Trends in Critical Care Beds and Use Among Population Groups and Medicare and Medicaid Beneficiaries in the United States: 2000–2010

Abstract

Objectives To analyze patterns of critical care medicine (CCM) beds, use, and costs in acute care hospitals in the United States (US), and relate CCM beds and use to population shifts, age groups, and Medicare and Medicaid beneficiaries from 2000 to 2010. Design Retrospective study of data from the federal Healthcare Cost Report Information System, American Hospital Association and US Census Bureau. Setting Acute care US hospitals with intensive care beds. Measurements and Main Results From 2000 to 2010, US hospitals with CCM beds decreased by 17% (3,586 to 2,977), while the US population increased by 9.6% (282.2M to 309.3M). Although hospital beds decreased by 2.2% (655,785 to 641,395), CCM beds increased by 17.8% (88,235 to 103,900), a 20.4% increase in the CCM/hospital bed ratio (13.5% to 16.2%). There was a greater percentage increase in premature/neonatal (29%, 14,391 to 18,567) than in adult (15.9%, 71,978 to 83,417) or pediatric (2.7%, 1,866 to 1,916) CCM beds. Hospital occupancy rates increased by 10% (59% to 65%), while CCM occupancy rates were stable (range 65%–68%). CCM beds per 100,000 total population increased by 7.4% (31.3 to 33.6). The proportional use of CCM services by Medicare beneficiaries decreased by 17% (37.9% to 31.4%) whereas that by Medicaid rose by 18% (14.5% to 17.2%). Between 2000 and 2010, annual CCM costs nearly doubled (92.9%, $56 to $108 billion). In the same period, the proportion of CCM cost to the Gross Domestic Product (GDP) increased by 32.1% (0.54% to 0.72%, $10,285 to $14,964 trillion). Conclusions Critical care medicine use and costs in the US continue to rise. The increasing use of CCM by the premature/neonatal and Medicaid populations should be considered by healthcare policy makers, state agencies, and hospitals as they wrestle with critical care bed growth and the associated costs.

Identifying Distinct Subgroups of ICU Patients: A Machine Learning Approach*

“…Improving the value and efficiency of our critical care delivery system is important in efforts to provide high quality care and contain growing healthcare expenditures (5, 31). However, the heterogeneity and unpredictability of critical illness have hampered easily generalizable solutions (32–34).…”

What matters most to sepsis survivors: a qualitative analysis to identify specific health-related quality of life domains

“…Half of patients recover, but among those who survive sepsis, one-sixth have permanent organ damage [2], cognitive impairment, and physical disability [3]. The number of sepsis patients who survive intensive care is growing due to a rise in the incidence of sepsis [1,4], a general increase in the number and use of intensive care unit (ICU) beds [5], as well as progress in the treatment of sepsis [6]. There is growing recognition among critical care clinicians and researchers that the health-related quality of life (HRQL) of sepsis survivors is an important endpoint for evaluating critical care [7].…”

Preventing Transmission of Multidrug-Resistant Pathogens in the Intensive Care Unit

“…1 Although nosocomial infections complicate 4% of overall hospital admissions, 2 9% to 20% of critically ill patients develop infections while in the ICU. 2–4 Nearly half of all health care–associated infections that occur in hospitals are attributable to the ICU.…”