Evidence map›Paper›PMID 33365212›Full record

ArticleCureus2020

Sick Leaves Pattern in a Tertiary Healthcare Facility in Saudi Arabia.

Kossay Elabd, Abdullah Alkhenizan, Abdullah Aldughaither

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2020. 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
0.5field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
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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

3 authors at 1 institution in 1 country.

Kossay ElabdFamily Medicine, King Faisal Specialist Hospital & Research Centre, Riyadh, SAU.
Abdullah AlkhenizanFamily Medicine and Polyclinics, King Faisal Specialist Hospital & Research Centre-Alfaisal University, Riyadh, SAU.
Abdullah AldughaitherPediatrics, King Faisal Specialist Hospital & Research Center, Riyadh, SAU.
King Faisal Specialist Hospital & Research Centre · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Frequent sick leaves in any healthcare organization is a critical problem that can undermine the patients' care through increasing the workload on other co-workers and costing the organization a lot of money. Methods This is a quantitative cross-sectional study looking at the frequency of sick leaves among employees of a large, tertiary healthcare facility in Riyadh. We randomly selected 474 employees, who were seen in family medicine clinics during a one-year period. We collected all the data retrospectively from their electronic medical records. Then we reviewed and analyzed all the data using SPSS software version 26.0 (IBM Corp., Armonk, NY). Results There was no difference in the sick leaves rate between males and females (p-value = 0.8618), but we saw a higher rate among younger employees (40 years old or less) compared to those 41 years or older (p-value <0.0001). We also investigated those who took four sick leaves or more during the period of the study, and we found that majority of them were nursing staff (31.71%), hospital assistances (24.39%) and housekeepers (14.63%). The commonest cause for taking sick leave in our study was viral upper respiratory tract infection (VURTI). Therefore, we studied the effect of influenza vaccine on the frequency of sick leaves and we found that those who took the vaccine were less likely to take a leave because of flu (p-value <0.0001, odds ratio 0.4067 with 95% CI: 0.2739-0.608). Conclusion Younger employees, nurses, hospital assistants and housekeepers are more likely to take sick leaves. Flu is the leading cause of sick leaves and influenza vaccine seemed to reduce its rate. In this study, we also discussed different methods that can be used by any healthcare organization to reduce the absence rate. Further studies are required to better manage the issue of excessive sick leaves.

Indexed as

employeesfrequencyhealthcare organisationsick leaves

Identifiers

PMID33365212
PMCPMC7748555
OpenAlexW3099281309

What OpenQuestion holds

Textmetadata
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.