Gap Analysis of Insight-Driven Personalized Health Services through Patient-Controlled Devices
Pei-Yun Sabrina HSUEH, , Michael MARSCHOLLEK, Yardena PERES, Stefan von CAVALLAR and Fernando J. MARTIN-SANCHEZ
IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
Hannover Medical School, Germany
IBM Research Lab in Haifa, Israel
IBM Research Lab in Melbourne, Australia
Melbourne Medical School, Australia
Mobile computing, wearable and embedded tech entail new and different styles of healthcare data processing, clinical and wellness decision support, and patient engagement schemes. This is especially important to the preventive and disease management scenarios that require better understanding of disease progression previously unable to achieve due to the lack of reliable means to capture granular patient-generated data in non-clinical settings. The new sources of data, when coupled with a framework to integrate analytical insights with feasible service models, enable reliable detection of inflection points, habit formation cycles and assessments of treatment efficacy. Research into data collection, recording, management and analysis of behavioral manisfestations and triggers will help address these challenges in areas spanning from simple fall detection to situations requiring complicated, multi-modal health monitoring such as Alzheimer’s progression and other adherence management cases. Leveraging recent advance in health devices and sensors as well as expertise in healthcare practice and informatics, the proposed workshop will help form a deeper understanding of requirements on patient-controlled devices to address unique healthcare challenges, identify care flow gaps and translate these findings to the design of platforms for patient-controlled devices and a portfolio of potential service models for preventive care and disease management.