Successful data conversion projects are often a result of great planning, due diligence and clear expectations. However, when it comes to data validation and testing, things can get tricky. Everyone knows that projects dealing with mission-critical data involves attention to detail by the project team, but sometimes the need for is lost on some of the other parties involved in testing, including end users. 

The questions and tips below provide background on the data testing process and will help you determine both the level of testing and amount of outside staff involvement needed for an efficient and accurate data conversion.

Data services is a complex and constantly changing field. Because of the constant change, data conversion firms and vendors are in high demand. As a healthcare system leader, it is necessary to understand the data conversion process, define your data details and expectations and ask the right questions up front to ensure the highest degree of accuracy during your conversion.

Of all processes within a data conversion project, testing and validation are always the tallest hills to climb. In this two-week blog series, we’ll look at the data conversion process and identify steps you can take to ensure both data validation and testing go smoothly and efficiently.

You made the EMR investment, built the system and completed a successful go-live. But the work is not done yet. Unfortunately, some of the decisions made during implementation may not be the best choices for your system as you move forward. User complaints are often a sign that new approaches are necessary to overcome concerns, improve user satisfaction and increase adoption.

If your goal is to optimize your technology investment, you’ll need a strategy. Here are some of the questions you’ll need to answer in order to develop an optimization strategy.

Coders all around the United States know October 1 means - coding updates. In 2016, we saw major code changes in ICD-10-CM and ICD-10-PCS, and 2017 updates will be more of the same. Here’s what to expect from this year’s updates.

“Normal is an illusion. What is normal for the spider is chaos for the fly.” -Morticia Addams

After an implementation or an upgrade, everyone is looking for things to “get back to normal.” Normal was a state where clinicians were generally satisfied with the system, everyone knew the work-arounds, ticket volume was constant and things moved at status quo speed. The IT team was busy but not frantic and the organization as a whole viewed technology as a necessary, but not critical, part of overall success.

Everything chugged along...and then came the new version, the new functionality or the new application. Here's what the journey back to normal looks like after a big roll-out.

While migrating to new systems, many medical facilities are inclined to find solutions for converting or archiving patient and financial data that suit their specific needs.  To maintain accuracy in data, projects are developed and Legacy system data is handled through many processes to maintain a comprehensive Legal Medical Record.  These six key areas and related questions will allow more efficiencies when planning data conversions and assist in driving the highest levels of accuracy and accountability throughout the conversion project.

Last week my colleagues and I attended #INFORUM2017. What a spectacular event filled with exciting new products and informative sessions focused on the Present and Future of Healthcare ERP and Clinical Interoperability with Cloverleaf Consolidator and BIRST. A customer-focused solution accounts for knowing what the customer wants most and what the company does best, then focusing on where they meet to produce the best possible customer centric product.

State of Data Security

We operate our businesses in a world where many of us are constantly looking over our shoulder.  Threats to the security of our personal information are real and consistent. These threats need to be confronted and dealt with.

Physical security, unlike cyber security, can be actively managed to an extent.  We can be aware of our surroundings, keep a lookout for threats, and confront or remove ourselves from hazardous situations.  

Threats to our privacy and personal information, however, are more insidious.  Many of us try to maintain a degree of information security in our lives.  We protect our personal computers and other electronics from potential malware and intrusions.  We make sure our personal information is protected from public scrutiny by electronic security, physical home security, or destruction as appropriate.  

However, for an individual, data security is not as substantial or straightforward.  There are many situations where private information is not in the hands of consumers to protect.  For example, credit information at the local store or gas station.  Names, addresses, and phone numbers can be sold very easily.

Similarly, personal credit and health information utilized by our local hospital. 

During the implementation of ICD-10 almost a year ago, ICD-10 coders poked fun at the many new diagnosis codes.  Did the World Health Organization (WHO), the producers of ICD-10, really think we would experience an influx of patients walking into lamp posts again and again?  Now, it seems ICD-10 is already prepared to capture injuries of the latest craze, Pokémon Go. 

Pokémon Go, a smart phone game, has acquired more than 30 million daily users since its launch less than two months ago.  Players are really getting into catching Pokémon characters in real-world locations.  But like your mama said, “it’s all fun and games until somebody gets hurt.”  Players are so enthralled in capturing more Pokémon characters to get to the next level, they end up losing focus of their surroundings.  Even though the application displays warnings to pay attention, players are not heeding to the warnings during their Pokémon hunt, and unfortunately, some end up injured. 

Medical data of all shapes and forms add additional contours to the existing IT Healthcare landscape, but what does it mean in layman’s terms? 

To simplify, one analogy is fairly clear, “You can throw the paper at the printer and hope some of it makes it into the feed or you can put the stack in the tray.”  Like everything else in life, wondrous variety exists in types of data and integrated systems from differing vendors to data fields and similar data sets.  Like the printer, if the formats are “groomed,” it eases complexity and adds efficiency to migrations.

Why does it matter? 

Not all data structures are created equal or contains equal languages and values.  To better suit both integration and data standards, it often helps to develop a template to corral the data into a clear and useful format.  System “A” may contain a date of birth in “month/day/year” format while System “B” may define the same value under a different field and carry with it a Julian calendar format (3 numeric digits 001-365 for the day of the year and 2 or 4 digits for the year.)  Though it is a rare occurrence, this type of difference provides illustration of the challenges involved in making one system’s data useful by the new system’s operational conventions.  Health Information Exchanges had the right idea of making data fit specific criteria for interoperability, but many vendors and homegrown/custom EMR systems maintain and use formats that do not match.  Due to the mismatch, transformation and validation become the keys to successfully migrating data to new systems.