By Iqbal Khan
Distributed caching provides scalability that can relieve overloaded server farms and re-invigorate listless systems.
As Web and service-oriented architecture technologies become more popular, hospitals are adopting them rapidly for automating their operations and allowing their administrative staffs, doctors and patients to directly access the hospital information system (HIS). While this has introduced a lot of efficiencies in hospital operations, it has also introduced new headaches for hospital IT management due to an increased load on the HIS.
An HIS consists of an integrated set of Web applications automating hospital operations. This includes applications managing administrative, financial, clinical, radiology and lab operations. There are usually thousands of different people using this system at any given time. However, despite a large number of users, everybody expects the system to perform well even during peak usage hours.
Hospitals try to address scalability by creating Web farms consisting of multiple Web servers tied together through a load balancer to distribute user load. Yet, as the number of users and transactions grows, various data access bottlenecks usually occur thus considerably reducing the performance of those operations.
Typical solutions for resolving this challenge, such as adding more servers, fall short and don’t provide the required scalability for sustaining HIS at their normal performance during peak usage. Scalability simply means keeping the same system performance even during peak usage times.
A hospital must always be operational; therefore, most applications in an HIS are considered mission critical. However, applications with a large number of simultaneous users are more prone to downtime or scalability issues. One such application is a clinical information system (CIS) that deals with electronic medical records. A CIS concentrates on patient-related and clinical-state-related data and is used by hospital staff, patients and even outside partners. This can easily account for thousands if not tens of thousands of people.
Due to its large number of users, a CIS is the most likely candidate for having scalability issues. It can be regarded as a mission critical application because doctors, nurses, patients, business offices and medical records personnel constantly rely on it. Therefore, it must provide 100 percent uptime and with no noticeable drop in performance. When a patient management system slows down due to scalability problems, a domino effect within hospital operations adversely affects business costs.