Evidence map›Paper›PMID 37468878›Full record

ArticleBMC health services research2023

Predictive risk modelling of high resource users under different prescription drug coverage policies in Ontario and Manitoba, Canada.

Kathy Kornas, Joykrishna Sarkar, Randall Fransoo, Laura C Rosella

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 88% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 1 country.

Kathy KornasDalla Lana School of Public Health, University of Toronto, Health Sciences Building 6th floor, 155 College Street, Toronto, ON, M5T 3M7, Canada.
Joykrishna SarkarManitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada.
Randall FransooManitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada.
Laura C RosellaDalla Lana School of Public Health, University of Toronto, Health Sciences Building 6th floor, 155 College Street, Toronto, ON, M5T 3M7, Canada. laura.rosella@utoronto.ca.
Manitoba Health · CAUniversity of Manitoba · CAUniversity of Toronto · CA

Funding

Canadian Institutes of Health Research Partnerships for Health System Improvement FRN 141803
6 · The paper itself

Abstract

introductionStudying high resource users (HRUs) across jurisdictions is a challenge due to variation in data availability and health services coverage. In Canada, coverage for pharmaceuticals varies across provinces under a mix of public and private plans, which has implications for ascertaining HRUs. We examined sociodemographic and behavioural predictors of HRUs in the presence of different prescription drug coverages in the provinces of Manitoba and Ontario.

methodsLinked Canadian Community Health Surveys were used to create two cohorts of respondents from Ontario (n = 58,617, cycles 2005-2008) and Manitoba (n = 10,504, cycles 2007-2010). HRUs (top 5%) were identified by calculating health care utilization 5 years following interview date and computing all costs in the linked administrative databases, with three approaches used to include drug costs: (1) costs paid for by the provincial payer under age-based coverage; (2) costs paid for by the provincial payer under income-based coverage; (3) total costs regardless of the payer (publicly insured, privately insured, and out-of-pocket). Logistic regression estimated the association between sociodemographic, health, and behavioral predictors on HRU risk.

resultsThe strength of the association between age (≥ 80 vs. <30) and becoming an HRU were attenuated with the inclusion of broader drug data (age based: OR 37.29, CI: 30.08-46.24; income based: OR 27.34, CI: 18.53-40.33; all drug payees: OR 29.08, CI: 19.64-43.08). With broader drug coverage, the association between heavy smokers vs. non-smokers on odds of becoming an HRU strengthened (age based: OR 1.58, CI: 1.32-1.90; income based: OR 2.97, CI: 2.18-4.05; all drug payees: OR 3.12, CI: 2.29-4.25). Across the different drug coverage policies, there was persistence in higher odds of becoming an HRU in low income households vs. high income households and in those with a reported chronic condition vs. no chronic conditions.

conclusionsThe study illustrates that jurisdictional differences in how HRUs are ascertained based on drug coverage policies can influence the relative importance of some behavioural risk factors on HRU status, but most observed associations with health and sociodemographic risk factors were persistent, demonstrating that predictive risk modelling of HRUs can occur effectively across jurisdictions, even with some differences in public drug coverage policies.

Indexed as

Prescription DrugsCanadaDelivery of Health CareHumansManitobaOntarioPublic PolicyPrescription DrugsHealth care utilizationHigh resource usersPrescription drug coverage

Identifiers

PMID37468878
PMCPMC10357670
OpenAlexW4384820823

What OpenQuestion holds

Textmetadata
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.