This case study analyzes the average cost per patient and length of stay for elective hip replacement surgeries in New York State. The case study was done in a remote simulation of Power BI so I am not able to share the project itself so I have taken screenshots which I will place below.
Here you can see the homepage I created for this report. Below the logo for the fictional consulting company this report is for, there is the title of the report and 4 page navigation buttons.
The first page of the report itself is an analysis of the average length of stay. The same navigation buttons are on the top of each page. Below the company logo there is a slicer to allow the user to select specific health service areas to show the statistics for that region. Below the navigation buttons are four card visuals showing the total number of surgeons, average length of stay in days, the total number of hospitals, and the total number of patients discharged in the data set for the selected area. There is also an analysis of the key factors influencing the average length of stay. Prominantly displayed is a line and clustered columns chart showing the total number of patients discharged and the average length of stay for the top 15 hospitals by number of discharges. Finally there are the 3 hospitals with the highest and lowest length of stay for the selected area.
The next page analyzes the average cost per patient to the hospitals. The same slicer is on this page to allow the user to select different health service areas. There are also 4 card visuals on this page, this time showing the average length of stay in days, the average cost per discharged patient, the total number of hospitals, and the total number of patients discharged in the dataset for the selected area. Like the last page there is an analysis of key influencers contributing to the statistic. This time there is a scatter plot showint the average length of stay compared to the average cost per discharge with each dot representing a hospital, colour coded by health service area, with the size of the dots representing the total number of discharged patients at that hospital. Finally this page also shows the top and bottom three hospitals in the selected area using bar charts.
The final page of this report is a dashboard profiling the individual hospitals. This time the slicer selects specific hospitals by name instead of health service area. There are six visuals. First there are guages showing the average length of stay and cost per discharged patient for the selected hospital compared to the average for the state as a whole. Next there are clustered column charts showing the total number of discharged patients by the severity of their illness and the risk of mortality for their procedure. Finally there are two donut charts showing the total number of patients discharged divided by the diagnosis leading to the surgery and the patient disposition which is a record of where the patient went after being discharged.