Informonster Podcast

Are you tired of dealing with unreliable data that hinders your decision-making process? Join Charlie Harp, the host of the Informonster Podcast, as he explores issues impacting data quality and explains how Simple Assessment Modules (SAMs) function within the PIQI framework.

In the final episode of our Data Quality in Healthcare - PIQI Framework series, Charlie guides you through the intricacies of SAMs which are specialized tests designed to evaluate the quality of your data entities for specific use cases. Discover how these plug-and-play modules can seamlessly integrate into evaluation profiles, allowing you to assess your data against a battery of relevant criteria.

Charlie also explains the concept of evaluation profiles, which establishes a comprehensive framework for measuring and assessing your information entities. You'll learn how these profiles produce quality scores and provide detailed statistics, empowering you to make informed decisions based on reliable data. 

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In the third installment of the Data Quality in Healthcare series, Charlie Harp explores the taxonomy of the PIQI Framework. He breaks down the primary categories of 1.) Delivery and 2.) Intrinsic Issues, and shows how the subcategories a.) availability b.) accuracy c.) conformity and d.) plausibility are used to analyze and address data quality challenges.

Come back for part four where Charlie talks about Simple Assessment Modules (SAMs) and the elegant simplicity of recursive failure. 

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Tune in as Charlie Harp unveils the rationale behind the Patient Information Quality Improvement’s (PIQI) streamlined data model, and explains how it turns complex patient information into an organized format for analysis. The next episode will cover the taxonomy that was used in the PIQI framework to identify the root causes of data issues and provide recommendations for improvement.

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When looking for a practical way to assess the quality of patient information from external sources, Charlie Harp found that existing frameworks were either too general or too specific to certain databases or schemas. So, he created the Patient Information Quality Improvement (PIQI) framework. In the second episode of the "Data Quality in Healthcare" series, Charlie gives a high-level overview of the PIQI framework and shares some use cases for this structure. Tune in as he shares the ultimate goal for the framework which is to enhance the quality of patient information to provide better outcomes and care across the healthcare industry.

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It’s time to take a closer look at healthcare data quality. This episode is the beginning of a series related to the challenges that all healthcare professionals face in gathering, organizing, and using patient data. Join the conversation as Charlie Harp shares how we got to this place as an industry and a solution for measuring the quality of patient information. Listen now to learn about the Patient Information Quality Improvement (PIQI) framework and how it can be used to help healthcare professionals make better informed decisions.

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In this episode of The Informonster podcast, Charlie Harp talks with Janice Kelly, President of AORN Syntegrity, Inc., (Association of periOperative Registered Nurses) with over 25 years of informatics experience. Janice shares how AORN is working to enhance workflows with surgical schedules and perioperative nursing. She also gives insights into how AORN collaborates with healthcare institutions to stay ahead of the curve when it comes to new procedures, CPT codes, and preference cards. 

Charlie and Janice explore the unexpected ways data quality impacts healthcare and how AORN's contributions are helping healthcare professionals maintain the gold standard in procedure lists and standard terminologies. 

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In this episode of the Informonster Podcast, Charlie Harp sits down with Patina Zarcone, Director, and Millie Malai, Technical Project Manager of Datapult, an APHL company. They discuss how Datapult and Clinical Architecture came together to create a system that would get lab data to public health faster, especially during the pandemic. They discuss the impact of this system on the timeliness of data for emerging infectious diseases, and how converting data from CSV to HL7 v2.5.1 was a game changer to ensure that public health received the highest quality data.

About Patina Zarcone
Patina (Zarcone) Gagne serves as the Association of Public Health Laboratories’ (APHL) Director of Datapult, a new APHL company, and has been with APHL approaching 21 years.  When joining APHL in 2003, Patina was the only informatics staff member focused primarily on helping governmental public health laboratories acquire laboratory information management systems.  Today, she is running Datapult, a company that made a major impact on the pandemic by reporting COVID laboratory results electronically to public health.  Prior to her tenure at APHL, Patina worked first in biotechnology as a bench scientist in gene therapy for Biogen Inc., in Cambridge MA then went on to work for the Massachusetts Department of Public Health, State Laboratory Institute helping run operations for the mosquito borne disease surveillance program. 

Patina has an undergraduate degree (BA) in Biology from Boston University and a Master’s Degree in Public Health (MPH), specializing in Health Service Administration also from Boston University.

Patina lives in Newbury, MA right next to the Atlantic ocean with her husband, Joel Gagne Esq. and 4 children.

About Millie Malai
Millie is the Technical Project Manager for Datapult and oversees technical development and implementation across Datapult’s service, including Expanded ELR. She has been in the field of public health informatics for over a decade, with experience in syndromic surveillance systems, laboratory information systems, immunization registries, electronic laboratory reporting, and health data interoperability. She holds a Master of Public Health with a concentration in applied public health informatics from Emory University, Rollins School of Public Health. 

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On this episode of the Informonster Podcast, Charlie discusses the importance of data quality and how it impacts the results of any analysis or decision-making process. He also shares insights from our inaugural survey which indicates that the industry recognizes the importance of data quality but acknowledges that it is a challenging effort.

Download the Data Quality Survey Report here: https://clinicalarchitecture.com/data-quality-survey/ 

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In this episode Charlie Harp talks with Lori Moore, Public Health Analyst and Stuart Myerburg, Informatics Team Lead with the CDC's National Center for Immunization and Respiratory Diseases (NCIRD) group, as they discuss what it’s like managing data around vaccines, the challenges they faced and opportunities they discovered while going through the COVID-19 crisis. 

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On this episode of the Informonster Podcast, Charlie provides a high-level primer on Observational Medical Outcomes Partnership (OMOP). He also discusses terminologies and adding data into an OMOP data repository. To learn more about OMOP please visit ohdsi.org. 

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