Assessment of Common Comorbidity Phenotypes Among Older Adults With Knee Osteoarthritis to Inform Integrated Care Models.
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2021-04
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Abstract
Objective
To establish the frequency of concordant, discordant, and clinically dominant comorbidities among Medicare beneficiaries with knee osteoarthritis (KOA) and to identify common concordant condition subgroups.Participants and methods
We used a 5% representative sample of Medicare claims data to identify beneficiaries who received a diagnosis of KOA between January 1, 2012, and September 30, 2015, and matched control group without an osteoarthritis (OA) diagnosis. Frequency of 34 comorbid conditions was categorized as concordant, discordant, or clinically dominant among those with KOA and a matched sample without OA. Comorbid condition phenotypes were characterized by concordant conditions and derived using latent class analysis among those with KOA.Results
The study sample included 203,361 beneficiaries with KOA and 203,361 non-OA controls. The largest difference in frequency between the two cohorts was for co-occurring musculoskeletal conditions (23.7% absolute difference), chronic pain syndromes (6.5%), and rheumatic diseases (4.5%), all with a higher frequency among those with knee OA. Phenotypes were identified as low comorbidity (53% of cohort with classification), hypothyroid/osteoporosis (27%), vascular disease (10%), and high medical and psychological comorbidity (10%).Conclusions
Approximately 47% of Medicare beneficiaries with KOA in this sample had a phenotype characterized by one or more concordant conditions, suggesting that existing clinical pathways that rely on single or dominant providers might be insufficient for a large proportion of older adults with KOA. These findings could guide development of integrated KOA-comorbidity care pathways that are responsive to emerging priorities for personalized, value-based health care.Type
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Lentz, Trevor A, Anne S Hellkamp, Nrupen A Bhavsar, Adam P Goode, Ajay Manhapra and Steven Z George (2021). Assessment of Common Comorbidity Phenotypes Among Older Adults With Knee Osteoarthritis to Inform Integrated Care Models. Mayo Clinic proceedings. Innovations, quality & outcomes, 5(2). pp. 253–264. 10.1016/j.mayocpiqo.2020.09.011 Retrieved from https://hdl.handle.net/10161/23310.
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Scholars@Duke

Trevor A. Lentz

Nrupen Bhavsar
I am a quantitative epidemiologist with methodological expertise in the design and analysis of observational studies that leverage data from cohort studies, registries, and the electronic health record (EHR). My background, training, and research is in the measurement and characterization of biomarkers, risk factors and treatment outcomes for chronic disease using real-world datasets. My primary research interests are in the use of novel sources of data, including the EHR, to conduct chronic disease research at the intersection of informatics, biostatistics, and epidemiology. My ongoing work aims to integrate informatics, epidemiology, and biostatistics to reduce the burden of chronic disease. I have topical expertise in multiple chronic diseases, including oncology, cardiovascular disease, and chronic kidney disease. In parallel, I have a portfolio of research that aims to understand the impact of social determinants of health, including dynamic neighborhood changes, such as gentrification, on the health of adults and children.

Adam Payne Goode
Dr. Goode is an Associate Professor in the Department of Orthopedic Surgery. He is a physical therapist by clinical training and epidemiologist by scientific training. His focus is on understanding the etiology of low back pain and other chronic musculoskeletal conditions and improving the delivery of care for patients with acute and chronic musculoskeletal conditions. In his research he has published in the areas of the relationship between individual radiographic features in the lumbar spine and clinical symptoms, biomarkers and peripheral joint osteoarthritis.

Steven Zachary George
Dr. George’s primary interest is research involving biopsychosocial models for the prevention and treatment of chronic musculoskeletal pain disorders. His long term goals are to 1) improve accuracy for predicting who is going to develop chronic pain; and 2) identify non-pharmacological treatment options that limit the development of chronic pain conditions. Dr. George is an active member of the American Physical Therapy Association, United States Association of the Study of Pain, and International Association for the Study of Pain.
Dr. George’s research projects have been supported by the National Institutes of Health, Department of Defense, and Orthopaedic Academy of the American Physical Therapy Association. Dr. George and his collaborators have authored over 330 peer-reviewed publications in leading medical, orthopaedic surgery, physical therapy, rehabilitation, and pain research journals. He currently serves as Editor-in-Chief for the Physical Therapy & Rehabilitation Journal. Dr. George has also been involved with clinical practice guideline development for the Academy of Orthopaedic Physical Therapy and the American Psychological Association.
Dr. George has been recognized with prestigious research awards from the American Physical Therapy Association, American Pain Society, and International Association for the Study of Pain. For example from the American Physical Therapy Association: he was named the 21st John H.P. Maley Lecturer, recognized as a Catherine Worthingham Fellow in 2017, and selected for the Marian Williams Award for Research in Physical Therapy in 2022.
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