Australia’s National Science Agency

Primary Care Data Quality FoundationsClinical Working Group

Brisbane | 4 December 2019

Presenter9.00 am arrival tea and coffee Tea and coffee on arrival

09.30 –9.45 amIntroduction and Welcome Kate Ebrill

9.45-10.00 TWG Progress Jim Steel10.00-10.30 National & Gloabal Update

• NCDHC

• RACGP and NACCHO - 715

• Secure Messaging

• Interoperability Strategy

• Others

Frances GilletMary Belfrage, Kate FreemanNathan PinskierTim Blake

10.30-10.45am NSW Medicines FHIR Tim Blake10.45-11.15am Break

11.15- 12.00pm Population Based Interventions- The Gippsland Perspective

Kasif Sheikh, Gippsland PHN

12.00-12.45pmNZ- Health Data Model Karen Blake

HealthAlliance NZ12.45-1.30pm Lunch1.30pm- 1.50 pm Search Demonstrator/SNOMED UI demo Kylynn Loi1.50pm-3.00pm Introduction to Phase 2 and Questionnaires Heather Leslie3.00-3.30pm Break3.30-4.15pm Workshop Activity All4.15-4:30 pm Wrap up and Next Steps Kate Ebrill

Introduction and Welcome Kate Ebrill

• “State of the nation”• “State of the world”• Phase 2 extension of common data model• SDOH• Risk factors• Family history• Smoking/Alcohol detail• Implementation use case – 700 series (715 priority?)

Objectives

TechnicalWG progressJim Steel

National Updates

National Children’s Digital Health CollaborativeFrances Gillet

715 HealthChecksMary Belfrage, Kate Freeman

Secure MessagingNathan Pinskier

NSW Health Integration Transitions of Care – lessons learnedTim Blake

Population-based interventions –a Gippsland perspectiveKasif Sheikh

NZ Health data modelKaren Blake

Search Demonstrator/SNOMED UI demoKylynn Loi

Introduction to Phase 2 and QuestionnairesHeather Leslie

• Natural evolution of Primary Care Data Dictionary• Social determinants of health• Risk factors• Family history• Smoking/Alcohol detail• Implementation use case – 700 series (715 priority?)

Scope considerations

Social determinants of HealthHeather Leslie

WHO• “The social determinants of health are the conditions in which people

are born, grow, live, work and age. These circumstances are shaped by the distribution of money, power and resources at global, national and local levels. The social determinants of health are mostly responsible for health inequities - the unfair and avoidable differences in health status seen within and between countries.”

• “…social inequalities and disadvantage are the main reason for unfair and avoidable differences in health outcomes and life expectancy across groups in society.”

Definition?

PWC• The social determinants of health — often-ignored social factors such as

employment; housing; income inequality; and level of access to clean water, education and transportation — undermine progress and can swamp the health systems that ignore them.

• Social determinants such as employment status, income level, educational attainment, pollution levels and neighbourhood crime all affect how people experience the world and the choices they make

https://www.pwc.com/gx/en/healthcare/pdf/pwc-social-determinants-of-health.pdf

Definition?

The Gravity Project use cases focus on three priority social domains:• food security • housing stability & quality• transportation accesscaptured across three core health care activities:• Screening• Assessment/Diagnosis• Treatment/Interventions

700 series reuse

715 assessment

715 modelling • Patient concern/issue

• Goal

• Problem/Diagnosis• Procedure

• Clinician checklist?

• Family history detail

• Recommendations/rationale• Care plan• Goals• Education

– Required– Provided

• “Service request”– Service– Referral– Procedure– …

• Medication order• Followup/reminders

Possible actions

• Autopopulate form where possible• Re-use as much as possible• Write back to health record• Questionnaire recorded as medicolegal requirement• Populate back to the EHR

Principles

Workshop

Data considerations

Smoking Data!

• SINGLE organisation• 15 years of questionnaire data

• 7 different diseases• 83 data dictionaries• Each disease

• Diagnosis• Family history• Social history• Lifestyle• Pregnancy• Lab results• Measurements• Mental state

• 4 different data managers over the years, tweaking…

Smokes _____ a day?

Intent?

• Cigarette smoking?• Tobacco smoking?• All smoking?• Vaping?• Tobacco use?

• Smoking• Non-smoking eg snus

• Typical use• Episodes of use

• Actual use• Today• On a specified day/date• Average in the past 5 years• Aged 20-30

Data intentionSingle instance • Usually an observation, repeated• Each instance recorded, standalone• Usually part of consultations or clinical events• Requires specific date, time• For example:

– Blood pressure measurement– Medication order– Examination findings

Persistent data• Usually recorded once, then

evolves/replaced/versioned over time• Update record or extend with more detail• Often components of ‘Lists’• Requires ‘Last updated’• For example:

– Adverse reaction risk – updated to add information about a new reaction episode

– Diagnosis– Refine the diagnosis name/code with more

specificity– Add more detail about clinical evidence

Tobacco smoking intentionDiary - single instance/observation • Yesterday• Cigarettes – 20

AND• Cigar - 1

• Today• Cigarettes – 14

AND• Cigar - 3

Summary - persistent data• Onset of daily smoking• Pregnancy episode• Cigarettes 5/day

• Current episode – typical pattern• Cigarettes 20/day• Cigar 1/week

• Quit date• Pack years• Last updated

• Instance data– Most recent?– Recorded in the past <timeframe>?– Maximum/minimum?– Average?– ….• Persistent data

– View data AND date last updated

Fit for use?

Prepopulated data?

Re-use?Consider reminders, care planning, populate EHR