Pharmacists’ awareness of clinical decision support in pharmacy information systems: An exploratory evaluation

2011 ◽  
Vol 7 (4) ◽  
pp. 359-368 ◽  
Author(s):  
Lisa E. Hines ◽  
Kim R. Saverno ◽  
Terri L. Warholak ◽  
Ann Taylor ◽  
Amy J. Grizzle ◽  
...  
2021 ◽  
Author(s):  
Maurice Henkel ◽  
Tobias Horn ◽  
Francois Leboutte ◽  
Pawel Trotsenko ◽  
Sarah G. Dugas ◽  
...  

Abstract Introduction Physicians spend more than half of their workday interacting with health information systems to care for their patients. Effective data management that provides physicians with comprehensive patient information from various information systems is required to ensure high quality clinical decision making.Objectives We evaluated the impact of a novel, CE-certified clinical decision support tool on physician’s effectiveness and satisfaction in the clinical decision-making process.Methods Using pre-therapeutic prostate cancer management cases, we compared physician’s expenditure of time, data quality, and user satisfaction in the decision-making process comparing the current standard with the software. Ten urologists from our department conducted the diagnostic work-up to the treatment decision for a total of 10 patients using both approaches.Results A significant reduction in the physician’s expenditure of time for the decision-making process by -59.9 % (p < 0,001) was found using the software. System usage showed a high positive effect on evaluated data quality parameters completeness (Cohen's d of 2.36), format (6.15), understandability (2.64), as well as user satisfaction (4.94).Conclusion The software demonstrated that effective data management can improve physician’s effectiveness and satisfaction in the clinical decision-making process. Further development is needed to map more complex patient pathways, such as the follow-up treatment of prostate cancer.


2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Lauren Shrader ◽  
Stuart Myerburg ◽  
Eric Larson

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.


2011 ◽  
pp. 1922-1933
Author(s):  
Rania Shibl ◽  
Kay Fielden ◽  
Andy Bissett ◽  
Den Pain

Our study of the use of clinical decision support systems by general practitioners in New Zealand reveals the pervasive nature of the issue of trust. “Trust” was a term that spontaneously arose in interviews with end users, technical support personnel, and system suppliers. Technical definitions of reliability are discussed in our chapter, but the very human dimension of trust seems at least as significant, and we examine what is bound up in this concept. The various parties adopted different means of handling the trust question, and we explain these. Some paradoxical aspects emerge in the context of modern information systems, both with the question of trust and with the provision of technical or organisational solutions in response to the existence of trust. We conclude by considering what lessons may be drawn, both in terms of the nature of trust and what this might mean in the context of information systems.


Author(s):  
Rania Shibl ◽  
Kay Fielden ◽  
Andy Bissett ◽  
Den Pain

Our study of the use of clinical decision support systems by general practitioners in New Zealand reveals the pervasive nature of the issue of trust. “Trust” was a term that spontaneously arose in interviews with end users, technical support personnel, and system suppliers. Technical definitions of reliability are discussed in our chapter, but the very human dimension of trust seems at least as significant, and we examine what is bound up in this concept. The various parties adopted different means of handling the trust question, and we explain these. Some paradoxical aspects emerge in the context of modern information systems, both with the question of trust and with the provision of technical or organisational solutions in response to the existence of trust. We conclude by considering what lessons may be drawn, both in terms of the nature of trust and what this might mean in the context of information systems.


Author(s):  
Ilia Semenov ◽  
Roman Osenev ◽  
Sergey Gerasimov ◽  
Georgy Kopanitsa ◽  
Dmitry Denisov ◽  
...  

This paper is an extension of work originally presented to pHealth 2019—16th International Conference on Wearable, Micro and Nano Technologies for Personalized Health. To provide an efficient decision support, it is necessary to integrate clinical decision support systems (CDSSs) in information systems routinely operated by healthcare professionals, such as hospital information systems (HISs), or by patients deploying their personal health records (PHR). CDSSs should be able to use the semantics and the clinical context of the data imported from other systems and data repositories. A CDSS platform was developed as a set of separate microservices. In this context, we implemented the core components of a CDSS platform, namely its communication services and logical inference components. A fast healthcare interoperability resources (FHIR)-based CDSS platform addresses the ease of access to clinical decision support services by providing standard-based interfaces and workflows. This type of CDSS may be able to improve the quality of care for doctors who are using HIS without CDSS features. The HL7 FHIR interoperability standards provide a platform usable by all HISs that are FHIR enabled. The platform has been implemented and is now productive, with a rule-based engine processing around 50,000 transactions a day with more than 400 decision support models and a Bayes Engine processing around 2000 transactions a day with 128 Bayesian diagnostics models.


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