PharPoint Research, Inc.’s Post

Hey LinkedIn! If you’re new to following me, I love my job and the industry in which I serve. Lately, I've been talking about a lot of aspects of being in Data Management, CROs, and working from home in a straightforward way. I've started a new fun outlet that allows me to delve into a plethora of industry-specific topics as well as personal/professional experiences: a blog. Https://www.DMinthePM.com Data Management, After Hours! #careergrowth #professionalengagement, #driventosuccess #clinicaldatamanagement. Hop on over to DMinthePM and share your experiences! ✒️

🔍 Understanding Query Management in Clinical Data Management 📊 In clinical trials, making sure our data is accurate and complete is essential. That's where the query management steps in. Here’s a simple guide to what it all means: 1. 🔄 Open Query : This is like an unanswered question. When something in the data doesn’t look right or is unclear, we raise a query. For instance, if a patient’s age is recorded as 150 years, we’d ask for clarification. 2. 📝 Answered Query : Once we get a response to our open query, it becomes an answered query. It means the site has given us more information or corrected the data, but we still need to check it. 3. ✅ Closed Query : After we review the answered query and confirm that everything is correct, we close it. This step makes sure the data is clean and ready for analysis. 4. 🤖 Auto Query : Some systems are smart enough to spot issues by themselves. They raise auto queries based on rules we set up, like flagging unusual values automatically. 5. 👀 Manual Query : Sometimes, we have to rely on our own eyes. Manual queries are raised by us when we notice something off that the system might miss. Example : Imagine you’re managing data for a clinical trial and see that a patient’s weight has dropped dramatically in a week. That’s a red flag, so you’d raise an open query to ask the site to check. They responded, saying there was a typo. You review their answer, find it makes sense, and then close the query. Effective query management is key to good data quality. It’s a team effort between data managers and site staff, ensuring we can trust the results of our clinical trials. Have you had any interesting experiences with query management? Let’s discuss and share insights to keep improving our work! #ClinicalDataManagement #QueryManagement #ClinicalTrials

From Clinician to Data School consultant! 🩺📊 Our Data School consultants join us from many different educational and career backgrounds including one of our newest consultants Samantha Fitzsimmons who has recently transitioned from the healthcare industry to our training program. In her latest blog, Samantha discusses the transferrable skills she's taken into her new career path. Take a read below! https://lnkd.in/ezJeizhv #thedataschool #dataanalytics #datajobs #careersindata

The Clinical Data Manager: Beyond Just Data Review: When most hear the title "Clinical Data Manager", their minds often jump to someone buried in excel sheets and Clinical databases, rigorously ensuring accuracy and completeness. And while that's a part of the picture, it's akin to seeing just the tip of an iceberg. The role, in its entirety, is a delicate blend of technical prowess, meticulous attention to detail, and leadership finesse. To many, data is just numbers and facts, black and white with no shades in between. But in the realm of clinical research, data tells a story—a story of patient journeys, of therapeutic breakthroughs, and sometimes, of the paths less traveled. Over nine enriching years in this domain, my initiation into this role began with the basic premise of reviewing data. It was a task-oriented start, where the immediate objective was to ensure consistency and accuracy. But as days transformed into years, I realized that being a Clinical Data Manager was not just about handling data but about understanding its very soul and purpose. Every drug trial, every patient cohort, every anomaly in data patterns taught me something new. From understanding the core sections of the protocol to discerning unobvious patterns during data review, my journey saw me evolve from being just a data reviewer to someone who viewed data as a canvas, ready to paint a coherent picture that would eventually contribute to medical advancements. It wasn't just the technical skills that were honed over time. The role demanded a constant interplay of soft skills—communication, negotiation, and above all, leadership. It was about ensuring that the data's story was told right, about guiding a team to see and interpret the story just as vividly, and about standing firm when data integrity was at stake. In essence, being a Clinical Data Manager is akin to being the guardian of a narrative, one that has the potential to revolutionize healthcare. It's a journey that's not just about numbers but about people, innovations, and the relentless pursuit of excellence. As we delve deeper into this series, I'll share more about the facets of this role and the myriad lessons I've garnered. Stay tuned. #ClinicalDataManagement #BeyondDataReview #MyJourney #30DayWritingChallenge #articles #linkedin #ClinicalResearch

Stop Waiting, Start Doing: If You're Waiting for Permission, You're Doing It Wrong You don't need external validation or permission from established professionals, employers, or recruiters to start or progress in data analytics. Seeking external validation can delay or hinder your journey. Instead, develop an action bias: • Line up projects that provide value, build them in public and talk about the value you provided often. 📈 • Get feedback. Improve. 📝 • Grow in directions useful to you and others. 🌟 #datajobs #datacareers #dataanalytics

As the life science industry becomes increasingly data-driven, the field of clinical data management (#CDM) is expanding, offering a wealth of career opportunities for those interested in leveraging data to improve patient outcomes and healthcare processes. In this article, we look at 9 #careerpaths within clinical data management, highlighting the key purpose of reach role. https://buff.ly/3VJ8YoW #lifesciencejobs #clinicaldatamanagement #cdmjobs #datajobs

As the life science industry becomes increasingly data-driven, the field of clinical data management (#CDM) is expanding, offering a wealth of career opportunities for those interested in leveraging data to improve patient outcomes and healthcare processes. In this article, we look at 9 #careerpaths within clinical data management, highlighting the key purpose of reach role. https://buff.ly/3VJ8YoW #lifesciencejobs #clinicaldatamanagement #cdmjobs #datajobs

As the life science industry becomes increasingly data-driven, the field of clinical data management (#CDM) is expanding, offering a wealth of career opportunities for those interested in leveraging data to improve patient outcomes and healthcare processes. In this article, we look at 9 #careerpaths within clinical data management, highlighting the key purpose of reach role. https://buff.ly/3VJ8YoW #lifesciencejobs #clinicaldatamanagement #cdmjobs #datajobs

Do you ever feel like your #data is trying to pull a fast one on you, like you're about to fall backwards and no one is there to catch you? Fear not! Syniti's blog post on trusting your data is here to save the day. Say goodbye to trust falls and hello to confident decision-making. #Syniti #DataThatIgnites

Do you ever feel like your #data is trying to pull a fast one on you, like you're about to fall backwards and no one is there to catch you? Fear not! Syniti's blog post on trusting your data is here to save the day. Say goodbye to trust falls and hello to confident decision-making. #Syniti #DataThatIgnites