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Health Data Quality

Health Data Quality. Lecture 3. Data and Information. Data and Information. Health data is raw health facts stored as characters, words, symbols, measurements, or statistics. Data is not very useful for decision making.

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Health Data Quality

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  1. Health Data Quality Lecture 3

  2. Data and Information

  3. Data and Information • Health data is raw health facts stored as characters, words, symbols, measurements, or statistics. • Data is not very useful for decision making. • Health care data is gathered through patient care documentation by clinical providers and administrative staff. • Example: • 80% • O+

  4. Information • Information is an extremely valuable asset at every level of a health care organization. • The same data may provide different information to different users. • One person’s data may be another person’s information. • Data creates information. We must have data before we can get information.

  5. Knowledge • “A combination of rules, relationships, ideas, and experience.” (Johns, 1997) • Knowledge is used for decision making.

  6. Data Quality • We must acquire high quality data to achieve high quality information. • Data quality must be established at the granular level.

  7. Medical Records Institute (MRI) • Medical Records Institute (MRI) is a professional organization dedicated to the improvement of patient records through technology. • Health care documentation has two parts: • Information capture:“the process of recording representations of human thought, perceptions, or actions in documenting patient care, as well as device-generated information that is gathered and/or computed about a patient as part of health care”. • Handwriting, speaking, typing, touching a screen or pointing and clicking on words or phrases, videotaping, audio recording, and generating images through X-rays and scans. • Report generation:“consists of the formatting and/or structuring of captured information. It is the process of analyzing, organizing, and presenting recorded patient information for authentication and inclusion in the patient’s healthcare record”.

  8. Medical Records Institute (MRI) • Medical Records Institute (MRI) has identified five major functions that are negatively affected by poor-quality documentation. • Patient safety is affected by inadequate information, illegible entries, misinterpretations, and insufficient interoperability. • Public safety, a major component of public health, is reduced by the inability to collect information in a coordinated, timely manner at the provider level in response to increase in and the threat of terrorism. • Continuity of patient care is affected by the lack of shareable information among patient care providers.

  9. Medical Records Institute (MRI) • Health care economics are affected, with information capture and report generation costs currently estimated to be well over $50 billion annually. • Clinical research and outcomes analysis is affected by a lack of uniform information capture that is needed to facilitate the derivation of data from routine patient care documentation.

  10. Poor Quality Data • Poor-quality data collection and reporting can affect each of the purposes for which we maintain patient records. • At the organizational level a health care organization may find diminished quality in: • Patient care • Poor communication among providers and patients • Problems with documentation • Reduced revenue generation due to problems with reimbursement • Diminished capacity to effectively evaluate outcomes or participate in research activities

  11. Poor Quality Data • These problems are found not only at the organizational level but also across organizations and throughout the overall health care environment. • Solution: Some of the problems presented may actually be reduced with the implementation of effective information technology (IT) solutions.

  12. Ensuring Data and Information Quality • Health care decision makers rely on high quality information. • Before an organization can measure the quality of the information it produces and uses, it must establish data standards. • Unfortunately, there is no universally recognized set of health care data quality standards in existence today. • Health care organizations mustestablish data quality standards specific to the intended use of the data or resulting information. • In the U.S two organizations have published guidance that can assist a health care organization in establishing its own data quality standards: • the Medical Records Institute (MRI) • American Health Information Management Association (AHIMA)

  13. MRI Principles of Health Care Documentation • Unique patient identification must be assured within and across healthcare documentation systems • Healthcare documentation must be • Accurate and consistent. • Complete. • Timely. • Interoperable across types of documentation systems. • Accessible at any time and at any place where patient care is needed. • Auditable. • Confidential and secure authentication and accountability must be provided.

  14. Type of Data Errors • Failures of data to meet established quality standards are called data errors. • A data error will have a negative impact on one or more of the characteristics of quality data. • Systematic errors: are errors that can be attributed to a flaw or inconsistency in adherence to standard operating procedures or systems. • Random errors: errors caused as the result of poor handwriting or transcription errors.

  15. Error Type Examples

  16. Error Type Examples • The following illustration is an example of a hand-written prescription for Metadate ER 10 mg tablets. Metadate is a drug used in the treatment of Attention Deficit Hyperactivity Disorder (ADHD). Due to the similarity in name, poor penmanship and the omission of the modifier "ER", the pharmacy filling the prescription incorrectly dispensed methadone 10 mg tablets. Methadone is a morphine-based product used as a heroin substitution therapy and analgesic. Methadone is not used for the treatment of ADHD.

  17. Error Prevention, Detection, and Correction • Both systematic and random errors lead to poor-quality data and information. • Errors that are not preventable need to be detected so that they can be corrected. • There are multiple points during data collection and processing where system design can reduce data errors.

  18. Error Prevention, Detection, and Correction

  19. Improve Data Quality • Provide data quality reports to users. • Give feedback of data quality results and recommendations. • Communicate with users.

  20. IT for Enhancing Data Quality • Information technology has tremendous potential as a tool for improving health care data quality. • Electronic Medical Records (EMRs) improve legibility and accessibility of health care data and information. • EMR systems were recorded in an unstructured format (narrative form).

  21. IT for Enhancing Data Quality • Physician notes and discharge summaries are often dictated and transcribed. This lack of structure limits the ability of an EMR to be a data quality improvement tool. • When health care providers respond to a series of prompts they are reminded to include all necessary elements of a health record entry. • Data precision and accuracy are improved when these systems also incorporate error checking.

  22. References • “Health Care Information Systems: A Practical Approach for Health Care Management”By Karen A. Wager, Frances W. Lee, John P. Glaser • “Information Systems and Healthcare Enterprises”By Roy Rada • Source: Examples from Schott, 2003, pp. 22-23.

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