Understanding breast cancer patient pathways and their impact on survival in Mexico.

BACKGROUND: Understanding patient pathways from discovery of breast symptoms to treatment start can aid in identifying ways to improve access to timely cancer care. This study aimed to describe the patient pathways experienced by uninsured women from detection to treatment initiation for breast cancer in Mexico City and estimate the potential impact of earlier treatment on patient survival. METHODS: We used process mining, a data analytics technique, to create maps of the patient pathways. We then compared the waiting times and pathways between patients who initially consulted a private service versus those who sought care at a public health service. Finally, we conducted scenario modelling to estimate the impact of early diagnosis and treatment on patient survival. RESULTS: Our study revealed a common pathway followed by breast cancer patients treated at the two largest public cancer centres in Mexico City. However, patients who initially sought care in private clinics experienced shorter mean wait times for their first medical consultation (66 vs 88 days), and diagnostic confirmation of cancer (57 vs 71 days) compared to those who initially utilized public clinics. Our scenario modelling indicated that improving early diagnosis to achieve at least 60% of patients starting treatment at early stages could increase mean patient survival by up to two years. CONCLUSION: Our study highlights the potential of process mining to inform healthcare policy for improvement of breast cancer care in Mexico. Also, our findings indicate that reducing diagnostic and treatment intervals for breast cancer patients could result in substantially better patient outcomes. POLICY SUMMARY: This study revealed significant differences in time intervals along the pathways of women with breast cancer according to the type of health service first consulted by the patients: whether public primary care clinics or private doctors. Policies directed to reduce these inequities in access to timely cancer care are desperately needed to reduce socioeconomic disparities in breast cancer survival.

How to develop a comprehensive Mangrove Quality Index?

Currently, the available indices to measure mangrove health are not comprehensive. An integrative ecological-socio economic index could give a better picture of the mangrove ecosystem health. This method explored all key biological, hydrological, ecological and socio-economic variables to form a comprehensive mangrove quality index. A total of 10 out of 43 variables were selected based on principal component analysis (PCA). They are aboveground biomass, crab abundance, soil carbon, soil nitrogen, number of phytoplankton species, number of diatom species, dissolved oxygen, turbidity, education level and fishing time spent by fishers. Two types of indices were successfully developed to indicate the health status viz., (1) Mangrove quality index for a specific category (MQISi ) and, (2) Overall mangrove quality index (MQI) to reflect the overall health status of the ecosystem. The indices for the five different categories were mangrove biotic integrity index ( M Q I S 1 ), mangrove soil index ( M Q I S 2 ), marine-mangrove index ( M Q I S 3 ), mangrove-hydrology index ( M Q I S 4 ) and mangrove socio-economic index ( M Q I S 5 ). The quality of the mangroves was classified from 1 to 5 viz. 1 (worst), 2 (bad), 3 (moderate), 4 (good), 5 (excellent). These MQI class could reflect the quality of mangrove forest which could be managed with the objective of improving its quality. Advantages of this method include: •PCA to select metrics from ecological-socioeconomic variables•Formulation of MQI based on selected metrics•Comprehensive index to classify mangrove ecosystem health.