Partnering For Timely, Accurate, And Complete Data
November 18, 2022
Utah Department of Health and Human Services
Introduction
As described in the report Public Health Forward: Modernizing the U.S. Public Health System, timely and actionable data are central to public health emergency response and program planning efforts. Modern and efficient information technology equips public health departments to fulfill these responsibilities, but technology alone does not ensure that health departments receive data when they are needed most. For this reason, public health departments must devote time and energy to supporting partners in submitting data that are timely, accurate, and complete.
Context
For several years, the Utah Department of Health and Human Services (UT DHHS) has worked to collect higher-quality data from its partners in a more streamlined fashion. The health department revised its communicable disease reporting rule to, among other things, mandate electronic reporting. It focused on international standards for electronic messaging and engaged with partners to move away from the burdensome system of manual data submissions to more efficient processes, all with a goal of enabling partners to provide complete and correct data the first time.
Before potential changes are published for public comment, it is helpful to talk to people who are required to submit data about potential barriers, challenges, and concerns. This step gives the health department an opportunity to make modifications that improve the regulation’s chance of success before going through the formal approval process.
Data collection is at the heart of health informatics, i.e., acquiring, processing, and studying health data. It is important to ensure that partners are equipped to manage their data submission efforts in a way that supports health informatics. This entails going beyond working with information technology (IT) groups to include staff with public health/population health expertise when setting up or otherwise improving data collection systems. This more comprehensive approach entails educating public health/population health staff about health informatics so that they are prepared to provide IT staff with resources and directions to ensure that data collection proceeds smoothly. This approach also promotes buy-in across the agency, as partners appreciate how their data submission efforts benefit them through the health department’s health informatics work.
Providers may be reluctant to share data about their patients because this is confidential information and they do not want to risk violating patient privacy. Therefore, it is important to specify in state rules how data are secured, conditions under which patients are contacted, when data are deidentified, and how long data are kept. It is important to take the time to explain this to providers and listen to their concerns to help build trust, correct any misconceptions, and otherwise address barriers that could impede data collection processes.
UT DHHS requires that all results of certain communicable disease tests, whether positive or negative, be submitted. Submission of negative tests can be particularly troublesome for providers; they may understand the need for public health departments to contact people who test positive and not be aware of the value of negative test results. One example of a reason for this practice is that it is possible to determine the time span when someone became infected if the individual previously tested negative and later tests positive, e.g., for cases of Hepatitis C or HIV. This is important because people who are newly infected are clinically managed differently from people who have had an infection for a long time. Another example of the need to report negative tests can be found with Lyme disease, which entails a series of two tests; both tests must be documented as negative before the case can be closed.
What data can and cannot be collected and shared is complex. It is imperative that health department staff understand the legalities and explain them to partners in a consistent way. Some providers may have concerns about how patients’ data are stored and who has access to them, so understanding safeguards that are in place to protect confidentiality may improve compliance.
UT DHHS stores identifiable reportable disease data for 18 months, after which they are deidentified. Data remain identifiable to enable the health department to follow up on cases as needed, identify new cases in people who previously tested negative, and for other clinical and public health purposes. After that time, the deidentified data are kept for surveillance purposes.
Hospital systems, commercial laboratories, local health departments, state health department partners, and constituents can benefit from data that have been collected. Ensuring accessibility can also generate support for data collection efforts.
This approach facilitates relationships, which may lead partners to reach out with questions before submitting incomplete or inaccurate information. Moreover, it can streamline communications, decreasing frustration and confusion that can result from excessive outreach from different health department staff. Finally, this approach also streamlines the work of health informatics staff by providing them with a high-level view of related issues (e.g., issues that affect different program areas) and facilitating their ability to identify redundancies.
UT DHHS has an informatics team that supports communicable disease, environmental epidemiology, and health promotion and prevention at the division level.
Routinely ask partners about pain points they experience in submitting data and their suggestions for improvements and communicate with partners when changes are implemented.
Tribes are not legally obligated to share their data and may be reluctant to do so because of the deep-rooted mistrust many tribes have for government agencies that stems from historical oppression and government malfeasance. Take the time needed to establish trust and engage tribes in the public health system. Thoroughly discuss surveillance processes, the value of health informatics, and mutually beneficial ways to use shared data to make health improvements.
Thoroughly orient health department staff to data collection requirements to ensure they understand the health department’s data stewardship and authority and are prepared to work within these boundaries.
The technology that supports public health informatics must be dependable or it will be more difficult to convince partners of the value of data collection efforts.
Health department contacts in partner organizations are typically information technology staff who do not have health or public health expertise but rather focus on computers and software systems. Therefore, they are not usually equipped to identify anomalies or inaccuracies in data before they are sent. Therefore, discussions with leadership about the importance of adhering to reporting regulations can have an impact on compliance.
It can be tempting to collect any number of data points because it would be interesting to have the information. Data requirements already are onerous for the submitters so it is imperative to only collect data that will be used for specific public health purposes.
UT DHHS is gradually increasing the number and type of analyses generated because it is receiving more and higher-quality data from their partners. Moreover, they have interactive dashboards that make data readily available so partners can conduct their own analyses (e.g., for program planning and grant applications).
It is critical to anticipate and address the impact of enhanced data collection (e.g., data coming in faster, and data being displayed differently) on well-established processes throughout the health department.
In UT DHHS, as data collection efforts improved, epidemiologists and disease investigators received positive test results much more quickly than in the past. It was important to ensure that, as a result, these staff did not contact people with positive test results before their providers reached them.
Unpredictable funding levels can make it difficult to maintain efforts to ensure appropriate data submission by partners. Therefore, data collection systems must be developed and maintained in a fiscally responsible way that is not reliant on a high and unsustainable level of funding.
Programs that are flexible and scalable help ensure that improvements can be readily made, the system can be adapted to meet emerging needs, and that it is less likely to require an overhaul (which can be especially important during lean fiscal times). A strong and stable IT system also means fewer technical changes will be required of data submitters, further facilitating data collection efforts.
UT DHHS uses open-source platforms and works with a consortium of other states with the same technology to make enhancements and improve their system over time.
Keeping communication lines open, making suggested improvements to the degree possible, and otherwise addressing the needs of data submitters are all actions that can lead to more consistency in successful data submissions.
Data collection is part of health informatics, and because health informatics is still a relatively new field, it is difficult to recruit staff who have the skills needed for this work. Many health informatics staff have learned on the job, so it is important to maintain the ability to train staff in this area. In addition, as the field of health informatics continues to grow and evolve quickly, it is important to plan for ongoing training to keep abreast of new developments.
Not only is it time- and resource-intensive to train new staff to assess data submissions and follow up as needed, time is lost in relationships when there is turnover. As a result, staff attrition can have a negative impact on data collection efforts. Staff retention strategies can go a long way in supporting a robust informatics system.
