Unintended discontinuation of medication following hospitalisation: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Whether unintended discontinuation of common, evidence-based, long-term medication occurs after hospitalisation; what factors are associated with unintended discontinuation; and whether the presence of documentation of medication at hospital discharge is associated with continuity of medication in general practice. DESIGN: Retrospective cohort study between 2012 and 2015. SETTING: Electronic records and hospital supplied discharge notifications in 44 Irish general practices. PARTICIPANTS: 20 488 patients aged 65 years or more prescribed long-term medication for chronic conditions. PRIMARY AND SECONDARY OUTCOMES: Discontinuity of four evidence-based medication drug classes: antithrombotic, lipid-lowering, thyroid replacement drugs and respiratory inhalers in hospitalised versus non-hospitalised patients; patient and health system factors associated with discontinuity; impact of the presence of medication in the hospital discharge summary on continuity of medication in a patient's general practitioner (GP) prescribing record at 6 months follow-up. RESULTS: In patients admitted to hospital, medication discontinuity ranged from 6%-11% in the 6 months posthospitalisation. Discontinuity of medication is significantly lower for hospitalised patients taking respiratory inhalers (adjusted OR (AOR) 0.63, 95% CI (0.49 to 0.80), p<0.001) and thyroid medications (AOR 0.62, 95% CI (0.40 to 0.96), p=0.03). There is no association between discontinuity of medication and hospitalisation for antithrombotics (AOR 0.95, 95% CI (0.81 to 1.11), p=0.49) or lipid lowering medications (AOR 0.92, 95% CI (0.78 to 1.08), p=0.29). Older patients and those who paid to see their GP were more likely to experience increased odds of discontinuity in all four medicine groups. Less than half (39% to 47.4%) of patients had medication listed on their hospital discharge summary. Presence of medication on hospital discharge summary is significantly associated with continuity of medication in the GP prescribing record for lipid lowering medications (AOR 1.64, 95% CI (1.15 to 2.36), p=0.01) and respiratory inhalers (AOR 2.97, 95% CI (1.68 to 5.25), p<0.01). CONCLUSION: Discontinuity of evidence-based long-term medication is common. Increasing age and private medical care are independently associated with a higher risk of medication discontinuity. Hospitalisation is not associated with discontinuity but less than half of hospitalised patients have medication recorded on their hospital discharge summary.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".