Eliminating patient matching in your EHR

The source of the problem Accurate patient matching is foundational to your EHR but all EHRs struggle with patient matching. Accurate patient matching is 10x more challenging today due to an explosion of data and data sources. Mergers/acquisitions within hospital systems, patient engagements, advanced analytics and information exchanges have all added to the patient matching challenges. EHRs’ patient matching woes are evidenced by rising duplicate rates. In 2008, an AHIMA study identified average duplicate record rates of between 8-12%. Black Book Market Research Survey shows that in 2018, this number has reached 18%.  By 2020, these rates are expected to rise to 20%. This is in sharp contrast to the ONC mandate of a .5% match rate. The cost of the problem No matter what EHR system you use, inaccurate patient matching has huge costs. According to the 2018, Mid-Year EHR Consumer Satisfaction Survey, Black Book Market Research, every duplicate record costs health systems $1,950 per inpatient stay, costs health systems $800 per Emergency Room visit and increases duplicate tests by 30%. The 2016, National Patient Misidentification Report by the Ponemon Institute reported that inaccurate patient matching causes $17.4M in denied claims annually for the average hospital. Traditional fixes Healthcare systems spend a lot of time “fixing” duplicate and inaccurate patient records.  Traditionally, this is done by data matching. Data matching can be either deterministic or probabilistic. In probabilistic, or referential matching, several field values from a variety of sources are compared between two records and each field is assigned a weight that indicates how closely the two-field values match. The sum of the individual field weights indicates the likelihood of a match between two records. In deterministic matching, a unique identifier for each record [...]

These Are 4 Common Causes of Patient Identity Errors to Watch Out For

Last year, the American Health Information Management Association (AHIMA) found that, on average, 10 percent of a health organization’s patient records are duplicates. Why is this statistic so disturbing? It means your organization is setting itself up to lose revenue. With any percentage of duplicates, the number of patient records in your system will not match the actual number of patients you serve. This skews patient population health metrics and impacts care plan compliance and overall patient outcomes. Not only does it cause revenue problems, but the Office of the National Coordinator for Health Information Technology (ONC) includes objectives for reducing duplicate records in its nationwide interoperability roadmap. This year, duplicate record rates are to be reduced from 2 percent, to 0.5 percent by 2020, and less than 0.1 percent by 2024. A John’s Hopkins study titled, “Implementing and Sustaining Improvement in Healthcare” found that 92% of patient identity errors occur at the time of the registration process. The registration process is understandably complex and requires great attention to detail. However, a busy waiting room, unfamiliar temporary staff, or inadequate workflow procedures can result in duplicate records or complete patient misidentification. Common Sources of Patient Identity Errors 1. Process flaws within an organization Many health organizations simply ask for verbal verification of name and birthday or photo identification, resources which can easily be obtained. Process flaws that allow the creation of duplicate records also pose risks to patient health. Relying on this misinformation from staff makes patient identity susceptible to human error, often enabling misidentification and medical identity theft. 2. Limited training on the importance of patient identification for new or temporary staff The John’s Hopkins study determined that inadequate emphasis was placed on the process of patient [...]

By | 2017-10-25T18:16:34+00:00 Tuesday, February 13, 2018|Categories: Uncategorized|Tags: , , |0 Comments

25 Seconds Can Save Hospitals $30 Million with Patient ID Systems

Did you know that the average hospital system has a 10% duplicate error rate and it costs about $100 to correct each error? If your healthcare facility has 500,000 registrations each year, that’s 50,000 errors and you spend about $5M correcting those errors. Did you know that the average hospital loses $17M in billing errors every year, primarily due to patient identity errors? In the Ponemon Institute’s 2016 survey, hospitals stated that an average of 35%of all denied claims were a result of inaccurate patient identification. This represented an estimated value of over $17M per year per hospital. Did you know that patient mis-identification also contributes to lost productivity for clinicians? The Ponemon Institute’s 2016 survey also stated that the average clinician wastes almost 30 minutes per shift due to patient mis-identification. This misidentification costs the average healthcare organization $900,000 per year in lost productivity. Did you know that there are over 2 million incidences of medical identity fraud every year? With 5,627 hospitals in the US, that is 355 potential incidents of medical identity fraud in each hospital. The average cost of medical identity fraud is around $13,500 per incident, which calculates to around $4.8M per year per hospital. With modern absolute patient ID techniques, there is no reason why medical identity theft still exists. Did you know that spending 25 seconds with a biometric patient id system can save you almost $30M a year? 25 seconds is all it takes for a biometric patient id system to accurately identify a registered patient, preventing duplicate registrations and the need to correct them. Patient ID systems play a critical role in helping providers reduce billing errors and collection problems associated with patient identity mistakes. Absolute patient id systems can save your healthcare organization millions [...]

These Are 4 Common Patient Identity Errors to Watch Out For

Last year, the American Health Information Management Association (AHIMA) found that, on average, 10 percent of a health organization’s patient records are duplicates. Why is this statistic so disturbing? It means your organization is setting itself up to lose revenue. With any percentage of duplicates, the number of patient records in your system will not match the actual number of patients you serve. This skews patient population health metrics and impacts care plan compliance and overall patient outcomes. Not only does it cause revenue problems, but the Office of the National Coordinator for Health Information Technology (ONC) includes objectives for reducing duplicate records in its nationwide interoperability roadmap. This year, duplicate record rates are to be reduced from 2 percent, to 0.5 percent by 2020, and less than 0.1 percent by 2024. A John’s Hopkins study titled, “Implementing and Sustaining Improvement in Healthcare” found that 92% of patient identity errors occur at the time of the registration process. The registration process is understandably complex and requires great attention to detail. However, a busy waiting room, unfamiliar temporary staff, or inadequate workflow procedures can result in duplicate records or complete patient misidentification. Common Sources of Patient Identity Errors 1. Process flaws within an organization Many health organizations simply ask for verbal verification of name and birthday or photo identification, resources which can easily be obtained. Process flaws that allow the creation of duplicate records also pose risks to patient health. Relying on this misinformation from staff makes patient identity susceptible to human error, often enabling misidentification and medical identity theft. 2. Limited training on the importance of patient identification for new or temporary staff The John’s Hopkins study determined that inadequate emphasis was placed on the process of patient [...]

By | 2017-10-25T17:47:15+00:00 Tuesday, May 2, 2017|Categories: Absolute Identity|Tags: |0 Comments