Temporal Trends Between 2010 and 2015 in Intensity of Care at End-of-Life for Patients With Chronic Illness: Influence of Age Under vs. Over 65 Years.

CONTEXT: Recent analyses of Medicare data show decreases over time in intensity of end-of-life care. Few studies exist regarding trends in intensity of end-of-life care for those under 65 years of age. OBJECTIVES: To examine recent temporal trends in place of death, and both hospital and intensive care unit (ICU) utilization, for age-stratified decedents with chronic, life-limiting diagnoses (<65 vs. ≥65 years) who received care in a large healthcare system. METHODS: Retrospective cohort using death certificates and electronic health records for 22,068 patients with chronic illnesses who died between 2010 and 2015. We examined utilization overall and stratified by age using multiple regression. RESULTS: The proportion of deaths at home did not change, but hospital admissions in the last 30 days of life decreased significantly from 2010 to 2015 (hospital b = -0.026; CI = -0.041, -0.012). ICU admissions in the last 30 days also declined over time for the full sample and for patients aged 65 years or older (overall b = -0.023; CI = -0.039, -0.007), but was not significant for younger decedents. Length of stay (LOS) did not decrease for those using the hospital or ICU. CONCLUSION: From 2010 to 2015, we observed a decrease in hospital admissions for all age groups and in ICU admissions for those over 65 years. As there were no changes in the proportion of patients with chronic illness who died at home nor in hospital or ICU LOS in the last 30 days, hospital and ICU admissions in the last 30 days may be a more responsive quality metric than site of death or LOS for palliative care interventions.

Error disclosure: a new domain for safety culture assessment.

OBJECTIVE: To (1) develop and test survey items that measure error disclosure culture, (2) examine relationships among error disclosure culture, teamwork culture and safety culture and (3) establish predictive validity for survey items measuring error disclosure culture. METHOD: All clinical faculty from six health institutions (four medical schools, one cancer centre and one health science centre) in The University of Texas System were invited to anonymously complete an electronic survey containing questions about safety culture and error disclosure. RESULTS: The authors found two factors to measure error disclosure culture: one factor is focused on the general culture of error disclosure and the second factor is focused on trust. Both error disclosure culture factors were unique from safety culture and teamwork culture (correlations were less than r=0.85). Also, error disclosure general culture and error disclosure trust culture predicted intent to disclose a hypothetical error to a patient (r=0.25, p<0.001 and r=0.16, p<0.001, respectively) while teamwork and safety culture did not predict such an intent (r=0.09, p=NS and r=0.12, p=NS). Those who received prior error disclosure training reported significantly higher levels of error disclosure general culture (t=3.7, p<0.05) and error disclosure trust culture (t=2.9, p<0.05). CONCLUSIONS: The authors created and validated a new measure of error disclosure culture that predicts intent to disclose an error better than other measures of healthcare culture. This measure fills an existing gap in organisational assessments by assessing transparent communication after medical error, an important aspect of culture.