Dataset Information

Use of Medicare Data to Identify Team-based Primary Care: Is it Possible?

ABSTRACT: BACKGROUND:It is unclear whether Medicare data can be used to identify type and degree of collaboration between primary care providers (PCPs) [medical doctors (MDs), nurse practitioners, and physician assistants] in a team care model. METHODS:We surveyed 63 primary care practices in Texas and linked the survey results to 2015 100% Medicare data. We identified PCP dyads of 2 providers in Medicare data and compared the results to those from our survey. Sensitivity, specificity, and positive predictive value (PPV) of dyads in Medicare data at different threshold numbers of shared patients were reported. We also identified PCPs who work in the same practice by Social Network Analysis (SNA) of Medicare data and compared the results to the surveys. RESULTS:With a cutoff of sharing at least 30 patients, the sensitivity of identifying dyads was 27.8%, specificity was 91.7%, and PPV 72.2%. The PPV was higher for MD-nurse practitioner/physician assistant pairs (84.4%) than for MD-MD pairs (61.5%). At the same cutoff, 90% of PCPs identified in a practice from the survey were also identified by SNA in the corresponding practice. In 5 of 8 surveyed practices with at least 3 PCPs, about ?20% PCPs identified in the practices by SNA of Medicare data were not identified in the survey. CONCLUSIONS:Medicare data can be used to identify shared care with low sensitivity and high PPV. Community discovery from Medicare data provided good agreement in identifying members of practices. Adapting network analyses in different contexts needs more validation studies.

SUBMITTER: Kuo YF

PROVIDER: S-EPMC6791761 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Use of Medicare Data to Identify Team-based Primary Care: Is it Possible?

Kuo Yong-Fang YF Raji Mukaila A MA Lin Yu-Li YL Ottenbacher Margaret E ME Jupiter Daniel D Goodwin James S JS

Medical care 20191101 11

<h4>Background</h4>It is unclear whether Medicare data can be used to identify type and degree of collaboration between primary care providers (PCPs) [medical doctors (MDs), nurse practitioners, and physician assistants] in a team care model.<h4>Methods</h4>We surveyed 63 primary care practices in Texas and linked the survey results to 2015 100% Medicare data. We identified PCP dyads of 2 providers in Medicare data and compared the results to those from our survey. Sensitivity, specificity, and ...[more]

PMID: 31568165

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Project description:BackgroundOwing to the shortage of medical professionals, as well as demographic and structural challenges, new care models have emerged to find innovative solutions to counter medical undersupply. Team-based primary care using medical delegation appears to be a promising approach to address these challenges; however, it demands efficient communication structures and mechanisms to reinsure patients and caregivers receive a delegated, treatment-related task. Digital health care technologies hold the potential to render these novel processes effective and demand driven.ObjectiveThe goal of this study is to recreate the daily work routines of general practitioners (GPs) and medical assistants (MAs) to explore promising approaches for the digital moderation of delegation processes and to deepen the understanding of subjective and perceptual factors that influence their technology assessment and use.MethodsWe conducted a combination of 19 individual and group interviews with 12 GPs and 14 MAs, seeking to identify relevant technologies for delegation purposes as well as stakeholders' perceptions of their effectiveness. Furthermore, a web-based survey was conducted asking the interviewees to order identified technologies based on their assessed applicability in multi-actor patient care. Interview data were analyzed using a three-fold inductive coding procedure. Multidimensional scaling was applied to analyze and visualize the survey data, leading to a triangulation of the results.ResultsOur results suggest that digital mediation of delegation underlies complex, reciprocal processes and biases that need to be identified and analyzed to improve the development and distribution of innovative technologies and to improve our understanding of technology use in team-based primary care. Nevertheless, medical delegation enhanced by digital technologies, such as video consultations, portable electrocardiograms, or telemedical stethoscopes, can counteract current challenges in primary care because of its unique ability to ensure both personal, patient-centered care for patients and create efficient and needs-based treatment processes.ConclusionsTechnology-mediated delegation appears to be a promising approach to implement innovative, case-sensitive, and cost-effective ways to treat patients within the paradigm of primary care. The relevance of such innovative approaches increases with the tremendous need for differentiated and effective care, such as during the ongoing COVID-19 pandemic. For the successful and sustainable adoption of innovative technologies, MAs represent essential team members. In their role as mediators between GPs and patients, MAs are potentially able to counteract patients' resistance toward using innovative technology and compensate for patients' limited access to technology and care facilities.

Project description:BackgroundThe science of effective teams is well documented; far less is known, however, about how specific team configurations may impact primary care team effectiveness. Further, teams experiencing frequent personnel changes (perhaps as a consequence of poor implementation) may have difficulty delivering effective, continuous, well-coordinated care. This study aims to examine the extent to which primary care clinics in the Veterans Health Administration have implemented team configurations consistent with recommendations based on the Patient-Centered Medical Home model and the extent to which adherence to said recommendations, team stability, and role stability impact healthcare quality. Specifically, we expect to find better clinical outcomes in teams that adhere to recommended team configurations, teams whose membership and configuration are more stable over time, and teams whose clinical manager role is more stable over time.Methods/designWe will employ a combination of social network analysis and multilevel modeling to conduct a database review of variables extracted from the Veterans Health Administration's Team Assignments Report (TAR) (one of the largest, most diverse existing national samples of primary care teams (nteams > 7000)), as well as other employee and clinical data sources. To ensure the examination of appropriate clinical outcomes, we will enlist a team of subject matter experts to select a concise set of clear, prioritized primary care performance metrics. We will accomplish this using the Productivity Measurement and Enhancement System, an evidence-based methodology for developing and implementing performance measurement.DiscussionWe are unaware of other studies of healthcare teams that consider team size, composition, and configuration longitudinally or with sample sizes of this magnitude. Results from this study can inform primary care team implementation policy and practice in both private- and public-sector clinics, such that teams are configured optimally, with adequate staffing, and the right mix of roles within the team.Trial registrationNot applicable-this study does not involve interventions on human participants.

Dataset Information

Use of Medicare Data to Identify Team-based Primary Care: Is it Possible?

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Use of Medicare Data to Identify Team-based Primary Care: Is it Possible?

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