Addressing unmet needs of cancer care in a lower middle income country by establishing an electronic hospital based cancer registry.

e13621 Background: Sri Lanka (SL) is a Lower Middle Income Country (LMIC) which has seen its cancer incidence double in the last 25 years. National Cancer Institute Sri Lanka (NCISL) is the only dedicated cancer hospital in SL and provide care to around 40% of all patients diagnosed with cancer in the country. The existing SL Cancer Registry, primarily contains only socio-demographic data and there was no systematic method to capture cancer treatment and outcome data This presents a missed opportunity in identifying and bridging gaps in cancer care delivery and health equities in an effective manner. Methods: We built an electronic hospital based cancer registry using the “free to use” cloud based District Health Information System (DHIS2) software platform and prospectively collected disease, demographic, treatment and outcome data on selected cancers treated at the NCISL from 2016 onwards. This platform is easily adaptable and will allow downloading data to standard statistical software directly for data analysis and can be integrated with other existing health information systems. its easily adaptable . The variables captured were identified through focus group sessions with both healthcare workers and patient representatives. Results: To date, data from over 5,000 breast, 1500 colorectal and 600 thyroid cancer patients have been captured. From this database data on disease characteristics, demographic details, survival rates, treatment toxicities, referral pathways, health care seeking patterns, comorbidity data, health care related quality of life, treatment guideline concordance, out of pocket expenses incurred while on treatment, palliative care delivery, cancer care equity gaps can be elicited. Conclusions: Our database demonstrates that it is feasible to build low cost, easy to maintain yet good quality custom made data bases to collect cancer care related data. Careful selection of variables will allow health systems to identify existing gaps which is the key initial step in addressing them with a view of improving cancer related outcomes. Integrating demographic and outcome data within the same database will help in identifying health system inequities. Continuous data collection will allow assessing the efficacy of any intervention launched to bridge these gaps in the future. This database can also be adapted with minimal change by other LMICs to generate real world data to inform national cancer control policy planning.