Evidence map›Paper›PMID 35970673›Full record

ArticleJournal of the American Dental Association (1939)2022

Translating periodontal data to knowledge in a learning health system.

Bunmi Tokede, Alfa Yansane, Joel White, Suhasini Bangar, Joanna Mullins, Ryan Brandon, Swaroop Gantela, Krishna Kookal, Donald Rindal, Chun-Teh Lee and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of the American Dental Association (1939), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. [Applications and perspectives of artificial intelligence in periodontology].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2025
    Review
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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

14 authors.

Bunmi Tokede
Alfa Yansane
Joel White
Suhasini Bangar
Joanna Mullins
Ryan Brandon
Swaroop Gantela
Krishna Kookal
Donald Rindal
Chun-Teh Lee
Guo-Hao Lin
Heiko Spallek
Elsbeth Kalenderian
Muhammad Walji

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

backgroundA learning health system (LHS) is a health system in which patients and clinicians work together to choose care on the basis of best evidence and to drive discovery as a natural outgrowth of every clinical encounter to ensure the right care at the right time. An LHS for dentistry is now feasible, as an increased number of oral health care encounters are captured in electronic health records (EHRs).

methodsThe authors used EHRs data to track periodontal health outcomes at 3 large dental institutions. The 2 outcomes of interest were a new periodontitis case (for patients who had not received a diagnosis of periodontitis previously) and tooth loss due to progression of periodontal disease.

resultsThe authors assessed a total of 494,272 examinations (new periodontitis outcome: n = 168,442; new tooth loss outcome: n = 325,830), representing a total of 194,984 patients. Dynamic dashboards displaying performance on both measures over time allow users to compare demographic and risk factors for patients. The incidence of new periodontitis and tooth loss was 4.3% and 1.2%, respectively.

conclusionsPeriodontal disease, diagnosis, prevention, and treatment are particularly well suited for an LHS model. The results showed the feasibility of automated extraction and interpretation of critical data elements from the EHRs. The 2 outcome measures are being implemented as part of a dental LHS. The authors are using this knowledge to target the main drivers of poorer periodontal outcomes in a specific patient population, and they continue to use clinical health data for the purpose of learning and improvement. PRACTICAL IMPLICATIONS: Dental institutions of any size can conduct contemporaneous self-evaluation and immediately implement targeted strategies to improve oral health outcomes.

Indexed as

Learning Health SystemPeriodontal DiseasesPeriodontitisTooth LossDental InformaticsHumansPopulation Healthbig dataClinical outcomesdecision makingdental informaticsepidemiologypopulation health

Identifiers

PMID35970673
PMCPMC9830777
OpenAlexW4291034558

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.