Evidence map›Paper›PMID 36224111›Full record

ArticleJournal of public health dentistry2023

Development of quality measures to assess tooth decay outcomes from electronic health record data.

Ryan G Brandon, Suhasini Bangar, Alfa Yansane, Ana Neumann, Joanna M Mullins, Elsbeth Kalenderian, Muhammad F Walji, Joel M White

Open access · hybridAbstract read
In one paragraph

Article in Journal of public health dentistry, 2023. 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
0.6field-weighted citation impact, top 32% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  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

8 authors at 4 institutions in 2 countries.

Ryan G BrandonWillamette Dental Group and Skourtes Institute, Hillsboro, Oregon, USA.ORCID 0000-0003-1335-2438
Suhasini BangarSchool of Dentistry, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Alfa YansaneDepartment of Preventive and Restorative Dental Sciences, University of California, San Francisco, San Francisco, California, USA.
Ana NeumannSchool of Dentistry, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Joanna M MullinsWillamette Dental Group and Skourtes Institute, Hillsboro, Oregon, USA.
Elsbeth KalenderianAcademic Center for Dentistry, Amsterdam, Netherlands.
Muhammad F WaljiSchool of Dentistry, University of Texas Health Science Center at Houston, Houston, Texas, USA.
Joel M WhiteDepartment of Preventive and Restorative Dental Sciences, University of California, San Francisco, San Francisco, California, USA.ORCID 0000-0001-8950-697X
The University of Texas Health Science Center at Houston · USUniversity of California, San Francisco · USWillamette University · USAcademic Center for Dentistry Amsterdam · NL

Funding

Implementing Dental Quality Measures in PracticeR01DE024166 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KALENDERIAN, ELSBETH, WALJI, MUHAMMAD · 2015 to 2025
$7.3M
NIDCR NIH HHS R01 DE024166
6 · The paper itself

Abstract

objectivesTo develop outcomes of care quality measures derived from the dental electronic health record (EHR) to assess the occurrence and timely treatment of tooth decay.

methodsQuality measures were developed to assess whether decay was treated within 6 months and if new decay occurred in patients seen. Using EHR-derived data of the state of each tooth surface, algorithms compared the patient's teeth at different dates to determine if decay was treated or new decay had occurred. Manual chart reviews were conducted at three sites to validate the measures. The measures were implemented and scores were calculated for three sites over four calendar years, 2016 through 2019.

resultsAbout 954 charts were manually reviewed for the timely treatment of tooth decay measure, with measure performance of sensitivity 97%, specificity 85%, positive predictive value (PPV) 91%, negative predictive value (NPV) 95%. About 739 charts were reviewed for new decay measure, with sensitivity 94%, specificity 99%, PPV 99%, and NPV 94%. Across all sites and years, 52.8% of patients with decay were fully treated within 6 months of diagnosis (n = 247,959). A total of 23.8% of patients experienced new decay, measured at an annual exam (n = 640,004).

conclusionMethods were developed and validated for assessing timely treatment of decay and occurrence of new decay derived from EHR data, creating effective outcome measures. These EHR-based quality measures produce accurate and reliable results that support efforts and advancement in quality assessment, quality improvement, patient care and research.

Indexed as

Dental CariesElectronic Health RecordsHumansQuality Indicators, Health CareQuality of Health Caredental cariesdental informaticselectronic health recordhealthcare quality assessmentoutcome assessmentquality improvement

Identifiers

PMID36224111
PMCPMC10006288
OpenAlexW4304774411

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.