* Investigative Techniques and Data Analysis
Expert-defined terms from the Professional Certificate in Healthcare Fraud Investigation course at HealthCareStudies (An LSPM brand). Free to read, free to share, paired with a globally recognised certification pathway.
Actuarial analysis #
A branch of mathematics that uses statistical methods to estimate the probability of certain events happening, such as the likelihood of fraud occurring in a healthcare setting. This type of analysis can be used to identify trends and patterns in healthcare data that may indicate fraudulent activity.
Benford's Law #
A principle that states that in many naturally occurring datasets, the leading digit is more likely to be a small number. For example, in a dataset of healthcare claims, the leading digit is more likely to be 1 than 9. Deviations from this pattern can indicate fraudulent activity.
Computer #
assisted coding (CAC): The use of software to automatically assign codes to medical procedures and diagnoses in healthcare claims. This can help to identify errors and inconsistencies in coding that may indicate fraud.
Data analytics #
The process of examining and interpreting data in order to draw conclusions and make informed decisions. In the context of healthcare fraud investigation, data analytics can be used to identify patterns and trends in healthcare data that may indicate fraudulent activity.
Data mining #
The process of automatically discovering patterns and trends in large datasets. In the context of healthcare fraud investigation, data mining can be used to identify suspicious patterns in healthcare data that may indicate fraud.
Data visualization #
The representation of data in a graphical or pictorial format. Data visualization can be used to help identify trends and patterns in healthcare data that may indicate fraudulent activity.
Digital forensics #
The process of collecting, analyzing, and preserving electronic evidence in order to investigate crimes or other legal matters. In the context of healthcare fraud investigation, digital forensics may be used to recover and analyze electronic records related to healthcare claims.
Electronic health record (EHR) #
A digital version of a patient's medical history that is stored and maintained electronically. EHRs can be a valuable source of information for healthcare fraud investigators.
Fraud detection #
The process of identifying and preventing fraudulent activity. In the context of healthcare, fraud detection may involve analyzing healthcare data for signs of fraud, such as unusual billing patterns or claims for services that were not provided.
Fraud investigation #
The process of gathering evidence and interviewing witnesses in order to determine whether fraud has occurred and, if so, who is responsible. In the context of healthcare, fraud investigation may involve analyzing healthcare data, medical records, and financial records.
Healthcare claims data #
Data related to healthcare claims, including information about the patient, the provider, the services provided, and the payment amount. Healthcare claims data can be a valuable source of information for healthcare fraud investigators.
Healthcare fraud #
The intentional submission of false or misleading information in order to obtain payment from a healthcare program or insurance company. Healthcare fraud can take many forms, including billing for services not provided, upcoding, and unbundling.
Healthcare program integrity #
The overall integrity of healthcare programs, including efforts to prevent, detect, and respond to fraud, waste, and abuse.
Machine learning #
A type of artificial intelligence that allows computers to learn and improve their performance on a task without being explicitly programmed. In the context of healthcare fraud investigation, machine learning algorithms can be trained to identify patterns in healthcare data that may indicate fraud.
Predictive modeling #
The use of statistical techniques to predict future outcomes based on historical data. In the context of healthcare fraud investigation, predictive modeling can be used to identify claims that are at high risk for fraud.
Upcoding #
The practice of billing for a more expensive service than was actually provided. Upcoding is a form of healthcare fraud.
Unbundling #
The practice of billing for multiple services separately, rather than as a single bundled service. Unbundling is a form of healthcare fraud.
Whistleblower #
A person who reports suspected wrongdoing, such as healthcare fraud, to the authorities. Whistleblowers can play an important role in identifying and preventing healthcare fraud.