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Record W4388288191 · doi:10.9745/ghsp-d-23-00050

Improving Malaria Case Management and Referral Relationships at the Primary Care Level in Ghana: Evaluation of a Quality Assurance Internship

2023· article· en· W4388288191 on OpenAlexaff
Amos Asiedu, Rachel A. Haws, Akosua Gyasi, Paul Boateng, Keziah Malm, Raphael Ntumy, Lolade Oseni, Gladys Tetteh

Bibliographic record

VenueGlobal Health Science and Practice · 2023
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsImpact
FundersPresident's Malaria InitiativeUnited States Agency for International Development
KeywordsReferralMedicineInternshipMentorshipMalariaFamily medicineWorkloadNursingMedical education

Abstract

fetched live from OpenAlex

In Ghana, Community-based Health Planning and Services (CHPS) compounds managed by trained nurses and midwives called community health officers (CHOs) play a major role in malaria service delivery. With heavy administrative burdens and minimal training in providing patient care, particularly for febrile illnesses, including malaria, CHOs struggle to comply with the World Health Organization’s test, treat, and track initiative guidelines and appropriate referral practices. A clinical training and mentorship program was implemented for CHOs to prevent and manage uncomplicated malaria and offer appropriate pre-referral treatment and referrals to district hospitals. Medical officers, pharmacists, midwives, health information officers, and medical laboratory scientists at 52 district referral hospitals were trained as mentors; CHOs from 520 poorly performing CHPS compounds underwent a 5-day internship at their assigned district referral hospital to improve knowledge and clinical skills for malaria case management. Three months later, mentors conducted post-training mentoring visits to assess knowledge and skill retention and provide ongoing on-the-job guidance. Significant percentage-point increases were observed immediately post-internship for history taking (+12.0, 95% confidence interval [CI]=8.3, 15.1; <i>P</i>&lt;.001); fever assessment (+24.9, 95% CI=20.9, 29.3; <i>P</i>&lt;.001); severe malaria assessment and referral (+32.0, 95% CI=28.2, 35.8; <i>P</i>&lt;.001); and knowledge assessment (+15.8, 95% CI=10.0, 21.3; <i>P</i>&lt;.001). Three months later, a third assessment revealed these gains were largely maintained. Analysis of national health management information system data showed statistically significant improvements in testing, treatment, and referral indicators at intervention CHPS compounds after the intervention that were not observed in comparison CHPS compounds. This training and mentorship approach offers a replicable model to build primary care provider competencies in malaria prevention and management and demonstrates how developing relationships between primary care and first-level referral facilities benefits both providers and clients. More methodologically rigorous studies are needed to measure the impact of this approach.

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 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)0.013
metaresearch head score (Gemma)0.001
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 score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.229
GPT teacher head0.471
Teacher spread0.242 · 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 teacher head, 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

Citations3
Published2023
Admission routes1
Has abstractyes

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