Health Data Integration: Why It’s Good and How to Do It Right

When we talk about healthcare data integration, emphasis is often placed on  components, such as EHR systems.

Sometimes, the problem isn’t about collecting data, but how to manage and use it easily. Imagine if everyone in healthcare used the same system for their data – that would make things a lot simpler, right? But, unfortunately, that’s not the case. 

Different companies use different systems and ways to store their data. Even within the same company, information can be fragmented across various systems. Mishandling of this data can lead to repeated information, inconsistent care for patients, or issues when trying to share it.

For everyone to be able to access it, we need to bring all that information in one place. This is what we call “health data integration.” But how do we go about it? Should we use systems like Redox or InterSystems, or just combine everything directly? Also, what issues might a clinic face while putting all this data together? Let’s dive deeper to answer these questions.

What Is Health Data and Why Integrate It?

Health data is information about an individual’s or population’s health. It includes aspects such as medical history, diagnostic results, and beyond. It also extends to environmental and behavioral factors that might influence medical outcomes.

In the past, doctors used to gather all the health information they needed when a patient came to see them. They would use this data to decide on the best treatments based on evidence.

But now, things have changed thanks to digital health technology. Doctors can now get important information much faster. Plus, they can use these new technologies to keep the information safe and make sure patients can access it easily. We have fitness trackers and health apps that help us collect facts outside of a doctor’s office.

In short, the main goal of health data is to make care better and less expensive. This is helpful to the patients and hospitals alike.

For instance, by predicting which patients are at risk of certain diseases, we can intervene earlier and prevent expensive treatments later on. It can also help avoid unnecessary or duplicate tests and procedures. Patients and healthcare providers thus save money.

According to Statista, the amount of global health data grew a lot in 2020. To give you an idea, in 2013, there were 153 exabytes of data (that’s a lot!) created. But in 2020, there were about 2,314 exabytes of new ones created. Now, think about how much more data we’ll have in the future, especially with big data technologies like AI and ML revolutionizing medicine.

Thus, it’s fair to say that combining all these different sets of information isn’t always easy. Before hospitals can use any of this data, they need to clean it up and make it standardized. This means making sure all the different bits of data fit together well.

Nonetheless, cleaning and standardizing data are only one facet of the problem. Let’s look at other challenges medical groups might face when they try to put all their information in one place.

Health Data Integration Challenges in Hospitals 

Research by Techcrunch shows that 44% of healthcare firms avoid data integration due to inherent risks and obstacles. Here are some of these challenges.

Healthcare data comes in many forms. This variety makes it hard to combine it from different sources. With no universal format, researchers often struggle to access valuable information.

Handling hospital records lacks a standard method, leading to potential data loss. Unclear data ownership rules compound this issue. Hence, strict protocols to standardize data handling and clarify ownership are a must.

Often, medical teams don’t fully understand the rules about keeping patient information private when they have to share it. This is why health companies in the US are making more efforts to follow privacy rules. Statista reported that more than half of the C-level execs said they are either updating privacy rules or training their workers as part of their plan.

Healthcare firms use many apps that hold similar data. But this asset isn’t always accessible across platforms. Even small discrepancies can hurt data-driven insights. Uniformity across apps, through compliance standards, is crucial.

New medical devices and wearables are increasing the number of data sources. But integrating information from wearables can be tough due to its format and privacy issues.

Another Statista survey revealed that in 2022, there were over 340 cases of health data breaches in the US. To give you a perspective, back in 2005, there were only 16 cases.

So what does this mean?

As technology and healthcare systems get more advanced, we also need to do a better job at keeping data safe. It’s super important for medical companies to protect their records from hackers. They have to follow the rules that are already in place.

For example, HIPAA gives guidelines on how to protect data. Differently, HL7 standards direct the sharing information between different healthcare providers’ apps. But how many of our medical institutions are really following these rules all the way? Are they really using the best ways to bring all their facts together? If you’re unsure, contact us to audit these questions.

Need more data?Keep reading. We’ll look at the best ways to integrate data, and you can see how this compares to what you’re doing now and figure out what you might need to add or get better at.

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What Is the Best Way to Integrate Data? Redox vs. InterSystems vs. Direct Integration

At our company, The APP Solutions, we use Redox, Intersystems, as well as direct integration with systems like Epic and Cerner. At the end of this article, we’ll share a real-life example where we used this expertise to help a client.

But before we get to that, let’s compare Redox, Intersystems, and direct integration so you can understand what each one involves.

Redox stands out as a leading name in healthcare integration in the US. It ensures secure, real-time data sharing between over 400 software vendors and more than 4500 healthcare organizations across 90+ Electronic Health Records (EHRs), health information networks like Carequality, and more.

The Redox platform is a cutting-edge, standardized API that minimizes integration challenges, allowing health tech innovators to concentrate on building unique workflows and experiences.

  • User-friendly: Redox provides a single endpoint. So, you write the code once and use it across any health system. All integrations, regardless of the EHR provider, will have the same appearance and functionality.
  • Speedy: The design of Redox encourages reuse. It lets you benefit from the technical mapping and connectivity already established with over 4,000 organizations.
  • Scalable: Hosted on AWS, Redox caters to the demands of its entire network. It processes over 750 million messages every month. In other words, you’re assured of dependable and scalable deployments.
  • Tech supported: A dedicated team of specialists handles healthcare integration and data management. They work as an extension of your team. Everything from product design to implementation planning and long-term support are managed. 
  • Secure: Redox holds HITRUST certification and is SOC II compliant.

Redox is available in the US and Canada and follows an annual licensing structure. It additionally includes a base platform fee and a cost per transaction. The cost depends on the expected total message volume and the complexity of transforming to JSON/FHIR. Early-stage digital health companies can avail of discounts.

Redox offers different subscription durations at varied costs. Please note that extra taxes or fees might apply. In case you need assistance with this question, schedule a call, and we’ll help you find the best solution for you.

All Redox plans come with developer tools and sandboxes. You get a centralized dashboard and transmission logs, and more alongside those.

Redox is available as Software as a Service (SaaS). The application is hosted and operated over the Internet by the vendor. Customers are billed for usage through their AWS account.

InterSystems runs on four main solutions. These are Health Connect, InterSystems Iris, InterSystems Caché, and InterSystems Ensemble. 

Health Connect is a versatile healthcare integration engine that supports high-volume transactions. It engineers process management and monitoring for crucial applications. You can use it as a Platform as a Service (PaaS) or for on-premises/private cloud.

Health Connect brings along benefits like 

  • swift scalability;
  • zero-downtime stability;
  • faster interface development, 

They all translate to cost savings. Health Connect caters to healthcare delivery systems of all sizes, from small clinics to large, complex networks.

At the heart of Health Connect is an efficient, multi-model data engine. This smoothly manages different types of information at high speeds. Other functionalities are:

InterSystems Ensemble consolidates all the data you need to capture, share, understand, and use within your organization. There’s no need to invest time and money in assembling multiple tools to gain a comprehensive integration environment. Ensemble has everything covered.

Every component of your integrated solution is stored as an object in Ensemble’s efficient, multi-model data repository. This provides a unified and consistent view of the systems, applications, and services that make up your solution, significantly reducing the complexity often associated with integration projects. This makes solution development faster and management easier.

InterSystems IRIS represents the latest evolution of the InterSystems data management suite. It includes all the features of InterSystems Caché and Ensemble tools, and adds a number of exciting new abilities. This makes it easier to create and launch applications for businesses that are based in the cloud, are analytics-focused, and require superior performance and scalability.

InterSystems Caché makes it easier to design and launch applications. It offers multiple options for high-availability, including a sophisticated mirroring approach, giving your applications a high level of reliability. You would require less hardware than solutions from other vendors.

Caché comes with a flexible security model that’s easy to adapt. It includes simple provisioning features, making it effortless to control who can access your resources.

The general framework of Caché is simple, and its powerful system management tools mean that you need fewer database administrators (DBAs) than with other databases. In many cases, you might not even need a dedicated DBA at all.

Epic and Cerner l are major companies that provide technology for health information. These systems help big hospitals and health services in the U.S. to save and share electronic medical records easily.

Integrating a Personal Digital Assistant (PDA) into the Epic Electronic Health Records (EHR) system necessitates a detailed process. It involves six key steps and typically takes about a year and a half. This task needs a clinical expert or health data integration company who can lead the process.

Cerner, on the other hand, focuses on making data accessible everywhere. Their Interoperability service ensures that healthcare professionals can get the information they need, no matter where it comes from. This aids in sharing data across different health services.

The specifics of integrating either Epic or Cerner are quite complex. If you’d like to understand more about them and see how they compare, we recommend reading this article where we discuss their differences.

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Action Plans for Tackling Data Integration

If you’re looking to weave together health information from various sources, it’s essential to have the right approach. Here’s what you can to effectively merge information at your healthcare practice.

To consolidate health data from various sources, make sure your technology can handle different data formats. Use integration tools (ESB or iPaaS) that can standardize this information, ensuring it’s accurate and easy to read.

Before merging data, review and update all information. This helps avoid integrating incorrect or outdated data. Back up all vital data to prevent any loss during the process.

Creating a structure for your data simplifies integration. Set up workflows for gathering, processing, cleaning, and sharing data from various systems.

These are storage solutions for data. They allow for data searching and analysis, although they work differently. Data warehouses are great for storing structured data, while data lakes can handle a mix of unstructured and structured data.

Data integration is an ongoing process. Determine which information needs to be integrated first and which can be done later to avoid disruptions.

Traditional IT systems in many organizations can’t exchange data with modern systems. In contrast, using cloud-based solutions can provide a unified view of data from different systems.

Consider how the end-user will see the data. This will help you present your findings in a meaningful way, making it easier for users to access and utilize the data effectively.

Health Data Integration with The APP Solutions: Orb Health Case

Orb Health provides a service that makes healthcare easier to manage for health centers, systems, hospitals, and unions. It helps improve patient results and makes the transition from traditional fee-for-service to value-based care smoother, without needing to add more staff or infrastructure.

The APP Solutions helped Orb Health to extend their service to more patients. We set up remote contact centers that are connected to electronic medical records (EMR), helping to provide a seamless healthcare service. 

Here are the solutions we delivered:

Redox Integration

Redox integration simplifies the process of connecting digital health products to different electronic health records (EHRs) systems, saving time and avoiding complications.

Genesys Integration

This solution allows existing workforce management software to easily integrate with other systems, which makes setting up a contact center quicker and easier.

Power BI Integration

We opted for Power BI integration so that the company could take data from various sources and turn it into clear and interactive insights. By doing so, they would better visualize and understand important data.

Data Security (HIPAA Standard)

Ensuring that sensitive patient data is stored securely was a top priority, and necessary to meet HIPAA standards.

As a result of these solutions, Orb Health saw significant improvements, such as:

54% | 22% ED / Hospitalization Decrease

  • 70% Care Gap Measure Closure
  • $6 MM Annually Medicare Savings Per 1k Patient
  • 26% Overall Patient Savings


Connecting health information is a special task for every company. If you’re thinking about using Redox, InterSystems, or direct integration, we suggest you engage an experienced team. At The APP Solutions, we assist health groups to surmont their integration woes and build interconnected systems for improved patient results.

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How to make EHR/EMR Epic Integration with Your Health App

The medical field in the United States was one of the first to be affected by universal digitalization, which had a positive effect on patient treatment. However, perfection knows no limits, and ordering medical records is the first step to a “bright future,” which is impossible without technology development.

Please dive deep into our Podcast with Jeff Fried, Director of Product Management at InterSystems. You can gather insights about EHR integration like Epic with the use of InterSystems technology.

The APP Solutions is a long-standing InterSystems partner, and we use InterSystems technology to integrate with 99% of EHR systems within the US. This is the quickest and most affordable way to solve all your interoperability challenges.

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What does Epic Software Mean?

Epic Software is an application created to help doctors and other healthcare professionals (insurance agents, pharmacists) effectively manage electronic medical records and track any information that is in any way related to a patient’s health. Such software helps access data much more quickly, not prescribing unnecessary tests or drugs that can cause side effects, etc. Epic software helps to significantly improve business processes.


According to statistics, in 2022, Epic named top EHR 12th straight year in nomination “Best overall software suite”. Isn’t that compelling enough reason to incorporate the system into your application?

What is EHR/EMR Integration?

EHR (electronic health records software) and EMR (electronic medical records) are medical records systems. Despite the similarity of concepts, they still have a defining difference that affects the degree of compatibility due to the amount of information. EMR contains data maintained by one doctor or group of doctors from one medical institution; as soon as you go to another hospital, you need to start all over again. 

The EHR absolutely systematizes all info from any medical personnel that has ever been entered into the system. Any doctor anywhere in the country can view the current data or send it to colleagues when needed.



EMR/EHR epic integration simplifies the life of medical staff and patients, allowing them to download the entire medical history of a person in seconds, and saves time on various burdensome but necessary formalities such as filling out personal and insurance information.


Does Epic have an API?

You can integrate your software with EHR (which we have found will give your product a huge advantage) in several ways:

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A White-Label Telemedicine Platform – organizing data transmission in FHIR HL7 standard for health care data exchange using FHIR HL7 infrastructure



Calmerry Online Therapy Platform

Orb Health – Сare Management As A Virtual Service

BuenoPR – 360° Approach to Health

But Epic is the most optimal because interoperability is easier to achieve using EHR solution providers’ public or open API. And the exchange of data between Epic EHR and your product takes place using the Epic API.

API is an application programming interface, a set of rules for working with data. With its help, you can understand how to retrieve info and send it back in each case. It acts as a kind of intermediary between the application and the EHR/EMR system.

Upon receiving a specific request, the API relays it to the system. It then receives, processes, and issues a response containing all the necessary information about the patient in a unified approved format USCDI (The U.S. Core Data for Interoperability). 



This standardization is part of the Affordable Care Act. It allows the creation of a homogeneous data set so that information does not get confused, and any doctor can quickly and easily figure it out.


Want to learn more about EHR integration? Watch our podcast with the expert Jeff Fried, Director of Product Management at InterSystems.


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How to Integrate Your Health App with Epic EMR/EHR Systems?

First, think about the server where your application is stored. Next, check the compatibility of the sites from which you are going to collect information. Make sure the EHR/EMR supports these sites. 


The next step is to create an account at, which we mentioned earlier. This is required to access the API key. Confirm your identity; it is important to protect data transmitted encrypted via the SSL protocol. 


Check if the API will have the necessary endpoints so that, at some point, your application does not stop receiving data from the system. Check everything from medical history to allergy markers. You will see the API key on the website, which is best tested to see if all endpoints are working as expected.

Include API calls in your application code using endpoints. After everything is implemented and tested, you can take advantage of the Epic EHR/EMR integration.

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The Benefits of Integration EHR/EMR

 Among other preferences, we wanted to emphasize again:

  • Quick access to any medical institution. Doctors don’t always have the opportunity to see a patient in their office; sometimes, they have to go out and work with no computer with available data. The implementation of Epic EHR allows viewing everything from a smartphone. With Epic, healthcare providers exchange more than 200 million records each month.
  • Cost optimization. The Epic API is easier to integrate than HL7 or CCD. In the latter case, the developer must write a lot on his own; this significantly affects the project’s cost. Whereas Epic syncs with EHR/EMR for free.
  • Scalability. With Epic’s electronic health record integration, you can easily resize your database. It is helpful for medical organizations such as intensive care units, where patients are under constant supervision, resulting in many entries.


Who Needs Epic EMR/EHR Integration?

In addition to the above cases, the Epic USCDI API is the best fit for applications focused on remote patient treatment. For example, telemedicine. The patient does not need to collect all of his data from different clinics to forward it to the appropriate specialist. The doctor will find where to get them.

Epic EHR/EMR integration is also suitable for patient management, which tracks and controls treatment plans. When a patient’s medical history is reviewed, the app retrieves baseline and current clinical data (drug status and test results) and tracks changes.




Which Healthcare Organizations don’t Need Epic EHR/EMR Integration?

Note: if your software requires more than just retrieving data, you need to consider other APIs, because Epic only allows you to view the data, not make edits! Thus, if the attending physician is going to add new or correct existing information, remember about HL7, FHIR API, etc.

Epic is also not suitable if you need data synchronization or extensive analytical data (as a rule, there will be no overload with data on one patient). Also, Epic is not suitable for patient-oriented applications, as the information stored in the EHR/EMR is primarily for physicians.

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Cloud Computing in Healthcare: Benefits, Use Cases, & Challenges

Cloud computing has become an important part of modern businesses, and the healthcare industry is no exception. Healthcare providers must use cloud-based solutions if they want to keep up with the fast changes in the industry and give patients the best care possible. When used in the medical field, it significantly affects how information is stored, retrieved, and shared. It can also help hospitals save money, increase speed and agility, and provide better care to patients.

By 2027, the global market for cloud computing in healthcare will be worth $42.21 billion. This growth is likely driven by the growing need for healthcare organizations to store and analyze data and the growing number of healthcare organizations that use cloud solutions.


In some way, more than 83% of healthcare organizations are already using cloud computing, according to a survey done by HIMSS. The survey also found that medical firms are using cloud-based data storage solutions more to improve patient care, lower operational costs, and make their work more efficient. According to a study, global spending on cloud services will increase from $494.7 billion in 2022 to nearly $600 billion by the end of 2023. 

But why are healthcare organizations moving to the cloud? Keep reading this article; we will discuss cloud computing, its use in healthcare, its benefits, various types and platforms, and how it impacts the healthcare industry. Let’s jump right into it!

What is Cloud Computing?

The term “cloud computing” is often used to make computing resources, such as data storage and processing power, available on demand through a network of remote servers. The “cloud” is a network of remote data centers that can be accessed through the internet and used by many people simultaneously.

cloud based healthcare solutions

Cloud computing makes it easy to store documents in a central place where people can access them from any device at any time. In the past, you had to be at a certain place to use software and apps stored on a computer or server. With the help of cloud solutions, users can now access their data and apps through the web. 

Ins and Outs of Cloud Computing in Healthcare

When we talk about “cloud-based healthcare,” we’re referring to the practice of using solutions based on the cloud to develop and administer healthcare services. In contrast to the traditional method of setting up data centers on-site to store data on individual computers, this method gives healthcare stakeholders various ways to access the data servers from a distance. Also, this is very helpful for big and small health organizations because it lets them store data safely away from their main office.

Real-World Illustrations of How Cloud Computing is Transforming Healthcare

how cloud computing helps in communication and data transfer for healthcare providers


Cloud computing can help providers improve patient care by assisting them in keeping up with the latest advances in medicine and technology. Here are ten examples of how cloud computing is used in healthcare:

Thanks to cloud and telehealth services, patients can get clinical care no matter where they are. Telemedicine projects, like telemedicine apps, telesurgery, etc., can use cloud computing as the backbone of their information and communication technology. Also, doctors and healthcare stakeholders can talk to each other and share their knowledge to treat more complex and challenging conditions. In the field of telemedicine, cloud-based solutions can be used for the following:

  • Real-time, cross-border exchange of patients’ medical records
  • Accessing the stored information at a time and location of their choosing
  • Saving time and money by reducing pointless doctor visits

In the drug discovery and recovery process, much computing power is needed to sort through trillions of chemical structures and find promising compounds. The many IaaS services available in the cloud make this process much easier and faster. Several joint ventures, like the one between Newcastle University, Molplex, and Microsoft Research, have used IaaS to help find new drugs, thus saving a lot of time and money.

The healthcare sector has adopted management information systems to improve internal and external communication and serve patients better in several ways. Some of these ways include improving querying services, billing and finances, and the management of human resources. 

Because the data in this system is sensitive, the developers build, test, and put it into use using cloud-based platform services. With the help of cloud technology, the system can be constructed quickly and encourage teamwork. It can also be more easily connected to other healthcare systems.


Health firms can also use the cloud to manage patient health records (PHR) and electronic health records (EHR). Patients usually keep their health records (PHR), while managed-care organizations and single hospitals each keep their electronic health records (EHR) and electronic medical records (EMR). Thanks to cloud computing, it is now easier to control who has access to which resources and how.

healthcare professionals can use EHRs to improve patient data recording

The clinical decision support system (CDSS) is a highly developed program that acts and thinks like a doctor to help doctors analyze patient records. It is an expert system that models its recommendations on the knowledge and actions of a practicing doctor who has reviewed the patient’s medical records. 

With the development of fitness trackers and smartphones with biometric sensors for monitoring vitals like heart rate, blood pressure, and glucose levels, these cloud-based systems are helpful for real-time diagnosis. In addition, health providers can use CDSS for making diagnoses and writing prescriptions.

The adaptability and cost-effectiveness of cloud technology have made it a useful tool in the classroom. Medical students, doctors, professionals, and researchers are increasingly turning to cloud-based libraries to keep up with the most recent developments in their field.  


Digital libraries ensure that teachers, students, doctors, and scientists can always find the most up-to-date resources when they need them. In addition, doctors can learn about developments in the healthcare system and find resources to help them become more efficient in their work.

With cloud systems, healthcare organizations can better connect with patients because they can access patient data quickly and easily. Also, doctors and nurses can check on patients from a distance and collect real-time data.


Cloud computing helps healthcare organizations manage their supply chain more efficiently. They can also better manage patient populations more effectively, as they can access real-time data and make better decisions faster. 

Cloud solutions make it easier and faster for healthcare organizations to make and use mobile health apps. Health firms can also store and manage medical images quickly, securely, and efficiently.


Cloud-based solutions can help healthcare organizations prescribe medications to patients safely and efficiently. In addition, the big data analytics feature of cloud computing makes it easier for healthcare providers to analyze patient data and make informed decisions.

Types of Cloud Computing in Healthcare

Cloud computing in healthcare is classified based on its deployment environment and distribution service. 

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In the deployment environment, there are three main types of cloud computing in healthcare: public, private, and hybrid. We’ll briefly describe them below:

  1. Private Cloud Services

Private cloud services run on the organization’s servers and are managed by the IT department of the organization. Private cloud services are better for healthcare organizations that need to store and access sensitive data because they give more control and security than public cloud services. 

  1. Public Cloud Services

Public cloud services are hosted on the public internet and managed by a third-party hosting provider. Public cloud services are typically the least expensive and most widely used in healthcare. Public cloud services are ideal for healthcare organizations that don’t have the resources to manage their cloud infrastructure. 

  1. Hybrid Cloud Services

Hybrid cloud services combine public with private cloud services so that businesses can get the best of both worlds. Hybrid service is ideal for healthcare organizations that need to store sensitive and non-sensitive data. Hybrid cloud services combine the flexibility of public cloud services with the security and control of private cloud services.


Under distributive service, there are three major types of cloud computing in healthcare: SaaS, PaaS, and IaaS. We’ll briefly describe them below:

  • SaaS

SaaS is a cloud-based technology that offers web-based applications that are already set up, such as medical records management systems. With software as a service (SaaS), healthcare organizations can use cloud-based applications, but an outside party handles the hosting and management of those applications.

  • PaaS

Platform as a Service (PaaS) is a type of architecture in which development environments are hosted and managed by a remote cloud service provider. It also deals with software and hardware tools, such as a debugger, compiler, and source code editor. With a PaaS, HealthTech developers can quickly build, test, and launch their apps in production environments.

  • IaaS

IaaS, which stands for “infrastructure as a service,” is when an outside cloud provider hosts a network’s servers and storage spaces.


9 Benefits of Cloud Computing in the Healthcare Industry

The introduction of cloud solutions has greatly benefited the health sector. Let’s look at some of the significant benefits of cloud computing in the healthcare industry.

benefits of cloud computing in the healthcare software domain

With the help of cloud computing, the managed healthcare system can easily combine data from many different sources, like other facilities, data repositories, healthcare apps, wearables, etc. As a result, it helps spread information about patients, lets doctors make quick diagnoses, and ensures that people get the proper treatment as soon as possible.

Cloud solutions are usually cheaper than on-premise solutions, which can help healthcare organizations save money. Also, they can help lower operational costs by automating data storage and computing power and eliminating the need for physical storage.

Cloud solutions can help healthcare organizations streamline processes to do more work in less time. Healthcare providers can do their jobs more effectively by making it easier to access and analyze data and by using less expensive and time-consuming IT infrastructure. 


Cloud providers typically use advanced encryption technologies and access control to protect sensitive medical data while in transit and at rest. Also, because cloud service providers regularly update their data security measures, health firms can keep sensitive medical information from getting into the wrong hands and prevent data breaches. 

By using cloud computing, organizations can take advantage of the security measures that providers have in place rather than developing and maintaining their security infrastructure, which can be costly and difficult to manage.

Cloud computing makes it easier for healthcare providers to collaborate and share data with other providers more quickly and securely. Also, healthcare providers can quickly and easily access patient information, which lets them give timely, personalized care.

Cloud solutions can make it easier and faster for organizations to grow their operations because they can get more resources when needed. Also, you are only charged for the resources like data storage and computing power that you use. Thus preventing business owners from spending money upfront for expensive in-house hardware and servers that they may or may not use to their full potential.


Cloud storage for medical records makes storing and finding data more accessible, reducing the need to re-enter data and making it more accessible. When patients have access to their records whenever they need them, they feel more in charge of their health care and have a more significant say in the decisions that affect them. It helps with self-care and boosts engagement.

Cloud adoption can help healthcare organizations respond more quickly to changing market conditions as they can access more resources as needed. It also helps healthcare organizations rapidly adapt to evolving regulations and technologies.

Cloud computing helps healthcare organizations reduce medical errors by providing real-time access to data. Organizations can also reduce their risk of data breaches, as cloud solutions are typically more secure than on-premise solutions.

The Daunting Sies of Using the Cloud for Healthcare

In the same way that there are benefits to using the cloud for medical care, the innovation also has potential drawbacks and dangers to look out for. As a result, many businesses are still determining whether or not to adopt the technology. Some potential risks of using the cloud for medical care include the following:

Moving from an aging system to a cloud-based one necessitates a comprehensive rethink of how work is done. Healthcare institutions need to let everyone know what their daily work means.

One of the main ways this technology is used is to store sensitive medical information in the cloud. However, because of this, it’s vulnerable to assault. In addition, in a typical configuration, the data of many healthcare organizations is stored on the same server, leading to a risk of security breaches. Also, the isolation mechanisms put in place to prevent cross-contamination may fail.


Like other industries, healthcare won’t become more efficient by only adopting cloud computing. Instead, to get the most out of the technology, healthcare organizations must connect it to IoT, AI, and data management systems.

When it comes to healthcare software, it can be hard to find skilled developers who know how to use the latest innovations. Similarly, it can take a lot of work to track down cloud experts with experience in the health system.

how to choose a cloud provider

Choosing the Best Cloud Platform for Your Healthcare Business

Microsoft Cloud, Amazon Web Services (AWS), IBM Cloud, and Google Cloud Platform (GCP) are all well-known platforms for healthcare. However, the best cloud platform for healthcare depends on the needs and budget of the healthcare organization. 

For example, a company might need to store and manage many data in a HIPAA-compliant way. Therefore, a public cloud platform like Amazon Web Services or Microsoft Azure may be the best. On the other hand, if an organization needs a more secure solution, a private cloud solution such as OpenStack or VMware vCloud may be the best option. 

Google Cloud Platform offers healthcare organizations various services, including big data analysis and AI. In comparison, IBM offers cloud-based AI and blockchain solutions.


How does Cloud Computing Impact Your Healthcare Practice?

Cloud Computing is disrupting the Healthcare Industry. Here are the five significant Impacts of Cloud Adoption in Healthcare:

  • Integration: Organizations can easily integrate and securely access patient data across multiple points of origin and storage. This enables healthcare providers to deliver timely, personalized care while also reducing operational costs.
  • Access to high-powered analytics: Healthcare organizations can compute relevant patient data from multiple sources and automate processes, providing real-time access to data and helping to reduce medical errors.
  • Scalability: Cloud Computing offers affordable and quicker scalability solutions that can be highly customized to healthcare needs. 
  • Regularly updated information: Cloud Computing helps healthcare organizations stay updated on the latest Medical Research and Treatments. Cloud computing is changing how data is stored, accessed, and shared in the healthcare industry. This can help them provide the best care and improve patient outcomes.
  • Increased collaboration: Cloud solutions have become a crucial part of healthcare organizations’ digital transformation, enabling them to securely share healthcare data and collaborate with other organizations more efficiently.


Cloud computing has significantly impacted the healthcare industry, and the technology is expected to keep growing in the coming years. It has become an important part of the digital transformation of the healthcare system because it lets healthcare organizations store and manage their data more efficiently and securely while giving their customers better services.


When choosing a cloud healthcare platform or engineers, organizations should consider what they need and how much they can spend. Cloud solutions can help healthcare organizations stay competitive and give their patients the best care possible.

If you still have questions, contact us. The APP Solutions has deep expertise in the field, so don’t hesitate to get us about this or any other issue.  

Do you want to take your healthcare business to the cloud? Check out this article to find out all you need to know about cloud computing solutions in healthcare.

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FHIR Standard: The Crucial Healthcare Data Solution for Secure Interoperability

The healthcare industry has experienced several technological advancements in the last few decades, most of which have reduced costs and increased efficiency.

However, one area that continues to receive attention from tech giants is healthcare information interoperability.

The health data generated by various sources must be shared within a patient’s care plan and across multiple systems and database environments. But this can only be possible with some industry-standardized set of rules.

/FHIR Standard exchanging data

Enter FHIR – short for Fast Healthcare Interoperability Resources.

This blog post will explore FHIR in detail and explain why healthcare organizations increasingly adopt FHIR standards.


What Do Fast Healthcare Interoperability Resources Mean?

Fast Healthcare Interoperability Resources (FHIR) refer to healthcare data standard developed by the HL7 organization that enables secure, real-time health data exchange across disparate healthcare organizations.

The ultimate goal of FHIR is “interoperability,” meaning all digital products within the healthcare ecosystem can exchange information with one another regardless of the vendor or system used.

So, Who Uses FHIR?

FHIR is used by healthcare providers, payers, technology vendors, and other stakeholders in the healthcare industry. It is especially popular among developers of healthcare applications, as it offers a flexible and easy-to-use standard for exchanging data.

who uses fhir - basic ehr operating system

Yes, FHIR is designed to be interoperable with other healthcare standards, such as HL7 v2 and CDA. It is also being used in conjunction with emerging technologies like blockchain and artificial intelligence to improve healthcare interoperability and data exchange.

Why FHIR standard is Important for Healthcare Providers

FHIR is an important standard for healthcare organizations because it enables the secure exchange of electronically-protected health information across systems and providers. Different data formats can be exchanged through FHIR.

This standard can help remove data silos created over time by disparate IT systems across multiple departments within a hospital system.

Let’s look at the key benefits of FHIR in the next section.

FHIR provides a standardized way for health systems, patients, physical records providers, and other healthcare applications to interact securely. It makes data sharing across different platforms in real-time more manageable. This can reduce the time required to access particular medical histories or test results within one system from multiple sources.


FHIR interoperability with EHRs

FHIR enables faster clinical decision support through near-instantaneous exchanges of the requested information, such as clinical data that may be required before a physician makes diagnosis/treatment decisions.

FHIR enables healthcare professionals to rapidly access patient information from multiple electronic health records (EHR) software systems by connecting different platforms. This helps reduce time lags arising from cross-platform implementations, allowing healthcare professionals to access vital client details remotely conveniently and timely.


Data standards defined by FHIR are instrumental in enhancing security protocols and ensuring compliance with HIPAA regulations. The open APIs offered via cloud technologies enable administrators to manage access to data, thereby aiding in the protection of sensitive patient information and safeguarding patient privacy.

FHIR’s well-defined terminology ensures everyone on a health IT system can understand what different components mean. This significantly speeds up how quickly clinical care is delivered, improves accuracy, and minimizes misunderstandings due to the ambiguity of non-cross-deployed API architecture implementations.

According to Statista, by 2025, the market for health-related financial analytics services using big data will increase to over 13 billion U.S. dollars. For organizations to be market-ready in the future, they must implement an efficient analytics system. FHIR also helps them because it allows for accurate longitudinal tracking of medical records within standards.

hl7 fhir statistics

This means healthcare organizations can leverage algorithmic-based machine intelligence tools to track disease patterns or other variables like appointment attribution automatically.

Improved data analytics also enable better planning/forecast decisions regarding resource allocation over time, resulting in financial savings and efficient use of personnel services.


If you want to know more about HL7 FHIR integration, you should definitely listen to our CareMinds podcast, particularly the episode with Redox specialist Nick McKenzie.

Nick went on to work with the EHR integration architecture, which he compares to building a house, where an entire team of contractors, roofers, electricians, and plumbers work cohesively under an architect. 

“I was always fascinated with this idea of being the translator helping clinicians translate their requirements into what they wanted the system to be designed and then translating back to the technical teams how to execute and interestingly enough. It’s all that product management really is.”

Watch other episodes as well!


How FHIR Works Across Healthcare Organizations

FHIR harnesses a modern, web-based approach to connect different healthcare systems, allowing data to flow effortlessly between them.

With its modular architecture, FHIR can adapt to the diverse needs of various healthcare organizations, from bustling hospitals to research institutions.

FHIR is built upon a set of resources, like building blocks representing standardized clinical and administrative data.

These resources are organized into modules, each representing a specific aspect of healthcare data.


For example, the Patient module has patient demographics, medical history, and care team data. The Observation module captures information on a patient’s vital signs, lab results, and other information in clinical documents.

For healthcare organizations to exchange critical information in a secure manner using FHIR, they rely on an interoperability layer that transforms the data into a universal format. This layer is an FHIR server, which can be hosted locally or in the cloud. Healthcare organizations can easily access FHIR servers using standard internet protocols like RESTful web services and OAuth 2.0 authentication.

When one healthcare organization needs to exchange data with another, it sends a request to the other organization’s FHIR server. The proposal indicates the data types, and the server responds by sending the requested data in a standardized format.

The receiving organization can then use the data in its systems, such as electronic health records, decision support systems, or population health management tools.


hl7 fhir Resources

What are FHIR Resources, and How Do They Function?

FHIR resources are structured documents and messages representing various health and medical entities.

The FHIR standard defines the structure and content of these documents, which include patient data, insurance claims and billing information, diagnostic and laboratory records, medication use information, and care plans.

These resources drive effective health information exchange between stakeholders, such as healthcare providers, insurers, and patients.


Must-Know Fundamentals of FHIR Interoperability

Here are four important things to know about FHIR interoperability basics:

  • FHIR is built for modern healthcare: It was designed using the latest web technologies and follows a modular approach, making it more flexible and scalable than other healthcare data exchange standards.
  • Flexible and customizable: FHIR resources can be easily extended to accommodate custom data elements and new use cases. This helps developers easily choose the components they require for particular use cases.
  • Promotes data interoperability: It drives the free flow of healthcare data among different systems. This enables healthcare providers to coordinate care more effectively and allows patients to access their health data easily.
  • Being widely adopted: Many major EHR vendors and healthcare organizations already use FHIR-based solutions because of their ease of use and ability to support modern healthcare workflows.
leverages existing logical

How Health Entertainment is Transforming Mental Healthcare

Health entertainment transforms mental healthcare by providing activities and games to improve relaxation, exercise the mind, or provide other forms of therapy.

These health-themed interactive programs are meant to divert from everyday stressors while helping people recognize signs of depression and seek help more enjoyably. Health entertainments often focus on creating positive experiences with wellness information through:

  • Music listening parties that promote self-care strategies.
  • Guided audio stories that explore mindfulness skills.
  • Videos that highlight new perspectives on relationships between emotion regulation techniques, understanding trauma, and resilience-building resources coupled with quality physical activity instruction.
    The physical activity instruction is specifically designed to address concerns about body image.



The FHIR standard is a positive approach to data communication and interoperability for the healthcare sector. It provides an efficient way to access, share, and manage health data in various settings.

Now that you have learned about its features and benefits, it’s time to ensure that your organization takes advantage of this technology as quickly as possible.

Organizations can improve healthcare outcomes by leveraging the FHIR Standard through effective security protocols such as authentication methods or encryption technologies while ensuring medical information’s safe transmission and accuracy.

What is EHR (electronic health record), and how does it work?

Healthcare and data science are something of a perfect pair. Healthcare operations require insights into patient data to function at a practical level. At the same time, data science is all about getting deep into data and finding all sorts of interesting things. 

The combination of these two resulted in the adoption of Electronic Health Records (EHR) that use a data science toolkit for the benefit of medical procedures.

In addition to this, healthcare is the perfect material for various machine learning algorithms to streamline workflows, modernize database maintenance, and increase the accuracy of results.

In this article, we will explain what EHR is and how machine learning makes it more effective.


What is EHR?

Electronic Health Record (aka EHR) is a digital compendium of all available patient data gathered into one database. 

The information in EHR includes medical history, treatment record data such as diagnoses, medications, treatment plans, immunization dates, allergies, radiology images, laboratory and test results.

  • The adoption of EHR in the industry kickstarted in the late 90s after the enacting and signing of HIPAA (Health Insurance Portability and Accountability Act) in 1996. 
  • However, due to technological limitations, things proceeded slowly. 
  • The technology received a significant boost after the passing of the HITECH (Health Information Technology for Economic and Clinical Health) Act in 2014 which specified the whats, whys, and hows of EHR implementation.

The main goal of implementing EHR is to expand the view of patient care and increase the efficiency of treatment.


In essence, EHR is like a good old patient’s paper chart which expands into a full-blown, interactive, data science dashboard, with real-time updates where you can examine the information and also perform various analytical operations. 

  • Think about it as a sort of Google Account type of thing, where your data is gathered into one place and you can use it for multiple purposes with tools like Office 365 or the likes.

The critical characteristics of Electronic Health Records are:

  1. Availability – EHR data is organized and updated in real-time for further data science operations, such as diagnostics, descriptive analytics, predictive analytics, and, in some cases, even prescriptive analytics. It is available at all times and shared with all required parties involved in a patient’s care – such as laboratories, specialists, medical imaging labs, pharmacies, emergency facilities, etc. 
  2. Security – the information is accessed and transformed by authorized users. All patient data is stored securely by extensive access management protocols, encryption, anonymization, and data loss protection routines.
  3. Workflow optimization – EHR features can automate such routine procedures as recurrent Automate and streamline provider workflow. In addition to this, EHR automation can handle healthcare data processing regulations such as HITECH, HIPAA (USA), and PIPEDA (Canada) by implementing required protocols during data processing.

Electronic Health Records vs. Electronic Medical Record – What’s the Difference?

There is also another type of electronic record system used in healthcare operations – Electronic Medical Records AKA EMR. 

The main difference between EHR and EMR is the focus on different persons involved in medical procedures. 

  • EMR is a digital version of the dataflow in the clinician’s office. It revolves around a specific medical professional and contains treatment data of numerous patients within the specialist’s practice.
  • In contrast, EHR data revolves around the specific patient and his medical history. 

In one way or another, EHR intertwines with numerous Electronic Medical Records within its workflow. There is a turnaround of data going back and forth – medical histories, examination data, test results, time-based data comparison, and so on.

Read a more detailed overview of EHR/EMR differences in the article EHR, EMR and PHR Differences

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How AI/ML fits into Electronic Health Record?

As was previously mentioned, the availability of data is one of the primary benefits of implementing Electronic Health Records into medical proceedings. 

Aside from data being available for medical professionals at all times, the way medical data features in EHR makes it perfectly fitting for various machine learning-fueled data science operations.


Overall, machine learning is a viable option in the following aspects of Electronic Health Record:

  • Data Mining
  • Natural Language Processing 
  • Medical Transcription
  • Document Search
  • Data Analytics
  • Data Visualization
  • Predictive Analytics
  • Privacy and regulatory compliance

Let’s look at them one by one.

Data mining 

Gathering valuable insights is one of the essential requirements for providing efficient medical treatment. One of the challenges that come with gaining insights is that, in order to do that, you need to go through a lot of data. This process takes a lot of time.

With the increasing scope of data generated by medical facilities and its growing complexity – the use of machine learning algorithms to process and analyze information during data mining becomes a necessity. 

Overall, the use cases for Data mining in Electronic Health Record revolve around two approaches with different scopes:

  • Finding data about the patient and his treatment. In this case, ML is used to round up relevant information in the medical history and treatment record to assist further in the decision-making process. 
  • On the other hand, patient-centered data mining is used to assess different types of treatment and outcomes by studying similar cases from the broader EHR database.
  • Data extraction for medical research across multiple EHR/EMR, and also public health datasets. In this case, a machine learning application is used to gather relevant data based on specific terms and outcomes across the EHR database. For example, to determine which types of medication for particular ailments were proven to be active and under what circumstances.
  • On the other hand, the same tools apply for exploratory research that reshapes available data according to specific requirements — for example, examining test result patterns of annual lipid profiles.



Predictive Analytics

EHR is all about data analytics and making it more efficient. One of the most important innovations brought by Electronic Health Record is streamlining the data pipeline for further transformations.

The thing is – EHR machine learning-fueled data processing provides a foundation to identify patterns and detect certain tendencies occurring throughout numerous tests and examinations of a specific patient across multiple health records. 

  • With all patient data and respective reference databases intertwined into a single sprawling system – one can leverage the available data to predict possible outcomes based on existing data. 
  • Predictive analytics assist the doctor’s decision-making process by providing more options while considering possible courses of action.
  • On the other hand, machine learning predictive analytics reduces the time required to pro.  

Predictive analytics models are trained case-by-case on the EHR databases. The accumulation of diverse data allows them to identify common patterns and outliers regarding certain aspects of disease development or a patient’s reaction to different treatment methods.

Let’s take DNA Nanopore Sequencing as an example. 

  • The system combines input data (coming from the patient) with data about the illness and ways of treating it. 
  • The predictive algorithm determines whether a particular match of treatment will result in a positive outcome and to which extent. (you can read more about Nanostream in our case study).

Natural Language Processing

In one way or another, natural language processing is involved in the majority of EHR-related operations. The reason for that is simple: most medical record documentation is in a textual form combined with different graphs and charts to illustrate points.

  • Why not use a simple text search instead? Well, while the structure of the document is more or less uniform across the field, the manner of presentation may vary from specialist to specialist. NLP solution provides more flexibility in that regard.

The main NLP use cases for Electronic Health Record are the following:

  • Document Search – both as part of the broader data mining operation and simply as an internal navigation tool. In this case, the system uses a named-entity recognition model trained on a set of specific terms and designations related to different types of tests and examinations. As a result, doctors can save time on finding relevant information in the vast scopes of data. Depending on the purpose, the search results form via the following methods:
  • By context – locating information within the document – vanilla document search. For example, you can perform a comparison of physical examination reports criteria by criteria.
  • Terms/Topics/Phrases – extracting instances of specific terms used or topics mentioned. For example, a doctor can obtain all blood test results and put them into perspective.
  • Search across multiple documents;
  • One of the most prominent current applications is the Linguamatics I2E platform which also provides data visualization features.
  • Medical transcription – in this case, NLP is used to recognize speech, and subsequently, format it in an appropriate way (for example, break down into segments by context).
  • The speech-to-text component operates with a set of commands like “new line” or “new paragraph.”
  • Nuance Communications make one of the most prominent products of this category. Their tools, Nuance Dragon, augments EHR with a conversational interface that assists with filling data into the record.
  • Report generation – in this case, NLP functions as a form of data visualization in a textual form. These models are trained on existing reports and operate on specific templates (for example, for blood test results). Due to the highly formalized language of the reports, it is relatively easy to train a generative model based on term and phrase collocation and correlation. 
  • In this case, the correct verbiage is analyzed out of the habitual juxtaposition of a particular word with another word or words with a frequency higher than chance (collocation) and the extent to which two or more variables fluctuate together (correlation). 


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Data Visualization

Data visualization is another important aspect of data analytics brought to its full extent with the implementation of Electronic Health Records. 

Visualization is one of the critical components that make Electronic Health Record more effective in terms of accessibility and availability of data for various data science operations. 

  • The thing is – as an electronic health record is basically a giant graph with lots of raw data regarding different aspects of the patient’s state, as such, it is not practical to use it in this state. The role of visualization, in this case, is to make data more accessible and understandable for everyday purposes. That has to be obvious, right?

However, you can’t use the same data visualization template for every EHR. While the framework remains the same, it requires room for customization to visualize patient data on the EHR dashboard adequately. 

The role of machine learning in this operation parallels its role in data mining. However, in the case of data visualization, it is about interpreting data in an accessible form. 

At the current moment, one of the most frequently used visualization libraries in Electronic Health Record is d3. For example, we have used its sunburst and pie charts in the Nanostream project. 


Regulatory compliance, privacy, and patient data confidentiality

Healthcare is an industry that mostly operates with sensitive data through and through. Pretty much every element of healthcare operation, in one way or another, touches certain aspects of privacy and confidentiality. 

The fact is that integrated systems like EHR are vulnerable to breaches, data loss, and other unfortunate things that may happen to data in the digital realm. 

In addition to that, healthcare proceedings are bound by government regulations that detail the ins and outs of personal data gathering, processing, and storing in general, and specifically in the context of healthcare.

Such regulations as the European Union’s GDPR, Canada’s PIPEDA, and United States’ HIPAA describe how to handle sensitive personal data and what the consequences are of its mishandling.

The implementation of EHR makes compliance with these regulations much more convenient as it allows us to automate much of the compliance workflow. Here’s how:

  • Anonymization during data processing – in this case, patient data is prepared for testing, but non-crucial identifiable elements, such as names, are concealed.
  • Access management – EHR structure allows limiting access to patient data only for those involved in a patient’s treatment. 
  • A combination of encryption for data-at-rest and data-in-transit – the goal is to avoid any outside interference into data processing.


In Conclusion

The adoption of electronic health records and the implementation of machine learning elevates healthcare operations to a new level.

On the one hand, it expands the view on patient data and puts it into the broader context of healthcare proceedings.

On the other hand, machine learning-fueled EHR provides doctors with a much more efficient and transparent framework for data science that results in more accurate data and deeper insights into it.

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How to leverage a mobile device management system to ensure EMR security in mobile healthcare apps

Mobile applications improve medical professionals’ productivity. One can use an app for communicating with the client, sharing health records with colleagues, and even calculate medication doses. The main issue of all medical software is that it contains health sensitive data that could be stolen by hackers. Even if you make your app HIPAA compliant, you need to consider additional security measures such as mobile device management.  

Unless you want your clinic name to appear on the “Wall of Shame” of the U.S. Department of Health and Human Services, due to data breaches, you need to be aware of the main mobile device management services to integrate into your app.  

But first, let us take a closer look at healthcare mobile apps adoption across the medical industry. 

Use of mobile devices in healthcare

To meet modern healthcare standards, care facilities and hospitals implement a ‘bright your own device’ (BYOD) policy toward medical personnel. The policy may concern mobile devices, tablets, and laptops for accessing EHR and EMR, communication with care staff, record care data, and lookup prescription information, which also have a positive impact on medical treatment results.  

In particular, the need for mHealth app adoption concerns the U.S. health organizations, where the Health Information Technology for Economic and Clinical Health Act, devoted to health records digitization, was agreed on at the governmental level in 2009. Here are some stats:

  • Global mHealth Apps Market is expected to reach $111.1 billion by 2025
  • 93% of physicians believe mobile medical apps have a positive impact on the treatment outcome. 
  • Over 70% of medical personnel use mobile devices to communicate with parents and access Electronic Medical Record (EMR). 
  • The majority (84%) of patients think that their medical records are safe from unauthorized viewing.

However, patient sensitive data and medical mobile app security are not as optimistic as they seem. Why? Let’s find out. 

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What is wrong with EMR

The adoption of mobile healthcare apps among medical professionals has resulted in an increased number of potential threat vectors and sensitive health data exposure, such as medical history and treatment plans.

  •  In the U.S. alone, 1,512 data breaches were affecting 154,415,257 patient records from 2013 to 2017, while 128 violations were related to EMR and affected 4,867,920 patient records. 
  • In total, data breaches on healthcare cause annual damage of $6.2 billion, which results in patient mistrust, loss of potential revenue, and penalties by the government.

According to the U.S. Department of Health and Human Services, which keeps an archive of health data breaches, the high percentage of breaches were traced to “other portable electronic device[s]”. What does this mean? Let us explain. 

Even if you develop EMR that competes with HIPAA security requirements, you are also responsible for information kept on mobile devices that access your EMR app. While 31% of decision-makers in healthcare avoid implementing EMR in mobile apps due to security reasons, around 49 consider implementing mobile device management tools to improve the security of their systems. 

In a nutshell, it is easier to keep all patient-related data in one place, but on the other hand, this can be quite risky. Therefore, to make your EMR mobile app secure from breaches, you need to integrate mobile device management software that will regulate user access to medical records.

“What is mobile device management software

Mobile device management strategies for healthcare organizations

As we said, consumer mobile devices are not secure by default. Moreover, healthcare organizations from the U.S. must meet recommendations by the Office for Civil Rights (OCR) which includes established policies for mobile device data security and staff training.  Otherwise, you will violate the Health Insurance Portability and Accountability Act or HIPPA. 

The solution is to apply mobile device management software. “What is mobile device management software”, you may ask. Well, MDM software enables you to control and monitor the mobile devices of users that installed your app. 

Before developing an EMR mobile app with MDM, you need to create a BYOD policy that will regulate: 

  • EMR app usage cases
  • Privacy and data ownership 
  • Types of approved devices and device provisioning
  • Security policies 
  • Evaluation of risks and liabilities
mobile device management use cases

[How does MDM work]

With this in mind, let’s find out more about mobile device management use cases and how to integrate them into your app.  


Geofencing is the type of geolocation app technology that detects user location via GPS and allows or prohibits using your app, or accessing particular data. In terms of the healthcare industry, MDM with geofencing will create boundaries around your hospital. If the app user crosses those boundaries by leaving your facility, the app triggers a response by restricting or allowing access to your EMR app.

mobile device management features

To integrate geofencing mobile device management features to your app, your mobile app development team will use MapKit or Google Maps SDK for iOS installed via CocoaPods for Apple devices and Geofencing API to add this feature to Android apps. 

App wrapping

You can enable mobility management and content delivery using existing mobile device management technology for data encryption or “wrapping,” such as XenMobile, which adds additional security to app data. Moreover, this MDM healthcare solution will automatically interrogate incoming users to know who they are, where they’re coming in from, using which device, and what data they’re trying to access. Besides this, XenMobileis includes other benefits of mobile device management:

  • Controlling native mobile apps and associated data 
  • Proving secure funnel file sharing solutions into management architecture
  • Enabling role-based access to different users. 
  • Tracking, locking, and wiping mobile devices that use your app
  • Enabling micro-app VPN for over-the-air data transmissions

To add this solution into an in-house EMR app, your development team needs to add just one line of code, since XenMobile is extremely easy to integrate. 

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Remote management

In terms of the BYOD policy, the staff’s mobile devices could be stolen or lost. In this case, to protect your healthcare organization’s data from breaches, integrate remote user management software. By means of such software, you can remotely lock the device down, encrypt particular data, or erase it from the device while keeping their personal information. 

Remote mobile device management is available in the following MDM solutions: 

Application control

If an outside app is tainted by malicious code, it can siphon data from other apps on the device, which jeopardizes patient data. Application control lets you decide which apps to permit, and which to blacklist or disable. Also, you can use “containerization” to partition an area of each device for dedicated work-use; that way, distrusted third-party apps are kept separate from the EHR app on a mobile app.

The best MDM products with an application control feature are the following: 


To control all the app users that receive access to your EMR, consider a session management feature that will automatically generate reports with the following data:

  • List of sessions 
  • Search for session 
  • View session info with user’s email, duration, session ID

Thanks to this feature, you can track, not only what is happening in your system, but also, identify suspicious patterns and threads. Moreover, the MDM reporting feature will provide you with insights into your organization’s mobile environment, including device status, user information, log-in attempts, and compliance with password policies in real-time. 

To ensure your patients’ health data security is to create a formal device policy that will educate your medical staff about security risks and best practices. Next, consider the integration of mobile device management into your app. By using software built by reliable MDM solution providers, you will receive control over all mobile devices in your corporate network, data stored, third-party and native apps, and data transmission. 

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Related reading: 

A Guide on How to Create a Telemedince App 

Calmerry Telemedicine Platform Case Study 

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