Difference between revisions of "Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set"

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== First Review ==
 
== First Review ==
  
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This is a review for Samuel Alfano's  ''Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set''. <ref name="Alfano"> Samuel Alfano, D. O. (2013). Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set. Physician executive, 39(5), 30.</ref>
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This is a review for Samuel Alfano's  ''Enhancing Physician Adoption of [[CPOE]]: The Search for a Perfect [[Order Set]]''. <ref name="Alfano"> Samuel Alfano, D. O. (2013). Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set. Physician executive, 39(5), 30. http://acpe.physicianleaders.org/docs/default-source/pej/enhancing-physician-adoption-of-cpoe.pdf?sfvrsn=4</ref>
  
 
=== Abstract ===
 
=== Abstract ===
  
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“Objective To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record ([[EHR]]) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical research.
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"As hospitals and health care providers throughout the US evaluate the impact of the 2009 [[ARRA| American Recovery and Reinvestment Act]], provisions in the package that call for the "[[meaningful use]]" of electronic medical records are prompting rapid growth in the implementation of computerized physician order entry ([[CPOE|CPOE]]). Despite this incentive, only 21.7% of hospitals had successfully implemented CPOE systems according to a 2011 KLAS report. Catholic Health Initiatives (CHI) is a large national hospital system consisting of 76 hospitals in 19 states. Several years ago they started a project called ONECARE. Their goal was to roll out an electronic medical record and CPOE to all hospitals and providers within five years. During the first few weeks most, if not all physicians, customized the order sets they commonly used. Even though they could share these sets with other members of their group or department, they rarely shared these widely." <ref name="Alfano"> Samuel Alfano, D. O. (2013). Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set. Physician executive, 39(5), 30.</ref>
  
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Methods The authors developed and distributed a software application that performs standardized data cleaning, preprocessing, and hashing of patient identifiers to remove all protected health information. The application creates seeded hash code combinations of patient identifiers using a Health Insurance Portability and Accountability Act , ([[HIPAA]]) compliant SHA-512 algorithm that minimizes re-identification risk. The authors subsequently linked individual records using a central honest broker with an algorithm that assigns weights to hash combinations in order to generate high specificity matches.
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=== Methods ===
  
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Results The software application successfully linked and de-duplicated 7 million records across 6 institutions, resulting in a cohort of 5 million unique records. Using a manually reconciled set of 11 292 patients as a gold standard, the software achieved a sensitivity of 96% and a specificity of 100%, with a majority of the missed matches accounted for by patients with both a missing social security number and last name change. Using 3 disease examples, it is demonstrated that the software can reduce duplication of patient records across sites by as much as 28%.
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The author and colleagues developed a portfolio of national order sets and posted them on the internet using XML and SharePoint. They then opened them to physicians within their system and allowed them to make comments as well as see other contributors' comments.  
  
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Conclusions Software that standardizes the assignment of a unique seeded hash identifier merged through an agreed upon third-party honest broker can enable large-scale secure linkage of EHR data for epidemiologic and public health research. The software algorithm can improve future epidemiologic research by providing more comprehensive data given that patients may make use of multiple healthcare systems.” (p. 1072,<ref name="Kho"> Kho, A. N., Cashy, J. P., Jackson, K. L., Pah, A. R., Goel, S., Boehnke, J., … Galanter, W. L. (2015). Design and implementation of a privacy preserving electronic health record linkage tool in Chicago. Journal of the American Medical Informatics Association, 22(5), 1072–1080. http://doi.org/10.1093/jamia/ocv038 (Links to an external site.)</ref>).
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=== Results ===
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Discovery of important considerations while negotiating the process to improve acceptability of the order sets developed. Attention to issues helps improve adoption of order sets to provide safe care to patients.
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=== Conclusion ===
 +
 
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It is important to give physicians' input on order sets and allow them to customize specific order sets in orders to enhance the adoption of CPOE.  
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=== Comments ===
 +
 
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This article gives insight to the steps taken to adopt CPOE in a large national hospital system. While the author explains different measure that are important to consider when implementing CPOE, there is no information on whether the implementation within the system as successful or not.
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== Second Review ==
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=== Introduction ===
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As the intensives to adopt CPOE systems in hospitals continue to grow, the rate of CPOE integration into clinics has not been impressive. This article seeks to elaborate on what is preventing a wider spread integration of CPOE systems by physicians. With this transition, more emphasis has been put towards the adaptation of order sets along with CPOE systems. Given order sets' history of improving patient outcomes, reducing costs, and improving efficiency, this article seeks to bring some of the obstacles of adaptation to light. <ref name="Alfano"> Samuel Alfano, D. O. (2013). Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set. Physician executive, 39(5), 30.</ref>
  
 
=== Methods ===
 
=== Methods ===
  
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The authors created a matching application to link medical records from 4 large medical centers, 1 large county healthcare system and 1 network of community health centers with multiple outpatient care sites. The algorithm uses rules to match patient identifiers such as first name, last name, and date of birth to create matches among records.   
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Those involved in the creation of this study introduced multiple physicians as well as other benefactors to certain order sets in order to attain their input and opinion.   
  
 
=== Results ===
 
=== Results ===
  
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The application was able to de-duplicate 7 million records that were provided by the participating institutions and turned it into 5.3 million records. The sensitivity of the matching algorithm was 0.9569 and the specificity was 0.9999. Errors made by the algorithm can be attributed to patients who did not have a social security number and patients who changed their last name.  
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Multiple critiques and useful suggestions were made regarding current order sets.
  
 
=== Conclusion ===
 
=== Conclusion ===
  
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It is possible for a matching application to link medical records through the use of patient identifiers.  
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The article reviews multiple suggestions regarding order sets and reestablishes the point that physicians are necessary in the development of order sets as to maximize efficiency.  
  
 
=== Comments ===
 
=== Comments ===
  
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This article is an example of how health records can be matched by using a combination of patient identifiers. The [[Patient identifier|national patient identifier]] could be a combination of things considering that SSNs are not guaranteed to be identical and are reused over time.  
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This is an excellent article depicting the partnership between EMR developers and physicians in order to establish better electronic healthcare systems.
  
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== Second Review ==
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== Related Article Reviews ==
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[[Main Page/The Use of Electronic Medical Records: Communication Patterns in Outpatient Encounters]]
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[[Computerized Provider Order Entry Reduces Length of Stay in a Community Hospital]]
  
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Add next review here.
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[[Why doctors quit]]
  
 
== References ==
 
== References ==
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[[Category:Reviews]]
 
[[Category:Reviews]]
 
[[Category:HI5313-2015-FALL]]
 
[[Category:HI5313-2015-FALL]]
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[[Category:CDS]]
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[[Category:CPOE]]
 
[[Category:EMR]]
 
[[Category:EMR]]
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[[Category:Privacy, Confidentiality, and Security]]
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[[Category: Technologies]]
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[[Category:CIS]]
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[[Category:Order Sets]]

Latest revision as of 05:27, 24 November 2015

First Review

This is a review for Samuel Alfano's Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set. [1]

Abstract

"As hospitals and health care providers throughout the US evaluate the impact of the 2009 American Recovery and Reinvestment Act, provisions in the package that call for the "meaningful use" of electronic medical records are prompting rapid growth in the implementation of computerized physician order entry (CPOE). Despite this incentive, only 21.7% of hospitals had successfully implemented CPOE systems according to a 2011 KLAS report. Catholic Health Initiatives (CHI) is a large national hospital system consisting of 76 hospitals in 19 states. Several years ago they started a project called ONECARE. Their goal was to roll out an electronic medical record and CPOE to all hospitals and providers within five years. During the first few weeks most, if not all physicians, customized the order sets they commonly used. Even though they could share these sets with other members of their group or department, they rarely shared these widely." [1]

Methods

The author and colleagues developed a portfolio of national order sets and posted them on the internet using XML and SharePoint. They then opened them to physicians within their system and allowed them to make comments as well as see other contributors' comments.

Results

Discovery of important considerations while negotiating the process to improve acceptability of the order sets developed. Attention to issues helps improve adoption of order sets to provide safe care to patients.

Conclusion

It is important to give physicians' input on order sets and allow them to customize specific order sets in orders to enhance the adoption of CPOE.

Comments

This article gives insight to the steps taken to adopt CPOE in a large national hospital system. While the author explains different measure that are important to consider when implementing CPOE, there is no information on whether the implementation within the system as successful or not.

Second Review

Introduction

As the intensives to adopt CPOE systems in hospitals continue to grow, the rate of CPOE integration into clinics has not been impressive. This article seeks to elaborate on what is preventing a wider spread integration of CPOE systems by physicians. With this transition, more emphasis has been put towards the adaptation of order sets along with CPOE systems. Given order sets' history of improving patient outcomes, reducing costs, and improving efficiency, this article seeks to bring some of the obstacles of adaptation to light. [1]

Methods

Those involved in the creation of this study introduced multiple physicians as well as other benefactors to certain order sets in order to attain their input and opinion.

Results

Multiple critiques and useful suggestions were made regarding current order sets.

Conclusion

The article reviews multiple suggestions regarding order sets and reestablishes the point that physicians are necessary in the development of order sets as to maximize efficiency.

Comments

This is an excellent article depicting the partnership between EMR developers and physicians in order to establish better electronic healthcare systems.

Related Article Reviews

Main Page/The Use of Electronic Medical Records: Communication Patterns in Outpatient Encounters

Computerized Provider Order Entry Reduces Length of Stay in a Community Hospital

Why doctors quit

References

  1. ↑ 1.0 1.1 1.2 Samuel Alfano, D. O. (2013). Enhancing Physician Adoption of CPOE: The Search for a Perfect Order Set. Physician executive, 39(5), 30. http://acpe.physicianleaders.org/docs/default-source/pej/enhancing-physician-adoption-of-cpoe.pdf?sfvrsn=4
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