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Record W2036266405 · doi:10.1186/1472-6963-12-210

Simplifying ART cohort monitoring: Can pharmacy stocks provide accurate estimates of patients retained on antiretroviral therapy in Malawi?

2012· article· en· W2036266405 on OpenAlexaboutno aff
Hannock Tweya, Caryl Feldacker, Anne Ben‐Smith, Anthony Harries, Ryuichi Komatsu, Andreas Jahn, Sam Phiri, Jean-Michel Tassie

Bibliographic record

VenueBMC Health Services Research · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersInternational Union Against Tuberculosis and Lung Disease
KeywordsPharmacyQuarter (Canadian coin)MedicineCohortHealth informaticsMedical recordCohort studyHealth administrationFamily medicineMedical emergencyPediatricsEmergency medicinePublic healthSurgeryNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Routine monitoring of patients on antiretroviral therapy (ART) is crucial for measuring program success and accurate drug forecasting. However, compiling data from patient registers to measure retention in ART is labour-intensive. To address this challenge, we conducted a pilot study in Malawi to assess whether patient ART retention could be determined using pharmacy records as compared to estimates of retention based on standardized paper- or electronic based cohort reports. METHODS: Twelve ART facilities were included in the study: six used paper-based registers and six used electronic data systems. One ART facility implemented an electronic data system in quarter three and was included as a paper-based system facility in quarter two only. Routine patient retention cohort reports, paper or electronic, were collected from facilities for both quarter two [April-June] and quarter three [July-September], 2010. Pharmacy stock data were also collected from the 12 ART facilities over the same period. Numbers of ART continuation bottles recorded on pharmacy stock cards at the beginning and end of each quarter were documented. These pharmacy data were used to calculate the total bottles dispensed to patients in each quarter with intent to estimate the number of patients retained on ART. Information for time required to determine ART retention was gathered through interviews with clinicians tasked with compiling the data. RESULTS: Among ART clinics with paper-based systems, three of six facilities in quarter two and four of five facilities in quarter three had similar numbers of patients retained on ART comparing cohort reports to pharmacy stock records. In ART clinics with electronic systems, five of six facilities in quarter two and five of seven facilities in quarter three had similar numbers of patients retained on ART when comparing retention numbers from electronically generated cohort reports to pharmacy stock records. Among paper-based facilities, an average of 13 4 hours was needed to calculate patient retention for cohort reporting using patient registers as compared to 2.25 hours using pharmacy stock cards. CONCLUSION: The numbers of patients retained on ART as estimated using pharmacy stock records were largely similar to estimates based on either paper registers or electronic data system. Furthermore, less time and staff effort was needed to estimate ART patient retention using pharmacy stock records versus paper-based registers. Reinforcing ARV stock management may improve the precision of estimates.

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)0.006
metaresearch head score (Gemma)0.039
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 score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.122
GPT teacher head0.492
Teacher spread0.370 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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