Demonstrate Compliance With Healthcare Data

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Demonstrate Compliance With Healthcare Data

Demonstrate Compliance With Healthcare Data

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ASSIGNMENT: Data Sets
Demonstrate compliance with healthcare data sets (Blooms 3)
Instructions:

Part I: Review the information on Data Sets from your lesson. Study the Table 1 provided in the lesson. Create your own table with 3 columns and copy the information from the table in the lesson for the first 2 columns for DEEDS, MDS, OASIS, UACDS, and UHDDS.

Part II: Research each of these online and/or in the Peden textbook

– In the 3rd column, show 4 data elements that are required for each of the data sets.

Part III: Open the inpatient record provided as an attachment below

– Analyze the documentation in the record to see if it would meet the requirement for the UHDDS data elements you included in your table.

– Type a Yes or a No after each of the data elements to indicate if you were able to find the data element in the chart.

Data standards are the principal informatics component necessary for information flow through the national health information infrastructure. With common standards, clinical and patient safety systems can share an integrated information infrastructure whereby data are collected and reused for multiple purposes to meet more efficiently the broad scope of data collection and reporting requirements. Common data standards also support effective assimilation of new knowledge into decision support tools, such as an alert of a new drug contraindication, and refinements to the care process. This chapter provides both a short overview introducing data standards to the lay reader and a more technical review of the specific data standards required for the informatics-oriented professional. Please note that in the technical portion of the paper, once a standard is introduced it will be referred to in its acronym form due to the number of data standards involved. Readers may refer to the list of acronyms in Appendix B for assistance as needed.
OVERVIEW OF HEALTH CARE DATA STANDARDS
Although much of the data needed for clinical care, patient safety, and quality improvement resides on computers, there is as yet no means to trans-
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Suggested Citation:”4 Health Care Data Standards.” Institute of Medicine. 2004. Patient Safety: Achieving a New Standard for Care. Washington, DC: The National Academies Press. doi: 10.17226/10863.

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fer these data easily and economically from one computer to another, despite the availability of the communications technologies to support such data exchange. The chief obstacle to achieving this capability has been the haphazard adoption of data standards for organizing, representing, and encoding clinical information so that the data can be understood and accepted by the receiving systems (Hammond, 2002). At the level of the health care organization, the lack of common data standards has prevented information sharing between commercial clinical laboratories and health care facilities, between pharmacies and health care providers regarding prescriptions, and between health care organizations and payers for reimbursement (Hammond, 2002). The lack of standards has also prevented the reuse of clinical data to meet the broad range of patient safety and quality reporting requirements, shown in Table 4-1. The first column of this table lists the data sources often associated with an electronic health record (EHR); the second, those associated with clinical information systems, decision support tools, and external data sources; the third, state, regulatory, and private-sector patient safety reporting systems; and the fourth, federal reporting systems. The fact that there is no standard means of representing the data for any of these datasets or requirements is astonishing and highlights the amount of unnecessary work performed by health care and regulatory organizations to prepare, transmit, and use what amount to custom reports. The federal government has recognized this problem and is moving forward with the integration of its safety-related systems. This study goes further by recommending common standards for the clinical and patient safety data that span the full range of data sources listed in Table 4-1. Many of the data standards required are already available; others need further development.

 

What Are Data Standards?
In the context of health care, the term data standards encompasses methods, protocols, terminologies, and specifications for the collection, exchange, storage, and retrieval of information associated with health care applications, including medical records, medications, radiological images, payment and reimbursement, medical devices and monitoring systems, and administrative processes (Washington Publishing Company, 1998). Standardizing health care data involves the following:

Definition of data elements—determination of the data content to be collected and exchanged.
Data interchange formats—standard formats for electronically encod-
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Suggested Citation:”4 Health Care Data Standards.” Institute of Medicine. 2004. Patient Safety: Achieving a New Standard for Care. Washington, DC: The National Academies Press. doi: 10.17226/10863.

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ing the data elements (including sequencing and error handling) (Hammond, 2002). Interchange standards can also include document architectures for structuring data elements as they are exchanged and information models that define the relationships among data elements in a message.
Terminologies—the medical terms and concepts used to describe, classify, and code the data elements and data expression languages and syntax that describe the relationships among the terms/concepts.
Knowledge Representation—standard methods for electronically representing medical literature, clinical guidelines, and the like for decision support.
At the most basic level, data standards are about the standardization of data elements: (1) defining what to collect, (2) deciding how to represent what is collected (by designating data types or terminologies), and (3) determining how to encode the data for transmission. The first two points apply to both paper-based and computer-based systems; for example, a laboratory test report will have the same data elements whether paper or electronic. A data element is considered the basic unit of information, having a unique meaning and subcategories of distinct units or values (van Bemmel and Musen, 1997). In computer terms, data elements are objects that can be collected, used, and/or stored in clinical information systems and application programs, such as patient name, gender, and ethnicity; diagnosis; primary care provider; laboratory results; date of each encounter; and each medication. Data elements of specific clinical information, such as blood glucose level or cholesterol level, can be grouped together to form datasets for measuring outcomes, evaluating quality of care, and reporting on patient safety events.

Associated with data elements are data types that define their form. Simple data types include date, time, numeric, currency, or coded elements that rely on terminologies (Hammond, 2002). Examples of complex data types are names (a structure for names) and addresses. For comparability and interchange, data types must be universal and must be carried through all uses of the data. The designation of common scientific units is also necessary. Units (e.g., kilograms, pounds) must be specified as another measure to prevent adverse events such as those related to dosing errors. Until recently, each institution or organization defined independently the data it wished to collect and the units employed, did not use data types, and created local vocabularies, resulting in fragmentation that prevented reuse.

For data elements that rely on terminologies and their codes for definition, merely referencing a terminology alone does not provide enough

Datasets.docx

You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.

Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.

Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor.

The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.

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