Advances are being made to develop IT infrastructure that are both inexpensive and robust. Medical data are complex, but there are data standards for diseases, procedure, and laboratory tests. An electronic medical record is much better and much safer than paper record.
TABLE 1. AHIMA Data Quality management Characteristics Characteristics Application Collection Warehousing Analysis
Data Accuracy
Data are the correct values and are valid to facilitate the accuracy, determine the applicant’s purpose, the question to be answered Ensuring accuracy involves education and training and timely and appropriate communication of data definitions to those who collect data. For example, data accuracy will help ensure that if a patient’s sex is
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Include a problem statement and cost-benefit or impact study when collected data are increased. For example, in addition to outcome it may be important to gather data that impact outcomes. Cost-effective comprehensive data collection may be achieved via interface to or download from other automated systems. Data definition and data precision impact comprehensive data collection. Warehousing includes managing relationships of data owners, data collectors, and data end-users to ensure that all aware of the available data in the inventory and accessible systems. This also helps to reduce redundant data collection Ensure that all pertinent data impacting the application are analyzed in concert
Data 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 It is outdated if it was current at some preceding time yet incorrect at a later time. The appropriateness or value of an application changes over time. For example, traditional quality assurance applications are gradually being replaced by those with the more current application of performance improvement. Data definitions change are modified over time. These should be documented so that current and future users know what the data mean. These changes should be communicated in a timely manner to those collecting and to the
In the medical field there have been a lot of technological advances and making health records electronic is one of them. The days of having a paper health record are almost obsolete. An electronic health record keeps a patient’s medical information and history on a computer which is accessible to more people in less time. I will explain how the continuity, communication, coordination and accountability of the electronic health record can help the medical office. I will explain what can be included in the electronic health record. As an advocate of the electronic health record I will also explain some disadvantages to the electronic system.
Identify bits of information which is used for compiling date, once data is interpreted and organized it can be presented as information.
To ensure the data I find is suitable for the purpose of the research, I should agree guidelines for exactly what is needed and in what format with my manager or whoever set the task.
Data consistency- means that all information within the document must be a reliable source of data.
Electronic Medical Records or Computerized Medical Record System what is it and what are the advantages along with the disadvantages of using this system? That is what we will discuss in this paper.
Data must be standardized for accurate correspondence and analysis. The data which was standardized is always ready to be shared across the organization. The standardized data is much useful during the data entry. It is easy to collect and secure the important data and reports. These data and reports are prepared at a specific period of time during a year, they are well defined and well organized.
In some cases, primary data is the only form of data available. On the other hand, primary data requires additional time so time management is vital. Also, a large amount of resources are required, a high amount of labor is also required, and often collecting primary data can be cumbersome requiring some amount of skills. Primary data is a good source due to its reliability, focus, and significant amount of control of information. (Hossain, 2012)
There exists many data coding standards in healthcare. The ICD is the international standard of the classification of diseases used by a multitude of healthcare professionals (“International Classification of Diseases”, 2016). Its latest version, ICD-10, has numerous benefits including helping doctors more correctly report conditions and differentiate payment by treatment type, more efficient disease management, and helping to prevent fraudulent claims as a result (Schwartz, 2013). In terms of current use, more and more countries have used it for reporting morbidity. In the United States, it has been the official standard for death certificates since 1999 (Brouch, 2000). For the future, ICD-11 is stated to be released to include recent advancements in healthcare and medicine and will allow open access for editing (“International Classification of Diseases”, 2016). LOINC® is used to standardize data for laboratory and medical clinic measurements (McDonald et al., 2003). Benefits include helping separate lab systems interpret shared lab test data, improving the efficiency of ordering lab tests from many labs, and also aiding in generating public health clinical data (“3.2 Benefits of LOINC”). Current usage is categorized into three areas: laboratory, clinical, and HIPAA specific proposals. The majority of US federal agencies and public health departments like New York State
Data is important to the company as it assists with decision making, competitive advantage, or support. Senior management has to rely on historical information to observe trends in order to formulate a plan to execute improvements for the future. Company performance information can be leveraged to compare among competitors in the industry to capture an idea of where the organization stands. Data can be used as support to confirm whether previously executed plans are effectively working or not against standards or metrics.
Information: Data that have been organized so that they have meaning and value to the recipient. (CH01)Slide#9
At this point the data should be reliable and have little to no mistakes within it and as like everything else in business there is a deadline for when the data should be distributed.
The term metadata first used in 1969 is called ‘data about data’ or ‘information about information’. The term ‘meta’ derives from the Greek word denoting a nature of a ‘higher order’ or more ‘fundamental kind’ , or ‘above’, ‘beyond’, and ‘of something in a different context’ , metadata is data associated with objects which relieves their potential users of having to have full advance knowledge of their existence or characteristics. It helps in finding data and tells how to interpret and use data. Metadata gives descriptive information about the producer, content , quality, condition and other characteristics of a dataset. Metadata ensures use of right data for right purpose, Metadata assigns quality and defines limitation, improves the appropriate use of data, provides entity and attribute information about the following:
· Operations - such as sales data, HR data, product data, inventory data, marketing data, systems data.
systematic procedure to collect essential data and these data should be adequate in Quantity and Quality.