A secure interoperable method for electronic health records exchange on cross platform blockchain network.

An Electronic Health Record (EHR) store essential and sensitive patient's medical information. Since health information is highly confidential data, it should be accessible with the consent of the patient. Blockchain based EHR management system offers improvised privacy and patient-centric approach.

Multi-Ideology, Multiclass Online Extremism Dataset, and Its Evaluation Using Machine Learning.

Social media platforms play a key role in fostering the outreach of extremism by influencing the views, opinions, and perceptions of people. These platforms are increasingly exploited by extremist elements for spreading propaganda, radicalizing, and recruiting youth. Hence, research on extremism detection on social media platforms is essential to curb its influence and ill effects.

Clinician Perceptions of Timing and Presentation of Drug-Drug Interaction Alerts.

Objective: Alert presentation of clinical decision support recommendations is a common method for providing information; however, many alerts are overridden suggesting presentation design improvements can be made. This study attempts to assess pediatric prescriber information needs for drug-drug interactions (DDIs) alerts and to evaluate the optimal presentation timing and presentation in the medication ordering process.

Methods: Six case scenarios presented interactions between medications used in pediatric specialties of general medicine, infectious disease, cardiology, and neurology.

Community pharmacists' and residents' decision making and unmet information needs when completing comprehensive medication reviews.

Objective: To (1) characterize community pharmacists' and community pharmacy residents' decision making and unmet information needs when conducting comprehensive medication reviews (CMRs) as part of medication therapy management and (2) explore any differences between community pharmacists and community pharmacy residents in CMR decision making and unmet information needs.

Design: Thirty-to 60-minute semistructured interviews framed using a clinical decision-making model (CDMM) were conducted with community pharmacists and residents.

Setting And Participants: Participants were recruited from practice-based research networks and researchers' professional networks.

High-priority and low-priority drug-drug interactions in different international electronic health record systems: A comparative study.

Objectives: To investigate whether alert warnings for high-priority and low-priority drug-drug interactions (DDIs) were present in five international electronic health record (EHR) systems, to compare and contrast the severity level assigned to them, and to establish the proportion of alerts that were overridden.

Methods: We conducted a comparative, retrospective, multinational study using a convenience sample of 5 EHRs from the U.S.

Lost in Translation: No Effect of a High-Profile Publication on the Concomitant Use of Interacting Drugs.

We sought to assess whether a high-profile publication that demonstrated serious clinical consequences of specific drug-drug interactions (DDIs) reduced the concomitant use of those drugs. We conducted a quasi-experimental study using 2000-2008 prescription claims from a commercial health insurer to examine trends in the dispensing of the interacting drug pairs (angiotensin-converting enzyme inhibitors[ACEI] + potassium-sparing diuretic, digoxin + clarithromycin, and glyburide + cotrimoxazole) and control drug pairs previously reported in a top-tier general medicine journal. We examined prepublication and postpublication dispensing trends using Poisson regression.

Analysis of variations in the display of drug names in computerized prescriber-order-entry systems.

Purpose: The variations in how drug names are displayed in computerized prescriber-order-entry (CPOE) systems were analyzed to determine their contribution to potential medication errors.

Methods: A diverse set of 10 inpatient and outpatient CPOE system vendors and self-developed CPOE systems in 6 U.S.

Recommendations for Providers on Person-Centered Approaches to Assess and Improve Medication Adherence.

Medication non-adherence is a significant clinical challenge that adversely affects psychosocial factors, costs, and outcomes that are shared by patients, family members, providers, healthcare systems, payers, and society. Patient-centered care (i.e.

Development of a Brief Multicultural Version of the Test of Mobile Phone Dependence (TMDbrief) Questionnaire.

Unlabelled: The Test of Mobile Phone Dependence (TMD) questionnaire (Chóliz, 2012) evaluates the main features of mobile phone dependence: tolerance, abstinence syndrome, impaired impulse control, associated problems, excessive use, etc.

Objective: The objective of this study was to develop a multicultural version of the TMD (TMDbrief) adapted to suit the novel communication tools of smartphones.

Procedure: In this study, the TMD was completed by 2,028 young respondents in six distinct world regions: Southern Europe, Northwest Europe, South-America, Mesoamerica, Pakistan, and India.

Recommendations to improve the usability of drug-drug interaction clinical decision support alerts.

Objective: To establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts.

Materials And Methods: A DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs.

Impact of incorporating pharmacy claims data into electronic medication reconciliation.

Purpose: The potential value of adding pharmacy claims data to the medication history in the electronic health record (EHR) to improve the accuracy of medication reconciliation was studied.

Methods: Three medication history sources were used for this evaluation: a gold-standard preadmission medication list (PAML) created by reviewing all available medication history information, an EHR-generated PAML, and pharmacy claims data. The study population consisted of patients from the Partners Medication Reconciliation Study with medication history information available from all three medication history sources.

Patient-centered priorities for improving medication management and adherence.

Objective: The Centers for Education and Research on Therapeutics convened a workshop to examine the scientific evidence on medication adherence interventions from the patient-centered perspective and to explore the potential of patient-centered medication management to improve chronic disease treatment.

Methods: Patients, providers, researchers, and other stakeholders (N = 28) identified and prioritized ideas for future research and practice. We analyzed stakeholder voting on priorities and reviewed themes in workshop discussions.

Patient-centered interventions to improve medication management and adherence: a qualitative review of research findings.

Objective: Patient-centered approaches to improving medication adherence hold promise, but evidence of their effectiveness is unclear. This review reports the current state of scientific research around interventions to improve medication management through four patient-centered domains: shared decision-making, methods to enhance effective prescribing, systems for eliciting and acting on patient feedback about medication use and treatment goals, and medication-taking behavior.

Methods: We reviewed literature on interventions that fell into these domains and were published between January 2007 and May 2013.

Evaluation of a Korean version of a tool for assessing the incorporation of human factors into a medication-related decision support system: the I-MeDeSA.

Objective: The Instrument for Evaluating Human-Factor Principles in Medication-Related Decision Support Alerts (I-MeDeSA) was developed recently in the US with a view towards improving considerations of human-factor principles when designing alerts for clinical decision support (CDS) systems. This study evaluated the generalizability of this tool, in cooperation with its authors, across cultures by applying it to a Korean system. We also examined opportunities to promote user acceptance of the system.

Evaluation of medication alerts in electronic health records for compliance with human factors principles.

Introduction: Increasing the adoption of electronic health records (EHRs) with integrated clinical decision support (CDS) is a key initiative of the current US healthcare administration. High over-ride rates of CDS alerts strongly limit these potential benefits. As a result, EHR designers aspire to improve alert design to achieve better acceptance rates.

Human factors considerations for contraindication alerts.

Alert fatigue is a ubiquitous problem in clinical decision support systems. Several remedies to alert fatigue have been proposed including improving the specificity of alerts and compliance with human factors principles. Human factors principles that are relevant for drug safety alerting have been identified and operationalized for drug-drug interactions (DDIs), resulting in a previously developed and validated quantitative instrument.

Criteria for assessing high-priority drug-drug interactions for clinical decision support in electronic health records.

Background: High override rates for drug-drug interaction (DDI) alerts in electronic health records (EHRs) result in the potentially dangerous consequence of providers ignoring clinically significant alerts. Lack of uniformity of criteria for determining the severity or validity of these interactions often results in discrepancies in how these are evaluated. The purpose of this study was to identify a set of criteria for assessing DDIs that should be used for the generation of clinical decision support (CDS) alerts in EHRs.

Design of decision support interventions for medication prescribing.

Objective: Describe optimal design attributes of clinical decision support (CDS) interventions for medication prescribing, emphasizing perceptual, cognitive and functional characteristics that improve human-computer interaction (HCI) and patient safety.

Methods: Findings from published reports on success, failures and lessons learned during implementation of CDS systems were reviewed and interpreted with regard to HCI and software usability principles. We then formulated design recommendations for CDS alerts that would reduce unnecessary workflow interruptions and allow clinicians to make informed decisions quickly, accurately and without extraneous cognitive and interactive effort.

Drug-drug interactions that should be non-interruptive in order to reduce alert fatigue in electronic health records.

Objective: Alert fatigue represents a common problem associated with the use of clinical decision support systems in electronic health records (EHR). This problem is particularly profound with drug-drug interaction (DDI) alerts for which studies have reported override rates of approximately 90%. The objective of this study is to report consensus-based recommendations of an expert panel on DDI that can be safely made non-interruptive to the provider's workflow, in EHR, in an attempt to reduce alert fatigue.

High-priority drug-drug interactions for use in electronic health records.

Objective: To develop a set of high-severity, clinically significant drug-drug interactions (DDIs) for use in electronic health records (EHRs).

Methods: A panel of experts was convened with the goal of identifying critical DDIs that should be used for generating medication-related decision support alerts in all EHRs. Panelists included medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use.

Preventability of adverse drug events involving multiple drugs using publicly available clinical decision support tools.

Purpose: The results of a retrospective evaluation of the frequency and preventability of adverse drug events (ADEs) involving multiple drugs among hospital inpatients are reported.

Methods: Data collected in a previous cohort study of 180 actual ADEs and 552 potential ADEs (PADEs) at six community hospitals in Massachusetts were analyzed to determine the frequency and types of multiple-drug ADEs and the extent to which the ADEs might have been prevented using publicly available clinical decision-support (CDS) knowledge bases. None of the hospitals had a computerized prescriber-order-entry system at the time of data collection (January 2005-August 2006).

Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation.

Clinical decision support systems--interactive computer systems that help doctors make clinical choices--can reduce errors in drug prescribing by offering real-time alerts about possible adverse reactions. But physicians and other users often suffer "alert fatigue" caused by excessive numbers of warnings about items such as potentially dangerous drug interactions. As a result, they may pay less attention to or even ignore some vital alerts, thus limiting these systems' effectiveness.