Leveraging ICT in the development of a clinical cancer registry – lessons learnt from the Kenya Oncological Research Database
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The International Agency for Research on Cancer estimates that worldwide, by 2020 there will be 15 million new cases of cancer a year, 70% of which will occur in developing countries1. It is feared that most cases of cancer in Africa will be diagnosed at advanced or metastatic stages2, 3. In most developing countries, Africa included, priority for cancer care is rated low, as more emphasis is placed on the control of communicable diseases and improving environmental sanitation. Developing countries are liable to be exposed to further risks of cancer with increasing industrialization, urbanization and intensification of agriculture in the course of development4. The presence of an adequate information system is an essential part of any cancer control strategy5. Traditional cancer registries are population-based6 and seek to describe incidence, rates and trends of all cancers within set populations. In Kenya there are currently two such registries: the Nairobi Cancer Registry and the Eldoret Cancer Registry which serve the Nairobi and Uasin Gishu District populations respectively 6, 7. The Cancer Abstract Forms employed by these registries are used to collect 27 data items covering patient demographics, tumor details, treatment, data sources and followup information7. These data make the population registries suitable for: routine population health surveillance, comparing the incidence and trends of cancer in Kenya with others internationally, quality assurance activities and providing representative samples for patterns of care surveys8. However, population-based registries have their shortcomings: the range of data collected by population-based registries is adequate for broad public health surveillance, but too narrow for clinical and other more specific service applications. In particular, these registries rarely collect data on stage of cancer at diagnosis, treatment information, time from diagnosis to first recurrence, and other outcomes apart from survival. While histological sub-types of cancers are identifiable, other subtypes defined by receptor status, biochemical and other markers are not routinely collected. Yet another shortfall of these registries is the timeliness of the data given that incidences and trends are a function of the larger population8. Clinical cancer registries provide the complementary staging, treatment and allied clinical data required to monitor clinical care and outcomes. Additionally they can be used in conjunction with other data sources to monitor and assess the effectiveness of new treatment protocols, compare patterns of care with guidelines and survival effects of different diagnostic and treatment practices to determine best practice8. These clinical cancer registries also allow for the expansion of the research parameters to allow for linkages with bio-specimen banks for future proteomics and genomics studies. Clinical registries have been shown to therefore supplement the effectiveness of population-based registries in improving cancer patient care9. The Kenya Oncological Research Database (KORDA) project was established in 2008 in order to establish a platform for the multi-clinician, multi-centric collation of clinical oncology datasets. We present our experiences and challenges in setting up the database and discuss prospects for the future.