Difference between revisions of "The Unintended Consequences of Computerized Provider Order Entry: Findings From a Mixed Methods Exploration"
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==Abstract== | ==Abstract== | ||
| − | *Objective—To describe the foci, activities, methods, and results of a four-year research project identifying the unintended consequences of computerized provider order entry (CPOE). | + | *Objective—To describe the foci, activities, methods, and results of a four-year research project identifying the unintended consequences of computerized provider order entry ([[CPOE]]). |
*Methods—Using a mixed methods approach, we identified and categorized into nine types 380 examples of the unintended consequences of CPOE gleaned from fieldwork data and a conference of experts. We then conducted a national survey in the U.S.A. to discover how hospitals with varying levels of infusion, a measure of CPOE sophistication, recognize and deal with unintended consequences. The research team, with assistance from experts, identified strategies for managing the nine types of unintended adverse consequences and developed and disseminated tools for CPOE implementers to help in addressing these consequences. | *Methods—Using a mixed methods approach, we identified and categorized into nine types 380 examples of the unintended consequences of CPOE gleaned from fieldwork data and a conference of experts. We then conducted a national survey in the U.S.A. to discover how hospitals with varying levels of infusion, a measure of CPOE sophistication, recognize and deal with unintended consequences. The research team, with assistance from experts, identified strategies for managing the nine types of unintended adverse consequences and developed and disseminated tools for CPOE implementers to help in addressing these consequences. | ||
*Results—Hospitals reported that levels of infusion are quite high and that these types of unintended consequences are common. Strategies for avoiding or managing the unintended consequences are similar to best practices for CPOE success published in the literature. | *Results—Hospitals reported that levels of infusion are quite high and that these types of unintended consequences are common. Strategies for avoiding or managing the unintended consequences are similar to best practices for CPOE success published in the literature. | ||
Revision as of 03:09, 12 October 2015
Contents
Abstract
- Objective—To describe the foci, activities, methods, and results of a four-year research project identifying the unintended consequences of computerized provider order entry (CPOE).
- Methods—Using a mixed methods approach, we identified and categorized into nine types 380 examples of the unintended consequences of CPOE gleaned from fieldwork data and a conference of experts. We then conducted a national survey in the U.S.A. to discover how hospitals with varying levels of infusion, a measure of CPOE sophistication, recognize and deal with unintended consequences. The research team, with assistance from experts, identified strategies for managing the nine types of unintended adverse consequences and developed and disseminated tools for CPOE implementers to help in addressing these consequences.
- Results—Hospitals reported that levels of infusion are quite high and that these types of unintended consequences are common. Strategies for avoiding or managing the unintended consequences are similar to best practices for CPOE success published in the literature.
- Conclusion—Development of a taxonomy of types of unintended adverse consequences of CPOE using qualitative methods allowed us to craft a national survey and discover how widespread these consequences are. Using mixed methods, we were able to structure an approach for addressing the skillful management of unintended consequences as well. [1]
Summary
Introduction
Previously, there has been little research into the unintended consequences (UCs) of CPOEs. Though research by Patterson and his team into bar coding systems has been done and their main concern is stopping UCs before they have a chance to affect the outcome of a patient. While CPOEs have been shown to reduce errors in a hospital setting it is the aim of this study to determine what new errors cause UCs within the new systems and how to prevent, manage, and overcome them. One example of these new error is called a juxtaposition euro, where the user selected something close to what they intended to select thus causing an error.
Methods
A sample of hospitals was selected from across the nation and data was collected between 2003 and 2007. The study began by interviewing and observing clinical personal who used the CPOE system, after determine what they thought to be the major UCs a telephone survey was created. This survey was then ran across all hospitals in the US who had a CPOE system. The initial data showed that the original UCs were to broad. Using a card sort method and grounded theory approach a new 9 name taxonomy with which all 380 instances fit in was created. Sub categories were then created for each of the 9 new UCs giving a better break down of all UCs determined in the study.
Results
Nine categories were determine to hold all UCs that were being seen across the country. Below they are ordered in decreasing frequency.
- More / New Work Issues- Physicians believe that CPOE increase their workload.
- Workflow Issues- Mismatches between CIS and workflow cause many new errors.
- Never Ending Demands- More space is needed for new hardware, for viewing information, and so on.
- Paper Persistence- paper is still being used.
- Communication Issues- Communication between departments is thought to be occurring but in fact is not.
- Emotions- User emotions tend to be negative.
- New Kinds of Errors- New errors such as juxtaposition errors are occurring.
- Changes in the Power Structure- Physicians are no longer the ones with the power.
- Overdependence on Technology- No backup paper systems in case of a technology malfunction.
The national survey showed that the new categories were in fact occurring.
Conclusion
Though the use of the interviews and shadowing, surveys were able to be created that led to the discovery of the 9 categories of UCs. These 9 categories were then shown to occur across the nation after the second national survey was completed. It would be a good idea to continue studying these UCs, and new UCs as they occur.
Comments
Interesting article. While I believe that this was a problem back in 2009, I think now as doctors have become more acquainted with the software and as a new generation of doctors appear who have used technology all their lives a lot of these UCs that have been occurring will actually start to decrease. I do believe though that we will in fact see new UCs starting to occur with the introduction of applications on smart phones into the medical field.
