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Record W4403700634 · doi:10.3389/fendo.2024.1359904

Temporal trend in quality indicators of diabetes care performance among persons with type 2 diabetes in primary care practice: a serial cross-sectional analytical study, 2013/14 to 2021/22

2024· article· en· W4403700634 on OpenAlexaff
Ratanaporn Awiphan, Woravut Kowatcharakul, Chidchanok Ruengorn, Kajohnsak Noppakun, Kednapa Thavorn, Surapon Nochaiwong

Bibliographic record

VenueFrontiers in Endocrinology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsInstitute for Clinical Evaluative SciencesOttawa HospitalUniversity of Ottawa
FundersChiang Mai University
KeywordsMedicineType 2 diabetesAlbuminuriaDiabetes mellitusGlycemicSmoking cessationQuality and Outcomes FrameworkReimbursementKidney diseaseDiabetes managementMedical prescriptionEmergency medicineInternal medicineEnvironmental healthHealth careFamily medicinePrimary careNursingEndocrinology

Abstract

fetched live from OpenAlex

Background Although the national-based policy implemented an initiative program to offer diabetes care management in Thailand, there are limited time trends of evidence to gauge whether the quality of diabetes care in primary care practice is improving. As such, we aimed to identify temporal trends in the quality of diabetes care performance among type 2 diabetes mellitus (T2DM) patients in primary care practice. Methods Using assembled patient-level data from a suburban community in northern Thailand, this serial retrospective cross-sectional analytical study obtained adult T2DM patients from nine consecutive fiscal years 2013/14 ( n = 976) to 2021/22 ( n = 1,242). Based on international and national guidelines recommended, nine quality indicators were examined, namely, smoking cessation, hemoglobin A1c monitoring, foot and eye examinations, albuminuria testing, statin prescription, angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker (ACEI/ARB) prescription for chronic kidney disease (CKD)/albuminuria, and blood pressure and glycemic control. Rates and time trends achieved in each quality indicator performance were estimated. Differences in the rates of patients who met each quality indicator across reimbursement schemes were explored. Results From 2013/14 to 2021/22, all quality indicators have increased over time ( p for trend <0.05) except for smoking cessation, which remained steady. In 2021/22, only three out of nine quality indicators (i.e., smoking cessation, annual HbA1c monitoring, and annual foot examination) were successfully met at 70% or greater. Differences in quality indicators of diabetes performance were observed, particularly those under the Civil Servant Medical Benefit Scheme compared with other health insurance counterparts. For overall time trends analysis (compared with 2013/14), significant relative changes in the fiscal year 2021/22 were found in the annual foot examination (adjusted 12.1% increase; p = 0.048), annual albuminuria testing (adjusted 12.1% increase; p = 0.048), and ACEI/ARB prescription for persons with CKD or albuminuria (adjusted 22.2% increase; p = 0.025). Conclusion Among adult T2DM patients from 2013/14 to 2021/22, overall quality indicators for diabetes performance have substantially improved over time. However, health inequity regarding diabetes care performance was found across different reimbursement schemes. Sustainable policy implementation and innovative strategies to narrow health inequity are warranted to optimize diabetes care in primary care practice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.396
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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