By Karly Rowe, Vice President Patient Access, Identity, and Care, Experian Health |
Already imperfect patient identifier and records systems are getting stressed by huge increases in the amount, novelty, and diversity of post-COVID health-related data. With the arrival of a national patient identifier scheme still sometime in the future, there are ways that providers can respond to the challenge now. Doing so will enable them to improve patient outcomes and position them for whatever the future may bring, too.
A tough situation is getting tougher
The challenges of incorrect, incomplete, and duplicate patient records were well known before the pandemic, starting at scheduling / registration and then compounding at testing and additional touch points to negatively impact patient outcomes, productivity and costs, and claims payments. Getting patients into the system so they could be treated was the right goal that often led to less-than-ideal results.
Now, as many as one-third of Americans who put off healthcare during the pandemic may return for treatment. Millions of them will arrive with changed or different healthcare coverage (starting with the estimated 40 million who were put out of work entirely, and a fifth of all American adults who moved or knew someone who did), and many of them won’t “arrive” physically as often, if at all, as use of telehealth skyrocketed during the pandemic and is unlikely to go away.
If there were ever a suitable time for a national standard for patient identity, it would be now; in lieu of that, however, there are three things that providers can do to achieve many of the same benefits of standardization.
Define what you are looking for
Most people know that when they go to buy a car or a house the application process for a loan will require first name, last name, date-of-birth, address, and Social Security Number. While healthcare entities don’t often require full SSN, there is also discrepancy as to what fields are required versus optional depending on what doctor or pharmacy or specialist you see. So how do you match a patient across entities with different data elements provided? Due to the commonalities in name, it isn’t enough to rely on a first name and last name exact match to constitute a match. Jane Smith 01-01-01 with Jane Smith 123 Tree Street. Healthcare entities need to standardize the information they collect and use to ensure high quality matching and prevention of duplicates or overlapping records.
Further, there should be no such thing as “optional” fields in your forms; rather, they should define specifically what data you require, whether collected or omitted. Think of the system as a self-protecting mechanism that actively insists on consistency before allowing registration or check-in to be completed, and that there are core data that you want to be able to rely on across your patients’ healthcare journeys.
Patients make this process a challenge, since they can unwittingly use a nickname or omit a middle name depending on their state of mind. A simple adjunct tool to improving your data integrity is to require two forms of identification at registration. Any time spent contending with this added work will pale when contrasted with the time (and cost) of dealing with the consequences of errors.
Format matters as much as content
Format is the next step of standardization that ensures an added degree of data quality and accuracy (though not perfect, it leaves less room for errors).
I am reminded of the differences in how data are formatted every time I visit Europe and see a date that lists the day before the month and year. To an American data collection system without an enforced format, this could lead to two different patient records getting linked together (an example would be the data “01-05-2007,” which could refer to one patient born January 5, 2007 and another born May 1, 2007). In fact, there are numerous seemingly minor format issues that can create inaccuracies or differences between patient files, such as use/non-use of a period at the end of an abbreviation or data entries that are too short to be searchable. Your system should have format requirements and safeguards (i.e. a calendar prompt pulls up upon clicking into the date-of-birth field), so an entry process can’t proceed unless those requirements have been met.
This has relevance for the use of notes or comments fields, which are finding great utility in clinical settings for the capture of data like photographs (or being shared by patients for inclusion in their files). Images aren’t searchable so there must be field(s) and format requirements for describing imagery. A picture might be worth a thousand words but if it’s invisible to search, the data are useless.
Check, match, and then repeat
There are any number of touch points in a typical healthcare journey at which a patient’s identity and records are checked and usually amended, each of which present an opportunity for the perpetuation or addition of errors. Determinant fields and format can help restrict these impacts, as can the empowerment of staff to recognize and address them. For instance, a test or other progress on a care journey might help make duplicate patient files appear far more similar or, conversely, better establish two distinct identities.
We can do it
Providers don’t have to wait for (or fund) massive upgrades in their records system but can implement step-by-step changes that move them closer to data standardization. Third-party services with established experience in delivering such improvements are ready for use (so looking outside your four-walls might help make things even easier). This includes using tools to rectify conflicts and other errors that crop up in data forms.
Further, industry action is possible apart from government intervention, as the new UPIs for electronic prescriptions will go into effect next year thanks to a collaborative process that started four years ago. Another avenue of work to consider would be similarly collaborating across hospitals and geographies to establish voluntary data standards that can benefit all.
Ultimately, the key to advancing data standards is to just get moving.
About the Author
Karly Rowe is responsible for the Patient Access, Identity, and Care Management product portfolios at Experian Health. With a diverse background across credit, retail, and healthcare, Karly is responsible for finding new ways to leverage Experian’s data and analytical capabilities to develop new, innovative solutions for the healthcare industry. Karly holds a Masters of Business Administration from Arizona State University and a Bachelor’s degree in Marketing Management and Retail Management from Syracuse University. She resides in Scottsdale, Arizona with her husband and two sons.
Twitter: @Experian_Health
