou@npoinc.org.

“Lean” methodology creates quality improvement and leadership capacity, which is currently missing in ambulatory care settings. Failure to create this capacity will minimize transformation efforts.

Quality Improvement  and Leadership Capacity Development Through Lean Methodology 

Little is known about how providers within accountable care organizations (ACOs) perceive ACO utility in early stages of operation. We explored initial perceptions of providers participating in the Johns Hopkins Medicine Alliance for Patients, LLC (JMAP), within 6 months of launching as an ACO.

 The survey was administered to primary care and cardiology providers in JMAP entities, including medical school faculty and physician practices, a regional ambulatory care network, and 3 additional community practices. We assessed their satisfaction with the care provided and perceptions of the ACO model, inter-provider coordination, and interventions likely to facilitate high-quality and cost-effective care within the organization. We compared perceptions by entity type and provider’s clinical area.

About half of invited providers responded, and a considerable proportion (29%-49%) was neutral in rating their comfort, understanding, or expectations about becoming an ACO. Community practice providers were the most positive about becoming an ACO, and faculty providers were the least satisfied with the chronic care they were providing. Cardiologists reported better coordination with hospital teams than did primary care physicians; cardiologists also reported a higher frequency of communication with primary care practices than vice versa. Interventions to facilitate care coordination and provide more comprehensive care, such as use of care coordinators, behavioral therapists, or support staff to facilitate gaps in care, were considered important for success.

Six months into JMAP operations, providers gave ambivalent responses about their understanding of the implications of being an ACO, and subgroups within the ACO held different views. Data pointed to room for improvement in care coordination and care delivery interventions moving forward.

To improve the quality and efficiency of healthcare, the US health system is increasingly shifting from fee-for-service to value-based payment models. An accountable care organization (ACO), through the Medicare Shared Savings Program (MSSP), is a model created under the Affordable Care Act to facilitate this transformation.

 In collaboration with a payer, provider groups voluntarily assume responsibility for quality and costs of care for a defined population of beneficiaries. If quality and spending targets are met, the provider organization may keep a portion of savings achieved. There are currently more than 740 ACOs in the public and private payer health sectors,

 and most of the US population lives in an ACO service area.

 Early results demonstrate potential flattening of the cost-curve, decreased utilization of emergency and postacute care, and improved clinical quality.

Engagement of healthcare providers facilitates success of ACOs.

 Perceptions of providers regarding ACOs in early stages of development have, however, been largely unexplored. Although previous research has identified effective inter-provider communication and shared objectives as essential to ACO performance,

 these dimensions of relational coordination have not been assessed among participants in ACOs at academic medical centers (AMCs). Compared with other settings, the challenges of provider engagement may be different for emerging ACOs at AMCs, which have to combine this new care delivery model with their clinical, research, and educational missions.

We surveyed providers within a new, large AMC ACO for their perceptions of the model, satisfaction with care provided, assessment of inter-provider coordination, and utility of interventions likely to facilitate high-quality and cost-effective care within the organization.

The Johns Hopkins Medicine Alliance for Patients, LLC (JMAP), is a non—risk-bearing MSSP ACO that was launched in January 2014 (

 Primary participating entities include: Johns Hopkins University Clinical Practice Association, comprising School of Medicine faculty and physician practices (hereafter referred to as SOM); Johns Hopkins Community Physicians (JHCP), including primary and specialty care outpatient sites; 2 primary care practices unaffiliated with Johns Hopkins Medicine (JHM); 1 cardiology community practice with a preexisting JHM relationship; and 5 JHM hospitals, which are all in Maryland and Washington, DC. There are approximately 2900 providers and 38,000 Medicare beneficiaries associated with JMAP.

JMAP undertook a multi-pronged communication effort at the program’s outset to inform providers and staff of JMAP goals and expected provider and beneficiary impact.

 Initiatives featured provider- and staff-focused webinars; practice-site “road show” visits; and clinical-, management-, and operations-related committee presentations. In addition, JMAP leadership established 3 regional advisory councils, which include medical and administrative leadership from each clinical site within the JMAP catchment area, to disseminate information and receive feedback on challenges or opportunities.

 To assess provider engagement and determine future interventions of focus, JMAP launched a provider survey in July 2014, approximately 6 months after ACO operations commenced. The survey was intentionally performed at outset of the organization to serve as a baseline of perceptions and also to assist in identifying priorities and strategies for management. At survey administration, the ACO outreach interventions previously described had been deployed. Medical and quality interventions were early in development and included implementation of care coordination in a high-risk subset of the Medicare beneficiary population in Baltimore through a related initiative. Within the ACO, providers or practices initially referred beneficiaries for care coordination support with JMAP. Early in 2015, the process transitioned to also employ a risk-prediction algorithm to identify beneficiaries most likely to benefit from available services. Other ACO interventions implemented in late 2014 included expanded population health functionality in the electronic health record (EHR) system and internal monitoring of ACO quality measures.

We invited all JMAP primary care (internal medicine practitioners, general practitioners, and geriatricians) and cardiology providers by e-mail to complete an online provider survey. The survey was launched in mid-July 2014 and closed in early August. The Johns Hopkins Institutional Review Board and the JMAP Board of Directors reviewed and approved the instrument, which was constructed using both previously validated

 and original items for the purpose of quality improvement (

). Response choices were yes/no or agreement on a 5-point Likert scale, or were open-ended to allow elaboration. The survey included questions in 8 domains, including provider demographics; satisfaction with the care of chronically ill beneficiaries; and coordination, staff support, and resource use in the provider’s group practice.

Another domain asked to which hospital the provider sent beneficiaries most often, how frequently the inpatient and outpatient teams communicated, whether communication was timely, and the extent of shared goals and problem-solving between the hospital and the responding provider—the same dimensions of relational coordination supported in a recent paper by Rundall and colleagues.

 Additional domains investigated coordination among providers, providers’ understanding of the ACO, and how likely they believed certain interventions were to facilitate high-quality and cost-effective care.

The final domain included 2 open-ended questions to elicit more general feedback: “Do you have any ideas of how to improve the quality or efficiency of care provided within the ACO?” and “What are things that are being asked of you day-to-day, that, if removed, would not negatively impact the quality of patient care?”

We compared respondents’ demographic and professional characteristics among ACO subgroups using Fisher’s exact tests for categorical variables and Kruskal-Wallis tests for continuous variables. To assess the differences among subgroups in rating coordination, communication, and perception of ACOs, we constructed ordinal logistic regression models to fit the ordered, discrete nature of the Likert-scaled dependent variables, and we adjusted for the respondent’s age, sex, years in practice, medical specialty, and clinical training. We accounted for clustering of responses from the same ACO subgroup using a fixed effect (dummy variable) for each group. To present how respondents rated interventions that may help achieve the ACO’s goals, we calculated the proportion of responses in the top 2 categories of the 5-point Likert scale—“very likely” and “likely”&mdash;by ACO subgroup. We examined differences among group preferences using binomial tests. All analyses were conducted using Stata software, version 14 (StataCorp LP, College Station, Texas). We report 2-sided 

The authors’ survey of providers in a new accountable care organization reports that initial perceptions of this care model are ambivalent and vary among participating practices.

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