Process Mining - CPA before and after COVID-19

Summary

In this presentation, Angelina Prima Kurniati discusses a study on process mining for clinical procedures before and after COVID-19 in Indonesia. The research explores changes in patient diagnostic processes by analyzing data from Universitas Gajah Mada and Oso BPJS Kesehatan. By comparing patient flows and diagnoses before and after the pandemic, the study highlights key shifts in clinical processes, offering valuable insights into how the healthcare system adapted to new challenges. The presentation underscores the importance of data validation and process mining in improving healthcare workflows and patient care.

Takeaways

• 😀 Angelina Prima Kurniati presents a paper on process mining in the clinical field, focusing on data before and after COVID-19 in Indonesia.
• 😀 The research involves comparing two different sets of clinical data, one from before COVID-19 and the other from after, to understand changes in healthcare processes.
• 😀 A major focus of the paper is on checking the conformance of the available data to see how well it aligns with expected or known standards.
• 😀 The process mining method involves understanding the flow of diagnoses, which is visually represented in diagrams showing the journey of patients before and after COVID-19.
• 😀 Key observations include the impact of COVID-19 on the number of patients, types of diagnoses, and overall clinical process flows.
• 😀 The study shows a significant difference in the number of patients diagnosed before and after COVID-19, with a recorded 170 patients before the pandemic.
• 😀 The research employs models to validate the data and visualize the diagnostic process, including adding additional clues to diagrams to improve accuracy and understanding.
• 😀 The study utilizes a model to demonstrate how the clinical process changed, highlighting the role of diagnostic flow in managing patient data.
• 😀 The presentation includes visual aids such as a video showing the diagnostic process before COVID-19 to help explain the changes more effectively.
• 😀 The research was conducted with the involvement of Universitas Gajah Mada and BPJS Kesehatan, focusing on improving the clinical diagnostic processes post-COVID-19.

Q & A

What is the main focus of the presentation?

The main focus of the presentation is on process mining for clinical data before and after COVID-19 in Indonesia, specifically analyzing the differences in patient diagnosis workflows during these two time periods.

Who is presenting the paper and what is their role?

The paper is presented by Angelina Prima Kurniati, who is sharing insights on process mining in the context of clinical data analysis before and after COVID-19.

What are the two sets of data mentioned in the study?

The two sets of data mentioned are from before the COVID-19 pandemic and from after the pandemic, with the goal of comparing patient diagnostic processes between these two periods.

Why is it important to check the conformance of the two datasets?

Checking the conformance of the two datasets is crucial to understanding how the clinical workflows and diagnostic processes have changed due to the pandemic and to ensure the accuracy of the process mining model.

What role does process mining play in the analysis?

Process mining helps to analyze the clinical data by uncovering patterns and insights in the patient diagnostic workflows, allowing for a better understanding of how these processes have evolved over time.

What does the video demonstrate in the presentation?

The video demonstrates the diagnostic flow for patients before COVID-19, showing key information such as the number of patients involved in different stages of the diagnostic process.

How is the data after COVID-19 different from the data before it?

The data after COVID-19 shows the impact of the pandemic on the healthcare system and patient pathways, which are likely altered due to various factors such as healthcare protocols, patient behavior, and resource limitations.

What additional clues are included in the process diagrams?

The process diagrams include additional clues that help to explain the changes in the diagnostic flow before and after COVID-19, offering more context for how the pandemic has influenced clinical workflows.

How many patients were involved in the dataset before COVID-19?

The dataset before COVID-19 involved 170 patients, as mentioned in the presentation.

Which institutions contributed data to the study?

The data for the study was contributed by Universitas Gajah Mada and BPJS Kesehatan, which are key institutions involved in healthcare data collection in Indonesia.