- Chronic disease management is one of the healthcare system’s greatest challenges, sapping billions of dollars from payers, patients, and providers each year. Managing the complex needs of patients with diabetes, heart failure, asthma, COPD, kidney disease, and other long-term conditions can cost up to seventeen times more than other patients, which can add up to almost $40,000 per beneficiary per year.
While healthcare organizations have been committed to lowering these costs by embracing innovative care strategies and data-driven population health management techniques, patients are still ending up in the emergency department – or back in the hospital after an initial discharge – at unsustainable rates.
Medicare is particularly eager to quickly and effectively slash spending on chronic diseases as it stares down an uncertain financial future, a rapidly aging population, a growing shortage of qualified clinicians, and an uphill battle to convince providers that abandoning the security of the traditional fee-for-service model is in the best interests of the industry as a whole.
In an effort to help illuminate the dire straits of the healthcare ecosystem – and equip stakeholders with the information they need to make smarter spending decisions – CMS has started to release new datasets that clearly illustrate just how much concerted effort is required to make a dent in the financial and clinical burdens of chronic disease, especially for minority patients.
“In 2014, two-thirds of Medicare beneficiaries had multiple chronic conditions and accounted for 94 percent of Medicare spending,” explained Cara V. James, PhD, Director of the Office of Minority Health at CMS in a blog post. “Racial and ethnic minorities experience disproportionately higher rates of disease, inferior quality of care, and reduced access to care as compared to their white counterparts.”
“Understanding disparities and their geographic variations is important to inform policy decisions and to identify populations and localities to target for interventions.”
To that end, CMS has developed the Mapping Medicare Disparities tool (MMD), a freely available, interactive dataset that starkly illustrates the geographical distribution of vulnerable populations.
While it might not come as much of a surprise that conditions like diabetes, obesity, and heart failure are more prevalent in the south than the northern regions, the data on spending, emergency department visits, and hospital utilization is a little less predictable.
Using data from the MMD database, HealthITAnalytics.com examines some of the chronic disease management patterns that directly impact healthcare spending in the United States.
Cost and prevalence do not always align
The healthcare system has always struggled with regional variations in price and quality, and the MMD data makes it clear just how wide the gaps can get when crossing state lines.
The states with the highest rates of typically costly chronic diseases like heart failure and diabetes aren’t always the ones spending the most on managing these conditions.
When it comes to heart failure, for example, there is a clear difference between states with the highest prevalence of the condition and those that spend the most risk-adjusted Medicare money to manage it.
Sixteen percent of Medicare patients in Texas have heart failure, which costs an average of $23,156 per beneficiary per year to manage. But just north of the border in Oklahoma, where the same proportion of patients suffer from heart failure, it only costs $21,831 to deliver a year’s worth of care.
In contrast, just 10 percent of Maine residents have this condition, but providers spend $23,843 on each patient each year.
The situation is similar when it comes to diabetes, one of the most common chronic diseases in the country. One in three patients in the Deep South may have diabetes, but risk-adjusted spending is actually higher up north.
Louisiana Medicare providers spend $15,657 per beneficiary per year on diabetes care. Next door in Alabama, providers are spending only $13,864 to deliver care.
In New Mexico, it only costs $12,997 to treat a similar patient. In Michigan, that number tops out at $15,933, the highest in the nation.
Some of these disparities may be due to the amount of time and effort healthcare providers have poured into refining their population health management strategies. Regions that have focused on developing more cost-effective techniques for identifying risk and delivering preventative care are likely to be seeing their costs trend downward, though it is difficult to pinpoint these potential patterns with the data at hand.
Worryingly large ethnic disparities in cost and outcomes
When spending rates are mapped by patient ethnicity, the puzzle gets even more complex. In Minnesota, it costs $5435 more to treat a black patient with heart failure than a white one. In North Dakota, the difference is closer to $7000.
Patients of Hispanic background in Texas with heart failure will incur almost $3000 more in yearly spending than white patients. For diabetes, it costs $14,819 to treat a white Texan, $15,529 for a Hispanic person, and $17,624 for a black patient.
Precious research has shown that the racial and ethnic identities of patients are clearly tied to their outcomes. Non-white patients undergoing coronary artery bypass graft surgery have a 33 percent higher chance of mortality after the procedure than their Caucasian counterparts, one study indicated.
Another study found that only 8.3 percent of eligible safety net patients receive routine Hepatitis C screenings. White patients received testing for the virus more than twice as often as patients who identified as Caribbean islanders or Haitians.
Variations in the application of standardized care guidelines have also been implicated in the gulf between colon cancer survival rates of white patients and those of other racial and ethnic backgrounds. Reducing inconsistencies in the application of best-practice treatment protocols may help to decrease state-by-state variations in costs and improve outcomes for vulnerable populations.
The challenge of managing multiple comorbidities
Patients who incur the highest costs are usually the ones with the most complex problems. One case study from Pennsylvania found that the top three percent of “persistent high users” of healthcare services counted for more than 20 percent of annual healthcare expenditure. Close to three-quarters of all healthcare costs between 1970 and 1996 are attributable to just ten percent of patients, the study added – and as the prevalence of chronic diseases increases, those numbers are slated to keep rising.
Again, there is a clear racial and ethnic disparity in spending rates. Chronic disease management costs for black patients with more than three comorbidities is an average of $2000 higher than the costs for treating white patients.
Interestingly, the geographical distribution of complex patients appears to be almost the exact opposite of how much it costs to treat them. While patients with three or more chronic diseases are most common in the Southeast of the United States, risk-adjusted spending is significantly higher in the Northwest.
Complex patients in the Deep South are among the least likely to experience a hospitalization, however. Residents of the Midwest and Maine end up in the inpatient setting most often.
No one region can lay claim to the secret of preventing avoidable hospital readmissions, however. Readmission rates for patients with multiple chronic diseases are slightly higher in the Northeast, but remain relatively even from coast to coast.
This may indicate that the variation in the amount of money being spent to manage these patients is not significantly impacting readmission rates, and that providers may need to investigate additional population health management strategies if they want to improve their performance on this key quality indicator.
Using data analytics to improve population health management
Statistics like these are vitally important for helping healthcare organizations identify the challenges of chronic disease management, which are often obscured by the day-to-day rush to get patients in and out of the door.
As CMS says in its Equity Plan for Improving Quality in Medicare, the agency “has an important opportunity and a critical role to play in promoting health equity,” starting with its unique ability to access huge volumes of data to present to the healthcare community.
CMS has targeted data analytics as its top priority, stating that improving its ability to collect, analyze, and share healthcare utilization and spending data is the first step towards understanding health disparities and addressing the industry’s shortfalls.
“Comprehensive patient data, including race, ethnicity, language, sexual orientation, gender identity, and disability status are required to plan for quality improvements, and to address changes among the target populations over time,” CMS says.
Using a combination of big data analytics, policy levers, quality improvement activities, and its unparalleled ability to communicate with stakeholders, CMS hopes to provide healthcare organizations with the tools and resources they need to apply clinical guidelines consistently for patients of all ages, identities, abilities, and backgrounds.
As these efforts combine with the growing sophistication of population health management and big data analytics tools, healthcare providers will soon be able to develop the broad competencies they need to reduce health disparities and manage chronic diseases more effectively and at a lower overall cost.