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Record W4413833477 · doi:10.2147/ceor.s538395

Beyond the COVID-19 Pandemic: Budget Impact Analysis of Remote Healthcare Delivery for Hypertension and Diabetes Mellitus Management in Thailand

2025· article· en· W4413833477 on OpenAlex
Jongkonnee Chongpornchai, Tuangrat Phodha, Thanawat Wongphan, Kamonwan Soonklang, Peter C. Coyte

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinicoEconomics and Outcomes Research · 2025
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersThammasat University
KeywordsPandemicMedicineCoronavirus disease 2019 (COVID-19)Diabetes mellitusHealthcare deliveryDiabetes managementSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakHealth careTelemedicineIntensive care medicineVirologyInternal medicineType 2 diabetesEconomic growthDiseaseInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

Purpose: The COVID-19 pandemic disrupted healthcare services globally, necessitating innovative care delivery models for non-communicable diseases. Remote healthcare pathways, including telehealth with pharmacy at home (PAH) and deferred care (DC), emerged as potential solutions for managing stable hypertension (HT) and diabetes mellitus (DM) patients. This study aims to estimate the budget impact of implementing PAH and DC compared to usual care (UC) for HT and DM patients in Thai tertiary care hospitals from the government perspective. Methods: A retrospective budget impact analysis was conducted using data from July-December 2021 (COVID-19 period) and July-December 2022 (new normal period). The study included stable patients from 35 tertiary care hospitals in Thailand. Direct medical costs were obtained from administrative databases and national costing studies. Multivariate log-linear regression models estimated conditional costs, controlling for patient characteristics. The analysis compared baseline scenario (UC only) versus alternative scenario (UC+PAH+DC). Sensitivity analyses were performed using 95% confidence intervals and ±20% population variations. Results: The alternative scenario demonstrated lower total budgets in both periods. During COVID-19, total costs were 12.23 versus 12.94 million USD (baseline), yielding 0.71 million USD in savings. In the new normal, costs were 11.93 versus 12.54 million USD (baseline), generating 0.61 million USD in savings. Cost-saving ratios were 0.06 USD and 0.05 USD per dollar allocated during the COVID-19 and new normal periods, respectively. Sensitivity analyses confirmed robustness across parameter variations. Conclusion: PAH and DC pathways represent economically advantageous alternatives, demonstrating cost savings from the government perspective. These findings support implementing remote healthcare delivery in resource-constrained settings, though comprehensive evaluations incorporating societal and patient perspectives are warranted. The findings are based on extrapolation-based results and should be interpreted with caution due to variability in parameters including adoption rates of PAH/DC, unit costs applied, patient numbers, retrospective design, bundled interventions, and the savings ratio.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.162
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.143
GPT teacher head0.506
Teacher spread0.363 · 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