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Predict Heart Failure

Identify high-risk HF patients, guide them into care programs, and reduce hospitalizations and costs.

Problem

Heart failure — sometimes known as congestive heart failure — occurs when the heart muscle doesn't pump blood as well as it should. When this happens, blood often backs up and fluid can build up in the lungs, causing shortness of breath. Certain heart conditions, such as narrowed arteries in the heart (coronary artery disease) or high blood pressure, gradually leave the heart too weak or stiff to fill and pump blood properly.Proper treatment can improve the signs and symptoms of heart failure and may help some people live longer. Lifestyle changes — such as losing weight, exercising, reducing salt (sodium) in your diet and managing stress — can improve your quality of life. However, heart failure can be life-threatening. People with heart failure may have severe symptoms, and some may need a heart transplant or a ventricular assist device (VAD).

Why it matters

  • $70 billion is the projected economic cost in 2030 for patients with HF (1).
  • 6.5 million adult Americans are living with heart failure (2).
  • 10% of HF patients survive 10 years after being diagnosed with HF (3).
  • 33% of all Medicare costs are for patients with heart failure (4).

Today, approximately 6.5 million adult Americans are living with heart failure (HF) (1).By 2030, this is estimated to rise to 8 million people with total economic costs reaching $70 billion at which point 2.97% of U.S. adults will have HF and 71% of them will be age 65 or older (2). With more than one million hospitalizations each year, HF is one of the most common causes of admissions and readmissions and a leading cause of mortality; after a diagnosis of HF, survival estimates are 50% and 10% at five and ten years, respectively (3).Beneficiaries with HF constitute 10.5% of all FFS Medicare beneficiaries and their costs (excluding medications) make up 33.2% of all Medicare costs (4). HF is a chronic disease characterized by acute exacerbation, and a major cost driver is treatment for worsening HF and fluid overload, 80% of which occurs in inpatient settings (2,3). Many instances of hospitalization for HF patients are considered preventable, yet HF remains the leading cause of hospitalization for patients over age 65 (2,5). HF admissions also generate the highest number and highest rate of 30-day readmissions among Medicare beneficiaries (6,7).

Solution

Organizations can employ predictive analytics to identify high risk HF patients and use insights from AI to enroll patients in care management programs. Proactively identifying high-risk HF patients and intervening to prevent significant exacerbations that cause hospitalization is essential to improving quality of life and reducing avoidable costs. For example, interventions centered on patient self-management have been shown to reduce the odds of readmission after one year by 40% (8). Such programs prevent hospitalizations by strengthening care continuity, improving adherence to complex medication regimens, and ultimately identifying early warning signs more readily.

Datasources

  • Medical Claims: Data extracted from health insurance medical claims with details about dates and place of service, diagnosis codes, key procedures, use of medical equipment, and provider specialties.
  • Rx Claims: Data extracted from health insurance pharmacy claims with details about each medication and its type, fill dates, days supply, pharmacy location, and prescribing clinician.
  • Electronic Health Records: EHR data with comprehensive patient histories of vital signs and symptoms, problem lists and chief complaints, tests results, diagnoses and procedures, and prescriptions.

Citations

  1. Benjamin, Emelia J., et al. “Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association.” Circulation, vol. 139, no.10, Jan. 2019.
  2. Fitch K, Lau J, Engel T, Medicis JJ, Mohr JF, Weintraub WS. The cost impact to Medicare of shifting treatment of worsening heart failure from inpatient to outpatient management settings. ClinicoEconomics and Outcomes Research. 2018.Volume 10:855-863. doi:10.2147/ceor.s184048
  3. Roger VL. Epidemiology of Heart Failure. Circulation Research. 2013;113(6):546-659. doi:10.1161/circresaha.113.300268
  4. Fitch K, Engel T, Lau J. The Cost Burden of Worsening Heart Failure in the Medicare Fee for Service Population: An Actuarial Analysis. Milliman, Inc; 2017.
  5. Michalsen A, Kónig G, Thimme W. “Preventable causative factors leading to hospital admission with decompensated heart failure.” BJM Journals, Heart, vol. 80, no. 5, Nov. 1998, pp. 437-441.
  6. Jencks, Steven F., et al. “Rehospitalizations among patients in the Medicare fee-for-service program.” The New England Journal of Medicine, vol. 360, no. 14, Apr. 2009, pp. 418-1428. doi:10.-1056/NEJMsa0803563
  7. Reddy, Yogesh, et al. “Readmissions in Heart Failure: Is More Than Just the Medicine.” Mayo Clinic Proceedings, vol. 94, no. 10, Oct. 2019, pp. 1919-1921. DOI30747-5/fulltext)
  8. Jovicic, A., et al. “Effects of Self-Management Intervention on Health Outcomes of Patients with Heart Failure: A Systematic Review of Randomized Controlled Trials? BMC Cardiovasc Disorders, vol. 6, no. 43, 2 Nov. 2006.

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