Healthcare organization use data collection and reporting for a variety of areas and reason. One main reason is statistics for several department/areas. This information is used to increase quality of care, to determine if there is an increase in a specific health diagnosis, as well as hospital census, which will help to determine the level of staff needed to provide that quality of care. The government also needs to maintain statistics on the population in order to provide services.
HIM professionals compute most of the data collected for healthcare facilities. They will often be asked to produce an almost limitless number of rates from data collection. All organizations concerned with ...view middle of the document...
• Accreditation Agencies – use data information to determine the most common diagnosis and procedures and whether the resources are available to treat patients with those diagnoses.
• Federal Government – use data information for public health issues
Data quality is defined by the business processes that ensure the integrity of an organization’s data during collection, application (including aggregation), warehousing, and analysis. Data quality measurements typically focus on structure of processes of care that have a demonstrated relationship to positive health outcome and are under the control of the heal care system. There are 10 characteristics of data quality. I have listed all of the characteristics below.
Data Accuracy: The extent to which the data are free of identifiable errors
Data Accessibility: Data items that are easily obtainable and legal to access with strong protections and controls built into the process
Data Comprehensiveness: All required data items are included—ensures that the entire scope of the data is collected with intentional limitations documented
Data Consistency: The extent to which the healthcare data are reliable and the same across applications
Data Currency: The extent to which data are up-to-date; a datum value is up-to-date if it is current for a specific point in time, and it is outdated if it was current at a preceding time but incorrect at a later time
Data Definition: The specific meaning of a healthcare-related data element
Data Granularity: The level of detail at which the attributes and values of healthcare data are defined
Data Precision: Data values should be strictly stated to support the purpose
Data Relevancy: The extent to which healthcare-related data are useful for the purposes for which they were collected
Data Timeliness: Concept of data quality that involves whether the data is up-to-date and available within a useful time frame; timeliness is determined by manner and context in which the data are being used
There are many factors that come into play with the importance of data retrieval and analysis with regards to healthcare. Health care data is considered sensitive information and is protected under the Health Information Portability and Accountability Act. Technology has taken the industry from the work of paper to electronics medical records. Providers have information at their fingertips, and it is VERY important for them to be able to retrieve information about patients and billed charges quickly and securely. With the daily threats of computer hackers and identify theft, these records need to be treated like bank records, seal and classified.
Health Information Management is the process of maintaining, storing and retrieving patient heal information in accordance with applicable Federal, State, and accrediting agencies’ requirements. There are ten responsibilities within the framework of health information management.
1. Medical Coding – which includes...