Evidence map›Paper›PMID 34758494›Full record

ArticleApplied clinical informatics2021

Workflow Automation for a Virtual Hypertension Management Program.

William J Gordon, Alexander J Blood, Kira Chaney, Eugene Clark, Corey Glynn, Remlee Green, John St Laurent, Charlotte Mailly, Marian McPartlin, Shawn Murphy and 7 more

Abstract read
In one paragraph

Article in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

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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

17 authors.

William J GordonDepartment of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
Alexander J BloodDepartment of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
Kira ChaneyMass General Brigham, Boston, Massachusetts, United States.
Eugene ClarkMass General Brigham, Boston, Massachusetts, United States.
Corey GlynnMass General Brigham, Boston, Massachusetts, United States.
Remlee GreenMass General Brigham, Boston, Massachusetts, United States.
John St LaurentMass General Brigham, Boston, Massachusetts, United States.
Charlotte MaillyMass General Brigham, Boston, Massachusetts, United States.
Marian McPartlinMass General Brigham, Boston, Massachusetts, United States.
Shawn MurphyHarvard Medical School, Boston, Massachusetts, United States.
Hunter NicholsMass General Brigham, Boston, Massachusetts, United States.
Michael OatesMass General Brigham, Boston, Massachusetts, United States.
Samantha SubramaniamMass General Brigham, Boston, Massachusetts, United States.
Matthew VarugheeseMass General Brigham, Boston, Massachusetts, United States.
Kavishwar WagholikarHarvard Medical School, Boston, Massachusetts, United States.
Samuel Aronson *Mass General Brigham, Boston, Massachusetts, United States.
Benjamin M Scirica *Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesHypertension is a modifiable risk factor for numerous comorbidities and treating hypertension can greatly improve health outcomes. We sought to increase the efficiency of a virtual hypertension management program through workflow automation processes.

methodsWe developed a customer relationship management (CRM) solution at our institution for the purpose of improving processes and workflow for a virtual hypertension management program and describe here the development, implementation, and initial experience of this CRM system.

resultsNotable system features include task automation, patient data capture, multi-channel communication, integration with our electronic health record (EHR), and device integration (for blood pressure cuffs). In the five stages of our program (intake and eligibility screening, enrollment, device configuration/setup, medication titration, and maintenance), we describe some of the key process improvements and workflow automations that are enabled using our CRM platform, like automatic reminders to capture blood pressure data and present these data to our clinical team when ready for clinical decision making. We also describe key limitations of CRM, like balancing out-of-the-box functionality with development flexibility. Among our first group of referred patients, 76% (39/51) preferred email as their communication method, 26/51 (51%) were able to enroll electronically, and 63% of those enrolled (32/51) were able to transmit blood pressure data without phone support.

conclusionA CRM platform could improve clinical processes through multiple pathways, including workflow automation, multi-channel communication, and device integration. Future work will examine the operational improvements of this health information technology solution as well as assess clinical outcomes.

Indexed as

HypertensionMedical InformaticsAutomationElectronic Health RecordsHumansWorkflow

Identifiers

PMID34758494
PMCPMC8580734

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LicenceCC BY-NC-ND
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Registered trials

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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.