| Literature DB >> 30866925 |
Monsey McLeod1, Georgios Dimitrios Karampatakis2, Lore Heyligen3, Ann McGinley4, Bryony Dean Franklin5,6.
Abstract
BACKGROUND: The increasing adoption of hospital electronic prescribing and medication administration (ePA) systems has driven a wealth of research around the impact on patient safety. Yet relatively little research has sought to understand the effects on staff, particularly pharmacists. We aimed to investigate the effects of ePA on pharmacists' activities, including interactions with patients and health professionals, and their perceptions of medication safety risks.Entities:
Keywords: Computerised physician order entry (CPOE); Electronic prescribing; Electronic prescribing and medication administration system; Interview; Medication safety; Mixed methods; Patient safety; Pharmacist; Work-sampling; Workflow
Mesh:
Year: 2019 PMID: 30866925 PMCID: PMC6417214 DOI: 10.1186/s12913-019-3986-4
Source DB: PubMed Journal: BMC Health Serv Res ISSN: 1472-6963 Impact factor: 2.655
Overview of observations
| Acute admissions | Medicine for the Elderly | Both wards combined | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Pre-ePA | Post-ePA | Pre-ePA | Post-ePA | Pre-ePA | Post-ePA | ||||
| Number of observations | 18 | 26 | – | 6 | 13 | – | 24 | 39 | – |
| Total observation time (h:min) | 33:21 | 47:42 | – | 10:09 | 25:38 | – | 43:30 | 73:20 | – |
| Mean duration of observation (h:min) | 1:51 | 1:50 (SD 14 mins) | 0.80 | 1:42 | 1:58 | 0.11 | 1:49 | 1:53 | 0.34 |
| Median number of patients reviewed per observation | 6 | 5 | 0.18 | 18 | 9 | 0.48 | 6 | 5 | 0.36 |
| Number of activity samples | 990 | 1424 | – | 297 | 752 | – | 1287 | 2176 | – |
| Median time per patient reviewed (mins, 95% CI) | 19 | 21 | 0.14 | 7 | 14 (5–24) | 0.20 | 17 | 22 (17–24) | 0.16 |
Abbreviations: CI confidence interval, ePA electronic prescribing and medication administration system, SD standard deviation
Fig. 1Estimated mean change in time per 10 patients reviewed by pharmacist post electronic prescribing and administration (ePA). *statistical significance based on Bonferroni p-value <0.0028 (unpaired t-test). ‘Other’: casual conversation, scheduled break, waiting for equipment to become available, researcher-related activity, searching for equipment, auditing, handwashing, and unknown tasks
Fig. 2Estimated percentage of time observed working alone or interacting with others by pharmacist. Estimations were based on 1346 activity samples pre-electronic prescribing and administration (ePA) and 2176 post-ePA. Total exceeds 100% as pharmacists sometimes interacted with more than one other individual. * denotes p-value <0.05 (unpaired t-test)
Fig. 3Estimated percentage of time observed working in different locations by pharmacist: (a) acute admissions, (b) medicine-for-the-elderly ward. Abbreviation: ePA, electronic prescribing and administration
Electronic prescribing and medication administration (ePA) features that contributed to perception of increased medication risk
| ePA features | Implications for practice | Examples from pharmacist interviews |
|---|---|---|
| 1. System nudges users to do the ‘wrong’ thing | These are risks that could be reduced with system improvements and/or better user training | “ |
| 2. System indiscriminately defaults to specific actions | ||
| 3. System makes error less visible (than a paper drug chart) | ||
| 4. System makes error more visible (than a paper drug chart) | This is a safety feature that raises awareness of an error | |
| 5. ePA makes other key information less visible (compared to paper drug charts) | This is a risk that could be reduced with system improvements and/or better user training | |
| 6. System clinical decision support not meeting users’ expectations | This is a risk that could be reduced with better user training |