Chapter 2 Health Care Data Quality

Data
Characters, words, symbols, measurements..stats
Information
Is processed data
Knowledge
A combination of rules, relationships, ideas and experience
Processing
(1) Healthcare Data (2) Healthcare Information and (3) Healthcare Knowledge
Medical Records Institutes (MRI)
Professional organization dedicated to the improvement of patient records through 5 major functions: (1) Patient Safety (2) Public Safety (3) Continuity of Patient Care (4) Healthcare Economics and (5) Clinical research and outcomes analysis
Information Capture
Process of recording representatives of human thought, perceptions, or actions in documenting patient care as well as device generated information.
Report Generation
Process of analyzing, organizing, and presenting recorded patient information for authentication and inclusion in the patient’s healthcare record.
Data Standards
Must be set to ensure high quality. ie. margin of error must be zero for critical lab tests to ensure patient safety is not in jeopardy.
Medical Records Institutes (MRI)
Published “Essential Principles of Healthcare Documentation”
American Heart Info Management Association (AHIMA)
Data Quality Model Characteristics: (1) Accuracy (2) Accessibility (3) Comprehensiveness (4) Consistency (5) Currency (6) Definition (7) Granularity (8) Precision (9) Relevancy (10) Timeliness
Data Accuracy
Data that reflect correct, valid values are accurate ie. misspelled names
Data Accessibility
Data that are not available to the decision makers needing them are of no use
Data Comprehensiveness
All of the data required for a particular use must be present and available to the user.
Data Consistency
Quality data are consistent ie. an abbreviation with two meanings
Data Currency
Many times the admitting dx is not the same as the one recorded upon d/c
Data Definition
Clear definitions of data elements must be provided so that both current and future data users will understand what the data mean.
Data Granularity
“automicity” cannot be further subdivided
Data Precision
How close to an actual size, weight, or other standard a particular measurement is
Data Relevancy
Data must be relevant to the purpose for which they are collected
Data Timeliness
ie. critical lab values must be available to the health care provider in a timely manner
Error Types
[1] Systemic and [2] Random
Systemic Error
Results from incorrect programming of the encoding software OR improper training of the individuals assigning the code ie. unclear data definitions, lack of sufficient data checks, poor interface and programming errors
Random Error
Results of poor handwriting or transcripting due to carelessness ie. illegible handwriting in data source, typing errors, and lack of motivation
Government Accountability Office (GAO)
Found that many of the data in existing EMR systems were recorded in an unstructured format ie. narrative rather than in data fields designated to contain specific pieces of information
AHIMA Data Quality Management Model
[Application] the purpose for which the data are collected [Collection] the processes by which data elements are accumulated [Warehousing] processes and systems used to archive data and data journals and [Analysis] the process of translating data into information utilized for an application