Agenda | Data & Analytics in Healthcare

Wednesday 4th March
Thursday 5th March

Wednesday 4th March

08:30

Registration, Coffee & Networking in the Exhibition Area

October 22 | 08:30 - 09:00

Speaking:

08:55

Corinium Global Intelligence Welcome Address

October 22 | 08:55 - 09:00

Speaking:

09:00

Chair’s Opening Remarks

Throughout the next two days, take advantage of our interactive event App. Pose questions to your speakers, take part in interactive panels, interviews and surveys, and communicate with your fellow delegates!

Chair’s Opening Remarks

October 22 | 09:00 - 09:05

Speaking:

09:05

Keynote Presentation: Using analytics to improve quality and safety of health services

How do we best measure improvement in quality and safety?
Hospital acquired complications - impact on care, safety and quality
The power of patient reported experience and outcomes data
The potential and pitfalls of big data linkage to improve quality and safety

Speaking:

Keynote Presentation: Using analytics to improve quality and safety of health services

April 21 | 09:05 - 09:40

How do we best measure improvement in quality and safety?
Hospital acquired complications - impact on care, safety and quality
The power of patient reported experience and outcomes data
The potential and pitfalls of big data linkage to improve quality and safety

Speaking:

09:40

Ensuring an accurate data capture system for improved patient outcomes

Designing and implementing the screens that clinicians are using to record their data
Measuring the effectiveness of the treatments delivered
How well does this match with what we are doing to fix them?
Encouraging clinicians to input the data - Observing the clinicians not the patients
Moving from each hospital has its own discreet system to a state wide system

Speaking:

Ensuring an accurate data capture system for improved patient outcomes

October 22 | 09:40 - 10:05

Designing and implementing the screens that clinicians are using to record their data
Measuring the effectiveness of the treatments delivered
How well does this match with what we are doing to fix them?
Encouraging clinicians to input the data - Observing the clinicians not the patients
Moving from each hospital has its own discreet system to a state wide system

Speaking:

10:05

Keynote session presented by Qlik

April 21 | 10:05 - 10:30

Speaking:

10:30

Mid-Morning Coffee & Networking in the Exhibition Area

October 22 | 10:30 - 11:00

Speaking:

11:00

Using and managing first party data to understand behaviour

How we took our data from inconsistent and fragmented to revealing actionable insights
Five stages of the Single View of Customer Project
to Collect, Enrich, Present & Act on our data in real-time
Ability to “Anonymous” doesn’t mean we can’t engage - how to handle anonymised data
1st Party data - Stitching data across engagements
Dynamically engaging with a subscriber and understanding their current stage in the support cycle
Using patient data in an ethical way: When does personalisation become creepy?

Speaking:

Using and managing first party data to understand behaviour

October 22 | 11:00 - 11:25

How we took our data from inconsistent and fragmented to revealing actionable insights
Five stages of the Single View of Customer Project
to Collect, Enrich, Present & Act on our data in real-time
Ability to “Anonymous” doesn’t mean we can’t engage - how to handle anonymised data
1st Party data - Stitching data across engagements
Dynamically engaging with a subscriber and understanding their current stage in the support cycle
Using patient data in an ethical way: When does personalisation become creepy?

Speaking:

11:25

Update from the Digital Health CRC - Digital Health data and Technology: Improving the quality of healthcare

Since mid-2018, the Digital Health CRC has been partnering with universities, industry and government to deliver

transformational outcomes through expertise in health data research and knowledge application. This session will be an update on their work to achieve the following:

Drivers for Digital Health: big data to smart data
Improving access to integrated healthcare information
Secure information platforms for research
Improving efficiency in the health system
Supporting clinical practice through applied research outcomes

Speaking:

Update from the Digital Health CRC - Digital Health data and Technology: Improving the quality of healthcare

April 21 | 11:25 - 11:50

Since mid-2018, the Digital Health CRC has been partnering with universities, industry and government to deliver

transformational outcomes through expertise in health data research and knowledge application. This session will be an update on their work to achieve the following:

Drivers for Digital Health: big data to smart data
Improving access to integrated healthcare information
Secure information platforms for research
Improving efficiency in the health system
Supporting clinical practice through applied research outcomes

Speaking:

11:50

Keynote Discussion Panel: Successfully managing the challenges of patient data privacy, consent and ethics

One of the largest challenges that the healthcare industry faces is the sensitivity around patient data. Getting the right processes for privacy, consent and ethics in place is an enormous challenges and one which warrants an industry wide discussion. This session will look at:

Navigating the ethical requirements when obtaining data and using patient data
What are the industry concerns around data sharing and privacy?
Who owns the data? The patient?
Why you can’t use it if it’s not handled properly
Is there a role for privacy watchdogs?
Impact of GDPR - What does it mean in Australia?

Speaking:

Keynote Discussion Panel: Successfully managing the challenges of patient data privacy, consent and ethics

October 22 | 11:50 - 12:25

Navigating the ethical requirements when obtaining data and using patient data
What are the industry concerns around data sharing and privacy?
Who owns the data? The patient?
Why you can’t use it if it’s not handled properly
Is there a role for privacy watchdogs?
Impact of GDPR - What does it mean in Australia?

Speaking:

12:25

Buffet Lunch & Networking in the Exhibition Area

October 22 | 12:25 - 13:25

Speaking:

1:25

Case Study: Automated AI approaches for Clinical Coding with Chiang Mai University using clinical data

The translation from clinical data to codes (for costing and reporting) getting more complex and currently requires highly trained experts who are in very limited supply
In conjunction with Chiang Mai University we used data from pathology, radiology, pharmacy and admission to predict ICD10 codes without human intervention
Learn how we utilised Neural Network based Artificial Intelligence approaches to predict primary diagnosis with levels of accuracy comparable to entry level coders

Speaking:

Case Study: Automated AI approaches for Clinical Coding with Chiang Mai University using clinical data

April 21 | 13:25 - 13:50

The translation from clinical data to codes (for costing and reporting) getting more complex and currently requires highly trained experts who are in very limited supply
In conjunction with Chiang Mai University we used data from pathology, radiology, pharmacy and admission to predict ICD10 codes without human intervention
Learn how we utilised Neural Network based Artificial Intelligence approaches to predict primary diagnosis with levels of accuracy comparable to entry level coders

Speaking:

1:25

Discussion Group: Improving data quality – ending the cycle of garbage in, garbage out

Quantifying the cost of poor data quality
Techniques for getting the data entered properly?
Ensuring the data you have represents what you want it to
How you can encourage clinicians to enter high quality data

Speaking:

Discussion Group: Improving data quality – ending the cycle of garbage in, garbage out

October 23 | 13:25 - 13:50

Quantifying the cost of poor data quality
Techniques for getting the data entered properly?
Ensuring the data you have represents what you want it to
How you can encourage clinicians to enter high quality data

Speaking:

1:50

Case study: Integrating data of disparate types to understand health needs

Why it’s so difficult to obtain access to, then learn from multiple data sets in healthcare
How to fast track data integration and model deployment
How to use different sources getting a single view of the patient
Overcoming data quality and bias issues in analytical modelling

Speaking:

Case study: Integrating data of disparate types to understand health needs

October 22 | 13:50 - 14:15

Why it’s so difficult to obtain access to, then learn from multiple data sets in healthcare
How to fast track data integration and model deployment
How to use different sources getting a single view of the patient
Overcoming data quality and bias issues in analytical modelling

Speaking:

1:50

Discussion Group: Keeping Patient Data Secure and Protected

Data security and compliance are essential components of data governance. They are extremely critical in healthcare, as patient information is personally sensitive, hard to replace (unlike a stolen credit card), and highly attractive to cyber-criminals. This session will examine the following points: · Do you have enough confidence and trust in the security of the systems holding your critical data? · What are the risks when sharing data to external providers? · Are you ready for tomorrow’s data protection, security and compliance challenges? · Security considerations when going to the cloud

Speaking:

Discussion Group: Keeping Patient Data Secure and Protected

October 22 | 13:50 - 14:15

Speaking:

2:15

Using linked administrative data to improve outcomes for vulnerable families in NSW

The NSW Government is taking an investment approach to improving outcomes for vulnerable families across NSW. Investment and policy decisions will be guided by individual-level lifetime modelling using a comprehensive linked health and human services data set. The first round of investment modelling was published in the Forecasting Future Outcomes report[1], a NSW government paper released in July 2019. This session will:

Present the striking key results from the modelling which projects lifetime pathways for all NSW residents currently under age 25 and includes key outcomes and interactions with government agencies across health (hospital, MBS and PBS), child protection, social housing, justice and welfare.
Highlights the benefits and challenges of using linked individual-level administrative data and focuses on the importance of health and mental health in determining long-term intergenerational outcomes.

Speaking:

Using linked administrative data to improve outcomes for vulnerable families in NSW

April 21 | 14:15 - 14:40

Present the striking key results from the modelling which projects lifetime pathways for all NSW residents currently under age 25 and includes key outcomes and interactions with government agencies across health (hospital, MBS and PBS), child protection, social housing, justice and welfare.
Highlights the benefits and challenges of using linked individual-level administrative data and focuses on the importance of health and mental health in determining long-term intergenerational outcomes.

Speaking:

2:15

Discussion group: Prioritising Data within your Organisation - Embedding a Culture of Data, Analytics and Insight Based Decision Making

Does the industry have a data strategy and what are they prioritising?
How do you prioritise data within healthcare organisations?
How can a data project compete with a new MRI for funding? Demonstrating the value and potential value of data
Tips for ensuring adequate support from senior management to invest in the required IT systems
Why is it important to use data for defining your strategy and prioritising initiatives

Speaking:

Discussion group: Prioritising Data within your Organisation - Embedding a Culture of Data, Analytics and Insight Based Decision Making

October 23 | 14:15 - 14:40

Does the industry have a data strategy and what are they prioritising?
How do you prioritise data within healthcare organisations?
How can a data project compete with a new MRI for funding? Demonstrating the value and potential value of data
Tips for ensuring adequate support from senior management to invest in the required IT systems
Why is it important to use data for defining your strategy and prioritising initiatives

Speaking:

2:40

Panel Discussion: Data literacy - How to design your data capture processes to enrich your data sets

It’s no surprise that data comes second place to providing care. All healthcare organisations exist to support patient outcomes – not necessarily data projects. However, the huge potential of data to underpin better clinical outcomes is the next evolution of healthcare. One of the key issues is that time poor clinicians aren’t necessarily capturing rich, accurate data sets. This session will look at how to improve data literacy, including:

Making data collection processes more intuitive and easier to complete
Standardising nomenclature and taxonomies of data to ensure a non-ambiguous format
Ensuring the data is entered in a format that can be used for surveillance
How to support clinicians to access their own data
How do you engage clinicians and help them get analytics that are useful?
How to teach clinicians the consequences of ‘garbage in and garbage out‘

Speaking:

Panel Discussion: Data literacy - How to design your data capture processes to enrich your data sets

October 23 | 14:40 - 15:05

Making data collection processes more intuitive and easier to complete
Standardising nomenclature and taxonomies of data to ensure a non-ambiguous format
Ensuring the data is entered in a format that can be used for surveillance
How to support clinicians to access their own data
How do you engage clinicians and help them get analytics that are useful?
How to teach clinicians the consequences of ‘garbage in and garbage out‘

Speaking:

2:40

Case study: Enabling access to real time data through interactive dashboards

From static reports to real-time reporting
Unlocking data from your electronical medical record system
Configuring dashboards that better serve the end user

Speaking:

Case study: Enabling access to real time data through interactive dashboards

October 23 | 14:40 - 15:05

From static reports to real-time reporting
Unlocking data from your electronical medical record system
Configuring dashboards that better serve the end user

Speaking:

3:05

Afternoon Tea & Networking in the Exhibition Area

October 22 | 15:05 - 15:35

Speaking:

3:35

Delivering the right information into the right hands – System Dynamics and the case of Emergency Care

Administrative and territorial boundaries can lead to siloed decision-making in healthcare wherein decisions within one part of the system are made without considering their impact on other parts.
System Dynamics (SD) is a scientifically rigorous, evidence-based approach that can span system level boundaries and provide decision makers with an aerial view of the system and an understanding of the consequences, both intended and unintended of their decisions.
SD offers a flexible intervention-testing tool that enables teams on the ground to utilise available data to make informed decisions under complex conditions.
There is ample evidence to show that systems tools are transforming performance in other large-scale complex industries – however their strategic use in healthcare has been limited despite the explosion in data accessibility and communications capabilities.
Research and innovation focussed on optimising the operational and strategic decisions that drive efficiencies can empower better delivery and ultimately better care.
New partnership are needed in a business meets research model. This has been a long time coming. As far back as 2005, the National Academy of Engineering and the Institute of Medicine in the US advocated for this. Veteran Affairs in the USA today are engaging system dynamists with data scientists in a participatory SD modelling project to increase delivery of evidence-based decisions to improve addiction and mental health care.
CBEH and Mater Health (public ED) have developed a pilot intervention-testing SD tool and the results have been very promising. The model can replicate ED flow accurately simulating the patient backlogs and delays. The model can change multiple modifiable factors simultaneously to see the impact on flow.
Decisions can be tested in a risk-free virtual system twin.

Speaking:

Delivering the right information into the right hands – System Dynamics and the case of Emergency Care

April 21 | 15:35 - 16:00

Administrative and territorial boundaries can lead to siloed decision-making in healthcare wherein decisions within one part of the system are made without considering their impact on other parts.
System Dynamics (SD) is a scientifically rigorous, evidence-based approach that can span system level boundaries and provide decision makers with an aerial view of the system and an understanding of the consequences, both intended and unintended of their decisions.
SD offers a flexible intervention-testing tool that enables teams on the ground to utilise available data to make informed decisions under complex conditions.
There is ample evidence to show that systems tools are transforming performance in other large-scale complex industries – however their strategic use in healthcare has been limited despite the explosion in data accessibility and communications capabilities.
Research and innovation focussed on optimising the operational and strategic decisions that drive efficiencies can empower better delivery and ultimately better care.
New partnership are needed in a business meets research model. This has been a long time coming. As far back as 2005, the National Academy of Engineering and the Institute of Medicine in the US advocated for this. Veteran Affairs in the USA today are engaging system dynamists with data scientists in a participatory SD modelling project to increase delivery of evidence-based decisions to improve addiction and mental health care.
CBEH and Mater Health (public ED) have developed a pilot intervention-testing SD tool and the results have been very promising. The model can replicate ED flow accurately simulating the patient backlogs and delays. The model can change multiple modifiable factors simultaneously to see the impact on flow.
Decisions can be tested in a risk-free virtual system twin.

Speaking:

4:00

Case study: Developing an Enterprise Data Platform to Increase efficiency and security

Managing 16 public and private hospitals, 21 aged care facilities, Medical research institutes and charitable foundations, St Vincent’s Health is a large, complex healthcare provider. With scale comes the challenges of integrating multiple data platforms. Here, we will hear from Stephanie Owen on how they have undertaken the huge task of creating an enterprise data platform. Stephanie will discuss:

How they have managed governance when integrating multiple data silos
The efficiencies created by unifying data analytics and warehousing
Proving the value of information in order to receive organisational support
The people and culture benefits and challenges
Standardising the technology stack and seeking scalability in the cloud

Speaking:

Case study: Developing an Enterprise Data Platform to Increase efficiency and security

October 23 | 16:00 - 16:25

How they have managed governance when integrating multiple data silos
The efficiencies created by unifying data analytics and warehousing
Proving the value of information in order to receive organisational support
The people and culture benefits and challenges
Standardising the technology stack and seeking scalability in the cloud

Speaking:

4:25

Case study: Using data analytics to create actionable insights and improve patient outcomes

Creating the analytics doctors need to do their research
Improving Data Literacy – our practice
Supporting clinicians to make better decision about a patient’s car
Using your networks and identifying ways of supporting clinicians

Speaking:

Case study: Using data analytics to create actionable insights and improve patient outcomes

October 22 | 16:25 - 16:50

Creating the analytics doctors need to do their research
Improving Data Literacy – our practice
Supporting clinicians to make better decision about a patient’s car
Using your networks and identifying ways of supporting clinicians

Speaking:

4:50

NSW Health Pathology Atlas of Variation - driving positive change in ordering practices at a local level to improve patient outcomes and throughput and reduce unwarranted waste

NSW Health Pathology’s laboratories serves NSW’s population of approximately 7.5 million people with 10.4 million encounters in the NSW Health System, receiving 10.5 million pathology requests, performing 46 million test panels and reporting 285 million results. Craig and Alex will report on:

Overcoming the challenges of disparate data sources and data linkage
Importance of collaborations to understand the challenges, build working relationships and meet desired outcomes
Identifying pathology ordering variation in patient pathways and throughput measures
Drivers that impact pathology ordering, local policy, systems and price setting
System Test Panels and opportunities to move towards intelligent Test Panels

Speaking:

NSW Health Pathology Atlas of Variation - driving positive change in ordering practices at a local level to improve patient outcomes and throughput and reduce unwarranted waste

October 23 | 16:50 - 17:15

Overcoming the challenges of disparate data sources and data linkage
Importance of collaborations to understand the challenges, build working relationships and meet desired outcomes
Identifying pathology ordering variation in patient pathways and throughput measures
Drivers that impact pathology ordering, local policy, systems and price setting
System Test Panels and opportunities to move towards intelligent Test Panels

Speaking:

5:15

Discussion session: Integrating data from silos to derive actionable insights

Why it’s so difficult to obtain access to from multiple data sets in healthcare
How to fast track data integration and spend less time data wrangling
Forming a holistic experience to the patient - getting away from a siloed approach
How to use different sources getting a single view of the patient
Integrating the different technologies so that your data and analytics are usable

Speaking:

Discussion session: Integrating data from silos to derive actionable insights

October 23 | 17:15 - 17:40

Why it’s so difficult to obtain access to from multiple data sets in healthcare
How to fast track data integration and spend less time data wrangling
Forming a holistic experience to the patient - getting away from a siloed approach
How to use different sources getting a single view of the patient
Integrating the different technologies so that your data and analytics are usable

Speaking:

5:40

Networking Drinks in the Exhibition Area

October 22 | 17:40 - 18:30

Speaking:

Thursday 5th March

08:00

Registration, Coffee & Networking in the Exhibition Area

October 23 | 08:00 - 08:30

Speaking:

08:30

Chair’s Opening Remarks

October 23 | 08:30 - 08:40

Speaking:

08:40

Establishing an Enterprise-wide Data Governance Roadmap

Key Healthcare Statistics – ADHB Region
Growth in healthcare costs vs GDP – NZ
Healthcare costs – Historical & Projected
The Challenge - Our goal as a health system
How we have connected data across care settings, and used artificial Intelligence, 3D printing and Big data
The role to be played by Internet of things, Natural language processing, and virtual and augmented reality
The governance challenge: Complex systems landscape, 700+ systems, many legacy systems nearing end of life and an overworked workforce
Data Governance: Our Implementation Approach
Phase 1 – Understanding the Business, Identifying Key Stakeholders and Building support and communicating
Importance of socialising governance recommendations and responsibilities with key stakeholders
Ensuring that minimal work is allocated to data stewards

Speaking:

Establishing an Enterprise-wide Data Governance Roadmap

October 23 | 08:40 - 09:05

Key Healthcare Statistics – ADHB Region
Growth in healthcare costs vs GDP – NZ
Healthcare costs – Historical & Projected
The Challenge - Our goal as a health system
How we have connected data across care settings, and used artificial Intelligence, 3D printing and Big data
The role to be played by Internet of things, Natural language processing, and virtual and augmented reality
The governance challenge: Complex systems landscape, 700+ systems, many legacy systems nearing end of life and an overworked workforce
Data Governance: Our Implementation Approach
Phase 1 – Understanding the Business, Identifying Key Stakeholders and Building support and communicating
Importance of socialising governance recommendations and responsibilities with key stakeholders
Ensuring that minimal work is allocated to data stewards

Speaking:

09:05

From insight to action: Using your data to improve patient outcomes

Comparing the effectiveness of data platforms from multiple jurisdictions, including Victoria

How they are designed to move patient analytics from insight to action
Possible barriers to achieving actionable insights

Speaking:

From insight to action: Using your data to improve patient outcomes

October 23 | 09:05 - 09:30

Comparing the effectiveness of data platforms from multiple jurisdictions, including Victoria

How they are designed to move patient analytics from insight to action
Possible barriers to achieving actionable insights

Speaking:

09:30

Case Study: Using Analytics to predict patient readmission

Epworth Healthcare has developed analytics to measure, with 88% accuracy, the likelihood of a patient being re-admitted, during the original hospital stay. This has huge potential to reduce the burden of readmission of the patient. This session will look at how the team:

Used hospital date to predict which patients would be re-admitted
Created models and tested these over the last 12 months
Are taking steps for preventing re-admission
Deploy a bedside a score per patient
Pushing the project forward to action
Journey to support clinician’s decisions
Being predictive not prescriptive

Speaking:

Case Study: Using Analytics to predict patient readmission

October 22 | 09:30 - 09:55

Used hospital date to predict which patients would be re-admitted
Created models and tested these over the last 12 months
Are taking steps for preventing re-admission
Deploy a bedside a score per patient
Pushing the project forward to action
Journey to support clinician’s decisions
Being predictive not prescriptive

Speaking:

09:55

Panel Discussion: Bridging the Data Talent Gap - How Healthcare organisations recruit, develop and retain top talent

Building a high performing data team is no small task. Finding and growing talent, determining the job functions needed to deliver on projects and creating a cohesive high-performing team requires enormous effort and skill.

This session will guide you on how to overcome your hurdles in developing your Data Science team as the keystone of strategic data-led initiatives.

Strategies to empower, firmly ground and connect your team to the value they’re driving
How to get the right structures in place and then build the people around that
Talent strategy - Identifying talent and growing your team, plus tips on combatting high attrition rates common in analytics
Does your analytics team need a healthcare background?

Speaking:

Panel Discussion: Bridging the Data Talent Gap - How Healthcare organisations recruit, develop and retain top talent

October 22 | 09:55 - 10:30

This session will guide you on how to overcome your hurdles in developing your Data Science team as the keystone of strategic data-led initiatives.

Strategies to empower, firmly ground and connect your team to the value they’re driving
How to get the right structures in place and then build the people around that
Talent strategy - Identifying talent and growing your team, plus tips on combatting high attrition rates common in analytics
Does your analytics team need a healthcare background?

Speaking:

10:30

Mid-Morning Coffee & Networking in the Exhibition Area

October 23 | 10:30 - 11:00

Speaking:

11:00

Case study: Rationalising data reporting across an organisation

Cabrini has had over 130 indicators that are collected and reported across the organisation. Many are very manual and require extensive investment to collect. Given the capacity of any manager, an organisation needs a small set of consistently collected and reported indicators – from the Board to the clinician. Determining what these core metrics are is a challenge. Once determined, Cabrini has been able to develop a structured, unified hierarchy of reporting with defined sources of truth. This session will examine how creating a unified set of key performance indicators (clinical, experience and financial) has enabled consistent strategic focus across the organisation.

Speaking:

Case study: Rationalising data reporting across an organisation

October 22 | 11:00 - 11:25

Speaking:

11:25

Case study: Integrating and analysing data in a Regional Health environment

Looking after a population of 310K people in Western NSW and Far West, Shane Glasheen looks after healthcare information in NSW’s largest health districts in land area. Here he will speak about some of the challenges to overcome in data analytics for a regional health environment, including geographical challenges, Indigenous health, virtual health, and issues with small numbers. He will talk about:

How he is writing the software to put this all together, including automation
Ensuring they are capturing all pre-defined health outcomes KPIs
How to get consistent data integrity from such a wide variety of data sources
Measures used to track closing the gap for Indigenous health
Measuring quality and safety KPIs that affect patient care
Merging of health data sets, both in and out of hospital, to produce a meaningful story of the patient journey

Speaking:

Case study: Integrating and analysing data in a Regional Health environment

October 22 | 11:25 - 11:50

How he is writing the software to put this all together, including automation
Ensuring they are capturing all pre-defined health outcomes KPIs
How to get consistent data integrity from such a wide variety of data sources
Measures used to track closing the gap for Indigenous health
Measuring quality and safety KPIs that affect patient care
Merging of health data sets, both in and out of hospital, to produce a meaningful story of the patient journey

Speaking:

11:50

Case study: Transitioning data analysis to study hospital performance

Queensland Health faces a challenge, where increasing demand for healthcare services is competing with a tough funding environment.
The system needed to build a funding model with enough activity to accommodate predicted growth in demand, within the waiting time performance indicators, that could still fit into the likely funding scenario.
One of the many problems to overcome was the disparate nature of the relative databases. Performance data meets the needs of performance reporting but doesn’t consider activity, and funding data bears no resemblance to performance datasets.
And what even is “demand”? Previous health funding considered demand as the volume of activity that was historically provided, but what about all of the patients still on a waitlist?
To answer these questions the Healthcare Purchasing and System Performance Division collaborated on a project to develop the “Purchasing for Performance” predictive modelling tool.
In this session Ruth will describe how the tool works, and share the many insights gathered along the way, such as:

How to fit round pegs into square holes
Figuring out what “demand” is
Managing expectations
Where to next?

Speaking:

Case study: Transitioning data analysis to study hospital performance

October 22 | 11:50 - 12:15

Queensland Health faces a challenge, where increasing demand for healthcare services is competing with a tough funding environment.
The system needed to build a funding model with enough activity to accommodate predicted growth in demand, within the waiting time performance indicators, that could still fit into the likely funding scenario.
One of the many problems to overcome was the disparate nature of the relative databases. Performance data meets the needs of performance reporting but doesn’t consider activity, and funding data bears no resemblance to performance datasets.
And what even is “demand”? Previous health funding considered demand as the volume of activity that was historically provided, but what about all of the patients still on a waitlist?
To answer these questions the Healthcare Purchasing and System Performance Division collaborated on a project to develop the “Purchasing for Performance” predictive modelling tool.
In this session Ruth will describe how the tool works, and share the many insights gathered along the way, such as:

How to fit round pegs into square holes
Figuring out what “demand” is
Managing expectations
Where to next?

Speaking:

12:15

Case study: How the Victorian Ambulance service is sharing real-time data to improve patient outcomes

Background to the automation piece they have been working on since February this year
Audit the interventions using machine learning
Uncovering important areas of variations in clinical care providers
Using agile methodologies and embedding those learnings
Opportunities: sharing real time data with hospitals
What we currently don’t know: Right now if a hospital has an influx the ambulances can we send the right number of people?
Working together as a system and no longer operating in silos
Increasing data sharing to make demand management decisions

Speaking:

Case study: How the Victorian Ambulance service is sharing real-time data to improve patient outcomes

October 22 | 12:15 - 12:40

Background to the automation piece they have been working on since February this year
Audit the interventions using machine learning
Uncovering important areas of variations in clinical care providers
Using agile methodologies and embedding those learnings
Opportunities: sharing real time data with hospitals
What we currently don’t know: Right now if a hospital has an influx the ambulances can we send the right number of people?
Working together as a system and no longer operating in silos
Increasing data sharing to make demand management decisions

Speaking:

12:40

Buffet Lunch & Networking in the Exhibition Area

October 23 | 12:40 - 13:40

Speaking:

1:40

Case study: The transformation journey from on- premise and complex analytics solutions to simplified and responsive cloud based services to deliver more efficient and faster business outcomes

Speaking:

Case study: The transformation journey from on- premise and complex analytics solutions to simplified and responsive cloud based services to deliver more efficient and faster business outcomes

October 23 | 13:40 - 14:05

Speaking:

1:40

Extended Discussion panel: Implementing a robust data governance framework to ensure high data quality and faster access

Handling the challenge of the breadth of information in healthcare
What good data governance looks like in healthcare and why it is so crucial to patient outcomes
Network governance models for ethical and compliant data use
Does anyone have an enterprise wide data governance framework in healthcare?
Why healthcare providers need a good data dictionary
Establishing Data Custodians - who owns the data in healthcare?

Speaking:

Extended Discussion panel: Implementing a robust data governance framework to ensure high data quality and faster access

October 23 | 13:40 - 14:30

Handling the challenge of the breadth of information in healthcare
What good data governance looks like in healthcare and why it is so crucial to patient outcomes
Network governance models for ethical and compliant data use
Does anyone have an enterprise wide data governance framework in healthcare?
Why healthcare providers need a good data dictionary
Establishing Data Custodians - who owns the data in healthcare?

Speaking:

2:05

Case study: The huge potential of analytics applied to clinical research – Cardiac incidents

How this project is analysing the rawest form of electronic health data analytics
Extracting electronic medical records from a patient’s episode of care including: Ambulance, Emergency Department investigations, clinical documentation, Images
Ensuring this data good quality and Distilled and collated correctly
How this information will be used to show how the facilities are performing and can improved

Speaking:

Case study: The huge potential of analytics applied to clinical research – Cardiac incidents

October 23 | 14:05 - 14:30

How this project is analysing the rawest form of electronic health data analytics
Extracting electronic medical records from a patient’s episode of care including: Ambulance, Emergency Department investigations, clinical documentation, Images
Ensuring this data good quality and Distilled and collated correctly
How this information will be used to show how the facilities are performing and can improved

Speaking:

2:30

Afternoon Tea & Networking in the Exhibition Area

October 23 | 14:30 - 14:50

Speaking:

2:50

Case study: AI supported IoT system for monitoring rehabilitation at home post knee and hip replacement operation

Speaking:

Case study: AI supported IoT system for monitoring rehabilitation at home post knee and hip replacement operation

October 22 | 14:50 - 15:15

Speaking:

3:15

Case study: An interactive live dashboard for risk adjusted Hospital Acquired Complications (HAC)

This case study explains an innovative method to analyse Hospital Acquired Complications (HACs) and compare performance with peer hospitals to improve patient safety and quality of care.

The case study benchmarked performance against external private and public hospitals with the same complexity/casemix. A web based benchmarking portal was designed, allowing hospitals to view results in real time, and drill down to patient level details. Benchmarking each complication type allowed hospitals to identify which complication was causing the most harm, after risk adjustment.

Speaking:

Case study: An interactive live dashboard for risk adjusted Hospital Acquired Complications (HAC)

October 22 | 15:15 - 15:40

This case study explains an innovative method to analyse Hospital Acquired Complications (HACs) and compare performance with peer hospitals to improve patient safety and quality of care.

Speaking:

3:40

Case study: Getting ready for Deep Learning - Modernising and improving data quality and data engineering through standardising approaches to metadata management

This session will showcase the metadata repository (CIDA) project undertaken in the Cancer Institute, which created an organisation-wide approach to the management of metadata, analytics, research output management, data use and security, aimed to modernising the use of analytics and embedding modern data science tools and techniques. It will cover:

Building secure, API-first, data engineering pipelines using modern data science tooling
Tracking data quality and data lineage across web assets
How to approach the design of modular and containerised IT stacks optimised for data science
Using Python and R to deliver web services and interactive analytics
How to address inconsistencies across data nomenclature and developing flexible taxonomies to connect disparate datasets
Replacing traditional ETL with a rapid-development data engineering pipelines
Creating a web based framework for managing research and reporting outputs

Speaking:

Case study: Getting ready for Deep Learning - Modernising and improving data quality and data engineering through standardising approaches to metadata management

October 23 | 15:40 - 16:05

Building secure, API-first, data engineering pipelines using modern data science tooling
Tracking data quality and data lineage across web assets
How to approach the design of modular and containerised IT stacks optimised for data science
Using Python and R to deliver web services and interactive analytics
How to address inconsistencies across data nomenclature and developing flexible taxonomies to connect disparate datasets
Replacing traditional ETL with a rapid-development data engineering pipelines
Creating a web based framework for managing research and reporting outputs

Speaking:

4:05

Case study: The Australian Hospital Patient Experience Question Set – early adoption

This case study describes early adoption of the Australian Hospital Patient Experience Question Set (AHPEQS) and use of a real-time dashboard to drive improvements in patient experience at ward level. Nurse Managers use the dashboard at ward level to view real-time quantitative and qualitative feedback from patients and make changes to improve patient experience.

The survey and dashboard is a key component of Back to Bedside, Healthscope’s change management strategy targeting consistent person-centred care through system and behavioural change.

Speaking:

Case study: The Australian Hospital Patient Experience Question Set – early adoption

April 21 | 16:05 - 16:30

The survey and dashboard is a key component of Back to Bedside, Healthscope’s change management strategy targeting consistent person-centred care through system and behavioural change.

Speaking:

4:30

Improving data linkage to reduce fragmentation and gain a whole view of the patient journey

Identifying patients while de-identifying the data - navigating he checks and balances
Understanding state and federal government efforts to link data sets
Techniques for streamlining the linking of patients across systems while maintaining anonymity
Ensuring privacy and ethics of data use

Speaking:

Improving data linkage to reduce fragmentation and gain a whole view of the patient journey

April 21 | 16:30 - 16:55

Identifying patients while de-identifying the data - navigating he checks and balances
Understanding state and federal government efforts to link data sets
Techniques for streamlining the linking of patients across systems while maintaining anonymity
Ensuring privacy and ethics of data use

Data & Analytics in Healthcare Online

Registration, Coffee & Networking in the Exhibition Area

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Corinium Global Intelligence Welcome Address

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Chair’s Opening Remarks

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Keynote Presentation: Using analytics to improve quality and safety of health services

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Ensuring an accurate data capture system for improved patient outcomes

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Keynote session presented by Qlik

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Mid-Morning Coffee & Networking in the Exhibition Area

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Using and managing first party data to understand behaviour

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Update from the Digital Health CRC - Digital Health data and Technology: Improving the quality of healthcare

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Keynote Discussion Panel: Successfully managing the challenges of patient data privacy, consent and ethics

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Buffet Lunch & Networking in the Exhibition Area

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Track A - Case studies

Case Study: Automated AI approaches for Clinical Coding with Chiang Mai University using clinical data

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Track B - Discussion Groups

Discussion Group: Improving data quality – ending the cycle of garbage in, garbage out

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Track A - Case studies

Case study: Integrating data of disparate types to understand health needs

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Track B - Discussion Groups

Discussion Group: Keeping Patient Data Secure and Protected

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Track A - Case studies

Using linked administrative data to improve outcomes for vulnerable families in NSW

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Track B - Discussion Groups

Discussion group: Prioritising Data within your Organisation - Embedding a Culture of Data, Analytics and Insight Based Decision Making

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Panel Discussion: Data literacy - How to design your data capture processes to enrich your data sets

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Track A - Case studies

Case study: Enabling access to real time data through interactive dashboards

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Afternoon Tea & Networking in the Exhibition Area

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Delivering the right information into the right hands – System Dynamics and the case of Emergency Care

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Case study: Developing an Enterprise Data Platform to Increase efficiency and security

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Case study: Using data analytics to create actionable insights and improve patient outcomes

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NSW Health Pathology Atlas of Variation - driving positive change in ordering practices at a local level to improve patient outcomes and throughput and reduce unwarranted waste

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Discussion session: Integrating data from silos to derive actionable insights

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Networking Drinks in the Exhibition Area

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Registration, Coffee & Networking in the Exhibition Area

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Chair’s Opening Remarks

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Establishing an Enterprise-wide Data Governance Roadmap

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From insight to action: Using your data to improve patient outcomes

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Case Study: Using Analytics to predict patient readmission

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Panel Discussion: Bridging the Data Talent Gap - How Healthcare organisations recruit, develop and retain top talent

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Mid-Morning Coffee & Networking in the Exhibition Area

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Case study: Rationalising data reporting across an organisation

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Case study: Integrating and analysing data in a Regional Health environment

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Case study: Transitioning data analysis to study hospital performance

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