scholarly journals Implementing Black Box Warnings (BBWs) in Health Information Systems

2012 ◽  
Vol 03 (01) ◽  
pp. 124-134 ◽  
Author(s):  
E. Yang ◽  
A. Daghstani ◽  
D. C. Kaelber ◽  
M. Ikezuagu
Keyword(s):  
Information Systems ◽  
Health Information ◽  
Improve Patient Safety ◽  
Health Information Systems ◽  
Clinical Decision ◽  
Black Box ◽  
Third Parties ◽  
Black Box Warnings ◽  
Types Of Information ◽  
Improve Patient

SummaryObjective: To develop a practical approach for implementing clinical decision support (CDS) for medication black box warnings (BBWs) into health information systems (HIS).Methods: We reviewed all existing medication BBWs and organized them into a taxonomy that identifies opportunities and challenges for implementing CDS for BBWs into HIS.Results: Of the over 400 BBWs that currently exist, they can be organized into 4 categories with 9 sub-categories based on the types of information contained in the BBWs, who should be notified, and potential actions to that could be taken by the person receiving the BBW. Informatics oriented categories and sub-categories of BBWs include – interactions (13%) (drug-drug (4%) and drug-diagnosis (9%)), testing (21%) (baseline (9%) and on-going (12%)), notifications (29%) (drug prescribers (7%), drug dispensers (2%), drug administrators (9%), patients (10%), and third parties (1%)), and non-actionable (37%). This categorization helps identify BBWs for which CDS can be easily implemented into HIS today (such as drug-drug interaction BBWs), those that cannot be easily implemented into HIS today (such as non-actionable BBWs), and those where advanced and/ or integrated HIS need to be in place to implement CDS for BBWs (such a drug dispensers BBWs).Conclusions: HIS have the potential to improve patient safety by implementing CDS for BBWs. A key to building CDS for BBWs into HIS is developing a taxonomy to serve as an organizing roadmap for implementation. The informatics oriented BBWs taxonomy presented here identified types of BBWs in which CDS can be implemented easily into HIS currently (a minority of the BBWs) and those types of BBWs where CDS cannot be easily implemented today (a majority of BBWs).

scholarly journals Towards an Integrative Cognitive-Socio-Technical Approach in Health Informatics: Analyzing Technology-Induced Error Involving Health Information Systems to Improve Patient Safety

2010 ◽  
Vol 4 (1) ◽  
pp. 181-187 ◽  
Author(s):  
E.M Borycki ◽  
A.W Kushniruk
Keyword(s):  
Information Systems ◽  
Health Information ◽  
Health Informatics ◽  
System Development ◽  
Improve Patient Safety ◽  
Health Information System ◽  
Health Information Systems ◽  
Technical Aspects ◽  
Information System Design ◽  
The Impact

The purpose of this paper is to argue for an integration of cognitive and socio-technical approaches to assessing the impact of health information systems. Historically, health informatics research has examined the cognitive and socio-technical aspects of health information systems separately. In this paper we argue that evaluations of health information systems should consider aspects related to cognition as well as socio-technical aspects including impact on workflow (i.e. an integrated view). Using examples from the study of technology-induced error in healthcare, we argue for the use of simulations to evaluate the cognitive-socio-technical impacts of health information technology [36]. Implications of clinical simulations and analysis of cognitive-social-technical impacts are discussed within the context of the system development life cycle to improve health information system design, implementation and evaluation.

Achieving Effective Health Information Systems

2009 ◽  
pp. 560-583
Author(s):  
Jim Warren ◽  
Karen Day ◽  
Martin Orr
Keyword(s):  
Information Systems ◽  
Health Information ◽  
Health Informatics ◽  
Clinical Decision Support Systems ◽  
Health Information Systems ◽  
Clinical Decision ◽  
Commodity Culture ◽  
Domain Specific ◽  
Quantitative And Qualitative Research ◽  
Hierarchy Of Evidence

In this chapter we aim to promote an understanding of the complexity of healthcare as a setting for information systems and how this complexity influences the achievement of successful implementations. We define health informatics and examine its role as an enabler in the delivery of healthcare. Then we look at the knowledge commodity culture of healthcare, with the gold standard of systematic reviews and its hierarchy of evidence. We examine the different forms of quantitative and qualitative research that are most commonly found in healthcare and how they influence the requirements for health information systems. We also examine some domain-specific issues that must be considered by health information systems developers, including those around clinical decision support systems and clinical classification and coding systems. We conclude with a discussion of the challenges that must be balanced by the health systems implementer in delivering robust systems that support evidence-based healthcare processes.

Improving Health Care Management Through the Use of Dynamic Simulation Modeling and Health Information Systems

2012 ◽  
Vol 5 (1) ◽  
pp. 19-36 ◽  
Author(s):  
Daniel Goldsmith ◽  
Michael Siegel
Keyword(s):  
Information Systems ◽  
System Dynamics ◽  
Health Information ◽  
Improve Patient Safety ◽  
Health Information Systems ◽  
Medical Decision ◽  
Effect Estimate ◽  
Dynamics Modeling ◽  
Medical Decision Support ◽  
Hospital Operations

To better understand the performance of hospital operations in response to IT-enabled improvement, this paper reports the results of a system dynamics model designed to improve core medical processes. Utilizing system dynamics modeling and emerging Health Information Systems (HIS) data, the authors demonstrate how current behavior within the hospital leads to a ‘stove-pipe’ effect, in which each functional group employs policies that are rational at the group level, but that lead to inefficiencies at the hospital level. The authors recommend management improvements in both materials and staff utilization to address the stove-pipe effect, estimate the resultant cost-saving, and report the results of an experiment conducted in the hospital to validate the approach. Results indicate that the major gains in health information systems use will accompany new information gathering capabilities, as these capabilities result in collections of data that can be used to greatly improve patient safety, hospital operations, and medical decision support.

scholarly journals Clinical Decision Support for Immunization Uptake and Use in Immunization Health Information Systems

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Lauren Shrader ◽  
Stuart Myerburg ◽  
Eric Larson
Keyword(s):  
United States ◽  
Decision Support ◽  
Information Systems ◽  
Health Information ◽  
Clinical Decision Support ◽  
Health Information Systems ◽  
Clinical Decision ◽  
The United States ◽  
Precise Integration ◽  
Vaccine Recommendations

Context: In the United States, immunization recommendations and their associated schedules are developed by the Advisory Committee on Immunization Practices (ACIP). To assist with the translation process and better harmonize the outcomes of existing clinical decision support tools, the Centers for Disease Control and Prevention (CDC) created clinical decision support for immunization (CDSi) resources for each set of ACIP recommendations. These resources are continually updated and refined as new vaccine recommendations and clarifications become available and will be available to health information systems for a coronavirus disease 2019 (COVID-19) vaccine when one becomes available for use in the United States. Objectives: To assess awareness of CDSi resources, whether CDSi resources were being used by immunization-related health information systems, and perceived impact of CDSi resources on stakeholders’ work.Design: Online surveys conducted from 2015–2019 including qualitative and quantitative questions.Participants: The main and technical contact from each of the 64 CDC-funded immunization information system (IIS) awardees, IIS vendors, and electronic health record vendors. Results: Awareness of at least one resource increased from 75% of respondents in 2015 to 100% in 2019. Use of at least one CDSi resource also increased from 47% in 2015 to 78% in 2019. About 80% or more of users of CDSi are somewhat or very highly satisfied with the resources and report a somewhat or very positive impact from using them. Conclusion: As awareness and use of CDSi resources increases, the likelihood that patients receive recommended immunizations at the right time will also increase. Rapid and precise integration of vaccine recommendations into health information systems will be particularly important when a COVID-19 vaccine becomes available to help facilitate vaccine implementation.

Current State of Dental Informatics in the Field of Health Information Systems: Systematic Review (Preprint)

2021 ◽  
Author(s):  
Benoit Ballester ◽  
Frédéric Bukiet ◽  
Jean-Charles Dufour
Keyword(s):  
Information Systems ◽  
Patient Care ◽  
Health Information ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Health Information Systems ◽  
Clinical Decision ◽  
Data Capture ◽  
Clinical Coding ◽  
Coding Systems

BACKGROUND Over the past 50 years, dental informatics has developed significantly in the field of health information systems. Accordingly, several studies have been conducted on standardized clinical coding systems, data capture, and clinical data reuse in dentistry. OBJECTIVE The primary objective of this systematic review was to summarize studies on standardized clinical coding systems and electronic dental record (EDR) data capture in dentistry. The secondary objective was to explore the practical implications of reusing EDR data in clinical decision support systems, quality measure development, and clinical research. METHODS Based on the definition of health information systems, we divided the literature search into 3 specific sub-searches: “standardized clinical coding systems,” “data capture,” and “reuse of routine patient care data.” PubMed and Web of Science were searched for peer-reviewed articles. The review was conducted following the PRISMA protocol. RESULTS A total of 43 articles were identified for inclusion in the review. Of these, 15 were related to “standardized clinical coding systems,” 15 to “data capture,” and 13 to “reuse of routine patient care data.” Articles related to standardized clinical coding systems focused on the design and/or development of proposed systems, on their evaluation and validation, on their adoption in academic settings, and on user perception. Articles related to data capture addressed the issue of data completeness, evaluated user interfaces and workflow integration, and proposed technical solutions. Finally, articles related to reuse of routine patient care data focused on clinical decision support systems centered on patient care, institutional or population-based health monitoring support systems, and clinical research. CONCLUSIONS While the development of health information systems, and especially standardized clinical coding systems, has led to significant progress in research and quality measures, the vast majority of reviewed articles were published in the US. Clinical decision support systems that reuse EDR data have been little studied. Likewise, few studies have examined the working environment of dental practitioners or the pedagogical value of using health information systems in dentistry.

Rationale and Design Considerations for a Semantic Mediator in Health Information Systems

1998 ◽  
Vol 37 (04/05) ◽  
pp. 518-526 ◽  
Author(s):  
D. Sauquet ◽  
M.-C. Jaulent ◽  
E. Zapletal ◽  
M. Lavril ◽  
P. Degoulet
Keyword(s):  
Information Systems ◽  
Software Engineering ◽  
Health Information ◽  
Rapid Development ◽  
Heterogeneous Systems ◽  
Health Information Systems ◽  
Semantic Interoperability ◽  
Point Of View ◽  
Current State ◽  
Engineering Environment

AbstractRapid development of community health information networks raises the issue of semantic interoperability between distributed and heterogeneous systems. Indeed, operational health information systems originate from heterogeneous teams of independent developers and have to cooperate in order to exchange data and services. A good cooperation is based on a good understanding of the messages exchanged between the systems. The main issue of semantic interoperability is to ensure that the exchange is not only possible but also meaningful. The main objective of this paper is to analyze semantic interoperability from a software engineering point of view. It describes the principles for the design of a semantic mediator (SM) in the framework of a distributed object manager (DOM). The mediator is itself a component that should allow the exchange of messages independently of languages and platforms. The functional architecture of such a SM is detailed. These principles have been partly applied in the context of the HEllOS object-oriented software engineering environment. The resulting service components are presented with their current state of achievement.

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