Population-Based Patient-Centric Care: Comprehensive Preventive Cancer Screening Using Health IT

NCT ID: NCT01372527

Last Updated: 2014-10-03

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 103870 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2011-06-30
• Study Completion Date: 2013-01-31

Brief Summary

Although there is considerable evidence that current health IT can improve certain elements of care, the most effective and efficient implementation of health IT systems for primary care population management are not currently known. Indeed, while many systems currently take a "case-management" approach to identify and address clinical care issues for high risk patients, no systems to our knowledge apply a risk-based approach that accounts both for adverse clinical outcome risk (e.g. breast cancer in a woman who has not had indicated screening for 4 years) and for clinical process risk (e.g. the likelihood that a specific patient will ignore a reminder letter and would therefore benefit from direct phone or in person contact). The investigators propose to directly test the hypothesis that implementing a health IT platform that 1) provides novel risk-based decision support using data derived from the electronic health record (EHR) and 2) leverages each clinician's unique knowledge of his or her patient panel will result in more effective and more efficient population-based primary care. The investigators will test this hypothesis in a practice-randomized clinical trial of preventive cancer screening within our primary care Practice-Based Research Network (PBRN).

Detailed Description

In prior NIH-funded research, the investigators have demonstrated the efficacy of an IT-based population management system to improve breast cancer screening (NCI R21 CA121908). The investigators will expand our current IT platform from this single function (breast cancer screening) to a package of cancer prevention actions (breast, cervical, and colorectal cancer screening) and examine the added benefit of population-level preventive cancer care that is directed by specific clinician knowledge of individual patient needs. Moreover, rather than compare our system to currently sub-optimal "usual care" practice, our goal is to test whether the impact of our intervention exceeds the current state-of-the-art of IT-based population management. Therefore, control group practices will receive augmented standard care defined as a population-level reminder system with automated patient contacts.

In augmented standard care control practices, the investigators will implement a system that includes: 1) a population-based perspective to identify all eligible patients overdue for screening, 2) an automated, centralized process to contact selected patients by letter, 3) a result management system that automatically tracks test scheduling and completion, 4) a web-based, easily accessible tool allowing practice personnel to contact patients not completing testing, and 5) use of patient navigators for high risk patients not responding to initial outreach. In the control arm, the process of escalating the reminder intervention from a letter, to contact by phone call, to a patient navigator, will occur in a standard algorithmic fashion without provider input. While not yet the standard of care nationwide, prior studies have proven the efficacy of such an approach. In intervention practices, the investigators will enhance augmented standard care by implementing a novel system that will enable physicians and clinical population managers to individualize care for each patient in their panel using tools to classify and organize patients by their clinical attributes. The investigators hypothesize that this personalized identification of patients by both their clinical outcome and clinical process risk status will improve the efficacy and efficiency of resource allocation decisions. The key additions to the health IT system for intervention practices will be: 1) a clinical systems IT platform to organize and present clinical data for each clinician's patient panel, 2) an accessible Web-based tool allowing clinicians (physicians and clinical population managers) to view, organize, and investigate their patient panels, and 3) a simple process where the clinician can make a tailored screening decision and designate the method of clinical intervention based upon the patient's risk profile.

Conditions

Breast Cancer; Colorectal Cancer; Cervical Cancer

Study Design

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

Study Groups

TopCare Intervention

The TOP-CARE intervention will be based on a medical informatics platform that:

1. Identifies all patients eligible for any of the three cancer screening programs

2. Links patients with a specific clinician

3. Offers a visit-independent method for clinicians to review panels of their eligible patients

4. For patients due for one or more cancer screenings, clinicians will access a web-based informatics tool to:

1. Screen their panel based upon risk

2. Defer patients, document exclusions, and update the EHR

3. Order a screening test with patient information material based upon the patient's risk profile and automatically initiate the process of:

1. Informing the patient by letter of the need to schedule a test, educating the patient with respect to the benefits of cancer screening, and properly documenting the transaction in the patient's EHR, or

2. Referral to a patient navigator for patients most likely to benefit from this more intensive approach

Group Type: EXPERIMENTAL

TopCare: Use of provider knowledge vs. automated system

Intervention Type: OTHER

We will be evaluating the system in practices where providers are involved in determining to contact a patient, including the most appropriate outreach method, compared with practices where the system is fully automated without provider input.

Augmented Standard Care

In augmented standard care control practices, we will implement a system that includes: 1) a population-based perspective to identify all eligible patients overdue for screening, 2) an automated, centralized process to contact selected patients by letter, 3) a result management system that automatically tracks test scheduling and completion, 4) a web-based, easily accessible tool allowing practice personnel to contact patients not completing testing, and 5) use of patient navigators for high risk patients not responding to initial outreach. In the control arm, the process of escalating the reminder intervention from a letter, to contact by phone call, to a patient navigator, will occur in a standard algorithmic fashion without provider input.

Group Type: ACTIVE_COMPARATOR

TopCare: Use of provider knowledge vs. automated system

Intervention Type: OTHER

We will be evaluating the system in practices where providers are involved in determining to contact a patient, including the most appropriate outreach method, compared with practices where the system is fully automated without provider input.

Interventions

TopCare: Use of provider knowledge vs. automated system

We will be evaluating the system in practices where providers are involved in determining to contact a patient, including the most appropriate outreach method, compared with practices where the system is fully automated without provider input.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Breast cancer: Women 42-74 years old
• Cervical cancer: Women 21-65 years old
• Colorectal cancer: Women and men 52-75 years old

Exclusion Criteria

• Breast cancer: History of bilateral mastectomy in their EHR
• Cervical cancer: History of total hysterectomy in their EHR
• Colorectal cancer: History of total colectomy in their EHR

• Minimum Eligible Age: 21 Years
• Maximum Eligible Age: 75 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Massachusetts General Hospital

OTHER

Sponsor Role: lead

Responsible Party

Steven Atlas

Principal Investigator

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Steven J Atlas, MD, MPH

Role: PRINCIPAL_INVESTIGATOR

Massachusetts General Hospital

Locations

Massachusetts General Hospital

Boston, Massachusetts, United States

Countries

United States

References

Atlas SJ, Zai AH, Ashburner JM, Chang Y, Percac-Lima S, Levy DE, Chueh HC, Grant RW. Non-visit-based cancer screening using a novel population management system. J Am Board Fam Med. 2014 Jul-Aug;27(4):474-85. doi: 10.3122/jabfm.2014.04.130319.

Reference Type: RESULT

PMID: 25002002 (View on PubMed)

Zai AH, Kim S, Kamis A, Hung K, Ronquillo JG, Chueh HC, Atlas SJ. Applying operations research to optimize a novel population management system for cancer screening. J Am Med Inform Assoc. 2014 Feb;21(e1):e129-35. doi: 10.1136/amiajnl-2013-001681. Epub 2013 Sep 16.

Reference Type: RESULT

PMID: 24043318 (View on PubMed)

Other Identifiers

R18HS018161

Identifier Type: AHRQ

Identifier Source: org_study_id

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