Related Experiment Video
Updated: Sep 15, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Using Data-driven Clinical Decision Support to Integrate Precision Cancer Symptom Management Into the Electronic
Mary E Cooley1, Leslie A Lenert2, Janet L Abrahm3
1Phyllis F. Cantor Center, Dana-Farber Cancer Institute, Research in Nursing and Patient Care Services, Boston, Massachusetts.
Objectives:
Electronic patient-reported outcome measures (ePROs) are being implemented in clinical care to monitor symptoms in patients with cancer. Although the use of these measures is associated with improved outcomes, challenges remain with integrating ePROs into the workflow due to burdensome training and unclear roles for who will manage uncontrolled symptoms. The use of clinical decision support (CDS) can mitigate these challenges. This article discusses the use of CDS, the integration of CDS into the electronic health record (EHR), lessons learned, and future directions.
Methods:
The Sapphire Cancer Symptom Management CDS system is used to illustrate the development, integration, and testing of CDS in the EHR. A team of experts designed this system based on previous experience and research literature. The discussion synthesizes peer-reviewed literature, expert opinion, systematic reviews, and meta-analysis as sources of data.
Results:
Symptom management algorithms were created for nine cancer symptoms and then programmed into the CDS platform and integrated into the EHR. Integration involved using innovative technologies, which included application programming interfaces and interoperable data standards, to integrate the system into the EHR. Relevant EHR and patient-reported data were used to generate individually tailored symptom management recommendations. Testing of the system was accomplished using test patients that reflected real-world patient experiences. We found that the data needed for the algorithms were complex and some elements were not readily available in the EHR. Having clinicians verify a few critical elements assured accuracy and safety of the recommendations.
Conclusion:
Innovative technologies enabled the integration of CDS into the EHR and the generation of individually tailored cancer symptom management recommendations. Future testing is needed to evaluate whether the use of CDS improves patient outcomes.
Implications For Nursing Practice:
CDS has the potential to improve guideline-concordant symptom management and facilitate supportive care referrals at the point-of-care to improve clinical care.
Related Concept Videos
Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Cancer Survival Analysis
Nursing Clinical Information System
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Health Information Technology and Healthcare Information System
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...
Statistical Software for Data Analysis and Clinical Trials

