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Jones A, Lapointe-Shaw L, Brown K, Babe G, Hillmer M, Costa A, Stall N, Quinn K. Short-term mortality and palliative care use after delayed hospital discharge: a population-based retrospective cohort study. BMJ Support Palliat Care 2024:spcare-2023-004647. [PMID: 38195118 DOI: 10.1136/spcare-2023-004647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/26/2023] [Indexed: 01/11/2024]
Abstract
OBJECTIVES In Canada, patients whose acute medical issues have been resolved but are awaiting discharge from hospital are designated as alternate level of care (ALC). We investigated short-term mortality and palliative care use following ALC designation in Ontario, Canada. METHODS We conducted a population-based retrospective cohort study of adult, acute care hospital admissions in Ontario with an ALC designation between January and December 2021. Our follow-up window was until 90 days post-ALC designation or death. Setting of discharge and death was determined using admission and discharge dates from multiple databases. We measured palliative care using physician billings, inpatient palliative care records and palliative home care records. We compared the characteristics of ALC patients by 90-day survival status and compared palliative care use across settings of discharge and death. RESULTS We included 54 839 ALC patients with a median age of 80 years. Nearly one-fifth (18.4%) of patients died within 90 days. Patients who died were older, had more comorbid conditions and were more likely to be male. Among those who died, 35.1% were never discharged from hospital and 20.3% were discharged but ultimately died in the hospital. The majority of people who died received palliative care following their ALC designation (68.1%). CONCLUSIONS A significant proportion of patients experiencing delayed discharge die within 3 months, with the majority dying in hospitals despite being identified as ready to be discharged. Future research should examine the adequacy of palliative care provision for this population.
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Affiliation(s)
- Aaron Jones
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- ICES, Toronto, Ontario, Canada
| | - Lauren Lapointe-Shaw
- ICES, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Division of General Internal Medicine and Geriatrics, Sinai Health System and the University Health Network, Toronto, Ontario, Canada
| | - Kevin Brown
- ICES, Toronto, Ontario, Canada
- Public Health Ontario, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | | | - Michael Hillmer
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Digital and Analytics Strategy, Ministry of Health, Toronto, Ontario, Canada
| | - Andrew Costa
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- ICES, Toronto, Ontario, Canada
| | - Nathan Stall
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Division of General Internal Medicine and Geriatrics, Sinai Health System and the University Health Network, Toronto, Ontario, Canada
- Women's Age Lab and Women's College Research Institute, Women's College Hospital, Toronto, Ontario, Canada
| | - Kieran Quinn
- ICES, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Sinai Health System, Toronto, Ontario, Canada
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Bann M, Meo N, Lopez JP, Ou A, Rosenthal M, Khawaja H, Goodman LA, Barone M, Coleman B, High HJ, Overbeek L, Shelbourn P, VerMaas L, Baughman A, Sekaran A, Cyrus R, O'Dorisio N, Beatty L, Loica-Mersa S, Kubey A, Jaffe R, Vokoun C, Koom-Dadzie K, Graves K, Tuck M, Helgerson P. Medically ready for discharge: A multisite "point-in-time" assessment of hospitalized patients. J Hosp Med 2023; 18:795-802. [PMID: 37553979 DOI: 10.1002/jhm.13184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/20/2023] [Accepted: 07/23/2023] [Indexed: 08/10/2023]
Abstract
BACKGROUND Time spent awaiting discharge after the acute need for hospitalization has resolved is an important potential contributor to hospital length of stay (LOS). OBJECTIVE To measure the prevalence, impact, and context of patients who remain hospitalized for prolonged periods after completion of acute care needs. DESIGN, SETTING, AND PARTICIPANTS We conducted a cross-sectional "point-in-time" survey at each of 15 academic US hospitals using a structured data collection tool with on-service acute care medicine attending physicians in fall 2022. MAIN OUTCOMES AND MEASURES Primary outcomes were number and percentage of patients considered "medically ready for discharge" with emphasis on those who had experienced a "major barrier to discharge" (medically ready for discharge for ≥1 week). Estimated LOS attributable to major discharge barriers, contributory discharge needs, and associated hospital characteristics were measured. RESULTS Of 1928 patients sampled, 35.0% (n = 674) were medically ready for discharge including 9.8% (n = 189) with major discharge barriers. Many patients with major discharge barriers (44.4%; 84/189) had spent a month or longer medically ready for discharge and commonly (84.1%; 159/189) required some form of skilled therapy or daily living support services for discharge. Higher proportions of patients experiencing major discharge barriers were found in public versus private, nonprofit hospitals (12.0% vs. 7.2%; p = .001) and county versus noncounty hospitals (14.5% vs. 8.8%; p = .002). CONCLUSIONS Patients experience major discharge barriers in many US hospitals and spend prolonged time awaiting discharge, often for support needs that may be outside of clinician control.
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Affiliation(s)
- Maralyssa Bann
- University of Washington School of Medicine, Seattle, Washington, USA
- Harborview Medical Center, Seattle, Washington, USA
| | - Nicholas Meo
- University of Washington School of Medicine, Seattle, Washington, USA
- Harborview Medical Center, Seattle, Washington, USA
| | - J P Lopez
- University of Washington, Seattle, Washington, USA
| | - Amy Ou
- University of California San Francisco, San Francisco, California, USA
| | - Molly Rosenthal
- University of Washington School of Medicine, Seattle, Washington, USA
- Harborview Medical Center, Seattle, Washington, USA
- University of Washington Medical Center, Seattle, Washington, USA
| | - Hussain Khawaja
- Brown University Warren Alpert Medical School, Providence, Rhode Island, USA
- Rhode Island Hospital, Providence, Rhode Island, USA
| | - Leigh A Goodman
- University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, USA
- Banner-University Medical Center-Phoenix, Phoenix, Arizona, USA
| | - Melanie Barone
- Cedars-Sinai Medical Center, Los Angeles, California, USA
| | | | - Heidi J High
- Cedars-Sinai Medical Center, Los Angeles, California, USA
| | | | | | | | - Amy Baughman
- Massachussetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Adith Sekaran
- Massachussetts General Hospital, Boston, Massachusetts, USA
| | - Rachel Cyrus
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Nathan O'Dorisio
- Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Lane Beatty
- Springfield Hospital, Springfield, Vermont, USA
| | | | - Alan Kubey
- Mayo Clinic, Rochester, Minnesota, USA
- Thomas Jefferson University Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Rebecca Jaffe
- Thomas Jefferson University Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Chad Vokoun
- University of Nebraska Medical Center, Omaha, Nebraska, USA
| | | | - Kencee Graves
- University of Utah Health, Salt Lake City, Utah, USA
| | - Matthew Tuck
- Washington DC VA Medical Center, Washington, District of Columbia, USA
| | - Paul Helgerson
- University of Virginia Health System, Charlottesville, Virginia, USA
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Arntzen RJ, van den Besselaar JH, Bekker R, Buurman BM, van der Mei RD. Avoiding Hospital Admissions and Delayed Transfers of Care by Improved Access to Intermediate Care: A Simulation Study. J Am Med Dir Assoc 2023; 24:945-950.e4. [PMID: 37290484 DOI: 10.1016/j.jamda.2023.04.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/19/2023] [Accepted: 04/21/2023] [Indexed: 06/10/2023]
Abstract
OBJECTIVE The current waiting times for intermediate care in the Netherlands prohibit timely access, leading to unwanted and costly hospital admissions. We propose alternative policies for improvement of intermediate care and estimate the effects on the waiting times, hospitalization, and the number of patient replacements. DESIGN Simulation study. SETTING AND PARTICIPANTS For our case study, data were used of older adults who received intermediate care in Amsterdam, the Netherlands, in 2019. For this target group, in- and outflows and patient characteristics were identified. METHODS A process map of the main pathways into and out of the intermediate care was obtained and a discrete event simulation (DES) was built. We demonstrate the use of our DES for intermediate care by evaluating possible policy changes for a real-life case study in Amsterdam. RESULTS By means of a sensitivity analysis with the DES, we show that in Amsterdam the waiting times are not a result of a lack in bed capacity but are due to an inefficient triage and application process. Older adults have to wait a median of 1.8 days for admission, leading to hospitalization. If the application process becomes more efficient and evening and weekend admissions are allowed, we find that unwanted hospitalization can be decreased substantially. CONCLUSION AND IMPLICATIONS In this study, a simulation model is developed for intermediate care that can serve as a basis for policy decisions. Our case study shows that the waiting times for health care facilities are not always solved by increasing bed capacity. This underlines the necessity for a data-driven approach to identify logistic bottlenecks and find the best ways to solve them.
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Affiliation(s)
- Rebekka J Arntzen
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Stochastics group, Centrum Wiskunde & Informatica, Amsterdam, the Netherlands.
| | - Judith H van den Besselaar
- Section of Geriatric Medicine, Department of Internal Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - René Bekker
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Bianca M Buurman
- Section of Geriatric Medicine, Department of Internal Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Rob D van der Mei
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Stochastics group, Centrum Wiskunde & Informatica, Amsterdam, the Netherlands
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