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

Abstract

Background Nation-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. Methods EMRAM 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. Results We 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. Conclusion Measuring 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.

Synthesizing Dimensions of Digital Maturity in Hospitals: Systematic Review

“…The systems and services indicator, which examines the digital systems implemented to support clinical care, is the most prominent indicator within this dimension. The systems identified as being important to digital maturity include electronic medical records, clinical decision support systems, e-prescribing, PACS [ 11 , 35 , 36 ], orders and results management, asset and resource optimization systems [ 22 ], and remote and assistive care systems [ 1 , 21 ]. The IT infrastructure indicator focuses on infrastructure [ 21 , 37 ] and architecture [ 1 ] designed and installed to support the aforementioned systems and services [ 12 ].…”

Understanding How to Improve the Use of Clinical Coordination Mechanisms between Primary and Secondary Care Doctors: Clues from Catalonia

“…Firstly, the negative association of the semi-integrated management model seems to be related to an unequal distribution of coordination efforts (common objectives, resources and coordination mechanisms between levels) among the PC centres of the territory, which focuses on the PC centres managed by the same entity as the hospital and excludes the rest [ 40 , 41 ]. Secondly, in areas with high technology hospitals, the greater size and technological level of the hospital may hinder coordination with the PC centres of its own area (in terms of time and available resources) [ 42 ], since these hospitals also cover complex cases from other areas.…”

The Impact of Health Information Technology on Hospital Performance: A Systematic Integrative Literature Review

“…According to affordance theory, the actual use of HIT functions and their affordances enable medical professionals to achieve their goals and tasks [18]. Therefore, HIT use is an important variable to consider [5] [6] [15] [19] [20] [21] [22]. However, in our review only ten studies (19.2%) define the use of HIT by explicitly measuring the use rate of HIT, for example by using the technology acceptance model (TAM) or the unified theory of acceptance and use of technology (UTAUT) [23].…”

“…Also, HIT consists of many subsystems, which may lead to varying influence on performance metrics. We found four reasons for these variations: hospitals implemented subsystems in a different sequence [5], hospitals implemented subsystems with a different strategy (bottom up versus top down or big bag versus phased) [20] [39], hospitals implemented subsystems to support different type of illness (chronic or acute) [5] and hospitals implemented different combinations of subsystems [5] [32] [35] [41].…”