Cost savings from palliative care teams and guidance for a financially viable palliative care program.
Ontology highlight
ABSTRACT: Objectives
To quantify the cost savings of palliative care (PC) and identify differences in savings according to team structure, patient diagnosis, and timing of consult.Data sources
Hospital administrative records on all inpatient stays at five hospital campuses from January 2009 through June 2012.Study design
The analysis matched PC patients to non-PC patients (separately by discharge status) using propensity score methods. Weighted generalized linear model regressions of hospital costs were estimated for the matched groups.Data collection
Data were restricted to patients at least 18 years old with inpatient stays of between 7 and 30 days. Variables available included patient demographics, primary and secondary diagnoses, hospital costs incurred for the inpatient stay, and when/if the patient had a PC consult.Principal findings
We found overall cost savings from PC of $3,426 per patient for those dying in the hospital. No significant cost savings were found for patients discharged alive; however, significant cost savings for patients discharged alive could be achieved for certain diagnoses, PC team structures, or if consults occurred within 10 days of admission.Conclusions
Appropriately selected and timed PC consults with physician and RN involvement can help ensure a financially viable PC program via cost savings to the hospital.
SUBMITTER: McCarthy IM
PROVIDER: S-EPMC4319879 | biostudies-literature | 2015 Feb
REPOSITORIES: biostudies-literature
Publications
Cost savings from palliative care teams and guidance for a financially viable palliative care program.
McCarthy Ian M IM Robinson Chessie C Huq Sakib S Philastre Martha M Fine Robert L RL
Health services research 20140715 1
<h4>Objectives</h4>To quantify the cost savings of palliative care (PC) and identify differences in savings according to team structure, patient diagnosis, and timing of consult.<h4>Data sources</h4>Hospital administrative records on all inpatient stays at five hospital campuses from January 2009 through June 2012.<h4>Study design</h4>The analysis matched PC patients to non-PC patients (separately by discharge status) using propensity score methods. Weighted generalized linear model regressions ...[more]
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