Quantifying Discharge Medication Reconciliation Errors at 2 Pediatric Hospitals

Morse, Keith; Chadwick, Whitney; Paul, W. E.; Haaland, Wren; Pageler, Natalie M.; Tarrago, Rod

doi:10.1097/pq9.0000000000000436

Cited by 7 publications

(9 citation statements)

References 17 publications

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“…Finally, this study adds to a nascent body of literature around free-text prescribing 5,6 . We found that the majority of medications prescribed using this method were common medications that could easily be prescribed using the structured fields in the EHR, and likely are perpetuated by poorly constructed user preference lists.…”

Section: Accepted Manuscriptmentioning

confidence: 89%

“…We define a provider as any clinician capable of signing a medication order, which in this instance includes pharmacists, advanced practice providers, and physicians. Supplies, insulins, unlisted medications and investigational drug prescription records were excluded from triggering the alert as these were deemed appropriate for use of the free-text method 6 . Providers were pseudo-randomly assigned to either the visible alert (intervention) or silent alert (control) group based on their EHR user ID.…”

Section: Interventionmentioning

confidence: 99%

“…Studies indicate that this form of prescribing is prevalent, with 3 to 10% of discharge medications being prescribed using this method. 5,6 Current research into free-text prescribing points to perceived efficiency gains and lack of native EHR functionality as key drivers. 7 While some prescriptions such as medical supplies, equipment, and shortacting insulins cannot be easily prescribed using discrete order entry fields, modern EHR systems now incorporate the ability to prescribe combination and taper dosing, which was a main limitation to discrete ordering in the past.…”

Section: Background and Significancementioning

confidence: 99%

“…Studies indicate that this form of prescribing is prevalent, with 3-10% of discharge medications being prescribed using this method 5,6 . Current research into free-text prescribing points to perceived efficiency gains and lack of native EHR functionality as key drivers 7 .…”

Section: Introductionmentioning

confidence: 99%

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Pseudorandomized Testing of a Discharge Medication Alert to Reduce Free-Text Prescribing

Rabbani

Dash

et al. 2023

Appl Clin Inform

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Background: Pseudo-randomized testing can be applied to perform rigorous yet practical evaluations of clinical decision support tools. We apply this methodology to an interruptive alert aimed at reducing free-text prescriptions. Using free-text instead of structured computerized provider order entry elements can cause medication errors and inequity in care by bypassing medication-based clinical decision support tools and hindering automated translation of prescription instructions. Objective: Evaluate the effectiveness of an interruptive alert at reducing free-text prescriptions via pseudo-randomized testing using native electronic health records (EHR) functionality. Methods: Two versions of an EHR alert triggered when a provider attempted to sign a discharge free-text prescription. The visible version displayed an interruptive alert to the user, and a silent version triggered in the background, serving as a control. Providers were assigned to the visible and silent arms based on even/odd EHR provider IDs. The proportion of encounters with a free-text prescription was calculated across the groups. Alert trigger rates were compared in process control charts. Free-text prescriptions were analyzed to identify prescribing patterns. Results: Over the 28 week study period, 143 providers triggered 695 alerts (345 visible and 350 silent). The proportions of encounters with free-text prescriptions were 83% (266/320) and 90% (273/303) in the intervention and control groups respectively (p-value = 0.01). For the active alert, median time to action was 31 seconds. Alert trigger rates between groups were similar over time. Ibuprofen, oxycodone, steroid tapers, and oncology-related prescriptions accounted for most free-text prescriptions. A majority of these prescriptions originated from user preference lists. Discussion: An interruptive alert was associated with a modest reduction in free-text prescriptions. Furthermore, the majority of these prescriptions could have been reproduced using structured order entry fields. Targeting user preference lists shows promise for future intervention.

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Section: Accepted Manuscriptmentioning

confidence: 89%

Section: Interventionmentioning

confidence: 99%

Section: Background and Significancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Pseudorandomized Testing of a Discharge Medication Alert to Reduce Free-Text Prescribing

Rabbani

Dash

et al. 2023

Appl Clin Inform

View full text Add to dashboard Cite

show abstract

“…This method proves the importance of utilizing pharmacists in the admission medication reconciliation process and adds clarity to the scale and severity of medication errors that has been previously difficult and cumbersome to measure and convey [ 25 , 26 ]. A potential next step is to apply this method into a real-time or near real-time dashboard that would easily and quickly convey the findings of pharmacist-mediated medication reconciliation to hospital quality staff and leadership.…”

Section: Discussionmentioning

confidence: 99%

Use of complete medication history to identify and correct transitions-of-care medication errors at psychiatric hospital admission

Vargas

Blakeslee²,

Banas³

et al. 2023

PLoS ONE

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Methods for categorizing the scale and severity of medication errors corrected by pharmacy staff during admission medication reconciliation using complete medication history continue to evolve. We established a rating scale that is effective for generating error reports to health system quality leadership. These reports are needed to quantify the value of investment in transitions-of-care pharmacy staff. All medication errors that were reported by pharmacy staff in the admission medication reconciliation process during a period of 6 months were eligible for inclusion. Complete medication history data source was utilized by admitting providers and all pharmacist staff and a novel medication error scoring methodology was developed. This methodology included: medication error category, medication error type, potential medication error severity, and medication non-adherence. We determined that 82 medication errors were detected from 72 patients and assessed that 74 of these errors may have harmed patients if they were not corrected through pharmacist intervention. Most of these errors were dosage discrepancies and omissions. With hospital system budgets continually becoming leaner, it is important to measure the effectiveness and value of staff resources to optimize patient care. Pharmacists performing admission medication reconciliation can detect subtle medication discrepancies that may be overlooked by other clinician types. This methodology can serve as a foundation for error reporting and predicting the severity of adverse drug events.

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Impact of pharmacist medication review for paediatric patients: an observational study

Solano

2022

International Journal of Pharmacy Practice

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Background Paediatric patients are at high risk of medication errors and adverse drug events due to complex medical care. Objective To assess the impact of pharmacist medication review for paediatric patients. Setting A single-centre prospective observational study was performed over 33 months, from February 2018 to October 2020 in a French Hospital. Method Clinical pharmacists provided medication counselling at a hospital and conducted telephone follow-ups between 3 and 7 days after discharge of paediatric patients with chronic diseases for whom treatment was introduced or modified during hospitalisation or hospital consultations. Main outcome measures The incidence of drug-related problems (DRPs), the number and type of pharmacist intervention and paediatrician acceptance rates were assessed. Parents’ understanding and drug-related needs were compared before and after medication review. Time to outpatient treatment and patient satisfaction were determined. Statistical analyses were performed in Excel. Results In total, 195 paediatric patients were included. Pharmacists identified 65 interventions, 95% of which were accepted. The most frequent DRPs included inappropriate drug administration (32.3%), herb–drug interactions (24.6%) and dose selection (17%). Parents’ knowledge increased by 28% from baseline after pharmacist’s medication counselling. Parents’ drug-related needs concerning administration and side effects decreased by 67% and 49%, respectively, following the pharmacist’s medication counselling. Most (75%) of the patients were able to get their treatment immediately after discharge. Conclusion Clinical pharmacists can improve medication safety for children during the discharge process or consultations, by reducing prescription errors, optimising administration, counselling patients or parents and helping to ensure care continuity.

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Quantifying Discharge Medication Reconciliation Errors at 2 Pediatric Hospitals

Cited by 7 publications

References 17 publications

Pseudorandomized Testing of a Discharge Medication Alert to Reduce Free-Text Prescribing

Pseudorandomized Testing of a Discharge Medication Alert to Reduce Free-Text Prescribing

Use of complete medication history to identify and correct transitions-of-care medication errors at psychiatric hospital admission

Impact of pharmacist medication review for paediatric patients: an observational study

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