Abstract: To automatically model oncology treatment severity levels for a particular patient, a plurality of independently generated and potentially inconsistent observation data records are received for a patient. A condition-specific plurality of observation data records each having a common cancer type identifier are selected, and those condition-specific observation records are filtered to potentially eliminate one or more observation data records failing to satisfy one or more preliminary filter criteria. A specific pre-processing process for the remaining observation data records is executed to generate one or more output data records having at least one shared identifier, and the output data records are provided as model input to a machine-learning based severity model to generate a severity score for the patient.

Abstract: To enable automated processing of certain observation data by machine-learning based models, as well as to ensure those machine-learning based models are trained utilizing reliable and consistent data, independently generated observation data records each comprising biomarker mutation indicators, are utilized to generate a model input data set by applying biomarker mutation indicator-based filters, including intra-date filters and inter-date filters to identify and rectify observation data records that do not satisfy applicable biomarker mutation indicators. By identifying and rectifying the observation data records that do not satisfy applicable biomarker mutation indicators, a clean, model input data set is generated that is then utilized to generate a severity score for the patient.

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for each record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Once an anchor procedure is identified, claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG). First, the date of service for each claim record is identified to determine whether the claim record falls within time window. The claim records falling within the window then are assessed to determine whether each claim record is sufficiently related to the anchor procedure (for example, by determining whether the diagnostic, procedure, or episode treatment group coding of each claim record is associated with the anchor procedure).

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis is based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG) using the date of service for each claim record and a level of relationship between the claim records and the anchor procedure. The requisite level of relationship between the claim records and the anchor procedure depends upon the position of the records within the time window. Claim records having the requisite relationship level associated with the portion of the time window in which they fall are included in the PEG.

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for ach record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG) using the date of service for each claim record and a level of relationship between the claim records and the anchor procedure. The requisite level of relationship between the claim records and the anchor procedure depends upon the position of the records within the time window. Claim records having the requisite relationship level associated with the portion of the time window in which they fall are included in the PEG.

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for each record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Once an anchor procedure is identified, claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG). First, the date of service for each claim record is identified to determine whether the claim record falls within time window. The claim records falling within the window then are assessed to determine whether each claim record is sufficiently related to the anchor procedure (for example, by determining whether the diagnostic, procedure, or episode treatment group coding of each claim record is associated with the anchor procedure).

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for each record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Once an anchor procedure is identified, claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG). First, the date of service for each claim record is identified to determine whether the claim record falls within time window. The claim records falling within the window then are assessed to determine whether each claim record is sufficiently related to the anchor procedure (for example, by determining whether the diagnostic, procedure, or episode treatment group coding of each claim record is associated with the anchor procedure).

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for each record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Once an anchor procedure is identified, claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG). First, the date of service for each claim record is identified to determine whether the claim record falls within time window. The claim records falling within the window then are assessed to determine whether each claim record is sufficiently related to the anchor procedure (for example, by determining whether the diagnostic, procedure, or episode treatment group coding of each claim record is associated with the anchor procedure).

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for each record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Once an anchor procedure is identified, claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG). First, the date of service for each claim record is identified to determine whether the claim record falls within time window. The claim records falling within the window then are assessed to determine whether each claim record is sufficiently related to the anchor procedure (for example, by determining whether the diagnostic, procedure, or episode treatment group coding of each claim record is associated with the anchor procedure).