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Project Tracks Impact of Reform on Hospital Use

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(IHA is closely monitoring the impact of the Affordable Care Act and, in particular, Medicaid expansion, which is being implemented through the Iowa Health and Wellness Plan.  As we have shared, preliminary studies indicate early success in meeting the essential goals of health care reform.  With that in mind, IHA is one of 24 state hospital associations working with the Robert Wood Johnson Foundation [RWJF] on its Hospital ACA Monitoring Project, which is described below, to further study progress.  Reprinted with permission.)

HealthCareReformihaTo monitor the impact of health reform on hospital utilization, the Robert Wood Johnson Foundation has embarked on an important surveillance project, working in collaboration with 24 state hospital associations. The RWJF Hospital ACA Monitoring Project, or HAMP, collects data each quarter on all inpatient admissions and emergency department (ED) visits by payer. HAMP also collects some information on a subset of diagnoses and procedures that are believed to be sensitive to insurance status.

Clearly, there are a variety of ways in which health reform may affect hospital utilization. Conventional wisdom might suggest that coverage expansion will result in fewer preventable hospitalizations, and less use of the ED for ambulatory care sensitive conditions. However, we saw in the Oregon Medicaid experiment that increased Medicaid enrollment resulted in more ED use. Another possibility is that increased demand for primary care may overwhelm the ambulatory care system, resulting in increased use of the hospital for primary care treatable conditions, even among those who were previously insured.

The potential financial impact of health reform on hospitals is also unclear. While the reduction in uncompensated care is clearly a plus, there may be significant increases in utilization by patients who have payers that reimburse at relatively low rates. Further, there is a possibility of increased bad debt from patients with Marketplace plans, which require significant cost-sharing. Additionally, there are reductions in DSH payments and other simultaneous changes in Medicare payments.

The HAMP effort is designed to shed light on some of the effects of health reform on hospitals and provide extremely timely data to researchers, policymakers and hospital leaders. Seventeen state hospital associations submitted information from individual hospitals, while seven others submitted state-level data. There are approximately 1,700 hospitals included in this data set, which is roughly one-third of all hospitals in the country. The participating states and the number of individual hospital submissions are shown in Table 1.

The individual diagnoses and procedures being collected include three reasons for inpatient hospitalization that are considered to be preventable, and have been defined as such by the federal Agency for Health Research and Quality (AHRQ). These include short-term complications of diabetes, hypertension and urinary tract infection. Additionally, HAMP is monitoring admissions for knee replacement—an inpatient procedure that may be sensitive to insurance status. It is also monitoring ED visits for three specific diagnoses that are considered primary care treatable or at least ambulatory care sensitive: upper respiratory infection, urinary tract infection and headache. More details about these specific conditions are shown in Table 2.

The types of hospitals that participate in this project are shown in Table 3. While about 65 percent are acute care hospitals, there are a number of critical access hospitals, particularly in Western states and rural areas. The distribution of participating hospitals is shown in Table 4.

Baseline Data Offers Trends to Watch

Data from 2013 from participating states show great variation in the number of inpatient admissions and ED visits, as shown in Tables 5 and 6. Tables 7 and 8 show the payer mix in the inpatient and ED setting. There are clearly differences between the two. While only about 6 percent of inpatients are reported as being “self-pay”, about 20 percent of ED visits are attributable to the uninsured. The state variation in the percentage of admissions and visits which fall into the “self-pay” category are significant. This range can be seen in Tables 9, 10 and 11. It is clear that certain states have a relatively high share of uncompensated care. For example, 30 percent of South Carolina’s ED visits are in the “self-pay” category, as compared to about 11 percent of those in Nebraska. Inpatient admissions range from about 2 percent self-pay in Minnesota to about 12 percent in Wyoming. Table 11 makes clear that states with a high percentage of self-payers in the inpatient setting tend to also have a high share of self-pay patients in the ED. Tables 12-14 show similar patterns for Medicaid.

One thing that is clear from these tables is that some of the participating states that have expanded Medicaid were exposed to relatively little uncompensated care in 2013. This is the case for Minnesota, Michigan, Connecticut and New York. However there are also a number of expanding states (New Jersey, Nevada, Colorado and Kentucky) that in 2013 had a significant amount of self-pay utilization both in the inpatient and ED settings. Depending on the degree of eligibility and take-up among these uninsured patients, these states may experience a fairly significant change in utilization patterns upon expansion. Early reports from national hospital chains suggest increases in Medicaid utilization and decreases in uncompensated care in expanding states—and no change in Medicaid and increase in uncompensated care in non-expanding states. Similarly, data released by the Colorado Hospital Association showed similar trends in Medicaid and uncompensated care as a percent of charges in Q1 2014 in expanding versus non-expanding states.

Future posts will provide more information about payer mix and utilization by state and variation within states and for more specific diagnoses and procedures. Data for Q1 2014 are expected by the end of the summer.

Katherine Hempstead is RWJF Coverage team director and senior program officer.

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This is how the day often starts for Dr. Daniel Taylor:  “My first patient was a two-week-old, born to a mother, 16, who was sleeping in the same bed with her infant.  The next child, a morbidly obese nine-year-old, was recently readmitted to our hospital for his third asthma attack this year.  With him came his brother, 10, with ADHD and learning issues.  Next up was an 18-month-old with speech delay whose parents are struggling with food insecurity. It was 9:30 a.m., and I still had nine more patients to go.”

Dr. Taylor goes on to reveal the common denominator for these young, struggling patients:  they live in the Pennsylvania First Congressional District, in the heart of Philadelphia, one of the poorest places in the United States.  That location is not unlike Camden, New Jersey, considered one of the nation’s most dangerous cities and the medical home for Dr. Jeffrey Brenner, who impressed a large and attentive audience at the IHA Summer Leadership Forum with his insights into population health and its impact on health care cost.

At the epicenter of Dr. Brenner’s work and that of his organization, the Camden Coalition of Healthcare Providers, are the “super users”, patients who churn in and out of the hospital at an astonishing pace.  Of the 79,000 residents in Camden, 386 constitute the top 1 percent of emergency department (ED) visitors.  In 2011, they made a total of 5,000 trips to one of the city’s three EDs for an average of 13 visits per patient.

Where do these patients come from?  Poverty and lack of access to medical and social services are clearly at the foundation of the issue.  However, there is a factor that many argue is even more important: adverse childhood experiences (also known as ACE or ACE events), including emotional and physical abuse or neglect, exposure to alcoholism, illicit drug use, mental illness, suicide or a household member being imprisoned.

In the mid-1990s, the Centers for Disease Control and Prevention and Kaiser Permanente conducted a large-scale epidemiologic study of the influence of ACE events on the origins of behaviors that underlie the leading causes of disability, health-related behaviors and early death.  In the study of some 17,000 participants, a simple scoring system was used where one point was given for each ACE experience.

The study found that compared to persons with an ACE score of zero, those with a score of four or more were twice as likely to be smokers, 12 times more likely to have attempted suicide, seven times more likely to be alcoholic and 10 times more likely to have injected street drugs.

At the Summer Leadership Forum, Dr. Brenner suggested that the ACE study is a road map to the origins of super users.  It’s no coincidence, he pointed out, that 50 percent of health care spending is attributable to 5 percent of the population, which is about the same portion of the population that has experienced six or more ACE events.

Iowa isn’t Philadelphia or Camden, one might argue, but then neither are all of Pennsylvania or New Jersey (which placed 17th and fifth, respectively, in the most recent Annie E. Casey Foundation “Kids Count” child well-being analysis; Iowa placed seventh).  In every state, in practically every community, there are pockets of social, physical and mental dysfunction that eventually present at the hospital’s doorstep in the form of a super user.

It’s a daunting task, but using tools like the ACE study and IHA ChimeMaps, health care providers can join with social services, law enforcement, education and other agencies to possibly derail the escalation that leads to the chronic mental and physical issues found among super users.  Communication, cooperation and data are the keys, along with the realization that prevention begins long before and far from the ED.

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Process Improvement on Four Wheels

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The tech world seemed to pause a bit last month when Google rolled out and demonstrated its fully autonomous car.  This wasn’t simply another off-the-shelf car retrofitted with the array of computers and sensors needed to make it autonomous, a set-up that manufacturers all over the world have been testing.  No, this was a brand new vehicle with all the gadgetry and none of the excess – meaning no steering wheel and no pedals.

Self-driving cars are intriguing to health care providers, who are more than a little interested in process improvement and safety.  The process in question here – transporting humans and their stuff overland from Point A to Point B as quickly as possible – has been the target of innovators since before the invention of the wheel.

One of history’s greatest process breakthroughs – Henry Ford’s assembly line – drove down car prices, making this new technology widely available to the public.  Unfortunately, that public was not well trained to operate a vehicle that was far faster than the horse-drawn carriage it replaced (though with little improvement in safety equipment).  The nation’s road system was equally unprepared.

This explains why fatalities from car accidents jumped 150 percent during the 1920s.  The Great Depression and the war that followed kept people off the road, easing the carnage, but a robust post-war economy, car-crazy baby boomers, cheap gas and the interstate highway system changed all that.  The late 1960s and early 1970s were the worst years for U.S. road fatalities, peaking in 1972 with 54,589 deaths.

While that is a staggering statistic, when the number of miles traveled is considered, it’s a vast improvement.  In 1972, the fatality rate was 4.3 deaths per 100 million vehicle miles traveled; in 1922, it was almost five times higher.

In the 50 years between, great strides were made in both automotive and road engineering.  Training and licensing laws also improved, particularly with regard to young people.  With even more advancements like airbags and anti-lock brakes, the fatality rate was cut in half between 1972 and 1992 and now hovers around 1.2 deaths per 100 million miles driven.

That still means more than 30,000 Americans die in car accidents each year (and 10 times that number are injured).  Yet, as health care providers can appreciate, further bending of the fatality curve presents an enormous challenge. How much more can be done?  At least part of the answer (again, obvious to providers) lies in mitigating the human element, which brings us back to autonomous vehicles.

More than nine out of 10 automobile accidents are attributable to driver error, so imagine the possibilities of a driver-less car.  Process improvement through automation would increase efficiency by optimizing road and lane availability, reacting more quickly and accurately to traffic changes, decreasing travel times (and accompanying fuel usage and pollution) while increasing safety.

Of course, the biggest obstacle to full automation is our human-designed, human-centered world and our own unpredictability.  It’s a question hospital quality teams constantly face:  How do we teach machines to work in concert with existing systems and around human frailties?

Process improvement within both the health care and transportation industries is challenged by the complexity of human behavior and the fragility of human life.  But it is only health care providers who must pick up and re-assemble the pieces when the transportation process goes tragically awry.

 

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At a recent Citibank conference in New York City, large and not-so-large non-profit health systems presented their business strategies and financial statistics to Wall Street types responsible for financing much of the debt used to propel health systems forward.  Common themes emerging during the presentations were growth strategies largely dependent upon acquisitions in expanding health care markets coupled with significant planned reduction of expense, including debt in the next three to five years.  Also apparent was the pivotal role that public insurance exchanges are playing in the creation of new markets.

Other strategies included focusing on primary care with a strong emphasis on integration of behavioral services as well as focusing on building partnerships with for-profit entities to enhance quality and drive more value into services offered.  Most proffered long-standing views that care delivered closest to the patient was key to enhancing patient experience, lowering cost and providing optimum outcomes.

Interestingly, a key strategy to improve population health was premised on the need for success in the perceived growth area of Medicaid.

A couple of reports issued just this week add support to the premise of the role that Medicaid will play going forward.  First, the Centers for Medicare & Medicaid Services issued a report detailing that six million more people are insured by Medicaid and the Children’s Health Insurance Program (CHIP) in the first quarter of 2014 compared to the July to September time frame for 2013, a 10 percent increase.  Among states that adopted Medicaid expansion and whose expansions were in effect in April, Medicaid and CHIP enrollments increased by 15.3 percent compared to the July-September 2013. Iowa’s increase exceeded 18 percent.  All told, 65 million people (or more than 20 percent of the nation’s population) are now enrolled in Medicaid and CHIP.

The implications of this growth are detailed in a second report issued by the Colorado Center for Health Information.  Absent study, common sense dictates that revenue growth results when the volume of insured patients rises substantially, regardless of the source of insurance.  Believed, but undocumented until now, is the corresponding decrease in self-pay and charity care.

Certainly, these results are early, but the analysis included 465 hospitals across 30 states (including Iowa) with equal numbers (15) of states that have and have not expanded Medicaid.  Specifically, in the states that expanded Medicaid, the proportion of Medicaid charges increased nearly 23 percent (from 15.3 percent to 18.8 percent) while self-pay charges dropped 34 percent (from 4.7 percent to 3.1 percent).  In Iowa, Medicaid increased 12.6 percent (from 11.9 percent to 13.4 percent) and self-pay decreased 19.5 percent (from 4.6 percent to 3.7 percent).

In addition to these hospital data trends, a June 4 Des Moines Register article by Dr. Barry Engebretsen, medical director for the Polk County Federal Qualified Health Center (FQHC), points toward similar trends among FQHCs.

If one considers the Affordable Care Act as two parts insurance reform (the public exchanges and Medicaid expansion) and one part payment reform, (non-payment for re-admissions, bundled payment and Accountable Care Organizations), it’s increasingly clear from sources like the Citibank conference and the Colorado study that intended objectives are beginning to jell, if not solidify.

Is there any doubt where the “Wall Streeters” will place their smart money?

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Providing Insurance, Saving Lives

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me-mapThroughout the national debate over the Affordable Care Act (and Medicaid expansion), critics have questioned whether providing coverage results in better health.  A new analysis adds to the growing evidence that it does.  Providing more people health insurance could save tens of thousands of lives nationwide, according to a study based on data from Massachusetts, whose reforms became the model for much of what is contained in ACA.

Mortality rates in Massachusetts measurably improved compared with similar places around the country after the state began guaranteeing its residents health coverage in 2006, according to researchers at the Harvard School of Public Health, Brigham and Women’s Hospital and the Urban Institute.  Overall, mortality rates declined 2.9 percent in Massachusetts after the reform compared with the control group.  That suggests one death was prevented for every 830 people who gained coverage.  Perhaps more notable:  The reduction was even more pronounced (4.5 percent) in deaths from diseases considered treatable with good access to medical care.

The study, published last month in the Annals of Internal Medicine, also warns that gaps among states in the health of their populations may widen in coming years.  That divide will result from some states taking advantage of federal money to provide health coverage – primarily through Medicaid expansion – and others passing on the opportunity.

Eight years ago, Massachusetts became the first state in the nation to create a system of universal coverage, guaranteeing its poorest residents Medicaid and providing subsidies to help moderate-income residents get insurance on a state marketplace where insurers could not turn away the sick. That structure became ACA’s foundation.  Previous research has shown this system increased access to care and reduced Massachusetts’ uninsured rate, now at less than 5 percent, the lowest in the nation (Iowa’s uninsured rate is about 10 percent, among the 10 lowest in the nation).

A similar trend is emerging nationally.  A nationwide Gallup poll released in May showed the percentage of working-age adults without coverage dropped from 18 percent last fall to 13.4 percent in April.  That’s good news, as is the fact that about half the states have joined Iowa in expanding Medicaid.  The bad news:  Many of the states that have refused to expand are, according countless studies and measures, among the nation’s least healthy.

There are doubters, many of whom still point to research conducted on Oregon’s 2008 Medicaid expansion.  That study found people who gained coverage made little progress controlling their cholesterol and blood pressure compared with low-income Oregonians without Medicaid.

In the long-term, those are certainly concerns.  However, Oregon’s short-term gains are arguably more significant, including dramatically improved connections to primary care providers and use of preventive screenings.  Medicaid coverage also improved self-reported well-being and significantly reduced the likelihood of depression.  And being insured made health-related financial issues much less likely. It’s also worth noting that despite Medicaid’s supposed shortcomings in improving health, no one in Oregon dropped their insurance.

As with all research, the Massachusetts study comes with the normal advisory:  Results may vary.  The researchers noted that many other states do not have Massachusetts’ health care advantages, such as broad insurance coverage, a record of tracking quality and a civic tradition of working to improve health.

Sounds like the Hawkeye State and the Bay State do indeed have a lot in common.

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