Predict Hospital-Acquired Conditions and Infections

It’s natural to expect that when a patient is admitted to the hospital, they will get better, not sicker. But patients can develop hospital-acquired conditions (HACs)—undesirable complications or medical conditions that were not present on admission and developed during their hospital stay. Unfortunately, HACs are common and costly. Approximately 2.5 million HACs occur annually in the U.S. among all inpatients over the age of 18 (1). Each year, Medicare levies substantial penalties on hospitals under the Hospital-Acquired Conditions Reduction Program—estimated at approximately $360 million (2).

Hospital-acquired infections (HAIs) represent a significant portion of all HACs and are among the leading causes of death in the United States (3). At any given time, one in every 31 hospitalized patients has a HAI, there are approximately 680,000 HAIs in U.S. acute care hospitals annually, and nearly 70,000 of these patients will die during their hospitalization (4,5). HAIs are also extremely costly and are responsible for between $28 and $33 billion in potentially preventable healthcare expenditures annually (3).

Size of the Problem

• 11% of patients with HAIs die during their hospitalization (5).
• 2.5 million HACs occur annually in the U.S. in inpatients over the age of 18 (1).
• 774 hospitals will face Medicare payment cuts in fiscal year 2021 under the HACRP (9).
• $30 billion is the potentially preventable annual expenditure attributed to HAIs (3).

‍

Patients with HAIs are also at increased risk for sepsis—the leading cause of both inpatient death and readmissions (6). Each year, at least 1.7 million adults in America develop sepsis, and nearly 270,000 die as a result (7). The AHRQ lists sepsis as the most expensive condition treated in the U.S., and the HHS recently estimated that healthcare costs associated with sepsis total more than $60 billion annually (8).

Ensuring patient health and safety is the number one priority for hospitals. In addition to maximizing prevention efforts to reduce the incidence of HACs, hospitals can leverage predictive analytics to identify patients likely to be at high risk for HACs. Identification of these patients can enable key interventions that may include patient education, antimicrobial stewardship, and consistent monitoring. This insight can lower costs and save lives.

• 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.
• 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.
• Social Needs Assessments: Self-reported data that identify an individual's specific needs and the acute social and economic challenges they are experiencing.

‍