Individualized interventions and precision health: Lessons learned from a systematic review and implications for analytics-driven geriatric research
Corresponding Author
Anna R. Kahkoska MD, PhD
Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Correspondence
Anna R. Kahkoska, Department of Nutrition, University of North Carolina at Chapel Hill, 2205A McGavran Greenberg Hall, Chapel Hill, NC 27599, USA.
Email: [email protected]
Search for more papers by this authorNikki L. B. Freeman MA
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorEmily P. Jones MLIS
Health Sciences Library, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorDaniela Shirazi BS
Department of Medicine, California University of Science and Medicine, Colton, California, USA
Search for more papers by this authorSydney Browder BS
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorAnnie Page BSPH
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorJohn Sperger BS
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorTarek M. Zikry BSPH
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorFei Yu PhD
School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorJan Busby-Whitehead MD
Division of Geriatric Medicine, Department of Medicine, Center for Aging and Health, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
Search for more papers by this authorMichael R. Kosorok PhD
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
Search for more papers by this authorJohn A. Batsis MD, AGSF
Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Division of Geriatric Medicine, Department of Medicine, Center for Aging and Health, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
Search for more papers by this authorCorresponding Author
Anna R. Kahkoska MD, PhD
Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Correspondence
Anna R. Kahkoska, Department of Nutrition, University of North Carolina at Chapel Hill, 2205A McGavran Greenberg Hall, Chapel Hill, NC 27599, USA.
Email: [email protected]
Search for more papers by this authorNikki L. B. Freeman MA
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorEmily P. Jones MLIS
Health Sciences Library, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorDaniela Shirazi BS
Department of Medicine, California University of Science and Medicine, Colton, California, USA
Search for more papers by this authorSydney Browder BS
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorAnnie Page BSPH
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorJohn Sperger BS
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorTarek M. Zikry BSPH
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorFei Yu PhD
School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Search for more papers by this authorJan Busby-Whitehead MD
Division of Geriatric Medicine, Department of Medicine, Center for Aging and Health, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
Search for more papers by this authorMichael R. Kosorok PhD
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
Search for more papers by this authorJohn A. Batsis MD, AGSF
Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
Division of Geriatric Medicine, Department of Medicine, Center for Aging and Health, School of Medicine, University of North Carolina, Chapel Hill, North Carolina, USA
Search for more papers by this authorFunding information: National Institutes of Health, Grant/Award Numbers: K23 AG051681, KL2TR002490; School of Medicine, University of North Carolina at Chapel Hill, Grant/Award Number: ACTP1R1001
Abstract
Older adults are characterized by profound clinical heterogeneity. When designing and delivering interventions, there exist multiple approaches to account for heterogeneity. We present the results of a systematic review of data-driven, personalized interventions in older adults, which serves as a use case to distinguish the conceptual and methodologic differences between individualized intervention delivery and precision health-derived interventions. We define individualized interventions as those where all participants received the same parent intervention, modified on a case-by-case basis and using an evidence-based protocol, supplemented by clinical judgment as appropriate, while precision health-derived interventions are those that tailor care to individuals whereby the strategy for how to tailor care was determined through data-driven, precision health analytics. We discuss how their integration may offer new opportunities for analytics-based geriatric medicine that accommodates individual heterogeneity but allows for more flexible and resource-efficient population-level scaling.
CONFLICT OF INTEREST
Dr. Batsis holds equity in SynchroHealth LLC, a remote monitoring startup.The authors have no conflicts of interest to disclose.
Supporting Information
Filename | Description |
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jgs18141-sup-0001-Supinfo.pdfPDF document, 529.3 KB | Text S1. Supporting information. Table S1. Reference number and key study information. Table S2. Methodological Quality of the Included Studies–Cochrane Risk-of-Bias Tool. Table S3. Design Characteristics of the Included Studies. Table S4. Participant Characteristics. Table S5. Study Aims and Results. Table S6. Method of precision medicine or individualization. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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