Which are valid adverse event reports? 💡 ✏️ The minimum dataset required to consider information as a reportable AE is indeed minimal, namely (1) an identifiable patient, (2) an identifiable reporter, (3) product exposure, and (4) an event. However, in addition to direct data collection, AEs can be detected through retrospective analysis of a population database, where direct patient or health care provider contact does not occur. Patient interactions include clinical interactions and data collection by phone, Internet, or other means; perusal of electronic medical records or insurance claims data would not be considered direct patient interaction. Reporting is rarely required for individual AEs observed in aggregate population data, since there is no direct patient interaction where an association might be suggested or inferred. Nevertheless, if aggregate or epidemiologic analyses suggest that an AE is associated with exposure to a drug or medical product, it is desirable that the minimum dataset information be forwarded to the manufacturer of the product, who will determine any need for, and timing of, reporting of study results to the relevant regulatory authorities.
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BEHIND-THE-SCENES AUDITS OFTEN HIDE CAUSE OF TEST CLAIM DENIALS PRIVATE PAYER AUDITS OF LAB TEST CLAIMS ARE HAPPENING MORE FREQUENTLY. This is particularly true for molecular and genetic test claims. It is one reason why your lab may see the regular flow of reimbursement payments from a specific health plan suddenly stop without warning. But there is another reason why a private payer may abruptly stop paying a lab company’s test claims. It’s because the payer believes the lab is on a federal government watch list. I know of several lab companies that – after payments for their test claims had ceased – discovered that one of their important payers believed they were on a federal government watch list. (See sidebar below for details.) Payers conduct claims audits behind the scenes and labs are unaware that their test claims are being audited. In the most common scenario, either the payer’s auditing department or an outside auditing service takes a small sampling of claims and runs them through an algorithm. Thepayer then extrapolates the data into a prediction of all claims filed by that lab. If the audit turns up something amiss, the payer will... Read The Dark Report article at https://hubs.ly/Q02GNzmj0 Not already a subscriber? Sign up for a FREE 14-Day Trial at https://hubs.ly/Q02GNFSM0 Need A Group Membership? Company Discounts are Available! Get more information now at https://hubs.ly/Q02GNzCc0
Behind-the-Scenes Audits Often Hide Cause of Test Claim Denials
https://www.darkintelligencegroup.com
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The Regulatory Strategist Toolbox: Clinical Endpoint Analysis Tools
raps.org
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