A Narrative Review of Clinical Decision Support for Inpatient Clinical Pharmacists

OBJECTIVE  Increasingly, pharmacists provide team-based care that impacts patient care; however, the extent of recent clinical decision support (CDS), targeted to support the evolving roles of pharmacists, is unknown. Our objective was to evaluate the literature to understand the impact of clinical pharmacists using CDS. METHODS  We searched MEDLINE, EMBASE, and Cochrane Central for randomized controlled trials, nonrandomized trials, and quasi-experimental studies which evaluated CDS tools that were developed for inpatient pharmacists as a target user. The primary outcome of our analysis was the impact of CDS on patient safety, quality use of medication, and quality of care. Outcomes were scored as positive, negative, or neutral. The secondary outcome was the proportion of CDS developed for tasks other than medication order verification. Study quality was assessed using the Newcastle-Ottawa Scale. RESULTS  Of 4,365 potentially relevant articles, 15 were included. Five studies were randomized controlled trials. All included studies were rated as good quality. Of the studies evaluating inpatient pharmacists using a CDS tool, four showed significantly improved quality use of medications, four showed significantly improved patient safety, and three showed significantly improved quality of care. Six studies (40%) supported expanded roles of clinical pharmacists. CONCLUSION  These results suggest that CDS can support clinical inpatient pharmacists in preventing medication errors and optimizing pharmacotherapy. Moreover, an increasing number of CDS tools have been developed for pharmacists' roles outside of order verification, whereby further supporting and establishing pharmacists as leaders in safe and effective pharmacotherapy.

[1]  Xian-tao Zeng,et al.  The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta‐analysis, and clinical practice guideline: a systematic review , 2015, Journal of evidence-based medicine.

[2]  Farah Magrabi,et al.  Reduced Verification of Medication Alerts Increases Prescribing Errors , 2019, Applied Clinical Informatics.

[3]  S. Raybardhan,et al.  Implementation of a Clinical Decision Support Tool to Improve Antibiotic IV-to-Oral Conversion Rates at a Community Academic Hospital. , 2019, The Canadian journal of hospital pharmacy.

[4]  Guilherme Del Fiol,et al.  When an Alert is Not an Alert: A Pilot Study to Characterize Behavior and Cognition Associated with Medication Alerts , 2018, AMIA.

[5]  Jacob A. McCoy,et al.  Clinical Decision Support Improves Initial Dosing and Monitoring of Tobramycin and Amikacin , 2011 .

[6]  David Newby,et al.  The impact of pharmacy computerised clinical decision support on prescribing, clinical and patient outcomes: a systematic review of the literature , 2010, The International journal of pharmacy practice.

[7]  M. Aziz,et al.  Effects of multidisciplinary teams and an integrated follow-up electronic system on clinical pharmacist interventions in a cancer hospital , 2017, International Journal of Clinical Pharmacy.

[8]  Myaa Lightfoot,et al.  Clinical Pharmacist Impact on Intensive Care Unit Delirium: Intervention and Monitoring , 2019, Hospital pharmacy.

[9]  F. Turck,et al.  Role of an electronic antimicrobial alert system in intensive care in dosing errors and pharmacist workload , 2015, International Journal of Clinical Pharmacy.

[10]  Willemijn L. Eppenga,et al.  Comparison of a basic and an advanced pharmacotherapy-related clinical decision support system in a hospital care setting in the Netherlands , 2012, J. Am. Medical Informatics Assoc..

[11]  Harold I Feldman,et al.  Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial , 2015, The Lancet.

[12]  N. Barrueco,et al.  Drug prescribing in patients with renal impairment optimized by a computer-based, semi-automated system , 2013, International Journal of Clinical Pharmacy.

[13]  Allison B McCoy,et al.  Real-time pharmacy surveillance and clinical decision support to reduce adverse drug events in acute kidney injury , 2012, Applied Clinical Informatics.

[14]  P. Dayan,et al.  Considerations for Designing EHR-Embedded Clinical Decision Support Systems for Antimicrobial Stewardship in Pediatric Emergency Departments , 2020, Applied Clinical Informatics.

[15]  Jan Christoph,et al.  EHR-Independent Predictive Decision Support Architecture Based on OMOP , 2020, Applied clinical informatics.

[16]  D. O’Mahony,et al.  Structured Pharmacist Review of Medication in Older Hospitalised Patients: A Cost-Effectiveness Analysis , 2016, Drugs & Aging.

[17]  Pieter Cornu,et al.  Performance of a clinical decision support system and of clinical pharmacists in preventing drug–drug interactions on a geriatric ward , 2014, International Journal of Clinical Pharmacy.

[18]  Karen Whalen,et al.  The Impact of a Computerized Potassium Alert on Adverse Drug Events and Pharmacists' Interventions , 2010 .

[19]  Andreas Sönnichsen,et al.  Information technology interventions to improve medication safety in primary care: a systematic review. , 2013, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[20]  B. Carter Evolution of Clinical Pharmacy in the USA and Future Directions for Patient Care , 2016, Drugs & Aging.

[21]  S. Abraham,et al.  Clinical pharmacists: Bridging the gap between patients and physicians , 2014, Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society.

[22]  B. Sproule,et al.  Pharmacy in the 21st century: Enhancing the impact of the profession of pharmacy on people’s lives in the context of health care trends, evidence and policies , 2018, Canadian pharmacists journal : CPJ = Revue des pharmaciens du Canada : RPC.

[23]  David C Kaelber,et al.  Differences, Opportunities, and Strategies in Drug Alert Optimization-Experiences of Two Different Integrated Health Care Systems. , 2019, Applied clinical informatics.

[24]  Adam Wright,et al.  Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems , 2011, J. Am. Medical Informatics Assoc..

[25]  Lisa E. Hines,et al.  Ability of pharmacy clinical decision-support software to alert users about clinically important drug-drug interactions , 2011, J. Am. Medical Informatics Assoc..

[26]  Charles P. Friedman,et al.  Viewpoint Paper: A "Fundamental Theorem" of Biomedical Informatics , 2009, J. Am. Medical Informatics Assoc..

[27]  C. Rodriguez-Gonzalez,et al.  Development and Evaluation of a Clinical Decision Support System to Improve Medication Safety , 2019, Applied Clinical Informatics.

[28]  Patrice Degoulet,et al.  Validity of a clinical decision rule based alert system for drug dose adjustment in patients with renal failure intended to improve pharmacists' analysis of medication orders in hospitals , 2013, Int. J. Medical Informatics.

[29]  P. Gallagher,et al.  Prevention of Adverse Drug Reactions in Hospitalised Older Patients Using a Software-Supported Structured Pharmacist Intervention: A Cluster Randomised Controlled Trial , 2015, Drugs & Aging.

[30]  G. Peterson,et al.  Review of computerized clinical decision support in community pharmacy , 2014, Journal of clinical pharmacy and therapeutics.

[31]  Computerized pharmaceutical intervention to reduce reconciliation errors at hospital discharge in Spain: an interrupted time-series study. , 2016 .

[32]  Charlene R. Weir,et al.  The pharmacist and the EHR , 2017, J. Am. Medical Informatics Assoc..

[33]  Yang Gong,et al.  Understanding Health Information Technology Induced Medication Safety Events by Two Conceptual Frameworks , 2019, Applied Clinical Informatics.