Evidence map›Paper›PMID 27724877›Full record

ArticleBMC health services research2016

Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care.

John Paul Kuwornu, Lisa M Lix, Jacqueline M Quail, Xiaoyun Eric Wang, Meric Osman, Gary F Teare

Abstract read
In one paragraph

Article in BMC health services research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Economic Burden and Healthcare Trajectories of Patients Awaiting Heart Transplantation in a French Tertiary Center.Transplant international : official journal of the European Society for Organ Transplantation · 2025
    Article
  3. Article
  4. Article
  5. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

John Paul KuwornuDepartment of Community Health Sciences, College of Medicine, Faculty of Health Sciences, University of Manitoba, 750 Bannatyne Avenue, Winnipeg, MB, R3E 0 W3, Canada. kuwornuj@myumanitoba.ca.
Lisa M LixDepartment of Community Health Sciences, College of Medicine, Faculty of Health Sciences, University of Manitoba, 750 Bannatyne Avenue, Winnipeg, MB, R3E 0 W3, Canada.
Jacqueline M QuailDepartment of Community Health Sciences, College of Medicine, Faculty of Health Sciences, University of Manitoba, 750 Bannatyne Avenue, Winnipeg, MB, R3E 0 W3, Canada.
Xiaoyun Eric WangSaskatchewan Health Quality Council, 111 Research Drive, Saskatoon, SK, S7N 3R2, Canada.
Meric OsmanSaskatchewan Health Quality Council, 111 Research Drive, Saskatoon, SK, S7N 3R2, Canada.
Gary F TeareDepartment of Community Health Sciences, College of Medicine, Faculty of Health Sciences, University of Manitoba, 750 Bannatyne Avenue, Winnipeg, MB, R3E 0 W3, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA patient's trajectory through the healthcare system affects resource use and outcomes. Data fields in population-based administrative health databases are potentially valuable resources for constructing care trajectories for entire populations, provided they can capture patient transitions between healthcare services. This study describes patient transitions from the emergency department (ED) to other healthcare settings, and ascertains whether the discharge disposition field recorded in the ED data was a reliable source of patient transition information from the emergency to the acute care settings.

methodsAdministrative health databases from the province of Saskatchewan, Canada (population 1.1 million) were used to identify patients with at least one ED visit to provincial teaching hospitals (n = 5) between April 1, 2006 and March 31, 2012. Discharge disposition from ED was described using frequencies and percentages; and it includes categories such as home, transfer to other facilities, and died. The kappa statistic with 95 % confidence intervals (95 % CIs) was used to measure agreement between the discharge disposition field in the ED data and hospital admission records.

resultsWe identified N = 1,062,861 visits for 371,480 patients to EDs over the six-year study period. Three-quarters of the discharges were to home, 16.1 % were to acute care in the same facility in which the ED was located, and 1.6 % resulted in a patient transfer to a different acute care facility. Agreement between the discharge disposition field in the ED data and hospital admission records was good when the emergency and acute care departments were in the same facility (κ = 0.77, 95 % CI 0.77, 0.77). For transfers to a different acute care facility, agreement was only fair (κ = 0.36, 95 % CI 0.35, 0.36).

conclusionsThe majority of patients who attended EDs did not transition to another healthcare setting. For those who transitioned to acute care, accuracy of the discharge disposition field depended on whether the two services were provided in the same facility. Using the hospital data as reference, we conclude that the discharge disposition field in the ED data is not reliable for measuring transitions from ED to acute care.

Indexed as

Emergency Service, HospitalHospital RecordsAdolescentAdultAgedAged, 80 and overChildDatabases, FactualEmergency Medical ServicesFemaleHospitalizationHumansInfantMaleMiddle AgedPatient TransferAgreementData linkageEmergency departmentHealthcare trajectoryHospital records

Identifiers

PMID27724877
PMCPMC5057464

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.