Time to Diagnosis and Clinical Decision for Patients at the Oncology Unit at the Jaramogi Oginga Odinga Teaching and Referral Hospital (Jootrh), Kisumu, Kenya
Abstract/ Overview
Delays in the onset of cancer to hospital visitation, diagnosis, and treatment of cancer can have adverse consequences on cancer management outcomes. Monitoring turnaround for various processes in the cancer pathway can provide important gaps that exist in the cancer treatment continuum; otherwise, patients would continually suffer due to personal delays, and hospital system delays leading to increased morbidity and mortality. This study aimed to explore the reasons for the patient’s delay in seeking early medical care for various cancers at the Jaramogi Oginga Odinga Teaching and Referral Hospital (JOOTRH). Specifically, this study determined the time taken for Cancer diagnosis (CAD) and clinical decision (CD) among patients and barriers to clinical decision (CD) and referral networks that exist. Data was obtained through a questionnaire and desk review of patient records, analysis done using various statistical packages R and SAS, and graphs and tables using Excel. The WHO Cancer classification based on anatomical classification was used. Of the 320 cancer participants enrolled, the majority >30% of the cancer cases were from Kisumu and Siaya counties. Breast, cervix, esophagus, and prostate cancers were most prevalent respectively. More than 60% of patients were in stages II and III at the time of diagnosis. The median overall TAT from onset to clinical decision was 21 months. In a Cox proportional Hazard regression model, employed patients were less likely to visit the hospital after the onset of the disease compared to the unemployed patients (HR: 0.51; 95% CI: 0.39-0.65; P < 0.005) while TB Patients were more likely to visit the hospital after onset of disease compared to their counterparts who did not have TB (HR: 3.68; 95% CI: 1.16-11.7; P = 0.03) and this outcome remained significant even on time between diagnosis and clinical decision. Females were less likely to be diagnosed with cancer (HR: 0.74; 95% CI: 0.56-0.98; P = 0.03) compared to male and equally married patients were less likely to have a shorter TAT for cancer diagnosis (HR: 0.71; 95% CI: 0.51-0.98; P = 0.04) compared to those who were single and similarly those who had initial cancer screening compared to those without (HR: 0.71; 95% CI: 0.53-0.97; P = 0.03). Further, alluding the role of social behavior on the impact of uptake of cancer services as amidst the many cancer screening programs in place. The turn around tine determined in this study demonstrated that regardless of cancer type or staging of the cancer , the delay was longer in all the two groups on time between onset of illness and time to first hospital visit. In conclusion, being a woman, being in a relationship through marriage, and having initial screening for cancer contributed to a delay in cancer turnaround time, while on the other hand, TB patients experienced short turnaround times across the cancer management pathways. There is a need for public health education and follow-up on the need for early cancer screening. The role of gender, employment status, and marital status on the social influence on the uptake of cancer needs to be investigated.