ArticleJMIR medical informatics2016
Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention.
Article in JMIR medical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Clinical Decision Support for Symptom Management in Lung Cancer Patients: A Group RCT.Journal of pain and symptom management · 2022Trial
- Changing functional status within 6 months posttreatment is prognostic of overall survival in patients with head and neck cancer: NRG Oncology Study.Head & neck · 2019Trial
- Nurse-Delivered Symptom Assessment for Individuals With Advanced Lung Cancer.Oncology nursing forum · 2018Trial
- Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.Interactive journal of medical research · 2024Review
- Exploring the symptoms and psychological experiences among lung cancer convalescence patients after radical lobectomy: A qualitative study.Cancer medicine · 2024Article
- A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all.BMC medical informatics and decision making · 2024Article
- Patient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and micro-levels.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Self-reported activities of daily living, health and quality of life among older adults in South Africa and Uganda: a cross sectional study.BMC geriatrics · 2020Article
- Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data.Journal of medical Internet research · 2020Article
- Medical knowledge infused convolutional neural networks for cohort selection in clinical trials.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Clinical trial cohort selection based on multi-level rule-based natural language processing system.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Algorithm-based decision support for symptom self-management among adults with Cancer: results of usability testing.BMC medical informatics and decision making · 2018Article
- Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.JMIR medical informatics · 2018Article
- Identifying Future Drinkers: Behavioral Analysis of Monkeys Initiating Drinking to Intoxication is Predictive of Future Drinking Classification.Alcoholism, clinical and experimental research · 2017Article
- Design and Evaluation of the Electronic Patient-Generated Index.Nursing researchArticle
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
backgroundManagement of uncontrolled symptoms is an important component of quality cancer care. Clinical guidelines are available for optimal symptom management, but are not often integrated into the front lines of care. The use of clinical decision support (CDS) at the point-of-care is an innovative way to incorporate guideline-based symptom management into routine cancer care.
objectiveThe objective of this study was to develop and evaluate a rule-based CDS system to enable management of multiple symptoms in lung cancer patients at the point-of-care.
methodsThis study was conducted in three phases involving a formative evaluation, a system evaluation, and a contextual evaluation of clinical use. In Phase 1, we conducted iterative usability testing of user interface prototypes with patients and health care providers (HCPs) in two thoracic oncology clinics. In Phase 2, we programmed complex algorithms derived from clinical practice guidelines into a rules engine that used Web services to communicate with the end-user application. Unit testing of algorithms was conducted using a stack-traversal tree-spanning methodology to identify all possible permutations of pathways through each algorithm, to validate accuracy. In Phase 3, we evaluated clinical use of the system among patients and HCPs in the two clinics via observations, structured interviews, and questionnaires.
resultsIn Phase 1, 13 patients and 5 HCPs engaged in two rounds of formative testing, and suggested improvements leading to revisions until overall usability scores met a priori benchmarks. In Phase 2, symptom management algorithms contained between 29 and 1425 decision nodes, resulting in 19 to 3194 unique pathways per algorithm. Unit testing required 240 person-hours, and integration testing required 40 person-hours. In Phase 3, both patients and HCPs found the system usable and acceptable, and offered suggestions for improvements.
conclusionsA rule-based CDS system for complex symptom management was systematically developed and tested. The complexity of the algorithms required extensive development and innovative testing. The Web service-based approach allowed remote access to CDS knowledge, and could enable scaling and sharing of this knowledge to accelerate availability, and reduce duplication of effort. Patients and HCPs found the system to be usable and useful.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.