Evidence map›Paper›PMID 22824551›Full record

ArticleBMC health services research2012

Assessing methods for measurement of clinical outcomes and quality of care in primary care practices.

Michael E Green, William Hogg, Colleen Savage, Sharon Johnston, Grant Russell, R Liisa Jaakkimainen, Richard H Glazier, Janet Barnsley, Richard Birtwhistle

Abstract readComparative Study
In one paragraph

Article in BMC health services research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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  16. Examining Primary Healthcare Performance through a Triple Aim Lens.Healthcare policy = Politiques de sante · 2016
    Article
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  18. Review
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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

9 authors.

Michael E GreenDepartment of Family Medicine, Queen's University, Kingston, Ontario, Canada. michael.green@dfm.queensu.ca
William Hogg
Colleen Savage
Sharon Johnston
Grant Russell
R Liisa Jaakkimainen
Richard H Glazier
Janet Barnsley
Richard Birtwhistle

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the appropriateness of potential data sources for the population of performance indicators for primary care (PC) practices.

methodsThis project was a cross sectional study of 7 multidisciplinary primary care teams in Ontario, Canada. Practices were recruited and 5-7 physicians per practice agreed to participate in the study. Patients of participating physicians (20-30) were recruited sequentially as they presented to attend a visit. Data collection included patient, provider and practice surveys, chart abstraction and linkage to administrative data sets. Matched pairs analysis was used to examine the differences in the observed results for each indicator obtained using multiple data sources.

resultsSeven teams, 41 physicians, 94 associated staff and 998 patients were recruited. The survey response rate was 81% for patients, 93% for physicians and 83% for associated staff. Chart audits were successfully completed on all but 1 patient and linkage to administrative data was successful for all subjects. There were significant differences noted between the data collection methods for many measures. No single method of data collection was best for all outcomes. For most measures of technical quality of care chart audit was the most accurate method of data collection. Patient surveys were more accurate for immunizations, chronic disease advice/information dispensed, some general health promotion items and possibly for medication use. Administrative data appears useful for indicators including chronic disease diagnosis and osteoporosis/ breast screening.

conclusionsMultiple data collection methods are required for a comprehensive assessment of performance in primary care practices. The choice of which methods are best for any one particular study or quality improvement initiative requires careful consideration of the biases that each method might introduce into the results. In this study, both patients and providers were willing to participate in and consent to, the collection and linkage of information from multiple sources that would be required for such assessments.

Indexed as

Health Knowledge, Attitudes, PracticeQuality Indicators, Health CareAdolescentAdultAgedChronic DiseaseCross-Sectional StudiesDiagnosis-Related GroupsFemaleHealth SurveysHumansMaleMedical AuditMiddle AgedOntarioOutcome Assessment, Health Care

Identifiers

PMID22824551
PMCPMC3431283

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LicenceCC BY
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Registered trials

None linked

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.