MDNet vs Learn to Talk to Learn

EHI’s EHR is the most advanced Electronic Health Record application for Providers to help ease adoption challenges with simple and intuitive Touch-Based user interface and integrated with cloud based Voice Recognition and Telehealth. Our new and improved EHR application will provide Real-Time analytics of a Patient at the point of service to improve care and meet payer based compliance requirements and performance measures to earn bonus. EHI EHR is a truly integrated application that connects all care givers and allows them to exchange data in Real-Time and Provides a global view of a Patient clinical data.EHI helps on-the-go physicians take care of patients and improve outcomes through awareness and timely decision making using our Mobile EHR. Highly scalable, EHI’s EHR is the right choice for multi-site as well as multi-specialty organizations.

Learn to Talk to Learn will help improve your vocabulary. *An entity is one of Sentence, Word or Number*. The speech recognition engine will evaluate what was spoken and automatically shuffle the list of entities to display the next entity. The 'Speak' feature will help understand how to pronounce the entity if need be. An optional 'Skip' feature provides the leverage to force a shuffle (Configurable via the Settings cogwheel). Stats record each and every spoken entity and calculate the successes / failures while reading individual entities. The stats list is sorted Failure first to encourage focusing on specific entities. How to use the app? 1. Once the splash screen is not visible anymore, the first screen of the application shows 'Numbers', 'Words' and 'Sentences. The 'Words' list contains Alphabets, Two Letter Words....Twenty Four Letter Words, the 'Numbers' list contains numbers starting from 0 through a configurable limit and the 'Sentences' list contains sentences starting from Two word sentence, Three word sentence through Twenty word sentence. 2. Upon clicking the entity types, the entity would show up one by one with three options: a. For the user to pronounce the entity. b. For the speech engine to speak the entity so user can understand how to pronounce the entity. c. Skip the entity using the Skip button at the bottom of the screen. * Entities read and recognized successfully on this screen count as a 'Success' and Skipped entities count as a 'Failure'. The Success/Failure state will be used while computing Stats (Available on the Home and Words screens at the top right of the navigation bar) 3. The Skip button can be hidden, if needed, and is configurable via the Settings cog wheel displayed on the right hand side of the navigation bar of the entity type screens. Tracking performance (As a measure of progress over time): Performance is measured as a metric of Success/Failure while reading successfully/skipping the entities on the entity type screens. 1. Tap the 'Stats' button on the navigation bar of the home screen. 2. The 'Stats' screen displayed will list an 'Overall' metric along with metrics for the entities. Drilling down, the numbers would list the stats for each number, the words would list the stats for all word types (Alphabets...24 letter words) and the sentences would list the stats for all sentence types (2 word sentences, 3 word sentences...24 word sentences). Along side each entity type would be listed the number of Successes/Failures which will be useful while deducing the entity types where additional effort needs to be put in. 3. Clicking on the word type (Any of Alphabet....24 letter words) displays an 'Overall' metric along with metrics for the word/s under that word type. For Alphabets, this would be A...Z. For 2 letter words, this would be words that have 2 characters in them (AT, BY...). Along side the word type would be listed the number of Successes/Failures which will be useful while deducing the 'word/s' where additional effort needs to be put in to pronounce the word/s with more clarity. 4. Clicking on the sentence type (Any of 2 word sentences....24 word sentences) displays an 'Overall' metric along with metrics for the sentence/s under that sentence type. For 2 word sentences, this would be Very good....Too good. For 3 word sentences, this would be sentences that have 3 words in them (Very well done, Laugh out loud...). Along side the sentence type would be listed the number of Successes/Failures which will be useful while deducing the 'sentence/s' where additional effort needs to be put in to pronounce the sentence/s with more clarity. *An entity is one of Sentence, Word or Number*