PROJECT SUMMARY/ABSTRACT Background: Efforts to measure, report, and incentivize the quality of healthcare are now widespread within the Veterans Health Administration (VA), Medicare, and private healthcare settings—but common musculoskeletal disorders including carpal tunnel syndrome (CTS) have been omitted from these efforts due to a lack of valid, feasible quality measures. Although clinical practice guidelines for the diagnosis and management of CTS have recently been published, no valid and feasible measures of these guidelines currently exist. Also, great interest exists across healthcare specialties in developing and implementing patient reported outcome measure-based quality measures (PRO-QMs). Before implementing process or outcome- based quality measures, it is essential to determine if they are valid and produce actionable information. Significance/Impact: VA is increasingly becoming a purchaser of community-based healthcare, making it essential to evaluate if healthcare quality measures are valid for both VA and cross-system comparisons. This proposal is aligned with VA ORD and HSR&D priorities including quality and safety, supporting the development of value-based payment models, methods for monitoring quality and safety of non-VA purchased care, and evaluating measures and methods to compare the quality of VA and non-VA care. The continued absence of valid CTS quality measures leaves all stakeholders without any means to identify quality gaps, evaluate the impacts of quality improvement initiatives, or to enact performance-based reimbursement or purchasing initiatives. Innovation: Enthusiasm for implementing PRO-QMs has outpaced careful consideration of issues related to logistics, statistics, measurement, and unintended consequences. Currently, methods are under-developed to evaluate if sufficient variability in outcomes exist to justify implementation of PRO-QMs. The work proposed in Aim 2 will significantly advance the conceptual and statistical basis of methods to examine outcome variance for quality measurement applications. In Aim 3, we propose to examine associations between fully operationalized and pilot tested process quality measures (Aim 1) with PROMs collected for Aim 2. Information about each process measure's predictive validity is essential for future prioritization and implementation. Specific Aims: Aim 1 – Complete development and validity testing of process-oriented quality measures for the treatment of CTS using diverse administrative datasets. Aim 2 – Evaluate the measurement characteristics of PRO-QMs for CTS. Aim 3 – Test the predictive validity of promising process measures from Aim 1 Methodology: Existing healthcare data from VA, Medicare, and 3 university and community systems will be used to examine the measurement characteristics of four currently proposed, but inadequately tested, CTS process quality measures (Aim 1). Patient reported outcome measures will be collected from 2000 patients in 5 diverse hea...