Clinical Decision Support (CDS) for Radiology Imaging

NCT ID: NCT02996045

Last Updated: 2020-07-15

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

3511 participants

Study Classification

INTERVENTIONAL

Study Start Date

2016-12-15

Study Completion Date

2018-12-31

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The goal of the study is to determine whether clinical decision support (CDS) for radiology affects the number, type, or appropriateness of targeted high-cost radiology imaging orders (i.e. magnetic resonance (MR), computed tomography (CT), nuclear medicine (NM) and Positron Emission Tomography (PET) scans). The CDS will be delivered to physicians in the Aurora Health Care system. It will be delivered in Epic, an industry-standard electronic medical record software, through ACR Select, 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). The ACR Select tool rates imaging orders 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

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

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.

In particular, there is widespread concern in both the medical profession and the public sector of the cost and health risks of "over-scanning". Estimates suggest that as many as 30% of imaging in the U.S. are unnecessary. 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 ; the indirect costs are likely considerably greater, since imaging often triggers additional follow up care. It is also estimated that about 2 percent of cancers in the U.S. are due to CT use.

Reflecting this concern, starting in 2018 Medicare will no longer reimburse for high-cost scans unless ordered using an "acceptable" Clinical Decision Support (CDS) system. Despite this upcoming policy change, the investigators 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, CT, NM, and PET scans), to healthcare providers treating patients in settings affiliated with the Aurora Health Care system headquartered in Wisconsin. 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: half will receive the CDS, while the remaining half of providers in the study will serve as the control group.

The CDS will be delivered through the order-entry software, Epic, through ACR Select 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 digitized 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.'

To learn more about how CDS impacts ordering behavior, the investigators will investigate whether those exposed to CDS orders in ways that avoids CDS, such as placing them via clerical workers or choosing different indications. The investigators plan to analyze outcomes across different settings (Inpatient vs Outpatient and in the ED). Last, if the investigators find effects of CDS on ordering they will examine effects on utilization, including length of inpatient stays.

The primary outcome is the number of imaging orders that would produce a best-practice alert suggesting a change. The investigators conducted power calculations using a 7-month intervention window and 6 months of pre-period data to calculate the lag of the dependent variable as a control. With this control, the minimum detectible effect is a 13% reduction compared to a mean of 11 scans over that time period.

In addition, the investigators will investigate the number of scans (all high-cost, high-cost scoring 1-3, high-cost scoring 4-6, and substitution to low-cost scans. The investigators will also investigate whether treatment group orders in ways that avoids the CDS, such as placing them via clerical workers or choosing different indications. The investigators plan to analyze outcomes across different settings (Inpatient vs Outpatient and in the ED). Last, if the investigators find effects of CDS on ordering they will examine effects on utilization, including length of inpatient stays.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

CT, MR, NM, and PET Image Orders

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

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 1-6, and scans scored 7-8 for which an alternative scan scored 8-9 exists.

This screen will show the appropriateness score of the original scan order, and will display up to 7 alternative scans that are scored \>4 and greater than or equal to the original score for the same indications and patient characteristics. It will also display a link to relevant ACR documentation relevant to the selected scan and indication.

Control

Will not receive Clinical Decision Support (CDS)

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

Clinical Decision Support (CDS)

A best practices alert (BPA) pop-up screen providing CDS will appear at physician sign-off for all scans scored 1-6, and scans scored 7-8 for which an alternative scan scored 8-9 exists.

This screen will show the appropriateness score of the original scan order, and will display up to 7 alternative scans that are scored \>4 and greater than or equal to the original score for the same indications and patient characteristics. It will also display a link to relevant ACR documentation relevant to the selected scan and indication.

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

* Medical provider actively employed at Aurora with a valid Epic log-in.
* Is a Medical Doctor (MD), Doctors of Osteopathic Medicine (DO), podiatrist (DPM), nurse practitioner (NP), physician assistant (PA), or certified nurse midwife (CNM)
* Has imaging order permissions at Aurora Health Care.
* Has at least one high- or low-cost imaging order in the year from November 1, 2015 to November 1, 2016 or is medical resident who joined Aurora since that time.

Exclusion Criteria

* Opted out of the study prior to November 24, 2016
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Wake Forest University Health Sciences

OTHER

Sponsor Role collaborator

Laura and John Arnold Foundation

OTHER

Sponsor Role collaborator

Massachusetts Institute of Technology

OTHER

Sponsor Role collaborator

Abdul Latif Jameel Poverty Action Lab

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Responsibility Role SPONSOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

Joseph Doyle, PhD

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Amy Finkelstein, PhD

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Sarah Reimer, MD

Role: PRINCIPAL_INVESTIGATOR

Wake Forest University Health Sciences

Laura Feeney, MA

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Sarah Abraham

Role: PRINCIPAL_INVESTIGATOR

Massachusetts Institute of Technology

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Aurora Health Care

Milwaukee, Wisconsin, United States

Site Status

Countries

Review the countries where the study has at least one active or historical site.

United States

References

Explore related publications, articles, or registry entries linked to this study.

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)

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)

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)

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

Reference Type BACKGROUND

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

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

Reference Type BACKGROUND

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

Reference Type BACKGROUND

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

JPAL-5002

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.

CT Data Collection Study
NCT03589664 COMPLETED