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What is MAISi?

Traditionally, the oversight of clinical trials at investigator sites has been a burdensome process, reliant on either the management of multiple shared spreadsheets or the high costs associated with software that often lacked relevance to the Australian setting. MAISi marks a significant advancement in this domain. Initially developed in 2001 as a data repository for clinical trials at a leading hospital, MAISi has evolved into a sophisticated workflow application aimed at optimizing various functions within research units. Acting as a centralized information hub, MAISi organizes data related to studies alongside the business units responsible for their management. This organized framework enhances the decision-making processes for management. Team members within each unit can access relevant information concerning their specific studies, patients, investigators, and study teams, while those with elevated access rights, such as Financial Officers and System Administrators, have the ability to retrieve detailed information across all units. Moreover, this efficient access not only fosters collaboration but also significantly boosts overall operational effectiveness, making MAISi an indispensable tool in modern clinical trial management. With its user-friendly design and tailored functionalities, MAISi is poised to redefine how clinical research is conducted in Australia.

What is MAISY Database?

The MAISY databases, launched in 1995, initially tracked the energy consumption of 10,000 utility clients in both commercial and residential sectors across the United States. Over the years, these databases have been updated annually, leading to the creation of the 2020 MAISY databases, which now encompass current energy consumption data and hourly load profiles for more than 7 million individual utility customers nationwide. Each entry in these comprehensive databases includes detailed information about the building characteristics, equipment types, operational practices, occupant demographics, and specific energy usage of the utility clients. The development of these hourly load profiles has been supported by a diverse array of data sources, such as utility companies, industry trade groups, governmental statistics, proprietary surveys from Jackson Associates, and thorough engineering evaluations of appliances. These databases not only provide a statistically valid representation of residential and commercial utility consumers across the country but also enhance the reliability and applicability of energy analysis and planning. The breadth of data contained within allows researchers and policymakers to gain deeper insights into energy consumption patterns and trends across various sectors, promoting more effective energy management strategies. Through this ongoing evolution, the MAISY databases continue to serve as vital resources for understanding the complexities of utility energy consumption.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

Windows

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Agile Health Computing

Company Location

Australia

Company Website

www.agilehealthcomputing.com

Company Facts

Organization Name

Jackson Associates

Date Founded

1995

Company Location

United States

Company Website

www.maisy.com/maisydatabases.htm

Categories and Features

Clinical Trial Management

21 CFR Part 11 Compliance
Document Management
Enrollment Management
HIPAA Compliant
Patient Database
Recruiting Management
Scheduling
Study Planning

Categories and Features

Database

Creation / Development
Data Security
Database Conversion
Mobile Access
NOSQL
Performance Analysis

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