*NEW RELEASE* AIM for Safer Birth Podcast episode with Congresswoman Lauren Underwood and HRSA Administrator Carole Johnson. CLICK HERE to listen now!

AIM Data Overview

AIM Data Team

AIM’s Data Team provides individualized technical assistance and capacity building to state and jurisdiction teams so data-driven quality improvement initiatives can be implemented at scale in a diversity of settings and contexts. Additionally, AIM develops and maintains freely available data resources, such as project measurement strategies for AIM Patient Safety Bundles and a Data Center for quality improvement data collection, visualization, and reporting. Through expert guidance and resource development and sharing, AIM helps state and jurisdiction teams meet their personal data and quality improvement goals.

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AIM Data Types

AIM develops project measurement strategies for its patient safety bundles to support adoption and evaluation of rapid cycle quality improvement activities. AIM works with clinical and public health subject matter experts to identify metrics for quality improvement, balancing clinical and public health priorities with the feasibility of data collection and administrative burden. 

AIM’s project measurement strategies include three common quality improvement measure types: Process, Structure, and Outcome Measures.

Process Measures

Process measures are used to monitor the adoption and implementation of evidence-based practices. By using data to track processes of care and examining these data disaggregated by race, ethnicity, and other social and structural drivers of health, facility teams can identify areas for improvement and intervention.

Structure Measures

Structure measures are used to assess if standardized, evidence-based systems, protocols, and materials have been established to improve patient care. Through adoption and regular review of structures, facility teams improve their readiness to respond to an obstetric event and provide high quality care to every patient, every time.

Outcome Measures

Outcome measures can be used to examine changes that occur in the health of an individual, group of people, or population that can be attributed to the adoption of clinical best practices. Outcome measures include severe maternal morbidity and the rate of nulliparous, term, singleton, vertex Cesarean births, and should be disaggregated by race, ethnicity, and other social and structural drivers of health to examine inequities. Outcome measures are typically calculated by state and jurisdiction teams and shared with participating facilities.