Sisense Case Studies Analyzing Data Quickly to Make Medical Breakthroughs

Edit This Case Study Record

	Analyzing Data Quickly to Make Medical Breakthroughs Sisense

Analyzing Data Quickly to Make Medical Breakthroughs

Sisense

Technology Category	Application Infrastructure & Middleware - Data Visualization Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics
Applicable Industries	Healthcare & Hospitals
Applicable Functions	Quality Assurance Business Operation
Use Cases	Predictive Quality Analytics Process Control & Optimization
Services	Training System Integration
Challenge	The Arizona Department of Health Services faced significant challenges in quickly analyzing data from newborn screenings. The process was labor-intensive and relied heavily on Excel spreadsheets, making it difficult to identify trends and quality issues in a timely manner. This delay in data analysis could lead to serious health consequences for newborns, as early detection and treatment of disorders are crucial. The department needed a more efficient and user-friendly solution to manage and analyze the data effectively. Read More
About Customer	The Arizona Department of Health Services is a state agency dedicated to improving the health and wellness of all Arizonans. They partner with public and private entities to collect and analyze health data, including newborn screenings for 28 blood disorders. The department handles data from over 90,000 newborns annually, working closely with hospitals across Arizona. Their mission is to ensure timely and accurate health information is communicated to physicians, hospitals, and parents, enabling early detection and treatment of potential health issues in newborns. Read More
Solution	The Arizona Department of Health Services adopted Sisense to address their data analysis challenges. Sisense provided an easy-to-use platform with simple dashboards and interactive data drilling capabilities. This allowed the department to analyze data immediately and identify quality issues quickly. The onboarding process was straightforward, with training and online resources available to help staff get up to speed. Sisense enabled the department to automate data loading and analysis, eliminating the need for manual data preparation and reducing the reliance on Excel spreadsheets. The tool went live in just a day, and within a week, the IT team was able to start development work and share prototypes with stakeholders. Read More Log in to view content
Contents

Technology Category

Application Infrastructure & Middleware - Data Visualization

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Applicable Industries

Healthcare & Hospitals

Applicable Functions

Quality Assurance

Business Operation

Use Cases

Predictive Quality Analytics

Process Control & Optimization

Services

Training

System Integration

Challenge

The Arizona Department of Health Services faced significant challenges in quickly analyzing data from newborn screenings. The process was labor-intensive and relied heavily on Excel spreadsheets, making it difficult to identify trends and quality issues in a timely manner. This delay in data analysis could lead to serious health consequences for newborns, as early detection and treatment of disorders are crucial. The department needed a more efficient and user-friendly solution to manage and analyze the data effectively.

About Customer

The Arizona Department of Health Services is a state agency dedicated to improving the health and wellness of all Arizonans. They partner with public and private entities to collect and analyze health data, including newborn screenings for 28 blood disorders. The department handles data from over 90,000 newborns annually, working closely with hospitals across Arizona. Their mission is to ensure timely and accurate health information is communicated to physicians, hospitals, and parents, enabling early detection and treatment of potential health issues in newborns.

Solution

The Arizona Department of Health Services adopted Sisense to address their data analysis challenges. Sisense provided an easy-to-use platform with simple dashboards and interactive data drilling capabilities. This allowed the department to analyze data immediately and identify quality issues quickly. The onboarding process was straightforward, with training and online resources available to help staff get up to speed. Sisense enabled the department to automate data loading and analysis, eliminating the need for manual data preparation and reducing the reliance on Excel spreadsheets. The tool went live in just a day, and within a week, the IT team was able to start development work and share prototypes with stakeholders.

Impact #1	Sisense allowed the Arizona Department of Health Services to automate data analysis, speeding up the process and ensuring no data was out of date.
Impact #2	The tool enabled staff to focus on their core responsibilities rather than struggling with data preparation and analysis in Excel.
Impact #3	The department could now run quality analysis daily, identifying trends and inconsistencies in newborn screening data more efficiently.

Impact #1

Sisense allowed the Arizona Department of Health Services to automate data analysis, speeding up the process and ensuring no data was out of date.

Impact #2

The tool enabled staff to focus on their core responsibilities rather than struggling with data preparation and analysis in Excel.

Impact #3

The department could now run quality analysis daily, identifying trends and inconsistencies in newborn screening data more efficiently.

Benefit #1	The Arizona Department of Health Services screens over 90,000 newborns annually.
Benefit #2	Sisense was implemented and went live in just one day.
Benefit #3	Within a week, the IT team began development work and shared prototypes with stakeholders.

Benefit #1

The Arizona Department of Health Services screens over 90,000 newborns annually.

Benefit #2

Sisense was implemented and went live in just one day.

Benefit #3

Within a week, the IT team began development work and shared prototypes with stakeholders.

Download PDF Version

Overview

Analyzing Data Quickly to Make Medical Breakthroughs

Operational Impact

Quantitative Benefit