Evidence map›Paper›PMID 33087106›Full record

ArticleBMC health services research2020

Adoption rates of electronic health records in Turkish Hospitals and the relation with hospital sizes.

Ilker Kose, John Rayner, Suayip Birinci, Mustafa Mahir Ulgu, Ismayil Yilmaz, Seyma Guner, HIMSS Analytics Team, MoH Team

Abstract read
In one paragraph

Article in BMC health services research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. The Economic Impact of Obesity in Turkey: A Micro-Costing Analysis.ClinicoEconomics and outcomes research : CEOR · 2024
    Article
  6. Review
  7. Basic electronic health record (EHR) adoption inBMC health services research · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

8 authors.

Ilker KoseDepartment of Health System Engineering, Istanbul Medipol University, 34810, Istanbul, Turkey. ikose@medipol.edu.tr.ORCID http://orcid.org/0000-0002-5549-5579
John RaynerHIMSS Analytics for Europe and Latin America, Huddersfield, UK.
Suayip BirinciMinistry of Health, 06800, Ankara, Turkey.
Mustafa Mahir UlguMinistry of Health, 06800, Ankara, Turkey.
Ismayil YilmazMinistry of Health, 06800, Ankara, Turkey.
Seyma GunerIstanbul Medipol University, 34810, Istanbul, Turkey.
HIMSS Analytics Team
MoH Team

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNation-wide adoption of electronic health records (EHRs) in hospitals has become a Turkish policy priority in recognition of their benefits in maintaining the overall quality of clinical care. The electronic medical record maturity model (EMRAM) is a widely used survey tool developed by the Healthcare Information and Management Systems Society (HIMSS) to measure the rate of adoption of EHR functions in a hospital or a secondary care setting. Turkey completed many standardizations and infrastructural improvement initiatives in the health information technology (IT) domain during the first phase of the Health Transformation Program between 2003 and 2017. Like the United States of America (USA), the Turkish Ministry of Health (MoH) applied a bottom-up approach to adopting EHRs in state hospitals. This study aims to measure adoption rates and levels of EHR use in state hospitals in Turkey and investigate any relationship between adoption and use and hospital size.

methodsEMRAM surveys were completed by 600 (68.9%) state hospitals in Turkey between 2014 and 2017. The availability and prevalence of medical information systems and EHR functions and their use were measured. The association between hospital size and the availability/prevalence of EHR functions was also calculated.

resultsWe found that 63.1% of all hospitals in Turkey have at least basic EHR functions, and 36% have comprehensive EHR functions, which compares favourably to the results of Korean hospitals in 2017, but unfavorably to the results of US hospitals in 2015 and 2017. Our findings suggest that smaller hospitals are better at adopting certain EHR functions than larger hospitals.

conclusionMeasuring the overall adoption rates of EHR functions is an emerging approach and a beneficial tool for the strategic management of countries. This study is the first one covering all state hospitals in a country using EMRAM. The bottom-up approach to adopting EHR in state hospitals that was successful in the USA has also been found to be successful in Turkey. The results are used by the Turkish MoH to disseminate the nation-wide benefits of EHR functions.

Indexed as

Electronic Health RecordsHealth Facility SizeHospitals, StateHumansSurveys and QuestionnairesTurkeyCDSSElectronic health records; meaningful use; CPOE; PACSeMAREMRAMHIMSS

Identifiers

PMID33087106
PMCPMC7580017

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Registered trials

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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.