Health information management

Health Information Management is the management of personal health information in hospitals or other healthcare organizations enabling the delivery of quality healthcare to the public. See "Health Informatics".

Overview

Hospitals and other healthcare organizations typically capture many different forms of health data and store them in many different ways ...

Background

The medical records departments are generally seen as the origins of ...

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Areas of interest

Health records managementData qualityData items definitionsCurrent software that assist with Health Information Management (HIM) is called Epic.

The patient health record is the primary legal record documenting the health care services provided to a person in any aspect of the health care system. The term includes routine clinical or office records, records of care in any health related setting, preventive care, lifestyle evaluation, research protocols and various clinical databases. This repository of information about a single patient is generated by health care professionals as a direct result of interaction with a patient or with individuals who have personal knowledge of the patient.

The Primary patient record is the record that is used by health care professionals while providing patient care services to review patient data or document their own observations, actions, or instructions.

The secondary patient record is a record that is derived from the primary record and contains selected data elements to aid non clinical persons in supporting, evaluating and advancing patient care. Patient care support refers to administration, regulation, and payment functions.

Methods to ensure Data Quality The accuracy of data depends on the manual or computer information system design for collecting, recording, storing, processing, accessing and displaying data as well as the ability and follow- through of the people involved in each phase of these activities. Everyone involved with documenting or using health information is responsible for its quality. According to AHIMA’s (American Health Information Management Association) Data Quality Management Model, there are four key processes for data:

•Application—The purpose for which the data are collected

•Collection—The processes by which data elements are accumulated

•Warehousing—The processes and systems used to store and maintain data and data journals

•Analysis—The process of translating data into information utilized for an application

These processes are evaluated with regard to 10 different data characteristics:

Accuracy: Data are the correct values and are valid.

Accessibility: Data items should be easily obtainable and legal to collect.

Comprehensiveness: All required data items are included. Ensure that the entire scope of the data is collected and document intentional limitations.

Consistency: The value of the data should be reliable and the same across applications.

Currency: The data should be up to date. A datum value is up to date if it is current for a specific point in time. It is outdate if it was current at some preceding time yet incorrect at a later time.

Definition: Clear definitions should be provided so that current and future data users will know what the data mean. Each data element should have clear meaning and acceptable values.

Granularity: The attributes and values of data should be defined at the correct level of detail.

Precision: Data values should be just large enough to support the application or process.

Relevancy: The data are meaningful to the performance of the process or application for which they are collected.

Timeliness: Timeliness is determined by how the data are being used and their context.

Healthcare quality and safety require that the right information be available at the right time to support patient care and health system management decisions. Gaining consensus on essential data content and documentation standards is a necessary prerequisite for high-quality data in the interconnected healthcare system of the future. Further, continuous quality management of data standards and content is key to ensuring that information is useable and actionable. [Mervat Abdelhak et al: “Health Information: Management of a Strategic Resource”, Second Edition]

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Further reading

* Shortliffe EH, Cimino JJ eds. Biomedical Informatics: Computer Applications in Health Care and Biomedicine (3rd edition). New York: Springer, 2006
* Olmeda, Christopher J. (2000). Information Technology in Systems of Care. Delfin Press. ISBN 978-0-9821442-0-6
* Donald E. Knuth. Selected Papers on Computer Science, CSLI Publications, Cambridge Univ. Press, 1996
* National Institute of Clinical Excellence, Principles of Best Practice in Clinical Audit. London: NICE, 2002. (ISBN 1-85775-976-1)
* Payne PR, Greaves AW, Kipps TJ., CRC Clinical Trials Management System (CTMS): an integrated information management solution for collaborative clinical research, AMIA Annu Symp Proc. 2003;:967.

External links

* [http://www.himss.org Healthcare Information and Management Systems Society]
* [http://www.IFHRO.org International Federation of Health Records Organizations]
* [http://www.AHIMA.org American Health Information Management Association]
* [http://www.HIMAA.org.au Health Information Management Association Australia]
* [http://www.LaTrobe.edu.au/publichealth/HIM LaTrobe University, Australia - Bachelor of Health Information Management]
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* [http://www.HL7.org.au Health Level 7 Australia]
* [http://www.epicsystems.com Epic Systems Corporation]
* [http://www.himonline.uc.edu/ University of Cincinnati Bachelor of Science in Health Information Management]
* [http://www.hhs.gov/ocr/hipaa/ National Standards to Protect the Privacy of Personal Health Information]