| Title | The post-acute delayed discharge risk scale: derivation and validation with Ontario alternate level of care patients in Ontario complex continuing care hospitals |
| Publication Type | Journal Article |
| Year of Publication | 2020 |
| Authors | Turcotte LA, Daniel I, Hirdes JP |
| Journal | Journal of the American Medical Directors Association |
| Volume | 21 |
| Issue | 4 |
| Pagination | 538-544. e1 |
| Date Published | Apr |
| ISBN Number | 1525-8610 |
| Accession Number | 32089427 |
| Keywords | *Hospitalization, *Patient Discharge, alternate level of care (ALC), delayed discharge, Hospitals, Humans, Ontario, Patient flow, post-acute care, Retrospective Studies |
| Abstract | Objectives: To describe and validate the Post-acute Delayed Discharge Risk Scale (PADDRS), which classifies patients by risk of delayed discharge on admission to post-acute care settings using information collected with the interRAI Minimum Data Set (MDS) 2.0 assessment.Design: Retrospective cohort study of individuals admitted to Ontario Complex Continuing Care (CCC) hospitals. Person-level linkage between interRAI MDS 2.0 assessments and Cancer Care Ontario Wait Time Information System records was performed.Setting and participants: Sample of 30,657 patients who received care in an Ontario CCC hospital and were assessed with the interRAI MDS 2.0 assessment between January 1, 2010, and March 31, 2013.Measures: Alternate Level of Care (ALC) designation of 30 or more days was used as the marker of delayed discharge. Scale validation was performed through computation of class-level effect sizes and receiver operating characteristic curves for each of Ontario's geographic health regions. Additionally, Clinical Assessment Protocol (CAP) decision-support tool trigger rates by PADDRS risk level were computed for problem areas that are clinically relevant with the delayed discharge outcome.Results: Overall, 9.4% of the sample experienced the delayed discharge outcome. The PADDRS algorithm achieved an overall area under the curve (AUC) statistic of 0.74, which indicates good discriminatory ability for predicting delayed discharge. PADDRS is generalizable across geographic regions, with AUC statistics ranging between 0.61 and 0.81 across each of Ontario's 14 Local Health Integration Networks. PADDRS demonstrated strong concurrent validity, as the percentage of patients triggering CAPs increased with the risk of delayed discharge.Conclusions and implications: PADDRS combines numerous important clinical factors associated with delayed discharge from a post-acute hospital into a cohesive decision-support tool for use by discharge planners. In addition to early identification of patients who are most likely to experience delayed discharge, PADDRS has applications in risk-adjusted quality measurement of discharge planning efficiency. |
| DOI | 10.1016/j.jamda.2019.12.022 |
| Link | https://www.jamda.com/article/S1525-8610(19)30892-8/abstract |
