Evidence map›Paper›PMID 35412476›Full record

SynthesisCritical care medicine2022

The Impact of Health Information Technology for Early Detection of Patient Deterioration on Mortality and Length of Stay in the Hospital Acute Care Setting: Systematic Review and Meta-Analysis.

Svetlana Herasevich, Kirill Lipatov, Yuliya Pinevich, Heidi Lindroth, Aysun Tekin, Vitaly Herasevich, Brian W Pickering, Amelia K Barwise

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Critical care medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
2.2field-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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 16 citations in OpenAlex.

  1. Pooled it
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  4. Article
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  8. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Svetlana HerasevichDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Kirill LipatovDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Yuliya PinevichDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Heidi LindrothDepartment of Nursing, Mayo Clinic, Rochester, MN.
Aysun TekinDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Vitaly HerasevichDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Brian W PickeringDepartment of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN.
Amelia K BarwiseDivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Mayo Clinic in Arizona · USMayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the impact of health information technology (HIT) for early detection of patient deterioration on patient mortality and length of stay (LOS) in acute care hospital settings. DATA SOURCES: We searched MEDLINE and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily, Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus from 1990 to January 19, 2021. STUDY SELECTION: We included studies that enrolled patients hospitalized on the floor, in the ICU, or admitted through the emergency department. Eligible studies compared HIT for early detection of patient deterioration with usual care and reported at least one end point of interest: hospital or ICU LOS or mortality at any time point. DATA EXTRACTION: Study data were abstracted by two independent reviewers using a standardized data extraction form. DATA SYNTHESIS: Random-effects meta-analysis was used to pool data. Among the 30 eligible studies, seven were randomized controlled trials (RCTs) and 23 were pre-post studies. Compared with usual care, HIT for early detection of patient deterioration was not associated with a reduction in hospital mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT interventions demonstrated a significant association with improved hospital mortality for the entire study cohort (odds ratio, 0.78 [95% CI, 0.70-0.87]) and reduced hospital LOS overall.

conclusionsHIT for early detection of patient deterioration in acute care settings was not significantly associated with improved mortality or LOS in the meta-analyses of RCTs. In the meta-analyses of pre-post studies, HIT was associated with improved hospital mortality and LOS; however, these results should be interpreted with caution. The differences in patient outcomes between the findings of the RCTs and pre-post studies may be secondary to confounding caused by unmeasured improvements in practice and workflow over time.

Indexed as

Critical CareMedical InformaticsHospital MortalityHospitalsHumansLength of Stay

Identifiers

PMID35412476
OpenAlexW4223510253

What OpenQuestion holds

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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.