Enhancing Care Transitions in Alberta: Measuring the Impact of Implementing a Provincial Clinical Information System on Hospital to Home Transitions
Bibliographic record
Abstract
Introduction: Transitions between hospitals and primary care pose challenges, leading to increased mortality, morbidity, and high costs due to information loss. To improve patient safety during transitions, the World Health Organization emphasizes standardized discharge planning, better documentation, and enhanced Clinical Information Systems (CIS). Together, Alberta's newly implemented CIS “Connect Care” (CC) and the Primary Health Care Integration Network's (PHCIN) Home to Hospital to Home (H2H2H) Transitions Guideline and related metrics, aim to improve patient outcomes and system integration. Who is it for: Adults ≥18 years transitioning from hospital to home within Alberta's healthcare system. Engagement/Involvement: Engaged 750+ stakeholders in co-designing the Home to Hospital to Home (H2H2H) Transitions Guideline and related metrics, including patients, families, caregivers, and trans-disciplinary providers. Methods: This study utilizes provincial data on H2H2H transitions measures within acute care hospitals using CC from April 1, 2022 to March 31, 2023. Provincial data sources encompass CC, discharge abstract database, practitioner claims, and the national ambulatory care reporting system. The integration measures aim to comprehensively assess H2H2H care transitions provincially and strengthen ongoing improvement initiatives. Serving as pivotal indicators, they assess various components of the patient journey during transitions, including confirming the primary care provider at hospital discharge, utilizing the LACE Readmission Risk Index, ensuring timely discharge summaries, monitoring primary care physician follow-up, and evaluating unplanned hospital readmissions post-discharge. Key Findings: Results include discharges of Albertan adults from 47 sites that have implemented CC, totaling 98,108 discharges from hospitals to home/home with support. Nearly 80% of discharges listed a primary care provider. Less than 5% of discharge summaries included the LACE index. Approximately 90%, 91%, and 93% of discharge summaries were signed within 24, 48, and 72 hours, respectively. Around 58% of moderate-risk and 52% of high-risk discharges had follow-up care within set timeframes. Readmission rates within 7, 14, and 30 days were below 4%, around 7%, and approximately 11%, respectively. Conclusion: The adoption of CC and H2H2H transition metrics enables provincial integrated care measurement in hospital-to-primary care transitions, emphasizing the need for enhancing risk index inclusion and high-risk discharge follow-up to further improve patient transitions. Ongoing initiatives are crucial for optimal patient outcomes and system integration in Alberta. International Relevance: The indicators employed in this study are potentially applicable to other health systems aiming to monitor hospital-to-home transitions in care. As countries strive to enhance patient safety during transitions, these standardized measures and metrics may offer valuable insights into establishing effective discharge planning, improving documentation, and bolstering electronic CIS. Next Steps: Continuing work involves devising additional integration metrics to enhance understanding and improve patient outcomes during hospital-to-home transitions.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".