playing with fhir - hisa

Playing with FHIRHow to Exploit the EHR

Mark L Braunstein, MDProfessor of the Practice

School of Interactive ComputingGeorgia Institute of Technology

Visiting Research FellowE-Health Centre, CSIRO

”

“ Australia ranks highest on Administrative Efficiency and Health Care Outcomes, and is among the top-ranked countries on Care Process and Access

Commonwealth Fund (2017)

Variable Results

Common Trends

https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-healthcare-and-life-sciences-predictions-2020.pdf

Aging Population

More Chronic Disease

Increased Costs

Including Australia

https://www.aihw.gov.au/reports/australias-health/australias-health-2018/contents/table-of-contents

Australian Institute of Health and Welfare 2018

Systems Not Designed for Chronic Care

https://www.mja.com.au/journal/2007/187/2/care-patients-chronic-disease-challenge-general-practice

Medical Journal of Australia

Poor Care Coordination

https://www.commonwealthfund.org/publications/surveys/2015/dec/2015-commonwealth-fund-international-survey-primary-care-physicians

Lack of Continuity

9692 90

8581

66 65 6460

28

UK NETH NZ SWE A US US NOR CA N SWIZ GER

https://www.commonwealthfund.org/publications/surveys/2015/dec/2015-commonwealth-fund-international-survey-primary-care-physicians

In Practice Nurses or Case Managers

Variable Use of Informatics

30

11

53

24

80

11

5760

0

10

20

30

40

50

60

70

80

90

Email Record Sharing

Australia NZ SWIZ US

Healthcare Professionals Want Digital Health

Activity

Currently using a computer,

smart phone or tablet

%

Not using, but interested in using

a computer, smart phone or

tablet

%

Not interested in using a

computer, smart phone or tablet

for this activity

%

Sharing health records with my patients 25 59 7

Transferring prescriptions to the pharmacy 25 56 8

Providing interactive decision-making support 32 53 6

Communicating with patients before or after consultations 33 49 7

Sharing health records with other practitioners 43 45 4

Top 5 activities health professionals want to use digital technologies to help better support them to deliver health services

Courtesy Australian Digital Health Agency

EHRs Have “Issues”

https://medicomp.com/whats-the-most-frustrating-about-ehrs/

Goals: IOM

safe, effective, patient-centered, timely, efficient, equitable

Learning Health Systemhttps://www.ahrq.gov/professionals/systems/learning-health-systems/index.html

Necessary Informatics Substrate

EMR Adoption Analytics Access to POCOpen

Interoperability

Variable EHR Readiness

http://www.oecd.org/els/health-systems/health-statistics.htm

Current EHR Limitations

No standards regarding discrete data

No integrated communication

Not user-friendly

Big data but not smart data

Lack of regulation

https://www.beckershospitalreview.com/healthcare-information-technology/the-problem-with-ehrs-5-complaints-from-cios.html

Remember these are we proceed

Hospital CIOs

What to Do?

Repair?

Replace?

Innovate!

“Fostering third party apps creates a market where innovations compete with each other for purchase and use by providers (and patients), thus reducing dependency on updates and specific functions made by an EHR vendor.”

--Ken Mandl, Josh Mandel, Isaac Kohane

https://www.sciencedirect.com/science/article/pii/S2405471215000046

It Works Quantitatively

https://research2guidance.com/325000-mobile-health-apps-available-in-2017/

Proof of Effectiveness is Lacking but …

11 of 23 randomized controlled trials showed a meaningful effect on health or surrogate outcomes attributable to apps … the overall evidence of effectiveness was of very low quality … pilot studies … only one has progressed to a large clinical trial.

https://www.nature.com/articles/s41746-018-0021-9

… Mostly “Siloed” Apps

Extend the Phone App Model to EHRs?

Harvard’s SMART

https://apps.smarthealthit.org/

Georgia Tech’s HDAP

http://www.hdap.gatech.edu/apps/

Cerner/Epic …

Even the US Government!

https://bluebutton.cms.gov/

What Will Happen Next?

“These apps will give new life to data entered into EHRs and other health IT platforms by providing the ability to visualize risks, trends, and trajectories; mash up clinical records with external data sources; and deliver decision support to clinicians and patients during and between encounters.”

--Ken Mandl, Josh Mandel, Isaac Kohane

https://www.sciencedirect.com/science/article/pii/S2405471215000046

A Better EHR?

Juxly Timeline



Not user-friendly


Juxly Trends



Not user-friendly


Coordinated, Continuous Care

Within Cerner

-

More Complete Patient View

EHR Data

Patient Generated Data



Not user-friendly


Outcome Prediction

HL7 Timeline

FHIR: V 3.0.1 April 19, 2017 …

Messaging (lab test results)

Model Driven (patient record summaries)

2018?

A Common Data Model



Not user-friendly


Condition: Human View

Condition: Machine View

73211009Remember me!

Uniform API

“Just Like” Amazon!

http://hapi.fhir.org/baseDstu3/Condition?code=SNOMED-CT|73211009

https://www.amazon.com.au/s/ref=nb_sb_noss?url=search-alias%3Daps&field-keywords=size+10+ladies+blue+sweater

Population level query

Condition Specific Charting

Medication Reconciliation

RxNorm for different names

Multipledispensings

One entry

Clinical InsightsNo standards regarding discrete data


Not user-friendly


Lower CostNo standards regarding discrete data


Not user-friendly


Precision MedicineNo standards regarding discrete data


Not user-friendly


What About Your Patients?

Patient Controlled Health Record

EHR Connected Mobile Apps

Over 500 Collaborating Hospitals/Clinics (June)

Sharing Models

Opt Out - Centralized Opt In - Federated

Secondary Use?

Chart Review

Search Results

Drill Down: Conditions/Medications

Drill Down: Notes

Research

“a historic effort to gather data from one million or more people living in the United States to accelerate research and improve health. By taking into account individual differences in lifestyle, environment, and biology, researchers will uncover paths toward delivering precision medicine.”

https://allofus.nih.gov/

FHIR App

Emory Artificial Intelligence Sepsis Expert (AISE)

Trained on 31,000 Emory ICU patients

Validated on 52,000 MIMIC III patients

Third International Consensus Definitions for Sepsis (Sepsis-3)

65 features (variables) calculated on hourly basis

Can predict sepsis 4 hours in advance (ROC of .85)*

*https://www.ncbi.nlm.nih.gov/pubmed/29286945

DeepAISE on FHIR

Decline ImprovementEmory AISE Score

Philips DRS Score: Higher predicts readmissionSubmitted to AMIA 2018

Text messagingor the eICU application

Drag/Drop Automatic



Not user-friendly


https://35.237.162.198:80/#/

eICU team adjudicates warnings

Medical Education on FHIR?

We are partnering with UQ ITEE and Faculty of Medicine to offer an experimental course to explore the potential of using FHIR to digitize case based learning.

Diabetes Case Study

Burn Case StudyNathan and is alert and oriented with a GCS of 15

Nathan’s % total body surface area (%TBSA) of burn is calculated using a Lund-Browder chart to be 62% with 59% full thickness burns, 2% deep dermal and 1% partial thickness burns

Want to Try It Yourself?

http://cs6440.gatech.edu/

[email protected]