Data association with the publication entitled: 'Demonstrating the Impact of POLST Forms on Hospital Care Requires Information not Contained in State Registries'
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Files contain project data and statistical code in R associated with the related publication. Background: Physician Orders for Life-Sustaining Treatment (POLST) programs have expanded rapidly, but evaluating their impact on hospital care is challenging. Objectives: To demonstrate how careful study design can reveal POLST’s impact at hospital admission and why analyses of state registry data are unlikely to capture POLST’s effects. Design: Prospective cohort study Setting and Participants: Adult in-patients with Do Not Intubate and/or Do Not Resuscitate (DNR/I) orders in the electronic medical record at the time of discharge from Johns Hopkins Hospital over 18 months. For patients with unplanned readmissions within 30 days, records were reviewed to determine if a Maryland Medical Order for Life-Sustaining Treatment (MOLST) form was presented and for the time from readmission to a DNR/I order in the EMR. Analyses were stratified by whether patients could communicate or were accompanied by a proxy at readmission. Results: Among 1,507 patients with DNR/I orders at discharge, 124 (8%) had unplanned readmissions, 112 (90%) could communicate or were accompanied by a proxy at readmission, and 12 (10%) could not communicate and were unaccompanied. For patients who were unaccompanied and could not communicate, MOLST significantly decreased the median time from readmission to DNR/I order (1.2 vs 27.1 hours, P=.001), but this association was greatly attenuated among patients who could communicate or were accompanied by a proxy (16.4 vs 25.4 hours P=.10). Conclusion: Among patients who wanted to avoid intubation and/or CPR, MOLST forms were protective when the patient was unaccompanied by a healthcare proxy at admission and could not communicate. Fewer than 10% of patients met these criteria during unplanned readmissions, and state registry data does not allow this sub-population to be identified.
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Publication Details
Subfield
General Health Professions
Field
Health Professions
Domain
Health Sciences
Confidence Score
99%
Source
Open Alex