Mentor Meeting: My mentor is the director of the Value-Based Clinical Care Department. We reviewed my clinical objectives. She then proceeded to explain to me how several committees have been created within our organization as a result of the 2017 final rule of the Medicare Access and CHIP Reauthorization Act of 2015. She explained the current initiatives underway that were in the final planning stages. As a part of the quality payment program under this rule, the committees created are introducing the Merit-Based Incentive Payment System (MIPS) to all of the Northside outpatient provider offices.
As a result of the Medicare Access and CHIP Reauthorization Act of 2015 there are new payment mechanisms and quality reporting requirements. To have a better understanding of this, my mentor enrolled me in two online classes as a part of my clinical rotation. They are Understanding Data Analytics and The Business of Value-Based Care.
The primary concept of this meeting was the importance of nurse involvement. You can see this represented in the first chapter of our textbook when Yoder-Wise (2015) states "one can conclude that no substantial health reform can unfold without active nursing engagement. nurses are expected to help fulfill health care's triple aim" (p. 3). The goal of triple aim is better healthcare, better health, and lowered cost (Yoder-Wise, 2015).
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Understanding Data Analytics: I obtained an understanding of how several different data systems are utilized within a healthcare organization and the need for centralization of this information.
An example of this can be seen in a hospital system. There is one data collection system for electronic health records, another collection system for laboratory values, and yet another system for diagnostic imaging. This doesn't include data collection systems for nutrition, care coordination, or previous medical records. Although the data systems are designed for patient care, they only capture specific data and not the whole picture.
As a result of the many different data systems utilized in patient care, clinical data warehouses have been created.
"The term analytics refers to the discovery of meaningful patterns in data, and is one of the steps in the data life cycle of collection of raw data, preparation of information, analysis of patterns to synthesize knowledge, and action to produce value" (Descriptive Analytics, 2015).
Understanding Data Analytics: This training involved learning how to review and correct data for errors prior to performing analysis on it. It also included hands on practice with Microsoft Excel. Practice activities included: pivot tables, histograms and chi-square test.
An example of correcting data after it has been reviewed is a patient's height. It the area to enter the height was missing, you can review EHR and add it. Another example could be the gender of the patient. If that area is missing I co...