innovation / Technology

Democratization of Data: Sharing with risk in mind

March 27, 2017

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The challenges identified in our last post, clearly indicate there is no single universal method for de-identification of data. Clarity around what should and shouldn’t be considered identifiable information can in some cases be dependant on the context of how data is used and ever-changing as auxiliary data becomes available elsewhere. As a result, the risk is never zero and should be compared against the value gained in sharing the data. This process can be as simple as understanding how the value in sharing will create benefits (e.g. optimizing acute care practices and thus reducing healthcare costs) and/or helping other citizens while periodically assessing risk of re-identification based on how data is being shared.

Sharing data, an imperative for value based funding models

There is growing consensus that value based funding can be one of the most significant changes to how systems practice healthcare in decades.

In a 2013 McKinsey and Co report[2] discussed the value of releasing data to analyze the healthcare ecosystem at large. In it, it cited five key pathways that contribute to the overall delivery of care and capture the value derived between the balance of cost and outcomes (patient impact). The five pathways are:

  • Right Living – Patients generate value by taking an active role in self-management, disease and disease prevention. We see an increasing trend towards wearables and other assessment services (23andme) that generate tremendous amount of data that help residents make appropriate decisions towards active self-management
  • Right Care – This involves patients getting timely, appropriate treatment in a coordinated approach. At a minimum this assumes there is a common understanding of the patient’s status in order to work towards a common goal. In the context of Ontario, referral services provided by the CCAC can play and significant role in orchestrating this type of coordination across the continuum of care providers. Additionally, Right Care means the appropriate level of care is provided given the patient’s needs. This relies heavily on the use of protocols to help standardize efforts
  • Right Provider – Finding the right professional that can meet the needs of the patient both given the complexity of the scenario as well as proven outcomes of the provider
  • Right Value – This involves continuous optimization of the value provided to patients while ensuring quality and outcomes are preserved. Again, having data improves the measure of clinical outcomes to support optimization of value
  • Right Innovation – Finally, the data generated across the network of care providers can be used to drive innovation in healthcare through research institutions, improve outcomes in clinical trials and provide quality data sets for public health researchers.

The five pathways within the continuum of care represent critical steps towards the execution of value based funding. That is, coordination and sharing of data is necessary to fully realize the benefits of value based funding. A health system cannot determine the optimal provider without knowing the context of the care required. Nor can you optimize on value provided to patients without knowing the type of care provided and the capabilities of the provider. At its core, an integrated system ultimately must support seamless access to data to drive continuous optimization.

Check our previous posts in this series:

Democratization of Data

The Democratization of Data: Policies and Practice

[2]http://www.mckinsey.com/~/media/mckinsey/industries/healthcare%20systems%20and%20services/our%20insights/the%20big%20data%20revolution%20in%20us%20health%20care/the_big_data_revolution_in_healthcare.ashx
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