Appendix E. Additional data sharing information, resources and considerations

Terminology and data exchange standard definitions

Terminology standards provide a foundation for interoperability by improving the effectiveness of information exchange. As such, terminology standards address a fundamental requirement for effective communication: the ability to represent concepts in an unambiguous manner between a sender and receiver of information. Whereas terminology standards specify the language that will be used by the sender and receiver of information, vocabularies specify the words. Most communication between systems relies on terminology standards, structured vocabularies, code sets, and classification systems to represent health concepts. At this time there are no defined terminology standards for school readiness, school disciplinary, or school attendance indicators; however, there are various data sources that can be used to inform the data needed to make decisions. 

Data exchange standards provide the framework or method for the exchange, integration, sharing, and retrieval of information. They exist to ensure the availability, integrity, and confidentiality of personally identifiable data to confirm it is accessible when and where needed while protecting patient privacy. While there is no one standard for the exchange of school readiness, school disciplinary, or school attendance indicators, data standards exist for SDOH. The Gravity Project, affiliated with the standards development organization Health Level Seven (HL7), aims to establish coded data elements and other national standards related to SDOH. Data standards exist for the exchange of behavioral health information, including developmental screening and surveillance, yet most exist to support pediatric electronic health records, e.g., the HL7 Child Health Functional Profile.

Common education data standards

The Common Education Data Standards (CEDS) Initiative is an “education data management initiative” that assists with the data exchange in preschool to grade 20 to workforce,37 and resources on suggested data elements that are relevant to the school readiness and school attendance indicators. CEDS includes a common vocabulary, a data model and tools that map local data elements to CEDS standardized values. While CEDS is currently being used by researchers and universities, it has not been widely used by health departments. However, the sources of information may inform health departments about attendance status, school readiness, and disciplinary actions. Data mapping tools are available from the CEDS website and may be helpful if data exchange is possible. The data mapping tools allow agencies to identify the organizations collecting the data within their jurisdiction. 

The attendance status element is associated with attendance events and may assist in the exchange of information for present, excused absences, unexcused absences, and tardies. 

CEDS data elements support the early learning developmental domains related to assessing a child’s kindergarten readiness. The assessment domains may be of interest to programs, yet depend on a state’s definition of school readiness. 

United States Core Data for Interoperability

The United States Core Data for Interoperability (USCDI) is a standardized set of data classes and data elements that promotes health information exchange. USCDI is part of a standard in the Office of the National Coordinator (ONC) Cures Act Final Rule and establishes a baseline for sharing electronic health information to support patient care. USCDI may be leveraged to share demographic information and SDOH information with state, territorial, local, and tribal agencies as they establish records or collect data on children. This data set is available in electronic form but may not be widely implemented in school record systems. 

Civil rights data collection

The Civil Rights Data Collection project supports the collection of data required by OCR from public schools every other year.38 Aggregate data available by school and district include enrollment demographics and disciplinary actions. This data source may be used to provide information on the population of the school. Tools available include comparison data, detailed graphs, and outcome rate calculators. While this data is informative, it is often two years behind in data collection. 

Discipline data points include:

  • Number of students who received one or more in-school suspensions 
  • Number of students who received one out-of-school suspension
  • Number of students who received more than one out-of-school suspension
  • Number of students who were expelled
  • Number of students who were arrested for school-related activity

Additional data exchange considerations

  1. What questions will the data be answering?
    1. Before reaching out to partners, health departments should be able to describe the questions they hope to answer by collecting CAMH data.  
      1. Example scenario: The state has undergone redistricting, combining schools that previously were separated. Is school attendance similar in the combined school as it was when the schools were separate? 
    2. Refer to the Partnerships section of this playbook for more information.
  2. What are the desired data sources and data elements? 
    1. Determine what systems provide data to inform CAMH work and exactly what data elements are needed to assess and improve CAMH. It is important to consider all data needed to support specific analyses and generate any desired reports. The needed data should be documented along with the standard code system and value set for each data element, when such a standardized vocabulary set exists. Consider developing this data model with your data sharing partners.39
  3. How will the data be exchanged? 
    1. Will data be pushed to the agency, or will it be pulled in? Will the agency obtain aggregated or individual-level data? Are there any intermediaries in the data exchange? This reference provides information about the surveillance data exchange processes and key considerations when planning data exchange.
  4. What are the legal issues that need to be addressed in data exchange? 
    1. Legal and policy clarification authorizing data collection and use should be analyzed in terms of acceptability and appropriateness from the perspectives of policymakers, public health, healthcare providers, and the general public. Reference the Summary of Laws Related to CAMH and the legal considerations included within this playbook.
  5. How confident is the health department in the quality of this data? 
    1. As data are pushed to the health department or pulled in, the agency should consider data quality and validity. Although all data, including that used to assess school attendance, disciplinary actions, and readiness, has limitations, it is still important to assess data quality.

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