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The American Journal of Managed Care December 2015
Interest in Mental Health Care Among Patients Making eVisits
Steven M. Albert, PhD; Yll Agimi, PhD; and G. Daniel Martich, MD
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Ilana Graetz, PhD; Jie Huang, PhD; Richard Brand, PhD; Stephen M. Shortell, PhD, MPH, MBA; Thomas G. Rundall, PhD; Jim Bellows, PhD; John Hsu, MD, MBA, MSCE; Marc Jaffe, MD; and Mary E. Reed, DrPH
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Health IT-Assisted Population-Based Preventive Cancer Screening: A Cost Analysis
Douglas E. Levy, PhD; Vidit N. Munshi, MA; Jeffrey M. Ashburner, PhD, MPH; Adrian H. Zai, MD, PhD, MPH; Richard W. Grant, MD, MPH; and Steven J. Atlas, MD, MPH
An Introduction to the Health IT Issue
Jeffrey S. McCullough, PhD, Assistant Professor, University of Minnesota School of Public Health; Guest Editor-in-Chief for the health IT issue of The American Journal of Managed Care
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Mark Reid, PhD; Samuel Cohen, MD; Hank Wang, MD, MSHS; Aung Kaung, MD; Anish Patel, MD; Vartan Tashjian, BS; Demetrius L. Williams, Jr, MPA; Bibiana Martinez, MPH; and Brennan M.R. Spiegel, MD, MSHS
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Katherine K. Kim, PhD, MPH, MBA; Robert S. Rudin, PhD; and Machelle D. Wilson, PhD
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Health IT-Assisted Population-Based Preventive Cancer Screening: A Cost Analysis

Douglas E. Levy, PhD; Vidit N. Munshi, MA; Jeffrey M. Ashburner, PhD, MPH; Adrian H. Zai, MD, PhD, MPH; Richard W. Grant, MD, MPH; and Steven J. Atlas, MD, MPH
An automated cancer screening outreach tool implemented in a mature health information technology environment can achieve cost savings through reduced clinician time devoted to screening efforts.
Novel health information technology (IT)-based strategies harnessing patient registry data seek to improve care at a population level. We analyzed costs from a randomized trial of 2 health IT strategies to improve cancer screening compared with usual care from the perspective of a primary care network.

Study Design: Monte Carlo simulations were used to compare costs across management strategies.

Methods: We assessed the cost of the software, materials, and personnel for baseline usual care (BUC) compared with augmented usual care (AUC [ie, automated patient outreach]) and augmented usual care with physician input (AUCPI [ie, outreach mediated by physicians’ knowledge of their patient panels]) over 1 year.

Results: AUC and AUCPI each reduced the time physicians spent on cancer screening by 6.5 minutes per half-day clinical session compared with BUC without changing cancer screening rates. Assuming the value of this time accrues to the network, total costs of cancer screening efforts over the study year were $3.83 million for AUC, $3.88 million for AUCPI, and $4.10 million for BUC. AUC was cost-saving relative to BUC in 87.1% of simulations. AUCPI was cost-saving relative to BUC in 82.5% of simulations. Ongoing per patient costs were lower for both AUC ($35.63) and AUCPI ($35.58) relative to BUC ($39.51).

Conclusions: Over the course of the study year, the value of reduced physician time devoted to preventive cancer screening outweighed the costs of the interventions. Primary care networks considering similar interventions will need to capture adequate physician time savings to offset the costs of expanding IT infrastructure.

Am J Manag Care. 2015;21(12):885-891
Take-Away Points
We assessed whether 2 approaches to technology-assisted, population-based cancer screening outreach—each neutral with respect to improving screening rates— changed the cost of screening promotion compared with usual care. One approach employed an algorithm to escalate outreach processes automatically. The other used physician input to target outreach more efficiently.
  • The cost of building and implementing these systems within a mature health information technology system was offset by the value of reductions in physician time devoted to cancer screening relative to usual care.
  • The physician-mediated approach reduced outreach costs relative to the algorithm- only approach, but this approach costs more because its software design was more expensive.
In 2011 and 2012, the Massachusetts General Primary Care Practice-Based Research Network conducted the TopCare clinical trial comparing 2 novel information technology (IT)-based population health management strategies, with each harnessing patient registry data to improve preventive screening rates for cancer. The trial was motivated by the low cancer screening rates observed nationally relative to US Preventive Services Task Force (USPSTF) recommendations.1 At the same time, the federal government had committed to expanding the country’s use of health IT and, subsequently, the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 was designed to improve, among other things, the quality and efficiency of healthcare.2

At the conclusion of the TopCare trial, there were high rates of cancer screening in both intervention strategies, but there were no differences of statistical or practical significance in overall screening rates between the study arms.3 However, the TopCare intervention was specifically designed to reduce clinician burden by managing cancer screening outside the context of the face-to-face office visit. Thus, whereas the TopCare population health management tools were unsuccessful at improving cancer screening rates, there remained the possibility that they would improve the efficiency of care. In the current study, we present a cost analysis conducted in parallel with the TopCare clinical trial assessing the relative efficiency of the 2 novel intervention strategies compared with pre-intervention usual care.

Overview of the TopCare Clinical Trial

The results of the TopCare clinical trial are reported elsewhere.3 Here we describe the outcomes of the trial, as well as the cost-relevant details surrounding the development of the intervention and the changes in work flow it required. In summary, the trial took place between June 2011 and June 2012 at 18 primary care practices associated with Massachusetts General Hospital (MGH). The study was designed to compare 2 IT-based population health interventions: 1) an automated patient outreach program encouraging patients to schedule breast, cervical, and/or colorectal cancer screenings; and 2) a strategy that leveraged physicians’ knowledge of their patients to streamline cancer screening outreach. The present analysis compared the 1-year costs of these 2 strategies with each other, as well as with usual care as it existed before the introduction of the health IT system. The TopCare trial and its embedded cost analysis were approved by the Partners HealthCare institutional review board.

Prior to the clinical trial, screening reminders came when a physician, accessing a patient’s electronic health record, usually as part of a clinical visit, would see an alert indicating that a patient was overdue for screening. We term this practice “baseline usual care” (BUC) (Figure).

The IT system tested in the trial included a patient registry that continuously identified patients overdue for a breast, cervical, or colorectal cancer screening according to USPSTF guidelines and tracked both scheduled and completed tests. In the clinical trial, the study arm called “augmented usual care” (AUC) used an automated outreach process in which overdue patients were first sent letters asking them to directly schedule an overdue test. They could also contact a call center if they had already received screening (eg, outside the care network), if they did not wish to be screened, or if they were no longer eligible for screening. Patients who did not make appointments or contact the call center were transferred by the IT tool to the list of a delegate in the provider’s office who could make outgoing reminder calls to the patient. If still overdue after 4 months, patients at high risk for nonadherence were transferred to patient navigators who would work closely with the patients to complete screening. Otherwise, patients still overdue were inactivated for a period of 8 months before being re-contacted.

For the other study arm, “augmented usual care with provider input” (AUCPI), the IT system regularly provided physicians with a list of patients believed to be overdue for screening. Physicians could use personal knowledge of their patients to update screening status or triage them for personalized letter, phone, or navigator outreach. The provider could also defer screening if, for example, they knew the patient had previously declined. If a provider did not act within 8 weeks, the patient defaulted to the automated outreach used in the AUC arm. The AUCPI intervention was designed to be faster and more effective than the AUC intervention.

For the TopCare trial, 9 practices were randomized to each study arm. These practices included 88 physician full-time equivalents (FTEs) serving 103,870 patients eligible for screening according to USPSTF guidelines during the 1-year trial. The trial found no significant difference in overall screening completion across the 2 arms of the study (81.6% vs 81.4%).3 Furthermore, the 2 novel programs did not significantly improve screening rates compared with BUC. However, both interventions did alter work flows, shifting cancer screening activities away from physician visits, raising the possibility of cost savings compared with BUC.

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