Welcome to the Data Analytics Toolkit PowerPoint presentation on applied analytic methods. This presentation covers applied analytic methods, focusing on describing the available analytic platforms.
When considering meaningful use there is a need to adopt analytic platforms and technologies that are cost effective and capable of handling large datasets. There also tends to be a steep learning curve for many analytic platforms. In this presentation, you will be introduced to some of the most popular analytic platforms and related tools in hopes of showing you the advantages and disadvantages so you can choose which application to adopt.
There are many statistical packages that can be adopted. Each have their own pros and cons. SPSS is a common stats platform that is most often used for psychological research. It s relatively easy to use due to its point and click interface; however, the software is not freely available. Prism is a less common platform and is very similar to SPSS in many ways. It is widely accepted for carrying out biological research. Prism also requires users to purchase a license. SAS is very prevalent and powerful, but also quite expensive. However, there is a huge demand for individuals who have knowledge of SAS as the platform is widely accepted in healthcare. It can hook up to an organization s databases, it s very versatile, and it supports a point a click interface as well as a programming language, but it may be cost prohibitive. R is an open-source analytics platform. It is becoming more popular in healthcare and is widely accepted by data analysts across different domains. It can hook up to an organization s database, support many stats techniques, and it is free! However, there is a learning curve with R as it requires users to use a programming language.
An analytic platform must have the capability to carry out many different functions, including data manipulation, statistics, and graphical visualizations. There are literally hundreds of applications that can be adopted to cover a multitude of these analytic tasks. Each of the platforms mentioned in the previous slide fulfill the requirement of performing each of the listed tasks.
When considering the most cost effective software, there are several platforms and tools that are free and open-source. One such platform is the statistical software R. When R is combined with other open-source software including Hadoop, which supports parallel processing for expediting large data extraction and analytics, and MySQL, which is a relational database for storing data, the possibilities for widespread adoption and mainstream use are easily recognized. Also, due to the fact that they are free platforms, their adoption is feasible for any organization.
There are a variety of software applications available that support enterprise data warehousing and analytics. Although these software applications are not free, many of them are quite popular in healthcare. Organizations are looking for tools that make analytics and visualization an easy process. These platforms offer a solution to overcome the burden of learning how to use some of the statistical platforms that require programming. Enterprise data warehousing and analytic platforms allow users to navigate through their data with just the click of their mouse. Because this software is connected to the organization s data, the software can quickly reveal trends in data that are benchmarked against national or organizational targets.
There are also efforts under way to support meaningful use with free online analytic tools that can assist in calculating meaningful use objectives. Project Cypress is one such tool. It offers an easy to use platform for calculating meaningful use stage 2 clinical quality measures. It has proven to be rigorous and repeatable.
There are also many options for adopting certified EHRs which are either open source or free. Some of these EHRs include vxvista, PracticeFusion, and Dr. Chrono. The adoption of these systems is becoming more widespread as organizations are taking steps to cut costs. The options that organizations face regarding analytic platforms, data storage software, and EHRs are widespread. Organizations must identify their needs and the amount they are willing to invest in terms of training, money, and time to adopt a particular system. However, analytic software and other related tools can provide organizations an opportunity to meet the demands of meaningful use and other organizational needs for monitoring the effectiveness of care delivery.