helena britt - the university of sydney - driving health data technology for improved health...

Family Medicine Research Centre

BEAC

H

SYDNEY MEDICAL SCHOOL

Driving health data technology for improved health outcomes


Helena Britt (PhD)

Associate Professor and Director

Future of Health Policy Reform Summit

October 2015


Driving Health Data Technology for Improved Health Outcomes

› Understanding current practices and interventions to improve care

› The role of health technology and eHealth in the Primary Care setting

› The case for improving health data and information standards

› I will concentrate on DATA– at all levels:

- patient; practice; PHN; state and national

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What we understand about current practice comes from the BEACH Program

› A continuous national study of general practice activity

› Began in April 1998; using ever-changing representative samples

› 1000 GPs per year

› Each records 100 encounters ~ 100,000 records per year.

• Highest quality data because our interest is scientific rigour

• In middle of 18th year– we have data for:~ 1.75 million encounters from ~ 17,500 participating-GPs to date

• Data used by governments, industry, health planners, researchers, students

• Continuity allows measures of change over time


What does BEACH tell us?

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Characteristics of the practising GPs:

Characteristics of the patients they see:

- Prevalence of overweight/obesity, at risk drinking and smoking (samples 35,000p.a.)

- Prevalence of individual chronic disease and of multimorbidity

- Annual GP visit rates for people with a selected individual chronic disease(+/- comorbidities)

- Annual GP visit rates for people with selected combinations of diagnosed chronic diseases


What about how GPs practice?

› The content of GP-patient encounters

› How often each problem type is managed in general practice

› How each problem type is managed (direct link):

- Medications prescribed; supplied by GP, advised for OTC purchase

- Clinical treatments given (advice; education; psych counselling etc)

- Therapeutic procedures undertaken

- Pathology tests ordered; imaging ordered

- Referrals to specialist; allied health professionals, ED & admission

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History of antibiotic GP scripts per 100 persons BEACH 1998 to 2011.

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1998-99

1999-00

2000-01

2001-02

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

2008-09

2009-10

2010-11

Other problems 61.37 55.98 53.86 50.23 46.52 47.72 47.42 49.98 48.33 52.28 52.42 53.01 55.51

Other RTIs 17.07 15.60 15.08 13.52 12.42 12.41 10.99 12.20 12.24 12.62 12.63 12.22 12.85

Acute URTI 15.69 14.28 13.97 10.55 11.00 8.50 11.08 10.88 9.86 11.10 12.44 10.35 9.19

0

10

20

30

40

50

60

70

80

90

100

Nm

be

r p

er

10

0 p

op

ula

tio

n

BEACH data year

Estimated number of antibiotic prescriptions generated by GPs nationally per head of population 1998-99 to 2010-11, for URTI, 'other RTIs’,

and all other problems.

Family Medicine Research Centre 9


Back pain – summary of findings

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Back Syndrome - New Diagnostic

Radiology

CT scan

Tests ordered per 100 back syndrome contacts 19.3 11.8

Back Syndrome - Old Diagnostic

Radiology

CT scan


Back symptom/complaint - New Diagnostic

Radiology

CT scan


Back symptom/complaint - Old Diagnostic

Radiology

CT scan


Britt H, Miller GC, Valenti L, Henderson J, Gordon J, Pollack AJ, Bayram C, Wong C. Evaluation of imaging ordering by general practitioners in Australia, 2002–03 to 2011–12.

General practice series no.35. Sydney: Sydney University Press, 2014. http://hdl.handle.net/2123/10610

http://hdl.handle.net/2123/10610


Effect of HPV vaccination programManagement rate per 1,000 age-sex specific encounters

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2000-02 2002-04 2004-06 2006-08 2008-10 2010-12

Genital warts 3.19 3.72 4.94 3.79 2.36 0.99

Control STIs 4.69 4.34 5.74 5.42 5.53 7.91

0123456789

10

Ra

te p

er

1,0

00

en

co

un

ters

Women aged 15-27 years

Effect of year per 100,000

encounters

GW trend

Pre

GW trend

Post

Control trend Pre Control trend Post

Females 15-27 years 28.95

(p = 0.064)

-71.47

(p <0.0001)*

36.69

(p = 0.0251)*

96.67

(p = 0.0027)*

Linear regression


EHR products being used in general practice

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0

10

20

30

40

50

60

70

80

Medical Director MedicalSpectrum

MedTech 32 Genie Solutions Monet Zedmed Best Practice Other

Pe

r ce

nt

2006-07

2007-08

2009-10

2010-11

2012-13

2013-14


recent passing comments ……

› “BEACH is stuck in the past!”

› “They need to move into the electronic age”.

› “Why don’t they just get it out of the EHRs?”

› Answer? We would if we could get the same data quality- but we can’t.

Lets consider why BEACH data is:

- reliable

- valid

- representative

- measures change where change might be expected ( policy, new med, etc)

- is very consistent when no change would be expected.

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Scientific development of methods

15

Previously on The Researchers

Data

Prove

Justify

Defensible

Work

=Quality

Result

Family Medicine Research CentrePfizer March 2013


1972

WONCA and

…

Way back in the distant past……….(classification)

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Lots of

people in

today.

Should keep

a count

1960’s Counting doesn’t help. Need

to classify them

ICD to the rescue

Shame it

doesn’t work

ICPC


Classification … ICPC-2

Coding … ICPC-2 PLUS

ICPC-2 PLUS

The International Classification of Primary Care V2 (ICPC-2)

• Patient RFEs

• Problems managed

• Clinical & therapeutic treatments

• Pathology tests

• Imaging tests

• Referrals

• the World Organisation of Family Doctors (Wonca)

• part of WHO ‘Family of Classifications’ – standard in >45 countries

• Australian standard for reporting GP and patient self-report data

• our interface GP terminology

• developed from > 1 million encounter records

• classified according to ICPC-2

• trained clinical coders


Classifying Drugs – CAPS

Coding Atlas for Pharmaceutical Substances

Classifies medications

prescribed, advised, supplied

• Drug Class (eg: antibiotics)

• Drug sub group (eg broad spectrum penicillins)

• Generic/molecule (amoxycillin)

• Brand (Amoxil)

• Strength

At generic level also classified to the Anatomic Therapeutic Chemical

(ATC) classification (WHO) – the inter/national standard.

+ regimen Prescribed Daily Dose


Way back in the distant past….(problem orientation, linkage)

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1968: Weed LL, N Engl J Med. 1968 Mar 14;278(11):593-600 (& republished NEJM 40 years later)

•The POMR: Problem Oriented Medical record

follows on a problem over time, with changing problem labels

• The SOAP record structure for consultation

• S= subjective

• O=Objective

• A= Assessment (problem label)

• P = Plan

with the consultation data linked

to the problem number

Quote Weed


Weed’s work applied…..

› By the mid 1970s >half of GPs in Aus had adopted the RACGP :

› a problem oriented health record, which linked changing problem labels for

s single patient problem over time (WEED YR)

› a health summary that linked prescribing to the problem being managed

› Consultation notes that linked management actions to individual

problem……..

›Then computers arrived.

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The miracle of computers

› It was assumed this would fix everything.

› People developed EHRs with no linkage of management to problems

› No common data model or core data set

› No definitions of data fields

› No built in classifications of data

› In summary : NO STANDARDS

› But with Government encouragement everyone moved to EHRs.

› Now about 97% of individual GPs use EHRs (to varying degrees)

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EHR source - development of methods

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More recently on The Researchers

= ?


One of the few with a scientific approach

› Professor Teng Liaw (20 examined the accuracy of 3 data extraction tools

with 2 EHR systems

“The DETs identified different numbers of diabetics and measures of

quality of care under the same conditions.

Discussion: Current DETs are not reliable and potentially unsafe.

Proprietary EHRs and DETs must support transparency and

independent testing with standardised queries. Quality control within an

appropriate policy and legislative environment is essential.”

› Maybe we should listen!› Liaw S.T. et al Aust Fam Physician Vol 42 Issue 11 2013.

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The role of health technology and eHealth in the Primary Care setting in the future

› Transfer of information (full record) between practices

› Transfer summary information to specialists, allied health, hospitals, EDs

› Receipt of reports from above + pathology, imaging

› Quality data about the individual patient, for clinical care

› Quality data about the patient population of the practice

› Quality data at the PHN, state and National levels, to inform policy & planning

› Patient based data integrated from across the health care system that can

give us a long term view of care and measures of outcomes.

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So what have we got?

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About 12 GP EHR software products – with

•different data elements with different data labels & no definitions

•no rules for GPs to know into which data field they have to put things!

•at least three different interface terminology only one classified at point of data entry

•one of two pharmaceutical coding systems (Mims, AZdex)

•decide which field(s) to search in each of the EHR systems

•use free text searches of their own making

•group terms into concepts in their own individual way

Three major extraction tools that individually ……


So what are we currently doing?

› EHR providers locking end-users in, by ensuring NO inter operability

› BIG $$ being spent trying to get “around” the lack of basic standards by - Multiple government organisations- Universities and other research groups- Many, many PHNs and many Local health districts

› Extraction tool providers developing new and better ‘ways’ to search the free text, in inconsistent data fields to try to make the recorded data into information.

›E.g. By using incorrect assumptions: “Metformin script in record… Oh patient DOES have diabetes – the GP just didn’t record it”.

NO actually – the patient has polycystic ovary syndrome–not diabetes.

› And…..of course ….. The PCEHR…..not coded, not classified, no linkages of current treatment to problems managed – of little clinical use (for a rumoured price tag of I Billion $)

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Solutions

We need finalised, and rolled-out

A core set of data elements with exactly the same labels and definitions using

national and international standards

Forced linkages of management actions to problem managed at the interface

Rules for GPs to know into which data field they have to put things!

Good quality controlled interface terminologies that are linked to …

a standardised reference terminology, that is mapped to …

ICD 10 AM and to ICPC-2

Many other things – but these would be a good start!

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We urgently need to fix things!


Relationships Interface terminologies, reference terminologies, classifications

Reference

Terminologies

SNOMED-CT

Classifications

and groupers

ICPC-2, ICPC-2 Plus

groupers

ICD 10 AM

Interface

terminologies

eg.

ICPC-2 Plus

Defines

Is defined by Classifies

Is classified by

Data in Research

data out

Classifies or groupsIs classified or

grouped

Clinical data out


The basics are there

› 1997: Functional requirements specs for clinical GP computer systems --IBM

› 2000: GP data model and core dataset developed by Simsion Bowles, GPs & other stakeholders

› 2003: The International Classification of Primary Care (ICPC–2) was recommended as the standard for classifying GP-recorded morbidity data—never mandated.

› 2005 NEHTA established & other dedicated government funding of IT development stopped.

NEHTA focused on developing PCEHR- without good EHR standards, of little clinical use

These projects were funded by the Department of Health, but their outcomes were not adopted, & government did not proceed with developing standards for EHR recording.

› Under a contract with the IHTSDO, we led the development of international core subset of SNOMED concepts for general practice/family medicine (needs addtiions for Aus)

› Yet NeHTA is insisting that GPs deal with the whole of SNOMED - using it naked (no interface terminology) – a recipe for disaster.!

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My contention

› it makes it extremely difficult to transfer patient data to other general practices

and health providers at all levels

› it makes it hard for practices to change to a different EHR system

› it makes it impossible to obtain reliable national information by HER download,

about the care provided to individuals and thepopula65tion

This is unacceptable when in 2011–2012 there are ~ 138 million GP consultation

services provided at cost to government of $5 billion+.

Why are we waiting??

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The absence of compulsory basic standards has three negative effects:


Discussion

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BEACH 2012-14

Many thanksto the GPs


Endorsed by

BEACH 2012-14

Free PDF versions of the BEACH reports can be downloaded from

http://sydney.edu.au/medicine/fmrc

(go to ‘Publications’ and select ‘Books - General Practice series’)

Follow us on twitter @Sydney_BEACH

Contact the FMRCWebsite: sydney.edu.au/medicine/fmrc

Phone: +61 2 9845 8151

Email: [email protected]

2014 -15 books will be released Nov. 4th 2015

Watch for the feature article:

Care of older people in general practice in Australia

mailto:[email protected]

helena britt - the university of sydney - driving health data technology for improved health...

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