Evidence map›Paper›PMID 27938401›Full record

ArticleBMC medical informatics and decision making2016

Testing modes of computerized sepsis alert notification delivery systems.

Mikhail A Dziadzko, Andrew M Harrison, Ing C Tiong, Brian W Pickering, Pablo Moreno Franco, Vitaly Herasevich

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

6 authors.

Mikhail A DziadzkoDepartment of Anesthesiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
Andrew M HarrisonMedical Scientist Training Program, Mayo Clinic, Rochester, Minnesota, USA.
Ing C TiongDepartment of Information Technology, Mayo Clinic, Rochester, Minnesota, USA.
Brian W PickeringDepartment of Anesthesiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
Pablo Moreno FrancoDivision of Critical Care Medicine, Mayo Clinic, Jacksonville, Florida, USA.
Vitaly HerasevichDepartment of Anesthesiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA. herasevich.vitaly@mayo.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe number of electronic health record (EHR)-based notifications continues to rise. One common method to deliver urgent and emergent notifications (alerts) is paging. Despite of wide presence of smartphones, the use of these devices for secure alerting remains a relatively new phenomenon.

methodsWe compared three methods of alert delivery (pagers, EHR-based notifications, and smartphones) to determine the best method of urgent alerting in the intensive care unit (ICU) setting. ICU clinicians received randomized automated sepsis alerts: pager, EHR-based notification, or a personal smartphone/tablet device. Time to notification acknowledgement, fatigue measurement, and user preferences (structured survey) were studied.

resultsTwenty three clinicians participated over the course of 3 months. A total of 48 randomized sepsis alerts were generated for 46 unique patients. Although all alerts were acknowledged, the primary outcome was confounded by technical failure of alert delivery in the smartphone/tablet arm. Median time to acknowledgment of urgent alerts was shorter by pager (102 mins) than EHR (169 mins). Secondary outcomes of fatigue measurement and user preference did not demonstrate significant differences between these notification delivery study arms.

conclusionsTechnical failure of secure smartphone/tablet alert delivery presents a barrier to testing the optimal method of urgent alert delivery in the ICU setting. Results from fatigue evaluation and user preferences for alert delivery methods were similar in all arms. Further investigation is thus necessary to understand human and technical barriers to implementation of commonplace modern technology in the hospital setting.

Indexed as

SepsisComputers, HandheldDecision Support Systems, ClinicalElectronic Health RecordsHospital Information SystemsHumansSmartphoneAlert fatigueDecision support systemMethods of alert deliveryNotificationSepsis

Identifiers

PMID27938401
PMCPMC5148853

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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.