Help Us Develop Our New Open Gov Plan
By Todd Park, Chief Technology Officer, HHS
In January 2009, President Obama issued the Open Government Directive, calling for government agencies to take action to become more transparent, participatory, and collaborative. We issued “Version 1” of HHS’s Open Government Plan on April 7, 2010. This plan has served as our guiding star as we’ve worked energetically to “liberate” HHS data and improve how HHS collaborates with the public and external stakeholders. We are now working on “Version 2” of our Open Government Plan, and would love to get your help in developing it. In particular, we’d love to get your input on the following questions:
- Are there any policy development or program implementation areas which should be areas of particular focus for our open government efforts?
- Are there new forms of public participation with which HHS should experiment? What kinds of new or improved techniques can we utilize to interact in the most meaningful possible ways with the American people?
- How can we more effectively reach non-traditional audiences in order to obtain the broadest level of input possible into HHS planning and implementation processes?
If you could share your thoughts with us on these questions (and any other areas of open government interest), we’d appreciate it very much – please send your thoughts to us at open@hhs.gov. We’re also working with open government stakeholder and advocacy groups on tapping other sources of public input as we engage in plan development. Once we’ve received a full range of inputs from external and internal audiences, we’ll assemble a draft plan. By late March, we’ll make our draft plan available on this website for public comment and feedback.
We look forward to working with you on this effort – thanks so much in advance for your help!
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To whom it may concern, Good afternoon! I have worked with the states as both a state employee and private sector resource for almost 20 years. Through the first HIPAA implementation, NPI, 5010, and now all the ACA, ARRA, HITECH, and other mandates, not to mention ICD-10. In all these initiatives, the greatest strides in open government, both from the federal and multi-state perspectives, has always come through the National Medicaid EDI Healthcare (NMEH) Workgroup. For more than 10 years, this group of more than 800 individuals from the Federal, State, and private sector of the Medicaid Industry have worked together to share ideas, create solutions, and advocate transparency for mutual progress. As HHS seeks new and innovative ways to create “open governmentâ€, my recommendation is to leverage a longstanding and respected organization to promote broad communication. If you have questions or an interest in additional information, please contact me. Thank you for the opportunity to comment. Andrea S. Danes Director, Healthcare & Human Services CSG Government Solutions
Thoughts on some key infrastructure data issues that need to be seriously looked at before there can be an effective sharing of data at any level:
Currently there is a limited focus on Data Quality including the definition at a meaningful level of what quality data is:
o What is good quality Data?
o What is bad quality Data?
o Does scrubbing data really make it more meaningful?
o What is the standard by which we define data and how clear is that definition?
o Will standards for data be interpreted so that multiple submitters can arrive at the same conclusion when analyzing it.
Is there a governance model overseeing data quality and quality remediation to assure that "information" isn't really "disinformation"?
Can data be made accessible in a more timely way (nearer to real time)?
Is aggregation consistent and clearly defined?
o What was the intent of the aggregation? Is that intent clear and consistently interpreted?
o Are the codes and other values used to aggregate data defined and consistently used?
o Was data aggregated differently over time?
De-identified data that maintains uniqueness of persons and provider is necessary to assure quality and analyze distributions. Currently much of the de-identified data loses the association to unique (while de-identified) entities.
Defining unique provider entities is still a major issue with large databases and requires a master provider indexing model to reconcile duplicate entities. The NPI does not really identify uniqueness because of the manner in which it is used for processing purposes. Identifying uniqueness at the level of bricks and belly buttons is still a difficult challenge
Attribution of a variety of metrics is still a significant challenge not only because of the difficulty in defining true unique entities, but also because of the varying roles that provider entities and others play in the care of the patient. Limitation of attribution in these metrics must be clearly understood and communicated
Historical data is often created with different standards and definitions over time. Particularly with the ICD-9 to ICD-10 transition, much of the data at a granular level is not comparable. Normalization models will be require to aggregate data for comparison and trending across these implementation periods at level that represents reliable comparisons. Before we can really rely on Open Government as a source of reliable information, I believe that there needs to be a serious and focused effort on addressing:
1. Well defined - harmonized data content standards
2. Data quality
3. Empowered data governance
4. Consistent and reliable unique entity identification
5. Reliable attribution models with a clear understanding of limits
6. Timely data
7. De-identification models with surrogate identifiers that allow for analysis at the (de-identified unique entity level)
8. Ongoing monitoring of data completeness, quality and reliability.
9. Data aggregation models that are shared and applied to assure “apples to apples†comparison of aggregated data.
10. Historical data must be consistently normalized to account for changes in data definition and aggregations over time over time. This will require serious and empowered leadership to drive an industry that seems to abhor standards to one that can communicate with the accuracy and reliability of the b banking industry.
In response to HHS CTO Todd Park's call for input, on January 27th "HHS is now working on “Version 2†of its Open Government Plan, and we are seeking help and feedback in the development phase. HHS is seeking your input on the following questions:" Siemens is pleased to submit these suggestions. Input to HHS Open Government 2.0 Initiative Thank you for the opportunity to provide input to Version 2 of the HHS Open Government Plan. We look forward to reviewing the draft plan when it is issued. We have reviewed Version 1.1 of the Plan, and have observed some of the good results of the initiative thus far, such as Health.data.gov and the CMS Dashboard. We commend HHS for promoting the goals of openness, collaboration, and innovation. We understand the necessity to protect confidential information, which requires due diligence before data is exposed to the public prematurely. But we also appreciate HHS’ recognition that the data is a treasured national resource. Pages or section numbers referenced in our suggestions below are from Version 1.1 of the HHS Open Government Plan. 1. Make the prioritization process more transparent and democratize it through web-enablement Our first suggestion addresses the second question that Todd Park asked in the request for input: “Are there new forms of public participation with which HHS should experiment? What kinds of new or improved techniques can we utilize to interact in the most meaningful possible ways with the American people?†In section 3.3, there is mention of an ongoing process for prioritization of what data should be released. It appears that the prioritization is internally driven by the HHS data council. Since the public “doesn’t know what it doesn’t know?†HHS could help by providing a “menu†of categories of data that are available (but not yet released) from HHS and under consideration, and a process for “voting†or at least providing input (stakeholder reasons why category X would be helpful). We believe that using modern web technologies (many of which are acknowledged in the plan) such as blogs, web surveys, and other social media, would provide a democratic way to participate in the prioritization process. More traditional means such as public hearings, pose a “barrier to participation†because of the time and expense of attending. And FACAs, while offering some expert input from a hand-selected group, do not provide adequate channels for participation, since public comments are not allowed during the discussion, only at the end, with no opportunity for interaction. 2. Reduce the time delay for release of data The release of HHS data such as the Medicare Claims Basic Files are an excellent start. We have noticed that they are typically at least two years old, and believe that HHS should strive toward increasing its timeliness to be within 6-12 months, or even sooner (depending on the type of data: we realize that claims may take longer to close than other types of data). While it may not be realistic to be “up to the minute†such timeliness would help innovators act upon the most relevant data, so that their applications are not based on “old news.†3. Use public/private partnership to measure the impacts of programs such as ARRA HITECH, PPACA, Medicare SSP In response to the question: “Are there any policy development or program implementation areas which should be areas of particular focus for our open government efforts?†we have this suggestion. In concert with organizations such as the HIT PC, NQF, etc., determine the metric that indicate whether the improvements that those programs are designed to stimulate are occurring over time. Data from Meaningful Use attestations, ONC ATCB certifications, etc., would be valuable sources especially as the numbers grow, correlated with data on morbidity and mortality particular in the areas where MU measures were required. For example, does requirement for EHRs to generate stroke CQMs for MU actually improve the quality of care given to stroke patients? Does the requirement to capture smoking data in EHRs result in decreases in smoking? Answers to these complex questions will require cross-cutting collaboration within HHS as well as with private industry, because the data may not be obtainable from a single source but require correlation of data from multiple programs and databases or files. HHS may choose to analyze such questions themselves, but they could also release the data to enable innovators (e.g., experts in analytics, suppliers of sophisticated data mining tools) to connect the dots. Thank you for the opportunity to provide input. David Tao, Karen Nielsen, and Rhonda Taller, on behalf of Siemens Healthcare
Revamping Grants.gov to free the data would be awesome. There is so much data in grants listing, that freeing the data could allow people to build apps to better target and spread info about grants, and then increase the quantity and quality of grant applications, leading to better outcomes from grant funding.