Quality Improvement in the Digital Age: The Promise of Using Informatics to Improve Obstetric Anesthesia Care

被引:1
作者
Ende, Holly B. [1 ]
Bateman, Brian T. [2 ]
机构
[1] Vanderbilt Univ, Med Ctr, Dept Anesthesiol, Nashville, TN USA
[2] Stanford Univ, Sch Med, Dept Anesthesiol Perioperat & Pain Med, Palo Alto, CA USA
关键词
IMPLEMENTATION; FEEDBACK;
D O I
10.1213/ANE.0000000000006841
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Informatics describes the study and use of processes for obtaining and utilizing data. In the clinical context, these data are then used to inform and educate providers to improve patient care. In the current digital age, informatic solutions can help clinicians to understand past or current quality issues (afferent tools), to benchmark personal performance against national averages (feedback tools), and to disseminate information to encourage best practice and quality care (efferent tools). There are countless examples of how these tools can be adapted for use in obstetric anesthesia, with evidence to support their implementation. This article thus aimed to summarize the many ways in which informatics can help clinicians to harness the power of data to improve quality and safety in obstetric anesthesia.
引用
收藏
页码:1215 / 1222
页数:8
相关论文
共 35 条
[1]  
Anesthesia Quality Institute, Anesthesia Incident Reporting System
[2]  
[Anonymous], AIM Patient Safety Bundles. Resources/Severe Maternal Morbidity/2022 AIM SMM Codes List
[3]  
[Anonymous], Quality Payment Program experience
[4]   Fetal Heart Rate Analysis for Automatic Detection of Perinatal Hypoxia Using Normalized Compression Distance and Machine Learning [J].
Barquero-Perez, Oscar ;
Santiago-Mozos, Ricardo ;
Lillo-Castellano, Jose M. ;
Garcia-Viruete, Beatriz ;
Goya-Esteban, Rebeca ;
Caamano, Antonio J. ;
Rojo-Alvarez, Jose L. ;
Martin-Caballero, Carlos .
FRONTIERS IN PHYSIOLOGY, 2017, 8
[5]   Centers of Excellence for Anesthesia Care of Obstetric Patients [J].
Carvalho, Brendan ;
Mhyre, Jill M. .
ANESTHESIA AND ANALGESIA, 2019, 128 (05) :844-846
[6]   Comparison of Natural Language Processing of Clinical Notes With a Validated Risk-Stratification Tool to Predict Severe Maternal Morbidity [J].
Clapp, Mark A. ;
Kim, Ellen ;
James, Kaitlyn E. ;
Perlis, Roy H. ;
Kaimal, Anjali J. ;
McCoy, Thomas H. ;
Easter, Sarah Rae .
JAMA NETWORK OPEN, 2022, 5 (10) :E2234924
[7]   Performance of racial and ethnic minority-serving hospitals on delivery-related indicators [J].
Creanga, Andreea A. ;
Bateman, Brian T. ;
Mhyre, Jill M. ;
Kuklina, Elena ;
Shilkrut, Alexander ;
Callaghan, William M. .
AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2014, 211 (06) :647.e1-647.e16
[8]  
Ehrenfeld JM, 2017, ANESTHESIOLOGY, V126, P431, DOI [10.1097/ALN.0000000000001516, 10.1097/aln.0000000000001516]
[9]   Implementation of an Epidural Rounding Reminder in the Electronic Medical Record Improves Performance of Standardized Patient Assessments during Labor [J].
Ende, Holly B. ;
French, Benjamin ;
Shi, Yaping ;
Damron, James ;
Bauchat, Jeanette R. ;
Dumas, Susan ;
Wanderer, Jonathan P. .
APPLIED CLINICAL INFORMATICS, 2023, 14 (02) :238-244
[10]   Health Information Technology in Healthcare Quality and Patient Safety: Literature Review [J].
Feldman, Sue S. ;
Buchalter, Scott ;
Hayes, Leslie W. .
JMIR MEDICAL INFORMATICS, 2018, 6 (02) :190-202