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Due to an error in the implementation of the project, CDS was provided to all providers, rather than to the intended random sample of providers.
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| Name | Class |
|---|---|
| Icahn School of Medicine at Mount Sinai | OTHER |
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The goal of the study is to determine whether clinical decision support (CDS) affects the number, type, or appropriateness of targeted high-cost radiology images (i.e. MR and CT) ordered. The CDS will be delivered in Epic through ACRSelect software, which is a leading decision support tool based on the American College of Radiology (ACR) Appropriateness Criteria (see http://www.acr.org/Quality-Safety/Appropriateness-Criteria), and presents the ACR appropriateness scores for each image on a scale of 1-9 with 1-3 labelled as 'usually not appropriate', 4-6 'May be appropriate', and 7-9 'usually appropriate'.
With healthcare spending accounting for almost one-fifth of the U.S. economy and an even larger share of public sector budgets, there is substantial interest in innovations in healthcare delivery that can reduce the "over use" of resources that have no or low value to patients. As a result, there is a key need for rigorous evidence on scalable interventions aimed at improving the efficiency of the U.S. healthcare sector in general, and in the public sector in particular, which accounts for $1.25 trillion in annual healthcare spending (Centers for Medicare & Medicaid Services, 2013).
In particular, there is widespread concern in both the medical profession (Callaghan et al., 2014; Sherman, 2012) and the public sector (U.S. Government Accountability Office, 2008) of the cost and health risks of "over-scanning". Estimates suggest that as many as 30% of imaging in the U.S. are unnecessary (Consumer Reports, 2015; Dehn et al., 2000; Georgiou et al., 2011). Medicare direct spending on "high-cost" scans (e.g. MRs and CTs) was about $10 billion in 2012, or about 2% of total Medicare costs (Medicare Payment Advisory Commission, 2014); the indirect costs are likely considerably greater, since imaging often triggers additional follow up care (Sherman, 2012; Shreibati and Baker, 2011). It is also estimated that about 2 percent of cancers in the U.S. are due to CT use (Brenner and Hall, 2007).
Reflecting this concern, starting in 2017 Medicare will no longer reimburse for high-cost scans unless ordered using an "acceptable" Clinical Decision Support (CDS) system (Pitts, 2014). Despite this upcoming policy change, we know of no large-scale randomized trials on the impact of CDS for imaging.
The intervention in this study provides Clinical Decision Support (CDS) for targeted high-cost radiology orders, MR and CT scans, to healthcare providers treating patients in outpatient settings affiliated with Mount Sinai Hospital and Mount Sinai Queens hospital in New York City. CDS is a tool embedded in an order entry system that provides information and guidance to providers on whether their intended order is "appropriate" and whether there are more highly recommended alternatives. The randomization is at the provider level: one group will receive the CDS, while the remaining providers will serve as the control group.
The CDS will be delivered through the order-entry software, Epic, through ACRSelect software, which is a leading decision support tool based on the American College of Radiology (ACR) Appropriateness Criteria.
Recommendations that appear in the CDS tool are a computerized version of guidelines created by the American College of Radiology (ACR). The guidelines score the appropriateness of a scan order for a given health indication, where indications include common symptoms and diagnosis keywords, such as "acute headache." In particular, indication-scan pairs are assigned an "appropriateness rating" from 1-9. Scores 1-3 are 'usually not appropriate,' 4-6 are 'may be appropriate,' and 7-9 are 'usually appropriate.'
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Treatment | Experimental | Clinical Decision Support (CDS) |
|
| Control | No Intervention | Will not receive Clinical Decision Support (CDS) |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Clinical Decision Support (CDS) | Other | A best practices alert (BPA) pop-up screen providing CDS will appear at physician sign-off for all scans scored 1-3, and scans scored 4-6 for which an alternative scan scored 7-9 exists. This screen will show the appropriateness score of the original scan order, and will display any alternative scans that are scored 7-9 for the same indications and patient characteristics. It will also display a link to relevant ACR documentation relevant to the selected scan and indication. Any time the pop-up alert appears, a checkbox removing the selected scan from unsigned orders will be checked by default. |
| Measure | Description | Time Frame |
|---|---|---|
| number of "non-advised" scans ordered per visiting provider | "non-advised" scans are (a) all magnetic resonance (MR) or computed tomography (CT) scans that ACR Select rates 1-3 ("usually not appropriate"), and (b) all MR or CT scans rated 4-6 ("may be appropriate") for which an alternative scan (MR, CT, or other modality) rated 7-9 ("usually appropriate") exists | first 365 days after CDS is turned on for the treatment group |
| Measure | Description | Time Frame |
|---|---|---|
| Number of scans ordered per visiting provider that ACR Select rates 1-3 ("usually not appropriate") | includes magnetic resonance (MR) and computed tomography (CT) scans scored by ACR Select | first 365 days after CDS is turned on for the treatment group |
| Number of scans ordered per visiting provider that ACR Select rates 4-6 ("may be appropriate") for which an alternative scan (MR, CT, or other modality) rated 7-9 ("usually appropriate") exists |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Amy Finkelstein, PhD | Massachusetts Institute of Technology | Principal Investigator |
| Madhu Mazumdar, Mazumdar | The Mount Sinai Health System | Principal Investigator |
| Bruce Darrow, MD, PhD | The Mount Sinai Health System | Principal Investigator |
| Joseph Kannry, MD | The Mount Sinai Health System | Principal Investigator |
| David S Mendelson, MD FACR | The Mount Sinai Health System | Principal Investigator |
| Joseph Doyle, PhD | Massachusetts Institute of Technology | Principal Investigator |
| Jesse Shapiro, PhD | Massachusetts Institute of Technology | Principal Investigator |
| Laura Feeney, MA | Massachusetts Institute of Technology | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Mount Sinai Queens | Long Island City | New York | 11102 | United States | ||
| Mount Sinai Hospital |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| Background | Centers for Medicare & Medicaid Services, 2013. National Health Expenditures 2013 Highlights. Centers for Medicare & Medicaid Services. | ||
| 24638246 | Background | Callaghan BC, Kerber KA, Pace RJ, Skolarus LE, Burke JF. Headaches and neuroimaging: high utilization and costs despite guidelines. JAMA Intern Med. 2014 May;174(5):819-21. doi: 10.1001/jamainternmed.2014.173. No abstract available. | |
| Background | Sherman, D., 2012. Stemming the tide of overtreatment in U.S. healthcare. Reuters. Feb 16, 2012. | ||
| Background | U.S. Government Accountability Office, 2008. Medicare Part B Imaging Services: Rapid Spending Growth and Shift to Physician Offices Indicate Need for CMS to Consider Additional Management Practices [WWW Document]. URL http://www.gao.gov/products/GAO-08-452 (accessed 2.23.15). |
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includes magnetic resonance (MR) and computed tomography (CT) scans scored by ACR Select |
| first 365 days after CDS is turned on for the treatment group |
| New York |
| New York |
| 10029 |
| United States |
| Background | Consumer Reports, 2015. Surprising Dangers of CT Scans and X-rays - Consumer Reports [WWW Document]. URL http://www.consumerreports.org/cro/magazine/2015/01/the-surprising-dangers-of-ct-sans-and-x-rays/index.htm (accessed 2.25.15). |
| Background | Dehn, T.G., O'Connell, B., Hall, R.N., Moulton, T., 2000. Appropriateness of imaging examinations: current state and future approaches. Imaging Econ 13, 18-26. |
| 21385821 | Background | Georgiou A, Prgomet M, Markewycz A, Adams E, Westbrook JI. The impact of computerized provider order entry systems on medical-imaging services: a systematic review. J Am Med Inform Assoc. 2011 May 1;18(3):335-40. doi: 10.1136/amiajnl-2010-000043. Epub 2011 Mar 8. |
| Background | Medicare Payment Advisory Commission, 2014. Health Care Spending and the Medicare Program. MedPAC. |
| 21517834 | Background | Shreibati JB, Baker LC. The relationship between low back magnetic resonance imaging, surgery, and spending: impact of physician self-referral status. Health Serv Res. 2011 Oct;46(5):1362-81. doi: 10.1111/j.1475-6773.2011.01265.x. Epub 2011 Apr 21. |
| 18046031 | Background | Brenner DJ, Hall EJ. Computed tomography--an increasing source of radiation exposure. N Engl J Med. 2007 Nov 29;357(22):2277-84. doi: 10.1056/NEJMra072149. No abstract available. |
| Background | Pitts, J., 2014. The Protecting Access to Medicare Act of 2014. |