Preventable Hospital Stays
Rate of hospital stays for ambulatory-care sensitive conditions per 100,000 Medicare enrollees. The 2023 County Health Rankings used data from 2020 for this measure.
Hospitalization for ambulatory-care sensitive conditions, diagnoses usually treatable in outpatient settings, suggests that quality outpatient care was not accessible. This measure may also represent a tendency to overuse emergency rooms and urgent care as a main source of care. Preventable hospital stays could be classified as both a quality and access measure, as some literature describes hospitalization rates for ambulatory care-sensitive conditions primarily as a proxy for access to primary health care.1
Data and methods
Mapping Medicare Disparities Tool
The Centers for Medicare & Medicaid Services Office of Minority Health's Mapping Medicare Disparities (MMD) Tool contains health outcome measures for all states and counties for disease prevalence, costs, hospitalization for 55 specific chronic conditions, emergency department utilization, readmissions rates, mortality, preventable hospitalizations, and preventive services.
Key Measure Methods
Preventable Hospital Stays is a rate
Preventable Hospital Stays measures the number of hospital stays for ambulatory-care sensitive conditions per 100,000 Medicare enrollees. Rates measure the number of events (e.g., deaths, births) in a given time period (generally one or more years) divided by the average number of people at risk during that period. Rates help us compare health data across counties with different population sizes.
Preventable Hospital Stays is age-adjusted
Age is a non-modifiable risk factor, and as age increases, poor health outcomes are more likely. We report an age-adjusted rate in order to fairly compare counties with differing age structures.
The method for calculating Preventable Hospital Stays has changed
In the 2019 County Health Rankings, the source for this measure switched from Dartmouth Atlas of Health Care to Mapping Medicare Disparities. The rate also switched from per 1,000 to 100,000 Medicare enrollees. The definition of hospitalizations also changed. Previously, hospitalizations for the following conditions were included: convulsions, chronic obstructive pulmonary disease, bacterial pneumonia, asthma, congestive heart failure, hypertension, angina, cellulitis, diabetes, gastroenteritis, kidney/urinary infection, and dehydration. See the numerator definition below for current hospitalizations included.
A limitation of this measure is that it uses Medicare claims data, which limits the population evaluated to mostly individuals age 65 and older. This measure, therefore, may potentially miss trends and disparities among younger age groups.
The numerator is the number of discharges for Medicare beneficiaries ages 18 years or older continuously enrolled in Medicare fee-for-service Part A and hospitalized for any of the following reasons: diabetes with short or long-term complications, uncontrolled diabetes without complications, diabetes with lower-extremity amputation, chronic obstructive pulmonary disease, asthma, hypertension, heart failure, dehydration, bacterial pneumonia, or urinary tract infection.
The denominator is the Medicare beneficiaries ages 18 years or older continuously enrolled in Medicare fee-for-service Part A. Individuals enrolled in Medicare Advantage at any point during the year are excluded. In addition, beneficiaries who died during the year, but otherwise were continuously enrolled up until the date of death, as well as beneficiaries who became eligible for enrollment following the first of the year, but were continuously enrolled from that date to the end of the year, are included in the analysis population.
Can This Measure Be Used to Track Progress
This measure can be used to track progress with some caveats. The trend graph data presented on County Health Rankings county snapshots for 2020 can be used to help understand change over time. Data in snapshots from before 2019 should not be used due to measure changes.
Finding More Data
Disaggregation means breaking data down into smaller, meaningful subgroups. Disaggregated data are often broken down by characteristics of people or where they live. Disaggregated data can reveal inequalities that are otherwise hidden. These data can be disaggregated by:
Prevention Quality Indicator data by age groups, sex, and race can be obtained from the Mapping Medicare Disparities tool.
1 Brumley R, Enguidanos S, Jamison P, et al. Increased satisfaction with care and lower costs: Results of a randomized trial of in-home palliative care. Journal of the Americans Geriatric Society. 2007; 55:993-1000.