Recent banking industries are systems of people, equipment, inventory and procedures arranged to interact in order to accomplish one or more objectives. Rapid changes due to globalization of banks, technological innovations, social and political changes cum increased awareness and demands from customers are putting pressures on banks which are being countered by new management approaches ranging from telecommuting to bank process reengineering. ICT is at the core of most innovations used today by banks to succeed or survive. ICTs are known for strategic management, communication, collaboration work, customers' access, managerial decision making, data management and knowledge management. This paper focused on advantages and disadvantages in using digital ICTs in banking activities for effective service delivery.

The number of missed appointments in healthcare institutions in Nigeria caused problems, hence the need for integrated healthcare system to intervene and provide seamless care for patients. Appointment scheduling system lies at the intersection of providing efficiency and timely access to health services. This research presents an online National Health Insurance Scheme (NHIS) Outpatient Medical Appointment Booking System where NHIS patients can access and view any available personnel or doctor schedule in order to book an appointment with the corresponding time as specified by the available doctor. The system was developed using PhP, macromedia dreamweaver, apache and MYSQL. This is to ensure that the application is robust, cheap and is able to run on different platforms. The system provides the platform to facilitate the booking and management of patients' appointment bookings. Patients can also view their appointment reports. It also provides the healthcare workers an easy access to manage patients' appointments and to generate relevant reports.

Disease rates vary between different locations particularly in the rural areas. While a database of diseases occurrence could be easily found, studies have been limited to descriptive statistical analysis, and are mostly restricted to diseases affecting adults. This paper therefore presents a Mathematical Model (MM) for predicting immunize-able diseases that affect children between ages 0 -5 years. The model was adapted and deployed for use in six (6) selected localized areas within Osun State in Nigeria. Using the MATLAB's ANN toolbox, the Statistics toolbox for classification and regression, and the Naïve Bayesian classifier the MM was developed. The MM is robust in that it takes advantage of three (3) data mining techniques: ANN, Decision Tree Algorithm and Naïve Bayes Classifier. These data mining techniques provided the means by which hidden information were discovered for detecting trends within databases, and thus facilitate the prediction of future disease occurrence in the tested locations. Results obtained showed that diseases have peak periods depending on their epidemicity, hence the need to adequately administer immunization to the right places at the right time. Therefore, this paper argues that using this model would enhance the effectiveness of routine immunization in Nigeria.

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