Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Nov 15;18(1):861.
doi: 10.1186/s12913-018-3639-z.

Can high-cost spending in the community signal admission to hospital? A dynamic modeling study for urgent and elective cardiovascular patients

Deborah Cohen  1   2   3   4 , Walter P Wodchis  5   6   7 , Andrew Calzavara  6
Affiliations

Can high-cost spending in the community signal admission to hospital? A dynamic modeling study for urgent and elective cardiovascular patients

Deborah Cohen et al. BMC Health Serv Res. .

Abstract

Background: Much of the research on high-cost patients in healthcare has taken a static approach to studying what is actually a dynamic process. High-cost patients often utilize services across multiple sectors along care pathways, but due to the cross-sectional nature of many study designs, we lack a clear understanding of the temporal relationship between high-cost spending in community and acute care. Studying care trajectories for high cost patients with cardiovascular disease (CVD) can shed light on the dynamic interplay between community-based and acute care along the care continuum, and provide information about signals in community care that may indicate future elective and urgent hospitalizations.

Methods: Using linked health administrative data in Ontario, Canada, 74,683 incident cases with cardiovascular disease were identified between the years 2009 and 2011. Patients were followed for 36 months (total study duration 2009-2014) until the first urgent or elective admission to hospital for a heart-related condition. We used an extended Cox survival model with competing risks to study the relationship between high-cost spending in community care with two mutually exclusive outcomes: urgent or elective hospitalizations.

Results: Elective hospitalizations were most clearly signaled by a high-cost utilization of community-based specialist services in the month prior to hospital admission (hazard ratio 9.074, p < 0.0001), while urgent hospitalizations were signaled by high cost usage across all community-based sectors of care (from general practitioner & specialist visits, home care, laboratory services and emergency department (ED) usage). Urgent hospitalizations were most clearly signaled by high cost usage in ED in the month prior to hospital admission (hazard ratio 2.563, p < 0.0001).

Conclusion: By studying the dynamic nature of patient care trajectories, we may use community-based spending patterns as signals in the system that can point to future and elective hospitalizations for CVD. These community-based spending signals may be useful for identifying opportunities for intervention along the care trajectory, particularly for urgent CVD patients for whom future hospitalizations are difficult to anticipate.

Keywords: Acute care; Cardiovascular disease; Community care; Healthcare spending; High-cost; Survival analysis.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

ICES is a prescribed entity under section 45 of Ontario’s Personal Health Information Protection Act. Section 45 authorizes ICES to collect personal health information, without consent, for the purpose of analysis or compiling statistical information with respect to the management of, evaluation or monitoring of, the allocation of resources to or planning for all or part of the health system. Projects conducted under section 45, by definition, do not require review by a Research Ethics Board. This project was conducted under section 45, and approved by ICES’ Privacy and Compliance Office.

Consent for publication

Data used in the study were based on anonymized linked health administrative databases. Therefore consent to publish was not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
High cost utilization in the 6 months preceding the hospital admission
See this image and copyright information in PMC

References

    1. Allison . Survival Analysis Using SAS: a practical guide. Cary: SAS Institute; 2010.
    1. Althaus F, Stucki S, Guyot S, et al. Characteristics of highly frequent users of Swiss academic emergency department: a retrospective consecutive case series. Eur J Emerg Med. 2013;20:413–419. doi: 10.1097/MEJ.0b013e32835e078e. - DOI - PubMed
    1. Antmann EM, Anbe DT, Armstrong PW, et al. ACC/AHA guidelines for the management of patients with ST-elevation myocardial infarction – executive summary: a report of the American College of Cardiology/American Heart Association taskforce on practice guidelines (writing committee to revise the 1999 guidelines for the Management of Patients with acute myocardial infarction) Circulation. 2004;110:588–636. doi: 10.1161/01.CIR.0000134791.68010.FA. - DOI - PubMed
    1. Arnett D, Goodman R, Halperin J, Anderson J, Parekh A, Zoghbi W. AHA/ACC/HHS strategies to enhance application of clinical practice guidelines in patients with cardiovascular disease and comorbid conditions. Circulation. 2014;130:1–6. doi: 10.1161/CIR.0000000000000128. - DOI - PMC - PubMed
    1. Austin P, Daly P, Tu J. A multi centred-study of the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care units in Ontario. Am Heart J. 2002;144(2):290–296. doi: 10.1067/mhj.2002.123839. - DOI - PubMed

MeSH terms

LinkOut - more resources