Developing a framework for establishing clinical decision support meaningful use objectives for clinical specialties – RAND – 2012

Posted on October 23, 2012. Filed under: Evidence Based Practice, Health Informatics, Knowledge Translation | Tags: , |

Developing a framework for establishing clinical decision support meaningful use objectives for clinical specialties – RAND – 2012

Extract from the preface

“The federal electronic health record (EHR) incentive program includes clinical decision support (CDS) as a central requirement of improving health outcomes; however, a process for identifying and prioritizing the most-promising targets for CDS has not been established. CDS provides those involved in care processes with general and person-specific information, intelligently filtered and organized, at appropriate times, to enhance health and health care.

This report describes a protocol for eliciting high-priority targets for electronic CDS for individual clinical specialties, which could serve to inform policymakers’ deliberations and establishment of CDS meaningful use objectives. Researchers from the RAND Corporation tested the protocol with four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics. A CDS target was defined as a clinical performance gap having one or more CDS opportunities that can be implemented to address the gap.  A CDS opportunity is defined as a specific CDS intervention that could be expected to address a clinical performance gap. CDS opportunities include existing CDS tools or interventions that might be developed in the short term.”

… continues on the site

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Enabling Health Care Decisionmaking Through Clinical Decision Support and Knowledge Management – AHRQ – April 2012

Posted on April 26, 2012. Filed under: Evidence Based Practice, Health Informatics, Knowledge Translation | Tags: , , |

Enabling Health Care Decisionmaking Through Clinical Decision Support and Knowledge Management – AHRQ – April 2012

Evidence Report / Technology Assessment no 2-3
AHRQ = Agency for Healthcare Research and Quality [US], Prepared by: Duke Evidence-based Practice Center, Durham, North Carolina

“Structured Abstract

Objectives: To catalogue study designs used to assess the clinical effectiveness of clinical decision support systems (CDSSs) and knowledge management systems (KMSs), to identify features that impact the success of CDSSs/KMSs, to document the impact of CDSSs/KMSs on outcomes, and to identify knowledge types that can be integrated into CDSSs/KMSs.

Data Sources: MEDLINE®, CINAHL®, PsycINFO®, and Web of Science®.

Review Methods: We included studies published in English from January 1976 through December 2010. After screening titles and abstracts, full-text versions of articles were reviewed by two independent reviewers. Included articles were abstracted to evidence tables by two reviewers. Meta-analyses were performed for seven domains in which sufficient studies with common outcomes were included.

Results: We identified 15,176 articles, from which 323 articles describing 311 unique studies including 160 reports on 148 randomized control trials (RCTs) were selected for inclusion. RCTs comprised 47.5 percent of the comparative studies on CDSSs/KMSs. Both commercially and locally developed CDSSs effectively improved health care process measures related to performing preventive services (n = 25; OR 1.42, 95% confidence interval [CI] 1.27 to 1.58), ordering clinical studies (n = 20; OR 1.72, 95% CI 1.47 to 2.00), and prescribing therapies (n = 46; OR 1.57, 95% CI 1.35 to 1.82). Fourteen CDSS/KMS features were assessed for correlation with success of CDSSs/KMSs across all endpoints. Meta-analyses identified six new success features: integration with charting or order entry system, promotion of action rather than inaction, no need for additional clinician data entry, justification of decision support via research evidence, local user involvement, and provision of decision support results to patients as well as providers. Three previously identified success features were confirmed: automatic provision of decision support as part of clinician workflow, provision of decision support at time and location of decisionmaking, and provision of a recommendation, not just an assessment. Only 29 (19.6%) RCTs assessed the impact of CDSSs on clinical outcomes, 22 (14.9%) assessed costs, and 3 assessed KMSs on any outcomes. The primary source of knowledge used in CDSSs was derived from structured care protocols.

Conclusions: Strong evidence shows that CDSSs/KMSs are effective in improving health care process measures across diverse settings using both commercially and locally developed systems. Evidence for the effectiveness of CDSSs on clinical outcomes and costs and KMSs on any outcomes is minimal. Nine features of CDSSs/KMSs that correlate with a successful impact of clinical decision support have been newly identified or confirmed.”

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Driving Quality and Performance Measurement – A Foundation for Clinical Decision Support – National Quality Forum – December 2010

Posted on January 20, 2011. Filed under: Clin Governance / Risk Mgmt / Quality, Health Informatics | Tags: , , , , |

Driving Quality and Performance Measurement – A Foundation for Clinical Decision Support – National Quality Forum – December 2010
Page Count: 58

Abstract

“Increasing deployment, adoption, and meaningful use of electronic health records (EHRs) and health IT systems in the United States offers great potential to im¬prove the healthcare system. An important means to advance this goal is to measure performance, ensuring that relevant clinical knowledge is available at the point of care and implemented in a manner that promotes optimal care delivery. Properly positioned, clinical decision support (CDS) tools can play an important role. This report describes the development of the NQF CDS Taxonomy, the relationship between quality measurement and CDS, and the mapping of the Taxonomy to the QDS Model—an information model that lays the foundation for automatic, patient-centric, longitudinal quality measurement. The CDS Taxonomy should assist health IT system developers, system implementers, and the quality improvement community to develop tools, content, and procedures that are compatible and enable comprehensive use of CDS, thereby improving delivery of appropriate, evidenced-based care.”

ISBN 978-0-9828421-2-6

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Clinical Decision Support Systems:State of the Art – Prepared for the Agency for Healthcare Research and Quality (US) – June 2009

Posted on August 2, 2009. Filed under: Health Informatics | Tags: , , |

Clinical Decision Support Systems:State of the Art – Prepared for the Agency for Healthcare Research and Quality (US) – June 2009
AHRQ Publication No. 09-0069-EF

A PDF version of this document is also available. [PDF; 184KB]

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HIMSS launches clinical decision support wiki – 31 July 2009

Posted on August 1, 2009. Filed under: Health Informatics | Tags: , , , |

HIMSS launches clinical decision support wiki
July 31, 2009 | Kyle Hardy, Community Editor

“CHICAGO – The Healthcare Information and Management Systems Society has deployed a new wiki to allow healthcare organizations to collaborate on realizing the full potential of clinical decision support solutions.

With CDS being a critical part of “meaningful use” criteria, implementation and proper use of the systems is expected to improve care delivery and diagnosis, lowering costs of care for patients. The HIMSS Clinical Decision Support Task Force has now opened its CDS Wiki to the public.

The wiki concept allows a group of users to collaboratively edit a centralized document online.” … continues on the HealthCareITNews site

HIMSS Clinical Decision Support Wiki

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