Transparency – What does it mean and how can it be achieved?

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Transcript Transparency – What does it mean and how can it be achieved?

Transparency in health care: Perspectives
on the potential of heath care “big” data
Public Sector HealthCare Roundtable
November 7, 2014
Jeanne De Sa, Principal
Healthsperien, LLC
Where is all the money going? Some context…
Movement away from FFS
and silo in payment,
toward “value based” and
population health models,
ways to transfer risk
Focus in areas with
unexplained variation in
care, growing cost
“Appropriateness” of care,
emphasis on use of
evidence-based guidelines
Input on clinical
transformation, care
models for specialty
Focus on care
coordination, smoother
transitions; primary care
and integrating with
specialty care
Right tools & data to
caregivers, families and
patients (shared decision
contracting, purchaser
leverage on providers
Nothing to see here! Why transparency?
• Researchers – want data on prices and quality to fill in gaps in system—wide
knowledge; how transparency can impact provider prices, consumer behavior
• Policy makers/regulators – want to support range of initiatives related to
quality and efficiency, understanding cost drivers, advancing health reform
goals, implementing cost-sharing rules
• Providers – benchmark cost and quality against peers, more consistency in
measures to report, show value to purchasers
• Health plans – develop initiatives to combat cost growth, offer members
lower cost, higher-quality options, reduce costs of innovation
• Consumers – information to help engagement, empower relationships with
providers, reduce out-of-pocket costs; concerns with
• Purchasers - paying for value and quality, reduce costs, meet needs of
employees and encourage engagement, develop good relationships with
providers in networks, communities.
“Big data” – the data is here and more is coming
More than traditional claims data
• Clinical sources, EHRs, medical charts, socio-demographic, adverse event/patient
safety reporting, vital statistics
• Day-to-day practice of medicine
• Genomic
• Mobile devices, patient-generated, social networks
• Images, video
• Sourced from providers, payers, public and private data utilities, patients
Trends and tools have evolved – way beyond where we were 5 to 10 years ago
• Tools map, normalize and validate data, to facilitate use in research and analysis
• Enabled by data warehousing, extraction and mining techniques
• Advances in statistical methods on working with structured, unstructured data;
advent of machine learning/natural language processing
• Computing power enables fast analysis of large information sets
• Multiple ways to access, organize, present data; application programming interfaces
(APIs) for complex data sets allow programmers/developers to make accessible
Health care data and analytics - yielding insights
Generation of vast new knowledge
Identification of variance, avoidable utilization; prediction of non-adherence
Opportunity identification
Allows different views of total cost of care, episode/care paths…
Improved accuracy of diagnoses
Data integration – claims and clinical; clinical data lets you look at
situational/early risks, adds value to claims analysis
• Unstructured formats provide rich, observational data, can supplement RCTs
• Drives population analytics; risk-stratification, predictive disease models,
focused opportunities to improve
• Real-time data; oriented toward workflow, clinical decision support
Health care data and analytics - enabling innovation
• Practice improvement, care process redesign
• Improve prevention, risk-assessment, quality (Star) ratings, compliance,
patient experience
• Inform payment and delivery model development; design and evaluate multipayer demonstration models
• Benchmarking to peers, development of risk-based analysis tools
• Develop risk-sharing, partnership opportunities with other providers
• Develop episodes of care, quality metrics
• Support outcomes-based payment approaches (performance bonuses,
• Facilitate transparency initiatives, research
• Show value to consumers, purchasers and payers
Transparency in action
State all-payer claims databases (APCDs)
Medicare and QE’s
Commercial claims data sets, Health Care Cost Institute, FAIR health
Clinical-claims initiatives
Private transparency tools for consumers
Mobile apps
Quantified self movement
The future?
Questions/risks for the future
Vast potential to address costs and quality – but will it be realized?
How can purchasers of care be more effective?
Capturing what we need to in a targeted way? Do we just have more noise?
Is data getting to the right people in the right way for the right purpose?
Are the incentives there and appropriately aligned?
Are providers on board? Agents or barriers to change?
Might price transparency lead to provider collusion?
Will consumers really engage/shop with more information?