Evidence map›Paper›PMID 33944953›Full record

ArticlePain medicine (Malden, Mass.)2021

ICD-10 Coding of Musculoskeletal Conditions in the Veterans Health Administration.

Brian C Coleman, Joseph L Goulet, Diana M Higgins, Harini Bathulapalli, Todd Kawecki, Christopher B Ruser, Lori A Bastian, Steve Martino, John D Piette, Sara N Edmond and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Pain medicine (Malden, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Brian C ColemanPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.ORCID 0000-0002-6926-5571
Joseph L GouletPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
Diana M HigginsAnesthesiology, Critical Care, and Pain Medicine Service, VA Boston Healthcare System, Boston, Massachusetts.ORCID 0000-0002-6885-266X
Harini BathulapalliPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
Todd KaweckiPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
Christopher B RuserPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
Lori A BastianPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
Steve MartinoPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
John D PietteCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan.
Sara N EdmondPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.ORCID 0000-0002-6042-0053
Alicia A HeapyPain Research, Informatics, Multimorbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut.
Yale University · USBoston University · USUniversity of Michigan · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Pain Management Collaboratory Coordinating Center (PMC3)U24AT009769 · NCCIH · YALE UNIVERSITY · PI WILLIAM C BECKER, Alicia Heapy · 2017 to 2026
$16.4M
Cooperative Pain Education and Self-management: Expanding Treatment for Real-world Access (COPES ExTRA)UG3AT009767 · NCCIH · YALE UNIVERSITY · PI HEAPY, ALICIA · 2017 to 2018
$1.1M
HSR&D IIR 12-118NCATS NIH HHS UL1 TR001863NCCIH NIH HHS U24 AT009769NCCIH NIH HHS UG3 AT009767United States Department of Veterans AffairsUnited States Department of Veterans Affairs Health Services Research and Development Service (HSR&D) IIR-16-262VA HSR&D Research Career ScientistVeterans Health Administration, Office of Academic Affiliations, Office of Research and Development
6 · The paper itself

Abstract

objectiveWe describe the most frequently used musculoskeletal diagnoses in Veterans Health Administration care. We report the number of visits and patients associated with common musculoskeletal International Classification of Diseases (ICD)-10 codes and compare trends across primary and specialty care settings.

designSecondary analysis of a longitudinal cohort study. SUBJECTS: Veterans included in the Musculoskeletal Diagnosis Cohort with a musculoskeletal diagnosis from October 1, 2015, through September 30, 2017.

methodsWe obtained counts and proportions of all musculoskeletal diagnosis codes used and the number of unique patients with each musculoskeletal diagnosis. Diagnosis use was compared between primary and specialty care settings.

resultsOf more than 6,400 possible ICD-10 M-codes describing "Diseases of the Musculoskeletal System and Connective Tissue," 5,723 codes were used at least once. The most frequently used ICD-10 M-code was "Low Back Pain" (18.3%), followed by "Cervicalgia" (3.6%). Collectively, the 100 most frequently used codes accounted for 80% of M-coded visit diagnoses, and 95% of patients had at least one of these diagnoses. The most common diagnoses (spinal pain, joint pain, osteoarthritis) were used similarly in primary and specialty care settings.

conclusionA diverse sample of all available musculoskeletal diagnosis codes were used; however, less than 2% of all possible codes accounted for 80% of the diagnoses used. This trend was consistent across primary and specialty care settings. The most frequently used diagnosis codes describe the types of musculoskeletal conditions, among a large pool of potential diagnoses, that prompt veterans to present to the Veterans Health Administration for musculoskeletal care.

Indexed as

Musculoskeletal DiseasesVeteransHumansInternational Classification of DiseasesLongitudinal StudiesVeterans HealthInternational Classification of DiseasesMusculoskeletal Diseases/Diagnosis*Musculoskeletal Pain/Diagnosis*Veterans

Identifiers

PMID33944953
PMCPMC8783617
OpenAlexW3159026919

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.