Clinical Decision Support (CDS) for Outpatient Radiology Imaging

NCT ID: NCT02578290

Last Updated: 2017-01-24

Basic Information

• Recruitment Status: TERMINATED
• Clinical Phase: NA
• Total Enrollment: 2033 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2015-10-31
• Study Completion Date: 2016-05-31

Brief Summary

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'.

Detailed Description

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.'

Conditions

CT and MR Image Orders

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Study Groups

Treatment

Clinical Decision Support (CDS)

Group Type: EXPERIMENTAL

Clinical Decision Support (CDS)

Intervention Type: 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.

Control

Will not receive Clinical Decision Support (CDS)

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

Clinical Decision Support (CDS)

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.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Outpatient medical provider with scan ordering permissions at Mount Sinai Hospital or Mount Sinai Queens
• Has an active ID in the Epic electronic medical record ordering system

Exclusion Criteria

• Opted out of the study prior to October 13, 2015

• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Icahn School of Medicine at Mount Sinai

OTHER

Sponsor Role: collaborator

Abdul Latif Jameel Poverty Action Lab

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Amy Finkelstein, PhD

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Madhu Mazumdar, Mazumdar

Role: PRINCIPAL_INVESTIGATOR

The Mount Sinai Health System

Bruce Darrow, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

The Mount Sinai Health System

Joseph Kannry, MD

Role: PRINCIPAL_INVESTIGATOR

The Mount Sinai Health System

David S Mendelson, MD FACR

Role: PRINCIPAL_INVESTIGATOR

The Mount Sinai Health System

Joseph Doyle, PhD

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Jesse Shapiro, PhD

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Laura Feeney, MA

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Locations

Mount Sinai Queens

Long Island City, New York, United States

Mount Sinai Hospital

New York, New York, United States

Countries

United States

References

Centers for Medicare & Medicaid Services, 2013. National Health Expenditures 2013 Highlights. Centers for Medicare & Medicaid Services.

Reference Type: 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.

Reference Type: BACKGROUND

PMID: 24638246 (View on PubMed)

Sherman, D., 2012. Stemming the tide of overtreatment in U.S. healthcare. Reuters. Feb 16, 2012.

Reference Type: 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).

Reference Type: 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).

Reference Type: 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.

Reference Type: 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.

Reference Type: BACKGROUND

PMID: 21385821 (View on PubMed)

Medicare Payment Advisory Commission, 2014. Health Care Spending and the Medicare Program. MedPAC.

Reference Type: 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.

Reference Type: BACKGROUND

PMID: 21517834 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 18046031 (View on PubMed)

Pitts, J., 2014. The Protecting Access to Medicare Act of 2014.

Reference Type: BACKGROUND

Other Identifiers

JPAL-3872

Identifier Type: -

Identifier Source: org_study_id