Computer-Based Patient Management for Healthcare

• US 20120065987A1
• Filed: 09/09/2011
• Published: 03/15/2012
• Est. Priority Date: 09/09/2010
• Status: Abandoned Application

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Siemens Medical Solutions USA Incorporated (Siemens AG)
• Inventors: Farooq, Faisal, Rosales, Romer E., Yu, Shipeng, Krishnapuram, Balaji, Rao, Bharat R.
• Application Number:
  US13/228,497
• Publication Number:
  US 20120065987A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 10/0633 Workflow analysis
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 10/103 Workflow collaboration or project management
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Computer-based patient management is provided for healthcare. Patient data is used to determine a severity, assign a patient to a corresponding diagnosis-related group, and provide a timeline for care at a medical facility. Reminders or alerts are sent to maintain the timeline for more cost effective care. Reminders, suggestions, transitions between care givers, scheduling and other risk management actions are performed. As more data becomes available as part of the care, the care and timeline may be adjusted automatically for more efficient utilization of resources. Accountable care optimization is provided as part of case management. Automated care before any injury or illness and automated care after discharge is provided to optimize the health and costs for a patient. The patient is assigned to the cohort based on the patient data.

Claims

1. A method for computer-based patient management for healthcare, the method comprising:

gathering, with a processor, first clinical data for a patient of a healthcare facility;

establishing, with the processor, a workflow for care of the patient as a function of the first clinical data and a cost factor, the workflow being for multiple actions by different entities of the healthcare facility and including a timeline for the actions;

gathering, with the processor, second clinical data after establishing and as part of the workflow for the care of the patient;

updating, with the processor, the workflow for the care of the patient as a function of the first and second clinical data and the cost factor, the updating occurring while the patient is at the healthcare facility; and

generating, with the processor, at least one alert for at least one of the multiple actions, the alert generated as a function of the timeline.

2. The method of claim 1 wherein establishing the workflow comprises predicting a severity and assigning the patient to a diagnosis-related group as a function of the severity.

3. The method of claim 1 wherein gathering comprises mining an electronic medical record of the patient, and wherein establishing comprise populating a feature vector with the mining and predicting a probability from the feature vector.

4. The method of claim 3 wherein mining comprises mining from a first data source of the electronic medical record and mining from a second data source of the electronic medical record, the first data source comprising structured data and the second data source comprising unstructured data, the mining outputting values for the feature vector in a structured format from the first and second data sources.

5. The method of claim 3 wherein mining comprises inferring a value for each of a plurality of variables, each value inferred by probabilistic combination of probabilities associated with different possible values from different sources, the inferred values for the variables comprising the feature vector.

6. The method of claim 3 where mining comprises mining as a function of existing knowledge, guidelines, best practices, or about specific institutions regarding case management.

7. The method of claim 1 wherein generating the at least one alert comprises generating a cell phone alert, a computer alert, an alert in the workflow, or combinations thereof.

8. The method of claim 1 further comprising:

automatically scheduling a job entry in a workflow of a case manager, the job entry being for examination to avoid readmission.

9. The method of claim 1 wherein gathering the second clinical data comprises obtaining the clinical data from performance of at least one of the multiple actions, and wherein updating comprises altering a severity for the patient and reassigning the workflow based on the altered severity.

10. The method of claim 1 wherein establishing the workflow and updating the workflow comprises setting the workflow as a function of the cost factor comprising a cost of care and a reimbursement for the care of the workflow.

11. The method of claim 1 further comprising predicting, with the processor, a probability of meeting the timeline, a cost associated with meeting the timeline, and a strongest link to the probability indicating a risk of failure to meet the timeline, the strongest link being relative to links for other variables to the risk.

12. The method of claim 1 wherein establishing the workflow for the care comprises establishing the workflow for the care of the patient after a discharge and to be performed by multiple medical professionals.

13. A system for computer-based patient management for healthcare, the system comprising:

at least one memory operable to store data for a plurality of patients; and

a first processor configured to;

classify each of the patients into diagnosis-related groups based on respective data for each of the patients;

select a timeline to discharge as a function of the diagnosis-related group for each of the patients;

alter the diagnosis-related group for at least one of the patients, the altering being based on a utilization and new data not used in the classifying;

change the timeline for the one of the patients, the changing being a function of the altering; and

monitor tasks across multiple medical professionals as a function of the timeline.

14. The system of claim 13 wherein the processor is configured to mine the data including mining unstructured information, the mining providing values for the variables, the values inferred from different possible values in the data and probabilities assigned to the possible values.

15. The system of claim 13 wherein the processor is configured to generate an alert in response to the monitoring.

16. The system of claim 13 wherein the processor being configured to alter based on the utilization and new data not used in the classifying comprises the processor being configured to change the diagnosis-related group for the one patient, the changing being a function of cost of the tasks, reimbursement for the tasks, and the new data, the new data being obtained after the classifying and while the patient is being treated at a healthcare facility.

17. In a non-transitory computer readable storage medium having stored therein data representing instructions executable by a programmed processor for computer-based patient management for healthcare, the storage medium comprising instructions for:

acquiring data for a patient;

establishing, as a function of the data, first care for the patient prior to an admission to a healthcare facility;

managing, as a function of the data, second care for the patient upon the admission to the healthcare facility; and

establishing, as a function of the data, third care for the patient after discharge from the healthcare facility.

18. The non-transitory computer readable storage medium of claim 17 further comprising generating an alert, reminder, or task as part of the first care, second care, third care, or combinations thereof.

19. The non-transitory computer readable storage medium of claim 17 wherein the first care, second care, and third care are across multiple medical providers associated with different institutions, one of the different institutions comprising the healthcare facility.

20. The non-transitory computer readable storage medium of claim 17 wherein acquiring the data comprises mining unstructured information, the mining providing values for variables, the values inferred from different possible values and probabilities assigned to the possible values.

21. The non-transitory computer readable storage medium of claim 17 wherein establishing the first care comprises identifying a first cohort for the patient, and wherein managing the second care, establishing the third care, or both comprise identifying a second cohort for the patient, the second cohort different than the first cohort.

22. The non-transitory computer readable storage medium of claim 17 wherein establishing, from the data, the third care comprises predicting a risk of readmission, predicting a financial impact, and predicting a severity.

23. The non-transitory computer readable storage medium of claim 17 wherein establishing the first care, managing the second care, and establishing the third care comprise setting as a function of healthcare resource consumption.

24. The non-transitory computer readable storage medium of claim 17 further comprising:

presenting first information associated with the first care, the second care, the third care, or combinations thereof to a first user of a first role;

presenting second information associated with the first care, the second care, the third care, or combinations thereof to a second user of a second role, the second role and second information different than the first role and first information, respectively.

25. The non-transitory computer readable storage medium of claim 17 further comprising indicating a performance of a medical professional across multiple patients including the patient.