Better Healthcare Decisions with AI
Whether it’s processing the wealth of data from a clinical trial, or leveraging patient historical data to improve healthcare decision-making process, AI and machine learning can benefit all parties in the healthcare value chain.
dotData’s 100% automated solution helps insurance providers by minimizing churn and maximizing customer lifetime value. dotData’s automated machine learning and data science automation solution helps payers build predictive models that can accurately identify customers who are likely to leave or uncovering insights on pricing, quality of service or managing proper patient healthcare by preventing adverse outcomes while reducing costs for the entire value chain.
Whether it’s managing fraud, minimizing costs, expediting claim processing or effectively managing customer care, AI models built with dotData’s automated solution can provide insurers and payers with an ideal, affordable model for benefitting from data science.
From improving patient outcomes to modeling cost reductions that don’t sacrifice the quality of service, leveraging machine learning and AI to model the healthcare process can be a boon to both large and small healthcare service providers alike. dotData can help accelerate 100% of the data science automation process to assist with anything from predicting hospital admission rates, to identifying patients that are at risk of healthcare-associated infections (HAI).
Because dotData automates 100% of the data science and AI process, benefiting from operational efficiencies, healthcare providers of any size can achieve better forecasting of patient inflow or managing staffing needs. Whether you are a single location or multi-location, multi-state healthcare provider, dotData can help accelerate your data science process and provide improved efficiencies and cost reductions to maximize your patient care and welfare.
2019 research data from the Massachusetts Institute of Technology showed that only 13.8% of drugs successfully pass clinical trials. Against this harsh reality of failure stands the equally high cost of conducting a clinical trial, which can cost upwards of $2 Billion to complete FDA approval. Pharmaceutical companies are leveraging AI and machine learning for critical use-case like predicting drug components that might be more likely to lead to success or predicting the effects of new treatments on patients.
dotData helps pharma companies by providing a fully automated means of leveraging in-house data to shorten clinical trials, accelerated approval processes, and reduce costs of innovations by modeling trials before they happen.
Healthcare Use Cases for AI & Machine Learning
Forecasting and managing admissions
Regardless of the size of your healthcare facility, forecasting and preparing for fluxes in admissions can be a costly proposition.
Whether it’s modeling patient levels using historical data or minimizing the readmission process by modeling probable causes, dotData can help healthcare organizations maximize efficiencies and significantly reduce the cost of operations by modeling causal relationships between critical events and patient levels and patient readmission problems.
Prediction of High-cost services
dotData’s 100% data science automation platform makes creating models based on historical data fast, simple, and intuitive, regardless of the size and scale of your operation.
Whether it’s usage of high-cost centers like your Intensive Care Unit, or predicting the effects of improved efficiencies in managing soaring emergency room costs, dotData can help healthcare companies leverage AI and machine learning to model which patients are in need of higher-cost care and which resources can be optimized to lower costs without sacrificing quality of service.
Hospital Acquired Infections cause significantly increased risk to the patient and are a grave concern to healthcare organizations that must dedicate resources to the management and care of patients to guard against HAIs.
Whether it’s due to problems during medical procedures, infections of wounds post-surgery, or through person-to-person contact, HAIs can be life threatening and costly to manage.
dotData can help you model the causes of HAIs and predict the procedures and processes that are most likely to be beneficial in reducing the risk of contracting HAIs and of treating them successfully when they happen.
Medication adherence monitoring
According to the Kaiser Family Foundation, 29% of patients in 2018 reported not taking their medications due to cost concerns.
Whether it’s affordability or behavioral issues, non-adherence to prescribed medications leads to over 100,000 deaths and over $100 billion per year in increased healthcare costs. dotData can help you leverage AI and machine learning to predict at-risk patients, whether it’s because of as of yet unforeseen financial problems or because of potential behavioral issues that you can impact with closer patient monitoring.
Identifying the stresses and inefficiencies of a healthcare process can lead to significantly reduced costs through better use of resources and a more targeted approach to the deployment of care where small changes can produce significant outcomes.
dotData can help you create targeted profiles of patient needs so that you can more accurately target your resources to those that are in the greatest need and likely to get the most significant benefit.
dotData helps Pharma companies by providing a data science automation platform that helps manage 100% of the process – from the collection of data to the creation of features that will be the basis of your machine learning models.
Whether your goal is to maximize the chances for success in developing a new drug, or to create better efficiencies in your supply chain and operations, using your data to build predictive models of your Pharma practice leads directly to increased capabilities, reduced costs, and greater success.
According to the National Healthcare Antifraud Association, , healthcare fraud costs the US over $68 Billion a year.
The cost of investigating fraud can be exorbitant and is often an exercise in frustration. dotData can help both providers and caregivers in identifying high-risk use-cases where fraud is more likely to occur and can help create models of care and resource utilization to minimize fraud in the first place and to correct the problem when it happens.
The Right Product for the Right User
Start by selecting the product you need, based on your environment, your use-case and your need to “get dirty” with the details of your data science workflow.
AutoML 2.0 & Data Science Automation
Leverage a full GUI experience to automate as much of your data science workflow as necessary. Empower citizen data scientists and data scientists alike.
How dotData Helps Healthcare Companies
Regardless of the size of your organization, if you manage data in the healthcare business, leveraging data for predictive analytics and AI is a reality with which you must deal. dotData can help you automate the process and achieve results:
Chief Data Officers
Get projects out of the lab
Automated machine learning and data science automation can boost the productivity of your data science team and enable an entire new class of users. dotData helps your team automate the 80% of the work that happens before the machine learning modeling with the only AutoML solution that can help automate the entire life-cycle. From accelerating data processing, feature engineering, model selection to integration into production environments, dotData can help shorten months-long projects into days.
Chief Data Scientists
The tools your team loves, without headaches
dotData’s award-winning automated machine learning and data science automation technology accelerates model development across the full data science life-cycle. dotData provides rapid feature engineering and accelerates ML model development. Automation expedites the development of models while giving your team insights they could have never gained manually.
Chief Information Officers
Data science without the headaches
More than 96% of data science projects never leave the lab. For most healthcare CIOs, the problem is not a lack of data; it’s how to best use data to solve business problems that impact healthcare businesses. Forrester called dotData “…AI’s best-kept secret…” because it allows your team to scale performance by providing your data science teams an automation tool they love in the coding environments they love.
AutoML 2.0: Data Science Automation Accelerates Your Business
Scaling a data science practice is challenging, time-consuming, and expensive. With Automated Data Science, you can empower data analysts, software engineers, and BI professionals to build and benefit from predictive models. Through Data Science Automation, you can embed models into applications seamlessly, while freeing up the time of your data science team to be more productive.
BI & Data Analysts
Unlike traditional AutoML systems that require users with in-depth knowledge of data wrangling and constructing feature tables, dotData automates 100% of the data science process. With dotData and minimal training, your BI team and data analysts can quickly learn to contribute to your ML and Enterprise AI initiatives, freeing precious resources and accelerating time to market for your AI & ML initiatives.
Data scientists spend 80% of their time in wrangling with data and constructing complex feature tables. By automating the entire workflow, you can liberate your data science team from the mundane tasks associated with data science and give them the power to provide tangible value to your business in a scalable, seamless manner that is not possible with hand-coded approaches or traditional AutoML platforms.
IT & Software
Integrating your AI and Machine Learning models into production environments is a crucial step in deriving value from your Enterprise AI projects. dotData gives your IT and engineering teams a seamless API-based integration model that enables Continuous Deployment and makes deploying and maintaining models fast and straightforward.
Executives and Line of Business
Giving executives and line of business leaders insights into the Machine Learning and Enterprise AI process provides the transparency and line of sight needed to keep projects moving and provide discernible ROI and value for the organization.