A scalable realtime analytics pipeline and storage architecture for physiological monitoring big data

A Systematic Review of Knowledge Visualization Approaches Using Big Data Methodology for Clinical Decision Support

“…The PRISMA flow diagram (Figure 1) summarizes the screening process. The 17 studies remaining were included in the qualitative synthesis [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] that follows.…”

“…We identified four main groups of users of big data visualization applications for clinical decision support: (1) academicians (clinical researchers and clinical epidemiologists, nurse educators) [11,12,17,18,26], (2) administrators (hospital administrators and managers) [12,17,25], ancillary staff (caretakers, lab managers, pharmacists) [11,13,25]; (3) health care providers (clinicians, nurses, physicians) [11][12][13][14][15][16][18][19][20][21][22][23][24][25][26][27] and (4) patients [11,14,22,23]. More than 94% of the studies (n = 16) were developed to support clinical healthcare provider decision-making.…”

“…Authors reported the number of records, tests and patient stay days that ranged from 15,700 to 17.8 million. Three studies [11,18,21] used structured and/or social media big data ranging from 7000 to 300 million records. About 65% of the studies (n = 11) used real time data such as ECG streaming, producing 500,000 messages per minute and 80 different types of vitals totaling 100,000 messages [26].…”

“…Three studies developed and used mobile care coordination [14,15,20], four studies designed web portals for healthcare providers [11,13,22,23] and patients [11]. Two studies used a multi-patient surveillance system [12,18] and one study used a multi patient dashboard to support clinical decisions.…”

“…One study [21] used only one visualization type (tabular), five studies (29%) presented two different visualization types (multidimensional and tabular, tabular and temporal, etc.) [15,17,18,20,24].…”