Quality of Care in Blood and Marrow Transplantation – a Systematic Review in Order to Define a Quality Framework and Develop Quality Indicators
Bibliographic record
Abstract
Abstract Introduction: Quality of health care is a major focus for providers, patients, payers and accreditors. Blood and marrow transplantation (BMT) is a complex and specialized process with unique quality needs. Accreditation bodies for BMT programs expect an implemented and coordinated management system. Currently, hospitals performing BMT have many tiers of quality evaluation from hospital accreditation, BMT accreditation, self-evaluation and in Ontario, provincial quality measurement. Hence, a quality framework with a clearly defined process of quality indicator (QI) prioritization, development and measurement is required. Methods: At Princess Margaret Cancer Centre, we conducted a structured review of the literature to identify published QI for BMT. The literature review from 1999 to 2014 focused on BMT with MESH terms including quality improvement/assurance, quality of health care, benchmarking, performance measures/indicators and standards of care. Focus was on the clinical aspects of care and laboratory/cell collection was excluded. We included Medline, Pubmed, Embase and CINAHL databases and a structured “grey zone” literature review. The identified QI were evaluated by a core expert panel and like concepts were merged and quality domains identified. Thereafter, end user engagement of the multidisciplinary team was completed through a modified Delphi Process. QI definitions were evaluated as medidata tables to link to data collection sources. Management/operational related and hospital accreditation QI were evaluated by the expert panel for relevance. A quality framework was then modeled off the Cancer System Quality Index to include the domains of safe, effective, efficient, integrated, equitable, responsive, accessible and innovative. QI were aligned to relevant domains in the framework to give an overall program evaluation and future direction. Results: Structured literature review identified 2211 citations with 111 abstracts meeting the inclusion criteria and only 20 full papers reporting on 114 QI. Grey zone literature review revealed a further 10 sources reporting on 100 QI. Of the 214 QI, 120 were quality domains or quality concepts (“Big Dot”) and not clearly defined QI. With consensus review, 214 QI were merged into 22 clinical and 12 operational/managerial “Big Dot” QI. Of the clinical QI, there were 8 only relevant to allogeneic BMT and 14 were relevant to both autologous and allogeneic BMT (see Table 1). Concurrently, mapping of QI within the framework as well as, alignment of both hospital and provincial BMT QI to the framework and to the 22 clinical QI indicators was done. . Conclusions: An integrated and comprehensive quality management plan is required for BMT which is standards based. We report a framework and strategy to align all quality endeavors occurring at local-regional to national levels as it relates to BMT. We also present a detailed literature review of QI in BMT and the need for more detailed, reproducible indicators in this area. As end-user engagement in quality improvement is necessary, the clinical multidisciplinary team will set QI prioritization for near term and future reporting though a modified Delphi exercise. Table 1: Big Dot Clinical QI in BMT for Prioritization and Development Apheresis Not Performed Due to Insufficient Mobilization Apheresis Not Performed Due to Other Reasons (i.e. progression) Appropriate Donor Screening and Testing Complications During Apheresis Complications During Bone Marrow Harvest Donor Outcomes (i.e. adverse events) Incidence and Measurement of Acute and Chronic Graft vs Host Disease Incidence of ICU Transfers Length of Stay in Hospital Routine Chimerism Analysis Median Time to Engraftment (in days) Number of Patients who enter the program that are not transplanted Nurse Sensitive Outcomes i.e. central venous catheter complications Need for Stem Cell Boost or Second Transplant for Graft Failure Patient Satisfaction at Discharge and at Transitions Rate of Serious Bacterial, Viral and Fungal Infections Readmissions within 30 Days of Discharge Relapse Rate Overall Survival Time to Find an Unrelated Compatible Donor Treatment Related Mortality Whether a Product was Collected From a Donor and Not Infused Disclosures No relevant conflicts of interest to declare.
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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 | 0.041 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.030 | 0.029 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".