Ever since the first Blue Cross health insurance plan was provided to Texas schoolteachers in 1929 for a monthly fee of $6, health insurance providers have formed the backbone of the American healthcare system.
Today, as that system faces ongoing scrutiny, health insurance providers are still at the heart of the action, striving to connect patients to the highest possible quality of care while navigating significant changes including rising costs, digital transformation, medical advances, customer expectations, and ever-present regulations. It's more important than ever for health insurance providers to simplify processes and increase efficiency — and the key to efficiency in modern healthcare lies in streamlining and managing the data at the core of operations.
In particular, home address data for patients and providers is a critical information point that can have ripple effects on efficiency throughout an organization. Addresses are important because they are often used to combine data from multiple sources. Address discrepancies create significant operational risks for health insurance providers — from inaccuracies in processing individual claims to organization-wide implications for data governance.
It doesn’t take much for an address to be wrong. It could be a missing unit number, a misspelled or abbreviated street name, or the wrong label (e.g., street vs. road). Even if an address isn’t technically incorrect, it can still cause problems in health data if it isn’t standardized.
The good news is that technology is making it easier for Health insurance providers to boost the accuracy of their address data. In this article, we’ll look at three key operational inefficiencies caused by inconsistent or incomplete address data to understand the crucial role of addresses in streamlining health plan operations.
Health Insurance providers need to send and receive patient data from providers, pharmacies, labs, and other facilities to coordinate patient care. One way they share this data is through a name, birthdate, and address. Patients provide their address to various providers and facilities, but they may write or enter it slightly differently at different times — for example, on a physical form at a doctor's office and in an online insurance application.
This type of human error can make it difficult to match patient data. When a health plan blends data from several sources to process and run reports, address discrepancies can cause duplicate patient records or result in data being attached to the wrong patient. In either case, an inaccurate address in one place can have a domino effect across data sources, such as sending a bill or a prescription to the wrong address or the wrong patient.
Clean address data, on the other hand, can help link records for a single patient — for example, if the patient's name is entered inconsistently as John or Johnathan, but the address and birthdate are the same. A system that can recognize and standardize addresses across data sources streamlines data blending and helps minimize errors on both the clinic side and the insurance side.
Patient address data is so critical that the U.S. Department of Health and Human Services and the Pew Charitable Trusts partnered to create standards for consistently formatting them, known as Project US@. According to HHS, “Among the many data elements that are used in patient matching, research has shown patient address to be one of the most sensitive to standardization and therefore impactful on patient matching, especially at scale.” As health IT teams implement these standards across the system, tools that can apply them to datasets are becoming increasingly valuable.
Address data is also an important element of provider directories, where incorrect provider addresses can hinder patients from finding care in their area. Provider directories are notoriously inaccurate, with one study finding that only 30% of patients using provider directories were able to successfully make an appointment with the provider they initially selected. When patients can’t find in-network care in their area, they can end up traveling long distances or paying out-of-network prices.
This is frustrating for patients and providers, but the impact goes even deeper. Inaccurate provider data can also cause treatment delays and higher costs. The problem is severe enough that some states are increasing oversight and penalties for health insurance providers that don’t comply with new standards for provider information accuracy.
Even when provider address information is correct, patient address information has to be accurate too. If a health plan doesn’t have a patient’s address exactly right, the directory may not display the right providers in their area, making it harder for them to get care — and potentially proving costly for the health plan provider to fix the mistake.
Health insurance providers also use provider address data in sales and marketing. For example, as part of a sales quote to a large employer, a health insurance provider might need to demonstrate that every covered employee would have a certain number of eligible healthcare providers within ten miles of their home. The more accurate the addresses in the provider directory, the more sophisticated these types of efforts can be.
One-third of denied claims result from inaccurate patient identification, including inaccurate and incomplete address data, according to market research company Black Book. The amount of time required to revisit appealed claims, identify problems, and track down new address information is a significant drain on a health insurance provider's operational resources and efficiency.
Denied claims have a financial impact on both patients and providers, and they also lead to delays in care that adversely affect patient health and future claims. Patients end up paying more than they expected and spending hours sorting out details of claims — and when patients find themselves paying physical and emotional costs in addition to financial costs, they’re more likely to start looking for other health insurance options.
Without clean address data, health IT teams struggle to manage patient data and provider data, and the extra manual work required to blend data and troubleshoot problems stunts operational efficiency.
Fortunately, today's technology makes it easier than ever to identify and correct incomplete or inaccurate address data. Address verification tools like Smarty can streamline processes by automating address validation. You can also prevent bad addresses from entering your system in the first place with autocomplete tools. With the right tools and processes in place, you can mitigate the operational risk caused by faulty address data and create a foundation of reliable health data for the future of your business.
Read the other articles in this series, The Silent Risks of Inaccurate Address Data for HealthPlans: