COVID-19 Hospital Data Coverage:
As part of the COVID-19 hospital data coverage, all hospitals authorized to provide 24-hour care were required to report supply fields every day of the week within one business day of the reporting date. As a result, the dataset could provide answers to the following research questions:
What is the total number of hospitals that have 14 ventilators or none at all?
How many of them were unable to receive ventilator supplies?
How many people received supplies and were able to keep them?
Was there a difference in supply maintenance when a hospital received more than one?
Simple summary statistics such as sum and counts are included in the methodologies. In order to answer question 1, frequency counts were performed in hospitals with 14 or no ventilators. To answer the following question, the metrics were grouped by dimensions, which were hospitals with ventilator counts. The third question is addressed based on the number of hospitals that received supplies and were able to keep them. The fourth question is a continuation of the previous one, in which there was a noticeable difference in maintaining supplies when there were two of them.
The majority of the hospitals had 14 or no ventilators; 1886 of them had none, compared to 2454 with ventilators. Surprisingly, there were very few of them with ventilators in between. As a result, it can be concluded that hospitals either had or did not have ventilators. However, it is worth noting that hospitals without ventilators were not only able to acquire ventilator supplies, but they were also able to maintain them over time, despite constituting a small but still significant portion of them.
Although there could have been other factors, given the margin of difference, it must be due to supplies or frequency, as hospitals with 14 ventilators fared quite well in terms of maintaining supplies. When hospitals with 11 ventilators had more than one supply, they performed even better at keeping their stores and had an average that was higher than hospitals with 14 ventilators. Hospitals with 14 ventilators, on the other hand, had an inventory of more than two days despite having a supply of one.
Dataset for reference:
https://healthdata.gov/d/b9rp-mvy6
3rd Discussion
In this case, the dataset used is “COVID-19 Hospital Reporting – State Certification Status,” which shows the certified hospitals that can assume reporting for the various hospitals in their state. As a result, it is simple to reduce the workload and burden on hospitals while still reporting the covid state in their state. The reported data is forwarded to the US Department of Health and Human Services.
When developing research questions for specific studies, it is critical to consider the type of data that will be collected as well as how the data will be related to one another. With this in place, the researcher will have a better understanding of the issues they are dealing with and, as a result, will be able to provide a better understanding of the research and the expected results based on the data collected. The data should provide answers to the research questions that were generated. “…pose significant questions that can be empirically investigated” (Cai et al., 2019). In this case, the research questions should therefore be related to the topic of Covid 19 hospital reporting and not to any other topic. As a result, the questions should evaluate the Covid 19 reporting process as well as the various ways in which different hospitals in the same states report the data collected to the US Department of Health and Human Services (Healthdata.gov, 2020). This will make it easier to align the research questions with the data and thus conduct a proper analysis. The research questions should be researchable, making it simple to gather information from various sources based on the data. The data presented is analytical rather than descriptive, making it simple to analyze the issue and ensure the readers have a clear picture of the situation. As a result, it will be simple to connect the research to the data and results obtained at the end. Finally, the research question should be simple enough to allow one to draw conclusions from the research (Healthdata.gov, 2020). The data should easily answer the research questions, allowing the audience to understand what the researcher is presenting and, as a result, come to the correct conclusions based on the analysis.
To Help in analyzing the data collected and answering the various research questions presented, I would use mixed methodologies as the method of analysis. “Research in which the investigator collects and analyzes data, integrates findings, and draws conclusions in a single study or program of inquiry using both qualitative and quantitative approaches or methods” (Palinkas et al., 2019). As a result, in this case, I will use both qualitative and quantitative data in the study to help better understand the covid reporting situation in various state hospitals. There are research questions that will be answered using data collected from other sources, allowing for a better understanding of how other countries carry out reporting activities. The data provided will provide a better picture of how the states are performing and, by analyzing the data, will provide a better picture of the hospital state and the various improvements that need to be made. As a result, getting answers to the research questions posed and conducting a better analysis of the information shared will be aided.
Reference
J. Cai, A. Morris, C. Hohensee, S. Hwang, V. Robison, M. Cirillo,… and J. Hiebert (2019). posing important research questions 114-120 in Journal of Research in Mathematics Education, 50(2).
Healthdata.gov. (2020). (2020). COVID-19 Hospital Reporting – Status of State Certification | HealthData.gov. Tyler Insights & Data https://healthdata.gov/Hospital/COVID-19-Hospital-Reporting-State-Certification-St/gskt-tzcc/data
L. A. Palinkas, S. J. Mendon, and A. B. Hamilton (2019). Mixed methods Assessment innovations. 40, 423, Annual Review of Public Health.
