Translating Nursing Data into Computational Metrics: An Evaluation Guideline for Inpatient Intravenous and Subcutaneous Insulin Management

2025 Annual Symposium On Demand

Presentation Time: 08:00 AM - 08:12 AM

Abstract Keywords: Nursing Informatics, Knowledge Representation and Information Modeling, Data Standards, Interoperability and Health Information Exchange, Documentation Burden, Artificial Intelligence, Human-computer Interaction, Patient Safety
Primary Track: Applications
Programmatic Theme: Clinical Informatics

A challenge in utilizing electronic health record data for artificial intelligence models is contextualization, including understanding differences between missing data and missed care. Our team aims to develop knowledge graphs and computational models that account for these contexts, such as when data is missing (nurses being unable to document), but acceptable nursing care was delivered. We developed evaluation guidelines for intravenous and subcutaneous insulin management to establish a binary variable derived from EHR data representing minimally acceptable safe and quality nursing care for use in computational modeling. These guidelines were developed by our nurse informatics team based on best practices and validated by three nurse subject matter experts. The resulting evaluation guidelines are agnostic to institutional policies and focus on evaluating minimally acceptable safe and quality levels of care to inform inferences about missing data versus missed nursing care. Future work includes data-driven validations and expanding to other clinical scenarios.

Speaker:
Varsha Varkhedi, Bachelor
Columbia University

Authors:
Varsha Varkhedi, Bachelor - Columbia University; Kenrick Cato, PhD, RN, CPHIMS, FAAN, FACMI - University of Pennsylvania/ Children's Hospital of Philadelphia; David Albers, PhD - University of Colorado, Department of Biomedical Informatics; Victoria Tiase, PhD, RN, NI-BC, FAMIA, FAAN, FNAP, ACHIP - University of Utah; Shalmali Joshi, PhD - Columbia University; Jennifer Thate, PhD, RN, CNE - Siena College; Kathryn Connell, PhD, RN, CCRN - University of Pennsylvania School of Nursing; William Hull, PhD - University of Utah; Amy Finnegan, PhD - IntraHealth International; Sarah Rossetti, RN, PhD - Columbia University Department of Biomedical Informatics;

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Examining the Influence of Nurse Staffing on Delayed Insulin Administration in Acute Care Settings Using EHR Data

2025 Annual Symposium On Demand

Presentation Time: 08:12 AM - 08:24 AM

Abstract Keywords: Nursing Informatics, Patient Safety, Healthcare Quality, Clinical Guidelines
Primary Track: Applications
Programmatic Theme: Clinical Informatics

Delayed insulin administration can lead to poor glycemic outcomes in patients with diabetes. Using EHR and BCMA data, we examined insulin administration patterns across different shifts and types of insulin, and the association between nurse staffing and delayed administration. We analyzed a total of 650 subcutaneous insulin administration events from 96 patients. We found that 42.0% (n=397) of the insulins had delayed administration during 7a-3p shift. Long-acting insulin (Lantus) (64.6%) had more delays than other types of insulin, suggesting that the pharmacokinetics properties of these insulins may influence how nurses prioritized their insulin administrations. We also found that higher patient-to-nurse ratio was associated with delayed insulin administration; however, we did not find nursing skill mix was associated with delays. Lastly, we found patients with delayed insulin administration had poorer glycemic control. Our study demonstrates the need for evidence-based staffing that enables nurses to deliver timely insulin administration during high-demands periods.

Speaker:
Mikie Rachman, RN, MSHI
Washington University in St. Louis

Author:
Po-Yin Yen, PhD, RN - Washington University in St. Louis;

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Re-designing inpatient nursing notes shared with families: an opportunity to enhance family-centered care delivery

2025 Annual Symposium On Demand

Presentation Time: 08:24 AM - 08:36 AM

Abstract Keywords: Pediatrics, Patient Engagement and Preferences, Documentation Burden, Information Extraction, Nursing Informatics, User-centered Design Methods, Quantitative Methods, Qualitative Methods
Primary Track: Applications
Programmatic Theme: Clinical Research Informatics

This modified explanatory sequential mixed methods study sought to inform redesign of nursing notes in the electronic health record. In the context of OpenNotes and patient and family access to nursing notes via the inpatient portal, redesigning nursing notes offers an opportunity to enhance family-centered care delivery and reduce nurses’ documentation burden. We analyzed data on note views via the inpatient portal for 258,841 nursing notes; annotated the contents of 100 nursing notes; and conducted interviews with 18 families and 8 nurses. Our findings support recommendations for more specific care plans, eliminating redundancies, and emphasizing nursing care and expertise otherwise absent from the patient chart. The results of this descriptive study lay the groundwork for pilot testing new nursing note structures.

Speaker:
Halley Ruppel, PhD
Children's Hospital of Philadelphia

Authors:
Halley Ruppel, PhD - Children's Hospital of Philadelphia; Amina Khan, MS - Children's Hospital of Philadelphia; Rose Mintor, DNP - Children's Hospital of Philadelphia; Jessica Nguyen, BS - Children's Hospital of Philadelphia; Meghan McNamara, BSN, MBA, RN - Children's Hospital of Philadelphia; Brooke Luo, MD - Children's Hospital of Philadelphia; Michelle Kelly, MD - University of Wisconsin School of Medicine and Public Health; Kenrick Cato, PhD, RN, CPHIMS, FAAN, FACMI - University of Pennsylvania/ Children's Hospital of Philadelphia; Elizabeth Froh, PhD - Children's Hospital of Philadelphia;

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‘Nurses-in-the-loop’: Narrative Note Extraction, Assessment and Consensus

2025 Annual Symposium On Demand

Presentation Time: 08:36 AM - 08:48 AM

Abstract Keywords: Nursing Informatics, Artificial Intelligence, Natural Language Processing, Human-computer Interaction, Information Extraction
Working Group: Nursing Informatics Working Group
Primary Track: Applications
Programmatic Theme: Clinical Informatics

This study describes a 'nurses-in-the-loop' methodology for selecting narrative nursing notes to train artificial intelligence (AI) systems. Expert nurses evaluated notes from adult falls and neonatal intensive care unit patients using a modified quality instrument across four iterative rounds. The process, involving two academic medical centers, identified 393 salient notes for natural language processing model development. The study highlights the importance of nursing expertise and understanding documentation nuances for effective AI integration with nursing data.

Speaker:
Kimberly Powell, PhD, RN, FAMIA
University of Missouri - Columbia

Authors:
Julie Vignato, PhD, RN, RNC-LRN, CNE - University of Iowa College of Nursing; Anna Krupp, PhD, MSHP, RN - University of Iowa, College of Nursing; Jaewon Bae, PhD, RN - University of Iowa; Jemmie Hoang, BS, RN - University of Iowa; Baris Karacan, BS, MS - University of Illinois, Chicago; Karen Dunn Lopez, PhD, MPH, RN, FAAN - University of Iowa College of Nursing;

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Phenotyping Co-Occurring Pressure Injuries Using Nursing Flowsheet Documentation: Insights into Injury Patterns and Associated Risk Factors

2025 Annual Symposium On Demand

Presentation Time: 08:48 AM - 09:00 AM

Abstract Keywords: Nursing Informatics, Patient Safety, Healthcare Quality, Data Mining
Primary Track: Applications
Programmatic Theme: Clinical Informatics

Pressure injuries (PrIs) negatively affect patient outcomes, but co-occurring PrIs remain understudied due to limited phenotyping methods. This retrospective cohort study developed an electronic health record-based phenotype identifying co-occurring PrIs in 18,195 patients, finding 24.3% had multiple injuries. Severe PrIs, Black or African American race, and spinal cord injury were significant risk factors, highlighting the need for targeted prevention strategies.

Speaker:
Veysel Baris, Nurse
Dokuz Eylul University

Authors:
Veysel Baris, Nurse - Dokuz Eylul University; Wenyu Song, PhD - Brigham and Women's Hospital, Harvard Medical School; Min-Jeoung Kang, PhD, RN - Brigham and Women's Hospital; Luwei Liu, BS - Mass General Hospital; Graham Lowenthal, BA - Brigham and Women's Hospital; Luciana Schleder Goncalves, PhD, RN - Department of Medicine, Brigham and Women’s Hospital; Tanya Martel, DNP - Center for Nursing Excellence, Brigham and Women’s Hospital; Sandy Cho, MPH BSN - Newton-Wellesley Hospital; Diane L. Carroll, PhD,RN - Yvonne L. Munn Center for Nursing Research, Massachusetts General Hospital; Debra Furlong, RN, MS - Center for Nursing Excellence, Brigham and Women’s Hospital; Wadia Gilles-Fowler, RN, BSN - Center for Nursing Excellence, Brigham and Women’s Hospital; Lisa Herlihy, MSN, RN - Salem Hospital, Salem, Massachusetts; Beth Melanson, MSN, RN - Center for Nursing Excellence, Brigham and Women’s Hospital; Jacqueline Massaro, MSN, RN - Center for Nursing Excellence, Brigham and Women’s Hospital; Lori D. Morrow, RN - Salem Hospital, Salem, Massachusetts; Paula Wolski, MSN, RN, NI-BC - Brigham and Womens Faulkner Hospital; PATRICIA C DYKES, PhD, MA, RN - Brigham and Women's Hospital/Harvard Medical School;

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Factors Associated with Patient-level Nursing Costs of a Medical-Surgical Ward

2025 Annual Symposium On Demand

Presentation Time: 09:00 AM - 09:12 AM

Abstract Keywords: Healthcare Quality, Healthcare Economics/Cost of Care, Nursing Informatics
Working Group: Nursing Informatics Working Group
Primary Track: Applications

Using retrospective hospital data, we estimated patient-level nursing costs and quantified the proportion of room charges attributable to nursing (Jan–Jul 2022). The average daily nursing cost per patient was $586.23, representing 25.6% of room charges. Lower patient acuity, complex diagnoses, and staffing factors were associated with higher costs. These findings demonstrate the utility of informatics in revealing nursing’s true cost contribution to patient care.

Speaker:
Seo Yoon Lee, PhD, MPH, RN
Vanderbilt University

Authors:
Chang Gi Park, PhD - University of Illinois Chicago; Andrew Boyd, MD - University of Illinois at Chicago; Lauretta T. Quinn, PhD, RN, CDCES, FAHA, FAAN - University of Illinois Chicago; Anthony Davila, DNP, MBA, RN, NEA-BC, CENP, CEN - University of Illinois Hospital and Health Science System; Eileen G. Collins, PhD, RN, FAAN, ATSF - University of Illinois Chicago;

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