Predicting Hospital Readmission Rates

Posted on Jan 8, 2023

Predicting hospital readmission rates for patients with diabetes is an important task as it can help healthcare providers identify high-risk patients and intervene before a readmission occurs. Β In this blog post, we will discuss the use of different modeling techniques for predicting hospital readmission rates for patients with diabetes.

The dataset could be found on Kaggle which reveals hospital readmission data From multiple hospitals for patients from 1998 to 2008. Some work had to be done before applying different predictive models. This included some data wrangling for missing chunks of data, developing heat maps to identify features with positive influence over readmission rates, and build revised datasets.

Logistic regression is a widely used statistical method for predicting binary outcomes, such as whether or not a patient will be readmitted to the hospital. In the context of predicting hospital readmission rates for patients with diabetes, logistic regression could be used to predict the probability of readmission based on a variety of factors, such as age, gender, past medical history, and medications.

Random forests are an extension of decision trees that build multiple decision trees and combine their predictions to make a final prediction. This can result in improved accuracy compared to a single decision tree. In the context of predicting hospital readmission rates for patients with diabetes, a random forest could be used to identify the most important factors that predict the likelihood of readmission and make a more accurate prediction compared to a single decision tree.Β Gradient boosting is a machine learning algorithm that works by creating a series of weak models and combining them to make a single strong model.

Some key takeaways are that patients are more likely to Β be readmitted if they were inpatients for at least 1 full day. Age played a factor for age groups over 40. Patients that took more than 1 daily medication had higher readmission rates compared to those that don't. Random Forest had the highest accuracy when compared to other modeling techniques most likely from our data source not having multiple linear relationships from the available features.


Overall, logistic regression, decision trees, random forest, and gradient boosting are all useful algorithms for predicting hospital readmission rates for patients with diabetes. Each of these algorithms has its own strengths and limitations, and the best approach will depend on the specific characteristics of the data and the goals of the analysis. Some future work in the project could include diagnosing admission types, BMI data on patients, and a different compilation of features used to train these algorithms.


<a href="">Image by starline</a> on Freepik

About Author


Hey everyone, my name is Erjon Brucaj and I originally studied chemical engineer. I worked as an engineer for a few years before decided it wasn't the career path for me. I've always enjoyed developing solutions to problems...
View all posts by Erjon >

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI