Using Time-Referenced Data to Assess Medication Administration Performance and Quality

Welton, John; Kleiner, Catherine; Valdez, Carolyn; Richardson, Sara; Boyle, Kathy; Lucas, Eric

doi:10.1097/nna.0000000000000580

Cited by 13 publications

(30 citation statements)

References 12 publications

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“…Many variables including organizational projects, multidisciplinary team rounds, and patient-centric initiatives occurred during routine medication administration times, 6 am to 2 pm and 5 pm to 10 pm . Our high-acuity patient population required an average of 18.9 medications per day, which was more than double the amount recently reported 13. The pros and cons of an interruption-free medication zone were explored, with attention to current best practices 14.…”

Section: Approachmentioning

confidence: 96%

“…Addressing workarounds was important to reduce inefficiencies, support user-friendly processes, and eliminate near miss events resulting from medication pass distractions and interruptions. 12,13 In the Do phase, planned interventions were implemented and aligned with improvement goals and methods. Collaboration and transparency were embraced throughout all interactions and unit activities.…”

Section: Plan-do-study-actmentioning

confidence: 99%

“…Our high-acuity patient population required an average of 18.9 medications per day, which was more than double the amount recently reported. 13 The pros and cons of an interruption-free medication zone were explored, with attention to current best practices. 14 Given the complex nature of such a practice change, the team agreed to abandon any formal recommendation at this time.…”

Section: Plan-do-study-actmentioning

confidence: 99%

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Reducing Near Miss Medication Events Using an Evidence-Based Approach

Smith-Love¹

2022

Journal of Nursing Care Quality

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Background: Near miss medication events are pervasive without patient harm, mostly because of coincidence. Dynamic clinical environments challenge nurse compliance with medication administration rights and proper use of electronic technology. Problem: All nurses are educated in appropriate medication management, but our unit's barcoded medication administration scanning and electronic patient identification practices fell below the 97% benchmarks, representing hundreds of near miss medication events each month. Approach: Transformative leadership guided frontline staff to identify gaps in care processes and determined root causes for unsanctioned medication administration practices using a FOCUS (Find-Organize-Clarify-Understand-Select)-PDSA (Plan-Do-Study-Act) methodology. Outcomes: An interdisciplinary team committed to zero events of preventable harm overcame challenges to improve care delivery. Medication management scores exceeded organizational benchmarks, with sustainable gains over 2 years. Conclusions: A rapid-cycle, evidence-based approach engaged staff to reduce near miss medication events. Workable solutions driven by transparent communication and interpersonal collaboration influenced positive safety behaviors.

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Section: Approachmentioning

confidence: 96%

Section: Plan-do-study-actmentioning

confidence: 99%

Section: Plan-do-study-actmentioning

confidence: 99%

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Reducing Near Miss Medication Events Using an Evidence-Based Approach

Smith-Love¹

2022

Journal of Nursing Care Quality

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“…[26][27][28][29][30][31] Only recently have researchers started to explore BCMA data for insights into nursing practice. [32][33]…”

Section: Accepted Manuscriptmentioning

confidence: 99%

A Novel Use of Bar Code Medication Administration Data to Assess Nurse Staffing and Workload

et al. 2022

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Objective To introduce an innovative use of bar code medication administration (BCMA) data, medication pass analysis, that allows for examination of nurse staffing and workload using data generated during regular nursing workflow Methods Using one year (October 1, 2014 to September 30, 2015) of BCMA data for 11 acute-care units in one Veterans Affairs Medical Center, we determined the peak time for scheduled medications and included medications scheduled for and administered within two hours of that time in analyses. We established for each staff member their daily peak-time medication pass characteristics (number of patients, number of peak-time scheduled medications, duration, start-time), generated unit-level descriptive statistics, examined staffing trends, and estimated linear mixed-effects models of duration and start-time. Results As the most frequent (39.7%) scheduled medication time, 9:00 was the peak-time medication pass; 98.3% of patients (87.3% of patient-days) had a 9:00 medication. Use of nursing roles and number of patients per staff varied across units and over time. Number of patients, number of medications, and unit-level factors explained significant variability in registered nurse (RN) medication pass duration (conditional R2 = 0.237; marginal R2 = 0.199; Intraclass correlation = 0.05). On average, an RN and a licensed practical nurse (LPN) with four patients, each with six medications, would be expected to take 70 and 74 minutes, respectively, to complete the medication pass. On a unit with median 10 patients per LPN, the median duration (127 minutes) represents untimely medication administration on more than half of staff days. With each additional patient assigned to a nurse, average start time was earlier by 4.2 minutes for RNs and 1.4 minutes for LPNs. Conclusion Medication pass analysis of BCMA data can provide health systems a means for assessing variations in staffing, workload, and nursing practice using data generated during routine patient care activities.

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“…Delays in inpatient physician visits due to off-service placement result in a longer length of stay [ 12 ]. This strongly suggests that delays are uniformly linked to negative outcomes in medicine when treatment is protocolized, obligatory, and supported by robust evidentiary support [ 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Delayed Symptomatic Treatment Implementation in the Intensive Care Unit

et al. 2021

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We estimated the harm related to medication delivery delays across 12,474 medication administration instances in an intensive care unit using retrospective data in a large urban academic medical center between 2012 and 2015. We leveraged an instrumental variables (IV) approach that addresses unobserved confounds in this setting. We focused on nurse shift changes as disruptors of timely medication (vasodilators, antipyretics, and bronchodilators) delivery to estimate the impact of delay. The average delay around a nurse shift change was 60.8 min (p < 0.001) for antipyretics, 39.5 min (p < 0.001) for bronchodilators, and 57.1 min (p < 0.001) for vasodilators. This delay can increase the odds of developing a fever by 32.94%, tachypnea by 79.5%, and hypertension by 134%, respectively. Compared to estimates generated by a naïve regression approach, our IV estimates tend to be higher, suggesting the existence of a bias from providers prioritizing more critical patients.

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Using Time-Referenced Data to Assess Medication Administration Performance and Quality

Abstract: The findings support use of time-referenced data to identify clinical processes and performance in administering scheduled and PRN medications.

Cited by 13 publications

References 12 publications

Reducing Near Miss Medication Events Using an Evidence-Based Approach

Reducing Near Miss Medication Events Using an Evidence-Based Approach

A Novel Use of Bar Code Medication Administration Data to Assess Nurse Staffing and Workload

The Impact of Delayed Symptomatic Treatment Implementation in the Intensive Care Unit

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