Healthcare analytics is the process of collecting, analyzing, and using data to improve outcomes, quality, and efficiency. It can help healthcare providers, payers, researchers, and policymakers make better decisions based on evidence and insights. In this article, we will explore what healthcare analytics is, how it is used, and what benefits it offers. Furthermore, we will cover how to get started in this field.
Key Takeaways
| Section | Key Takeaways |
|---|---|
| What is healthcare analytics? | Healthcare analytics uses various data science techniques, such as statistics, visualization, mining, machine learning, and artificial intelligence. |
| How is data analytics used in healthcare? | Healthcare analytics services provide solutions and support for healthcare data and analytics. |
| Healthcare analytics services | Healthcare analytics services provide solutions and support for healthcare data and analytics. |
| Healthcare analytics platform | Some examples of healthcare analytics platforms are Microsoft Azure, Google Cloud, Amazon Web Services, Databricks, Qlik, and Tableau. |
What is Healthcare analytics?
Healthcare analytics can be broadly defined as applying data science techniques to healthcare data. Data science is an interdisciplinary field that combines mathematics, statistics, and computer science. Moreover, it requires domain knowledge to extract meaningful information from data. Data science techniques include data collection, data cleaning, data exploration, and data visualization. Additionally, it includes data modeling, data mining, machine learning, artificial intelligence, and more.
There are different types of healthcare analytics, depending on the purpose and scope of the analysis. Some of the common types are:
Data Analytics in Healthcare
Data analytics in healthcare is the process of analyzing data to describe, summarize, and understand the current state. For example, data analytics can help answer questions such as:
- How many patients are admitted to a hospital each day?
- What are the most common diagnoses and treatments?
- How much does it cost to provide healthcare services?
- How satisfied are the patients and staff with the healthcare quality?
- How does the healthcare performance compare to the benchmarks or standards?
Data analytics can use descriptive statistics, such as mean, median, and percentage, to summarize and present the data. It can also use data visualization tools, such as charts, graphs, and dashboards, to display data in an easy-to-understand format.
Predictive Analytics in Healthcare
Predictive analytics in healthcare is the process of using data to predict future outcomes, trends, and behaviors. Furthermore, predictive analytics can help answer questions such as:
- What is the chance of a patient developing a certain condition or complication?
- What is the best treatment option for a patient based on their characteristics and preferences?
- What is the expected demand for healthcare resources and services in the future?
- What are the potential risks and opportunities for healthcare improvement and innovation?
Predictive analytics can use statistical methods, such as regression, correlation, and hypothesis testing to identify and quantify the relationships between variables. Additionally, it can use machine learning techniques, such as classification, clustering, and recommendation systems, to learn from the data and generate predictions.
Prescriptive Analytics in Healthcare
Prescriptive analytics in healthcare is the process of using data to prescribe optimal actions and decisions. Furthermore, prescriptive analytics can help answer questions such as:
- What is the best action for a patient or a healthcare provider in a given situation?
- How can the healthcare system optimize its performance and efficiency?
- How can the healthcare system achieve its goals and objectives?
- How can the healthcare system adapt to changing conditions and uncertainties?
Prescriptive analytics can use optimization methods, such as linear programming, integer programming, and dynamic programming. It helps in finding the best solutions that maximize or minimize a certain objective function. Moreover, prescriptive analytics can also use simulation methods, such as Monte Carlo simulation, discrete event simulation, and agent-based simulation. They can help model and evaluate the outcomes of different scenarios and alternatives.
Big Data Analytics in Healthcare
Big data analytics in healthcare is the process of using data that is characterized by the “four Vs”. The four Vs are volume, velocity, variety, and veracity. Additionally, Big data refers to the large data sets that are generated at a high speed and from diverse sources. For example, such as electronic health records, medical claims, clinical trials, genomic data, wearable devices, social media, and more. Moreover, big data poses challenges and opportunities. It requires advanced tools and techniques to store, process, analyze, and use the data effectively and efficiently.
Big data analytics can help unlock the hidden value and potential of the data. It provides new insights and discoveries that can improve healthcare quality, safety, and outcomes. Big data analytics can use techniques such as:
- Data integration: the process of combining and harmonizing data from different sources and formats
- Data mining: the process of discovering patterns and associations in the data
- Text mining: the process of extracting information and insights from unstructured text data
- Natural language processing: the process of analyzing and understanding natural language data
- Sentiment analysis: the process of identifying and measuring the emotions and opinions in the data
- Image analysis: the process of analyzing and understanding image data
- Video analysis: the process of analyzing and understanding video data
- Audio analysis: the process of analyzing and understanding audio data
- Deep learning: the process of using artificial neural networks to learn from the data and perform complex tasks
Advanced Healthcare Analytics
Advanced healthcare analytics is the process of using data to perform sophisticated and innovative analyses. It can provide novel and actionable insights and solutions. Furthermore, advanced healthcare analytics can use techniques such as:
- Artificial intelligence: creating systems that can perform human-like tasks
- Cognitive computing: creating systems that can mimic and augment human cognition
- Blockchain: creating and maintaining a distributed and secure ledger of transactions and records. It can enhance the transparency, trust, and efficiency of healthcare data exchange and management
- Internet of Things: connecting and communicating with devices and sensors. It can collect and transmit healthcare data in real-time and enable remote monitoring and control
- Augmented reality: creating and displaying an enhanced version of reality. It can overlay digital information and images on the physical environment and provide immersive and interactive experiences
- Virtual reality: creating and displaying a simulated version of reality. It can immerse and transport the user to a different environment and provide realistic and engaging experiences
How is Data Analytics Used in Healthcare?
Data analytics is used in healthcare for various purposes and applications, such as:
Healthcare Analytics Use Cases
Some of the main use cases for healthcare analytics are:
- Clinical analytics: the use of data analytics to improve clinical care and outcomes. For example, it can be used for diagnosis, treatment, prevention, and quality improvement
- Operational analytics: the use of data analytics to improve operations and efficiency. For example, it is used for resource allocation, scheduling, workflow, and performance measurement
- Financial analytics: the use of data analytics to improve financial management and performance. It is used for revenue cycle, cost reduction, profitability, and risk management
- Population health analytics: the use of data analytics to improve the health and well-being of a defined population or group. It can be used for chronic disease management, care coordination, and health promotion
- Research analytics: the use of data analytics to advance research and innovation. It is used for drug discovery, clinical trials, and evidence-based practice
- Policy analytics: the use of data analytics to inform and evaluate policies and regulations. It is used for healthcare reform, quality standards, and public health initiatives
Healthcare Analytics Services
Healthcare analytics services are the services that provide solutions and support to organizations and stakeholders. Furthermore, these services can include:
- Data collection and management: the service of collecting and managing healthcare data from various sources and formats. It involves electronic health records, medical claims, clinical trials, genomic data, wearable devices, social media, and more
- Data analysis and modeling: the service of analyzing and modeling healthcare data using various techniques and methods. It includes descriptive statistics, data visualization, data mining, machine learning, artificial intelligence, and more
- Data interpretation and reporting: the service of interpreting and reporting the results and findings of the data analysis and modeling. It uses various tools and formats, such as charts, graphs, maps, dashboards, reports, and presentations
- Data consulting and advisory: the service of providing expert advice and guidance on how to use and apply the data analysis and modeling results and findings. It identifies and prioritizes opportunities, developing and implementing strategies, and evaluating and monitoring outcomes
Healthcare Analytics Companies
Healthcare analytics companies are companies that specialize in providing services and products to organizations and stakeholders. Furthermore, companies can vary in their size, scope, and focus. It depends on their target market, value proposition, and competitive advantage. Some examples of companies are:
- IBM Watson Health: leverages artificial intelligence and cognitive computing to provide data-driven insights and solutions for healthcare challenges and opportunities
- Optum: offers a comprehensive portfolio of data, analytics, and technology solutions and services for transformation and optimization
- Cerner: provides healthcare information technology and electronic health record systems that enable data-driven decision-making and care delivery
- Epic: provides healthcare information technology and electronic health record systems. They facilitate data integration and interoperability across healthcare settings and organizations
- McKesson: provides healthcare supply chain and distribution solutions and services that enhance data visibility and efficiency
Healthcare Analytics Solutions
Healthcare analytics solutions are the products and tools that enable and facilitate applications and services. Moreover, healthcare analytics solutions can include:
- Data platforms: the solutions that provide the infrastructure and capabilities for storing, processing, and accessing healthcare data. It includes cloud computing, data warehouses, data lakes, and data hubs
- Data tools: the solutions that provide the functionalities and features for manipulating and analyzing healthcare data. It involves data integration, data quality, data governance, and data security
- Analytics platforms: the solutions that provide the environment and framework for performing and deploying models and algorithms. It includes analytics engines, analytics libraries, and analytics pipelines
- Analytics tools: the solutions that provide the functionalities and features for creating and using healthcare analytics models and algorithms. It includes data exploration, data visualization, data mining, machine learning, artificial intelligence, and more
- Analytics applications: the solutions that provide specific and customized healthcare analytics use cases and scenarios. It involves clinical decision support, operational optimization, financial management, population health management, and more
Healthcare Analytics Platform
A healthcare analytics platform is a type of solution that provides a comprehensive and integrated set of data, analytics capabilities, and services for healthcare applications and users. A healthcare analytics platform can help healthcare organizations and stakeholders to:
- Access and manage healthcare data from various sources and formats. Some of the formats are electronic health records, medical claims, clinical trials, genomic data, and wearable devices.
- Explore and understand healthcare data using various techniques and methods. Some of the analyses involve descriptive statistics, data visualization, data mining, and machine learning.
- Create and deploy models and algorithms that can provide insights. They provide solutions for healthcare challenges and opportunities. For example, they can be used for diagnosis, treatment, prevention, quality improvement, and resource allocation.
- Monitor and evaluate models and algorithms using various tools and formats. For example, they include charts, graphs, maps, dashboards, reports, and presentations.
- Collaborate and communicate with users using various channels and modes.
Examples of Healthcare Analytics Platforms
Some examples of healthcare analytics platforms are:
- Microsoft Azure: a platform for healthcare data and analytics services via cloud computing.
- Google Cloud: a cloud computing platform that offers various data and analytics services and products for healthcare applications.
- Amazon Web Services: Amazon offers a cloud computing platform with data and analytics services that can be applied to healthcare.
- Databricks: a data and analytics platform that provides a unified and collaborative environment for healthcare. They support data engineering, data science, and machine learning.
- Qlik: a data and analytics platform that provides a self-service and interactive approach to healthcare data.
- Tableau: a data and analytics platform that provides a user-friendly and intuitive approach to healthcare data.
Benefits of Data Analytics in Healthcare
Data analytics in healthcare can provide various benefits for healthcare organizations and stakeholders, such as:
- Improving healthcare quality and safety: data analytics can help improve the accuracy, timeliness, and effectiveness of healthcare diagnosis, treatment, and prevention. It can reduce the errors, complications, and adverse events that can harm the patients and staff
- Improving healthcare outcomes and satisfaction: data analytics can help improve the health and well-being of patients and populations. It increases the satisfaction and loyalty of the patients and staff, by providing personalized, patient-centered, and evidence-based care and services
- Improving healthcare efficiency and productivity: data analytics can help improve the utilization and allocation of healthcare resources and services. It increases the performance and productivity of the healthcare providers and staff, by optimizing the healthcare operations and workflows
- Improving healthcare profitability and sustainability: data analytics can help improve the revenue and profitability of healthcare organizations and stakeholders. Additionally, it ensures the long-term viability and sustainability of the healthcare system. Moreover, it reduces healthcare costs and waste and increases the healthcare value and quality
- Improving healthcare innovation and transformation: data analytics can help improve the research and innovation of healthcare organizations and stakeholders. Additionally, it enables the transformation and advancement of the healthcare system. Moreover it helps by discovering new insights and solutions and creating new products and services
Healthcare Analytics Salary and Job Outlook
Healthcare analytics is a growing and lucrative field that offers various career opportunities and pathways for data and analytics professionals. According to the US Bureau of Labor Statistics, the employment of healthcare data and analytics occupations is projected to grow 15% from 2019 to 2029. This growth is much faster than the average for all occupations, and the median annual wage for these occupations was $91,160 in May 2020, higher than the median annual wage for all occupations of $41,950.
Healthcare Analytics Job Outlook
The demand for healthcare data and analytics professionals is expected to increase in the coming years, as the healthcare industry faces various challenges and opportunities, such as:
- The increasing volume and complexity of healthcare data, from various sources and formats, such as electronic health records, medical claims, clinical trials, genomic data, wearable devices, social media, and more
- The increasing need and expectation for healthcare quality, safety, and outcomes, from various stakeholders and regulators, such as patients, providers, payers, researchers, and policymakers
- The increasing pressure and competition for healthcare efficiency, productivity, and profitability, from various market forces and trends, such as healthcare reform, value-based care, and consumerism
- The increasing potential and opportunity for healthcare innovation and transformation, from various technologies and developments, such as artificial intelligence, cognitive computing, blockchain, internet of things, augmented reality, virtual reality, and more
Healthcare Analytics Roles and Positions
Some of the common and emerging healthcare data and analytics roles and positions are:
- Healthcare data analyst: collects, cleans, and analyzes healthcare data using various techniques and methods. Moreover, they use descriptive statistics, data visualization, data mining, machine learning, artificial intelligence, and more. Furthermore, they provide reports and presentations of the results and findings.
- Healthcare data scientist: creates and deploys models and algorithms using various techniques and methods. Furthermore, they use data exploration, data visualization, data mining, machine learning, artificial intelligence, and more. Additionally, they provide insights and solutions for healthcare challenges and opportunities.
- Healthcare data engineer: builds and maintains the healthcare data infrastructure and pipelines using various tools and technologies. Furthermore, they use cloud computing, data warehouses, data lakes, data hubs, data integration, data quality, data governance, and data security.
- Healthcare data architect: designs and implements the healthcare data architecture and strategy. Moreover, technologies used are cloud computing, data warehouses, data lakes, data hubs, data integration, data quality, data governance, and data security.
- Healthcare data manager: oversees and manages the healthcare data operations and projects. Furthermore, they handle project management, change management, risk management, and stakeholder management.
- Healthcare data consultant: provides expert advice and guidance on how to use and apply healthcare data and analytics for various purposes and applications. Moreover, they work in clinical analytics, operational analytics, financial analytics, population health analytics, research analytics, and policy analytics.
Healthcare Analytics Salary
The salary of healthcare data and analytics professionals can vary depending on various factors, such as education, experience, skills, location, industry, and employer. According to PayScale, a website that provides salary information and data, the average salary for some specific healthcare data and analytics roles and positions are:
- Healthcare data analyst: $64,221
- Healthcare data scientist: $95,865
- Healthcare data engineer: $91,493
- Healthcare data architect: $113,436
- Healthcare data manager: $77,577
- Healthcare data consultant: $81,084
These are only estimates and averages. However, the actual salary of healthcare data and analytics professionals may differ depending on the individual and the employer.
Healthcare Analytics Jobs
Healthcare analytics jobs are the jobs that require or involve healthcare data and analytics skills and knowledge. Moreover, these jobs can be found in various healthcare settings and organizations, such as:
- Hospitals: healthcare settings that provide inpatient and outpatient care and services for various medical conditions and specialties, such as surgery, emergency, intensive care, cardiology, oncology, and more
- Clinics: healthcare settings that provide outpatient care and services for specific medical conditions and specialties, such as primary care, dental care, mental healthcare, and more
- Laboratories: healthcare settings that provide testing and analysis of biological samples and specimens, such as blood, urine, tissue, and DNA, for various purposes and applications, such as diagnosis, treatment, research, and innovation
- Pharmacies: healthcare settings that provide dispensing and delivery of prescription drugs and medications, as well as other healthcare products and services, such as immunizations, health screenings, and counseling
- Insurance companies: healthcare organizations that provide health insurance plans and policies that cover the costs and risks of healthcare services and products for individuals and groups, such as employers, employees, and families
- Government agencies: healthcare organizations that provide healthcare programs and initiatives that benefit the public and society, such as Medicare, Medicaid, Veterans Health Administration, Centers for Disease Control and Prevention, and more
- Research institutes: healthcare organizations that conduct and support healthcare research and innovation, such as the National Institutes of Health, Mayo Clinic, Johns Hopkins University, and more
- Technology companies: healthcare organizations that develop and provide healthcare technology products and services, such as IBM, Google, Amazon, Microsoft, and more
Healthcare Analytics Jobs Posting
Healthcare analytics jobs can be found on various online platforms and websites, such as:
- LinkedIn: a professional networking and social media platform that connects and engages healthcare data and analytics professionals and employers, and provides various features and resources, such as profiles, connections, groups, posts, articles, events, and more.
- Indeed: a job search and employment platform that aggregates and displays healthcare data and analytics jobs and opportunities from various sources and employers, and provides various features and resources, such as resumes, alerts, reviews, salaries, and more.
- Glassdoor: a job search and employment platform that provides healthcare data and analytics jobs and opportunities, as well as insights and information on healthcare data and analytics employers and workplaces, such as ratings, reviews, salaries, benefits, interviews, and more
How to Get Started in Healthcare Analytics
If you are interested in pursuing a career or advancing your skills in healthcare analytics, here are some steps and tips to help you get started:
1. Get qualified.
To become a healthcare data and analytics professional, you need to have the relevant education and credentials that demonstrate your knowledge and competence in the field. Depending on your desired role and position, you may need to have a bachelor’s degree, a master’s degree, a certificate, or a license in healthcare data and analytics, or a related field, such as data science, computer science, statistics, mathematics, health informatics, health administration, or healthcare management.
2. Earn Your Degree
One of the most common and effective ways to get qualified in healthcare data and analytics is to earn a degree from an accredited and reputable institution. A degree can provide you with the theoretical and practical knowledge and skills that are essential and valuable for healthcare data and analytics applications and careers. A degree can also help you build your network and portfolio, and increase your credibility and employability.
There are various degrees that can prepare you for healthcare data and analytics, depending on your level and interest. Some of the common and popular degrees are:
2.1 Healthcare Analytics Masters
A healthcare analytics master’s degree is a graduate-level degree that provides advanced and specialized education and training in healthcare data and analytics. A master’s degree can help you develop and enhance your analytical, technical, and managerial skills. Additionally, it helps prepare you for leadership and senior roles. Moreover, it can also help you pursue further education and research, such as a doctoral degree or a postdoctoral fellowship.
A healthcare analytics master’s degree typically requires two years of full-time study, or longer for part-time or online study. Furthermore, A master’s degree usually consists of core and elective courses, such as:
- Healthcare data and systems
- Healthcare statistics and research methods
- Healthcare data mining and machine learning
- Healthcare data visualization and communication
- Healthcare analytics applications and projects
- Healthcare Analytics Ethics and Regulations
A healthcare analytics master’s degree may also require a capstone project, a thesis, or an internship, where you can apply your knowledge and skills to a real-world healthcare data and analytics problem or opportunity.
Some examples of healthcare analytics master’s degrees are:
- Master of Science in Healthcare Analytics from Duke University
- Master of Science in Health Data Science from the University of Michigan
- Master of Science in Health Data Science from Harvard University
- Master of Science in Health Informatics and Analytics from Northwestern University
- Master of Health Data Science from Saint Louis University
2.2 Healthcare Analytics Certificate
A healthcare analytics certificate is a short-term and focused program that provides basic and introductory education and training in healthcare data and analytics. A certificate can help you acquire and improve your foundational and essential skills. It helps prepare you for entry-level and intermediate roles. Furthermore, a certificate can also help you supplement and complement your existing education and experience, and enhance your career prospects and opportunities.
A healthcare analytics certificate typically requires a few months to a year of study, depending on the program and format. Moreover, a certificate usually consists of a few courses, such as:
- Healthcare data and systems
- Healthcare statistics and research methods
- Healthcare data mining and machine learning
- Healthcare data visualization and communication
- Healthcare analytics applications and projects
A healthcare analytics certificate may also require a final project or an exam, where you can demonstrate your knowledge and skills.
Some examples of healthcare analytics certificates are:
- Certificate in Healthcare Analytics from the University of California, Irvine
- Certificate in Healthcare Data Analytics from Cornell University
- Certificate in Healthcare Data Analytics from the University of Minnesota
- Certificate in Healthcare Data Analytics from the University of Texas at Austin
- Certificate in Healthcare Data Analytics from Johns Hopkins University
3. Gain the right skills.
To become a successful and effective healthcare data and analytics professional, you need to have the right skills that are relevant and valuable for healthcare data and analytics applications and careers. Depending on your desired role and position, you may need to have a combination of analytical, technical, and soft skills, such as:
- Analytical skills: the skills that enable you to collect, clean, analyze, and use healthcare data using various techniques and methods, such as descriptive statistics, data visualization, data mining, machine learning, artificial intelligence, and more
- Technical skills: the skills that enable you to use various tools and technologies for healthcare data and analytics, such as cloud computing, data warehouses, data lakes, data hubs, data integration, data quality, data governance, data security, engines, libraries, pipelines, software, and more
- Soft skills: the skills that enable you to work effectively and efficiently with healthcare data and analytics users and stakeholders, such as communication, collaboration, problem-solving, critical thinking, creativity, and leadership
Healthcare Analytics Learning Resources
To gain and improve your skills in healthcare data and analytics, you can use various resources and opportunities, such as:
- Online courses: online courses are convenient and flexible ways to learn and practice healthcare data and analytics skills, from various platforms and providers, such as Coursera, edX, Udemy, Udacity, and more
- Books: books are comprehensive and in-depth sources of information and knowledge on healthcare data and analytics, from various authors and publishers, such as Healthcare Data Analytics by Chandan K. Reddy and Charu C. Aggarwal, Healthcare Data Analytics by Hui Yang and Eva K. Lee, and more
- Blogs: blogs are timely and relevant sources of insights and tips on healthcare data and analytics, from various experts and practitioners.
- Podcasts: podcasts are engaging and entertaining sources of stories and conversations on healthcare data and analytics, from various hosts and guests, such as The Healthcare Analytics Podcast, Data Skeptic, Data Stories, and more
- Webinars: webinars are interactive and informative sources of presentations and demonstrations on healthcare data and analytics, from various organizations and institutions, such as IBM, Google, Amazon, Microsoft, and more
- Conferences: conferences are immersive and collaborative sources of networking and learning on healthcare data and analytics, from various events and venues, such as Healthcare Analytics Summit, Healthcare Data and Analytics Association Conference, and more
- Communities: communities are supportive and helpful sources of feedback and guidance on healthcare data and analytics, from various platforms and groups, such as Kaggle, Stack Overflow, Reddit, and more
3. Gain experience.
To become a competent and confident healthcare analytics professional, you need to have relevant experience that demonstrates your skills and abilities in the field. Depending on your desired role and position, you may need to have a certain amount and level of experience in healthcare data and analytics, or a related field, such as data science.
To gain and improve your experience in healthcare analytics, you can use various resources and opportunities, such as:
- Projects: projects are practical and hands-on ways to apply and showcase your healthcare data and analytics skills and knowledge, using real or simulated healthcare data and problems, such as analyzing healthcare costs and outcomes, predicting healthcare risks and events, prescribing healthcare actions and decisions, and more
- Portfolios: portfolios are professional and personal ways to document and display your healthcare data and analytics projects and achievements, using various platforms and formats, such as Kaggle, blogs, GitHub, Medium, and more
- Internships: internships are experiential and educational ways to learn and practice healthcare data and analytics skills and knowledge, under the supervision and guidance of healthcare data and analytics professionals and employers, in various healthcare settings and organizations, such as hospitals, clinics, laboratories, pharmacies, insurance companies, government agencies, research institutes, technology companies, and more
- Jobs: jobs are formal and contractual ways to work and contribute as a healthcare data and analytics professional, for healthcare data and analytics employers and clients, in various healthcare settings and organizations, such as hospitals, clinics, laboratories, pharmacies, insurance companies, government agencies, research institutes, technology companies, and more
- Freelancing: freelancing is a flexible and independent way to work and earn as a healthcare data and analytics professional, for healthcare data and analytics employers and clients, in various healthcare settings and organizations, using various platforms and websites, such as Upwork, Fiverr, Freelancer, and more
4. Healthcare Analytics Consulting
Healthcare analytics consulting is a type of healthcare data and analytics service that provides expert advice and guidance on how to use and apply healthcare data and analytics for various purposes and applications, such as clinical analytics, operational analytics, financial analytics, population health analytics, research analytics, and policy analytics. Moreover, Healthcare analytics consulting can help healthcare organizations and stakeholders to:
- Define and clarify their healthcare data and analytics goals and objectives
- Assess and evaluate their healthcare data and analytics needs and capabilities
- Design and implement their healthcare data and analytics strategies and solutions
- Monitor and measure their healthcare data and analytics outcomes and impacts
- Improve and optimize their healthcare data and analytics performance and efficiency
Healthcare analytics consulting can be provided by various healthcare data and analytics professionals and experts, such as healthcare data analysts, healthcare data scientists, healthcare data engineers, healthcare data architects, healthcare data managers, and healthcare data consultants. Healthcare analytics consulting can be delivered in various modes and formats, such as online, onsite, on-demand, project-based, retainer-based, and more.
Examples of Consulting Services and Providers
Some examples of healthcare analytics consulting services and providers are:
- Accenture: a global professional services company that provides healthcare analytics consulting services and solutions for healthcare transformation and optimization, such as Accenture Health Analytics, Accenture Health Insights Platform, Accenture Health Data Governance, and more
- Deloitte: a global professional services company that provides healthcare analytics consulting services and solutions for healthcare innovation and excellence, such as Deloitte Health Informatics, Deloitte Healthcare Data Science, Deloitte Healthcare Data Visualization, and more
- IBM: a global technology company that provides healthcare analytics consulting services and solutions for healthcare intelligence and insights, such as IBM Watson Health, IBM Health Analytics Services, IBM Health Data Platform, and more
- PwC: a global professional services company that provides healthcare analytics consulting services and solutions for healthcare value and quality, such as PwC Health Analytics, PwC Health Data Solutions, PwC Health Data Governance, and more
- KPMG: a global professional services company that provides healthcare analytics consulting services and solutions for healthcare performance and improvement, such as KPMG Health Analytics, KPMG Health Data Solutions, KPMG Health Data Analytics Platform, and more
I hope this article has given you an overview and introduction to healthcare data and analytics, and how to get started in this field. Healthcare analytics is a fascinating and rewarding field that can make a positive difference in healthcare and society. Read more on AI in Healthcare to learn more about how artificial intelligence is changing the healthcare industry.