Task 1 Health Data Structures, Usage, and Data Collection Tools
The author has worked in the healthcare industry for eighteen years. Healthcare is full of data, data on patients, data that is kept in medical records, data that is stored on diagnosis, and quality data to name a few. For all the different ways to use data, there are also many types of data. Aggregate data is data without any identifiable information. This means that the identity of the patient is unable to be determined from the data collected. The benefits of this type of data collection are obvious. The data collected is anonymous. Concerns of HIPAA regulations are unfounded due to the lack of identifying information. Aggregate data can be analyzed for many different uses, the possibilities are endless. Aggregate data can be used to trends in hospital admissions. For example, collecting aggregate data on the number of visits to the Emergency Department can be used for staffing or when the department is the busiest. On the other side of the coin, aggregate data is very limited in terms of variety of information. If more information is needed there is no way in backtracking and collecting more because there is not identifying patient information. Another downfall is that aggregate data is so vast, more detailed analysis may not be able to be accomplished. Aggregate data while vast is also non specific in the fact of needing to drill down to see something smaller.
When wanting to compare a number of different groups, comparative data is vital. Comparative data allows the reviewer to compare like the name suggests. The reviewer may look at cancer survival rates of hospitals around the state or even the country. Comparative data can allow for transparency across the industry. Which hospital has an acceptable time for intervention of a stroke. Comparative data can also
