Building Data Capacity for Patient-Centered Outcomes Research Interim Report 2–Data Standards, Methods, and Policy (2022) / Chapter Skim
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4 Data Policies and Other Data Infrastructure Considerations
4 Data Policies and Other Data Infrastructure Considerations
Pages 45-54
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From page 45... ...
This includes addressing basic resource needs both in the clinical setting and at an individual patient level, as well as using data to address population health issues. Riley noted that the District of Columbia Medicaid agency is currently working to help develop a community-level social needs screening referral and resource inventory and is also working on ways to support data collection, sharing, and use to improve clinical care delivery and population health.
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From page 46... ...
Approaches to data sharing need to consider the sensitivities, and balance the need to reduce how many times people are being asked to provide the same information with the need to ensure that those who provide the data have confidence in giving permission for the intended uses, which could range from improving their own care to fulfilling a broader purpose. In terms of interoperability and combining data from multiple data sources, Riley argued that clinical claims data that are being collected from nonclinical entities is one area that represents a challenge.
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From page 47... ...
He said that it is important to consider not only the implications of research bias, but also social bias. For example, gender information has historically not been considered useful for record linkages, because this information typically has binary values in electronic health records.
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From page 48... ...
The information available in health records to identify a person for the purposes of record linkages is also constantly changing. While b inary gender is captured in virtually all electronic health records, Kho and his colleagues have been noticing an increase in the availability of data on sex assigned at birth and sexual orientation.
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From page 49... ...
On the patient-centered side, there is a need to support efforts that advance robust identity matching across data sources, in part to overcome the challenges posed by data fragmentation, but also to address the need for longitudinal data. Some examples of projects that are targeting identity matching to support more comprehensive and longitudinal data are Gravity and the Da Vinci Payer Coverage Decision Exchange.
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From page 50... ...
There are also provisions for the use of limited data sets, which involves removing some identifying information but allowing some identifying data elements to be left in. McGraw said that the Common Rule is not included among the laws that govern data disclosure, because the Common Rule is a research ethics rule, not a privacy rule.
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From page 51... ...
However, the new information blocking rules1 that went into effect in April 2021 create a presumption for sharing electronic health information for any lawful purpose, including research. These rules apply to health care providers, certified electronic health records vendors, and health information exchanges.
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From page 52... ...
The revisions proposed at the time were to expand the access, use, and sharing of PHI from treatment, payment, and health care operations to also include "data research." In 2015, H.R.6 passed the House by a vote of 344 to 77, but it did not pass the Senate. Detmer described several current prevailing options for data sharing, clinical registries, and de-identified data sets, each of which he considers flawed.
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From page 53... ...
A theme that emerged from the discussion was the need to better under stand what type of information is truly important to people. Participants discussed projects such as Pastors 4 PCOR that involved community-based organizations to facilitate community engagement in research, identify specific disease priorities, and build trust.
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From page 54... ...
The workshop made it clear that there are concerns about the laws and rules governing data access and data sharing. HIPAA, in particular, was developed several decades ago, and its approach to setting thresholds for data disclosures makes it outdated.
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