scholarly journals The Iranian Integrated Care Electronic Health Record

2021 ◽  
Author(s):  
Ehsan Bitaraf ◽  
Maryam Jafarpour ◽  
Vajiheh Jami ◽  
Fatemeh Sarani Rad
Keyword(s):  
Electronic Health Record ◽  
Integrated Care ◽  
Service Oriented Architecture ◽  
Point Of Care ◽  
Medical Knowledge ◽  
Healthcare Services ◽  
Health Record ◽  
Care Systems ◽  
Point Of Care Systems ◽  
Electronic Health

E-health plays a crucial role in E-government by proposing healthcare services based on information technology. However, the way to administer these services by using E-health solutions is one of the challenging issues. One of these significant challenges is how one integrates heterogeneous healthcare information of the different point of care systems. This paper introduces the Iranian integrated care electronic health record using the information gathered from several point-of-care systems in healthcare enterprises in Iran. This service-oriented architecture has a remarkable characteristic – its accessibility to medical knowledge and medical concepts through archetypes and ontology, respectively. The Ministry of Health and Medical Education of the Islamic Republic of Iran has designed and implemented this national architecture.

Implementation of Electronic Health Record (EHR) System in the Healthcare Industry

2016 ◽  
pp. 1001-1016
Author(s):  
Robert P Schumaker ◽  
Kavya P. Reganti
Keyword(s):  
Electronic Health Record ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Health Management ◽  
Healthcare Delivery ◽  
Healthcare Services ◽  
Health Record ◽  
Healthcare Industry ◽  
Efficient Delivery ◽  
Electronic Health

The purpose of this research is to demonstrate the efficiency of the Electronic Health Record (EHR) software that is adopted in the healthcare industry to provide better patient care. The authors examine the impact of EHRs on the efficient delivery of healthcare services. More specifically, they detail the origin of EHR, its significance in modern healthcare delivery along with the selection and implementation criteria for EHR software. They present a survey on the extent of adoption of EHR by clinicians. They also highlight the challenges and barriers faced by organizations in adopting EHR software such as cost, workflow impact and data security. Finally, the authors contemplate the future of EHR, its role in the implementation of health information exchange and its implementation in the cloud. They conclude that the implementation of EHR in the cloud is an important step towards better health management across the population with the end-goal of better health outcomes.

scholarly journals Care-paradigm shift promoting smoking cessation treatment among cancer center patients via a low-burden strategy, Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment

2019 ◽  
Author(s):  
Alex T Ramsey ◽  
Ami Chiu ◽  
Timothy Baker ◽  
Nina Smock ◽  
Jingling Chen ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Electronic Health Record ◽  
Paradigm Shift ◽  
Point Of Care ◽  
Cancer Center ◽  
Evidence Based ◽  
Health Record ◽  
Smoking Cessation Treatment ◽  
Cessation Treatment ◽  
Electronic Health

Abstract Tobacco smoking is an important risk factor for cancer incidence, an effect modifier for cancer treatment, and a negative prognostic factor for disease outcomes. Inadequate implementation of evidence-based smoking cessation treatment in cancer centers, a consequence of numerous patient-, provider-, and system-level barriers, contributes to tobacco-related morbidity and mortality. This study provides data for a paradigm shift from a frequently used specialist referral model to a point-of-care treatment model for tobacco use assessment and cessation treatment for outpatients at a large cancer center. The point-of-care model is enabled by a low-burden strategy, the Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment program, which was implemented in the cancer center clinics on June 2, 2018. Five-month pre- and post-implementation data from the electronic health record (EHR) were analyzed. The percentage of cancer patients assessed for tobacco use significantly increased from 48% to 90% (z = 126.57, p < .001), the percentage of smokers referred for cessation counseling increased from 0.72% to 1.91% (z = 3.81, p < .001), and the percentage of smokers with cessation medication significantly increased from 3% to 17% (z = 17.20, p < .001). EHR functionalities may significantly address barriers to point-of-care treatment delivery, improving its consistent implementation and thereby increasing access to and quality of smoking cessation care for cancer center patients.

scholarly journals When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record

2019 ◽  
pp. bmjqs-2018-008968 ◽  
Author(s):  
Ron C Li ◽  
Jason K Wang ◽  
Christopher Sharp ◽  
Jonathan H Chen
Keyword(s):  
Electronic Health Record ◽  
Point Of Care ◽  
Set Design ◽  
Health Record ◽  
Additional Item ◽  
Order Sets ◽  
Usage Patterns ◽  
Electronic Health ◽  
Order Set ◽  
A La Carte

BackgroundOrder sets are widely used tools in the electronic health record (EHR) for improving healthcare quality. However, there is limited insight into how well they facilitate clinician workflow. We assessed four indicators based on order set usage patterns in the EHR that reflect potential misalignment between order set design and clinician workflow needs.MethodsWe used data from the EHR on all orders of medication, laboratory, imaging and blood product items at an academic hospital and an itemset mining approach to extract orders that frequently co-occurred with order set use. We identified the following four indicators: infrequent ordering of order set items, rapid retraction of medication orders from order sets, additional a la carte ordering of items not included in order sets and a la carte ordering of items despite being listed in the order set.ResultsThere was significant variability in workflow alignment across the 11 762 order set items used in the 77 421 inpatient encounters from 2014 to 2017. The median ordering rate was 4.1% (IQR 0.6%–18%) and median medication retraction rate was 4% (IQR 2%–10%). 143 (5%) medications were significantly less likely while 68 (3%) were significantly more likely to be retracted than if the same medication was ordered a la carte. 214 (39%) order sets were associated with least one additional item frequently ordered a la carte and 243 (45%) order sets contained at least one item that was instead more often ordered a la carte.ConclusionOrder sets often do not align with what clinicians need at the point of care. Quantitative insights from EHRs may inform how order sets can be optimised to facilitate clinician workflow.

scholarly journals From screening to ascertainment of the primary outcome using electronic health records: Challenges in the STRIDE trial

2020 ◽  
Vol 17 (4) ◽  
pp. 346-350
Author(s):  
Denise Esserman
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Health Care Systems ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Health Records ◽  
Record Data ◽  
Care Systems ◽  
Electronic Health ◽  
Data Elements

Electronic health record data are a rich resource and can be utilized to answer a wealth of research questions. It is important when using electronic health record data in clinical trials that systems be put in place and vetted prior to enrollment to ensure data elements can be collected consistently across all health care systems. It is often overlooked how something conceptualized on paper (e.g. use of the electronic health record in a study) can be difficult to implement in practice. This article discusses some of the challenges in using electronic health records in the conduct of the STRIDE (Strategies to Reduce Injuries and Develop Confidence in Elders) trial, how we handled those challenges, and the lessons we learned for the conduct of future trials looking to employ the electronic health record.

scholarly journals An efficient approach for surveillance of childhood diabetes by type derived from electronic health record data: the SEARCH for Diabetes in Youth Study

2016 ◽  
Vol 23 (6) ◽  
pp. 1060-1067 ◽  
Author(s):  
Victor W Zhong ◽  
Jihad S Obeid ◽  
Jean B Craig ◽  
Emily R Pfaff ◽  
Joan Thomas ◽  
...  
Keyword(s):  
Health Care ◽  
Electronic Health Record ◽  
Health Care Systems ◽  
Diabetes Type ◽  
Health Record ◽  
Childhood Diabetes ◽  
Electronic Health Record Data ◽  
Efficient Approach ◽  
Care Systems ◽  
Electronic Health

Abstract Objective To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data. Materials and Methods Presumptive diabetes cases &lt;20 years of age from 2 large independent health care systems were identified as those having ≥1 of the 5 indicators in the past 3.5 years, including elevated HbA1c, elevated blood glucose, diabetes-related billing codes, patient problem list, and outpatient anti-diabetic medications. EHRs of all the presumptive cases were manually reviewed, and true diabetes status and diabetes type were determined. Algorithms for identifying diabetes cases overall and classifying diabetes type were either prespecified or derived from classification and regression tree analysis. Surveillance approach was developed based on the best algorithms identified. Results We developed a stepwise surveillance approach using billing code–based prespecified algorithms and targeted manual EHR review, which efficiently and accurately ascertained and classified diabetes cases by type, in both health care systems. The sensitivity and positive predictive values in both systems were approximately ≥90% for ascertaining diabetes cases overall and classifying cases with type 1 or type 2 diabetes. About 80% of the cases with “other” type were also correctly classified. This stepwise surveillance approach resulted in a &gt;70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods. Conclusion EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed.

scholarly journals Scalable Decision Support at the Point of Care: A Substitutable Electronic Health Record App for Monitoring Medication Adherence

2013 ◽  
Vol 2 (2) ◽  
pp. e13 ◽  
Author(s):  
William Bosl ◽  
Joshua Mandel ◽  
Magdalena Jonikas ◽  
Rachel Badovinac Ramoni ◽  
Isaac S Kohane ◽  
...  
Keyword(s):  
Decision Support ◽  
Medication Adherence ◽  
Electronic Health Record ◽  
Point Of Care ◽  
Health Record ◽  
Electronic Health

Implementation of Electronic Health Record (EHR) System in the Healthcare Industry

2014 ◽  
Vol 2 (2) ◽  
pp. 57-71 ◽  
Author(s):  
Robert P Schumaker ◽  
Kavya P. Reganti
Keyword(s):  
Electronic Health Record ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Health Management ◽  
Healthcare Delivery ◽  
Healthcare Services ◽  
Health Record ◽  
Healthcare Industry ◽  
Electronic Health ◽  
The Impact

The purpose of this research is to demonstrate the efficiency of the Electronic Health Record (EHR) software that is adopted in the healthcare industry to provide better patient care. The authors examine the impact of EHRs on the efficient delivery of healthcare services. More specifically, they detail the origin of EHR, its significance in modern healthcare delivery along with the selection and implementation criteria for EHR software. They present a survey on the extent of adoption of EHR by clinicians. They also highlight the challenges and barriers faced by organizations in adopting EHR software such as cost, workflow impact and data security. Finally, the authors contemplate the future of EHR, its role in the implementation of health information exchange and its implementation in the cloud. They conclude that the implementation of EHR in the cloud is an important step towards better health management across the population with the end-goal of better health outcomes.

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