Budget impact of the Walk With Ease program for knee osteoarthritis.

Objective: Walk With Ease (WWE) is an effective low-cost walking program. We estimated the budget impact of implementing WWE in persons with knee osteoarthritis (OA) as a measure of affordability that can inform payers' funding decisions. Methods: We estimated changes in two-year healthcare costs with and without WWE. We used the Osteoarthritis Policy (OAPol) Model to estimate per-person medical expenditures. We estimated total and per-member-per-month (PMPM) costs of funding WWE for a hypothetical insurance plan with 75,000 members under two conditions: 1) all individuals aged 45+ with knee OA eligible for WWE, and 2) inactive and insufficiently active individuals aged 45+ with knee OA eligible. In sensitivity analyses, we varied WWE cost and efficacy and considered productivity costs. Results: With eligibility unrestricted by activity level, implementing WWE results in an additional $1,002,408 to the insurance plan over two years ($0.56 PMPM). With eligibility restricted to inactive and insufficiently active individuals, funding WWE results in an additional $571,931 over two years ($0.32 PMPM). In sensitivity analyses, when per-person costs of $10 to $1000 were added with 10-50% decreases in failure rate (enhanced sustainability of WWE benefits), two-year budget impact varied from $242,684 to $6,985,674 with unrestricted eligibility and from -$43,194 (cost-saving) to $4,484,122 with restricted eligibility. Conclusion: Along with the cost-effectiveness of WWE at widely accepted willingness-to-pay thresholds, these results can inform payers in deciding to fund WWE. In the absence of accepted thresholds to define affordability, these results can assist in comparing the affordability of WWE with other behavioral interventions.

Causal relationships between pain, medical treatments, and knee osteoarthritis: A graphical causal model to guide analyses.

OBJECTIVE: Randomized controlled trials (RCTs) are a gold standard for estimating the benefits of clinical interventions, but their decision-making utility can be limited by relatively short follow-up time. Longer-term follow-up of RCT participants is essential to support treatment decisions. However, as time from randomization accrues, loss to follow-up and competing events can introduce biases and require covariate adjustment even for intention-to-treat effects. We describe a process for synthesizing expert knowledge and apply this to long-term follow-up of an RCT of treatments for meniscal tears in patients with knee osteoarthritis (OA). METHODS: We identified 2 post-randomization events likely to impact accurate assessment of pain outcomes beyond 5 years in trial participants: loss to follow-up and total knee replacement (TKR). We conducted literature searches for covariates related to pain and TKR in individuals with knee OA and combined these with expert input. We synthesized the evidence into graphical models. RESULTS: We identified 94 potential covariates potentially related to pain and/or TKR among individuals with knee OA. Of these, 46 were identified in the literature review and 48 by expert panelists. We determined that adjustment for 50 covariates may be required to estimate the long-term effects of knee OA treatments on pain. CONCLUSION: We present a process for combining literature reviews with expert input to synthesize existing knowledge and improve covariate selection. We apply this process to the long-term follow-up of a randomized trial and show that expert input provides additional information not obtainable from literature reviews alone.

An approach to virtual clinical trial site visits: Lessons from the MeTeOR trial.

Objective: To provide a framework for conducting clinical trial site visits virtually over videoconference, and to report on our experience doing so during the twelve-year follow-up of the Meniscal Tear in Osteoarthritis Research (MeTeOR) trial. Design: Using published FDA guidance and prior literature, we created a structure for virtual site visits that prioritized monitoring for protocol compliance, safety, and data integrity. We conducted site visits in three stages: preparation for the visit, the virtual meeting itself, and follow-up. The preparation phase involved a review of relevant site-specific documents and a written report on the findings prior to the visit. The virtual visit itself was focused on any questions the site staff had about the pre-visit report, observing a mock study visit, touring physical spaces, and understanding the site staff's work environment. In the follow-up phase, we wrote a post-visit report summarizing the discussion during the visit and feedback given by the coordinating site. Results: We found that the virtual site visits conducted as part of the MeTeOR trial follow-up ran smoothly. Although we could not directly compare in-person and virtual site visits, site staff unanimously appreciated the efficiency and effectiveness of the virtual site visits. We noted that displaying physical workspaces over videoconferencing was difficult, and a notable drawback to this method. Conclusions: To our knowledge, this is the first published framework for conducting virtual clinical trial site visits. Conducting these visits virtually confer several advantages in terms of time, money, and efficiency.

Toward Reducing Health Information Inequities in the Caribbean: Our Experience Building a Participatory Health Informatics Project.

Precision medicine seeks to leverage technology to improve the health for all individuals. Successful health information systems rely fundamentally on the integration and sharing of data from a range of disparate sources. In many settings, basic infrastructure inequities exist that limit the usefulness of health information systems. We discuss the work of the Yale Transdisciplinary Collaborative Center for Health Disparities focused on Precision Medicine, which aims to improve the health of people in the Caribbean and Caribbean diaspora by leveraging precision medicine approaches. We describe a participatory informatics approach to sharing data as a potential mechanism to reducing inequities in the existing data infrastructure.