The Impact of Duplicate Patient Records on Revenue

Understanding wide-ranging implications adds urgency to developing solutions.

Duplicate patient records in your hospital or health system can have negative impacts on revenues. Duplicative and incomplete patient records have long caused problems in the traditional fee-for-service revenue cycle, and they also can undermine performance measures that drive revenues under value-based payment models.

Understanding the wide-ranging impacts of this data-quality problem adds urgency to projects focused on cleaning up existing problems with duplicates and provides a financial rationale for implementing systems that minimize future problems.

Patient Accounting Inefficiencies

Duplicate or incomplete patient records can cause hospitals to inadvertently bill payers or patients for more than or less than the correct amount, leading to direct revenue loss. Incorrect billing results in wasted time and resources, lengthening of days in accounts receivable (A/R), and an increase in bad debt write-offs. When insurance information is available on one episode of care, but not appropriately attached to another for the same patient, the patient guarantor may be erroneously billed for the full balance, or an incomplete claim may be submitted to insurance. These are not only potential missed payment opportunities, but these occurrences could also affect patient satisfaction scores.

Similarly, incomplete information will lead to delays because health plans must ask for more information to process claims, or claims may be denied because they are not timely. Without complete views of patients and their billing records, it can take a significant amount of time to gather information to send to payers. When inefficient back-and-forth communications are the only method to gather fragmented billing information, there are risks to the bottom line in terms of wasted time, sluggish cash realization, and loss of expected A/R.

Impacts on Metrics

There are numerous ways in which duplicate or incomplete patient records can undermine hospitals’ quality efforts and metrics that directly drive the payment formulas for Medicare, Medicaid, and other private payers under various value-based payment methods.

Population health. Many of the metrics related to payment are process and outcomes measures that are part of care plans intended to ensure all members of a population at risk for a specific condition are getting the right care at the right time. Incomplete patient records can lead to providers failing to recognize at-risk patients and missing opportunities to proactively schedule screenings or treatments. For example, if records in one location’s system identify a patient as diabetic, but that diagnosis is missing from another database used by the team doing outreach to patients with chronic care needs, a screening test may be missed, or diet counseling may be overlooked. Effectiveness of the population health system declines, resulting in low-quality metrics and impediments to maximizing revenues.

Clinical quality. Incomplete information due to duplicate or partial records can contribute to clinical errors and adverse events. For example, providers without access to a single, complete patient record may not know what medications their patients are taking. This can lead to duplicate medications prescribed, as well as potential adverse effects from dangerous drug interactions or allergies that may have been documented in one system but are missing from others.

Another heightened risk is errors of omission, where a drug that would likely have benefitted a patient is not prescribed because the full condition of the patient is not accessible to the ordering clinician. If the occurrence rates get too high, these types of adverse events may be counted as hospital-acquired conditions and are part of the basket of measures that can drive down Medicare payments and perhaps payment under other types of value-based models, such as accountable care organizations, gainsharing, or alternative payment models.

Patient satisfaction. As we have seen, poor data quality in patient records can lead to billing errors and confusion around clinical processes. These problems will often lead to frustration and anger on the part of patients and their families. Such negative experiences will inevitably be reflected in poor scores on patient satisfaction surveys.

Patient satisfaction scores affect the formula for Medicare payments and many private payers use similar metrics. Furthermore, negative reviews on social media sites such as Yelp, Facebook, and Healthgrades can result in bad public relations and the loss of future revenue.

In addition to undermining performance on process, quality, and satisfaction measures, poor data quality makes it harder for hospitals to properly measure performance and focus improvement efforts. With bad data, health systems cannot accurately calculate quality measures in the same ways that their payers can. With miscalculated quality measures, providers may develop a false sense of their progress; conversely, an erroneous report showing poor results may lead to wasted efforts to fix nonexistent or low-priority problems.

Technology Considerations

Duplicate and incomplete records can hurt revenues under both fee-for-service and value-based payment, and these issues are intensifying as providers with disparate systems merge. To improve performance on traditional and emerging revenue cycle metrics, revenue cycle leaders should consider technology that improves data quality.

For example, enterprise master patient indexes (EMPIs) allow hospitals and health systems to identify and match patient records stored across multiple IT systems to prevent duplicate data and ensure accurate patient records. Next-generation EMPI solutions use patient matching algorithms to deliver the following resources:

• Access to accurate patient records from multiple IT systems
• A reduction in duplicate data and manual data governance and cleansing
• Self-service patient portals to support patient-driven care
• A common data backbone for patient analytics programs

Technology solutions that integrate patient data from all clinical, operational, and financial systems can create a unified view of patient records that helps clinicians and operations staff perform at their best. At the same time, an improved patient experience will raise satisfaction and engagement.

Gordon Cooper is founder and CEO, VisionWare.

Christie Scanlon is healthcare cost consultant, Scanlon Enterprises, LLC, and is a member of HFMA’s Tennessee Chapter.