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Digital Data Improvement Priorities for Continuous Learning in Health and Health Care Workshop Summary (2013) / Chapter Skim
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3 Digital Health Data Uses: Leveraging Data for Better Health
Pages 15-26

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From page 15...
... • ACOs represent an alignment of incentives for the collection of higher-quality data, with greater completeness and accuracy, and the increased liquidity of this data. Kush • Data standards are key to improving data quality.
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From page 16...
... • Public health surveillance systems must be prepared to take full advantage of the data influx resulting from implementation of Meaningful Use. • Linking public health and direct health care services research through data will serve to strengthen the population-level ap proach to surveillance.
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From page 17...
... PRACTICE MANAGEMENT In his discussion of the digital data utility and its role in clinical practice management, Mark Leenay emphasized the requirements necessary to enable sustainable private health information exchanges while ensuring data are connected, intelligent, and aligned. Actionable data at the point of care, increased data liquidity, and integration of data across the care continuum, as well as across different types of data, are all integral to incorporating digital health data into practice management.
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From page 18...
... In summary, Leenay underscored several priorities to improve integration of the digital data utility into clinical care moving forward: identity resolution, information exchange standards, registries, and attention to disparities. Identity resolution will be critical to increase the accuracy of digital record use for patient care; strategies to develop and improve current dataset systems must include a focus on standards and normalization to facilitate coordinated information exchange.
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From page 19...
... As depicted in Figure 3-1, Kush laid out these requirements on a sliding scale, dependent "Sushi-Grade" Clinical Decisions Regulated Research Signal Validation; Quality Requirements Active Safety Surveillance Basic Research Signal or Trend Detection Nonmedical Sales and Marketing Type of Project "All-You-Can-Eat Buffet Grade" FIGURE 3-1  Spectrum of data quality requirements based on intended use. SOURCE: Reprinted with permission from Rebecca Kush.
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From page 20...
... meets global regulations for collection of electronic research data and produces the minimum dataset needed on any clinical trial for regulated purposes. This combination of workflow enablers and standards has been used in safety reporting, regulatory reporting, and Phase 4 trials; and presents an opportunity to support research with EHRs and contribute to the process of research informing clinical decisions faster with higher quality information.
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From page 21...
... Additionally, Kush noted, data quality measures should be considered and incorporated throughout the postmarketing process. In her final comments, Kush emphasized that greater standardization offers considerable promise for clinical research moving forward, particularly in leveraging EHRs for research.
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From page 22...
... The data management system also links the EHR to a clinical trials database, providing clinicians with the means to identify relevant trial eligibility criteria. All of these strategies, Levy emphasized, offer promise for the effective and efficient incorporation of complex and varied digital data into the process of cancer care.
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From page 23...
... SUPPORTING PUBLIC HEALTH AND SURVEILLANCE AT THE NATIONAL LEVEL In the context of public health surveillance, data quality has varying definitions. As James Buehler of the CDC explained in his comments, quality requirements depend on the public health purpose the data are serving.
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From page 24...
... Accuracy is crucial for monitoring cancer clusters, while currency, comprehensiveness, and access to the primary data source all are relevant for public health surveillance and clinical decision support. These quality characteristics all contribute to the usability of public health surveillance data today.
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From page 25...
... Public health agencies need similar incentives and support to modernize state and local systems in order to enable bidirectional flow of this information. Additionally, LaVenture noted that better use of existing standards and adopting new standards for the content and quality of data will reduce variability and increase usability for multiple purposes, and continuous improvement of data sources will ensure that their output is of the highest quality possible.
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Key Terms

  • health surveillance
  • health data
  • digital health
  • digital data
  • quality requirements

  • health information
  • practice management
  • translational informatics
  • decision support
  • surveillance data

  • data utility
  • clinical care
  • regulated clinical
  • clinical decisions
  • care services

  • information exchange
  • kush emphasized
  • clinical data
  • quality data
  • direct health

  • linking public
  • supporting public
  • clinical decision
  • quality information
  • quality measures

  • regulated research
  • services research
  • information management
  • research process
  • rebecca kush


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