Abstract: A system for automated classification of an image of an electronic document such as a facsimile document. The image is converted to a textual representation, and at least some of the terms in the textual representation may be associated with one or more predefined classification types, thereby enabling the document to be classified, and for multi-page documents, determining boundaries used to split the document into sections. The development of associations between terms and classification types may result from providing, to the system, a training set of manually-classified documents. A training module analyzes the training set to calculate probabilities that particular terms may appear in documents of a particular classification type. Probabilities established during training are used during automated document processing to assign a classification type to the document. A confidence score associated with the assigned classification type provides a metric for assessing the accuracy of the automated process.

Abstract: Embodiments of methods and systems for predicting provider negotiated rates are disclosed. One method includes obtaining claims data and provider data, grouping the claims data into priceable units, computing prices for each of the priceable units based on the claims data and the provider data, and estimating provider negotiated rates based on the priceable units and the computed prices for the priceable units.

Abstract: Embodiments of methods and systems for predicting provider negotiated rates are disclosed. One method includes obtaining claims data and provider data, grouping the claims data into priceable units, computing prices for each of the priceable units based on the claims data and the provider data, and estimating provider negotiated rates based on the priceable units and the computed prices for the priceable units.

Abstract: Embodiments of computer-methods and computer systems for predicting out-of-pocket expense for a patient are disclosed. One computer-method includes obtaining claims data and provider data and grouping the claims data into priceable units. A server computes prices for each of the priceable units based on the claims data and the provider data. The priceable units are collected into bundled services as required for predicting the out-of-pocket expense of an episode. Attributes of a health plan of the patient are applied, and an out-of-pocket calculator predicts the out-of-pocket expense based on the collected priceable units and the computed prices for the collected priceable units. The out-of-pocket expense is communicated to patient through a network.

Abstract: A system for automated classification of an image of an electronic document such as a facsimile document. The image is converted to a textual representation, and at least some of the terms in the textual representation may be associated with one or more predefined classification types, thereby enabling the document to be classified, and for multi-page documents, determining boundaries used to split the document into sections. The development of associations between terms and classification types may result from providing, to the system, a training set of manually-classified documents. A training module analyzes the training set to calculate probabilities that particular terms may appear in documents of a particular classification type. Probabilities established during training are used during automated document processing to assign a classification type to the document. A confidence score associated with the assigned classification type provides a metric for assessing the accuracy of the automated process.

Abstract: A medical practice management system can be used to manage a medical practice. A medical practice management server communicates with a medical practice client user interface over a first network and communicates with a payor server over a second network. The medical practice management server receives information associated with a visit by a patient to the medical practice. Prior to using the information to create a claim, the medical practice management server automatically and repeatedly interacts with the information to ensure correct information by either applying one or more rules to the information or by performing one or more transactions with the payor server. The medical practice management server performs a correcting action in response to finding an error in the information and subsequently uses the information to create an insurance claim.

Abstract: Incorporating new technology into an existing medical practice is often difficult. Documents associated with a patient, for example, a patient's medical charts, are typically provided physically, i.e., as “hard copies,” when a patient is being serviced by multiple health care providers Disclosed are means for electronically annotating an image associated with a patient workflow. In one implementation, there is a method that includes receiving an image via a communications network, presenting the image to a user, and capturing an annotation made to the image by the user. The annotations and the image to a medical practice management server via the communications network and the annotated image is stored as part of a patient medical record.

Abstract: Automating medical practice workflow and billing presents difficulties in many aspects, especially in interacting with the workflow, other healthcare providers, and within the constraints of payor requirements. Disclosed are methods, systems, software and means for automatically providing additional documentation to reconcile a billing claim. In one implementation, there is a computerized method for automatically providing additional documentation to reconcile a billing claim. The method, typically executed in software, includes providing a billing claim based on a patient's workflow, the billing claim typically associated with an a payor such as an insurance provider. The method also involves automatically identifying a document associated with the billing claim based on the patient's workflow. Typically the claim is submitted to the payor and the document is sent to the payor as well, the communications with the payor occurring over a communications network.

Abstract: Incorporating new technology into an existing medical practice is often difficult. Documents associated with a patient, for example, a patient's medical charts, are typically provided physically, i.e., as “hard copies,” when a patient is being serviced by multiple health care providers Disclosed are means for electronically annotating an image associated with a patient workflow. In one implementation, there is a method that includes receiving an image via a communications network, presenting the image to a user, and capturing an annotation made to the image by the user. The annotations and the image to a medical practice management server via the communications network and the annotated image is stored as part of a patient medical record.

Abstract: A medical practice management system can be used to manage a medical practice. A medical practice management server communicates with a medical practice client user interface over a first network and communicates with a payor server over a second network. The medical practice management server receives information associated with a visit by a patient to the medical practice. Prior to using the information to create a claim, the medical practice management server automatically and repeatedly interacts with the information to ensure correct information by either applying one or more rules to the information or by performing one or more transactions with the payor server. The medical practice management server performs a correcting action in response to finding an error in the information and subsequently uses the information to create an insurance claim.