Evidence map›Paper›PMID 31332535›Full record

SynthesisJournal of medical systems2019

Decision-Making based on Big Data Analytics for People Management in Healthcare Organizations.

Maria José Sousa, António Miguel Pesqueira, Carlos Lemos, Miguel Sousa, Álvaro Rocha

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of medical systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 4 pooled it
–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

15 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Review
  8. Digital Twins in Industry 5.0.Research (Washington, D.C.) · 2023
    Article
  9. Article
  10. Article
  11. Observational
  12. Review
  13. Analytics and Lean Health Care to Address Nurse Care Management Challenges for Inpatients in Emerging Economies.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2021
    Article
  14. Review
  15. 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

5 authors.

Maria José SousaISCTE-Instituto Universitário de Lisboa, Lisbon, Portugal. mjdcsousa@gmail.com.ORCID http://orcid.org/0000-0001-8633-4199
António Miguel PesqueiraTakeda, Zurich, Switzerland.
Carlos LemosFaculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal.
Miguel SousaUniversity of Essex, Colchester, UK.
Álvaro RochaUniversity of Coimbra, Coimbra, Portugal.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Big data analytics enables large-scale data sets integration, supporting people management decisions, and cost-effectiveness evaluation of healthcare organizations. The purpose of this article is to address the decision-making process based on big data analytics in Healthcare organizations, to identify main big data analytics able to support healthcare leaders' decisions and to present some strategies to enhance efficiency along the healthcare value chain. Our research was based on a systematic review. During the literature review, we will be presenting as well the different applications of big data in the healthcare context and a proposal for a predictive model for people management processes. Our research underlines the importance big data analytics can add to the efficiency of the decision-making process, through a predictive model and real-time analytics, assisting in the collection, management, and integration of data in healthcare organizations.

Indexed as

Big DataData Interpretation, StatisticalDecision MakingCost-Benefit AnalysisData ScienceDelivery of Health CareForecastingHumansInformation SystemsKnowledge ManagementPersonnel ManagementQuality Indicators, Health CareAnalyticsBig dataBusiness intelligence; Prisma methodologyDecision-makingHealthcare organizationsLeadersOutcomes

Identifiers

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.