The healthcare strategy of large IT vendors must rely on powerful middleware solutions that they must apply as enabling technologies resolve system inefficiencies.
Concurrently with the global financial crisis, the first stages of healthcare reform have imposed a new economic environment on medical imaging providers. Reimbursement cuts, the slowdown in procedure volume growth and tightened technology purchasing budgets are some of the factors creating economic pressures on providers. All of these dynamics create a need for efficiency gains and increases in cost containment in medical imaging operations.
Throughout the past two decades, information technologies such as RIS and PACS have played a central role in digitizing and streamlining medical imaging workflow processes. However, today, these solutions fall short of allowing medical imaging providers to make the next leap forward to next generation healthcare, which involves a forklift upgrade of their operational efficiency, financial model, IT organization as well as their patient outcomes and quality of care.
Indeed, on the operational front, first-generation RIS/PACS systems do not provide all the analytics tools necessary for a proper assessment of current gaps and weaknesses in the workflow. This evaluation is a prerequisite to any prospective effort by providers to address workflow inefficiencies.
Similarly on the financial front, traditional solutions lack the business intelligence tools that would provide the critical information required to back more informed business decisions. Likewise on the IT front, current IT solutions do not always provide adequate support to the modern day medical imaging enterprise, which is evolving within a multi-site, multi-specialty and multi-vendor RIS/PACS environment.
Finally, on the clinical front, the fact that first-generation RIS/PACS platforms offer limited integration and interoperability capabilities yields a diagnostic imaging environment that is limited to medical images and basic patient information. This limits the amount of relevant information available to medical imaging specialists at the time of interpretation. By the same token, it also restricts their ability to make better informed diagnoses, to compare with similar historic cases, to add value to their interpretation, and to communicate more effectively about patients with their referral basis.
As the healthcare system starts to move slowly, but surely, towards the accountable care organizations (ACO) model, the next frontier for the medical imaging enterprise lies in its ability to build solid operational, business and clinical decision support (CDS) capabilities for medical imaging. Moreover, it has to be able to do so in a cost-effective manner, while leveraging previous IT investments and the plethora of unstructured patient and enterprise data isolated in disparate enterprise silos.
In this context, the healthcare strategy of large IT vendors must rely on powerful IT middleware solutions that they must be able to apply as enabling technologies in order to resolve system inefficiencies. The vendors that succeed both on the technology enablement aspect and on the technology delivery side of the value chain will be best positioned to prepare providers for the new phase lying ahead.
Microsoft and IBM are two such large IT vendors whose commitment to healthcare is providing key enabling technologies for next-generation medical imaging. Based on the company’s Health Intelligence Platform, Microsoft’s Amalga for PACS allows providers to consolidate imaging-related information disseminated throughout the enterprise. Then, by synthesizing the relevant information, presenting it in a context specific manner and making it an integral part of the diagnostic workflow, the system essentially automates the function of a resident or fellow radiologist tasked with preparing and previewing cases prior to radiologist review, typical of academic settings.
The other possibly groundbreaking enabling technology for medical imaging is the Watson supercomputer developed by IBM. Like Amalga, Watson taps into disparate IT systems in order to extract the relevant pieces of information currently unstructured or unavailable. Unlike Amalga however, Watson-based analytics are geared towards predicting future outcomes based on the statistical analysis of a huge number of previous outcomes. Providing clinical decision support and preventing patient readmissions are two of the major benefits that this capability can offer to medical imaging providers.
Both Microsoft and IBM have elected industry partnerships as one of the key channels to deliver their enabling technology. Illustrative of that is the announced joint venture between Microsoft and GE Healthcare that was just named Caradigm, as well as the announced collaboration between IBM and Nuance on Watson analytics.
Amalga and Watson, both enabling technologies, provide a technological alternative to the prior authorization model involving radiology benefit management firms (RBMs) currently under consideration as part of the healthcare reform of medical imaging. Forming an opposing force to the highly criticized RBM model, these technologies would help support the competing model based on clinical decision support and appropriateness criteria. Along with accreditation, the CDS model is the model currently defended by medical imaging advocates and by the medical imaging and patient communities in general.
Frost & Sullivan Principal Analyst Nadim Daher has more than eight years of medical imaging expertise. His industry analysis covers the U.S. and Canadian markets and includes a focus on medical imaging informatics and medical imaging modalities.