Stakeholder Research Priorities to Promote Implementation of Shared Decision-Making for Lung Cancer Screening: An American Thoracic Society and Veterans Affairs Health Services Research and Development Statement

Rationale: Shared decision-making (SDM) for lung cancer screening (LCS) is recommended in guidelines and required by Medicare, yet it is seldom achieved in practice. The best approach for implementing SDM for LCS remains unknown, and the 2021 U.S. Preventive Services Task Force calls for implementation research to increase uptake of SDM for LCS. Objectives: To develop a stakeholder-prioritized research agenda and recommended outcomes to advance implementation of SDM for LCS. Methods: The American Thoracic Society and VA Health Services Research and Development Service convened a multistakeholder committee with expertise in SDM, LCS, patient-centered care, and implementation science. During a virtual State of the Art conference, we reviewed evidence and identified research questions to address barriers to implementing SDM for LCS, as well as outcome constructs, which were refined by writing group members. Our committee (n = 34) then ranked research questions and SDM effectiveness outcomes by perceived importance in an online survey. Results: We present our committee's consensus on three topics important to implementing SDM for LCS: 1) foundational principles for the best practice of SDM for LCS; 2) stakeholder rankings of 22 implementation research questions; and 3) recommended outcomes, including Proctor's implementation outcomes and stakeholder rankings of SDM effectiveness outcomes for hybrid implementation-effectiveness studies. Our committee ranked questions that apply innovative implementation approaches to relieve primary care providers of the sole responsibility of SDM for LCS as highest priority. We rated effectiveness constructs that capture the patient experience of SDM as most important. Conclusions: This statement offers a stakeholder-prioritized research agenda and outcomes to advance implementation of SDM for LCS.

What Is the Return on Investment of Caring for Complex High-need, High-cost Patients?

Randomized controlled trials to improve care for complex, high-need, high-cost patients have not consistently demonstrated a relative decrease in acute care utilization or cost savings. However, the Veterans Health Administration (VHA) has been able to glean lessons from these trials and generate realistic expectations for success. Lessons include the following: (1) combining population management tools (e.g., risk scores) and clinician judgment is more effective than either alone to identify the patients best suited for intensive management; (2) treatment adherence and engagement may contribute more to preventable emergency department visits and hospitalizations than care coordination; and (3) efforts should focus on assessing for and treating those risk factors that are most amenable to intervention. Because it is unlikely that cost savings can fund add-on intensive management programs, the VHA Office of Primary Care plans to incorporate those intensive management practices that are feasible into existing patient-centered medical homes as a high reliability organization.

Outcomes of a randomized quality improvement trial for high-risk Veterans in year two

OBJECTIVE

The Veterans Health Administration (VHA) conducted a randomized quality improvement evaluation to determine whether augmenting patient-centered medical homes with Primary care Intensive Management (PIM) decreased utilization of acute care and health care costs among patients at high risk for hospitalization. PIM was cost-neutral in the first year; we analyzed changes in utilization and costs in the second year.

DATA SOURCES

VHA administrative data for five demonstration sites from August 2013 to March 2019.

DATA SOURCES

Administrative data extracted from VHA's Corporate Data Warehouse.

STUDY DESIGN

Veterans with a risk of 90-day hospitalization in the top 10th percentile and recent hospitalization or emergency department (ED) visit were randomly assigned to usual primary care vs primary care augmented by PIM. PIM included interdisciplinary teams, comprehensive patient assessment, intensive case management, and care coordination services. We compared the change in mean VHA inpatient and outpatient utilization and costs (including PIM expenses) per patient for the 12-month period before randomization and 13-24 months after randomization for PIM vs usual care using difference-in-differences.

PRINCIPAL FINDINGS

Both PIM patients (n = 1902) and usual care patients (n = 1882) had a mean of 5.6 chronic conditions. PIM patients had a greater number of primary care visits compared to those in usual care (mean 4.6 visits/patient/year vs 3.7 visits/patient/year, p < 0.05), but ED visits (p = 0.45) and hospitalizations (p = 0.95) were not significantly different. We found a small relative increase in outpatient costs among PIM patients compared to those in usual care (mean difference + $928/patient/year, p = 0.053), but no significant differences in mean inpatient costs (+$245/patient/year, p = 0.97). Total mean health care costs were similar between the two groups during the second year (mean difference + $1479/patient/year, p = 0.73).

CONCLUSIONS

Approaches that target patients solely based on the high risk of hospitalization are unlikely to reduce acute care use or total costs in VHA, which already offers patient-centered medical homes.

What Do Patient-Centered Medical Home (PCMH) Teams Need to Improve Care for Primary Care Patients with Complex Needs?

BACKGROUND

Intensive primary care (IPC) programs for patients with complex needs do not generate cost savings in most settings. Strengthening existing patient-centered medical homes (PCMH) to address the needs of these patients in primary care is a potential high-value alternative.

OBJECTIVES

Explore PCMH team functioning and characteristics that may impact their ability to perform IPC tasks; identify the IPC components that could be incorporated into PCMH teams' workflow; and identify additional resources, trainings, and staff needed to better manage patients with complex needs in primary care.

METHODS

We interviewed 44 primary care leaders, PCMH team members (providers, nurses, social workers), and IPC program leaders at 5 VA IPC sites and analyzed a priori themes using a matrix analysis approach.

RESULTS

Higher-functioning PCMH teams were described as already performing most IPC tasks, including panel management and care coordination. All sites reported that PCMH teams had the knowledge and skills to perform IPC tasks, but not with the same intensity as specialized IPC teams. Home visits/assessments and co-attending appointments were perceived as not feasible to perform. Key stakeholders identified 6 categories of supports and capabilities that PCMH teams would need to better manage complex patients, with care coordination/management and fully staffed teams as the most frequently mentioned. Many thought that PCMH teams could make better use of existing VA and non-VA resources, but might need training in identifying and using those resources.

CONCLUSIONS

PCMH teams can potentially offer certain clinic-based services associated with IPC programs, but tasks that are time intensive or require physical absence from clinic might require collaboration with community service providers and better use of internal and external healthcare system resources. Future studies should explore the feasibility of PCMH adoption of IPC tasks and the impact on patient outcomes.

The Primary Care Analytics Team: Integrating research and clinical care within the Veterans Health Administration Office of Primary Care

By designing and evaluating health system improvements and providing evidence to clinical decision-makers, embedded researchers are a critical part of a Learning Health System (LHS). In this article, we describe the evolution and mission of the Primary Care Analytics Team (PCAT), an integrated research team within the Veterans Health Administration Office of Primary Care. We discuss challenges and strategies for success in working with clinical operations partners and provide recommendations for other Learning Health Systems units embedded in large integrated health care organizations.