Association of Clinical Documentation Improvement Specialists
Certified Clinical Documentation Specialist-Outpatient Credential Committee
Dixon Hughes Goodman Llp
Senior Manager, Chief Financial Officer Advisory Practice
E4 Services Sep 2013 - Nov 2015
General Manager, Clinical Documentation and Coding Practice
Ahima Sep 2013 - Nov 2015
Cdi Practice Council Member
Unitedhealth Group Feb 2012 - Aug 2013
Product Manager, Optum Clinical Documentation Improvement Module
Education:
Southwest University, Kenner Louisiana
Bachelors, Bachelor of Arts, Health Services
Saint Vincent School of Nursing
Weber State University
Associates, Associate of Arts
Skills:
Leadership Consulting Requirements Analysis Agile Waterfall Sdlc Documentations Agile Project Management Medicare Ambulatory Health Information Management Physicians Hipaa Data Analysis Document Imaging Business Development Business Analysis Healthcare Software Documentation Ehr Scrum Process Improvement Strategy Medical Records Revenue Cycle Emr Healthcare It Revenue Cycle Management Healthcare Information Technology Healthcare Webmaster Change Management Ehealth Product Management Software Implementation Enterprise Software Lean Healthcare Nursing Icd 9 Document Management Systems Project Management Cpoe Workflow Analysis Software Development Healthcare Management Healthcare Industry Software Project Management Hit Medical Coding Healthcare Consulting Hospitals
Certifications:
Registered Nurse Registered Health Information Technician (Rhit) Certified Professional In Healthcare Quality (Cphq) Certified Professional In Utilization Review (Cpur) Pennsylvania State Board of Nursing American Health Information Management Association Healthcare Quality Certification Board Interqual/Mckesson
Us Patents
Automated Clinical Indicator Recognition With Natural Language Processing
- Eden Prairie MN, US Mark Morsch - San Diego CA, US Michelle Wieczorek - Waterford PA, US
International Classification:
G16H 50/20 G06Q 50/22 G16H 10/60
Abstract:
Computer-based, natural language processing systems and methods are provided for review of clinical documentation and other medical records, and for clinical documentation improvement. The systems and methods are configured to analyze received diagnoses and/or procedures in view of documents in the record using a natural language processor and a tiered information model to identify clinical indicators, and optionally markers. The identified information is compared with the received data for use in generating queries requesting evidence in support of the received diagnosis or procedure, or for use in validating the received information.
Automated Clinical Indicator Recognition With Natural Language Processing
- San diego CA, US Mark Morsch - San Diego CA, US Michelle Wieczorek - Waterford PA, US
International Classification:
G06Q 50/22 G06Q 10/10
US Classification:
705 3
Abstract:
Computer-based, natural language processing systems and methods are provided for review of clinical documentation and other medical records, and for clinical documentation improvement. The systems and methods are configured to review documents in the record using a natural language processor and to identify clinical indicators with associated contextual information. The clinical indicators are compared to scenarios to generate markers based on an information model. The markers used to generate physician queries and other informational requests with supporting evidence for each query based on indicators identified in the record. In additional examples, pragmatic guidelines including business-based rules can also be utilized, either in combination with, or as part of, the scenarios in the information model.
Automated Clinical Indicator Recognition With Natural Language Processing
- San Diego CA, US Mark Morsch - San Diego CA, US Michelle Wieczorek - Waterford PA, US
International Classification:
G06F 19/00
US Classification:
705 3
Abstract:
Computer-based, natural language processing systems and methods are provided for review of clinical documentation and other medical records, and for clinical documentation improvement. The systems and methods are configured to analyze received diagnoses and/or procedures in view of documents in the record using a natural language processor and a tiered information model to identify clinical indicators, and optionally markers. The identified information is compared with the received data for use in generating queries requesting evidence in support of the received diagnosis or procedure, or for use in validating the received information.
Michelle Wieczorek 1987 graduate of New Britain High School in New britain, CT is on Classmates.com. See pictures, plan your class reunion and get caught up with Michelle and other ...
Michelle Wieczorek 1984 graduate of St. Vincent - School of Nursing in Erie, PA is on Classmates.com. See pictures, plan your class reunion and get caught up with Michelle and ...