Tutorial Module 6: Rationale for Moving to Data Standards in Public Health

With some notable exceptions, the public health and health services research communities have not actively participated in national standards discussions or implemented national standards at the state or local level.(1) Unless serving as providers or insurers, public health organizations face no clear federal mandate to adopt uniform national standards required by the Administrative Simplification Provisions of the Health Insurance Portability and Accountability Act (HIPAA), and the rationale or business case for such action has not been communicated widely. This needs to change, because, over time, uniform data standards will increase access to, decrease costs of, and improve the quality of public health information. The purpose of this module is to deliver messages about the importance of data standards in public health.(2)

Data standards increase the efficiency of data transactions and reduce costs

Public health can expect benefits similar to the private sector by using uniform standards for electronic data interchange (EDI). The private sector’s primary motivation to create standards for EDI in the early 1990’s was to lower administrative costs and improve operations. The federal government via the HIPAA legislation of 1996 mandates that the United States adopt national uniform standards for electronic health care transactions. National uniform standards for EDI decrease the time and money associated with administrative transactions and improve the quality, quantity, and accessibility of information.

For the public health community, electronic interchange of data and standards adoption will allow faster processing of and response to data received, reduction of errors, and consistent reporting. For providers, especially those laboratories or hospital systems serving multiple states, standards will decrease the burden associated with reporting data to multiple public health jurisdictions.

The benefits of standards for EDI are expected to outweigh the hardware, software, and training costs necessary for implementation. Electronic submission of claims for reimbursable public health services (including Medicaid) will reduce costs to public health agencies and/or increase returns on investments (ROI).

Data standards are necessary to transition systems of data flow from paper to electronic

The transition from paper-based to electronic transmission of public health data requires national data standards. Electronic data transmission in public health (of emergency department data, for example) will increase the speed of data reporting and support a more rapid response to public health threats. Automation improves compliance with reporting requirements and completeness and timeliness of reports.

Automation frees up the time of public health workers to do more important tasks like investigation, analysis, and response. Public health departments will spend less time waiting for data, reentering data, searching for data, and cleaning data.

Standards improve public health’s ability to perform core functions

Standardization is necessary to carry out state and federal legal mandates for vital statistics, disease reporting, and assuring the population’s health. Standards already define the data collection processes for the national vital statistics system, as well as rates of natality and mortality for reporting purposes. National electronic transmission standards will complete the package. Access to better data through adoption of data standards will improve the ability of public health officials to:

• Identify public health threats;

• Assess the health status of the population;

• Focus programs and policies where they are needed most and are proven to be effective;

• Inform and educate people about health issues;

• Evaluate policy and program effectiveness; and

• Conduct research to improve health and health care.

(See Module 1 for more information about public health core functions. See Modules 3 and 4 for more information about public health data and its use.)

Standards improve data quality and utility

When standards are used to collect data, the quality and utility of data improve at data aggregation, synthesis, analysis and reporting stages. “Without standards, data are not meaningful; they are random.”(3)

Data standardization improves the ability to link data from different sources or programs and increases its comparability. Data standards facilitate the identification of critical linkages (e.g., across disease types, between environmental factors and disease). For example, linkage of data sets across diseases can identify critical relationships such as that of multidrug-resistant tuberculosis to HIV.

Data standards make comparing data across states and localities possible. Public health data from seemingly unrelated events across the country can be analyzed to identify patterns and trends and suggest public health actions to safeguard populations. For example, Escherichia coli (E coli) outbreaks might be related to the same food contamination in multiple states.

Data standards support the larger goal of integration

National data standards are necessary to support the larger goal of integration. Public health’s core functions are accomplished through partnerships among federal agencies, state and local health departments, hospitals and physician providers, laboratories, educational institutions, associations, foundations, communities, and individuals. Data from these various sources reside in disparate systems, introducing informatics challenges. These data sources must be integrated securely and accurately, with individual-level data compiled into usable, aggregate forms at the population level. “This information must be presented in clear and compelling ways to legislators and other policy makers, scientists, advocacy groups, and the general public.”(4)

(See Module 2 for more information about the structure and function of public health and Module 3 for more information about the variety of public health data. See Module 8 for more information about public health informatics.)

Data standards and integration are necessary to support linkage of different data types (e.g., administrative, clinical and survey data) at the individual level for research and decision making purposes, while protecting confidentiality and privacy in a secure environment. Standard identifiers will create the ability to link different data types to create a more complete picture of the health of the public and how various factors impact it.

Integration can occur at many levels: across programs; across organizations; across jurisdictions; across levels of government; across settings of care; across public and private sectors; or across different types of data. For example, integrating and comparing vital record data, such as fetal death data, with Medicaid data may help to understand precursors of infant mortality. Some states are already developing systems by implementing standards that integrate data across the full range of their programs, e.g., Missouri, Utah, Illinois, New York. States can achieve economies of scale in information system development if they work together. Also, integrated data systems increase the ability of our public health system to identify and control threats such as bioterrorism, multi-drug resistant bacteria, and emerging infections that cross programmatic and geographic barriers.

Better and more comparable data support performance measurement and improvement

Comparable data allows public health officials and researchers to better evaluate programs and strategically allocate resources. Measuring and comparing performance relative to national benchmarks, such as Healthy People 2010 objectives, provides an incentive for improved performance.

An electronic environment is emerging in the health sector, including public health, for which data standards are the foundation

The care delivery system is rapidly moving to an electronic environment both for administrative transactions and for clinical data management and exchange to promote better use of information for health and health care. Data standards are the foundation of this National Health Information Infrastructure. Public health professionals will improve public health practice as well as to preserve and strengthen its ties to the care delivery system by adopting standards.

There is a critical distinction between entities creating their own electronic environment versus entering the emerging e-environment (Internet connection) in the health care sector. Some public health organizations may have achieved technical sophistication specific to their organization or specific programs. However, a move to an electronic environment based on proprietary technologies, applications, and systems misses the larger goal of interoperability across all programs and jurisdictions and with data trading partners. Systems based on data standards reduce the investment of organizations in building customized interfaces in order to share or integrate information.(5)

Usefulness of public health data will be jeopardized if public health leaders are not engaged in the standards setting process

If public health officials or researchers choose not to participate in the standards development discussion, they run the risk of data standardization policies being developed that may not support needed access to data by public health. Absence from the standards setting table may lead to the development of standards that do not meet public health and researcher needs, e.g., missing data elements or poorly defined data elements.

Internet References

• Administrative Simplification Statement by Bob Davis, New York State Department of Health

• American Public Health Association (APHA)

• DHHS Data Council

• Healthy People 2010 Initiative

• Health Plan Employer Data and Information Set (HEDIS)

• Illinois Department of Public Health

• Massachusetts Health Data Consortium

• National Health Information Infrastructure

• Public Health Data Standards Consortium

Endnotes

(1) The Public Health Data Standards Consortium is filling a gap in the national standards setting process representing public health and health services research communities.
(2) This module was adapted from Appendix D of the Public Health Data Standards Consortium Education Strategy Final Report. Prepared for the National Center for Health Statistics. Prepared by The Lewin Group, in conjunction with the National Association of Health Data Organizations and the Public Health Data Standards Consortium Education Strategy Work Group. May 2001.
(3) Interviews with Robert Kambic and Anna Orlova, Johns Hopkins University. October/November 2002.
(4) O’Carroll, Patrick W., William Yasnoff, M. Elizabeth Ward, Laura H. Ripp, Ernest L. Martin, eds. (2003). Public Health Informatics and Information Systems. Springer-Verlag. New York, NY.
(5) Interview with William Yasnoff, National Health Information Infrastructure, Department of Heatlh and Human Services. November 2002.