Big data: a new era in sleep medicine? H. Woehrle Sleep and Ventilation Center Blaubeuren/ Lung Center Ulm
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1 Big data: a new era in sleep medicine? H. Woehrle Sleep and Ventilation Center Blaubeuren/ Lung Center Ulm hwoehrle@lungenzentrum-ulm.de
2 Ulm and Neu-Ulm
3 Disclosures Lecture Fees/Consulting: Astra Zeneca, Bayer, Boehringer Ingelheim, GSK, Inspire, ResMed, Vital Air, Weinmann Research Grants: Weinmann, MAP, ResMed Employment as Medical Director (SERVE-HF study management ) by ResMed Quelle: TheAtomicMoose.ca
4 Big Data Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. The term big data refers not only to large data sets, but also to the frameworks, techniques, and tools used to analyze it. It can be collected through any data-generating process such as social media, public utility infrastructure, and search engines. Big data may be either semistructured, structured, or unstructured.
5 Big Data growing fast
6 The Five V s of Big Data: 4 + value resmed.com
7 Big Data Source: blog.ness-ses.com;
8 Validity of Machine Learning
9 Big Data Pros Insights (e.g., phenotyping, precision medicine) Safety (long-term, real time; interactions) Trends, trajectories Monitoring Cons Inherent biases in how all data are collected and interpreted. Objections to the idea that data mining can replace hypothesis driven theory by content experts. The observation that the larger the data set the more likely that spurious correlations that are not useful will be identified Bottles et al; PEJ JULY AUGUST/2014
10 Big data data privacy?
11 Big data data ownership?
12
13 Big Data and Medicine
14 Digital health - Sleep
15
16 Telehealth in sleep apnea management 1. Telediagnostics 2. Teleconsultation 3. Teletherapy 4. Telemonitoring
17 e-health/telemonitoring during PAP-Tx Quelle: JMIR, ResMed
18 Telemonitoring AirView Therapy Data Physician / Home Care Clinician Notifications (Action Groups / U-Sleep) Patient Patient Engagement and Notifications (myair / U-Sleep)
19 Academic industrial collaboration on big data
20 CPAP-Therapy VORTEX BLOWER and SOFT MASK (Sullivan)
21 Emerging central sleep apnea during CPAP CPAP oahi=43/h, mit p=8cm keine zentralen H20, cai=28/h Apnoen Morgenthaler, Sleep 2006
22 Case study CSA persistent
23 Case study CSA transient
24 Patient selection US sample, IRB waiver
25 Trajectories of CSA n=
26 CSA Trajectories Emergent CSA (CAI <5/h week 1, 5/h week 12) 19,7% CSA Prevalence n = 133, days therapy data Persistent CSA (CAI 5/h week 1, 5/h week 12) 25,2% 3.5% 55,1% Transient CSA (CAI 5/h week 1, <5/h week 12) Liu et al., Chest 2017
27 CSA Trajectories Therapy Termination CSA = CAI > 5 83% 79% 76% 72% HR = 1.0 HR = 1.3 HR = 1.5 HR = 1.7 Liu et al., Chest 2017
28 AirView ASV Big Data: Switchers
29 AirView ASV Big Data: Switchers
30 AirView ASV Big Data: Switchers
31 e-health/m-health and Patient Engagement Quelle: ResMed, Respironics
32
33
34
35 Proactive TM guided patient care Reactive Service Pro-active Service health care provider health care provider Source: ResMed
36 Proaktive TM gestützte Patientenversorgung
37 Effect of Tele- Education and Telemonitoring on CPAP Adherence: The Tele-OSA Randomized Trial Hwang et al. AJRCCM 2017 Aug 31
38 Effect of Tele- Education and Telemonitoring on CPAP Adherence: The Tele-OSA Randomized Trial Hwang et al. AJRCCM 2017 Aug 31
39 39
40 mhealth
41 Quo vadis?
42 The near future
43 Big data: a new era in sleep medicine? H. Woehrle Sleep and Ventilation Center Blaubeuren/ Lung Center Ulm hwoehrle@lungenzentrum-ulm.de
Central Sleep Apnoea during CPAP therapy First insights from a big data analysis. April 2018
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