Alerts for community pharmacist-provided medication therapy management: recommendations from a heuristic evaluation

BackgroundMedication therapy management (MTM) is a service, most commonly provided by pharmacists, intended to identify and resolve medication therapy problems (MTPs) to enhance patient care. MTM is typically documented by the community pharmacist in an MTM vendor’s web-based platform. These platforms often include integrated alerts to assist the pharmacist with assessing MTPs. In order to maximize the usability and usefulness of alerts to the end users (e.g., community pharmacists), MTM alert design should follow principles from human factors science. Therefore, the objectives of this study were to 1) evaluate the extent to which alerts for community pharmacist-delivered MTM align with established human factors principles, and 2) identify areas of opportunity and recommendations to improve MTM alert design.MethodsFive categories of MTM alerts submitted by community pharmacists were evaluated: 1) indication, 2) effectiveness; 3) safety; 4) adherence; and 5) cost-containment. This heuristic evaluation was guided by the Instrument for Evaluating Human-Factors Principles in Medication-Related Decision Support Alerts (I-MeDeSA) which we adapted and contained 32 heuristics. For each MTM alert, four analysts’ individual ratings were summed and a mean score on the modified I-MeDeSA computed. For each heuristic, we also computed the percent of analyst ratings indicating alignment with the heuristic. We did this for all alerts evaluated to produce an “overall” summary of analysts’ ratings for a given heuristic, and we also computed this separately for each alert category. Our results focus on heuristics where ≤50% of analysts’ ratings indicated the alerts aligned with the heuristic.ResultsI-MeDeSA scores across the five alert categories were similar. Heuristics pertaining to visibility and color were generally met. Opportunities for improvement across all MTM alert categories pertained to the principles of alert prioritization; text-based information; alarm philosophy; and corrective actions.ConclusionsMTM alerts have several opportunities for improvement related to human factors principles, resulting in MTM alert design recommendations. Enhancements to MTM alert design may increase the effectiveness of MTM delivery by community pharmacists and result in improved patient outcomes.

[1]  Sarah P. Slight,et al.  A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care , 2017, AMIA.

[2]  Stephanie A. Gernant,et al.  Variation in Medication Therapy Management Delivery: Implications for Health Care Policy , 2018, Journal of managed care & specialty pharmacy.

[3]  Michael Weiner,et al.  Systematic Heuristic Evaluation of Computerized Consultation Order Templates: Clinicians’ and Human Factors Engineers’ Perspectives , 2017, Journal of Medical Systems.

[4]  Monique W. M. Jaspers,et al.  A comparison of usability methods for testing interactive health technologies: Methodological aspects and empirical evidence , 2009, Int. J. Medical Informatics.

[5]  L. Strand,et al.  Pharmaceutical Care Practice: The Clinician's Guide , 2004 .

[6]  P. Harris,et al.  Research electronic data capture (REDCap) - A metadata-driven methodology and workflow process for providing translational research informatics support , 2009, J. Biomed. Informatics.

[7]  Alissa L. Russ,et al.  Computerized Medication Alerts and Prescriber Mental Models: Observing Routine Patient Care , 2009 .

[8]  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..

[9]  David W Bates,et al.  The Costs Associated With Adverse Drug Events Among Older Adults in the Ambulatory Setting , 2005, Medical care.

[10]  Titus K L Schleyer,et al.  Heuristic evaluation of clinical functions in four practice management systems: a pilot study. , 2007, Journal of the American Dental Association.

[11]  Hhs Centers for Medicare Medicare Services Medicare program; Medicare prescription drug benefit. Final rule. , 2005, Federal register.

[12]  Thomas B. Sheridan,et al.  Understanding Human Error and Aiding Human Diagnostic Behaviour in Nuclear Power Plants , 1981 .

[13]  Christopher D. Wickens,et al.  Dual-Task Performance Consequences of Imperfect Alerting Associated With a Cockpit Display of Traffic Information , 2007, Hum. Factors.

[14]  L. Strand,et al.  Pharmaceutical Care Practice , 1998 .

[15]  P. M. van de Ven,et al.  Clinical medication reviews in elderly patients with polypharmacy: a cross-sectional study on drug-related problems in the Netherlands , 2015, International Journal of Clinical Pharmacy.

[16]  Eda Bilici,et al.  The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review , 2018, Digital health.

[17]  J Brender,et al.  STARE-HI – Statement on Reporting of Evaluation Studies in Health Informatics , 2013, Applied Clinical Informatics.

[18]  Alissa L. Russ,et al.  Applying human factors principles to alert design increases efficiency and reduces prescribing errors in a scenario-based simulation. , 2014, Journal of the American Medical Informatics Association : JAMIA.

[19]  N Staggers,et al.  Usability Evaluation of An Electronic Medication Administration Record (eMAR) Application , 2011, Applied Clinical Informatics.

[20]  Christopher D. Wickens,et al.  False Alerts in Air Traffic Control Conflict Alerting System: Is There a “Cry Wolf” Effect? , 2009, Hum. Factors.

[21]  Medication Therapy Management Interventions in Outpatient Settings Executive Summary , 2022 .

[22]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[23]  Robyn Tamblyn,et al.  Enabling Medication Management Through Health Information Technology , 2011 .

[24]  Alissa L. Russ,et al.  The science of human factors: separating fact from fiction , 2013, BMJ quality & safety.

[25]  Linn Brandt,et al.  A systematic review of trials evaluating success factors of interventions with computerised clinical decision support , 2018, Implementation Science.

[26]  D. Bates,et al.  Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. , 2003, Archives of internal medicine.

[27]  S. Corman,et al.  The role of clinical decision support in pharmacist response to drug-interaction alerts. , 2015, Research in social & administrative pharmacy : RSAP.

[28]  Shobha Phansalkar,et al.  Evaluation of medication alerts in electronic health records for compliance with human factors principles. , 2014, Journal of the American Medical Informatics Association : JAMIA.

[29]  David W. Bates,et al.  Development and preliminary evidence for the validity of an instrument assessing implementation of human-factors principles in medication-related decision-support systems - I-MeDeSA , 2011, J. Am. Medical Informatics Assoc..

[30]  Neil Watson,et al.  Improving medication‐related clinical decision support , 2018, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

[31]  B. Bluml Definition of medication therapy management: development of professionwide consensus. , 2005, Journal of the American Pharmacists Association : JAPhA.

[32]  Diane L. Seger,et al.  A review of human factors principles for the design and implementation of medication safety alerts in clinical information systems , 2010, J. Am. Medical Informatics Assoc..

[33]  Leila C. Kahwati,et al.  Medication therapy management interventions in outpatient settings: a systematic review and meta-analysis. , 2015, JAMA internal medicine.

[34]  Michael S. Wogalter,et al.  Handbook of Warnings , 2006 .

[35]  P. Carayon,et al.  SEIPS 2.0: a human factors framework for studying and improving the work of healthcare professionals and patients , 2013, Ergonomics.

[36]  A. Burns Medication Therapy Management in community pharmacy practice: core elements of an MTM service (version 1.0). , 2005, Journal of the American Pharmacists Association : JAPhA.

[37]  K. Watkins,et al.  Effectiveness of implementation strategies for clinical guidelines to community pharmacy: a systematic review , 2015, Implementation Science.

[38]  Vimla L. Patel,et al.  Using usability heuristics to evaluate patient safety of medical devices , 2003, J. Biomed. Informatics.

[39]  Stéphanie Bernonville,et al.  Human Factors Based Recommendations for the Design of Medication Related Clinical Decision Support Systems (CDSS) , 2011, MIE.

[40]  A. Burns Medication therapy management in pharmacy practice: core elements of an MTM service model (version 2.0). , 2008, Journal of the American Pharmacists Association : JAPhA.

[41]  Elske Ammenwerth,et al.  Usability flaws of medication-related alerting functions: A systematic qualitative review , 2015, J. Biomed. Informatics.

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

[43]  V. Hasselblad,et al.  Effect of Clinical Decision-Support Systems , 2012, Annals of Internal Medicine.

[44]  Jakob Nielsen,et al.  Heuristic evaluation of user interfaces , 1990, CHI '90.