The Adoption Level of Electronic Health Records in Turkish Hospitals and the Relation with Hospital Sizes

Abstract Background: Considering the benefits of using electronic health records (EHR) for maintaining the overall quality of clinical care, the nationwide adoption of EHR in hospitals has become a policy priority. The electronic medical record maturity model (EMRAM) is one of the most popular survey tools developed by the Healthcare Information and Management Systems Society (HIMSS) that measures the level of adoption for EHR functions in a hospital or a secondary care setting. Turkey has accomplished many standardizations and infrastructural studies in the health IT domain as a part of the first phase of the Health Transformation Program between 2003 and 2017. The Turkish MoH applied a bottom-up approach to adopting EHR in public hospitals, as the USA did. This study aims to measure the EHR adoption level of public hospitals in Turkey and criticize the relation between adoption and hospital size. Methods: EMRAM surveys were completed by 600 (68.9%) public hospitals of Turkey between 2014 and 2017. The availability and prevalence of medical information systems and EHR functions 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 is better than the results of Korean hospitals of 2017 but still lower than the USA hospitals of 2015 and 2017. Our findings suggest that small hospitals are better than larger hospitals at adopting certain EHR functions. Conclusion: Measuring the overall adoption level 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 public hospitals in a country by using EMRAM. It can be suggested that using a bottom-up approach as applied by the USA on adopting EHR in public hospital gives successful results also in Turkey. The results are used by MoH of Turkey to disseminate the benefits of EHR functions overall in the country.

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The Adoption Level of Electronic Health Records in Turkish Hospitals and the Relation with Hospital Sizes

10.21203/rs.2.17869/v1 ◽

2019 ◽

Author(s):

Ilker Kose ◽

John Rayner ◽

Suayip Birinci ◽

Mustafa Mahir Ulgu ◽

Ismayil Yilmaz ◽

...

Keyword(s):

Electronic Health Records ◽

Medical Information ◽

Clinical Care ◽

Public Hospitals ◽

Maturity Model ◽

Health Records ◽

Hospital Size ◽

Electronic Health ◽

Adoption Level ◽

Better Than

Abstract Background Considering the benefits of using electronic health records (EHR) for maintaining the overall quality of clinical care, the nationwide adoption of EHR in hospitals has become a policy priority. The electronic medical record maturity model (EMRAM) is one of the most popular survey tools developed by the Healthcare Information and Management Systems Society (HIMSS) that measures the level of adoption for EHR functions in a hospital or a secondary care setting. This study aims to measure the digital capacity of public hospitals in Turkey and criticize the relation between adoption and hospital size. Methods EMRAM surveys were completed by 600 (68.9%) public hospitals of Turkey between 2014 and 2017. The availability and prevalence of medical information systems and EHR functions 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 is better than the results of Korean hospitals of 2017 but still lower than the USA hospitals of 2015 (1)[1]and 2017. Our findings suggest that small hospitals are better than larger hospitals at adopting certain EHR functions. Conclusion Measuring the overall adoption level 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 public hospitals in a country by using EMRAM. The results are used by MoH of Turkey to disseminate the benefits of EHR functions overall in the country.

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Adoption Rates of Electronic Health Records in Turkish Hospitals and the Relation with Hospital Sizes

10.21203/rs.2.17869/v3 ◽

2020 ◽

Author(s):

Ilker Kose ◽

John Rayner ◽

Suayip Birinci ◽

Mustafa Mahir Ulgu ◽

Ismayil Yilmaz ◽

...

Keyword(s):

Electronic Health Records ◽

Medical Information ◽

Clinical Care ◽

The United States ◽

Health Records ◽

Bottom Up ◽

Hospital Size ◽

Survey Tool ◽

State Hospitals ◽

Electronic Health

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.

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

BMC Health Services Research ◽

10.1186/s12913-020-05767-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Ilker Kose ◽

◽

John Rayner ◽

Suayip Birinci ◽

Mustafa Mahir Ulgu ◽

...

Keyword(s):

Electronic Health Records ◽

Medical Information ◽

Clinical Care ◽

The United States ◽

Health Records ◽

Bottom Up ◽

Hospital Size ◽

Survey Tool ◽

State Hospitals ◽

Electronic Health

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.

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Adoption Rates of Electronic Health Records in Turkish Hospitals and the Relation with Hospital Sizes

10.21203/rs.2.17869/v4 ◽

2020 ◽

Author(s):

Ilker Kose ◽

John Rayner ◽

Suayip Birinci ◽

Mustafa Mahir Ulgu ◽

Ismayil Yilmaz ◽

...

Keyword(s):

Electronic Health Records ◽

Medical Information ◽

Clinical Care ◽

The United States ◽

Health Records ◽

Bottom Up ◽

Hospital Size ◽

Survey Tool ◽

State Hospitals ◽

Electronic Health

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.

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A comparative quantitative study of utilizing artificial intelligence on electronic health records in the USA and China during 2008–2017

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-018-0692-9 ◽

2018 ◽

Vol 18 (S5) ◽

Cited By ~ 14

Author(s):

Xieling Chen ◽

Ziqing Liu ◽

Li Wei ◽

Jun Yan ◽

Tianyong Hao ◽

...

Keyword(s):

Artificial Intelligence ◽

Electronic Health Records ◽

Quantitative Study ◽

Health Records ◽

The Usa ◽

Electronic Health

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Adoption of Electronic Health Care Records

Information Systems and Technologies for Enhancing Health and Social Care ◽

10.4018/978-1-4666-3667-5.ch010 ◽

2013 ◽

pp. 148-165

Author(s):

Jerald D. Hatton ◽

Thomas M. Schmidt ◽

Jonatan Jelen

Keyword(s):

Electronic Health Records ◽

New Technologies ◽

Phenomenological Study ◽

Cost Effective ◽

Research Quality ◽

Control Cost ◽

Health Records ◽

The Usa ◽

Electronic Health ◽

Support Of Research

Political, economic, and safety concerns have militated for the adoption of Electronic Health Records by physicians in the United States, but current rates of adoption have failed to penetrate the 50% level. A qualitative phenomenological study of practicing physicians reveals stumbling blocks to adoption. Maintaining a physician’s perceived sense of control of the process is key. Electronic Health Records (EHRs) are critical to the support of research, quality control, cost reduction, and implementation of new technologies and methods in healthcare. Progress in the USA towards adoption of standardized EHRs has been halting. The authors discuss the results of a phenomenological study of physicians and draw conclusions that will assist all stakeholders in building a more consistent, comprehensive, and cost-effective healthcare system. When attempting to persuade physicians to migrate to an EMR-based solution, a strong focus on the control that physicians will have should be emphasized. The transition to an EHR system is eased by clearly articulating early in the process the potential benefits and the degree of control physicians can have in the use of the applications.

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Determinants and extent of weight recording in UK primary care: an analysis of 5 million adults’ electronic health records from 2000 to 2017

BMC Medicine ◽

10.1186/s12916-019-1446-y ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 5

Author(s):

B. D. Nicholson ◽

P. Aveyard ◽

C. R. Bankhead ◽

W. Hamilton ◽

F. D. R. Hobbs ◽

...

Keyword(s):

Primary Care ◽

Electronic Health Records ◽

Negative Binomial ◽

Cox Regression ◽

Clinical Care ◽

Negative Binomial Regression ◽

Routine Activity ◽

Health Records ◽

Clinical Events ◽

Electronic Health

Abstract Background Excess weight and unexpected weight loss are associated with multiple disease states and increased morbidity and mortality, but weight measurement is not routine in many primary care settings. The aim of this study was to characterise who has had their weight recorded in UK primary care, how frequently, by whom and in relation to which clinical events, symptoms and diagnoses. Methods A longitudinal analysis of UK primary care electronic health records (EHR) data from 2000 to 2017. Descriptive statistics were used to summarise weight recording in terms of patient sociodemographic characteristics, health professional encounters, clinical events, symptoms and diagnoses. Negative binomial regression was used to model the likelihood of having a weight record each year, and Cox regression to the likelihood of repeated weight recording. Results A total of 14,049,871 weight records were identified in the EHR of 4,918,746 patients during the study period, representing 26,998,591 person-years of observation. Around a third of patients had a weight record each year. Forty-nine percent of weight records were repeated within a year with an average time to a repeat weight record of 1.92 years. Weight records were most often taken by nursing staff (38–42%) and GPs (37–39%) as part of a routine clinical care, such as chronic disease reviews (16%), medication reviews (6–8%) and health checks (6–7%), or were associated with consultations for contraception (5–8%), respiratory disease (5%) and obesity (1%). Patient characteristics independently associated with an increased likelihood of weight recording were as follows: female sex, younger and older adults, non-drinkers, ex-smokers, low or high BMI, being more deprived, diagnosed with a greater number of comorbidities and consulting more frequently. The effect of policy-level incentives to record weight did not appear to be sustained after they were removed. Conclusion Weight recording is not a routine activity in UK primary care. It is recorded for around a third of patients each year and is repeated on average every 2 years for these patients. It is more common in females with higher BMI and in those with comorbidity. Incentive payments and their removal appear to be associated with increases and decreases in weight recording.

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Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19

10.1101/2020.08.11.20172809 ◽

2020 ◽

Cited By ~ 1

Author(s):

Akhil Vaid ◽

Suraj K Jaladanki ◽

Jie Xu ◽

Shelly Teng ◽

Arvind Kumar ◽

...

Keyword(s):

Electronic Health Records ◽

Large Datasets ◽

Mortality Prediction ◽

Patient Privacy ◽

Local Data ◽

Health Records ◽

Electronic Health ◽

Mlp Model ◽

Combined Data ◽

Better Than

Machine learning (ML) models require large datasets which may be siloed across different healthcare institutions. Using federated learning, a ML technique that avoids locally aggregating raw clinical data across multiple institutions, we predict mortality within seven days in hospitalized COVID-19 patients. Patient data was collected from Electronic Health Records (EHRs) from five hospitals within the Mount Sinai Health System (MSHS). Logistic Regression with L1 regularization (LASSO) and Multilayer Perceptron (MLP) models were trained using local data at each site, a pooled model with combined data from all five sites, and a federated model that only shared parameters with a central aggregator. Both the federated LASSO and federated MLP models performed better than their local model counterparts at four hospitals. The federated MLP model also outperformed the federated LASSO model at all hospitals. Federated learning shows promise in COVID-19 EHR data to develop robust predictive models without compromising patient privacy.

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The Digitization of Patient Care: A Review of the Effects of Electronic Health Records on Health Care Quality and Utilization

Annual Review of Public Health ◽

10.1146/annurev-publhealth-040218-044206 ◽

2019 ◽

Vol 40 (1) ◽

pp. 487-500 ◽

Cited By ~ 22

Author(s):

Hilal Atasoy ◽

Brad N. Greenwood ◽

Jeffrey Scott McCullough

Keyword(s):

Electronic Health Records ◽

Health Informatics ◽

Health Care Quality ◽

Clinical Care ◽

Academic Research ◽

Care Quality ◽

Health Records ◽

Policy Practice ◽

Electronic Health ◽

Cost Implications

Electronic health records (EHRs) adoption has become nearly universal during the past decade. Academic research into the effects of EHRs has examined factors influencing adoption, clinical care benefits, financial and cost implications, and more. We provide an interdisciplinary overview and synthesis of this literature, drawing on work in public and population health, informatics, medicine, management information systems, and economics. We then chart paths forward for policy, practice, and research.

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