The previous two posts focused on getting a server up and running, and setting up your server with user access. In this post, we finally work on installing R and RStudio Server on our instance and configuring the application. Pay special attention to the packages notes at the end of this post. This will ensure
The previous post focused on the initial task of instantiating a server. We chose Digital Ocean because it has an easy-to-use interface, great pricing, and great customer support. I should note that you can use any cloud service you’d like, so long as you can install Ubuntu 14.04 on it. If you do choose Digital
There are many advantages to moving away from local data analysis and pushing it to the cloud. I’ve talked a little bit about them here. This post, however, isn’t intended to convince you even more. I’m hoping that you’re already convinced. And if you are, see below a complete tutorial of what I believe to
Although this post has been a very long time coming, I’ve gotten many good questions and requests over comment/email to create a streaming API tutorial, so here it is! This second post is a follow up to my initial Collecting Tweets Using R and the Twitter Search API post. As always, before I dig into
How healthy is your community? Now you can find out! AskCHIS Neighborhood Edition is now live! Watch our launch webinar here. Here’s just a snippet of what you can do with this new app!
Sentiment Analysis and Natural Language Processing (NLP) have always fascinated me yet I never really understood the inner-workings of this type of analysis and never made the time to dig into the science. Until recently, I didn’t even know that you could collect tweets for free using Twitter’s Search and Streaming APIs. A few days
The U.S. Government Accountability Office (GAO) recently released a document detailing an investigation on the difficulties and costs associated with launching Healthcare.gov, the federal health insurance marketplace implemented as a result of the Patient Protection and Affordable Care Act (PPACA), informally known as Obamacare. The report, titled HEALTHCARE.GOV: Ineffective Planning and Oversight Practices Underscore the Need
CoveredCA previously released enrollment numbers in the Affordable Care Act (ACA) health insurance exchanges here. According to their reports, almost 1.4 million (1,395,929) Californians enrolled in insurance plans sold on the exchange through April 15th, 2014, with Los Angeles, Orange County and San Diego County taking the top 3 spots in total number of enrollments (see table below).
About a year ago, I posted a visualization of EMR/EHR attestation numbers from data provided by CMS and the ONC. Almost 16 months later, the attestation landscape hasn’t changed very much. From a geographical perspective, highly populated states continue to have the highest overall percentage attesting organizations (EPs and hospitals). However, keep in mind that these
Kaiser Health News recently published a table with readmission rate penalties from Medicare data. The data shows the percentage of hospitals within a state who will be penalized for excessive readmissions as part of the Hospital Readmissions Reduction Program. Here’s a quick choropleth map showing the geographic distribution of these penalties. Interestingly, all seven hospitals