IMPLEMENTATION AND EVALUATION OF A DKA ORDER SET IN A PEDIATRIC TERTIARY CARE HOSPITAL: A QUALITY IMPROVEMENT INITIATIVE
Bibliographic record
Abstract
Abstract BACKGROUND Diabetic ketoacidosis (DKA) is a common clinical presentation in new and previously diagnosed paediatric patients with type 1 diabetes. In contrast to other Canadian tertiary paediatric hospitals, our center lacked a physician-endorsed evidence-informed care pathway for management of DKA. In the absence of a standardized approach to DKA, variability in patient management and outcomes were observed. This project was a quality improvement initiative that sought to develop and pilot a paediatric DKA order set. OBJECTIVES Our primary aim was to attain broad clinical uptake of the order set at our tertiary care center over a 12-month period. Secondary aims included improved standard-of-care DKA management: appropriate fluid bolus volume and maintenance rates; initial potassium management; and timely dextrose supplementation. DESIGN/METHODS A paediatric multidisciplinary collaborative was created to examine evidence for the development and implementation of a DKA order set. Implementation of the order set involved department wide education, targeted end-user education, and quarterly end-user review. A modified plan-do-study-act (PDSA) cycle guided by end-user feedback and early clinical outcomes allowed progressive order set modifications. RESULTS A retrospective chart review of fifty paediatric patients presenting to our center between April 2014 and September 2016 (pre-implementation) was compared to thirty paediatric patients presenting in DKA during the post-implementation phase (September 2016 – September 2017). There were no statistically significant differences in demographic and clinical characteristics between the groups. We achieved 83% uptake of the order set for patients presenting to our tertiary center and 67% uptake for patients transferred from peripheral centers. Improvements in DKA management included: appropriate intravenous (IV) maintenance fluid rates (20% vs. 48.3%, p=0.008), earlier administration of potassium to IV fluids (66% vs. 93.1%, p=0.006); appropriate potassium chloride dosing (40 mmol/L) to IV fluid (40% vs. 79.3%, p=0.0007) and earlier addition of IV dextrose (67.4% vs. 93.1%, p=0.009). No differences in moderate to severe hypokalemia (< 3.0 mmol/L), hypoglycemia (<4.0 mmol/L) or clinically suspected cerebral edema occurred. CONCLUSION Implementation of a DKA order set in a tertiary hospital required identification of key stakeholders, formation of a multidisciplinary team, and the development of an evaluation process. There was an observed increase in physician order set uptake and DKA management practice improvements. Future goals involve expanding the implementation and evaluation process to regional and remote centers and analyzing the impact on resource utilization.
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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 | 0.062 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".