In this day and age, every profession seems to have a suite of digital tools specific to their field. Designers have Photoshop, music producers use Logic Pro, project managers use any number of tools like Jira, Asana, and Trello. Experts working in the field of health care data analytics also tend to be familiar with a specific set of digital programs that they use to collect and analyze data. Because health care data analytics resides at the unique intersection of tech and health care, some software is used across industries and might be familiar to professionals in other fields while other programs are primarily only used by those in medical fields.
Health care analytics software for collecting data
The first step in finding solutions using data is to locate the data that can give you information about potential issues. Below are a few common data collection software examples.
Electronic health record systems
One of the most obvious places that data analysts working in health care can retrieve information about their organization and its patients is an electronic health record (EHR) system. EHRs are used in all types of settings: doctors’ offices, emergency rooms, clinics, inpatient facilities and more. With that broad reach, they also collect a broad set of data: patient demographic and insurance information, physician and procedure notes, administrative data like how many hospital beds are available or estimated wait times. Some EHRs also are able to import data from personal devices like smartwatches, smartphones, heart monitors and others, while some of those objects require their own software and need data to be exported and uploaded between the different systems.
If you’re coming to health care data analytics from a medical background you might be familiar with one or more EHR systems. Some of the most popular are Epic, Cerner, MEDITECH and Allscripts. Many of these systems license software to health care organizations in different packages based on their size and use. Several of them even include their own reporting tools that can easily pull in data to be explored within the EHR itself.
Google Forms, Access, Excel
Although these programs weren’t created specifically for medical data collection, they are often used by researchers in laboratories. Google Forms is pretty self-explanatory. It is used to collect a specific set of information sought by the form creator and can be used internally or externally, collecting anonymous or de-identified information. Microsoft Access is a relational database tool that can be used to manage large amounts of data and build custom applications. A lot of people will use Access along with Microsoft Excel, with Excel serving as the tool that they can use to perform complex equations on the data stored within Access.
Health Care analytics software for analyzing data findings
There are seemingly endless options for health care data analysts looking to process their data. Most of the programs in this blog include some amount of analysis capability. However, considering the large amount of data that most health data analysts deal with, certain tools are necessary.
A common issue with health care data is the massive volume of it that any one organization is able to gather. Organizations use Hadoop instead of maintaining a ginormous server. Hadoop works by “clustering” multiple computers in order to bring data ranging in size from gigabytes to petabytes together to be interrogated for insights. Hadoop’s “ecosystem” has evolved and grown over time and includes a number of other data analysis and management programs. Two of them are MapReduce and Spark.1
MapReduce is like the engine of the Hadoop vehicle. The name of the program refers to two sequential tasks that Hadoop programs perform. First is the map job, which takes a set of data and converts it into another set of data. Here individual elements are broken down into pairs of keys and values that are called tuples. Then the reduce job takes the output from a map and combines those data tuples into a smaller set of tuples.2 You can think of this process as being similar to how you might count the colors of jelly beans in several jars. First you would map to find you have the numbers of jelly beans of each color in each jar (Jar A: three blue, two red, one yellow; Jar B: five blue, three red, one yellow) and combine them to find the total number of each color (eight blue, five red, two yellow) across all jars. It’s essentially combining and simplifying data sets.
Spark, which was developed more recently, is very similar to MapReduce. Spark is able to process batches of data with real-time streaming and employing the user’s preferred programming language: Python, SQL, Scala, Java or R. It’s also scalable and can be used across machines for machine learning. Health care organizations can use Spark to predict and recommend patient treatment. Outside of health care, an example of Spark’s capabilities is as a home valuation tool for Zillow. Zillow uses machine-learning algorithms from Spark to process large data sets in near real time to calculate the estimated market value for a specific home.3
Health care analytics software for presenting data
While theoretically you could present the data from most of the previous systems to share findings, there are also a number of software programs available that are critical for data visualization. These tools are great for when you need to demonstrate your methods and conclusions to executives or those outside of health data analytics.
Tableau is a popular program for data visualization and one you would be likely to encounter as a data analyst in any field. The great thing about Tableau is that even those who aren’t programming experts can pretty easily use the tool to generate charts, graphs, maps, dashboards and other visual representations of data to tell a story. The tool is also configured to make it easy to share data internally or externally, on websites, in handouts, or wherever you need it.
In recent years you might have interacted with Tableau without even knowing it. Many health departments have used Tableau to share COVID-19 data like infection and vaccine rates, numbers of cases and other relevant information.
Google Charts is a much simplified version of Tableau and could also be related to the capabilities of Microsoft Excel. An advantage of Google Charts is that it's free to use and you can create line graphs, scatter plots, bar charts and more. Although it has fewer bells and whistles, Google Charts is still incredibly useful and a great resource for any data analyst.
Learn the ins and outs of health care data analytics software
The curriculum of Marquette University’s online Master of Science in Health Care Data Analytics is split evenly between health context and data science so that you enter the field prepared to tackle complex projects. Take courses in business intelligence tools, data visualization, managing data at scale and everything in between. Our expert faculty will teach you how to use several different programming languages, Hadoop, MapReduce, Spark, Tableau, Google Charts and more. Speak with an Admissions Advisor to learn more about the program and discover the possibilities of a career in health care data analytics.
- Retrieved on May 6, 2022, from aws.amazon.com/emr/details/hadoop/what-is-hadoop/
- Retrieved on May 6, 2022, from ibm.com/topics/mapreduce
- Retrieved on May 6, 2022, from aws.amazon.com/big-data/what-is-spark/