scholarly journals Review of Reported Clinical Information System Adverse Events in US Food and Drug Administration Databases

2011 ◽  
Vol 02 (01) ◽  
pp. 63-74 ◽  
Author(s):  
R.B. Myers ◽  
S.L. Jones ◽  
D.F. Sittig
Keyword(s):  
Adverse Events ◽  
Medical Devices ◽  
Clinical Information System ◽  
Clinical Information ◽  
Clinical Information Systems ◽  
Implementation Processes ◽  
The Us ◽  
Potential Risks ◽  
Us Fda ◽  
Incorrect Data

Summary Background: The US FDA has been collecting information on medical devices involved in significant adverse advents since 1984. These reports have been used by researchers to advise clinicians on potential risks and complications of using these devices. Objective: Research adverse events related to the use of Clinical Information Systems (CIS) as reported in FDA databases. Methods: Three large, national, adverse event medical device databases were examined for reports pertaining to CIS. Results: One hundred and twenty unique reports (from over 1.4 million reports) were found, representing 32 manufacturers. The manifestations of these adverse events included: missing or incorrect data, data displayed for the wrong patient, chaos during system downtime and system unavailable for use. Analysis of these reports illustrated events associated with system design, implementation, use, and support. Conclusion: The identified causes can be used by manufacturers to improve their products and by clinical facilities and providers to adjust their workflow and implementation processes appropriately. The small number of reports found indicates a need to raise awareness regarding publicly available tools for documenting problems with CIS and for additional reporting and dialog between manufacturers, organizations, and users.

Prioritizing the Risk Factors Influencing the Success of Clinical Information System Projects

2008 ◽  
Vol 47 (03) ◽  
pp. 251-259 ◽  
Author(s):  
C. Sicotte ◽  
M. Jaana ◽  
D. Girouard ◽  
G. Paré
Keyword(s):  
Risk Factors ◽  
Information System ◽  
Information Systems ◽  
Information Technologies ◽  
Clinical Information System ◽  
Clinical Information ◽  
Clinical Work ◽  
Perceived Usefulness ◽  
Clinical Information Systems ◽  
Factors Influencing

Summary Objective: The aim of this study is to gain a better understanding of the risk factors influencing the success of clinical information system projects. Methods: This study addresses this issue by first reviewing the extant literature on information technology project risks, and second conducting a Delphi survey among 21 experts highly involved in clinical information system projects in Québec, Canada, a region where government have invested heavily in health information technologies in recent years. Results: Twenty-three risk factors were identified. The absence of a project champion was the factor that experts felt most deserves their attention. Lack of commitment from upper management was ranked second. Our panel of experts also confirmed the importance of a variable that has been extensively studied in information systems, namely, perceived usefulness that ranked third. Respondents ranked project ambiguity fourth. The fifth-ranked risk was associated with poor alignment between the clinical information systems’ characteristics and the organization of clinical work. The large majority of risk factors associated with the technology itself were considered less important. This finding supports the idea that technology-associated factors rarely figure among the main reasons for a project failure. Conclusions: In addition to providing a comprehensive list of risk factors and their relative importance, the study presents a major contribution by unifying the literature on information systems and medical infor - matics. Our checklist provides a basis for further research that may help practitioners identify the effective countermeasures for mitigating risks associated with the implementation of clinical information systems.

scholarly journals Current Challenges and Opportunities for Better Integration of Human Factors Research with Development of Clinical Information Systems

2009 ◽  
Vol 18 (01) ◽  
pp. 48-58 ◽  
Author(s):  
J. J. Saleem ◽  
A. L. Russ ◽  
P. Sanderson ◽  
T. R. Johnson ◽  
J. Zhang ◽  
...  
Keyword(s):  
Information Systems ◽  
Human Factors ◽  
User Satisfaction ◽  
Clinical Decision Making ◽  
Clinical Information System ◽  
Healthcare Delivery ◽  
Clinical Information ◽  
Lessons Learned ◽  
Clinical Information Systems ◽  
Human Factors Research

Summary Objectives Clinical information system (CIS) developers and implementers have begun to look to other scientific disciplines for new methods, tools, and techniques to help them better understand clinicians and their organizational structures, clinical work environments, capabilities of clinical information and communications technology, and the way these structures and processes interact. The goal of this article is to help CIS researchers, developers, implementers, and evaluators better understand the methods, tools, techniques, and literature of the field of human factors. Methods We developed a framework that explains how six key human factors topics relate to the design, implementation, and evaluation of CISs. Results Using this framework we discuss the following six topics: 1) informatics and patient safety; 2) user interface design and evaluation; 3) workflow and task analysis; 4) clinical decision making and decision support; 5) distributed cognition; and 6) mental workload and situation awareness. Conclusions Integrating the methods, tools, and lessons learned from each of these six areas of human factors research early in CIS design and incorporating them iteratively during development can improve user performance, user satisfaction, and integration into clinical workflow. Ultimately, this approach will improve clinical information systems and healthcare delivery.

Model-based Design of Clinical Information Systems

2008 ◽  
Vol 47 (05) ◽  
pp. 399-408 ◽  
Author(s):  
J. Werner ◽  
Y. Lee ◽  
B. Malin ◽  
A. Ledeczi ◽  
J. Mathe
Keyword(s):  
Information System ◽  
Information Systems ◽  
Service Oriented Architecture ◽  
Clinical Information System ◽  
Clinical Information ◽  
Security And Privacy ◽  
Clinical Information Systems ◽  
Great Promise ◽  
Model Based ◽  
Business Process Execution

Summary Objective: The goal of this research is to provide a framework to enable the model-based development, simulation, and deployment of clinical information system prototypes with mechanisms that enforce security and privacy policies. Methods: We developed the Model-Integrated Clinical Information System (MICIS), a software toolkit that is based on model-based design techniques and highlevel modeling abstractions to represent complex clinical workflows in a service-oriented architecture paradigm. MICIS translates models into executable constructs, such as web service descriptions, business process execution language procedures, and deployment instructions. MICIS models are enriched with formal security and privacy specifications, which are enforced within the execution environment. Results: We successfully validated our design platform by modeling multiple clinical workflows and deploying them onto the execution platform. Conclusions: The model-based approach shows great promise for developing, simulating, and evolving clinical information systems with formal properties and policy restrictions.

???Extreme Duplication??? in the US FDA Adverse Events Reporting System Database

Drug Safety ◽  
2007 ◽  
Vol 30 (6) ◽  
pp. 551-554 ◽  
Author(s):  
Manfred Hauben ◽  
Lester Reich ◽  
James DeMicco ◽  
Katherine Kim
Keyword(s):  
Adverse Events ◽  
Reporting System ◽  
System Database ◽  
The Us ◽  
Us Fda

Trends in software as a medical device (Preprint)

2020 ◽  
Author(s):  
Aaron Ceross ◽  
Jeroen Bergmann
Keyword(s):  
Health Care ◽  
Data Analysis ◽  
High Risk ◽  
Adverse Events ◽  
Medical Device ◽  
Empirical Analysis ◽  
Medical Devices ◽  
Digital Revolution ◽  
The Us ◽  
Software Registration

UNSTRUCTURED Software-as-a-medical-device (SaMD) has gained popularity as a type of medical device. However, to date, empirical analysis of SaMD trends have been lacking. Using databases managed by the US medical device regulator (the Food and Drug Administration), we map the path SaMD takes towards classification and recorded adverse events. The findings show that while SaMD has been identified in literature as an area of development, the data analysis suggests that this growth has been modest. These devices are overwhelming classified as moderate to high risk and they take a very particular path to that classification. The digital revolution in health care is less pronounced when evidence is considered of SaMD. In general, the trend for software registration mimics that of medical devices.

Novel Adverse Events of Bevacizumab in the US FDA Adverse Event Reporting System Database

Drug Safety ◽  
2012 ◽  
Vol 35 (6) ◽  
pp. 507-518 ◽  
Author(s):  
Behrooz K. Shamloo ◽  
Pankdeep Chhabra ◽  
Andrew N. Freedman ◽  
Arnold Potosky ◽  
Jennifer Malin ◽  
...  
Keyword(s):  
Adverse Event ◽  
Adverse Events ◽  
Reporting System ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Event Reporting ◽  
System Database ◽  
The Us ◽  
Us Fda

scholarly journals Potential Utility of Pre-Emptive Germline Pharmacogenetics in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1219
Author(s):  
Philip S. Bernard ◽  
Whitney Wooderchak-Donahue ◽  
Mei Wei ◽  
Steven M. Bray ◽  
Kevin C. Wood ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Side Effects ◽  
Adverse Events ◽  
Proton Pump ◽  
Gene Interactions ◽  
Potential Utility ◽  
Dose Selection ◽  
The Us ◽  
Inflammatory Drugs ◽  
Us Fda

Patients with breast cancer often receive many drugs to manage the cancer, side effects associated with cancer treatment, and co-morbidities (i.e., polypharmacy). Drug–drug and drug–gene interactions contribute to the risk of adverse events (AEs), which could lead to non-adherence and reduced efficacy. Here we investigated several well-characterized inherited (germline) pharmacogenetic (PGx) targets in 225 patients with breast cancer. All relevant clinical, pharmaceutical, and PGx diplotype data were aggregated into a single unifying informatics platform to enable an exploratory analysis of the cohort and to evaluate pharmacy ordering patterns. Of the drugs recorded, there were 38 for which high levels of evidence for clinical actionability with PGx was available from the US FDA and/or the Clinical Pharmacogenetics Implementation Consortium (CPIC). These data were associated with 10 pharmacogenes: DPYD, CYP2C9, CYP2C19, CYP2D6, CYP3A5, CYP4F2, G6PD, MT-RNR1, SLCO1B1, and VKORC1. All patients were taking at least one of the 38 drugs and had inherited at least one actionable PGx variant that would have informed prescribing decisions if this information had been available pre-emptively. The non-cancer drugs with PGx implications that were common (prescribed to at least one-third of patients) included anti-depressants, anti-infectives, non-steroidal anti-inflammatory drugs, opioids, and proton pump inhibitors. Based on these results, we conclude that pre-emptive PGx testing may benefit patients with breast cancer by informing drug and dose selection to maximize efficacy and minimize AEs.

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