Evidence map›Paper›PMID 28692434›Full record

ArticleComputers, informatics, nursing : CIN2017

Assessing Intensity of Nursing Care Needs Using Electronically Available Data.

Elaine L Larson, Bevin Cohen, Jianfang Liu, Philip Zachariah, David Yao, Jingjing Shang

Abstract read
In one paragraph

Article in Computers, informatics, nursing : CIN, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

6 authors.

Elaine L LarsonAuthor Affiliations: School of Nursing (Drs Larson, Liu, and Shang and Ms Cohen) and Mailman School of Public Health (Dr Larson), College of Physicians and Surgeons (Dr Zachariah), and Department of Industrial Engineering and Operations Research (Dr Yao), Columbia University.
Bevin Cohen
Jianfang Liu
Philip Zachariah
David Yao
Jingjing Shang

Funding

Nursing Intensity of Patient Care Needs and Rates of Healthcare-associated Infections (NIC-HAI)R01HS024915 · AHRQ · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI LARSON, ELAINE LUCILLE · 2016 to 2018
$1.4M
AHRQ HHS R01 HS024915
6 · The paper itself

Abstract

Although previous research has confirmed that nurse staffing affects patient outcomes, some potentially important factors have not been accounted for in tools to assess relationships between staffing and outcomes. The aim of this project was to develop and test a Nursing Intensity of Care Index using electronically available data from 152 072 patient discharges from three hospitals. Initially, 1765 procedure codes were reviewed; 69 were confirmed as directly increasing nursing workload by at least 15 minutes per shift. Two research staff independently reviewed a random sample of 5 patient days to assess interrater reliability with complete scoring agreement. To assess face validity, eight nurse clinician experts reviewed factors included in the Nursing Intensity of Care Index to assess the accuracy of the nursing time estimates in the tool. To examine concurrent validity, Nursing Intensity of Care Index scores for a random sample of 28 patients from four clinical units were compared with assessments made by a unit-based clinical nurse (low/medium/high intensity) for the same patients on the same day with a Spearman correlation of 0.94. In preliminary testing, data for the Nursing Intensity of Care Index, which accurately reflect nursing care intensity, can be obtained electronically in real time. The next steps will be a discrete-event simulation model and large-scale field trials.

Indexed as

Nursing AssessmentWorkloadElectronic Health RecordsHumansNursing Staff, HospitalPersonnel Staffing and SchedulingTime Factors

Identifiers

PMID28692434
PMCPMC5722656

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.