Evidence map›Paper›PMID 38032421›Full record

ArticleAdministration and policy in mental health2024

Toward Efficient, Sustainable, and Scalable Methods of Treatment Characterization: An Investigation of Coding Clinical Practice from Chart Notes.

Benjamin M Isenberg, Kimberly D Becker, Eleanor Wu, Hyun Seon Park, Wendy Chu, Danielle Keenan-Miller, Bruce F Chorpita

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Article in Administration and policy in mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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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

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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

2 citing papers in PubMed.

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4 · The record

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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

7 authors.

Benjamin M IsenbergDepartment of Psychology, University of California Los Angeles, Franz Hall, Los Angeles, CA, 90095, United States of America.
Kimberly D BeckerDepartment of Psychology, University of South Carolina, 1512 Pendleton Street, Columbia, SC, 29208, United States of America.
Eleanor WuDepartment of Psychology, University of South Carolina, 1512 Pendleton Street, Columbia, SC, 29208, United States of America.
Hyun Seon ParkDepartment of Psychology, University of California Los Angeles, Franz Hall, Los Angeles, CA, 90095, United States of America.
Wendy ChuDepartment of Psychology, University of South Carolina, 1512 Pendleton Street, Columbia, SC, 29208, United States of America.
Danielle Keenan-MillerDepartment of Psychology, University of California Los Angeles, Franz Hall, Los Angeles, CA, 90095, United States of America.
Bruce F ChorpitaDepartment of Psychology, University of California Los Angeles, Franz Hall, Los Angeles, CA, 90095, United States of America. chorpita@ucla.edu.

Funding

William T. Grant Foundation 187173
6 · The paper itself

Abstract

purposeChart notes provide a low-cost data source that could help characterize what occurs in treatment with sufficient precision to improve management of care. This study assessed the interrater reliability of treatment content coded from chart notes and evaluated its concordance with content coded from transcribed treatment sessions.

methodFifty randomly selected and digitally recorded treatment events were transcribed and coded for practice content. Independent coders then applied the same code system to chart notes for these same treatment events. ANALYSIS: We measured reliability and concordance of practice occurrence and extensiveness at two levels of specificity: practices (full procedures) and steps (subcomponents of those procedures).

resultsFor chart notes, practices had moderate interrater reliability (M k = 0.50, M ICC = 0.56) and steps had moderate (M ICC = 0.74) to substantial interrater reliability (M k = 0.78). On average, 2.54 practices and 5.64 steps were coded per chart note and 4.53 practices and 13.10 steps per transcript. Across sources, ratings for 64% of practices and 41% of steps correlated significantly, with those with significant correlations generally demonstrating moderate concordance (practice M r = 0.48; step M r = 0.47). Forty one percent of practices and 34% of steps from transcripts were also identified in the corresponding chart notes.

conclusionChart notes provide an accessible data source for evaluating treatment content, with different levels of specificity posing tradeoffs for validity and reliability, which in turn may have implications for chart note interfaces, training, and new metrics to support accurate, reliable, and efficient measurement of clinical practice.

Indexed as

Clinical CodingMental Health ServicesHumansReproducibility of ResultsCommunity Mental Health ServicesData CollectionElectronic Health RecordsEvidence-Based Practice

Identifiers

PMID38032421

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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.