Evidence map›Paper›PMID 27307266›Full record

ArticleJournal of medical systems2016

Information Needs Assessment for a Medicine Ward-Focused Rounding Dashboard.

Christopher A Aakre, Rajeev Chaudhry, Brian W Pickering, Vitaly Herasevich

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 3 institutions in 1 country.

Christopher A AakreDivision of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, 200 First St SW, Rochester, MN, USA. aakre.christopher@mayo.edu.
Rajeev ChaudhryDivision of Primary Care Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Brian W PickeringDepartment of Anesthesiology, Mayo Clinic, Rochester, MN, USA.
Vitaly HerasevichDepartment of Anesthesiology, Mayo Clinic, Rochester, MN, USA.
WinnMed · USMayo Clinic · USMayo Clinic in Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify the routine information needs of inpatient clinicians on the general wards for the development of an electronic dashboard. Survey of internal medicine and subspecialty clinicians from March 2014-July 2014 at Saint Marys Hospital in Rochester, Minnesota. An information needs assessment was generated from all unique data elements extracted from all handoff and rounding tools used by clinicians in our ICUs and general wards. An electronic survey was distributed to 104 inpatient medical providers. 89 unique data elements were identified from currently utilized handoff and rounding instruments. All data elements were present in our multipurpose ICU-based dashboard. 42 of 104 (40 %) surveys were returned. Data elements important (50/89, 56 %) and unimportant (24/89, 27 %) for routine use were identified. No significant differences in data element ranking were observed between supervisory and nonsupervisory roles. The routine information needs of general ward clinicians are a subset of data elements used routinely by ICU clinicians. Our findings suggest an electronic dashboard could be adapted from the critical care setting to the general wards with minimal modification.

Indexed as

User-Computer InterfaceHospital AdministrationHumansInformation SystemsIntensive Care UnitsNeeds AssessmentPatient HandoffElectronic dashboardHandoffHealth information technologyNeeds assessmentRounding

Identifiers

PMID27307266
OpenAlexW2442858351

What OpenQuestion holds

Textmetadata
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.