We frequently encounter EHR data integrity problems within electronic health records (EHR), practice management, billing, and laboratory information systems. These issues can range from simple anomalies in reporting to complex structural database problems. While some issues can be easily resolved, others require more complex solutions. Today, we encountered a particularly nonsensical issue that highlights a […]
How do you get all of the information you want out of a system? Some systems have great reporting, some have mediocre reporting, and some have terrible reporting. What we’ve found is that even the best systems almost never allow you to extract all the information you need in one report. Even when custom reporting […]
We were recently working with a client where we needed to gather data from many different places, one of which involved clearinghouse data management. But why do we need data from a clearinghouse? Why can’t we get it from a practice management system, billing system, or EHR? Well, most billing systems, regardless of the brand, […]
I’m constantly impressed by how bad the data is in healthcare IT systems. We’re encountering one of these clinix data integrity issues again today, and they seem to pop up all over the place. You could consider these to be metadata issues, but in reality, they are data integrity issues. For example, there are some […]
Let’s say you have a post date for payments in May. Whatever you posted in May should be closed and should never change because you’re capturing the time at which a function was performed, and you can’t time-travel back to do that. However, some systems allow this, and the problem is that the EHR data […]
I’ll bet you didn’t know time travel was possible. Well, with some healthcare IT systems, it is. It’s not uncommon in billing to find yourself in a situation where there’s some unapplied balance. You receive an ERA, an EOB, or some form of payment, and for whatever reason, you can’t post the entire amount—or even […]
Analytics, statistics, data science, artificial intelligence. What does all this mean? What are we doing in data science in healthcare, specifically in revenue cycle management concerning financial data for healthcare? First, what is data science? This is a way of categorizing or grouping a whole bunch of things related to big data computer science, which […]
Where you get your data from does make a big difference in healthcare data analysis. Suppose I look at the progression of how we accessed data from our clients. In that case, we’d initially had the idea that we could go into the billing system, whether it’s a practice management system, EMR, or laboratory information […]
When are benchmarks, not benchmarks? This will be a long podcast, so strap in a little bit. The MGMA collected data from 2,500 practices. There was a webinar where the MGMA, in conjunction with WhiteSpace, which makes data warehousing effectively, offers data warehousing, did a presentation and talked about MGMA benchmarks. They spoke a bit […]