Clinical decision support: from data to clinical information

2002 ◽  
Author(s):  
B. Thull ◽  
G. Rau ◽  
P. Hanrath
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Information ◽  
Clinical Decision

An Overview of Efforts to Bring Clinical Knowledge to the Point of Care

2005 ◽  
pp. 285-296
Author(s):  
Dean F. Sittig
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Point Of Care ◽  
Clinical Decision Support Systems ◽  
Clinical Information ◽  
Clinical Decision ◽  
Clinical Knowledge ◽  
The Right

By bringing people the right information in the right format at the right time and place, state of the art clinical information systems with imbedded clinical knowledge can help people make the right clinical decisions. This chapter provides an overview of the efforts to develop systems capable of delivering such information at the point of care. The first section focuses on “library-type” applications that enable a clinician to look-up information in an electronic document. The second section describes a myriad of “real-time clinical decision support systems.” These systems generally deliver clinical guidance at the point of care within the clinical information system (CIS). The third section describes several “hybrid” systems, which combine aspects of real-time clinical decision support systems with library-type information. Finally, section four provides a brief look at various attempts to bring clinical knowledge, in the form of computable guidelines, to the point of care.be sufficiently expressive to explicitly capture the design rational (process and outcome intentions) of the guideline’s author, while leaving flexibility at application time to the attending physician and their own preferred methods.” (Shahar, 2001)

scholarly journals Description of a clinical decision support tool with integrated dose calculator for paediatrics

2021 ◽  
Author(s):  
Lukas Higi ◽  
Karin Käser ◽  
Monika Wälti ◽  
Michael Grotzer ◽  
Priska Vonbach
Keyword(s):  
Decision Support ◽  
Medical Device ◽  
Medication Errors ◽  
Clinical Decision Support ◽  
Clinical Information ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Drug Dosing ◽  
Clinical Decision Support Tool

AbstractMedication errors, especially dosing errors are a leading cause of preventable harm in paediatric patients. The paediatric patient population is particularly vulnerable to dosing errors due to immaturity of metabolising organs and developmental changes. Moreover, the lack of clinical trial data or suitable drug forms, and the need for weight-based dosing, does not simplify drug dosing in paediatric or neonatal patients. Consequently, paediatric pharmacotherapy often requires unlicensed and off-label use including manipulation of adult dosage forms. In practice, this results in the need to calculate individual dosages which in turn increases the likelihood of dosing errors. In the age of digitalisation, clinical decision support (CDS) tools can support healthcare professionals in their daily work. CDS tools are currently amongst the gold standards in reducing preventable errors. In this publication, we describe the development and core functionalities of the CDS tool PEDeDose, a Class IIa medical device software certified according to the European Medical Device Regulation. The CDS tool provides a drug dosing formulary with an integrated calculator to determine individual dosages for paediatric, neonatal, and preterm patients. Even a technical interface is part of the CDS tool to facilitate integration into primary systems. This enables the support of the paediatrician directly during the prescribing process without changing the user interface.Conclusion: PEDeDose is a state-of-the-art CDS tool for individualised paediatric drug dosing that includes a certified calculator. What is Known:• Dosing errors are the most common type of medication errors in paediatric patients.• Clinical decision support tools can reduce medication errors effectively. Integration into the practitioner’s workflow improves usability and user acceptance. What is New:• A clinical decision support tool with a certified integrated dosing calculator for paediatric drug dosing.• The tool was designed to facilitate integration into clinical information systems to directly support the prescribing process. Any clinical information system available can interoperate with the PEDeDose web service.

Clinical decision support to reduce laterality ordering errors for breast imaging procedures.

2018 ◽  
Vol 36 (30_suppl) ◽  
pp. 241-241
Author(s):  
Karen Hernandez ◽  
Mahmoud El-Tamer ◽  
Jonathan Gurman ◽  
Robin Moulder ◽  
Reshma Nevrekar ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Health Informatics ◽  
Breast Imaging ◽  
Clinical Information System ◽  
Clinical Information ◽  
Clinical Decision ◽  
Radiology Department ◽  
Patient Arrival ◽  
Operative Notes

241 Background: Data showed 46 modifications to breast imaging orders upon patient arrival to the Radiology Department, in a 4 month period (Sept-Dec 2014.) Upon further investigation, we found that patients were arriving in radiology, scheduled for exams for which the laterality needed to be modified prior to the exam. (The most frequent occurrence was a patient with a history of a unilateral mastectomy, arriving in radiology for a bilateral mammogram.) These laterality order errors were traced back to either the referring LIP requesting the exam, or to the referring office’s clerical staff transcribing the order. The ordering errors came from many different referring services. Methods: Our objective was to develop Clinical Decision Support in our Clinical Information System (CIS,) to offer an upfront alert of a potentially incorrect laterality when a user was entering or transcribing an order, prompting the user to confirm that the correct exam had been ordered before scheduling took place. The Health Informatics team developed a Medical Logic Module (MLM) in CIS which cross-checks the surgical history in the Clinical Documentation Operative Notes with the current CIS order; if a mismatch is found, the alert fires. Results: In the first 2 months (Dec 2016-Jan 2017), 110 alerts were generated. Fifty-seven alerts flagged users of incorrect orders which were corrected before being scheduled; 21 MLM alerts were acknowledged and comments entered explaining the need for the test; 32 alerts did not generate an order (and in most of these instances, the user backed out and entered the incorrect order again; upon the second time seeing the alert, they changed the order, resulting in many of the 57 changed orders referenced above). Conclusions: The MLM alert allows for immediate feedback to the user entering an order with a potentially incorrect laterality. Not only does this reduce the time and burden associated with investigating and modifying these orders upon patient arrival; more importantly, it ensures orders are entered correctly from the start, reducing the possibility of an incorrect exam taking place.

scholarly journals Towards Meaningful Medication-Related Clinical Decision Support: Recommendations for an Initial Implementation

2011 ◽  
Vol 02 (01) ◽  
pp. 50-62 ◽  
Author(s):  
A. Wright ◽  
G.J. Kuperman ◽  
A.J. Vaida ◽  
A.M. Bobb ◽  
R.A. Jenders ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Organizations ◽  
Clinical Information ◽  
Clinical Decision ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Healthcare Settings ◽  
Clinical Content ◽  
National Expert

SummaryClinical decision support (CDS) can improve safety, quality, and cost-effectiveness of patient care, especially when implemented in computerized provider order entry (CPOE) applications. Medication-related decision support logic forms a large component of the CDS logic in any CPOE system. However, organizations wishing to implement CDS must either purchase the computable clinical content or develop it themselves. Content provided by vendors does not always meet local expectations. Most organizations lack the resources to customize the clinical content and the expertise to implement it effectively. In this paper, we describe the recommendations of a national expert panel on two basic medication-related CDS areas, specifically, drug-drug interaction (DDI) checking and duplicate therapy checking. The goals of this study were to define a starter set of medication-related alerts that health-care organizations can implement in their clinical information systems. We also draw on the experiences of diverse institutions to highlight the realities of implementing medication decision support. These findings represent the experiences of institutions with a long history in the domain of medication decision support, and the hope is that this guidance may improve the feasibility and efficiency CDS adoption across healthcare settings.

scholarly journals Clinical decision support system for decision making in mammary glands thermography

2017 ◽  
Author(s):  
◽  
M. B. Bastida
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Genetic Load ◽  
Clinical Information ◽  
Clinical Decision ◽  
Physical Parameters ◽  
Thermal Features

A decision tree based system with heuristic weight factors oriented to diagnosis by thermography was developed. The proposed clinical decision support system (CDSS) includes binary decision trees for statistical classification of some diseases of the mammary gland. These include weight constant factors found by the correlation of the variables involved in the development of breast disorders according to the statistical attachment of the thermal features, as well as complementary clinical information (medical history, physical parameters, genetic load and habits, among others), regarding its diagnostic incidence. The certainty of the system for inflammatory disorders is 96%, for fibrocystic mastopathy is 78 %, for fat necrosis is 62% and for breast cancer is 86%. The 14% error is associated to microcalcifications that with the reported thermographic technique it is not possible to differentiate. Thus, it is possible to catalog the risk of a patient having a condition according to the results obtained after conducting a thermal test. Then, with the CDSS the possibility of applying early detection tests in the population suffering from contraindications to perform the others is improved, in addition it allows a comprehensive diagnosis for other patients.

Trust and Clinical Information Systems

2011 ◽  
pp. 1922-1933
Author(s):  
Rania Shibl ◽  
Kay Fielden ◽  
Andy Bissett ◽  
Den Pain
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
New Zealand ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Information ◽  
Clinical Decision ◽  
Human Dimension ◽  
Modern Information

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.

Trust and Clinical Information Systems

2011 ◽  
pp. 48-64
Author(s):  
Rania Shibl ◽  
Kay Fielden ◽  
Andy Bissett ◽  
Den Pain
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
New Zealand ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Information ◽  
Clinical Decision ◽  
Human Dimension ◽  
Modern Information

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.

Evaluating the Effect of Unstructured Clinical Information on Clinical Decision Support Appropriateness Ratings

2017 ◽  
Vol 14 (6) ◽  
pp. 737-743 ◽  
Author(s):  
Andrew K. Moriarity ◽  
Aaron Green ◽  
Chad Klochko ◽  
Matthew O’Brien ◽  
Safwan Halabi
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Information ◽  
Clinical Decision

scholarly journals Clinical decision support system for decision making in mammary glands thermography

2017 ◽  
Author(s):  
◽  
M. B. Bastida
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Genetic Load ◽  
Clinical Information ◽  
Clinical Decision ◽  
Physical Parameters ◽  
Thermal Features

A decision tree based system with heuristic weight factors oriented to diagnosis by thermography was developed. The proposed clinical decision support system (CDSS) includes binary decision trees for statistical classification of some diseases of the mammary gland. These include weight constant factors found by the correlation of the variables involved in the development of breast disorders according to the statistical attachment of the thermal features, as well as complementary clinical information (medical history, physical parameters, genetic load and habits, among others), regarding its diagnostic incidence. The certainty of the system for inflammatory disorders is 96%, for fibrocystic mastopathy is 78 %, for fat necrosis is 62% and for breast cancer is 86%. The 14% error is associated to microcalcifications that with the reported thermographic technique it is not possible to differentiate. Thus, it is possible to catalog the risk of a patient having a condition according to the results obtained after conducting a thermal test. Then, with the CDSS the possibility of applying early detection tests in the population suffering from contraindications to perform the others is improved, in addition it allows a comprehensive diagnosis for other patients

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