Dataset Information

A Quantitative Framework for Measuring Personalized Medicine Integration into US Healthcare Delivery Organizations.

ABSTRACT: Personalized medicine (PM) approaches have revolutionized healthcare delivery by offering new insights that enable healthcare providers to select the optimal treatment approach for their patients. However, despite the consensus that these approaches have significant value, implementation across the US is highly variable. In order to address barriers to widespread PM adoption, a comprehensive and methodical approach to assessing the current level of PM integration within a given organization and the broader healthcare system is needed. A quantitative framework encompassing a multifactorial approach to assessing PM adoption has been developed and used to generate a rating of PM integration in 153 organizations across the US. The results suggest significant heterogeneity in adoption levels but also some consistent themes in what defines a high-performing organization, including the sophistication of data collected, data sharing practices, and the level of internal funding committed to supporting PM initiatives. A longitudinal approach to data collection will be valuable to track continued progress and adapt to new challenges and barriers to PM adoption as they arise.

SUBMITTER: Agarwal A

PROVIDER: S-EPMC8000405 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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A Quantitative Framework for Measuring Personalized Medicine Integration into US Healthcare Delivery Organizations.

Agarwal Arushi A Pritchard Daryl D Gullett Laura L Amanti Kristen Garner KG Gustavsen Gary G

Journal of personalized medicine 20210312 3

Personalized medicine (PM) approaches have revolutionized healthcare delivery by offering new insights that enable healthcare providers to select the optimal treatment approach for their patients. However, despite the consensus that these approaches have significant value, implementation across the US is highly variable. In order to address barriers to widespread PM adoption, a comprehensive and methodical approach to assessing the current level of PM integration within a given organization and ...[more]

PMID: 33809012

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Project description:Neurodegenerative diseases (NDDs) pose a significant challenge in modern medicine due to their clinical heterogeneity, multifactorial etiologies, and frequent co-pathologies. Traditional diagnostic systems, based on clinical symptoms and post mortem findings, are limited in capturing the complex interactions among genetic, molecular, and neuroanatomical factors. This manuscript introduces a novel tridimensional diagnostic framework that integrates these factors across three key axes: etiology (genetic and environmental influences), molecular markers (primary and secondary biomarkers), and neuroanatomoclinical correlations. Through case studies, we demonstrate the framework's ability to synthesize incomplete datasets, stratify patients, and guide precision medicine. By incorporating omics technologies, neuroimaging, and AI-driven probabilistic modeling, the framework enhances diagnostic accuracy and clinical relevance. This approach may contribute to overcoming the limitations of traditional nosologies, offering a scalable and adaptable tool for both clinical practice and research and advancing the field of precision medicine in NDD management. HIGHLIGHTS: Tridimensional diagnostic system: We propose a new framework that incorporates three axes - etiology, molecular markers, and neuroanatomical-clinical correlations - to enhance diagnostic accuracy for NDDs. Personalized medicine: The tridimensional system enables the integration of genetic, molecular, and clinical data, allowing for highly personalized treatment strategies tailored to individual patients. Proteinopathies as key biomarkers: This diagnostic system emphasizes the use of primary proteinopathies (amyloid, tau, synuclein) and secondary biomarkers (eg, NfL, GFAP) to monitor disease progression and treatment efficacy. Addressing clinical heterogeneity: The framework accommodates the complexity and heterogeneity of NDDs, offering an adaptable diagnostic approach for classical conditions like Alzheimer's disease, Parkinson's disease, frontotemporal dementia, and ALS. Case studies and real-world application: Practical case studies illustrate how this system can be implemented in clinical practice, enabling the combination of DMTs with symptomatic treatments.

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Dataset Information

A Quantitative Framework for Measuring Personalized Medicine Integration into US Healthcare Delivery Organizations.

Publications

A Quantitative Framework for Measuring Personalized Medicine Integration into US Healthcare Delivery Organizations.

Similar Datasets

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