Physician Compliance With a Computerized Clinical Decision Support System for Anemia Management of Patients With End-stage Kidney Disease on Hemodialysis: Retrospective Electronic Health Record Observational Study
Bibliographic record
Abstract
BACKGROUND: Previous studies on clinical decision support systems (CDSSs) for the management of renal anemia in patients with end-stage kidney disease undergoing hemodialysis have previously focused solely on the effects of the CDSS. However, the role of physician compliance in the efficacy of the CDSS remains ill-defined. OBJECTIVE: We aimed to investigate whether physician compliance was an intermediate variable between the CDSS and the management outcomes of renal anemia. METHODS: We extracted the electronic health records of patients with end-stage kidney disease on hemodialysis at the Far Eastern Memorial Hospital Hemodialysis Center (FEMHHC) from 2016 to 2020. FEMHHC implemented a rule-based CDSS for the management of renal anemia in 2019. We compared the clinical outcomes of renal anemia between the pre- and post-CDSS periods using random intercept models. Hemoglobin levels of 10 to 12 g/dL were defined as the on-target range. Physician compliance was defined as the concordance of adjustments of the erythropoietin-stimulating agent (ESA) between the CDSS recommendations and the actual physician prescriptions. RESULTS: We included 717 eligible patients on hemodialysis (mean age 62.9, SD 11.6 years; male n=430, 59.9%) with a total of 36,091 hemoglobin measurements (average hemoglobin and on-target rate were 11.1, SD 1.4, g/dL and 59.9%, respectively). The on-target rate decreased from 61.3% (pre-CDSS) to 56.2% (post-CDSS) owing to a high hemoglobin percentage of >12 g/dL (pre: 21.5%; post: 29%). The failure rate (hemoglobin <10 g/dL) decreased from 17.2% (pre-CDSS) to 14.8% (post-CDSS). The average weekly ESA use of 5848 (SD 4211) units per week did not differ between phases. The overall concordance between CDSS recommendations and physician prescriptions was 62.3%. The CDSS concordance increased from 56.2% to 78.6%. In the adjusted random intercept model, the post-CDSS phase showed increased hemoglobin by 0.17 (95% CI 0.14-0.21) g/dL, weekly ESA by 264 (95% CI 158-371) units per week, and 3.4-fold (95% CI 3.1-3.6) increased concordance rate. However, the on-target rate (29%; odds ratio 0.71, 95% CI 0.66-0.75) and failure rate (16%; odds ratio 0.84, 95% CI 0.76-0.92) were reduced. After additional adjustments for concordance in the full models, increased hemoglobin and decreased on-target rate tended toward attenuation (from 0.17 to 0.13 g/dL and 0.71 to 0.73 g/dL, respectively). Increased ESA and decreased failure rate were completely mediated by physician compliance (from 264 to 50 units and 0.84 to 0.97, respectively). CONCLUSIONS: Our results confirmed that physician compliance was a complete intermediate factor accounting for the efficacy of the CDSS. The CDSS reduced failure rates of anemia management through physician compliance. Our study highlights the importance of optimizing physician compliance in the design and implementation of CDSSs to improve patient outcomes.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".