Comparison of two validated instruments to measure financial hardship in cancer survivors: comprehensive score for financial toxicity (COST) versus personal financial wellness (PFW) scale.

PURPOSE: Financial distress and financial toxicity are recognized challenges in cancer survivorship. Financial toxicity includes both objective measures of hardship and subjective distress. We hypothesized that subjective financial distress is correlated to overall holistic financial toxicity. We compared two widely accepted instruments to measure financial distress and financial toxicity. METHODS: Patients in the follow-up phase of care at a single institution were surveyed regarding demographic and economic status. Financial toxicity was measured using the comprehensive score for financial toxicity-functional assessment of chronic illness (COST-FACIT) and financial distress using the personal financial wellness (PFW) scale. Surveys were analyzed for correlation and internal consistency. Patient score distributions were compared. Associations between survey scores and patient factors were assessed using multivariable linear regression models. RESULTS: A total of 116 patients were included. Scores from the COST-FACIT showed a strong correlation with PFW scores (r = 0.90, p < 0.0001). Scale reliability was high for both the COST-FACIT (α = 0.92) and PFW (α = 0.97) surveys. Score distributions exhibited left skew for both surveys, with 9.5% of patient scores falling in the worst quartile of possible scores on each respective survey. The strongest predictors of financial distress and financial toxicity included young age, lower monetary savings, lower household income, and less perceived social support during cancer treatment. CONCLUSIONS: The COST-FACIT measure of financial toxicity correlated strongly with PFW measure of financial distress. Although these instruments were designed to assess different concepts (financial distress vs financial toxicity), they gave strikingly similar results. Either instrument may be used as a meaningful patient-reported outcome for study of financial distress in cancer survivors. However, the COST-FACIT construct of financial toxicity does not appear to add additional information beyond financial distress.

Informing healthcare operations with integrated pathology, clinical, and epidemiology data: Lessons from a single institution in Kenya during COVID-19 waves.

Pathology, clinical care teams, and public health experts often operate in silos. We hypothesized that large data sets from laboratories when integrated with other healthcare data can provide evidence that can be used to optimize planning for healthcare needs, often driven by health-seeking or delivery behavior. From the hospital information system, we extracted raw data from tests performed from 2019 to 2021, prescription drug usage, and admission patterns from pharmacy and nursing departments during the COVID-19 pandemic in Kenya (March 2020 to December 2021). Proportions and rates were calculated. Regression models were created, and a t-test for differences between means was applied for monthly or yearly clustered data compared to pre-COVID-19 data. Tests for malaria parasite, Mycobacterium tuberculosis, rifampicin resistance, blood group, blood count, and histology showed a statistically significant decrease in 2020, followed by a partial recovery in 2021. This pattern was attributed to restrictions implemented to control the spread of COVID-19. On the contrary, D-dimer, fibrinogen, CRP, and HbA1c showed a statistically significant increase (p-value <0.001). This pattern was attributed to increased utilization related to the clinical management of COVID-19. Prescription drug utilization revealed a non-linear relationship to the COVID-19 positivity rate. The results from this study reveal the expected scenario in the event of similar outbreaks. They also reveal the need for increased efforts at diabetes and cancer screening, follow-up of HIV, and tuberculosis patients. To realize a broader healthcare impact, pathology departments in Africa should invest in integrated data analytics, for non-communicable diseases as well.