Identifying cancer patients who received palliative care using the SPICT-LIS in medical records: a rule-based algorithm and text-mining technique

Background Due to limited numbers of palliative care specialists and/or resources, accessing palliative care remains limited in many low and middle-income countries. Data science methods, such as rule-based algorithms and text mining, have potential to improve palliative care by facilitating analysi...

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Bibliographic Details
Published in:BMC palliative care Vol. 23; no. 1; pp. 83 - 10
Main Authors: Limsomwong, Pawita, Ingviya, Thammasin, Fumaneeshoat, Orapan
Format: Journal Article
Language:English
Published: London BioMed Central 01.04.2024
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Algorithms
Analysis
Cancer
cancer patients
Care and treatment
Data dictionaries
Data Mining
Developing countries
Digital health and new technologies in palliative care
Electronic Health Records
Evaluation
Family physicians
Hospitals
Humans
LDCs
Medical personnel
Medical records
Medicine
Medicine & Public Health
Neoplasms - therapy
Pain Medicine
Palliative Care
Palliative Medicine
Palliative treatment
Patient outcomes
Patients
Quality of Life Research
Reproducibility of Results
Rule-based algorithm
Sentiment analysis
SPICT-LIS criteria
Text-mining techniques
Thailand
Palliative care
Rule-based algorithm
SPICT-LIS criteria
Text-mining techniques
cancer patients
ISSN:1472-684X, 1472-684X
Online Access:Get full text
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Summary:Background Due to limited numbers of palliative care specialists and/or resources, accessing palliative care remains limited in many low and middle-income countries. Data science methods, such as rule-based algorithms and text mining, have potential to improve palliative care by facilitating analysis of electronic healthcare records. This study aimed to develop and evaluate a rule-based algorithm for identifying cancer patients who may benefit from palliative care based on the Thai version of the Supportive and Palliative Care Indicators for a Low-Income Setting (SPICT-LIS) criteria. Methods The medical records of 14,363 cancer patients aged 18 years and older, diagnosed between 2016 and 2020 at Songklanagarind Hospital, were analyzed. Two rule-based algorithms, strict and relaxed, were designed to identify key SPICT-LIS indicators in the electronic medical records using tokenization and sentiment analysis. The inter-rater reliability between these two algorithms and palliative care physicians was assessed using percentage agreement and Cohen’s kappa coefficient. Additionally, factors associated with patients might be given palliative care as they will benefit from it were examined. Results The strict rule-based algorithm demonstrated a high degree of accuracy, with 95% agreement and Cohen’s kappa coefficient of 0.83. In contrast, the relaxed rule-based algorithm demonstrated a lower agreement (71% agreement and Cohen’s kappa of 0.16). Advanced-stage cancer with symptoms such as pain, dyspnea, edema, delirium, xerostomia, and anorexia were identified as significant predictors of potentially benefiting from palliative care. Conclusion The integration of rule-based algorithms with electronic medical records offers a promising method for enhancing the timely and accurate identification of patients with cancer might benefit from palliative care.
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ISSN:1472-684X
1472-684X
DOI:10.1186/s12904-024-01419-1