Examining Social Risk Factors in a Pressure Ulcer Quality Measure for Three Post-Acute Care Settings

Abstract

OBJECTIVE To describe and explore relationships between social demographic factors and incidence or worsening of pressure ulcer scores among post-acute care (PAC) settings. DESIGN The authors present the incidence of new or worsening pressure ulcers stratified by self-reported patient race and sex. Investigators used logistic regression modeling to examine relative risk of developing new or worsened pressure ulcers by sociodemographic status and multiple regression modeling to estimate the relative contribution of facility-level factors on rates of new or worsening pressure ulcers. SETTING Three PAC settings: long-term care hospitals, inpatient rehabilitation facilities, and skilled nursing facilities. PARTICIPANTS Medicare Part A residents and patients with complete stays in PAC facilities during 2015. MAIN OUTCOME MEASURE The incidence of new or worsened pressure ulcers as calculated using the specifications of the National Quality Forum-endorsed pressure ulcer quality measure #0678. MAIN RESULTS The sample included 1,566,847 resident stays in 14,822 skilled nursing facilities, 478,292 patient stays in 1,132 inpatient rehabilitation facilities, and 121,834 patient stays in 397 long-term care hospitals. Significant differences in new or worsened pressure ulcer incidence rates by sociodemographic factors were found in all three settings. Black race, male sex, and advanced age were significant predictors of new or worsened ulcers, although controlling for health conditions reduced the racial disparity. The authors noted significant differences among facilities based on ownership type, urban/rural location, and sociodemographic makeup of facilities’ residents/patients. CONCLUSIONS There is evidence of disparities in the incidence of new or worsened pressure ulcers across PAC settings, suggesting publicly available quality data may be used to identify and ameliorate these problems.

Surveillance for Pressure Injuries on Admission to Inpatient Rehabilitation Hospitals During the COVID-19 Pandemic

“…Regression analyses also confirmed that male gender was significantly associated with higher odds of PI. 26 Obesity seemed to offer some protection for PIs, which is consistent with previous reports.…”

“… 24 , 25 This study found that male gender was a risk factor for development of a PI during the acute hospital stay. 26 This variable has limited evidence in the literature to support their classification as risk factors for PIs. 29 , 30 , 31 , 32 , 33 , 34 However, these factors have been shown to play a role in the severity of COVID-19 morbidity, which may play a role in the development of PIs, and in the case of malnutrition (low blood albumin levels), and PI severity.…”

Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature

“…We identified 13 studies for the topic of pressure injuries (PIs). Of these 13 studies, 7 studies used a retrospective cohort design, 230 231 232 233 234 235 236 3 used a prospective cohort design, 237 238 239 1 used a clinical trial, 240 1 used a cross-sectional design, 241 and 1 used secondary data analysis. 242 A variety of data sources were used for the studies, including EHR data, 233 234 238 239 data warehouses, 230 231 235 236 a publicly available dataset, 232 sensor data, 240 242 and surveys as the primary collection tool.…”

“…Of these 13 studies, 7 studies used a retrospective cohort design, 230 231 232 233 234 235 236 3 used a prospective cohort design, 237 238 239 1 used a clinical trial, 240 1 used a cross-sectional design, 241 and 1 used secondary data analysis. 242 A variety of data sources were used for the studies, including EHR data, 233 234 238 239 data warehouses, 230 231 235 236 a publicly available dataset, 232 sensor data, 240 242 and surveys as the primary collection tool. 237 The samples across studies were adult patients admitted in hospitals, 230 231 232 234 236 238 239 adults in residential hospices, 237 elderly patients in nursing homes (NHs), 241 Medicare beneficiaries, 235 and adults (unspecified).…”

“…242 A variety of data sources were used for the studies, including EHR data, 233 234 238 239 data warehouses, 230 231 235 236 a publicly available dataset, 232 sensor data, 240 242 and surveys as the primary collection tool. 237 The samples across studies were adult patients admitted in hospitals, 230 231 232 234 236 238 239 adults in residential hospices, 237 elderly patients in nursing homes (NHs), 241 Medicare beneficiaries, 235 and adults (unspecified). 240 242 Six studies were based in the United States, 230 231 232 234 235 236 with other study locations including Brazil, 239 Canada, 240 France, 242 Indonesia, 241 Italy, 237 South Korea, 238 and Taiwan.…”