How to Become a Healthcare Data Analyst (Step by Step)

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By Queen Clev

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If you’re keen on exploring opportunities in the fast-developing field of healthcare data analytics jobs, you’re in the right place. In today’s data-driven world, the demand for hiring a skilled healthcare data analyst is on the rise.

With the right knowledge and skills, you can unlock a rewarding career in this dynamic sector. Healthcare data analysts help medical facilities operate more efficiently. If you’re interested in collecting data and working with medical staff, a position as a healthcare data analyst may be ideal for you.

It’s important to understand the education and technical skills the role requires before you pursue this career. This guide will provide you with essential insights on how to navigate the path toward becoming a proficient healthcare data analyst.

What is a healthcare data analyst?

A healthcare data analyst is an individual who uses data analytics to improve healthcare outcomes. By acquiring, combining, and analyzing data from multiple sources, healthcare data analysts contribute to better patient care, streamlined healthcare processes, and well-assessed healthcare institutions.

They work primarily on the business side of medicine, unlike doctors, nurses, or medical assistants, who work on the clinical side. 

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Professionals who work as healthcare data analysts may have one of many healthcare data analytics job titles. In addition to health care data analysts, titles can be broad or specific, including:

  • Healthcare information management analyst
  • “Health care business analyst
  • Health care consultant
  • Clinical data analyst
  • Public health data analyst
  • Healthcare risk management data analyst

Healthcare data analysts typically work in these environments:

  • Health care providers (hospitals, clinics, doctor’s offices)
  • Health insurance companies
  • Consulting companies
  • Health-focused non-profit organizations 
  • Electronic health record companies
  • Federal, state, or local government organizations

How to become a healthcare data analyst

Say you’re ready to pursue this career field. What are the next steps you’ll need to take? Here’s how to get started and land your healthcare data analytics jobs.

Step 1: Earn a Degree or Educational Background 

The first step to becoming a healthcare data analyst is building an educational background. But the question is, what education is needed to become a data analyst in the healthcare sector?

Health data analytics can be a rewarding career if you have a bachelor’s degree in health information management.

Many healthcare data analyst positions require, at a minimum, a bachelor’s degree in a relevant field. It can be anything from IT or computer science to math, statistics, or a domain-specific degree in a healthcare-related subject.

Eventually, when you take the next step up on the career ladder, you might want to consider a master’s or Ph.D. This isn’t something to worry about if you’re new to data analytics, but it’s good to keep the future in sight.

You can also become a successful health information management professional if you come from the following backgrounds: 

  • Computer Science 
  • Data Science/ Data Analytics
  • Statistics
  • Mathematics 
  • Health Information Management 
  • Health informatics 
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However, learning the necessary healthcare data analyst skills can help you build a career in this field if you come from a different background. It’s just a bonus and not mandatory to have the educational experience stated above.

There are several exceptions in the industry who do not have a STEM education but have successfully transitioned into careers as healthcare data analysts. The willingness to study and learn skills is the most crucial prerequisite.

Step 2: Build Necessary Skills in Data Analytics

As a healthcare data analyst, you should be skilled in mathematics, statistics, and data analysis, followed by strong technical and programming knowledge.

It’s also essential to have a better grasp of the healthcare data analytics sector and understand the most commonly used tools by health data analysts.

Several software applications and databases are used in electronic health records to store and analyze healthcare data. Knowledge of these tools can improve your grasp of how to deal with healthcare data. The most common ones are listed below. 

  • SQL
  • Microsoft Excel
  • R
  • Tableau
  • SAS

You can also build the right skill set by working on these exciting healthcare data analytics projects. These projects have been perfectly curated to help you master all the necessary skills to become a successful healthcare information management professional. 

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Step 3: Get a Healthcare Data Analyst Certification

The next step is to earn professional credentials, such as a Certified Health Data Analyst (CHDA) credential from the American Health Information Management Association (AHIMA), which necessitates passing a written certification test as well as one of the following credentials:

  • A bachelor’s degree with three years of professional experience 
  • A master’s degree and at least a year of experience working with healthcare data 
  • A registered health information technician (RHIT) certification and at least three years of experience working with medical care data. 

Step 4: Speak to someone in the industry

Whether you know someone personally or through a friend, try to speak to someone who works in the healthcare industry.

Ideally, this should be a fellow data analyst. But if you know a doctor, a nurse, another healthcare professional, or just somebody who works in insurance, take the opportunity to ask them about what they do. What does their job involve? How do they use data? Where could novel analytics approaches help them to do their job better?

Ultimately you want to learn as much about the industry as you can. Be like a sponge!

If you’re a recent graduate, you might want to do some of these things before applying for your first healthcare analytics role. Alternatively, if you’re more experienced, why not make the shift into healthcare right now?

Whichever category you fall into, there are many paths to pursue in this exciting and fast-developing sector. And remember, whichever route you pursue within the data analytics field, it’s important to make sure your portfolio reflects your skills and interests.

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What is the importance of data analytics in healthcare?

Data analytics has significantly changed how doctors and medical professionals use, manage, and organize data to ensure better patient results. In turn, big data analytics effectively improves health systems and the overall quality of patient treatment.

Generic databases, wearable technology, electronic health records, numerous patient portals, and exercise equipment are just a few critical sources of big data for the healthcare industry.

It is clear that this healthcare data is diverse due to its formats, types, and context, making it challenging to integrate into standard databases.

Here are a few benefits of using data analytics in the healthcare industry:

  • Improves Patient Treatment: Healthcare is shifting towards better patient outcomes through data analytics, which can help determine which practices work best for patients. 
  • Improved Diagnostics: One of the primary advantages of data analytics is that it allows healthcare practitioners to identify diseases faster and more accurately than ever before. Algorithms analyze data provided by healthcare professionals to anticipate the most likely diagnosis.
  • Save Costs: Healthcare practitioners can use electronic health records (EHRs) to detect broad trends leading to a better understanding of patients’ health patterns. This, in turn, can help save costs by avoiding unnecessary care or hospitalization.
  • Preventive Care: Big data analytics enables healthcare practitioners to predict the probability of an individual having a disease based on their lifestyle and activity. As a result, they can detect warning indications of severe sickness considerably sooner, helping them treat the disease more efficiently. 
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What Do Health Data Analysts Do?

Health data analysts work for hospitals, health systems, insurance companies, health technology vendors, large clinical practices, state and federal agencies, public health, and consulting companies.

Job duties vary based on place of employment, population served, and education obtained, but typical day-to-day responsibilities include:

  • Organizing and maintaining clinical databases and registries
  • Collecting data from patient records
  • Writing automated internal and external reporting systems to have a constant flow of new data
  • Using machine learning and programming to determine patterns in the collected data
  • Interpreting the data and drawing conclusions based on the analysis
  • Summarizing data, analysis, and conclusions into reports senior staff can use to make decisions
  • Making recommendations for policy changes based on data gathered and analyzed
  • Running data models to help senior staff make decisions such as merging with another clinic, building a new hospital wing, or hiring more staff

Types of data analyzed

Every data analyst has tasks and responsibilities specific to their role. In healthcare, the main aim is to spot patterns that can help improve clinical care, reduce costs, and help healthcare institutions run more efficiently and effectively.

But which data do healthcare data analysts work with? Let’s examine a few.”

1. Clinical data

When people first hear about healthcare analytics, the first thing they often think of is directly improving medical outcomes. Medical records are a form of clinical data that can be used to do this.

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Clinical data analysis is probably the oldest application of analytics in the medical industry.

However, the level of insight we can now obtain from clinical data has increased vastly since the introduction of electronic health records (EHRs) in the United States and around the world.

2. Claims and cost data

Many healthcare analysts work for insurance providers or related organizations. Claims data generally refers to the information relating to patient claims and subsequent medical interventions.

Analyses of this data can be used in many ways. For instance, they might help medical institutions identify which medical areas to invest in or help insurers get a better grasp of their premiums.

The data might also help identify areas where resources are being wasted or misused. The applications of claim data are very broad.

3. Pharmaceutical data

The pharmaceutical sector employs healthcare data analysts to support research and development and improve products and processes.

For instance, several international pharmaceutical companies have an agreement in place to share historic cancer research data. They aim to accelerate the discovery and development of new cancer drugs.

Pharma companies might also use data from genome sequencing or medical devices to target specific patients for clinical trials, ultimately improving the outcome of those trials (with more accurate data to use!)

4. Behavioral and sentiment data

Patient behavior and sentiment analysis might not be the first thing you consider when thinking of healthcare analytics. However, these are an increasingly vital aspect of the industry.

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Today, it’s far easier (and far more acceptable) to track people’s retail habits, personal preferences, and feedback.

For example, patient feedback on specific medical interventions can now be monitored in real-time. This means good behaviors or habits can be promoted, while common issues can be identified and dealt with quickly.

For example, if patients suggest that they’re dissatisfied with a particular drug or medical treatment, this could inform an information campaign. Private enterprises frequently use behavioral and sentiment data to market their medical products.

In addition to these four key sources of healthcare data, analysts also work across the supply chain and in HR.

As such, the opportunities for data analysts in the healthcare sector are extremely varied. This means novice healthcare data analysts have a multitude of exciting career paths to choose from.

Understanding Healthcare Data Analyst Skills

As the name suggests, healthcare data analysts help improve healthcare outcomes using data from a variety of sources. Most commonly, healthcare analysts work on the business side of medicine, improving patient care or streamlining the way things are run.

Other names you might come across when looking for healthcare data analyst roles include:

  • Healthcare business analyst
  • Healthcare information management analyst
  • Healthcare consultant

Healthcare data analysts use soft and hard skills, such as:

Data collection and analytics

To streamline the way organizations operate, healthcare data analysts perform the following steps in the data collection process:

  • Obtaining data: Healthcare data analysts collect data by making observations. For instance, they may observe the number of patients who file claims with an insurance provider or the time it takes for patients to see a doctor after admission.
  • Recording data: From their observations, healthcare data analysts know how to record their data to interpret it later. For example, before purchasing a new medical tool, they may record how many instruments the facility needs and the costs of maintaining the instrument.
  • Interpreting data: With their records, healthcare data analysts can determine what their information means. They use critical thinking to decide the areas where the medical facility needs to improve and the causes of discrepancies.
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Communication

When collaborating with other medical personnel, healthcare data analysts use these types of communication:

  • Verbal: When healthcare data analysts train new personnel, they use verbal communication to describe how the databases work and what data to collect. They also need public speaking skills, such as voice articulation and pronunciation, when conducting presentations.
  • Written: It’s important that their writing is clear and comprehensive, making it easy for readers to understand. They also need to ensure their words are accurate, which can help them avoid discrepancies in reports or data analysis.
  • Interpersonal: Healthcare data analysts adjust their communication styles depending on who they’re working with, such as using medical terminology when speaking to a physician and discussing programming languages with a software engineer. Interpersonal communication enables healthcare data analysts to have productive conversations with colleagues.

Medical terminology

Medical terminology that healthcare data analysts understand may include:

  • Clinical codes: By knowing what the clinical codes represent, healthcare data analysts can interpret the information on patient medical records. These codes update regularly, so it’s important to be aware of any updates.
  • Patient diagnoses: Healthcare data analysts may have basic knowledge of different medical conditions and how they progress in patients. They can acquire knowledge of medical terminology and pathology independently or on the job.
  • Treatment plans: To monitor the quality of patient care, healthcare data analysts need to know the effectiveness of treatment plans. They may develop this knowledge by working with physicians or other providers as they progress in their careers.
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Problem-solving

Problem-solving skills enable healthcare data analysts to identify problems in facility operations and devise helpful solutions. For example, if a quarterly report shows an increase in readmitted patients with the same condition, they may attribute the increase to treatment plans.

To minimize the costs of retreating patients, a healthcare data analyst may recommend that doctors prescribe a stronger medication, which can alleviate patients’ symptoms more quickly.

Technology

Healthcare data analysts use technology to manage their data collection. They need knowledge of:

  • Analytical tools: Healthcare data analysts can use analytical tools to gather statistics and discover trends in the data. Familiarity with different statistical software programs may help you in your career.
  • Software management: Healthcare data analysts must secure the databases that store medical and financial records. They also know how to retrieve and update records as needed.
  • Programming languages: Healthcare data analysts may use various programming languages, such as JavaScript, to create new applications for databases and reorganize facility records. You may find it useful to take a course on coding or learn it independently.
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Specialist Healthcare Data Analyst Skills

As your career in the healthcare industry progresses, the range of skills you need will also grow.

Unfortunately, there’s no single list of software and skills that you can refer to. What you learn will vary greatly as your area of expertise becomes more focused.

The necessary software and skills, therefore, depend on the role, the career path you’ve chosen, the type of data you’re working with, and which aspect of the analytics process you’re specializing in.

To offer a flavor, though, we’ve pooled some high-level examples of industry-specific knowledge you might need:

  • Working with healthcare claims (for example, if you’re applying for a job with an insurance provider.)
  • Working with electronic health records (often, though not always, for roles in a clinical setting)
  • Understanding of clinical classification systems, such as the International Classification of Disease (ICD).
  • Experience with procedures such as the Healthcare Common Procedure Coding System (HCPCS)
  • Knowledge of region-specific data standards, such as the US Risk Adjustment Processing System (RAPS) or the European Data Protection Supervisor (the healthcare equivalent of GDPR),
  • SQL, alongside knowledge of relational databases, data warehouses, and data management principles (i.e., data science skills).
  • Healthcare-specific business intelligence tools, such as physician-facing software like UpToDate and Definitive Healthcare.
  • Practical knowledge of the sector, such as how hospitals are run, how diseases and illnesses progress, or experience as a healthcare practitioner

As this demonstrates, the required skills in healthcare analytics can quickly become quite niche! But don’t worry—as a newly qualified data analyst, you won’t be expected to know all of these things.

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We merely wanted to offer an idea of the industry-specific knowledge you’ll gradually need to accumulate. Consider this your first taste of what the future might hold!

Healthcare Analytics Salary – How Much Does a Healthcare Data Analyst Make?

Those working in health care analytics can expect a higher than average salary. According to Glassdoor, for example, the average salary for a healthcare analyst was $93,896 as of May 2022.

Other positions that those working in health care analytics might possess had similarly high salaries. Data scientists, for instance, made an average salary of $121,018 during the same period, according to Glassdoor.

Healthcare Data Analyst Job Description

The roles and responsibilities of a healthcare analyst include the following: 

  • Healthcare data collection from various sources like cost reports, electronic health records (EHR), and patient satisfaction surveys.  
  • Perform data analysis, data acquisition, data governance, data management, and data visualization to deliver optimal healthcare management activities. 
  • Understand data storage and sharing methods  
  • Create data and information models to capture a variety of healthcare operations
  • Find patterns and trends in data analysis. 
  • Explore innovative research methods to improve data analysis, such as machine learning algorithms or natural language processing approaches.
  • Suggest ways to improve the quality of healthcare and reduce costs
  • Transform data into understandable insights for healthcare providers
  • Apply medical codes to clinical data
  • Work with insurers, vendors, and other health organizations to synthesize data that informs decision-making, population health management, cost containment, and quality improvement.
  • Create presentations and reports to present data visuals.
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Conclusion

Mastering the essential skills and gaining in-depth insights into the healthcare data landscape is your gateway to a thriving career as a healthcare data analyst.

This comprehensive guide has equipped you with the knowledge needed to navigate this dynamic field successfully.

As you embark on your journey to becoming a healthcare data analyst, remember that continuous learning and adaptability are key.

Stay updated with industry trends and technologies, and you’ll not only secure healthcare data analyst roles but also become a valuable asset in transforming healthcare through the power of data.

FAQS on Healthcare Data Analyst

How Long Does it Take to Become a Health Data Analyst?

Professionals can begin a career as entry-level health data analysts with as little as two years of education post-high school. However, the classes required for a bachelor’s or master’s degree will allow students to pursue more senior or specialized jobs.

Who is qualified to be a data analyst?

Earn a bachelor’s degree in a field with an emphasis on statistical and analytical skills, such as math or computer science. Learn important data analytics skills. Consider certification. Get your first entry-level data analyst job.

Can I learn data analysis with my phone?

Yes, you can learn data analysis on your Android phone using various mobile applications that provide courses, tutorials, and interactive learning. Here are some popular applications that you can use to learn data analysis: DataCamp: This app offers courses in data science, data analysis, and machine learning.

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