What Factors Increase Odds of Long-Stay Delayed Discharge in Alternate Level of Care Patients?

OBJECTIVE: The objective of this study was to determine the factors that increase the odds of long-stay delayed discharge in alternate level of care (ALC) patients using data collected from the Ontario Wait Time Information System (WTIS) database. DESIGN: Retrospective cohort study utilizing data from Niagara Health's WTIS database. WTIS includes individuals admitted to any of the Niagara Health sites that have been designated as ALC. SETTING AND PARTICIPANTS: Sample consisted of 16,429 ALC patients who received care in Niagara Health hospitals from September 2014 to September 2019 and were recorded in the WTIS database. METHODS: ALC designation of 30 or more days was used as the threshold for a long-stay delayed discharge. This study used binary logistic regression modeling to analyze sex, age, admission source, and discharge destination as well needs/barriers requirements to assess the likelihood of a long-stay delayed discharge among acute care (AC) and post-acute care (PAC) patients given the presence of each variable. Sample sizes calculations and receiver operating characteristic curves were used to verify the validity of the regression model. RESULTS: Overall, 10.2% of the sample were considered long-stay ALC patients. Both AC and PAC long-stay ALC patients were more likely to be male [OR = 1.23, (1.06-1.43); OR = 1.28, (1.03-1.60)] and have a discharge destination of a long-term care bed [OR = 28.68, (22.83-36.04); OR = 6.22, (4.75-8.15)]. AC patients had bariatric [OR = 7.16, (3.45-14.83)], behavioral [OR = 1.89, (1.22-2.91)], infection (isolation) [OR = 2.31, (1.63-3.28)], and feeding [OR = 6.38, (1.82-22.30)] barriers hindering discharge. PAC patients had no significant barriers hindering patient discharge. CONCLUSIONS AND IMPLICATIONS: Shifting the focus from ALC patient designation to short- vs long-stay ALC patients allowed this study to focus on the subset of patients that are disproportionately affecting delayed discharges. Understanding the importance of specialized patient requirements in addition to clinical factors can help hospitals become more prepared in preventing delayed discharges.

Dementia and Poor Continuity of Primary Care Delay Hospital Discharge in Older Adults: A Population-Based Study From 2001 to 2016.

OBJECTIVES: Delayed discharge, remaining in acute care longer than medically necessary, reflects less than optimal use of hospital care resources and can have negative implications for patients. We studied (1) the change over time in delayed discharge in people with and without dementia, and (2) the association of delayed discharge with discharge destination and with the continuity of primary care prior to urgent admission. DESIGN: A retrospective population-based study. SETTING AND PARTICIPANTS: Delayed discharge after urgent admission and length of delayed discharge were studied in all hospital users aged ≥70 years with at least 1 urgent admission in British Columbia, Canada, in years 2001/02, 2005/06, 2010/11, and 2015/16 (N = 276,299). METHODS: Linked administrative data provided by Population Data BC were analyzed using generalized estimating equations (GEE), logistic regression analysis, and negative binomial regression analyses. RESULTS: Delayed discharge increased among people with dementia and decreased among people without dementia, whereas the length of delay decreased among both. Dementia was the strongest predictor of delayed discharge [odds ratio 4.76; 95% confidence interval (CI) 4.59-4.93], whereas waiting for long-term care placement [incidence rate ratio (IRR) 1.56; 95% CI 1.50-1.62] and dementia (IRR 1.50; 95% CI 1.45-1.54) predicted a higher number of days of delay. Continuity and quantity of care with the same physician before urgent admission was associated with a decreased risk of delayed discharge, especially in people with dementia. CONCLUSIONS AND IMPLICATIONS: This study demonstrates the need for better system integration and patient-centered care especially for people with dementia. Population aging will likely increase the number of patients at risk of delayed discharge. Delayed discharge is associated with both the patient's complex needs and the inability of the system to meet these needs during and after urgent care. Sufficient investments are needed in both primary care and long-term care resources to reduce delayed discharges.

The Post-Acute Delayed Discharge Risk Scale: Derivation and Validation With Ontario Alternate Level of Care Patients in Ontario Complex Continuing Care Hospitals.

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.