H3 : A Hybrid Handheld Healthcare Framework

Handheld devices, which have been widely adopted to clinical environments for medical data archiving, have revolutionized error-prone manual processes of the past. Meanwhile, the use of devices has been reported to be limited to data entries and archiving, without fully leveraging their computing and retrieval capabilities. This paper studies a hybrid system which complements current state-of-art, by combining intelligent retrieval techniques developed over middleware environments for retrieval effectiveness and flash-aware data management techniques for retrieval efficiency. By enabling intelligent ranked retrieval, the limited resources of handheld devices, eeg., limited display and computation capabilities, can be utilized effectively, by selectively retrieving the few most relevant results. However, to achieve this goal, we need a hybrid approach, bridging middleware-based ranked retrieval techniques to optimize for flash memory storage, as typically adopted by handheld devices. We address this newly emerging challenge and propose a flash-aware framework H3, which we empirically validate its effectiveness over baseline alternatives.