Childhood Obesity Preventer

The Office of the National Coordinator for Health Information Technology’s (ONC) 21st Century Cures Act Information Blocking Rule (Info Blocking Rule) prohibits covered actors – including health care providers, health IT developers of certified health IT, and health information exchanges/health information networks– from engaging in practices likely to interfere with, prevent, or materially discourage access, exchange, or use of electronic health information (EHI). The Info Blocking Rule includes eight exceptions that provide actors with certainty that, when their practice interferes with the access, exchange, or use of EHI and meets the conditions of one or more exception, such practice will not be considered information blocking. An actor’s practice that does not meet all the conditions of an exception will be evaluated on a case-by-case basis to determine whether information blocking has occurred.

Panel management is an essential function of a health center. When done well, it smooths the scheduling and operations of the health center; when done poorly it creates challenges with productivity, patient continuity, Quality Improvement reporting, and more. This resource offers guidance on improving panel management activities, including real-life examples from two health centers of the challenges and successes in managing panels.

The HITEQ Center interviewed ten health centers and health center partners to identify solutions and promising practices for addressing childhood obesity across the health center program. The focus included how health centers are meeting the Uniform Data System (UDS) measure and how they are taking further steps to identify and intervene with those at risk of obesity leveraging health information technology, electronic health records, and the data they have. Seven key areas are identified in the resulting issue brief.

As more health centers seek to break down siloes that can fragment patient care, collaboration with or integration of behavioral health care has been strengthened, although data integration remains difficult and privacy remains paramount. This brief discusses some of the approaches, successes, and challenges in integrating behavioral health data within primary care services.

This brief explores the concept of rising risk in the health field. Given that it is well understood that the top 5% of patients account for more than 50% of utilization, it follows that identifying risk in the population early and intervening effectively has the potential to save resources and improve health outcomes. The growing emphasis on efficiency and value, a new set of data collection and analysis tools, and the recognition that uncoordinated, after-the-fact response is not optimal all support a focus on rising-risk populations. 

HealthNet’s successful use of Health IT to move metrics is highlighted in case studies focused on the value of leveraging IT to standardize care and improve patient outcomes. With the assistance of electronic health records and a variety of IT interventions, HealthNet has reduced low birth weights, improved care outcomes for pediatric patients, and significantly increased patient satisfaction.

This health center-tested Dental Dashboard, created by NNOHA and partners, is an interactive resource that allows users to monitor a set of dental measures through an online data collection tool and a chart presentation tool, allowing monitoring of performance and opportunities for QI. A case study is also included.

This mini-case study describes Petaluma Health Center, a Federally Qualified Health Center’s approach to incorporating social determinants data into their daily workflows.  They then used Tableau visualization to represent the data to enable them to target interventions in the community.  Petaluma’s lessons learned and next steps are discussed, and a link to the full, detailed case study is provided.

Healthcare organizations are flooding with data. Health centers have a wealth of data about their patients and their community. It is essential that these organizations  build a strong foundation of people, processes and technology to leverage that data to improve care and better serve the underserved.

Improving performance can be boiled down to three approaches: improving the completeness and accuracy of data, decreasing missed opportunities, and improving the quality of services. Determining which of these is appropriate for your circumstance requires doing some data validation to assess where the issue lies. If you have not taken that step yet, please visit that section of the HITEQ site.