Success lies in the details.

Clinical Cohort Patient Management System

Industry
Healthcare

Project Size
Medium

Problem
Infectious Diseases Institute (IDI) at Makerere University Medical School in Kampala, Uganda is an out patient clinic serving patients with AIDS and other infectious diseases. IDI is a leading research and educational institution for AIDs in Africa.

IDI has a research program that follows a set of 1000 patients who are on Anti Retro Viral (ARV) drugs for a period of 5 years. IDI needed a custom software package designed for the management of ARV patients and ARV therapy in an African setting. The software requirements included a robust database to hold significant quantities of detailed medical information; mechanisms to ensure high data quality; and a scalable architecture for easy addition of new medical forms.

Solution
A software application was built to accommodate the data from baseline and follow up medical forms for children and adults. Because the amount of data per patient was quite large, special care was take with the user interface to segment the data input screens and encode business rules to aid in the entry of correct and consistent data. Simple reports calculating population statistics was provided.

Software Features
Application functionality highlights include:

Content includes:

• Multi-page baseline clinical form for adults and pediatrics patients with and without anti-retro viral treatment
• Multi-page follow-up clinical form for adults and pediatrics patients with and without anti-retro viral treatment
• Quality of Life forms for adults and pediatrics
• Workflow for quality assurance purposes
• Simple population reports
• Ability to self administer lists of symptoms
• Feature level access rights

Technology
.Net, C#, Oracle, IIS, IE browser

Challenges
Because the data will be used for research purposes, it is imperative that the data is clean and consistent and the data set fully populated. The system captures over 450 pieces of data per patient per medical form. Field level validation is used extensively as well as conditional user input elements. Age and gender specific rules were implemented to hide/unhide appropriate questions and field combinations driven by the patient's profile. Workflow was implemented so that quality assurance specialists can review the data before it is available for research purposes.