When designing data definitions, you will be assigning meaning to the data elements that are part of the computerized data. If there is no definition to the data, then it is not information. Write a paper of two (2) pages not including the title page, abstract page, and reference page that discusses the following:
- Design a list of 10 data elements related to the patient demographic information (refer back to the data sets if necessary).
- Indicate characteristics of each example, such as date format, text, alphanumeric, and so on.
- Define the number of characters for each data element and if it is required data based on a data set.
Be sure to support your information by citing at least 2 references using APA format.
Data Elements used in Patient Demographic Information and their Characteristics
The first type of data that is extracted from patients upon presentation to any health facility is their demographic information. Triage nurses are mostly involved in collecting this type of data, and it helps to identify the different characteristics of the patient and hence guide on the treatment plan (Wallace et al., 2020). The following are some of the common demographic data elements and their specific characteristics.
- Patient ID. The details of the patient ID include their surname, their first name, and the assigning authority ID. If the patient is recurrent in the facility, they would need to give the medical record number or other information that identifies the patient with their previous information (Okuda et al., 2020). Regarding the characteristics of this data element, each facility has its own preferred way of collecting the patient identification.
- Date of birth (DOB). The characteristics of this data set includes the use of an alpha-numeric format, in which the month of birth is written in alphabets while the day and year are written in numerals. The place of birth could also be collected as an additional element of the dataset.
- The data element of gender is usually categorized as either male or female, as the there are no provisions in the hospital for transgender individuals.
- Blood type. The blood type is categorized as either Rhesus Positive or Rhesus negative as well as the blood group A, B, AB, or O.
- Place of Residence. The address of the patient includes the street address, their state, apartment, and all other details that could guide easy access to their home in the event of need.
- Emergency contact information. The phone number of the close family members is the primary information collected at this stage.
- Major medical history. This data element includes things such as previous major diagnoses as well as the current drugs that the patient is taking.
- The data element includes the idea of whether the patient is black, white, Caucasian, Hispanic, or has other ethnicities (Unger et al., 2020).
- Primary Language. The primary language of the patient could either be English or other languages that the care providers can easily understand.
- Contact information. The data element requires the patients to give their phone numbers, email address, their physical address, work address, as well as all other information that would guide the healthcare providers in doing a follow-up on them.
Okuda, B. C., Tabbaa, S., Edmonds, M., Toubouti, Y., & Saltaji, H. (2020). Direct to consumer orthodontics: Exploring patient demographic trends and preferences. American Journal of Orthodontics and Dentofacial Orthopedics. https://doi.org/10.1016/j.ajodo.2019.12.024
Unger, J. M., Blanke, C. D., LeBlanc, M., Barlow, W. E., Vaidya, R., Ramsey, S. D., & Hershman, D. L. (2020). Association of patient demographic characteristics and insurance status with survival in cancer randomized clinical trials with positive findings. JAMA network open, 3(4), e203842-e203842. doi:10.1001/jamanetworkopen.2020.3842
Wallace, S. J., Murphy, M. P., Schiffman, C. J., Hopkinson, W. J., & Brown, N. M. (2020). Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty. Knee Surgery & Related Research, 32(1), 1-7. https://doi.org/10.1186/s43019-020-00075-y
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