Dr Inga Hunter, Hinz 2015 Conference, Christchurch

1. HINZ Conference 19-22 October 2015,
Christchurch
Dr Inga Hunter
Senior Lecturer, Massey University
Senior Medical Officer, MidCentral DHB
NZ representative to IMIA
FRNZCGP, FACHI i.hunter@massey.ac.nz

2.  15th World Congress on Health & Biomedical Informatics 19th to 23rd
August 2015.
 São Paulo, Brazil
 hosted by Brazilian Health Informatics Association on behalf of the
International Medical Informatics Association (IMIA)
 1st time in South America
 Portugese, Spanish

3.  5 Keynotes
 21Tutorials
 27 Panels
 30 Workshops
 16 Demonstrations
 178 Papers
 247 Posters
 7 Satellite Symposiums
 531 Presentations
(Total)
 Over 1000 attendees
 67 countries.
 Use of translating
headsets for audience.
 13 concurrent sessions
 5 days
 Rigorous review process
from nearly 800
submissions by 2,500
authors from 59
countries
 http://goo.gl/yTWc5z
open access for
proceedings

4.  Use of the word citizen very prominent
instead of patient;
 Data sharing across countries in Europe. Have
data from more than 50 million patients from
primary care, hospitals, clinical trials, etc.
 Buenos Aires hospital has medicines
reconciliation done by doctors.

5.  Patients and shared decision making - co-
design with patients as stakeholders.

 Discussion around patient generated data
and bi-directional flow of data and
information, how and does health providers
want to receive and use patient generated
data. Regulatory and medico legal issues
discussed.

6. Emmanuel
Chazard, Milena
Soriano Marcolino,
Chloé Dumesnil,
Alexandre Caron,
Daniel Moore F.
Palhares, Grégoire
Ficheur, Barbara C.
A. Marino, Maria
Beatriz M. Alkmim,
Régis Beuscart,
Antonio Luiz
Ribeiro

8.  Keynote on day 2
 Fernan Gonzalez, Bernaldo de Quiros
"Transforming Healthcare through Clinical
Information Systems: Is it an impossible task?"
 Increasing emphasis on recording social
determinants of health, eg level of isolation and
environmental data (wearable devices,
neighbourhood data such as location of what
types of shops, housing details such as steps).
 Current EHR are for the supplier but need to be
for the population.

9. 6 talks patient portals, US (part 2 meaningful use)
U.S. hospital admissions are required to offer a portal
access to the information from that admission, GP visit
same requirement but different portal, likewise for
specialists = may end up with 3 unconnected portal
accesses.
One talk looked at quality of Px entered data into a
tertiary hospital patient portal – past medical/surgical
and social Hx.
◦ Patients could enter diagnosis and operations/procedures.
Mental health was common new entry. Social history new entry
most were on sexual history.
◦ Surgery procedures had lots of duplication, meaning that
patients were telling the truth, but had a lower level of
granularity (general not specific data). Less new diagnoses in
procedures than medical.

10.  3 main problems – 1. sparse data (of useable quality
data where you know the data collection methods), 2.
data is consistently inconsistent, 3. moving data.
 Sparse data can be fused with data from other sources
using matrix factorisation – see paper. This method
gives predictions of whet would be the missing
data. Can also have probalistic factorisation.
 Moving data - distributed networks create issues with
optimisation. Advantages is can help preserve privacy.
Research occurring on methods to perform distributed
computing on data analysis.
◦ Not studying a patient when investigating EHRs but studying
the record of the patient.

11. Electronic phenotype for cohort identification for
research studies - using EHR and other machine
readable data to identify the members of the
cohort. Combine genotype with phenotype from
EMR and other sources of machine readable
data.
◦ Molecular and genomic data
◦ Images
◦ Structured clinical data
◦ Unstructured clinical data
◦ Self-reported data
◦ Environmental data (exposome informatics)
◦ ....

12.  Availability of data
 Phenotyping data often temporal
 Syntactic and semantic interoperability
 Privacy and confidentiality
 Phenotype interpretation
 Future:
◦ NLP better integration
◦ More data type resources
◦ Real time surveillance
◦ Decision support – clinicians and researchers

13.  Clinical use of big data for clinical decision
making
 Identify ' patents like you' and ' patients like
mine'.
 Moving from ‘big data’ to ‘precision
medicine’
 Use of Exposome Informatics

14. Need for a Translational Health Information Language (THIL)

15.  HIV and HIS presentation on HIV workforce in
sub-Saharan Africa - Kenya.
 95% of data successfully exchanged.
 Outcomes looked at location of HIV infected
people's location and HIV nurses, and ration
of health workforce to HIV people's.
 Challenges- data, cost, lack of common
standards, legacy data inconsistencies with
new code text.

16. European wide, 3
centres, with own
data warehouse.
For management of
diabetes.
Provides advanced
functions to
clinicians not
available with
existing EMR .
 Can use data to
compare single Px to
the whole
population

17.  EHR is an extension medical record of the patient
- from different organisations, plus includes
genomic data, environmental data, etc. can track
from summarised info back to sources as
temporal data.
 One speaker proposes lifetime bank of info -
EHR sustainability - an independent non-centric
record bank. Providers are no longer the
owner/manager of the record data. Proposes
there should be community consultation on the
idea of independent record banks