Five steps for a successful, pain-free switch to electronic health records
By Laura Madsen
Speak to anyone in any branch of healthcare today and one thing is certain to come up: electronic health records (EHRs). Or in other words, the pain of migrating from traditional, hard-copy record keeping to a digital system that promises to make things better for clinics, physicians, and patients.
EHR and the office manager: The chart stops here
For those that have made the switch to EHRs already, the road has not been completely smooth. A study by the American College of Physicians released after the spring HIMSS13 conference shows that EHR user dissatisfaction rose by 12% in the "very dissatisfied" category.
Why all the problems? Quite simply, too many clinics and other healthcare organizations view the transition to EHRs as a technology issue instead of a process improvement. With the best will in the world, when the transition is technology led, it can often mean a lower level of involvement from management and other departments, quick product fixes and a challenging, time-intensive user experience for the physicians and support staff entering data.
A team approach to electronic health records
Making the switch to electronic health records
In order to avoid some of that pain, it’s critical to look at the transition as the launch of an organizational data management process, or – in other words – the creation of a business intelligence (BI) program. BI programs bring together data together to give you better transparency into the operational, financial, and clinical aspects of an organization’s work. So rather than just implementing an EHR to check a box, make an investment in your organization by creating a market-differentiating BI Program.
Creating a successful business intelligence program for easy EHR transition
- Data quality is critical. Just like seatbelts are critical. Of course, you don’t have to invest in a system to provide quality data (or a seatbelt), but the day will come when you wish you had. Creating a dynamic, enterprise data governance function that guides data quality standards will provide the foundation for efficient operations and future growth.
- Build organizational support. A strong structure of sponsorship from all parts of your clinic or organization must be built. That sponsorship will assure that, regardless of shifts in mission or leadership, your program will have the best chance of continuing to deliver real value. The leader of any BI team must focus on a clear, defined path for the program and work hard to engage sponsors across the organization in order to navigate through the challenges that come with any program launch.
- Consider your technology platform carefully. There are no black and white dos and don’ts. You need to make informed decisions about the trade-offs, whether it concerns hardware, software or architecture. To do this, you need to engineer a trusted partnership between the IT group delivering the technical aspects and the BI team that represents the broader organization and its business needs. Don’t try to short-cut important decisions about how you structure your data or how to apply best practices for the extract, transform, and load (ETL) work where business rules are applied to the data to ensure quality and usability. Doing so will only impact user adoption and almost certainly degrade user experience.
- Show value.This seems obvious, but the truth is many BI programs get bogged down in the “below the waterline” work and fail to deliver value to management. To avoid this, you must view everything through the quality delivery lens – even small incremental items that provide the business with information never seen before, or delivered in a new way (e.g. dashboards). Doing this will allow you to continue working on the foundational aspects of the BI program and shortcut doubts about value to the business. Without it you will lose your sponsorship and eventually funding.
- Consider impact on organizational culture from the start.BI programs will transition your organization from decision by instinct to decision by data, but that doesn’t just happen organically. You have to prepare your organization for that kind of change so keep this in mind and make small, incremental changes as you proceed to ensure long-term success.
At the end of the day, EHRs are simply transactional systems. They are not intended to hold data, so transitioning from one record to another, or even holding populations over time to show improved outcomes, can present difficult issues. Data warehouses can and should be used to stage and hold data. These should be agnostic systems that allow clinics or organizations to use a best in class, front-end system for all clinicians to ultimately improve use, lower time invested and result in better record keeping for the future.
Laura Madsen is founder of the Healthcare Business Intelligence Summit, now in its fifth year, as well as a sought-after speaker and expert on business intelligence programs in the healthcare industry. She is author of “Healthcare Business Intelligence: A Guide to Empowering Successful Data Reporting and Analytics” and can be contacted at [email protected].
