Electronic Health Record

In this study, we examined the implementation of an electronic health records (EHR) system in a small family practice clinic. We used three data collection instruments to evaluate user experience, work pattern changes, and organisational changes related to the implementation and use of the EHR system: (1) an EHR user survey, (2) interviews with key personnel involved in the EHR implementation project, and (3) a work analysis of clinic staff. A longitudinal design with two data-collection rounds was employed: data were collected prior to EHR implementation and after EHR implementation. Both quantitative and qualitative data were collected and analysed. Employees of the small clinic perceived few changes in their work after the implementation of the EHR system, except for increased dependency on computers and a small increase in perceived workload. The work analysis showed a dramatic increase in the amount of time spent on computers by the various job categories. The EHR implementatio...

Turkey's National Health Information System (NHIS) aims to provide a nation-wide infrastructure for sharing the Electronic Health Records (EHRs). The current implementation supports the transfer of EHRs, called the "Transmission Schema" instances from the Family Medicine Information Systems (FMIS) and the Hospital Information Systems (HIS) to the NHIS servers at the Ministry of Health (MoH). During the localization of the

As of June 2011, the adoption of electronic prescription (EP) systems will be mandatory in Portugal. New Primary Care Units (PCU) since 2008, and increasingly, existing ones, are using a full Electronic Health Record (EHR), which is regarded as a ...

The history of medical ethics demonstrates how different values have been upheld at different times and how ethical frameworks have developed: how certain arguments have risen to prominence, while others have fallen into disrepute. The central values of the classical Hippocratic ethics were nonmaleficence (Do no harm!), beneficence and confidentiality. After World War II, medical ethics started to advocate patient autonomy in the guise of informed consent. However, over the last 20 years, there has been growing dissatisfaction with the individual rights-centred ethical framework.

Within clinical ethics, it has been noted that an obligation to respect the patient’s self-determination has worked against beneficence and trust and has thus done a great deal of damage to the doctor–patient relationship. The opinion that the rights-based ethics is not in the best interest of the patient and that patient care is best served by a
limited form of paternalism has been gathering support. The central moral concern of public health ethics is to specify the conditions that warrant paternatilistic interventions that override individual autonomy to prevent people from adopting unhealthy behaviours.

Likewise, in the context of research ethics, it has been argued that principles of individual autonomy and informed consent and privacy can seriously hamper medical research that aims to further the common good. It has become clear that prior, free, specifically informed and explicit consent may not be an achievable ideal in emergent research fields, such as biobank research. The need to develop new ethical frameworks focusing on more collective values, such as reciprocity, mutuality, solidarity, citizenry and universality, has been advocated. In the last two decades, there has been talk of the ‘communitarian turn’ in ethics.

The basic difference between liberal and communitarian ethical frameworks lies in the fact that liberalism claims that the individual is more important than the society in which he ⁄ she lives, whereas communitarianism regards society as more important
than the individual. Liberalism stresses rights, communitarianism the common good. In the traditional communitarian model, individual rights and interests are subordinate to the common good; however, the more recent neo-communitarian approach tries to balance individual rights with community interests.

Here, I will discuss the view that although autonomy and beneficence seem at times to be in conflict, there is no reason to see one or the other as predominant. A wider understanding of autonomy is crucial for understanding how to avoid a division between autonomy and beneficence.

Background & Purpose: The healthcare (HC) sector, globally, invests huge amounts of funds in an attempt to attain international quality standards but the structure and content barriers make the electronic patient records (EPRs) and electronic health record (EHRs) fall short. This study seeks to illuminate theories and practices of HC knowledge management (KM) so this process can facilitate the narrowing of EPR and EHR gap, that ultimately will cascade to improving the HC quality which is therefore assessable by the quality management system (QMS) model. Design/methodology/approach: This research is theoretical in nature. It examines relevant theories and reviews literature on (1) HC quality assessment and tools, (2) HC KM, (3) EPRs and EHRs, (4) knowledge representation and (5) the Symantec web. This study passed through phases of research. In the first phase, EPR and EHR were researched to analyze why they fall short in facilitating the HC’s initiative to improve quality. Next, HC KM was studied to analyze and establish a viable link between (1) EPR and EHR and (2) KM. Technologies and techniques like the Symantec web and Knowledge Representation were also analyzed to make the facilitation of HC KM possible.
Findings: The findings indicate that, by this paper contributing a conceptual, integrative, and strategically viable HC KM facilitator model for EPRs and EHRs, this paper answers its research question that HC KM can facilitate EPR and EHR to improve HC quality.
Research limitations/implications, Originality & Value: This research provides an integrated and a conceptual model grounded in theory. This model needs to be tested in a real or simulated HC environments. This paper is one of the first studies to solve the barriers of EPR and EHR using KM.
Keywords: Electronic Patient Record, Electronic Health Record, Electronic Medical Record, Healthcare Knowledge Management, Knowledge Representation, Symantec Web, Quality Management System, Knowledge Management facilitator model.

Database is a core component the Electronic Health Record (EHR) system, and creating a datamodel for that database is challenging due to the EHR system’s special nature. Because of complexity, spatial, sparseness, interrelation, temporal, heterogeneity, and fast evolution of EHR data, modeling its database is complex process. This paper tried to build dynamic, complete and stable data model for EHR database. There are a little work and standards in this aspect because of its difficulty.
We will use object relational modeling approach and entity attribute value with classes and relationships to build the model. This design facilitates and enhances the operations of data mining and decision support which is integrating component of an EHR system.

Integrating clinical research data entry with patient care data entry is a challenging issue. At the G. Pompidou European Hospital (HEGP), pulmonary function testing reports are captured twice, first in the Electronic Health Record (EHR) and then in Clinical Data Management System (CDMS). Statuary requirements and data standards are different for EHR and clinical research. So, this work has for object to suggest an integration solution between EHR and CDMS. This object can be divided in two steps: the first consists in modeling clinical research workflow in a university hospital environment in order to investigate the possible use of her in this context. The second step consist in conceiving, implementing and assessing an integration solution between EHR and CDMS taking into consideration standardization efforts and statuary requirements. The REUSE demonstrator showed that automatic transfer of data reduces errors risk, and enables to preserve collected data during clinical trials in the EHR that may be useful. We proposed the integration profile “Retrieve and Integrate Form for Data Capture”. Beyond syntactic interoperability, a perspective is to implement this integration profile in the REUSE demonstrator in order to address the issue of semantic interoperability between both domains.

Many healthcare leaders find themselves overwhelmed with data, but lack the information they  need  to  make  right  decisions.  Knowledge Discovery  in  Databases  (KDD)  can  help organizations  turn  their  data  into  information. Organizations  that  take  advantage  of  KDD techniques  will  find  that  they  can  lower  the healthcare  costs  while  improving  healthcare
quality  by  using  fast  and  better clinical  decision making. In this paper,  a review study is done on existing  data  mining  and  knowledge  discovery techniques, applications  and process models that are  applicable  to  healthcare  environments.  The
challenges  for  applying  data  mining  techniques in healthcare environment will also be discussed.

A Big Data Platform (BDA) with Hadoop/MapReduce technologies distributed over HBase (key-value NoSQL database storage)
and generate hospitalization metadata was established for testing functionality and performance. Performance tests retrieved
results from simulated patient records with Apache tools in Hadoop’s ecosystem. At optimized iteration, Hadoop distributed file
system (HDFS) ingestion with HBase exhibited sustained database integrity over hundreds of iterations; however, to complete its
bulk loading via MapReduce to HBase required a month. The framework over generated HBase data files took a week and a month
for one billion (10TB) and three billion (30TB), respectively. Apache Spark and Apache Drill showed high performance. However,
inconsistencies of MapReduce limited the capacity to generate data. Hospital system based on a patient encounter-centric database
was very difficult to establish because data profiles have complex relationships. Recommendations for key-value storage should be
considered for healthcare when analyzing large volumes of data over simplified clinical event models.

Numerous advantages are derived from the electronic health record (EHR). Though achieving such advantages depends on its architecture, at present no unique understanding of the architecture dimensions and specifications is available. Therefore, the aim of the present study is a systematic review of architecture perception of the electronic health record. The authors searched the literature in Science Direct, Scopus, PubMed and Proudest Databases (2000 to Jun 2015). Data extraction was done by 2 reviewers on content, structure, content/structure relationship, confidentiality and security of the EHR. Subsequent to refining the 87 retrieved studies, 25 studies were finally included in the study. In the studies and paradigms so far proposed for the EHR, a unique comprehensive architecture model from the viewpoint of research criteria has not been investigated and it has been considered only from some dimensions. Hence, we provide a new definition of the EHR architecture.

A radical change in technical approach is needed to achieve electronic health records suitable to support an engineered system of healthcare. This chapter suggests a redefinition of interoperable health information. It provides examples of how to break the electronic ...

Objectives: To select best medical informatics research works published in 2013 on electronic health record (EHR) adoption, design, and impact, from the perspective of human factors and organizational issues (HFOI).
Methods: We selected 2,764 papers by querying PubMed (Mesh and TIAB) as well as using a manual search. Papers were evaluated based on pre-defined exclusion and inclusion criteria from their title, keywords, and abstract to select 15 candidate best papers, finally reviewed by 4 external reviewers using a standard evaluation grid.
Results: Five papers were selected as best papers to illustrate how human factors approaches can improve EHR adoption and design. Among other contributions, these works: (i) make use of the observational and analysis methodologies of social and cognitive sciences to understand clinicians’ attitudes towards EHRs, EHR use patterns, and impact on care processes, workflows, information exchange, and coordination of care; (ii) take into account macro- (environmental) and meso- (organizational) level factors to analyze EHR adoption or lack thereof; (iii) highlight the need for qualitative studies to analyze the unexpected side effects of EHRs on cognitive and work processes as well as the persistent use of paper.
Conclusion: Selected papers tend to demonstrate that HFOI approaches and methodologies are essential to bridge the gap between EHR systems and end users, and to reduce regularly reported adoption failures and unexpected consequences.

Health transformation is the head of the electronic
transformation which occurs in many areas in parallel with the
advances in technology and the increase  ofthe internet usage.
The personal health data which is accepted in the personal data
in legal adjustments has become to be kept under the name of
Electronic Health Record (EHR) after the electronic
transformation. Although EHR has the advantages of the
accessibility regardless of time and location, hazards such as
privacy invasion would occur because of the unauthorized access.
Personal health data, EHR and privacy in the area of the studies
in social science, laws and regulations remain only as definitions.
Moreover, in many areas, the discrepancy in the meanings can be
seen. It is significant to construct the definitions in this area in a
way such that they can express a common meaning. This paper
focuses on the improvements about the technological
infrastructure of privacy and security in light of the definitions,
the necessity of the consent management to protect the rights of
the individuals on their health data and it surveys the studies in
the area of information technology.

PurposeData mining on electronic health records (EHRs) has emerged as a promising complementary method for post-marketing drug safety surveillance. The EU-ADR project, funded by the European Commission, is developing techniques that allow mining of EHRs for adverse drug events across different countries in Europe. Since mining on all possible events was considered to unduly increase the number of spurious signals, we wanted to create a ranked list of high-priority events.Data mining on electronic health records (EHRs) has emerged as a promising complementary method for post-marketing drug safety surveillance. The EU-ADR project, funded by the European Commission, is developing techniques that allow mining of EHRs for adverse drug events across different countries in Europe. Since mining on all possible events was considered to unduly increase the number of spurious signals, we wanted to create a ranked list of high-priority events.MethodsScientific literature, medical textbooks, and websites of regulatory agencies were reviewed to create a preliminary list of events that are deemed important in pharmacovigilance. Two teams of pharmacovigilance experts independently rated each event on five criteria: ‘trigger for drug withdrawal’, ‘trigger for black box warning’, ‘leading to emergency department visit or hospital admission’, ‘probability of event to be drug-related’, and ‘likelihood of death’. In case of disagreement, a consensus score was obtained. Ordinal scales between 0 and 3 were used for rating the criteria, and an overall score was computed to rank the events.Scientific literature, medical textbooks, and websites of regulatory agencies were reviewed to create a preliminary list of events that are deemed important in pharmacovigilance. Two teams of pharmacovigilance experts independently rated each event on five criteria: ‘trigger for drug withdrawal’, ‘trigger for black box warning’, ‘leading to emergency department visit or hospital admission’, ‘probability of event to be drug-related’, and ‘likelihood of death’. In case of disagreement, a consensus score was obtained. Ordinal scales between 0 and 3 were used for rating the criteria, and an overall score was computed to rank the events.ResultsAn initial list comprising 23 adverse events was identified. After rating all the events and calculation of overall scores, a ranked list was established. The top-ranking events were: cutaneous bullous eruptions, acute renal failure, anaphylactic shock, acute myocardial infarction, and rhabdomyolysis.An initial list comprising 23 adverse events was identified. After rating all the events and calculation of overall scores, a ranked list was established. The top-ranking events were: cutaneous bullous eruptions, acute renal failure, anaphylactic shock, acute myocardial infarction, and rhabdomyolysis.ConclusionsA ranked list of 23 adverse drug events judged as important in pharmacovigilance was created to permit focused data mining. The list will need to be updated periodically as knowledge on drug safety evolves and new issues in drug safety arise. Copyright © 2009 John Wiley & Sons, Ltd.A ranked list of 23 adverse drug events judged as important in pharmacovigilance was created to permit focused data mining. The list will need to be updated periodically as knowledge on drug safety evolves and new issues in drug safety arise. Copyright © 2009 John Wiley & Sons, Ltd.

There is currently a strong focus worldwide on the potential of large-scale Electronic Health Record systems to cut costs and improve patient outcomes through increased e-ciency. A number of countries are developing nationwide EHR systems to aggregate services currently pro- vided by isolated Electronic Medical Record databases. However, such aggregation introduces new risks for patient privacy and data security, both

With the deployments of Electronic Health Records (EHR), interoperability testing in healthcare is becoming crucial. EHR enables access to prior diagnostic information in order to assist in health decisions. It is a virtual system that results from the cooperation of several heterogeneous distributed systems. Interoperability between peers is therefore essential. Achieving interoperability requires various types of testing. Implementations need to be tested using software that simulates communication partners, and that provides test data and test plans. In this paper we describe a software that is used to test systems that are involved in sharing medical images within the EHR. Our software is used as part of the Integrating the Healthcare Enterprise (IHE) testing process to test the Cross Enterprise Document Sharing for imaging (XDS-I) integration profile. We describe its architecture and functionalities; we also expose the challenges encountered and discuss the elected design solut...