En cours

Petek & Associates

Job Description:

Hello,

My name is Robbie McCuistion and I co-own a psychology practice specializing in First Responders. We currently do evaluations to make sure the best officers are hired to become Fire Fighters, Police, Dispatchers, Corrections Officers. This testing is more important than ever! After COVID we had to pivot and change all of our testing protocol from in person to virtual. The canidates start by completing a history questionnaire that we email via our EMR (Simple Practice) in a HIPPA compliant link. The next step is to complete a 90 minute testing process monitored via Simple Practice. The two tests are graded and the results are forwarded to our Psychologists. They compile a list a questions based on these results. The last step is the psychologist conducts a 30min virtual interview with the canidate. The notes from the interview are combined with the test results and history questionnaire and a final report is generated and shared with the hiring team from the department. This process is very cumbersome and involves multiple touch points. A friend of mine is a computer programmer and he helped us generate the attached file on how we could streamline this process using predictive text and some auto features. He suggested using Google Docs. He didn't have time to help us complete the program but suggested this site. We'd love to further the conversation with someone and develop a program to help us make our process more streamlined and cut out human error.

We want the history questionnaire to generate a narrative report based on the canidates responses. The examples in the two Word documents i attached hopefully explain what we want it to do. Basically an if this/than that program. Also it is very important that the information would be sent/received in a HIPPA compliant format.

Best,

Robbie and Alex

Compétences : Google Docs, Microsoft Word, Automation, Process Automation, Python, Architecture Logicielle

Concernant le client :
( 0 commentaires ) lake tapps, United States

Nº du projet : #35883170