2. What is health informatics?
Why is it important?
What does health informatics include?
What does it mean for me?
How do I find out where to learn
more?
5. the study of information processing as it is
used in healthcare
the field that deals with the storage,
retrieval, sharing, and optimal use of
health information, data, and knowledge
for problem solving and decision making
includes science and practice of
healthcare, its information and knowledge
and their management with information
and communication technologies to
promote the health of people, families and
communities world wide
6. HINZ – www.hinz.org.nz
IMIA - www.imia.org
Health IT cluster - www.healthit.org.nz
Ministry of Health - www.health.govt.nz
National Health IT Board -
www.ithealthboard.health.nz
7.
8.
9. Particular commitment to “patient controlled
record” by 2014
eHealth Vision
◦ “better access to information about our health”
◦ “better, sooner, more convenient health care”
◦ integrated consumer-centred care
◦ having access to their own health information
◦ improving electronic storage
◦ share information regionally and nationally
◦ consolidated platform for shared care
◦ high quality health care and improved patient
safety
10. Electronic Health Records
Knowledge Management
Decision support
Telemedicine and telehealth
Standards
Evidence for benefit/harm
Ethics and Security
11. Communications
Data collection
and analysis
Knowledge
Decision support
Electronic health record
Surveillance, Public Health
Coding
ICD10 - Classification
Messaging, HL7
Telecare
EHealth
MHealth
Evidence-Based Practice
Ontologies and vocabularies
All aiming for better health outcomes
12.
13. October 2012
“The Herald understands staff allegedly
accessed the man's medical file and emailed the
x-rays. It is understood the incident could lead
to court action against those involved.”
What technology is involved and is this a
technological issue?
14. They don’t learn
They can’t tell what you mean
They don’t get bored
15. Discrete variables
National Health Index – NHI
Name, date of birth, gender, address
Values collected – blood test results
Clinical data - blood pressure, clinical signs,
diagnosis, medications
Data itself is nothing…
Should provide useful, usable
information that makes a difference
to patient care
16. Data in context
120/80 means something if you
know it is mmHg
However it still doesn’t tell you
anything about whether the patient is
sick or well.
Need more data to provide context –
when taken, other readings, age,
medical history, medications
17. Adds MEANING to information
120/80 is high blood pressure in an
infant
May be high relative to other readings
in an adult
Relies on expertise to interpret.
Information to knowledge usually
done by humans, can see clinical
diagnosis as this sort of process…
Can utilise Decision Support Systems
19. Patients
◦ Self treatment and support
Clinical staff
◦ Support diagnosis and treatment
Administration and funders
◦ Cost Estimation
◦ Management
◦ Resource allocation
◦ Outcomes
20. • What are EHRs?
• Examples of EHRs
• Issues with EHR
21. “Computer-based systems for input, storage,
display, retrieval, and printing of information
contained in a patient's medical record” – Pubmed
Part of a clinical information system relating to
individuals
Records information about a person:
◦ Presenting symptoms
◦ Results of tests and clinical examinations
◦ Encounters with health professionals
◦ Treatment and plans for further management
23. A NZ veterinary practice is advertising online
that they offer electronic health records for
pets. If your Vet is closed another in the town
can see your pet and access their health record
and provide care.
Why can’t we do this for people too?
What do you think might be the potential
benefits of EHRs?
What might be some of the issues for EHRs?
24. Always available
Legible
Searchable
Sharable
Different views
Audit and decision support
Security
25. Consistency of data
Free text versus coding
Security – who can access and when
Protecting an individual's privacy
Need a computer
“Fishing expeditions”
Sharing information safely
27. Data collected should be available for:
Supporting clinical intervention
Clinical Governance
Administration (in all parts of health)
Strategy and policy development
Research
29. Use data from Electronic Health Record
combined with rules
Reminders – eg high blood pressure,
protocols
Decision Analysis – need utility values
Alerts
Linking to resources
Recalls-Cervical screening, immunisations
Telehealth
30. Data to record diagnoses, observations,
outcomes.
• Coding - Diagnostic related groups (DRGS)
◦ ICD 10 codes
◦ Read codes
◦ Snomed CT
Vocabularies – to standardise terms, shared
meanings
◦ Pre-eclampsia, PE, Toxaemia, PET, Gestational
Proteinuric Hypertension GPH
31. International Classification of disease (ICD) currently
version 10.
http://www.who.int/classifications/icd/en/
World Health Organisation standard
http://www.cdc.gov/nchs/about/otheract/icd9/icd10cm.ht
m
ICD10 Code Description
O104.11 Pre-existing secondary hypertension complicating pregnancy, first trimester
O104.12 Pre-existing secondary hypertension complicating pregnancy, second trimester
O104.13 Pre-existing secondary hypertension complicating pregnancy, third trimester
O104.19 Pre-existing secondary hypertension complicating pregnancy, unspecified trimester
35. Global standard
Hierarchical
Concepts - also link concepts
Synonyms and different languages
>600,000K Concepts
clinical vocabulary administered by
international health terminology standards
development organisation (IHTSDO)
http://www.ihtsdo.org/.
Member countries; Australia, Canada,
Denmark, Lithuania, Netherlands, NZ, Sweden,
UK & USA
38. Structured Pathology Reporting for Cancer from Free Text: Lung Cancer
Case Study
Anthony Nguyen, Michael Lawley, David Hansen, Shoni Colquist
Abstract
.
Results: Checklist items were identified in the free text report and used
for structured reporting. The synthesised TNM staging values classified
by the system were evaluated against explicitly mentioned TNM stages
from 487 reports and achieved an overall accuracy of 78%, 89% and 95%
for T, N and M stages respectively.
Conclusion: A system to generate structured cancer case reports from
free-text pathology reports using symbolic rule-based classification
techniques was developed and shows promise. The approach can be
easily adapted for other cancer case structured reports.
http://research.ict.csiro.au/software/snapper
39.
40. Communication of information is a
key task in health informatics
Communication must be accurate,
reliable and timely
◦ Prescriptions (from hospital or GP to
Pharmacy)
◦ Referrals (from GP to hospital)
◦ Discharge Summaries (from hospital to
GP)
◦ Lab results
41. Potential architectures
Single Clinical Information system
◦ Everybody accesses own part and gets views of
other data.
Centralised model
◦ Requires very large investment
◦ Issues with who “owns” data
◦ Connectivity always needed – robust & 24/7
42. Independent systems that communicate
Low investment needed
Fewer issues with ownership
Only data that needs to be transferred is
sent
BUT
◦ N(n-1) connections
◦ Interface issues
◦ Who looks after it ?
43. Standard message formats (HL 7 –
simple way to format message for safe
transmission)
Use VPN, SSL and other encryption to
allow use of standard commercial
infrastructure
DICOM - A system for transferring
images, including X-rays, ultrasound
etc. Aims to prevent image information
separating from patient data.
44.
45.
46. Treaty of Waitangi
Professional codes of conduct
Privacy Act & Health Information Privacy
Code
Technological solutions:
◦ Audit trails – who looked at the data
◦ Industry-standard security and authentication
◦ Rules for data preservation
◦ Data consistency and cross-checking
◦ Sealed envelopes
47. Rule 1: Purpose of collection of health information
Rule 2: Source of health information
Rule 3: Collection of health information from
individual
Rule 4: Manner of collection of health information
Rule 5: Storage and security of health information
Rule 6: Access to personal health information
Rule 7: Correction of health information
Rule 8: Accuracy etc of health information to be
checked before use
Rule 9: Retention of health information
Rule 10: Limits on use of health information
Rule 11: Limits on disclosure of health information
Rule 12: Unique identifiers
48.
49.
50.
51. QUOTE: The past is gone; the future is unknown
-- but the present is real, and your
opportunities are now.
QUESTION:
From what you have seen and read list trends
that will be more dominant in the future of
technology and health care.
52. International trends include:
◦ Communication technologies
◦ Portability
◦ Digital divide
◦ Changing public
◦ Genomics
◦ Tele-health
53. What basic information literacy skills
should health professionals possess?
Where and how should they get the
education for this?
To what extent should health
professionals be trained in IT to enable
them to work with health information
systems?
54. Professionals in health and IT need the skills
that provide for
◦ lifelong learning
◦ career development
◦ critical thinking ability
◦ communication skills
◦ information literacy
Follow Up:
Personal assessment and plan
International Computer Driving License
Notes de l'éditeur
Participants to complete pre workshop survey and also to please note their names and email addresses clearly on the attendance form for certificates.Thanks to hosts Introduce ourselves as the presenters
What this workshop will cover.We will cover a number of concepts during this 2 hour workshop and use a number of diagrams as some people find these easier to follow than just hearing it, or seeing it written.
Either this one – or next 2 slides – hide which ever you don’t want to useEmphasize USE – for patient care/outcomes.
These are a range of definitions:1st – from www.virtualinformatics.com2nd - from Ed Shortliffe – used repeatedly but first coined in 1990 Shortliffe EH, Perreault LE, Wiederhold G, Fagan LM, eds.Medical Informatics: Computer Applications in Health Care.Reading, MA.: Addison-Wesley; 1990.3rd- based on International Medical Informatics Association – Nursing Informatics (IMIA-NI) group definition
The information being presented comes from a range of sources, but those wishing to follow up can look at the internet for:Health Informatics New Zealand (HINZ) – national health informatics groupInternational Medical Informatics Association (IMIA) – international informatics group – NZ is a memberHealth Information Technology Cluster – a collaborative group of NZ companies that develop and work in the health IT area (New Zealand is fortunate to have a number of health IT vendors and “health care” is the largest software export category for NZ) Ministry of Health – government National Health IT Board – government body in the MoH who provide strategy and leadership for health IT
Diagram from National Health IT Board. Board overview of strategy for NZ health IT. But doesn’t show NGOS
Introduced in 2010 with national aims and objectives
Health Informatics is very broad and includes the list above Following slide shows this diagrammatically, and then slide after that shows them as competencies (hide slide 12 if you don’t want to show competencies until the end).
The list shown diagrammatically, and next slide shows these as competencies (hide slide 12 if you don’t want to show competencies until the end).
Divide group up and allow 5- 10 minutes for discussion. Vignette came from ADHB. Change to local incident if you have one. Point is that people made bad judgements. Technology made it easier to spread.
This slide is an introHide this slide if you don’t want to use it. But include intro to Data
Explain what Data is. Give examples – NHIOther examples can change depending on audience.
120/80 – could be a fraction, or anything.mmHg – lets you know it’s a measure – and therefore tells you it’s a blood pressure.Could use white board and write up 90/50 – could be low BP, child, need to know previous reading, meds etc – ie need context
But how do we standardise availability of expertise…Information well presented – so data readily available; trends easily seenIntroduce Decision Support Systems – acknowledging not available everywhere
Patients – support and self-management – ie especially for long term conditions; knowledge can improve complianceArea of Consumer Health Informatics.Changing role of patients – may bring printout with them for consultation, but need help understanding. Issues of credibility of information they’ve sourced and applicability to NZ and their specific situation.Clinical – Patient Information Systems; Clinical information Systems; Decision Support SystemsAdmin - Patient Management Systems (PMS); etc
Aim – to provide legible, accessible, timely data – what you need, when you need it, where you need it!We need an improvement on the old paper record
Can be for instances of careCan be longitudinal – across time Can be interdisciplinary – probably best when they are….Can include both health professionals and consumers views/wishesBut patient/individual is central.
Diagrammatically shown as … EHR for the individual is central
Use this slide as a summary of what the vignette discussion brings up.
Use this slide as a summary of what the vignette discussion brings up.
Distinguish between EHR – for health professionals and PCHR - Personally Controlled Health Records- In terms of content and purpose
Why we need clinical data – from Ministry of Health
And we’d add a 6th use – for the patient/consumer
Depending on audience you could expand on any of these…
DRGS – used by Ministry of HealthICD10 - New Zealand hospitals use this clinical coding classification developed by the World Health Organization Read Codes – used by ACCSnomed CT - January 2012 eighteen countries are members – including USA, UK, Australia Examples follow – then a bit more detail about SnomedCT
Can hide this slide if coding detail not suitable for audience, or else just show briefly to indicate detail.Could indicate role of Clinical Coders and that Ministry of Health has a web page showing the courses available- http://www.health.govt.nz/nz-health-statistics/classification-and-terminology/using-icd-10-am-achi-and-acs/courses-clinical-coding.
Can hide this slide if coding detail not suitable for audience, or else just show briefly to indicate detail.
Context – means clinical context for the patientSemantics – meaning and definition of termsOntology - In the IT world, an ontology formally represents knowledge as a set of concepts within a domain, and the relationships between pairs of concepts.Observations – objective and subjective data (symptoms, measures etc)Codes – Also mention that rules can be addedDocuments – include images, prescriptions etc
Diagrammatic explanation of use of SNOMED
Example of how SNOMED can be used clinically
Amount of detail provided here will depend on audience
There are Professional, Organisational and Technological aspectsAbove highlights professional and technological more – but organisational responsibility is also important - including tracing and education.Legal/Ethical practice + Sanctions+ Training = Public Confidence
Source – http://privacy.org.nz/information-privacy-principlesThese should be known by those working in the health and health IT sector.Consider audience and focus on 2 or 3 as appropriate – or make 2 slides if audience needs to focus on these more.
Use this slide depending on your time as:Further discussion Things to think about after this workshopHow do these questions relate to you
Technology is here to stay. Not everyone wants to take health informatics further, but everyone in health needs a basic understanding.Consider assessing your own needs and abilities, and for those interested… the next slide about HINZ health informatics competencies, and opportunities for further education.
This workshop was just an introduction... Mention Health Informatics NZ – website www.hinz.org.nz and a group from HINZ have identified these core competencies in health informatics. HAND-OUT about education options available in NZ. *** Participants to complete post workshop survey and check they have added their name of the attendance form for their certificates.THANK YOU to host organisation and key people.Be available to answer questions.