Evidence map›Paper›PMID 34420120›Full record

ArticleJournal of clinical psychology in medical settings2022

Measuring Productivity in Primary Care Behavioral Health: A Delphi Study.

Matthew P Martin, Ana J Bridges, Travis Cos

Abstract readConsensus Statement
PubMed Publisher
In one paragraph

Article in Journal of clinical psychology in medical settings, 2022. 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
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Matthew P MartinCollege of Health Solutions, Arizona State University, 550 N. 3rd St Phoenix, Phoenix, AZ, 85004, USA. mpmarti6@asu.edu.ORCID http://orcid.org/0000-0003-1603-526X
Ana J BridgesDepartment of Psychological Science, University of Arkansas, Fayetteville, AR, USA.
Travis CosHealth Federation of Philadelphia, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High productivity by behavioral health consultants (BHC) is a defining aspect of the primary care behavioral health (PCBH) model to maximize access to care and is often measured by patient volume. Studies of productivity in health care settings suggest a single productivity target may not be optimal. We used a Delphi method to obtain expert consensus on an operational definition of high productivity by BHCs in the PCBH model. Clinicians, managers, and researchers in PCBH were recruited to participate in a multi-round survey using a modified Delphi technique and develop consensus on PCBH productivity metrics. Ten participants completed all three survey rounds and rated 28 metrics. After three rounds, two direct metrics (average number of billable BHC visits each day; number of patients seen per day) received at least 80% consensus as "Essential", two received at least 50%, and five received less than 50%. One influencer (level of integration at the practice) received at least 80% consensus as "Very Much" influential, 19 received at least 50%, and eight items received less than 50%. Several themes arose from participant comments. PCBH productivity can be interpreted as being high volume. Numerous practice factors influence how productive a BHC may be. Future studies should determine the feasibility of our metrics in clinical practice, establish productivity expectations based on patient needs and clinic resources, and identify patient-, clinician-, or practice-level moderators of productivity.

Indexed as

PsychiatryDelphi TechniqueHumansPrimary Health CareSurveys and QuestionnairesBehavioral healthDelphi surveyIntegrated carePrimary careProductivity

Identifiers

What OpenQuestion holds

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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.