A risk assessment algorithm is used for standardized identification of individuals with suspected disease, or suspected high risk for disease. A risk assessment test should distinguish individuals with a high probability for disease by analyzing several variables indicated by the algorithm. Among individuals who have a positive risk assessment for CVD, additional diagnostic testing and clinical testing are necessary to establish a diagnosis. A multitude of Risk Assessment algorithms are used throughout a variety of specialties in medicine and are crucial in identifying high-risk individuals, so they can receive an appropriate diagnosis and/or treatment early. Early treatment and diagnosis of disease are vital to help reduce negative effects of disease in individuals.

For cardiovascular risk assessment in pregnant and postpartum patients, a reliable clinical Risk Assessment approach that monitors the hospital and clinician performance is lacking. Timely identification of patients at risk of CVD and follow-up may improve maternal health outcomes, i.e., maternal morbidity and mortality and lifetime onset of CVD.

The California Maternal Quality Care Collaborative (CMQCC) is a multi-stakeholder organization with the goal to end preventable morbidity, mortality, and racial disparities in California maternal care. Dr. Afshan Hameed led the Cardiovascular Disease in Pregnancy and Postpartum Task Force which developed the CMQCC Cardiovascular disease in pregnancy toolkit to encourage obstetric and other healthcare providers to retain a high index of suspicion for CVD.  It includes resources for providers, infographics for patients on signs and symptoms of CVD, future CVD risk and long-term health issues, contraception options and planning a pregnancy with known CVD. The toolkit also includes a discussion on racial and ethnic disparities in CVD prevention and diagnosis. 

A clinical decision tool was created as part of the CMQCC Cardiovascular Disease in Pregnancy Toolkit to identify pregnant and postpartum patients with CVD or risk of developing CVD. The Risk Assessment algorithm also includes follow-up recommendations for patients who have a positive risk assessment for CVD risk. This Risk Assessment algorithm is intended for all pregnant and postpartum patients as a guide to diagnosing CVD. With improved detection of disease, appropriate treatment may improve the outcomes of patients and their pregnancies.

This initiative aims to help develop and validate new measures for diagnostic performance. With funding from the Gordon and Betty Moore Foundation,  Diagnostic Excellence Initiative UCI’s cardio-obstetric program developed a quality measure and implemented them at four health systems: University of California, Irvine, Medical Center Health Systems, University of California, San Diego, Medical Center health systems, the University of Tennessee, and St. Thomas health systems, and University of Missouri-Kansas City, St. Luke’s health system.

Currently, there is a lack of HEDIS (Healthcare Effectiveness Data and Information Set) indicators for pregnant/postpartum patients that monitor or mandate cardiovascular (CVD) detection and/or CVD risk assessment using a validated tool. These measures target patients of reproductive age who access the health care system for maternity services to identify patients with CVD or increased risk of developing CVD. The measures offer an innovative approach for universal CVD Risk Assessment during the pregnancy and postpartum period.

In partnership with New York City’s Albert Einstein College of Medicine and Montefiore Medical Center, UCI is conducting a study to validate the CVD risk-assessment tool in pregnant and postpartum patients who receive services at UCI. The study will assess the predictive value of the total score and each CVD screening algorithm’s items on identifying previously unknown CVD.

For more information about the Toolkit and Algorithm, please see the resources below:

CMQCC Cardiovascular Disease in Pregnancy Toolkit

CMQCC Cardiovascular Disease Risk Assessment Algorithm