Why Applying Quality Improvement Techniques to Non-clinical Data Makes Sense

Posted September 25, 2015 by Sabrina Selk

The growing trend of increasing capacity and timeliness of collecting surveillance data (such as birth and death records used by epidemiologists) is opening up opportunities for these rich data sources to be used for quality improvement (QI) efforts. In the Collaborative Improvement and Innovation Network to Reduce Infant Mortality (IM CoIIN), states are working towards using preliminary vital records data from birth and death records to better understand infant mortality, as well as the risk factors that contribute to a U.S. infant mortality rate that is almost three times higher than other industrialized countries.

Sabrina SelkUsing surveillance data in QI activities—which calls for small, rapid tests of change—brings a new lens to how this surveillance data can be used. It establishes a demand for increased, real-time monitoring and learning, which can allow for improvements in both policies and programs targeted at improving public health. Encouraging the use of real time data can help state programmatic and policy leaders see the impact of innovative programs, and when necessary make course corrections to make the best use of evidence-based practices. Using a QI lens in public health efforts provides tremendous opportunity for new learning from ongoing efforts to reduce infant mortality and other public health challenges. It provides a new way of looking at data that is already being routinely collected.

To use these tools, it is first important to appreciate some of the differences between how data is analyzed in these two disciplines. Here are four key differences in how QI practitioners and epidemiologist look at data.

  1. More data over more time periods. QI data is generally examined over time in a run chart. The more points we have, the greater the ability to detect trends, shifts or astronomical data points in our system. While monthly data is often difficult to achieve, we are seeing greater and greater ability to develop quarterly reporting on datasets including vital records, which allows for an increased ability to view data and see variation across time. 
  2. Increasing timeliness of data to support learning. In order to respond to data and learn from interventions and programmatic efforts, programs and policy developers need to be able to see data that is as close to real time as possible. This means increasing data timeliness and in some cases the use of provisional data to begin to learn from the data that is available, rather than waiting for final data, which may take a year or longer to become available.
  3. Determining an acceptable level of bias. Epidemiological studies are focused on removing as much bias as possible. In QI, the focus is not on removing bias, but ensuring that it remains consistent across time. QI statistics and techniques allows you to account for potential bias and accept its presence without it impacting on the learning from your data. However, completeness of data may still be an issue to consider when determining an acceptable level of bias.
  4. Accounting for variability is key to both methodologies. In QI, the large number of data points allows us to account for variability in our charts by creating control lines to see if changes in our data are due to a common cause or a special cause. In both QI and epidemiology, the use of statistical methods allows us to help account for variation in our data, and make appropriate interpretations based on our understanding of what our data is showing. Although the methods may differ, the end result is the same as we are able to detect points that fall outside the ‘expected’ results.
QI and epidemiology often look at very similar problems and more and more often are able to make use of the same data. However, these two branches of study utilize different tools to help us understand what is contributing to our outcomes. But it is important to understand that both methodologies are attempting to help us understand cause and effect relationships, and learn from our programmatic efforts how to better implement and understand the impact of interventions to improve health. When we combine these skill sets, we add an important layer of understanding that can only improve our ability to deliver effective and evidence-based programs and policies to improve the health of children.

Sabrina Selk is a senior analyst at NICHQ


Share:

Add your comment

 
 

 

Archive

Tagcloud

quality improvement tips QI PDSA cycle baby box safe sleep nichq infant mortality family engagement eccs coiin immunizations health equity health disparities accreditation im coiin astho onboarding collaboration engagement partnerships larc nashp breastfeeding new york wic new york state hospitals mom mother partners epilepsy data AAP early childhood pdsas texas community support learning session children's health new technology engineering transgender collaborative learning planning PDSA planning paralysis underplanning analysis paralysis vision eye health smoking smoke-free housing second-hand smoke toolkit e-module infant health dental care oral health underserved populations health inequity public health Maternal and Child Health Journal leadership engagement Sickle cell disease indiana SCD medicaid perinatal regionalization sudden infant death syndrome national birth defects prevention month birth defects pregnancy planning one key question prepregnancy health preconception health public breastfeeding support families patients experts insights CHOPT childhood obesity innovation food desert telemedicine TBLC breastfeeding supporting preterm birth prematurity racial disparities audiology ehdi follow-up illinois talana hughes vulnerable populations sports asthma soccer basketball obesity football SIDS Pokemon Go gamification smartphones interconception care birth spacing issue brief contraceptive use postpartum care CoIN HRSA early childhood trauma NHSA community health consumer advocacy womens health interconception health teenage health PATCH wisconsin missouri risk appropriate care community health workers SCD< infographic infant mortality awareness month inspirations childrens health national breastfeeding month maternal health patient engagement hearing loss hearing treatment pediatric vision vision screening eyesight pre-term birth early-term birth SCD clinic los angeles LOCATe CDC levels of care neonatal care maternal care smoking cessation project safe sleep practices neonatal abstinence syndrome NAS opioids maternal and child health MCH Family voices quality care mental health hydroxyurea SCDTDP men dads testing change data sharing state government city government apps sleep AJPM preconception care senior leadership breastfeeding support video series access BQIH exclusive breastfeeding long-acting reversible contraception unplanned pregnancies social determinants of health health innovations Best Babies Zone CoIIN baby boxes Rhode Island progesterone rooming-in Baby-Friendly parent partner patient and family engagement healthy weight healthy lifestyles primary care telementoring ECHO video conferencing socioemotional health childhood development pediatric Tennessee interview National Coordinating and Evaluation Center medical-legal partnerships mobile app disparities perinatal care overweight obese healthy weight clinic wellness pilot sites data collection education resources paternal engagement risk-appropriate care preterm infants high-risk babies Ten Steps public relations social movement reversible contraceptives medical home pediatric medical home patient transformation facilitator PTF skin-to-skin rooming in prenatal smoking information visualization charts SUID postpartum new mother webinar AMCHP QI Tips ongoing improvement fourth trimester partnership quality and safety coaching leadership support year end holiday message reflections gratitute Medicaid data doctor relationship PQC perinatal quality collaboratives vision care vision health evidence-based guidelines ASH health and wellness healthy living healthy eating home visitors home visiting programs March of Dimes APHA results evaluation supplementation formula reduction video infant loss social media advocacy leadership Berns Best Fed Beginnings Ten Steps to Successful Breastfeeding sustainability stress prenatal care data capacity epidemiologists surveillance data PFAC community partners preconception and interconception care motivational interviewing Native Americans ADHD NICHQ Vanderbilt Assessment Scale ADHD Toolkit system design care coordination skin to skin newborn screening reduce smoking aim statement safe birth Texas Ten Step skin-to-skin contact 10 Steps staff training small tests acute care mother-baby couplet collective impact population health preconception Newborn Screening Program substance abuse breast milk formula milk bank crisis first responders NYC improvement healthcare health system sickle cell diease treatment protocol family health partner maternity care Collaborative Improvement and Innovation Network Health Outcomes Cross-Sector Collaboration Knowledge Sharing Child Health