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1.
Artigo em Inglês | MEDLINE | ID: mdl-38990207

RESUMO

Maternal morbidity and mortality remain significant challenges in the United States, with substantial burden during the postpartum period. The Centers for Disease Control and Prevention, in partnership with the National Association of Community Health Centers, began an initiative to build capacity in Federally Qualified Health Centers to (1) improve the infrastructure for perinatal care measures and (2) use perinatal care measures to identify and address gaps in postpartum care. Two partner health center-controlled networks implemented strategies to integrate evidence-based recommendations into the clinic workflow and used data-driven health information technology (HIT) systems to improve data standardization for quality improvement of postpartum care services. Ten measures were created to capture recommended care and services. To support measure capture, a data cleaning algorithm was created to prioritize defining pregnancy episodes and delivery dates and address data inconsistencies. Quality improvement activities targeted postpartum care delivery tailored to patients and care teams. Data limitations, including inconsistencies in electronic health record documentation and data extraction practices, underscored the complexity of integrating HIT solutions into postpartum care workflows. Despite challenges, the project demonstrated continuous quality improvement to support data quality for perinatal care measures. Future solutions emphasize the need for standardized data elements, collaborative care team engagement, and iterative HIT implementation strategies to enhance perinatal care quality. Our findings highlight the potential of HIT-driven interventions to improve postpartum care within health centers, with a focus on the importance of addressing data interoperability and documentation challenges to optimize and monitor initiatives to improve postpartum health outcomes.

3.
J Midwifery Womens Health ; 68(2): 179-186, 2023 03.
Artigo em Inglês | MEDLINE | ID: mdl-36565235

RESUMO

INTRODUCTION: Patients receiving care at Federally Qualified Health Centers (FQHCs) have low postpartum care attendance. Perinatal morbidity and mortality disproportionately affect patients with low-income and are potentially preventable. The purpose of this study was to develop a clinical decision support tool to identify FQHC patients less likely to return for postpartum care. To accomplish this purpose, we evaluated established predictors and novel risk factors in our patient population. METHODS: This is a retrospective, secondary data analysis of 50,022 patients who received prenatal care past 24 weeks' gestation in FQHCs between 2012 and 2017. The postpartum visit was defined using Healthcare Effectiveness Data and Information Set measures as early care (birth to 21 days) and later care (21-84 days). Anderson's Behavioral Model for Access to Healthcare guided inclusion of potentially predictive factors. We stratified data by postpartum care attendance, and a final predictive model was selected by model fit statistics and clinical relevance. RESULTS: In our sample, 64% of birthing persons attended postpartum care at FQHCs. Of those who returned for care, 38% returned within 21 days postbirth and 62% returned between 21 and 84 days, with 28% returning for both early and later care. Predictors for postpartum care attendance included maternal age, parity, gestational age at first visit, and number of prenatal care visits. A clinical decision support tool for identifying patients less likely to return for care was created. DISCUSSION: An easy to implement clinical decision support tool can help identify FQHC patients at risk for postpartum nonattendance. Future interventions to improve adequacy of prenatal care can encourage early entry into prenatal care and sufficient prenatal visits. These efforts may improve postpartum care attendance and maternal health.


Assuntos
Cuidado Pós-Natal , Estudos Retrospectivos , Registros Eletrônicos de Saúde , Sistemas de Apoio a Decisões Clínicas , Disparidades em Assistência à Saúde , Continuidade da Assistência ao Paciente , Humanos , Feminino , Gravidez , Adulto
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