Healthcare Data Analytics Services

With 30 years of experience working with large data sets, the ADN Data Analytics team can analyze your data to identify patterns, trends and priorities within the clinical, quality, financial and patient safety arenas. We work closely with you to help you achieve a better understanding of your data in order to take action where it can make an impact.

Data Analytics Service Summary

Healthcare organizations are at a pivotal crossroads and, in order to survive and thrive, must harness new clinical data sources if they are going to realize improvements. While the art of quality and patient safety emphasizes clinical judgment, it is ceding ground to the science of improvement, which relies on precisely measured variables to assess opportunities and inform strategy.

We specialize in sophisticated comparison and population matching, evidence-based practices, regulations and requirements, national quality and safety measures, cost and physician attributions, the latest data visualization, predictive analytics and machine learning techniques, as well as a heightened understanding of the relationships between data, processes and outcomes.

Our team possesses the expertise and skills to help your team excel. Our staff includes PhD statisticians, clinicians – Registered Nurses, quality and patient safety experts, data/business analysts, chart abstractors, and SAS, R, Python and SQL programmers. Several members of our team have also served on the boards of directors of the National Association for Healthcare Quality (NAHQ) and the Governor’s Quality Award.

Our Portfolio Includes

Identifying Excess Cost & LOS for Adverse Patient Safety Events

Evaluated the prevalence and financial impacts associated with AHRQ’s Patient Safety Indicators (PSIs).

GI Task Force: Cost/LOS for Surgical Digestive DRGs

Analytics project aimed at reducing cost/LOS for Surgical Digestive DRGs. Our team queried the database of a large hospital and presented findings that identified opportunities as well as completed manual audits of patient charts to identify/rule out causations for excess cost/LOS.

Falls Regression Analysis

Our team evaluated voluntarily reported patient falls from the American Data Network Patient Safety Event Reporting Application to identify those characteristics which increased fall causation and applied machine learning technology to assist in predicting future falls.

Interactive Predictive Performance Tool

Our team of PhD statisticians, data analysts and engineers built an interactive  tool that allows forecasting how improved performance will trend over time, using accurate prediction based on a hospital’s real historical data points (based on the Prophet Forecasting Model).

Financial Impact & Trends of Falls & Meds

Our team linked voluntarily reported safety events from our patient safety event reporting application to financial data in our Clinical Benchmarking System application to identify trends, financial impact, opportunities and make a business case for patient safety by estimating the cost associated with adverse events.

Vent Day Utilization Analysis

ADN worked with a large regional hospital to compare ventilator days in critical care settings across our database, identifying opportunities for reduction in days.

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