Clinical Perspectives on Actionable Risk Factors for Deterioration in Acute Myeloid Leukemia: Implications for Clinical Decision Support

BACKGROUND: Acute myeloid leukemia (AML) is associated with high complication rates following induction chemotherapy, yet clinicians lack tools that anticipate deterioration and support proactive care. Preliminary predictive modeling using structured electronic health record data and symptoms extracted through natural language processing identified key risk factors for deterioration within 30 days of discharge. How clinicians interpret these risk factors in practice remains unclear. OBJECTIVE: This study aimed to explore how hematology clinicians understand actionable risk factors for deterioration in AML and how these factors should inform the design of clinical decision support. INTERVENTIONS/METHODS: Seven hematology clinicians-including hematologist-oncologists, a nurse practitioner, and physician assistants-at a Midwestern academic medical center participated in individual or group semistructured interviews. Interview questions addressed perceived risk factors, actionability, and needs for clinical decision support. Data were analyzed using conventional content analysis. RESULTS: Three themes emerged: (1) generic tools do not adequately support the complexity of AML care; (2) actionability is context‑dependent, with both nonmodifiable and modifiable factors influencing discharge decision‑making; and (3) clinical decision support must integrate predictive risk scoring with user‑centered design features such as intuitive displays, timely alerts, and transparency about contributing factors. CONCLUSIONS: Clinicians expressed strong support for a clinical decision support tool that anticipates deterioration, provides individualized and interpretable risk alerts, and aligns with existing workflows to reduce preventable complications and readmissions. IMPLICATIONS FOR ONCOLOGY NURSING PRACTICE: Clinical decision support tools that integrate dynamic clinical data with intuitive, workflow‑aligned interfaces may enhance risk communication, strengthen discharge decision‑making, and support proactive monitoring in AML care.

Authors

Institutions

Publication Details

Journal
Cancer Nursing
Published
2026-07-22
DOI
https://doi.org/10.1097/ncc.0000000000001606
Primary Topic
Acute Myeloid Leukemia Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Clinical Perspectives on Actionable Risk Factors for Deterioration in Acute Myeloid Leukemia: Implications for Clinical Decision Support

Nayung Youn, Sena Chae, Karen Dunn Lopez, Alaa Harb et al.
Cancer Nursing
Acute Myeloid Leukemia Research
article

Clinical Perspectives on Actionable Risk Factors for Deterioration in Acute Myeloid Leukemia: Implications for Clinical Decision Support

Nayung Youn, Sena Chae, Karen Dunn Lopez, Alaa Harb, Priscilla A. M. Annan
article en

Abstract

BACKGROUND: Acute myeloid leukemia (AML) is associated with high complication rates following induction chemotherapy, yet clinicians lack tools that anticipate deterioration and support proactive care. Preliminary predictive modeling using structured electronic health record data and symptoms extracted through natural language processing identified key risk factors for deterioration within 30 days of discharge. How clinicians interpret these risk factors in practice remains unclear. OBJECTIVE: This study aimed to explore how hematology clinicians understand actionable risk factors for deterioration in AML and how these factors should inform the design of clinical decision support. INTERVENTIONS/METHODS: Seven hematology clinicians-including hematologist-oncologists, a nurse practitioner, and physician assistants-at a Midwestern academic medical center participated in individual or group semistructured interviews. Interview questions addressed perceived risk factors, actionability, and needs for clinical decision support. Data were analyzed using conventional content analysis. RESULTS: Three themes emerged: (1) generic tools do not adequately support the complexity of AML care; (2) actionability is context‑dependent, with both nonmodifiable and modifiable factors influencing discharge decision‑making; and (3) clinical decision support must integrate predictive risk scoring with user‑centered design features such as intuitive displays, timely alerts, and transparency about contributing factors. CONCLUSIONS: Clinicians expressed strong support for a clinical decision support tool that anticipates deterioration, provides individualized and interpretable risk alerts, and aligns with existing workflows to reduce preventable complications and readmissions. IMPLICATIONS FOR ONCOLOGY NURSING PRACTICE: Clinical decision support tools that integrate dynamic clinical data with intuitive, workflow‑aligned interfaces may enhance risk communication, strengthen discharge decision‑making, and support proactive monitoring in AML care.

Cancer Nursing
University of Iowa (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 9%
Acute Myeloid Leukemia Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.