Meeting the challenges of the digital medical enterprise of the future by reusing enterprise software components

Managing medical digital information objects, and in particular medical images is an enterprise-grade problem. Firstly, there is the sheer amount of digital data that is generated in the proliferation of digital (and film-free) medical imaging. Secondly, the managing software ought to enjoy high availability, recoverability and manageability that are found only in the most business-critical systems. Indeed, such requirements are borrowed from the business enterprise world. Moreover, the solution for the medical information management problem should too employ the same software tools, middlewares and architectures. It is safe to say that all first-line medical PACS products strive to provide a solution for all these challenging requirements. The DICOM standard has been a prime enabler of such solutions. DICOM created the interconnectivity, which made it possible for a PACS service to manage millions of exams consisting of trillions of images. With the more comprehensive IHE architecture, the enterprise is expanded into a multi-facility regional conglomerate, which presents extreme demands from the data management system. HIPPA legislations add considerable challenges per security, privacy and other legal issues, which aggravate the situation. In this paper, we firstly present what in our view should be the general requirements for a first-line medical PACS, taken from an enterprise medical imaging storage and management solution perspective. While these requirements can be met by homegrown implementations, we suggest looking at the existing technologies, which have emerged in the recent years to meet exactly these challenges in the business world. We present an evolutionary process, which led to the design and implementation of a medical object management subsystem. This is indeed an enterprise medical imaging solution that is built upon respective technological components. The system answers all these challenges simply by not reinventing wheels, but rather reusing the best “wheels” for the job. Relying on such middleware components allowed us to concentrate on added value for this specific problem domain.