Can Vignettes Be Used to Improve Practice & Outcome

NCT ID: NCT00122148

Last Updated: 2010-02-08

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

TERMINATED

Clinical Phase

NA

Study Classification

INTERVENTIONAL

Study Start Date

2005-09-30

Study Completion Date

2006-06-30

Brief Summary

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This is a pilot study to first measure the cross-sectional relationship between variations in physicians� vignette scores and aggregated scores of individual physicians� patient health outcomes; and second to (longitudinally) determine whether feedback of vignette scores improves physicians� clinical performance as measured by vignettes

Detailed Description

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1. Study Design: Physicians will complete computerized vignettes for four conditions � diabetes, coronary artery diseases (CAD), chronic obstructive pulmonary disease (COPD), and depression. We will collect retrospective outcomes data and develop composite outcome measures for on two conditions, Diabetes and CAD. For the longitudinal analysis, only vignette data will be collected and fed back to providers. Feedback will consist of specific data on vignette outcome scores for the individual physicians and for the sites overall.
2. Site Selection: Primary care clinics at 2 VAMCs
3. Study Population and Sampling: We will enroll primary care physicians at 2 VAMCs. 30 consenting physicians will be prospectively randomized into two groups. One group will receive feedback of their vignette scores, and the other group will serve as control, receiving no feedback.
4. Variables and Measurement Instruments: Computerized vignettes measuring clinical practice completed by the physicians for diabetes, CAD, COPD, and Depression and a composite health outcome measures from the medical records of these physicians� patients with diabetes and CAD.
5. Data Collection Strategy and Timeline: Vignettes will be administered to all physicians at baseline, with feedback of scores 3 months later and readministration of vignettes 9 months thereafter to measure the trend in improvement. The composite outcome data will only be collected at baseline only.
6. Data Analysis: The statistical analysis will compare the effects within the context of an analysis of covariance (ANCOVA) model. The analyte is the quality of care physicians give to patients with four common conditions. The relationship between vignette scores and patient outcomes will be modeled accounting for clustering effects. The prospective experimental design will be used to quantify possible differences between the intervention and control groups. The data will be analyzed using a three-way crossed, one-way nested ANCOVA model where the covariate is the baseline vignette score. This model can be used to look at case effects, by domain, level of training, and by site.

Conditions

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Healthy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

SINGLE_GROUP

Blinding Strategy

NONE

Study Groups

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1

Group Type OTHER

Feedback on provision of care

Intervention Type BEHAVIORAL

Interventions

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Feedback on provision of care

Intervention Type BEHAVIORAL

Eligibility Criteria

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Inclusion Criteria

Physician at SF VAMC with panel of primary care patients

Exclusion Criteria

None
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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US Department of Veterans Affairs

FED

Sponsor Role lead

Responsible Party

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Department of Veterans Affairs

Principal Investigators

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Sharad Jain, MD

Role: PRINCIPAL_INVESTIGATOR

San Francisco

Locations

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San Francisco

San Francisco, California, United States

Site Status

Countries

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United States

References

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Peabody JW, Luck J, Jain S, Bertenthal D, Glassman P. Assessing the accuracy of administrative data in health information systems. Med Care. 2004 Nov;42(11):1066-72. doi: 10.1097/00005650-200411000-00005.

Reference Type RESULT
PMID: 15586833 (View on PubMed)

Other Identifiers

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IIR 01-189

Identifier Type: -

Identifier Source: org_study_id

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