Healthcare Data

Healthcare data refers to any information that is collected from the healthcare industry. It's mostly used by pharmaceutical and healthcare professionals e.g. in clinical trials and patient behaviour analysis. Datarade helps you find the right data providers and datasets. Learn more →
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249 countries covered
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HealthIQ by AnalyticsIQ - Consumer Healthcare Data USA - 118M Households 241M individuals icon
241M individuals
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3 months of historical data
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Adstra Health enables marketers to reach individuals based on ailment propensities, health/wellness lifestyle data, and prevention indicators. Plus, it’s 100...
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John Snow Labs
Based in USA
John Snow Labs
John Snow Labs is a data provider offering Clinical Data, Electronic Health Record (EHR) Data, Healthcare Data, Healthcare Provider (HCP) Data, and 3 others....
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Automaton AI
Based in India
Automaton AI
We are a full-stack AI company with a mission to democratize Data. Automaton AI is an AI industry expert who is Transforming how businesses see the world wi...
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ShAIp
Based in USA
ShAIp
Shaip offers a human-in-the-loop data platform and services to support all aspects of managing training data for AI/ML development. From data collection, lic...
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The Ultimate Guide to Healthcare Data 2021

Learn about healthcare data analytics, sources, and collection.

What is Healthcare Data?

Healthcare data refers to all the information that is gathered during patient care. When you go to a doctor, a lot of information about your health is collected, processed, stored, analyzed and disseminated.
This data offers insights and supports decision-making in key areas such as medical costs, patient behavior and pharmaceuticals, allowing companies to advance treatment methods, enhance health outcomes, and lower overall costs.

Healthcare data is not only crucial to solving local organizational issues, like reducing workloads and increasing profits of an agency, but it also helps solve global problems, such as forecasting epidemics and combating existing diseases more efficiently.

That said, healthcare data is growing at a rapid rate, and witnessing about a 48% increase annually. It was expected to amount to 2,314 exabytes by 2020.

What is Healthcare Data Used For?

Healthcare data is useful for healthcare startups, established corporations, and pharmaceutical companies for numerous reasons. It’s a powerful tool that offers them insights and helps them identify the needs within a customer or physician segment, and target geographical areas. Companies are able to make decisions with confidence, determine the right investments, and refine marketing strategies.

Clinics and hospitals are able to improve patient care, insurance providers can use it to reduce fraudulent activity, rectify false claims, provide better services to their customers and reconcile records faster.
Manufacturers also benefit from it by creating better, innovative products to solve health issues, and pharmaceuticals are able to do better research and development, resulting in more effective drugs, shorter production times, and lower costs.

Healthcare data can be analyzed for the following use cases:

Product Development
Developing new drugs and health-related products is a long process that requires a lot of time and money. Collecting healthcare data is a key element that allows businesses to develop innovative products for a fraction of time and cost.

Through data analysis, teams are able to find useful information much faster and more efficiently, thus reducing the time needed for product development and market placement. This process removes guesswork, and creates products that are more precise.

Patient Outcomes
Doctors and other medical professionals can more efficiently and accurately identify diagnoses and treatments. Rare conditions that would otherwise seem incurable are more likely to be traded, since research can progress at a much faster pace.

Operational Efficiency
Collecting and analyzing data allows healthcare organizations and pharmaceutical companies in a myriad of ways. From improving employee output, to designing a more efficient workflow, to redirecting resources to where they are most needed – healthcare data could assist in all these directions.

Driving innovation
Innovation is crucial for advancements in medicine. Healthcare data speeds up the rate at which new drugs are discovered, thus improving the quality and reducing the overall cost of healthcare.

How Much Healthcare Data is There?

The amount of healthcare information available is vast. Over the last several decades, with ever-advancing data capture technology, healthcare data has been growing at an unprecedented rate due to improved forms for which this data is currently being collected. As of 2013, it was estimated that there were about 153 exabytes of healthcare data generated in that year alone. Over time, it has been estimated that by the end of 2020, this data could have grown to 2314 exabytes. Statistics provided by healthcare databases and data vendors show that healthcare information has grown by a tremendous 878% since 2016.

What Are Typical Healthcare Data Attributes?

Healthcare data allows organizations to enhance health outcomes. Companies can track health records that include vital signs like heart rate, as well as diagnostic- related information, like laboratory test results from blood tests.

Through collecting and interpreting data, companies are able to analyze profiles and demographics, and identify and target prospective members. They can assess hospital claims and prescriptions fulfilment data to create targeted campaigns for specific health conditions. Companies can also leverage pricing data against quality metrics to identify the highest value, lowest cost providers for certain procedures and services.

Ultimately, the efficient use of data helps businesses understand what is going on in the healthcare industry, identify problems, and find innovative solutions that will help reduce costs.

The healthcare data attributes also depend on the type of healthcare data:

Claims data
Claims data includes patient demographics, dates of services, diagnosis codes, cost of services, and the like. This information helps the provider understand the basic condition of the patient, what concerns are they facing, and how much will it cost to treat them.

Patient-generated health data
Also known as PGHD, patient-generated health data can be collected in various forms, like satisfaction surveys, patient-reported outcomes, and the data collected through wearable fitness trackers and IoT devices.

Social and community determinants of health
Socioeconomic data could be a vital indicator of the health of a community. Social and community attributes like the average income, food choices, transportation access, education levels, and the like could reveal tons of information about the patients.

EHR data
Also called electronic health record data, EHR data contains crucial information about the process of care, feedback of the patients regarding the provider and so on.

What is Big Data in Healthcare?

As a part of data science, big data is a modern day business tool that has found applications in almost every sector of the world economy as a means for businesses to leverage the available large volumes of information to boost sales and customer experience. In healthcare, big data refers to large volumes of information that is collected by digital means pertaining to patient records, analysis and hospital information. Greater insights can be gained through healthcare data analysis mechanisms, which help data analysts gain greater insights concerning healthcare systems, based on real-time and historical data, showing transformation and growth in this vital and valuable sector.

How to Analyze Healthcare Data?

The major hurdle with analyzing healthcare data is how to handle the large volume of healthcare information. As such, the process of analyzing healthcare data starts with storing the collected information in a file format that is easily accessible and readable for enhanced analysis. Once the data is collected and stored in readable formats, the next step entails pulling together varying fields of information technology, statistics, and mathematics that work together to put the data to work. Artificial intelligence and machine learning tools are also important components of healthcare data analysis processes to make healthcare analytics more reliable and efficient.

How does Data Mining Work in Healthcare?

Data mining in healthcare involves the process of uncovering, exploring and analyzing massive blocks of healthcare information, a process that is aimed to uncover patterns in the sector, define standard themes of operation, and establish future trends. Using methods from generic data science and big data analytics, data mining in healthcare joins techniques derived from computer science models and statistics to help amass large amounts of healthcare information. This data is then stored and managed by either in-house servers of healthcare facilities or third-party providers of data mining services. Third-party providers of healthcare data are also involved in the data mining and analysis process, as they apply advanced algorithmic codes to collect and analyse data before offering it for purchase as healthcare datasets from data marketplaces.

How Healthcare Data Is Typically Collected?

Healthcare data is primarily collected from many different sources. It generally involves a diverse set of public and private data collection systems, including health surveys, administrative enrolment, billing records, medical records, used by various entities, such as hospitals, CHCs, physicians, and health plans.

Nowadays, the information is mostly gathered with the help of digital channels and numerous applications available in the market.

The most popular tools for gathering medical information include:

  • CRM - integrated customer relationship management systems for generating and handling general information, providing reports and analyzing various issues.
  • EHR - electronic health record systems for accumulating and analyzing personal patient information and generating deeper insights.
  • Mobile applications - software that runs on portable devices to connect clinicians and patients, aggregate and access information in various databases.

What is PHI Data in Healthcare?

When a patient visits a healthcare facility, any medical or health data that can be applied to identify this patient during the dissemination of healthcare service is what is referred to as Protected Health Information. PHI entails a list of records, health histories, examination results and medical bills which basically uniquely identifies a patient. A PHI form is a basic element of healthcare information which most healthcare data providers use as a source for the data they eventually supply in aggregated form.

How is Healthcare Data Incorporated into Statistics and Research?

Once healthcare data is collected and analyzed, users can identify statistical and qualitative trends. The massive amounts of data amassed from healthcare systems worldwide provides a form of record-keeping. These records of historical healthcare data and real-time healthcare data are a resource for researchers, who use the information to observe compliance and meet the regulatory needs of the healthcare industry, where patient care and safety is paramount. When the data is collected, transferring it into health-targeted databases has opened new insights for research purposes that can be used for product development and consumer marketing. Healthcare data is a form of evidence, to be used for research initiatives so as to avoid bias when drawing conclusions and recommendations for better healthcare systems and products.

How to Assess the Quality of Healthcare Data?

When healthcare data is correctly collected and interpreted, it becomes a powerful tool that helps companies make informed decisions, cut costs and create more efficient products. A lack of access to valuable data inputs in today’s world means that in order for healthcare data to be useful, companies must be able to filter through a lot of information efficiently.

For that reason, it becomes quite challenging for organizations to pinpoint exactly where opportunities exist. So when choosing appropriate solutions for data collection, you should take into account many aspects, such as services provided, the number of doctors and patients supported, existing tools and infrastructure, and budget.

Which Datasets are Used for Healthcare Information?

As far as healthcare information is concerned, the most common datasets are made up of information concerning patient medical data, statistical data, demographic information of patients or group of patients, and insurance details. Healthcare information is grouped into major clinical data types that range from electronic health records, administrative data, claims data, patient disease registry forms, health surveys, and clinical trials data. Depending on the user’s needs, all these datasets are available on commercial healthcare datasets, where anyone looking to access them can either buy the health data online or gain access through specialized healthcare information subscription services.

How Healthcare Data Is Typically Priced?

Healthcare data is often available as subscription packages, however, the process usually depends on each provider. They offer access to hundreds of different databases that target each company’s exact customers by specialty, job role, location, ownership, and many other selects. Given the lack of standardization in the market, custom quotes are a common form of pricing as well.

What Are The Common Challenges When Buying Healthcare Data?

Companies need to evaluate their goals when buying Healthcare data, since there are a few obstacles when getting the right kind. Despite the overwhelming amount of data in healthcare, it’s very challenging to capture the relevant data cohesively.

Proper capture
Finding data that is precise and offers actual value is quite difficult, and considering how sensitive patient records are, properly storing them becomes critical for data security. Data stewardship is a very important aspect to consider, as there must be proper knowledge about where it was obtained, when, by who and the associated conditions.

One study conducted at an ophthalmology clinic revealed that EHR data matched patient-reported data only in 23.5% of records. Various patients reported having three or more eye health-related symptoms, but their HER data didn’t sync at all.

Cleaning
Updated information is also crucial, considering how patient care is constant, so information about each visit should be available.

Storage
Although generating and acquiring healthcare data is relatively easy, what is tough is to store it properly. As the healthcare data is growing exponentially, a lot of organizations and companies find it tough to store the data properly.

What to Ask Healthcare Data Providers?

  • Do they offer adequate security measures to ensure that customers’ data is safely stored?
  • Do they ensure the level of accuracy and compliance required to propel healthcare businesses forward?
  • Do they guarantee continual execution of automatic and manual processes that reflect the latest profile updates and regulatory changes?
  • Do they enable you to access sales, prescription, and claims data for deeper provider insights?
  • Can their dataset be integrated into your current business technologies and how does that process look like?

Who are the best Healthcare Data providers?

Finding the right Healthcare Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Healthcare Data providers that you might want to buy Healthcare Data from are John Snow Labs, Automaton AI, ShAIp, Dateva - Health Data to Health Insights, and Knuckle Head.

Where can I buy Healthcare Data?

Data providers and vendors listed on Datarade sell Healthcare Data products and samples. Popular Healthcare Data products and datasets available on our platform are BoldData - Healthcare Company Data (2.5M companies) by BoldData, HealthIQ by AnalyticsIQ - Consumer Healthcare Data USA - 118M Households by AnalyticsIQ, and Adstra Health | Healthcare Marketing Data USA 100% HIPAA compliant by Adstra.

How can I get Healthcare Data?

You can get Healthcare Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Healthcare Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Healthcare Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to Healthcare Data?

Healthcare Data is similar to Environmental Data, B2B Data, Energy Data, Real Estate Data, and Geospatial Data. These data categories are commonly used for Analytics and Healthcare Data analytics.

What are the most common use cases for Healthcare Data?

The top use cases for Healthcare Data are Analytics.