Difference between revisions of "Systematic review of clinical decision support interventions with potential for inpatient cost reduction"
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| − | + | With government mandate through the HITECH act of 2009 to push the use of computers as an everyday tool for medicine, EMR's have touted the benefit of CDS not just as a quality measure which would increase patient safety and decrease errors, but that it would be a cost-saving tool as well. Multiple other studies have shown that EMR's, in fact, do not have the anticipated cost reduction benefits as originally speculated. This study adds to the evidence that the potential benefits of health IT and CDS are not well grounded in empirical evidence from a fincancial prospective. | |
| − | + | Hospitals are a turning point in which multiple forces (government, public, insurance companies) are adding pressure to reduce cost. | |
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| − | + | As healthcare organizations continue to rapidly adopt health IT, leadership within those organizations must decide how to best use limited resources. Presumably, the potential cost savings associated with intervention candidates is a major factor in making those decisions. However, as a discipline, informatics does not appear to be meeting the needs of these healthcare decision makers with regard to CDS, as we have not been providing sufficient, rigorous data related to the cost benefits of CDS interventions in the inpatient setting. Further research with specific attention to cost implications of CDS systems in the inpatient setting is clearly needed. | |
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Revision as of 22:32, 2 March 2015
This is a review for Christopher L Fillmore, Bruce E. Bray and Kensaku Kawamoto's systematic review of other completed studies to assess if clinical decision support CDS interventions cut inpatient costs. [1]
Contents
Research question
In the inpatient setting, has there been a conclusion of whether CDS cut the cost of healthcare and if so by what average amount and in which specific area?
Methods
MEDLINE was searched up through July 2013 to find the studies which deal with the economic savings of CDS intervention. These studies were identified through titles and abstracts, and subsequently full text articles were accessed and reviewed to make a final determination on inclusion. Relevant details of the studies were extracted and summarized.
Environment
MEDLINE was used in searching from the beginning of the project to July 2013. The following search terms were used in combination:
- Clinical decision support systems
- Decision-making
- Computer-assisted
- Computerized decision support
- Reminder systems
- Guideline adherence
- Medical informatics
All researched articles dealt with human beings and were written in the English language.
Design
Data was gathered by a single reviewer in order to prevent multiple biases using a standard form. If there was uncertainty any uncertainty, it was resolved through consensus. Each article was examined followed the exact same steps in the following order:
1. Evaluation for inclusion criteria 2. Data extraction 3. Analysis of trial design 4. Analysis of intervention 5. Analysis of trial results
The inpatient setting was defined by the wards, ER, ICU and surgical settings.
Measurement
The design of the study was such that data gathered were analyzed and summarized in a table. Themes, trends and patterns were identified and looked to see if identifiable patterns were evolving. A Fisher's exact test of independence was used. The independent variable was a statistically and clinically significant improvement in cost (reduction in cost). A p-value of < 0.05 was considered statistically significant.
Results
After an extensive search, a total of 7,663 articles and 78 manuscripts were reviewed. The types of studies were broken down into before-after studies with control groups which had 78.2%. and randomized controlled studies which encompassed 15.4%. The largest studied area by far was pharmacotherapy which had 53.8% of the studies 70.5% of the studies resulted in statistically and clinically significant improvements in an explicit financial measure or a proxy financial measure. However, of all the studies, data on cost effectiveness was available for only one study.
Conclusion
Despite how it is often claimed that CDS would save money, there is a large void to actually prove the financial efficacy of CDS in EMR systems. More research is necessary to determine financial impact on how and where CDS can have an impact on reducing inpatient costs.
Commentary
With government mandate through the HITECH act of 2009 to push the use of computers as an everyday tool for medicine, EMR's have touted the benefit of CDS not just as a quality measure which would increase patient safety and decrease errors, but that it would be a cost-saving tool as well. Multiple other studies have shown that EMR's, in fact, do not have the anticipated cost reduction benefits as originally speculated. This study adds to the evidence that the potential benefits of health IT and CDS are not well grounded in empirical evidence from a fincancial prospective.
Hospitals are a turning point in which multiple forces (government, public, insurance companies) are adding pressure to reduce cost.
As healthcare organizations continue to rapidly adopt health IT, leadership within those organizations must decide how to best use limited resources. Presumably, the potential cost savings associated with intervention candidates is a major factor in making those decisions. However, as a discipline, informatics does not appear to be meeting the needs of these healthcare decision makers with regard to CDS, as we have not been providing sufficient, rigorous data related to the cost benefits of CDS interventions in the inpatient setting. Further research with specific attention to cost implications of CDS systems in the inpatient setting is clearly needed.
References
- ↑ . Systematic review of clinical decision support interventions with potential for inpatient cost reduction. BMC Medical Informatics and Decision Making 2013, 13:135. http://www.biomedcentral.com/1472-6947/13/135
