Health  informa.cs    

Fernando  Mar*n-­‐Sanchez  Ins$tute  for  a  Broadband-­‐Enabled  Society  

&  Melbourne  Medical  School  

 

Introduc$on  •  Broadband  can  provide  many  opportuni$es  for  the  health  sector:  –  Improving  youth  mental  health  and  aged  care  services  

–  Monitoring  health  condi$ons      –  Enabling  shared  electronic  health  records    

•  Broadband  technologies  are  revolu$onising  the  delivery  of  health  care.  Convergence  with  other  technologies  towards  Digitally  Enabled  Personalized  Medicine  

Aging  Well    – Mobile  and  broadband  

technologies  for  ameliora.ng  social  isola.on  in  older  people  

–  Smart  Homes  for  the  Elderly  –  recent  developments  in  Korea  

−  HORYZONS:  Online  Recovery  for  Youth  Onset  Psychosis  

Youth  Mental  Health      

Telehealth      –  Individual  Electronic  Health  Records  

–  The  Telestroke  Study  –  Hap*c  Tele-­‐Rehabilita/on    –  Teleden/stry      –  Virtual  visits:  Inves*ga*ng  the  acceptability  of  webcam  consulta*ons  for  young  

adults’  sexual  health  –  Wireless  broadband  monitoring  of  knee  osteoarthri/s  –  Overcoming  geographical  barriers  for  community  health  –  Interpreter  mediated  cogni*ve  assessments  using  video  conferencing  soFware  –  SeeCare  IPTV:  Personalised  Health  Literacy  Demonstrator  –  Mobile  Augmented  Reality  –  Interpreter  mediated  cogni/ve  assessments  using  video  conferencing  soFware    –  High  resolu*on  monitoring  of  atmospheric  pollutants  to  iden*fy  their  impact  on  

popula*on  health  –  Overcoming  geographical  barriers  for  community  health  –  Using  video-­‐conferencing  to  pilot  an  educa*on  and  clinical  support  package  for  

rural  GPs  in  Mildura  

Health Informatics: Towards

Digitally Enabled Personalised Medicine

Current challenges in Medicine •  Need  of  earlier  diagnosis      •  More  personalized  therapies  •  Risk  profiling,  disease  predic$on  and  preven$on      

•  Improve  disease  classifica$on  systems      •  Control  health  system  costs    •  Clinical  trials  and  the  development  of  new  drugs  need  to  be  more  agile  and  effec$ve.  

•  Ci$zens  could  take  more  responsibility  for  the  maintenance  of  their  own  health.  

•  Shortage  of  health  professionals  

The Digitalization of Medicine •  Digital  revolu$on  in  other  domains  (banking,  insurance,  leisure,  government,…)  

•  The  incorpora$on  of  digital  systems  in  healthcare  is  lagging  behind  other  sectors:  –  Reasons:  complexity,  privacy,  volume  of  data,  lack  of  demand  

–  It  has  greatly  affected  healthcare  at  the  hospital  or  research  centre  level.    

–  The  digital  revolu$on  has  not  yet  reached  medicine,  at  the  pa$ent/ci$zen  level    • BUT  THIS  IS  STARTING  TO  HAPPEN  NOW  !!!  

Enabling scientific and technological advancements

•  New  converging  areas  make  feasible  for  the  first  $me  the  idea  of  an  integrated  digital  infrastructure  for  medicine,  reaching  the  ci$zen,  that  will  make  feasible  the  concept  of  personalized  medicine  – Nanotechnology  –  Biotechnology  –  Informa$on  Technologies  –  Cogni$ve  science  

Enabling scientific and technological advancements

•  Broadband  technologies  and  networks  •  High  performance  compu$ng  (and  A.I.  systems)  •  Ubiquity  of  smartphones,  tablets,  …  •  Sensors,  imaging  and  wearables  •  Personal  genome  sequencing,  gene$c  tes$ng  and  

epigene$cs  •  Metagenomics  and  the  Human  Microbiome  

Project •  Social  networks  and  the  Quan$fied  Self  •  Knowledge  management  on  gene$c  diseases  and  

systems  biology  modelling  

•  Smartphone  ECG  system  to  provide  physicians  and  pa$ents  with  hospital-­‐quality  heart  rhythm  monitoring  outside  of  the  hospital  se`ng  

Smartphone apps

•  Benchtop  Ion  Proton™  Sequencer  –  designed  to  sequence  the  en$re  human  genome  in  a  day  for  $1,000  

Advances in genomic technology

Graphs of my total cholesterol (blue), my “bad” LDL cholesterol (red), and my “good” cholesterol (green) over a decade.

(Larry Smarr, CalTech)

Genomic sensors Environmental sensors

Phenomic sensors

Biomarkers (DNA sequence, proteins, gene expression, epigenetics

Environmental risk factors (pollution, radiation, toxic agents, …)

Physiological, biochemical parameters (cholesterol, temperature, glucose, heart rate…)

Integrated personal health record

Remote  pa$ent  data  monitoring  and  data  collec$on  

Digitally  enabled  personalised  medicine    •  Personalized  medicine  refers  to  the  tailoring  of  

medical  treatment  to  groups  of  pa$ents  with  similar  gene$c  or  molecular  profiles.    

•  Ultra  high  speed  broadband  networks  will  be  required  to  transmit  enormous  volumes  of  data  from  pa$ents’  homes  to  health  prac$$oners  and  vice  versa  in  a  $mely  manner,  and  to  enable  the  processing  of  this  deluge  of  data.  

•  Personalised  medicine  offers  enormous  opportuni$es  for  improving  preven$ve,  diagnos$c  and  therapeu$c  solu$ons  à  improving  healthcare  outcomes,  reducing  costs  and  increasing  pa$ent  safety.  

Digitally  enabled  

personalised  medicine  

Patient Data (sensors and imaging)

Genomic Phenomic Environmental

Integrated Personal Health Record

Health Profile Assessment

Tables (weighted factors)

Risks Diagnosis Personal

Health Profile

Health Profile Improvement

Module 1

Module 2

Decision matrix, protocols Risk reduction Therapy

Follow-up Personalised Health Recommendations

Sensors

GWAS

CDSS

EHR

Trialbanks NBN

Modelling

Social  media  and  biomedical  and    clinical  research  

•  We  are  witnessing  a  transi$on  from  research  informa$on  systems  centralized  at  hospitals  and  clinical  research  centres  to  distributed  systems  that  reach  out  to  the  residence  of  any  ci$zen  /  pa$ent  who  opts  in.    

•  Social  media  as  a  research  tool  •  Clinical  Research  with  the  pa$ents,  not  on  the  pa$ents  •  Examples  

–  23andMe  –  Parkinson’s  Disease  –  PLoS  Gene$cs,  2  new  gene$c  associa$ons  

–  Pa$entsLikeMe  –  Nature  Biotech.  Self-­‐reported  data  from  600  pa$ents  on  the  use  of  lithium  for  Amyotrophic  Lateral  Sclerosis  (ALS)  

Pa$ent  empowerment  Current networks

NBN-enabled Driving forces: patient empowerment, personalized medicine, social networks

EHR – Electronic Health Record

Personally Controlled EHR

Citizens are able to maintain and control their own health information

Gene-disease association studies

Personal genomics

Citizens ask for genetic analysis of their DNA through the Internet and receive reports on various aspects of their health

Clinical trials Crowdsourced clinical trials

The patient voluntarily shares information on treatments and evolution of his/her illness with other patients

Barriers •  New  regulatory  framework  (new  models  of  clinical  

trials)  •  New  informa$cs  methods  to  compile  and  interpret  all  

the  informa$on  •  Educa$on  of  pa$ents  and  health  professionals  •  Ethics,  data  security  and  confiden$ality  issues  •  Wide  availability  of  clinical  decision  support  systems  at  

the  point-­‐of-­‐care  •  New  cost-­‐effec$veness  assessment  and  financial  

models  of  care  •  Need  to  prove  clinical  effec$veness  before  DTC  services  

are  offered.  

Conclusions •  The  rou$ne  applica$on  of  personalised  medicine  is  s$ll  a  long  way  ahead,  however  we  have  now  all  the  ingredients  to  make  it  happen.

•  The  convergence  of  medicine  and  the  digital  revolu$on  will  produce  an  informa.on  ecosystem  that  will  facilitate  the  advent  of  safer  and  more  efficient  preven$ve,  diagnos$c  and  therapeu$c  solu$ons.    

•  The  ci$zen  will  have  access  to  her  gene.c  profile  and  clinical  record,  and  will  monitor  and  adjust  her  health  using  next  genera$on  sensors  and  social  networks  to  share  this  informa$on  with  peers,  clinicians  and  researchers.    Virtual  pa$ent  –  Pa$ent  avatar  

Conclusions •  But  all  of  this  will  only  be  possible  if  we  realise  that  it  is  .me  for  us  

to  take  responsibility  for  our  own  health.    –  “The  Crea$ve  Destruc$on  of  Medicine”  (Topol),  –   “Networked  individualism”  (Rainie),  or  –   “P4  Medicine”  (Hood).  

•  We  prefer  the  term  “Digitally  enabled  personalized  medicine”  and  have  already  started  research  work  in  several  areas:  clinical  genomics,  modelling  and  the  use  of  social  media  for  biomedical  research.    

•  We  believe  that  the  synergy  between  Health  Informa$cs  and  the  broadband  network  in  the  context  of  mul$disciplinary  collabora$on  and  innova$on  offered  by  Carlton  Connect  will  contribute  to  accelerate  the  advent  of  personalised  medicine.      

Thank  you      

oms@unimelb.edu.au  www.healthinforma$cs.unimelb.edu.au  

Twiqer:  @ibeshbir