Improving laboratory quality and capacity through leadership and management training: Lessons from Zambia 2016–2018
Bibliographic record
Abstract
Competent leadership and management are imperative for delivering quality laboratory services; however, few laboratory managers receive job-specific training in organisational management and leadership.To develop and evaluate participants' competencies in organisational leadership and management as measured through learner and laboratory quality improvement assessments.This professional development programme employed a mentored, blended learning approach, utilising in-person didactic and online training, with the practical application of a capstone project in the laboratories. Programme impact was evaluated through a series of pre- and post-laboartory assessments using the Stepwise Laboratory Improvement Process Towards Accreditation checklist, as well as learner-competency assessments through online quizzes and discussions.From 2016 to 2018, 31 managers and quality officers from 16 individual laboratories graduated from the programme having completed capstone projects addressing areas in the entire laboratory testing process. Laboratories increased their compliance with the International Organization for Standardization 15189 standard and all but two laboratories significantly increased their accreditation scores. Two laboratories gained three stars, two laboratories gained two stars, and five laboratories gained one star. Five laboratories subsequently achieved International Organization for Standardization 15189 accreditation in 2019.This programme taught leadership theory to laboratory managers and allowed them to implement leadership and management practices in the laboratory setting. Programmes such as this complement existing laboratory quality management training programmes such as Strengthening Laboratory Management Toward Accreditation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".