Evidence map›Paper›PMID 35959196›Full record

ArticleDigital health

Digital health transformation in Saudi Arabia: A cross-sectional analysis using Healthcare Information and Management Systems Society' digital health indicators.

Nouf Al-Kahtani, Sumaya Alruwaie, Bnan Mohammed Al-Zahrani, Rahaf Ali Abumadini, Afnan Aljaafary, Bayan Hariri, Khalid Alissa, Zahra Alakrawi, Arwa Alumran

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Nouf Al-KahtaniHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Sumaya AlruwaieHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Bnan Mohammed Al-ZahraniHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Rahaf Ali AbumadiniHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Afnan AljaafaryHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Bayan HaririHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Khalid AlissaDepartment of Networks and Communication, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Zahra AlakrawiHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
Arwa AlumranHealth Information Management and Technology, College of Public Health, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.ORCID https://orcid.org/0000-0001-6454-3678

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The digital revolution has had a huge impact on healthcare around the world. Digital technology could dramatically improve the accuracy of diagnosis, treatment, health outcomes, efficiency of care, and workflow of healthcare operations. Using health information technology will bring major improvements in patient outcomes. Purpose: This study aims to measure the readiness for digital health transformation at different hospitals in the Eastern Province, Saudi Arabia in relation to Saudi Vision 2030 based on the four dimensions adopted by the Healthcare Information and Management Systems Society: person-enabled health, predictive analytics, governance and workforce, and interoperability. Methods: The study was conducted with a cross-sectional design using data collected through an online questionnaire from 10 healthcare settings, the questionnaire consists of the four digital health indicators. The survey was developed by Healthcare Information and Management Systems Society for the purpose of assessing the level of digital maturity in healthcare settings. Results: Ten healthcare facilities in the Eastern Province, both private and governmental, were included in the study. The highest total scores for digital health transformation were reported in private healthcare facilities (median score for private facilities = 77, public facilities = 71). The 'governance and workforce' was the most implemented dimension among the healthcare facilities in the study (median = 80), while the dimension that was least frequently implemented was predictive analytics (median score = 70). In addition, tertiary hospitals scored the least in digital transformation readiness (median = 74) compared to primary and secondary healthcare facilities in the study. Conclusion: The results of the study show that private healthcare facilities scored higher in digital health transformation indicators. These results will be useful for promoting policymakers' understanding of the level of digital health transformation in the Eastern Province and for the creation of a strategic action plan.

Indexed as

Data ScienceHealth Information InteroperabilityHealth information systemsHealth Status Indicators

Identifiers

PMID35959196
PMCPMC9358341

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.