Use of order sets in inpatient computerized provider order entry systems: a comparative analysis of usage patterns at seven sites.

Background: Many computerized provider order entry (CPOE) systems include the ability to create electronic order sets: collections of clinically related orders grouped by purpose. Order sets promise to make CPOE systems more efficient, improve care quality and increase adherence to evidence-based guidelines. However, the development and implementation of order sets can be expensive and time-consuming and limited literature exists about their utilization.

Order sets in computerized physician order entry systems: an analysis of seven sites.

Most computerized physician order entry (CPOE) systems have built-in support for order sets (collections of orders grouped by a clinical purpose). Evidence and experience suggest that order sets are important tools for ordering efficiency and decision support and may influence ordering. Developing and maintaining order sets is costly, so hospitals often must prioritize which order sets can be created.

The state of the art in clinical knowledge management: an inventory of tools and techniques.

Purpose: To explore the need for, and use of, high-quality, collaborative, clinical knowledge management (CKM) tools and techniques to manage clinical decision support (CDS) content.

Methods: In order to better understand the current state of the art in CKM, we developed a survey of potential CKM tools and techniques. We conducted an exploratory study by querying a convenience sample of respondents about their use of specific practices in CKM.

Categorizing the unintended sociotechnical consequences of computerized provider order entry.

Objective: To describe the kinds of unintended consequences related to the implementation of computerized provider order entry (CPOE) in the outpatient setting.

Design: Ethnographic and interview data were collected by an interdisciplinary team over a 7 month period at four clinics.

Measurements: Instances of unintended consequences were categorized using an expanded Diffusion of Innovations theory framework.

Adding insight: a qualitative cross-site study of physician order entry.

The research questions, strategies, and results of a 7-year qualitative study of computerized physician order entry implementation (CPOE) at successful sites are reviewed over time. The iterative nature of qualitative inquiry stimulates a consecutive stream of research foci, which, with each iteration, add further insight into the overarching research question. A multidisciplinary team of researchers studied CPOE implementation in four organizations using a multi-method approach to address the question "what are the success factors for implementing CPOE?" Four major themes emerged after studying three sites; ten themes resulted from blending the first results with those from a fourth site; and twelve principles were generated when results of a qualitative analysis of consensus conference transcripts were combined with the field data.

Adding insight: a qualitative cross-site study of physician order entry.

The research questions, strategies, and results of a six-year qualitative study of computerized physician order entry implementation (CPOE) at successful sites are reviewed over time. The iterative nature of qualitative inquiry stimulates a consecutive stream of research foci which, with each iteration, add further insight into the overarching research question. A multidisciplinary team of researchers studied CPOE implementation in four organizations using a multi-method approach to address the question "what are the success factors for implementing CPOE?" Four major themes emerged after studying three sites; ten themes resulted from blending the first results with those from a fourth site; and twelve principles were generated when results of a qualitative analysis of consensus conference transcripts were combined with the field data.

Using medication list--problem list mismatches as markers of potential error.

The goal of this project was to specify and develop an algorithm that will check for drug and problem list mismatches in an electronic medical record (EMR). The algorithm is based on the premise that a patient's problem list and medication list should agree, and a mismatch may indicate medication error. Successful development of this algorithm could mean detection of some errors, such as medication orders entered into a wrong patient record, or drug therapy omissions, that are not otherwise detected via automated means.