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Special Edition: Title V Technical Assistance MeetingExpand Special Edition: Title V Technical Assistance Meeting
Title V Technical Assistance Meeting

 An Epidemiological Focus on Quality Improvement

Sumrita Bindra
Maternal & Child Health Epidemiologist, Bureau of Family Health, Louisiana Department of Health

Cara Bergo
Mortality Surveillance Epidemiologist, Bureau of Family Health, Louisiana Department of Health

Jane Herwehe
Epidemiology Supervisor, Bureau of Family Health, Louisiana Department of Health

Quality improvement (QI) is a priority at the Bureau of Family Health (BFH): It's an integral component of the CoIIN initiatives, Title V and the general move toward the state's public health accreditation.

Although QI activities have been occurring within the bureau for a number of years, the BFH created a Quality Improvement Coordinating Team (QICT) as the first step of many in formalizing QI. The QICT used many tools to introduce and demystify the principles of QI for the general staff. It illustrated examples of projects employing QI principles and promoted the concept of small wins. Using real-life examples proved to be effective, as it increased awareness of QI at work within the bureau. During QICT meetings, BFH teams can share their QI efforts, discuss strategies and develop ways to foster smoother, well-informed processes.

The bureau's Data to Action Team (epidemiology team) spearheads many QI projects, focusing on improved efficiencies in data collection and management that impact data quality, including:

Streamlining data collection for child death reviews: In accordance with state legislation, Louisiana reviews records for all unexpected (non-medical) deaths for children under age 15. This data informs prevention strategies and data analyses. Data abstraction is time-consuming due to the number of variables included in the Child Death Review case registry. Certain variables are not needed for the specific death being reviewed, such as birth weight for a 7-year-old who died in a motor vehicle crash. The mortality epidemiologist created a data algorithm outlining variables that are needed for certain cases to refine data abstraction. The goal is to increase the quality of the essential data while reducing time wasted on collecting unnecessary data.

Improving Quality of Birth Certificate Data: Birth certificate data are regularly examined for missing and/or underreported data that is outside a predetermined acceptable range. Tthe Louisiana Center for Vital Statistics Quality Manager uses a quality report with each birthing hospital to improve its reporting procedures. Accurate birth records are essential to birth outcomes surveillance.

​Gaining operational efficiencies for Pregnancy Risk Assessment Monitoring System (PRAMS): Data from PRAMS are used to inform program development, policy and resource allocation. A threshold response rate of 65 percent is required for generalizability of results. Louisiana's response rate had not exceeded 60 percent since 2004 – due in part to an inability to reach mothers with inaccurate or missing contact information and materials not clearly communicating the benefit of participation. Contact information was improved by electronically linking data sources (such as WIC and Newborn Screening records) to identify alternate address and phone information; this eliminated time-consuming manual searches, which had interfered with time for phone interviews. Through iterative prototype design, the new materials were released in 2015. The combination of these efforts led to an increase in the unweighted response rates from 57 percent in 2014 to 67 percent in 2015.

With a designated QICT leading the way, QI is becoming a regular part of operations at BFH. While the approach to how QI is conducted across programs is evolving, the momentum and enthusiasm for this process is thriving. It is becoming increasingly important to integrate QI into all the work done at BFH in order to create a culture of quality improvement.