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Healthcare Analysis with Power BI

1. Healthcare Analysis with Power BI

Hello! My name is Lyndsay, and I'll be your instructor for this case study.

2. What is a case study?

A case study is an opportunity to put your Power BI skills into action. You’ll apply the skills you learned in previous courses and practice them on a real-world problem. Here are some of the prerequisite courses that we recommend before completing this case study.

3. Case study goals

In this case study, a fictitious consulting company called HealthStat has hired you to uncover insights on potential hospital efficiency opportunities. By the end of this course, you will successfully analyze a state-wide hospital dataset and leverage your Power BI skills to create an engaging dashboard of insights.

4. Framework for healthcare quality

In healthcare analytics, quality metrics are often classified across these six domains. For this case study, we'll be focusing on efficiency, which is all about avoiding waste. This includes minimizing waste of equipment, supplies, ideas and energy.

5. Measuring Hospital efficiency

Length of stay (or LOS) is considered an important indicator of the efficiency of hospital management. It's calculated as the total duration in days for a patient stay in hospital. A shorter LOS is often desirable in hospital operations. Primarily, shorter LOS means costs can be lowered. Reducing LOS can also release capacity in the system and improve throughput, enabling hospitals to serve more patients. Many factors can impact LOS. Patient age, health status, the type of procedure (or surgery), whether or not there were any complications, and the size of the hospital are some common factors.

6. Terminology overview

Here are some terms you will encounter throughout this case study: An inpatient is a person who has been admitted to a hospital bed. A discharge, is defined as the release of a patient from hospital care by a medical worker. Disposition, is the patient destination or status upon discharge, for instance to another facility or to home. An elective surgery is a procedure that was planned in advance, in other words, it was not due to an emergency.

7. Patient population for analysis

In this case study, the focus is on patients who received hip replacement surgery. Here's a bit of a background on what this procedure is all about. Patients with hip pain, typically arthritis, may require elective hip replacement surgery. In this procedure, damaged bone and cartilage is surgically removed and replaced with prosthetic components. Hospital stay can range from 0 to 2 or more days.

8. The dataset

For this case study, we will be working with a dataset that includes New York state-wide hospital discharge data for a year. Elective hip replacement surgery was the main reason for their hospital stay. The dataset is one single table with 30 columns Each row in the dataset represents a single inpatient stay, from their admission to discharge date. The health information in this dataset is not individually identifiable. This means the file does not contain personal health information.

9. Dataset outcome attributes

The dataset has some key attributes to analyze efficiency. Length of stay measured in total days Total costs attributed to each hospital stay.

10. Dataset explanatory attributes

Listed here are some of the key attributes of interest for the case study. These include a unique identifier for facility, a grouping of patient age, patient's disposition, the diagnosis description, severity of illness, and risk of mortality. We will closely evaluate these (and others) in the case study as we work to understand what factors impact length of stay and related costs.

11. Your final deliverable

Your final deliverable for this case study will be to create a dashboard that enables your stakeholders to: Progress through key insights in a logical flow, View informative, concise visuals Get data they need to make business decisions for improving efficiency.

12. Let's start analyzing!

It's time to check your understanding of terms introduced so far. Let's start analyzing!