A Randomised Controlled Trial of Medication Liaison Services—Acceptance and Use by Health Professionals
Bibliographic record
Abstract
Objectives: To determine the acceptance and utility of a Medication Liaison Service (MLS) by hospital and community healthcare professionals. The MLS aimed to improve the quality and transfer of medication‐related information associated with hospital admission. Method: 240 patients were randomly selected from acute wards and a pre‐admission clinic (PAC) at two major hospitals and randomly assigned to MLS (n = 113) or control (n = 127) groups. General practitioners (GPs) and community pharmacists attending each intervention patient were asked to anonymously complete a survey to assess acceptance and utility of the MLS 30 days post‐discharge. Hospital resident medical officers (RMOs, n = 12) exposed to the MLS while working in the PAC were also surveyed. Results: Surveys were returned from 76% of GPs, 84% of community pharmacists and 83% of RMOs. The comprehensiveness of medication information was rated as ‘good’ or ‘excellent’ by 100% of RMOs, 92% of GPs and 89% of community pharmacists. Timeliness was rated as at least ‘adequate’ by all but one GP and one community pharmacist. Over 70% of GPs utilised the information provided in patient care and GPs reported making 52 interventions to drug therapy as a result of MLS information. While only 11 interventions were made by community pharmacists, 70% requested routine access to the MLS information. Problems with storage and retrieval of information were factors limiting the utility of MLS information provided on discharge. Conclusion: MLS information was rated highly by RMOs, GPs and community pharmacists in terms of comprehensiveness and timeliness. The MLS facilitated medication management decisions and the majority of users requested routine access to the service in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".