Best Possible Medication History by a Pharmacy Technician at a Tertiary Care Hospital
Bibliographic record
Abstract
INTRODUCTIONAt all interfaces of care during a hospital stay (admission, transfer, and discharge), the potential exists for inaccurate information about a patient’s drug therapy to be used for various purposes. If inaccurate information is used in establishing or modifying therapy, adverse drug events may occur. Such adverse events may span the range of drug-related problems, from inappropriate initiation or discontinuation to inappropriate route or dose. Medication reconciliation upon admission to hospital has been recognized as an important process in preventing adverse drug events at one interface of care.1 Conceptually, medication reconciliation on admission involves compiling an accurate list of the patient’s medications before admission (the best possible medication history [BPMH]) and ensuring that any subsequent therapy does not result in new drug-related problems. For optimal therapeutic transition, the BPMH would be obtained before any admission orders were written. However, many factors, such as cognitive impairment or a need to stabilize the patient’s condition, can prevent completion of the BPMH before in-hospital initiation of therapy. An alternative approach would be to compare the BPMH with therapy prescribed in hospital at some point after admission. This would allow prompt and efficient initiation of drug therapy but would also ensure subsequent review to identify and resolve any discrepancies. Such a comparison between the BPMH and admission orders ensures continuation of all appropriate medications while the patient is in hospital. Because medication reconciliation will be a requirement for hospital accreditation by 2010,1 it was necessary to devise a strategy for implementing this process at the authors’ hospital. Until now, physicians and nurses have reviewed each patient’s history at the time of admission, although neither discipline has medication use as the primary focus of these investigations. Pharmacists have extensive knowledge about medications, as well as the patient-interviewing skills required for high-quality assessment of patients’ drug therapy needs during transitions of care. However, pharmacists’ expertise would be better used in assessing the appropriateness of therapy rather than performing the technical task of compiling a BPMH. Because of resource constraints leading to inadequate attention or time on the part of physicians, nurses, and pharmacists, an alternative method of obtaining the BPMH was required. Although some institutions have assisted the admitting physicians or nurses by developing a standardized documentation form for use during the admission process, such forms have not been demonstrated to improve the rate of identified discrepancies upon admission.2 The use of pharmacy students for medication reconciliation has been reported, but the need to ensure a continuous supply of students and to provide training for new students limits the applicability of this method for most institutions.3 Several centres have studied the participation of pharmacy technicians in the medication reconciliation process.4-7 In these studies and others, the technicians were able to complete the BPMH with a 95% accuracy rate (B. Tugwood, Trillium Health Centre, personal communication by e-mail, January 29, 2008), and their involvement in medication reconciliation reduced the time spent by physicians, nurses, and pharmacists at the time of admission (L. Saulnier, South-East Regional Health Authority, personal communication by e-mail, August 14, 2007). When working in conjunction with a pharmacist, technicians can obtain the information necessary for timely identification and reconciliation of discrepancies, thus helping to prevent the occurrence of adverse drug events. Pharmacy technicians appear to be suitable candidates for completing medication histories. They are familiar with the dosage forms, strengths, and usual dosing schedules of a wide range of medications. In addition, they have received training about the medications that can be obtained without a prescription, which facilitates the identification of medications not included in prescription databases, such as the BC PharmaNet. Although lacking a pharmacist’s understanding of the indications, side effects, and combinations of medications, pharmacy technicians have many skills that allow identification of medications used on an outpatient basis. The study reported here was undertaken to demonstrate the feasibility of training a hospital pharmacy technician to obtain the BPMH and to communicate discrepancies to the pharmacist for patients who had been admitted to a tertiary care hospital.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".