Reference no: EM133026992

Assignment: Data Dictionary

Purpose: Construct a data dictionary to model a healthcare database collection tool.

Background: At the time of discharge, data is collected from patient records to form secondary databases for use in producing indexes (diagnosis, operative, and physician), special registries, quality studies, reports about utilization of facility services, analysis of physician practice patterns, long term planning needs, etc.

The data is often collected through an abstracting process which involves extracting specific data elements from the patient's record and entering the data element on a data collection tool. The data collection tool may be in the form of a paper abstract or an electronic database. Once the data is collected and entered into the system, a variety of reports can be produced based on queries of the database. These reports can take the form of summaries of patient data entered in the system, graphics that illustrate selected data, statistical information, etc.

With specialized registries, there may also be a follow-up data collection component in which data about each patient in the registry is collected at designated times (e.g. annually) to update the data in the system to provide information about survival rates, efficacy of treatment, etc.

In the past few years the number and variety of specialized registries has increased dramatically. Registries can be operated at any and/or all levels: facility-specific, multiple facilities, state-mandated and national. Some are voluntary; others are required by a governmental unit. For example, participation in a Cancer Registry is usually voluntary but if a hospital decides to maintain a Cancer Registry, it must adhere to standards of the American College of Surgeons. In some states, reporting of cancer data to a state data system is required and an individual facility cancer registry may be a vehicle for collecting the data that is required. At the national level, cancer data is collected, analyzed, researched and published by a number of different organizations such as The American College of Surgeons, the National Cancer DataBase, the SEER Program (a national coordinating group for cancer registries), etc.

Because of their background in data collection techniques, HIM professionals are appropriate professionals to be involved in the design of data collection tools for developing databases and specialized registries. One of the important elements of designing a database is identification and definition of the data elements that will be collected. This project is intended to focus attention on the development of databases, data collection and potential uses of aggregate patient data.

In this assignment, you will be developing a modified data dictionary for a specialized registry/database for a disease or condition described in one of the scenarios below or one of your choosing and approved by the instructor.

1. Select a specialized registry scenario from the list (below) or develop your own scenario for a disease or operative registry.

2. Write 2-3 paragraphs explaining your condition/disease and why this topic was chosen.

3. Based on format and content guidelines for a data dictionary (see readings, slides, supplemental articles), identify a minimum of twelve (12) data elements that you will collect in the selected registry (you may choose to include more than 12). The data elements should include:

» Demographic data (minimum of six elements) about the patient (e.g. patient DOB). Note: with six elements, you will not capture every important item about patient demographics so you are doing just those that you select as most important (for example, you may want age but not street address). You may want to know the sex if the condition can be different in different sexes (including LGBTQ and more)
» Clinical data (minimum of six data elements) specific to disease/condition that the registry (e.g. blood sugar lab results for a diabetes registry). This information will come from your research.
» At least one clinical data element must have a reference range (e.g. lab value, BP, etc.). You will need to do research about your disease process in order to identify lab values, clinical signs/symptoms, etc. in order to identify a data element with a reference range.
» Identify at least one required government standard (eg Joint Commission, Medicare/Medicaid).
» Any other data that you deem to be useful (think long term ~ what data elements might help research in 10-20 years). There are no wrong answers - think futuristic.

4. Develop a data dictionary using either a table or spreadsheet and include the following :

» A title for your data dictionary
» Name of the data elements/attributes
» Unique Mnemonic/Identifier for each data element/attributes
» Description or definition of each data element/attribute
» Result Type (e.g. numeric, alphabetic, free text, etc.)
» Description of the attributes of each data element and/or inclusion of any relevant numeric ranges or alpha interpretation (ex: Sex = M, F or U)
» Size parameters for data field
» Formatting rules for the data field (ex: Date of discharge = MM/DD/YYYY; field is limited to numerical data)
» Reference ranges, as appropriate (e.g. Oral temp/Celsius = 36.8-37.3°)
» Whether attribute is required or optional
» Use a variety of data types such as alpha, numeric, text, drop downs, multi-selection, etc.

5. Give examples of how your data collection tool (and collected data) could be used in the future. (2-3 paragraphs)

6. A bibliography of resources should be included. The bibliography must include references about the specific disease/condition that you selected for the registry. You might also want to read articles about disease registries, data dictionaries, standards for data items, etc. .

SCENARIOS FOR CLINICAL DATABASES (You may choose one of these or develop your own):
• Violence-related injuries: trauma/injuries that are the result of a violent act including such things as firearm injuries, domestic about, etc.
• AIDS/HIV: NOT interested in patient-identifiable data and want to assure that the system protects the confidentiality of the patient but include risk factors present in individuals who contract the disease, associated complications or co-morbid conditions that occur, length of survival and effectiveness of various treatment modalities.
• Cardiovascular diseases: especially interested in assessing risk factors related to CV disease
• Premature births in Minnesota and related perinatal morbidity/mortality. Include maternal health factors that could be linked to premature birth (e.g. smoking).
• Multiple Sclerosis: include genetic and environmental factors that may be linked to the development of MS.
• Caesarean section including the reason for C-section, the health status of the mother at the time of delivery, associated diagnoses, the condition of the infant at birth including common indicators such as birth weight, APGAR score, medical diagnoses, etc.
• Motor vehicle accidents (all types of motorized vehicles) that result in injury to an individual with emphasis on types and severity of injuries that result, mortality rates and occurrence of associated debilitating conditions, gender and age data, etc.
• Diabetes mellitus: emphasis on risk factors, management of diabetes especially personal health and wellness initiatives.
• Gulf War Veteran medical database tracking associated physical and psychological conditions associated with wartime action. Database should include Gulf War I, Iraqi war, and Afghanistan war veterans.
• Crohn's disease registry with focus on risk factors, treatment, and age/gender.
• Autism registry with focus on risk factors, genetic/familial history, severity of condition.
• You may also develop your own scenario but it must be approved by the instructor (e.g. birth defects registry, diabetes registry, transplant database, influenza database)

Attachment:- Assignment Data Dictionary.rar