Abstract
Researchers at the University of Central Florida have
developed technologies for quantitatively evaluating, tracking and managing patient
medical records. With unique methodologies and statistical analyses, the
technologies provide tools for assessing the strength, completeness,
consistency, and accuracy of patient electronic medical records (EMRs) in one
or more databases. One of the inventions also allows organizations to track
chronic condition diagnoses and determine plans for staging and managing the
conditions. By helping organizations identify the strengths and shortcomings of
their record-keeping procedures, the UCF technologies provide the healthcare industry
with a clearer path to ensuring the highest standard of care.
Technical Details
IP Track Codes 33510 and 34394, Method and System for Managing
Healthcare Patient Record Data: These inventions provide methods and systems
for managing patient EMRs in terms of completeness, consistency, and accuracy
relative to established guidelines. One tool that the systems use to assess
patient EMRs is the Data Completeness Analysis Package (DCAP). DCAP analyzes a
patient’s medical records holistically to identify the lack of pertinent and
necessary patient data. Once implemented, DCAP uses scoring algorithms and
robust statistical analysis techniques to determine the completeness of
individual patient records as well as aggregate patient records across healthcare centers and subpopulations. The system can also verify individual fields
for completeness across an entire database.
Additionally, technology 34394 enables organizations
to assess and compare two or more EMR databases as well as comparing the strength
of a selected data field across the databases. The invention’s graphical user
interface can provide remote access to a database over a network.
In one example implementation, DCAP generates visual
representations (concept maps) of data in conjunction with statistical
analysis. The concept mapping method works as a schema to represent stored data
that users can uniformly examine regardless of the platform that originally held
the data or other health care protocols that may make cross-examinations of
data sets more difficult. Once developed through DCAP, the system converts the
concept maps to standard data format CSV (comma-separated values) files. The
CSV files are analyzed through a parser that allows the user to determine the
strength of individual patient records and record-keeping throughout a
particular database.
The result is a Record Score Strength (RSS) that is based
upon the care provider’s input of Importance Weights (IW), along with a Patient
Database Score (PDS) that defines the overall strength of the records. Using
database segmentation techniques, DCAP also generates a Patient Subgroup Score
(PSS) to compare subpopulations of patient records. It attains the PSS by
averaging the RSS scores of the patients of interest by age, race, gender, and
insurance status.
IP Track Code 34565, Method and System for Managing Chronic
Illness Health Care Records: The invention is a system and methods for
identifying inconsistencies in the EMRs of patients with chronic illnesses. The
system includes a scoring algorithm called Chronic Condition Mapping Package
(CCMP) which can track chronic condition diagnoses in terms of completeness,
consistency, and accuracy relative to established guidelines.
In one example use, the system first converts native EMR
data into a standardized comma-separated values (CSV) data format using concept
mapping to identify how data is stored. It then extracts data relevant to
chronic condition diagnoses, including encounter level data, subjective
narrative data, and objective data. The encounter level data can identify the
stage of a chronic illness at each encounter to determine if and how the
chronic illness has changed. Afterward, it analyzes the data relative to data
translators, such as an ICD-10 chronic condition identifier. Once it processes
the data, the system uses a complex scoring algorithm to identify and compare
scores that incorporate the algorithm's aims. The scoring algorithm enables
organizations to compare patient records, subpopulations, and databases, both
at a chronic condition level and across chronic conditions. Scores form the
basis for improvement in chronic condition data capturing and improving
healthcare delivery for patients. The system also generates alerts to inform
users when a pre-existing chronic illness is not subsequently identified or if a
subsequent diagnosis indicates that the condition has changed by some
predetermined amount.
Partnering Opportunity
The research team is looking for partners to develop the
technology further for commercialization.
Stage of Development
Working prototypes available via test environment.
Benefit
Strengthens patient data quality while reducing costsImproves record-keeping proceduresEnables proper staging and management of health conditionsEasy to implementMarket Application
HospitalsHealth care centersMedical clinicsPrivate practices and medical groups
Brochure
