Laboratory Medicine Handoff Gaps Experienced by Primary Care Practices: A Report from the Shared Networks of Collaborative Ambulatory Practices and Partners (SNOCAP)
Bibliographic record
Abstract
BACKGROUND: The majority of errors in laboratory medicine testing are thought to occur in the pre- and postanalytic testing phases, and a large proportion of these errors are secondary to failed handoffs. Because most laboratory tests originate in ambulatory primary care, understanding the gaps in handoff processes within and between laboratories and practices is imperative for patient safety. Therefore, the purpose of this study was to understand, based on information from primary care practice personnel, the perceived gaps in laboratory processes as a precursor to initiating process improvement activities. DESIGN: A survey was used to assess perceptions of clinicians, staff, and management personnel of gaps in handoffs between primary care practices and laboratories working in 21 Colorado primary care practices. Data were analyzed to determine statistically significant associations between categorical variables. In addition, qualitative analysis of responses to open-ended survey questions was conducted. RESULTS: Primary care practices consistently reported challenges and a desire/need to improve their efforts to systematically track laboratory test status, confirm receipt of laboratory results, and report results to patients. Automated tracking systems existed in roughly 61% of practices, and all but one of those had electronic health record-based tracking systems in place. One fourth of these electronic health record-enabled practices expressed sufficient mistrust in these systems to warrant the concurrent operation of an article-based tracking system as backup. Practices also reported 12 different procedures used to notify patients of test results, varying by test result type. CONCLUSION: The results highlight the lack of standardization and definition of roles in handoffs in primary care laboratory practices for test ordering, monitoring, and receiving and reporting test results. Results also identify high-priority gaps in processes and the perceptions by practice personnel that practice improvement in these areas is needed. Commonalities in these areas warrant the development and support of tools for use in primary care settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".