Selectively redeemable bundled services recommender systems and methods
US12125087B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 26, 2022 |
| Grant date | Oct 22, 2024 |
| Priority date | — |
| Expiry date | Apr 17, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H20/00
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
An exemplary healthcare services recommender implementation may be configured to recommend selectively redeemable bundled services comprising care for conditions predicted as likely by a machine learning model based on patient data input. The likely conditions may be predicted for a patient or a patient population comprising a plurality of patients. The machine learning model may comprise a neural network trained to determine a probability distribution of patient condition trends for a future time period based on patient data input. The patient data input may comprise data from an Electronic Medical Record (EMR), diagnosis, lab test, patient-provided information such as survey/symptom data, and/or wearable device data. The machine learning model may be trained using a training data set including at least healthcare outcomes sampled during a past time period from a plurality of patient healthcare episodes each comprising a plurality of procedures performed for the patient in at least one encounter.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.