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Record W2152169827 · doi:10.1186/1472-6963-14-s1-s7

Pilot-testing service-based planning for health care in rural Zambia

2014· article· en· W2152169827 on OpenAlexafffund
Fastone Goma, Gail Tomblin Murphy, Miriam Libetwa, Adrian MacKenzie, Selestine Nzala, Clara Mbwili‐Muleya, Janet Rigby, Amy Gough

Bibliographic record

VenueBMC Health Services Research · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchInternational Development Research CentreGovernment of Canada
KeywordsMedicineHealth administrationWorkforcePublic healthHealth informaticsHealth carePopulationNursing researchRural healthCommunity healthEnvironmental healthHealth policyPopulation healthHealth services researchService (business)Rural areaNursingBusinessEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Human resources for health (HRH) planning in Zambia, as in other countries, is often done by comparing current HRH numbers with established posts, without considering whether population health needs are being met. Service-based HRH planning compares the number and type of services required by populations, given their needs, with the capacity of existing HRH to perform those services. The objective of the study was to demonstrate the effectiveness of service-based HRH planning through its adaptation in two rural Zambian districts, Gwembe and Chibombo. METHODS: The health conditions causing the greatest mortality and morbidity in each district were identified using administrative data and consultations with community health committees and health workers. The number and type of health care services required to address these conditions were estimated based on their population sizes, incidence and prevalence of each condition, and desired levels of service. The capacity of each district's health workers to provide these services was estimated using a survey of health workers (n=44) that assessed the availability of their specific competencies. RESULTS: The primary health conditions identified in the two districts were HIV/AIDS in Gwembe and malaria in Chibombo. Although the competencies of the existing health workforces in these two mostly aligned with these conditions, some substantial gaps were found between the services the workforce can provide and the services their populations need. The largest gaps identified in both districts were: performing laboratory testing and interpreting results, performing diagnostic imaging and interpreting results, taking and interpreting a patient's medical history, performing a physical examination, identifying and diagnosing the illness in question, and assessing eligibility for antiretroviral treatment. CONCLUSIONS: Although active, productive, and competent, health workers in these districts are too few to meet the leading health care needs of their populations. Given the specific competencies most lacking, on-site training of existing health workers to develop these competencies may be the best approach to addressing the identified gaps. Continued use of the service-based approach in Zambia will enhance the country's ability to align the training, management, and deployment of its health workforce to meet the needs of its people.

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)0.003
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 score0.060
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.093
GPT teacher head0.456
Teacher spread0.362 · 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

Citations41
Published2014
Admission routes2
Has abstractyes

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