Learn How to Become a Healthcare Data Analyst with This Guide

today I'm going to try and do something that I don't think has been done before I'm going to try to create a healthcare data analyst roadmap now it's impossible to be an expert in everything in healthcare there's so many different places that you can work and so many different types of data so I'm going to try and simplify things a little bit and hone in on the most common type of data analyst in healthcare and that's data analysts that work directly with patient or clinical data to improve the outcomes of patients in a hospital or clinic let's get started the first step in this process is Step Zero and in this step you're just trying to figure out if data analytics and Healthcare is right for you there's just two questions that you need to figure out here the first question is what do data analysts and Healthcare even do the second question is does this seem like something I would want to do for a living I won't spend a ton of time talking about this because I have videos about these subjects already and I'll drop those in the description below but at a high level my work typically consists of meeting with managers of various service lines to figure out their requirements for a report and I'll write some code in SQL to pull up a data set and then I'll plug that data into a data visualization tool like Tableau or power bi to make sense of that data the work that me and other analysts do in healthcare is really rewarding because it improves patient lives it's an industry that's growing really rapidly the pay is really good and it's super fun but it's not without its pain points Healthcare has many rules and regulations so you can expect to see tight deadlines every now and then and there's a lot to learn when you're first starting out so once you've weighed the pros and cons we can proceed to step one which is developing your hard skills this phase is all about developing the technical skills that you need to hit the ground running when you become a data analyst the two tools that I personally use the most in my job are SQL and Tableau or power bi just about every hospital is going to have a database of some sort where they store patient data survey data research data among other things SQL is a tool that you use to query that data out of the database there's tons of free resources out there for you till we're in SQL online but my favorite resource is sqlzoo.net I will also be releasing videos in the near future about how to set up your own SQL database on your own computer after you understand the basics of SQL you should move on to learning a data visualization tool like Tableau or power bi you data visualization to take raw data and transform that into graphs tables figures dashboards things that will basically make sense of your data and this is the part that I love the most between Tableau and power bi personally I prefer Tableau because I think it's easier to use but Power bi is also great too I actually already have a couple of Tableau tutorials on my channel already including a tutorial where I cover how to build an emergency room dashboard so check that out if you haven't already the other tool that you're going to need to know is Excel it's sort of like the Swiss army knife of data analytics and that it does just a little bit of everything just about anyone that works with data knows how to use Excel and you can do a lot of things with it like basic data analysis to creating graphs at the very least you should know how to build some basic graphs in Excel and also know how to build if statements pivot tables and also how to use aggregate functions like sum or account now you might be thinking Josh what about out R what about python well here's the thing about these programming languages these tools are great for doing a wide variety of things like doing Advanced Data visualization that you couldn't do in Tableau or power bi doing Predictive Analytics automating certain processes but in my eight years being a data analyst in healthcare I don't really use python or R very often when I'm not in meetings I'll probably spend 60 percent of my time in SQL 25 of my time in Tableau 10 of my time in Excel and maybe five percent of my time in Python and that's a really generous estimate when I have used python or art in my work it's been for things like importing Excel files into SQL forecasting patient volumes using machine learning or creating data pipelines that move data from one environment to another a process called ETL these use cases are pretty rare for me and the majority of my data analyst colleagues are not that familiar with python or R but if you do eventually learn them you will be assigned to some really cool projects in your career so it's definitely worth pursuing but for now I want you to focus on SQL Excel and Tableau I would learn python or R after you've landed a job and started to get really comfortable with those three tools that I mentioned now you might be asking how do I know when I'm ready to succeed in a data analyst role well I would say that you're ready when you can start developing your own portfolio entries unprompted by tutorials now tutorials can be really great when you're trying to build your foundational skills but at some point you need to build them on your own and when you can do that that's when you're ready this leads me to step number two I want you to build a tableau or power bi portfolio of at least three items it would be ideal if you could find some subjects that are relevant to Public Health or health care if you're not sure where to start I do have a video where I talk about some of my favorite data sets that are relevant to the industry as well as some portfolio ideas to get you started so check that out if you haven't already now what you can do to make these portfolio entries even better is if you can incorporate SQL into those Tableau or power bi dashboards in some way and I recommend this because you're going to be doing this all the time as a data analys but if you don't know how to combine those two things yet that's okay I'm going to have more videos about that in the future now before we go any further I do have an exciting announcement to make I'm going to be working on two courses where I teach you the skills that you need to become a data analyst in healthcare I'm going to be developing this on a website over the next several months if you want to know when those classes will become available or if you have feedback for what I should include in those courses send me an email I'm going to leave my address in the description down below after you build your portfolio I want you to move on to building some domain knowledge in healthcare and I don't care if you're a clinician or someone who studied Public Health in school or maybe you have no background at all in healthcare I still want you to build domain knowledge the first and easiest way you can do that is by subscribing to my channel because I'm going to have so much more content like this in the future but for now I'm going to give you a study guide on some of the most essential things that you should know for each of my recommendations I'm going to drop a link in the description below as you're learning these things just keep in mind that you don't have to be an expert in these things in fact I have plenty of colleagues that got data analyst roles in healthcare without any prior health care experience or knowledge but it will be a little bit easier for you to land a job if you're at least a little conversant in some of these subjects first up is Healthcare coding Concepts you should be aware that in hospitals or clinics patients are often going to be diagnosed using something called an icd-10-cm code so if you go to the doctor and you have a fever you might be assigned to the ICD-10 code are 50.9 which represents a fever and if that fever was the result of something like mononucleosis then you might get an additional ICD-10 code like b27.90 it's not uncommon for a single patient to generate hundreds or thousands of these codes throughout their lifetime so do not try to memorize any of these just be aware that this is a thing in healthcare and that data analysts like me will use I ICD-10 codes to figure out the volume of patients for a certain medical conditions there's other codes that I often use in healthcare like ICD-10 PCS which are procedure codes in the inpatient or hospital setting there's CPT codes and there's other codes that I'll list here but I very rarely use them if at all the next thing that I want you to be familiar with is basic concepts Healthcare quality I looked at dozens of postings for data analyst positions in healthcare and more than half of them talk about either quality or process Improvement somewhere in the description of that job let's talk about that the sole reason that Healthcare exists is to treat its patients it used to be that Healthcare institutions were run like a machine where every service that was rendered for the patient was rewarded financially and quality and patient safety was yeah more of an afterthought that trend has now been shifting over the past couple of decades where Healthcare institutions are penalized for care that does not meet certain standards so now Healthcare quality is being tracked just about everywhere to some extent and there are hundreds if not thousands of metrics that are being developed to track Healthcare quality so rather than knowing all of these metrics which is impossible what I want you to do instead is learn these fundamental concepts in healthcare quality you should be aware of septi which is a model for healthcare quality and what that stands for is patient care is safe efficient patient-centric timely effective and Equitable this is also known as the six domains of healthcare quality and usually my reports are going to be influenced by at least one of those domains you should also be aware of Donna bedian's model the idea behind this is that quality metrics and Healthcare can often be lumped into one of three categories you have structure measures process measures and outcome measures structure deals with the resources or training that is available within the hospital for example have our surgeons been trained on the proper technique to prepare our patients for surgery these structure measures are going to influence your process measures process measures look at how often or how closely did we follow evidence-based guidelines that will influence the outcome measures so for example how often did a surgeon give a patient antibiotics prior to surgery so that they don't develop a surgical site infection later on finally outcome measures are the direct result of some process that we're trying to follow we either want to increase the outcome measure if the thing is good or decrease the outcome measure if the thing is bad so continuing with this example the thing that we're trying to reduce is surgical site infections as our outcome measure check out the articles that I posted in the description below if you want to explore Healthcare quality more deeply here's two more resources that you can check out there's the ihi open school which is completely free if you have a edu email account or if you're a resident of one of these countries now if you don't qualify for that free edition of the ihi open school then what I would recommend instead is checking out this class on udemy.com now besides quality the other buzzword that shows up a lot in data analyst positions in healthcare is knowledge of metrics or metric building metrics are how we measure how good our care is in a hospital or a clinic but as I mentioned already there's just so many of them so here's some common ones that you should know about there's alos or the average length of stay which measures how many days on average did our patients stay in the hospital or in a particular Department you have patient census which measures the number of patients that occupy a hospital bed in a certain department or area at midnight you have readmission rates which measures the number of patients that came back to the hospital typically for reasons that are unplanned hais or Hospital acquired infection and like that sounds this is a situation where a patient develops an infection while they are in the hospital this might be things like catheter-associated urinary tract infections or maybe the patient develops pneumonia from their ventilator which is called a ventilator Associated event another one is adverse drug events where patients are given the wrong dosing of a medication or the wrong type of medication I'll cover these things in separate videos but for now check out the links that I provide in the description below one last piece of advice I have is to read anything by a tool gawande gawande is a famous surgeon and writer who writes about a variety of different issues in health care including patient safety and quality issues end-of-life care covid-19 and current health care Trends as well you can find many of his articles on newyorker.com and he has a lot of excellent books that I'm going to recommend in the description down below so now we are at the final step of my roadmap and that is landing a job and as you know that's going to be harder than that sounds I have a video where I describe what you need to do to get ready for this so check that video out if you haven't already but I'm going to summarize my process here when you apply for jobs you could try your luck by going to indeed.com or Glassdoor but this is probably the least effective way to find a job nowadays instead you should be networking think of all of the people that you know and try to connect with them on LinkedIn and I don't care who they are or where they work you should be connecting with everyone that you know friends family people you went to school with professors in college your Barber your butcher your football coach connect with as many people as you know at least a little bit because the chances are one of them either works directly with Health Care data or they know somebody that works with Healthcare data and when you find the people that do work with Healthcare data you should request an informational interview to figure out who these people are go to linkedin.com type in the name of the healthcare organization that you want to work for under people you're going to see these three buttons that say first second and third the first contacts are the people that you already know and are connected with on LinkedIn so if you see anybody under that first button reach out to them and request an informational interview if you don't have any first contacts click on the second button to see if you have any second contacts these are people that your first contacts are connected with figure out who those second contacts are and then reach out to the first Contact to see if they would be willing to introduce you and if that person would be willing to give you an informational interview then take that opportunity to ask that person for a guidance about how to become a data analyst in healthcare doing this process will not only give you more ideas about how to become a data analyst in healthcare but it will also gently hint to that person that you want a job where they work if you leave a good impression on that person they might end up referring you to a job opening at that organization when you're done with that informational interview ask that person if they know of anyone else that you could reach out to this is going to take a while but eventually you will get your first interview and this is how I actually got my first job now I threw a lot at you so if you are overwhelmed or you're not quite sure where to start I've got a playlist here that you can explore that talks about data analytics and Healthcare and I have lots of more videos coming out in the future so check that out if you haven't already thank you so much for watching and I'll see you in another video

Channel: Data Wizardry

Views: 37,545

Keywords: healthcare analytics, business intelligence, data analyst, tableau, data analyst interview, how to become a data analyst, healthcare data analyst, application of healthcare analytics, data analytics, business analyst, business intelligence analyst, health informatics, clinical analyst, tech careers 2023, data wizardry, healthcare technology, health care data, healthcare business analyst, patient data, data analytics in healthcare industry, healthcare data

Id: ime7OBlERiM

Length: 15min 18sec (918 seconds)

Published: Mon May 08 2023