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The Digital Outcome Measure
Author(s) -
Adam B. Cohen,
Simon C. Mathews
Publication year - 2018
Publication title -
digital biomarkers
Language(s) - English
Resource type - Journals
ISSN - 2504-110X
DOI - 10.1159/000492396
Subject(s) - outcome (game theory) , standardization , consistency (knowledge bases) , measure (data warehouse) , data collection , patient reported outcome , wearable computer , gold standard (test) , health care , computer science , data science , medicine , nursing , data mining , artificial intelligence , statistics , quality of life (healthcare) , political science , mathematics , mathematical economics , embedded system , operating system , law
Improving clinical outcomes remains the gold standard in advancing healthcare. Focusing on outcomes holds the potential to unite all clinical stakeholders including payers, industry, providers, and patients. Yet, the dominant ways in which outcomes are captured, provider-collected or patient-reported, have significant limitations. The emerging field of biosensors and wearables, which aims to capture many types of health data, holds promise to specifically capture outcomes while complementing existing outcome collection methods. A digital outcome measure, unlike a traditional provider-collected or patient-reported outcome measure, depends less on active patient or provider participation. Thus, digital outcome measures may be more amenable to standardization as well as greater collection consistency, frequency, and accuracy.

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