Quality of Inpatient Tuberculosis Health Care in High-Burden Resource-Limited Settings: Protocol for a Comprehensive Mixed Methods Assessment Study
Bibliographic record
Abstract
BACKGROUND: The quality of care for tuberculosis (TB) is deficient in high-burden countries and urgently needs improvement. However, comprehensively identifying the required improvements is challenging. Providing high-quality TB care is an important step toward improving patients' quality of life and decreasing TB morbidity and mortality. Effective tools for assessing the quality of TB services using international standards and guidelines can identify existing gaps in services and inform improvements to ensure high-quality inpatient TB services. OBJECTIVE: This study aimed to develop evaluation instruments for defining the quality of provision of TB services. METHODS: To assess quality of services in the largest TB hospital in Armenia, we developed instruments based on the Joint Commission International Accreditation Standards for Hospitals, International Standards for TB Care, TB Laboratories Bio-Safety Standards, and the World Health Organization framework for conducting TB program reviews. A mixed methods approach was utilized, triangulating quantitative (checklists) and qualitative (in-depth interviews) results. A scoring system and strengths, weaknesses, opportunities, and treats analysis was applied to detail results for each of the 122 standards assessed. A scaling approach was used to present overall performances of inpatient services for eight patient-centered functions and five organization management functions. RESULTS: Overall, 40 in-depth interviews and 91 checklists (21 observations, 16 policy papers, 20 staff qualification documents, and 34 medical records) were developed, utilized, and analyzed to explore practices of health care professionals, assess inpatient treatment experience of patients and their family members, evaluate facility environmental conditions, and define the degree of compliance to standards. CONCLUSIONS: The effective comprehensive evaluation instruments and methods developed in this study for quality of inpatient TB services support the implementation of similar effective assessments in other countries. It may also become a platform to develop similar approaches for assessing ambulatory TB services in resource-limited countries. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13903.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.076 | 0.051 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.040 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".