Evidence map›Paper›PMID 36821535›Full record

ArticlePloS one2023

RETRACTED: Analysis the patients' careflows using process mining.

Abdel-Hamed Mohamed Rashed, Noha E El-Attar, Diaa Salama Abdelminaam, Mohamed Abdelfatah

RetractedErratum issuedAbstract readRetracted Publication
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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.

  1. Article
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  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Abdel-Hamed Mohamed RashedInformation System Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha City, Egypt.ORCID 0000-0001-8312-9878
Noha E El-AttarInformation System Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha City, Egypt.
Diaa Salama AbdelminaamInformation System Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha City, Egypt.
Mohamed AbdelfatahInformation System Department, Faculty of Computers and Artificial Intelligence, Benha University, Benha City, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, The Egyptian health sector whether it is public or private; utilizes emerging technologies such as data mining, business intelligence, Internet of Things (IoT), among many others to enhance the service and to deal with increasing costs and growing pressures. However, process mining has not yet been used in the Egyptian organizations, whereas the process mining can enable the domain experts in many fields to achieve a realistic view of the problems that are currently happening in the undertaken field, and thus solve it. This paper presents application of the process mining techniques in the healthcare field to obtain meaningful insights about its careflows, e.g., to discover typical paths followed by certain patient groups. Also, to analyze careflows that have a high degree of dynamic and complexity. The proposed methodology starts by the preprocess step on the event logs to eliminate outliers and clean the event log. And then apply a set of the popular discovery miner algorithms to discover the process model. Then careflows processes are analyzed from three main perspectives: the control-flow perspective, the performance perspective and, the organizational perspective. That contributes with many insights for the domain experts to improve the existing careflows. Through evaluating the simplicity metric of extracted models; the paper suggested a method to quantify the simplicity metric. The paper used a dataset from a cardiac surgery unit in an Egyptian hospital. The results of the applied process mining techniques provide the hospital managers a real analysis and insights to make the patient journey easier.

Indexed as

AlgorithmsHospitalsData MiningHealth OccupationsHumansOrganizations

Identifiers

PMID36821535
PMCPMC9949667

What OpenQuestion holds

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LicenceCC BY
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.