The three-stage effort will promote the adoption of meaningful use of interoperable health information technology. Initiated in 2009, Stage I of the program covered the adoption of EHRs in hospitals and clinics, which are capable of recording important individual health information into structured data. Stage II, which began in 2013, involves the exchange of data between systems. The reporting of clinical quality measures and public health information was now being sent to the designated governmental agencies and registries. Stage III begins in 2015 and is about using the acquired knowledge to improve population health and public health, and to reduce disparities of quality healthcare. Large organizations that were quick to adopt EHR technology have shown the benefits to include improvement in patient outcomes and safety, a reduction in disparities of care, and reductions in cost (Escobedo, Kirtane & Berman, 2013). There is an immense challenge to integrating the widely dispersed and independent elements of our health care system. Recent government figures show that 48 percent of physicians have adopted EHRs, while hospitals are in place at 59 percent. Only 20-30 percent of providers use EHRs to communicate with physicians from …show more content…
ACOs play an integral part in the massive healthcare reform law. They are conceived as a model for streamlining and improving health services. ACOs are paid to take care of the overall health of a population. The more proactive and capable of delivering a higher quality of care, the more overall cost savings (Goedert, 2013). HIEs provide the foundation for ACOs to coordinate care and manage the involved risk. CIOs have a broad mix of technology involved in their ACO and all types of physicians who need to be integrated. It is required of CIOs to think broad enough about all of these different components of technology and about all the physicians. An ACO will need to fully integrate an HIE with solutions for case management, quality reporting, population health management, disease management, and more. Powerful intelligence engines will be needed to sift through the data to start identifying higher risk patients (McNickle,