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The new and improved way to match patient data

Published: June 25, 2019 by Experian Health

Since the Health Insurance Portability and Accountability Act (HIPAA) heralded the mainstreaming of electronic medical records over two decades ago, healthcare organizations have been slowly making the shift from paper-based patient information to online records. Digital records are more efficient, no doubt, but the transition hasn’t been smooth. There are challenges and risks in managing and protecting patient data online.

With patient information flowing through multiple systems, devices and facilities, it can be extremely difficult to guarantee the accuracy and freshness of the data. Patients move to a new house, change their name or switch doctors. They may go for years without any interaction with the healthcare system. How can hospitals and other providers be sure that the records they hold are correct for each patient who walks through the door?

Incorrect patient matching is a major source of revenue leakage for many providers, with around a third of claims denied on the basis of inaccurate patient identification. When it costs $25 to rework a claim and around $1,000 for each mismatched pair of records, that’s a lot of lost revenue. In 2017, the total lost revenue for the average hospital was around $1.5 million.

Clearly this a financial headache for providers, but it’s also a major patient safety issue. How can patients get the right treatment at the right time, if their physician is looking at an out-of-date record, or worse, the record of a completely different patient? Good health outcomes rely on good data.

Matching patient records: the old way

Traditionally, healthcare providers might use a patient matching engine (an enterprise master patient index or EMPI) to identify patients and match up their records from different parts of the health system. These work by checking demographic data to compare the details on each record and combine the ones that are likely to refer to the same person. This can usually handle a simple change of name or address, but for anything more complex, it’ll likely hit a roadblock.

EMPIs are limited by their reliance on a single data source – the data that’s visible to them in patient rosters. So what happens if that demographic data is wrong? What if there are typos or spelling mistakes? How do you differentiate between a misspelled name and a completely different person?

Any errors in the data are inherited by the matched record, and as a result, EMPIs are often plagued by gaps, mistakes or outdated patient information.

A new solution for patient matching: Universal Patient Identifiers

A better solution is to combine the information in patient rosters with comprehensive reference and demographic data held by data companies such as Experian, to create a more complete picture of each patient. A universal patient identifier (UPI) can be assigned to each patient and stored in a master identity index, so that whenever and wherever they pop up in the health system, the referential matching technology knows exactly which data is theirs.

When health systems implement UPIs, you can connect disparate data sets and have confidence in the fact that every new data point will be instantly checked and updated. You’ll know that the Maria currently seeking diabetes treatment in Austin is the same Maria who was treated for asthma in Houston last year. You’ll know that Thomas sometimes goes by Tom. You’re far less likely to have a patient turn up at the pharmacist and be given a prescription that belongs to another patient with the same name. It’s more efficient for clinical and admin staff, and copes more efficiently with patient mobility.

Highlighting the importance of reliable patient matching technology, Karly Rowe, Vice President of Identity Management and Fraud Solutions at Experian Health says:

“When you send us your patient demographic information, we will provide you with the insights and identifiers that you need to better manage your patient identities. The benefits are improved patient safety, better care coordination, better patient engagement, and overall driving better efficiencies and financial benefits.”

Not all reference data is created equal

Of course, referential matching is only as good as the data it’s trying to match. Some vendors repurpose data matched for credit checks, using patients’ Social Security Numbers. But this data can be equally vulnerable to inaccuracies.

Experian offers access to the industry’s broadest and most trustworthy datasets and provides ongoing monitoring to constantly check the accuracy of that data. Our healthcare-specific algorithm is finely tuned to meet the data needs of the healthcare industry, without any risky repurposing.

With this in mind, ValleyCare Health System in California used Experian Health’s Identity Verification solution to give patient access staff the freshest demographic information, including more accurate names and addresses, leading to a 90% reduction in undelivered mail.

Janine Edwards, Patient Access Services Quality Assurance and Training Coordinator at ValleyCare told us:

“Since implementing Identity Verification, we’ve improved the accuracy of patient demographic information throughout ValleyCare Health System. More valid data up-front means better revenue cycle results on the backend.”

The entire health ecosystem relies on knowing who patients truly are. With the highest quality reference data and powerful unique patient identifiers, Experian goes beyond the limits of conventional methods to give providers the highest confidence in matching and managing patient identities.

To start resolving your patient identities today, contact us to see how many duplicate records we can fix.

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Manage the claims adjudication process with greater ease to save time and money. Use these strategies to help reduce claim denials.

Published: May 16, 2024 by Experian Health

When it comes to medical coding and billing, accuracy is everything. Even the smallest error can result in a claim being bounced back by the payer, causing delays and missed revenue opportunities. Coding requirements change frequently, and with denials totaling billions of dollars per year, providers can’t afford to risk under- or over-coding or relying on outdated codes. Automation and software-driven solutions can uncomplicate the complex world of medical coding. Getting claims right the first time accelerates the adjudication process, leading to faster and higher reimbursements. Providers can make more reliable financial forecasts, avoid losing time reworking rejected claims, and give patients greater clarity about what they’ll owe. For this reason, providers should brush up on medical coding and billing best practices to improve claims management and maximize reimbursements. Here are 7 areas to focus on: 1. Stay up-to-date with coding changes Medical codes convert information about the patient’s healthcare encounter into an electronic format that payers use to adjudicate claims for reimbursement. If a claim includes outdated, incorrect or missing codes, then it will be denied. The most common medical coding systems include: International Classification of Disease 10th edition (ICD-10) codes: these codes denote the patient’s diagnosis or condition. The 11th version was published in January 2022, and while the implementation timeline in the US remains unclear, providers will need to be ready to adapt. Current Procedural Terminology (CPT) codes: Where ICD codes describe the patient’s symptoms, CPT codes record their treatment. If there’s a discrepancy between diagnosis and treatment, the claim is likely to be denied. Healthcare Common Procedure Coding System (HCPCS) codes: the Centers for Medicare and Medicaid Services (CMS) use these to apply CPT codes to procedures, services, products and equipment offered to Medicaid and Medicare patients and those covered by private insurance. These codes are constantly being revised and are often recycled, so coders must pay close attention to avoid errors. National Drug Code (NDC): claims need to include NDC codes when the patient is taking prescribed or over-the-counter medications. The NDC directory is updated daily. Diagnosis-Related Group (DRG) codes: these combine ICD and CPT codes to determine the final amount that a hospital can be reimbursed. CMS assigns annually calculated weightings to DRGs based on severity and length of illness, treatment trends and other factors. There are also multiple coding directories for different specialties, such as dental care, mental health and patients with disabilities. With hundreds of thousands of constantly-changing codable terms to consider, medical coders face a daunting task. In the past, coders would rely on manual coding directories to find the right codes, but today, most use digital encoders and digital coding libraries to generate electronic codes. For example, Experian Health’s claims management software integrates government and payer edits so that no changes to coding requirements are missed. Each patient encounter can be processed in real time and incorrect codes can be flagged before the claim is submitted. 2. Automate the claims management process to increase medical billing and coding accuracy Manually matching each patient encounter to a specific set of codes is time-consuming and vulnerable to errors. Software programs improve the process by analyzing unstructured clinical charts and notes to draw out information relevant to the claim. They can cross-reference multiple coding directories in an instant to identify the correct code. They also compile data in standardized, interoperable formats so information can be exchanged between coding and billing teams, clearinghouse staff and payer systems with ease. While some of the output generated by machine learning systems still needs to be checked by human eyes, automated solutions drastically reduce the burden on staff and ensure greater accuracy. With automated claims management, medical coding and billing teams can optimize their workflows, submit cleaner claims, and get insights into the root causes of denials. Case study: see how Summit Medical Group Oregon – Bend Memorial Clinic used automated claims management technology to achieve a primary clean claims rate of 92%. 3. Eliminate workflow inefficiencies to save time According to the Council for Affordable Quality Healthcare (CAQH), automation could save more than an hour of staff time for every three claim status checks. Automation frees up staff to focus on the highest priority tasks that require a human touch. Fewer errors mean less time spent on reworking denied claims. And if claims are processed more quickly, this means that they reach the payer adjudication stage sooner which ultimately will result in faster payments. The medical coding and billing process takes anywhere from a week to a few months, so every hour saved makes a difference. To this end, Enhanced Claim Status monitors how claims are progressing through the claims adjudication process, reducing the amount of time staff need to spend interacting with payers. It eliminates manual follow-up and allows teams to address pending, returned, denied and zero-pay transactions before the Electronic Remittance Advice and Explanation of Benefits are processed. Worklists are generated based on actionable data so staff can work more productively, and claims get settled sooner. 4. Customize claims edits to your specifications One way to drive up medical coding accuracy is to use customized claims edits. Some claims management software solutions only apply updates using universal claim edits or using groups of edits. This doesn’t work for large medical groups that need to cover multiple combinations of payer, specialty and geographical edits. Since no two payer policies are the same, claims edits would need to be checked manually to make sure nothing has been missed. Experian Health’s claims management software solves this by incorporating government and commercial edits alongside client-specific customized edits. Providers can keep pace with changes and capture the requirements of all reimbursement policies that are relevant to a particular claim. For example, ClaimSource runs front-end claims editing to coordinate federal, state and commercial payer edits together with customized provider edits to avoid coding errors. Similarly, ClaimScrubber automatically reviews and adjusts claims, helping medical groups streamline claims submissions. 5. Upgrade record-keeping technology to maintain medical billing and coding accuracy If patient records are peppered with typos and outdated contact information, then it’s highly likely that errors will be inherited on claims forms. A fifth of patients have spotted errors in their health records, including incorrect details about diagnoses, medications and test results. Preventing these errors is key to maintaining medical billing and coding accuracy. Interoperable electronic patient records protect against inaccuracies by creating a single, complete record for each patient. With a tool such as Universal Identity Manager, patient data is matched against multiple data sources to verify that the record is complete and accurate. Staff can have confidence that all information held on a patient will be taken into account when their medical encounters are coded, and avoid coding discrepancies that can occur when a patient’s treatment doesn’t seem to match their diagnosis. 6. Double-check claims before submitting  Running a line-by-line review of each claim before it’s submitted means errors can be found and fixed before they result in financial losses. This would be a painstaking task to do by hand, but with tools such as ClaimSource and ClaimScrubber, hospitals and medical groups can audit claims automatically to check for coding discrepancies or missing patient information. A streamlined claims cycle benefits payers and patients too. Payers can adjudicate accurately coded claims more quickly without pushing them into a queue for manual review, and patients get earlier clarity about how much they’ll owe. 7. Audit the claims management process to spot medical coding inaccuracies Finally, it makes sense to undertake regular audits of the medical coding and billing procedures to weed out any recurring issues. While a coding audit will focus on coding accuracy and compliance, a billing audit can investigate the systems and processes involved in everything from patient eligibility verification to patient collections. This helps uncover recurring issues with under- and over-coding, use of redundant and retired codes, non-compliance and poor documentation. Again, maintaining robust, quality data and records will make this process easier. Partnering with a single, trusted vendor to deliver an end-to-end claims management solution can help achieve this. Find out more about how Experian Health’s automated claims management solutions can help healthcare organizations maintain medical billing and coding accuracy, drive down denials and create a more predictable revenue cycle.

Published: October 6, 2022 by Experian Health

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