Nhu cầu về dữ liệu lớn trong thực hành lâm sàng góc nhìn từ bác sỹ tim mạch

Big Data: Perspective from Cardiology A/Prof (Adj) Yeo Khung Keong, MBBS, FAMS, FACC, FSCAI National Heart Centre Singapore Disclosures • • • • • Abbott Vascular: Speaker, Proctor (MitraClip) Boston Scientific: Consultant, honorarium Philips: Honorarium Medtronic: Research support St Jude Medical: Speaker, honorarium What is Big Data? • • • • • • HUGE data volume Clinical Administrative data Genetics/Genomics/metabolomics… Imaging SPEED What’s the Big Deal? • New medical discoveries • Improved ability to predict cost, outcomes • Policy and planning – Manpower – Resources – Budgeting • Management of epidemic and outbreaks • Pragmatic Research trials D ATA A N D T E C H N O L O G Y H AV E T R A N S F O R M E D F I N A N C E Human Model Expert Model Early 1900-1995 1995 - Current Big Data Model Trending Healthcare is at the beginning of a necessary transformation “The future of precision medicine will enable health care providers to tailor treatment and prevention strategies to people’s unique characteristics, including their genome sequence, microbiome composition, health history, lifestyle, and diet To get there, we need to incorporate many different types of data, from metabolomics (the chemicals in the body at a certain point in time), the microbiome (the collection of microorganisms in or on the body), and data about the patient collected by health care providers and the patients themselves Success will require that health data is portable, that it can be easily shared between providers, researchers, and most importantly, patients and research participants.” Key words “The future of precision medicine will enable health care providers to tailor treatment and prevention strategies to people’s unique characteristics, including their genome sequence, microbiome composition, health history, lifestyle, and diet To get there, we need to incorporate many different types of data, from metabolomics (the chemicals in the body at a certain point in time), the microbiome (the collection of microorganisms in or on the body), and data about the patient collected by health care providers and the patients themselves Success will require that health data is portable, that it can be easily shared between providers, researchers, and most importantly, patients and research participants.” 10 Opportunities • • • • • Asia: disparate, ginormous, young If only… We had money We worked together We had the proper governance Challenges • Legal • Risks – Patient confidentiality and privacy – Real patient hard • Governance – Who owns the data – What about algorithms Risks • Patient privacy and confidentiality – Long viability • Patient safety – Eg allergy • Expensive • Missed opportunity Governance • • • • • 30 Who ‘owns’ the data? How should or can it be used? Who should be on the paper? What if data does not look good? Who should be in-charge? Singapore Myocardial Infarction Registry • Singapore MIR (1988–1997)1,2 – Set up in 1987, SMIR is a nationwide unselected registry of patients with acute MI – National Registry of Diseases (Acute Myocardial Infarction Notification) Regulations 2012 come into operation on 1st September 2012 MIR, Myocardial Infarction Registry 1Tan ATH et al Ann Acad Med Singapore 2002;31:479–86 (1988–1997); 2Singapore Myocardial Infarction Registry (Report 1, 2012, www.nrdo.gov.sg./, data collation 2007–2010 For further study details please see slide notes SingCLOUD Jurong General Sengkang General Data Available 541 Tables / views built and tested SingCLOUD Data Sources 7957 Total Number of Data Fields available to users Percentage of patients by cohort 6330 4677 166,491 Medications (Drug Name) 52,654 Patients Unique count of patient number (PAT_ID) in presentation table 44812 Unique count of drug name in presentation table Data Sources Foundation Total Number of Rows Number of patients by age group 33 45,753,182 CAD 376 Tables / views built and tested 1,043,945,394 Total Number of Rows Number of patients by age group CHF CAD+CHF 2433 Total Number of Data Fields available to users Number of patients by gender Unknown Male Female 8,108,134 Patients 2,689,306 Medications (Drug Name) Null 10000 20000 30000 Examples • Medicare, CMS data • SwedeHeart What is needed? • • • • • • • Governance Professional and political will power! Money Perseverance Good IT & IT infrastructure People Data (!!!!) Proposal • National Data from each country • Asia Pacific Society of Cardiology – STEMI admin data, registry data – No patient level data – Biobank Invitation • Join us! 38 ... many different types of data, from metabolomics (the chemicals in the body at a certain point in time), the microbiome (the collection of microorganisms in or on the body), and data about the patient... many different types of data, from metabolomics (the chemicals in the body at a certain point in time), the microbiome (the collection of microorganisms in or on the body), and data about the patient... Quality indicators 0,5 point point Reperfusion in STEMI/LBBB 80% 85% Reperf within recommended time in STEMI/LBBB 75% 90% Angiography in target group of NSTEMI patients 75% 80% LMWH/ Heparin/