Evidence map›Paper›PMID 31311532›Full record

ArticleBMC medical informatics and decision making2019

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

Margie E Snyder, Heather Jaynes, Stephanie A Gernant, Julie DiIulio, Laura G Militello, William R Doucette, Omolola A Adeoye, Alissa L Russ

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 10 citations in OpenAlex.

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  4. Observational
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 1 country.

Margie E SnyderDepartment of Pharmacy Practice, Purdue University College of Pharmacy, 640 Eskenazi Ave, Indianapolis, IN, 46220, USA. snyderme@purdue.edu.ORCID 0000-0003-1482-8020
Heather JaynesDepartment of Pharmacy Practice, Purdue University College of Pharmacy, 640 Eskenazi Ave, Indianapolis, IN, 46220, USA.
Stephanie A GernantDepartment of Pharmacy Practice, University of Connecticut School of Pharmacy, Storrs, CT, USA.
Julie DiIulioApplied Decision Science, LLC, Cincinnati, OH, USA.
Laura G MilitelloApplied Decision Science, LLC, Cincinnati, OH, USA.
William R DoucetteDivision of Health Services Research, Department of Pharmacy Practice and Science, University of Iowa College of Pharmacy, Iowa City, IA, USA.
Omolola A AdeoyeDepartment of Pharmacy Practice, Purdue University College of Pharmacy, 640 Eskenazi Ave, Indianapolis, IN, 46220, USA.
Alissa L RussDepartment of Pharmacy Practice, Purdue University College of Pharmacy, 640 Eskenazi Ave, Indianapolis, IN, 46220, USA.
University of Indianapolis · USApplied Decision Science (United States) · USRegenstrief Institute · USUniversity of Connecticut · USUniversity of Iowa · US

Funding

Indiana Clinical and Translational Sciences InstituteTL1TR001107 · NCATS · INDIANA UNIVERSITY INDIANAPOLIS · PI DENNE, SCOTT C., SHEKHAR, ANANTHA · 2013 to 2017
$2.0M
AHRQ HHS R21 HS025005NCATS NIH HHS TL1 TR001107
6 · The paper itself

Abstract

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.

Indexed as

Community Pharmacy ServicesDecision Support Systems, ClinicalHeuristicsMedical Order Entry SystemsMedication Therapy ManagementHumansCommunity pharmacy servicesDecision support systems, clinicalErgonomicsMedication therapy management

Identifiers

PMID31311532
PMCPMC6636156
OpenAlexW2957090205

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.