Integrated Health Information System

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Executive Summary Cerner, one of the top two EHR systems in the country, was chosen by UAB when leaders in the health system decided to switch to a fully integrated health information system. The decision to utilize the Cerner EHR, PowerChart, as part of an integrated system, fulfilled a core value of the organization and follows the trend of many institutions throughout the country (Ford, 2013). PowerChart provides users with an integrated, clinical database that allows them to view real-time clinical data, enter orders via a CPOE module, and ­­­document in patient's chart from multiple locations throughout the health system (Alsip, 2017). The process of EHR adoption at UAB as outlined by Dr. James Willig, an internal medicine physician, …show more content…

However, the processes of LIS selection, implementation, and training should not be taken lightly. Organizations must first define their goals, objectives, and desired outcomes before evaluating potential vendors. The defined current state and desired future state of the organization should drive the ultimate selection of the particular LIS vendor. For example, we learned during our tour that one of UAB’s core values is optimization of system integration between core clinical systems and key ancillary systems. This core value influenced UAB’s decision to choose one vendor, Cerner, for their core clinical systems, including PowerChart and PathNet, the LIS. Optimizing integration between the EHR and LIS further improved efficiencies and accuracy of the entire process of ordering and resulting labs. The strategic decisions surrounding vendor selection and the accompanying outcomes at UAB were similar to the reading about UHIC’s decision to choose Epic Beaker (CP) as their LIS, which built off of the system-wide implementation of Epic’s EHR several years prior. Also similar to UAB, UHIC found that the transition from a paper-based workflow to electronic showed a reduction …show more content…

Intelligent management of laboratory information during the pre-analytic and post-analytic aspects of laboratory testing can help improve clinical care. For example, during the pre-analytic phase, a clinical decision support laboratory knowledge base could be interfaced so that at the time of test ordering, the expert system incorporates patient information, previous test results, and clinician input to suggest appropriate tests, test frequency, and interpretative criteria. At the time of test ordering, the system could also automatically display to the clinician previous test results, pending related orders, and recommended tests based on inputs, which may lead the clinician to either cancel a duplicative test or decide an alternative test is more appropriate (Sepulveda & Young, 2013). This is not what we found at UAB, as the lab staff voiced one of the most common issues they experienced was the fact that multiple authorized users are allowed to order the same lab test for a patient at around the same time. For example, a patient may have 4 CBCs ordered, one every hour from 1 AM to 4 AM. While there are certain medical conditions in which this type and frequency of testing would be clinically appropriate, those are few and far between, and most testing done this frequently is carried out

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