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 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.

The trend of opioid prescriptions among cancer patients in a tertiary hospital: A multimethod quantitative study.

Introduction: Pain is a major symptom in cancer patients. World Health Organization recommends opioids as the main analgesic agent. Few studies have examined the amount of opioid uses in cancer patients in Southeast Asia, however, none of them have examined the factors associated with the amount of opioid uses which were lower than required. Objectives: To assess the trends and factors associated with opioid prescriptions for cancer patients in Songklanagarind Hospital, the largest referral center in Southern Thailand. Design: Multi-method quantitative study. Methods: We reviewed the electronic medical records of 20,192, outpatients aged ≥18 years diagnosed with cancer between 2016 and 2020 who received opiod prescriptions. Oral morphine equivalents (OME) were calculated using the standard conversion factors and the OME trend during the study period was assessed by a generalized additive model. Factors affecting the morphine equivalent daily dose (MEDD) were assessed using multiple linear regression with a generalized estimating equation. Results: The mean overall MEDD for all study patients was 27.8 ± 21.9 mg per day per patient. The bone and articular cartilage cancer patients had the highest MEDD. For every 5-year increase in the duration of cancer, the MEDD increased by 0.02 (95% confidence interval [CI]: 0.01 - 0.04). Patients with stage 4 cancer received a higher average MEDD of 4.04 (95% CI: 0.30-7.62) as compared to those with stage 1 cancer. Patients with bone metastasis received a average higher MEDD of 4.03 (95% CI: 0.82-7.19) compared to those without. Age was inversely associated with the MEDD. Patients aged 42-58, 59-75 and >76years old received MEDDs of 4.73 (95% CI: 2.31-7.15), 6.12 (95% CI: 3.66-8.59) and 8.59 (95% CI: 6.09-11.09) compared with those aged 18-42 years old. Brain metastasis was inversely associated with MEDD of 4.49 (95% CI: 0.61-8.37) compared to those without. Conclusion: Opioid use in cancer patients in this study is lower than the average global usage. Promoting opioid prescriptions for pain management through medical education can help doctors overcome opiophobia.