From enhancing medical image analysis to helping pharmaceutical companies speed up the drug discovery process, machine learning models are creating new opportunities across healthcare. In this blog, we’ll explore seven key benefits of machine learning applications in healthcare and how they impact both healthcare professionals and patients alike.

1. Improved Medical Imaging and Diagnostics

One of the most valuable applications of machine learning in healthcare is its ability to analyze medical images with incredible accuracy. Machine learning algorithms are used to detect abnormalities in X-rays, MRIs, and other scans, often faster and more accurately than traditional methods. These models help healthcare professionals diagnose conditions like cancer, heart disease, and neurological disorders earlier, leading to quicker treatments and better patient outcomes.

Key benefits:

• Enhanced accuracy in detecting abnormalities
• Faster diagnosis of serious conditions
• Early intervention leading to better outcomes

2. Personalized Treatment Plans

Machine learning models allow for more personalized treatment plans by analyzing patient data in real time. Through the application of machine learning in healthcare, healthcare professionals can tailor treatments based on individual patient records, genetic data, and lifestyle factors. This approach results in more effective treatment plans, especially for chronic diseases such as diabetes, heart disease, and cancer.

Key benefits:

• Tailored treatment plans based on real-world patient data
• Improved effectiveness of chronic disease management
• Data-driven decisions for individualized care

3. Streamlined Clinical Trials

Clinical trials are a critical part of developing new treatments, but they can be time-consuming and expensive. AI and machine learning in healthcare are changing that by optimizing the clinical trial process. Machine learning algorithms help identify the best candidates for trials based on electronic health records and patient data, speeding up recruitment and improving the accuracy of trial results. This results in shorter trial times and quicker access to new treatments.

Key benefits:

• Faster recruitment for clinical trials
• More accurate trial results
• Accelerated drug discovery process

4. Enhanced Drug Discovery Process

Pharmaceutical companies are using machine learning models to speed up the drug discovery process. By analyzing vast amounts of medical records, scientific literature, and patient data, machine learning can predict which compounds are most likely to succeed in treating specific diseases. This reduces the time and cost associated with traditional drug development while bringing life-saving treatments to market faster.

Key benefits:

• Reduced time and cost in drug discovery
• Predictive analysis of drug success
• Faster access to new medications for patients

5. Efficient Data Collection and Analysis

Machine learning algorithms excel at handling large datasets, making them ideal for analyzing complex healthcare data. From patient records to real-time data collection from medical devices, machine learning can quickly process and identify trends. This ability to analyze electronic health records and other patient information helps healthcare professionals make more informed decisions about treatment options and patient care.

Key benefits:

• Efficient handling of large datasets
• Real-time analysis of patient data
• Informed decision-making for healthcare professionals

6. Predictive Analytics for Better Outcomes

Another key example of machine learning in healthcare is its use in predictive analytics. Machine learning models can analyze patient records and medical data to predict potential health risks, such as the likelihood of heart disease, diabetes, or other chronic conditions. By using real-world data, these models help healthcare providers intervene earlier and take preventative measures to improve patient health outcomes.

Key benefits:

• Early detection of health risks
• Preventative care based on predictive analytics
• Improved patient outcomes through early intervention

7. Improved Natural Language Processing (NLP) for Patient Care

Natural language processing (NLP) is a subset of machine learning that can interpret and analyze unstructured data, such as doctors’ notes, medical records, and research papers. In healthcare, NLP applications help healthcare professionals better understand patient data and make more informed decisions. By extracting insights from these documents, machine learning in healthcare ensures that no vital information is missed, leading to more accurate diagnoses and improved care.

Key benefits:

• Interpretation of unstructured data (e.g., medical records, doctor’s notes)
• Better insights into patient data for improved care
• More accurate diagnosis and treatment plans

The Bottom Line

Machine learning applications in healthcare are revolutionizing the way healthcare professionals diagnose, treat, and manage patient care. From improved medical image analysis to personalized treatment plans and more efficient data collection, the benefits of machine learning in healthcare are vast.

By leveraging AI and machine learning algorithms, the healthcare industry can make faster, more accurate decisions, ultimately improving patient outcomes and enhancing the quality of care. Whether it’s streamlining the clinical trial process or helping doctors predict potential health risks, machine learning is paving the way for a smarter, more efficient healthcare system.

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1. Analyzing Medical Records and Clinical Notes

The use of natural language processing in healthcare is essential for analyzing unstructured data, such as medical records and clinical notes. Doctors and nurses often manually review patient data to make informed decisions, but this process can be time-consuming. With NLP algorithms, healthcare organizations can quickly scan through clinical notes and extract important information about a patient’s medical history.

Key benefits:

• Speeds up the review of medical records
• Extracts relevant information from unstructured data
• Improves accuracy in patient care

2. Improving Clinical Decision Support

One of the major roles of natural language processing in healthcare is to enhance clinical decision support (CDS) systems. NLP technologies can process large volumes of patient data, identify patterns, and offer real-time insights that help healthcare professionals make better clinical decisions. By integrating NLP with electronic health records (EHR), healthcare providers can access the most relevant data to support treatment plans.

Key benefits:

• Provides real-time clinical decision support
• Enhances accuracy in diagnosing and treating patients
• Integrates seamlessly with EHR systems

3. Entity Recognition for Better Data Organization

Entity recognition is one of the most popular NLP applications in healthcare. This process involves identifying specific entities, such as medications, diseases, or procedures, within clinical notes or medical records. By recognizing these entities, NLP tools can organize data into a structured format, making it easier for healthcare professionals to access the information they need without manually reviewing extensive records.

Key benefits:

• Extracts key entities from unstructured data
• Organizes patient data into structured formats
• Reduces the time spent manually reviewing records

4. Mining Social Media for Health Insights

The role of natural language processing in healthcare goes beyond traditional medical records—it also extends to analyzing social media content. Healthcare organizations and researchers can use NLP tools to mine social media posts for health-related insights. For example, they can track trends in public health or monitor discussions about symptoms, treatments, or side effects related to medications.

Key benefits:

• Identifies public health trends in real time
• Monitors patient experiences with treatments
• Provides healthcare organizations with valuable real-world data

5. Streamlining Clinical Trials

Natural language processing NLP technologies also play a key role in making clinical trials more efficient. By analyzing patient data and medical history, NLP tools can help identify suitable candidates for clinical trials. This speeds up the recruitment process, ensuring that trials can be conducted faster and more accurately. Additionally, NLP can be used to sift through trial results to identify trends or patterns.

Key benefits:

• Speeds up the clinical trial recruitment process
• Improves accuracy in candidate selection
• Analyzes clinical trial results more effectively

6. Enhancing Electronic Health Records (EHR)

Electronic health records are a goldmine of information, but they often include unstructured data, such as doctors’ notes or patient histories. The use of natural language processing in healthcare helps convert unstructured data into structured data that is easier to analyze and access. NLP tools can extract meaningful insights from EHRs, improving the overall efficiency of healthcare organizations.

Key benefits:

• Converts unstructured data in EHRs to structured data
• Improves accessibility and usability of patient records
• Helps healthcare professionals make informed decisions

7. Developing AI-Powered Virtual Assistants

Artificial intelligence (AI) and NLP are working together to develop virtual assistants that can interact with patients and healthcare professionals. These AI-powered virtual assistants can answer patient questions, provide appointment reminders, and even assist doctors in gathering patient information. By leveraging NLP technologies, these assistants can understand and respond to human language, making healthcare more accessible.

Key benefits:

• Improves communication between patients and healthcare providers
• Offers real-time support for healthcare professionals
• Increases patient engagement through personalized interactions

The Bottom Line

Natural language processing in healthcare and biomedicine is opening up exciting new possibilities for improving patient care and making healthcare systems more efficient. From enhancing clinical decision support to analyzing social media trends, the applications of NLP in healthcare are vast.

By processing unstructured data like clinical notes and medical records, NLP algorithms are helping healthcare organizations streamline operations and make better-informed decisions. As AI and machine learning continue to evolve, the role of natural language processing in healthcare will only grow, benefiting both healthcare professionals and patients.

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These apps help users manage health issues, track treatment plans, and make informed decisions in real time. If you’re wondering what an app in healthcare looks like or how app developers design these tools, keep reading.

1. Teladoc – Affordable Virtual Care

Teladoc offers affordable medical care with a flat fee of $75 per session. Patients can access doctors, dietitians, and coaches for various health issues. The app developers designed it to improve healthcare access through a smooth user experience.

• Key Features:
  • Option to prescribe medication
  • Available in multiple languages, including American Sign Language
  • Real-time health monitoring tools

2. Amwell – Best for Insurance Coverage

Amwell is an app in healthcare known for its wide insurance acceptance. Users can schedule video consultations with doctors and mental health professionals, ensuring better access to medical care.

• Highlights:
  • Works with major insurance providers
  • Provides evidence-based treatment plans
  • Integrates with electronic health records (EHRs)

3. Medisafe – Medication Reminders Made Easy

Medisafe helps users manage chronic conditions by sending reminders to take medications. This healthcare app development focuses on improving patient compliance with treatment plans.

• Features:
  • Virtual pillbox notifications
  • Caregiver support
  • Tracks progress with daily and weekly reports

4. ZocDoc – Easy Appointment Scheduling

ZocDoc is a mobile app in the healthcare industry that helps users find healthcare services and book appointments instantly. This app works by showing real-time availability for doctors, avoiding long wait times.

• Why Users Love It:
  • Simplifies the scheduling process
  • Provides reviews of healthcare providers
  • Integrates with healthcare systems for a better user experience

5. Doctor on Demand – Telehealth for Everyone

Doctor on Demand is a popular mobile health app that connects patients to licensed doctors and therapists. Through video consultations, users can get medical care for non-emergency health conditions from anywhere. The app works seamlessly, letting users book appointments or get care on-demand.

• Key Features:
  • Prescribe medication during virtual visits
  • Treatment plans for physical and mental health issues
  • Available on iOS and Android

6. Heal – Doctor House Calls Made Simple

Heal brings back the traditional house call with a modern twist. Users can schedule in-home visits with doctors via this medical app, which enhances patient care by offering personalized attention.

• Benefits:
  • Available in select U.S. cities
  • Ideal for patients with mobility issues
  • Doctors can prescribe medication during visits

7. Fitbit – Track Your Health and Fitness

Fitbit isn’t just a fitness tracker—it’s a mobile health app that offers insights into health conditions like heart rate variability. This app for healthcare enhances patient engagement through activity challenges and real-time data logging.

• Why It Stands Out:
  • Syncs with wearable devices
  • Tracks workouts and health metrics
  • Integrates with treatment plans for chronic conditions

8. MyChart – Your Health Records, Simplified

MyChart gives users easy access to their electronic health records. This healthcare app development simplifies how patients interact with their healthcare providers, making it easy to manage chronic conditions.

• Features:
  • Pay bills and view test results
  • Schedule appointments and message providers
  • Enhances patient care with better communication

9. Talkspace – Therapy at Your Fingertips

Talkspace offers a mobile app for healthcare services focused on mental well-being. It connects users with therapists and psychiatrists through text or video chats. This medical app is designed to provide quick access to therapy, enhancing the user experience by making mental healthcare more accessible.

• Why It Works:
  • Secure platform for evidence-based therapy
  • Personalized treatment plans
  • 24/7 access to therapists

10. GoodRx – Save on Prescriptions

GoodRx is a mobile health app that helps users find the lowest prices on prescription medications. It enhances patient care by providing tools to manage health costs.

• What It Offers:
  • Search discounts at over 75,000 pharmacies
  • Compare prices to make informed decisions
  • Helps patients stay on track with medication management

The Bottom Line

The healthcare system benefits greatly from mobile apps that improve access, simplify workflows, and enhance patient outcomes. Whether you’re looking for an app to manage chronic conditions, access healthcare services remotely, or track fitness data, these apps for healthcare provide innovative solutions.

App developers are playing a crucial role in building secure and user-friendly tools. The best healthcare apps combine evidence-based practices with intuitive design to meet the needs of users. With medical apps like Teladoc, Medisafe, and MyChart leading the way, the mobile health app landscape will continue to grow, creating better healthcare experiences for all.

These apps aren’t just tools—they’re transforming how medical care is delivered and accessed. If you’re curious about what an app in healthcare looks like or how these apps work to enhance patient care, these examples provide a great starting point.

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In this blog post, we explore three of the main benefits of adopting new or custom technology in healthcare, focusing on how advanced systems and tools like AI, telehealth, and hospital management systems drive efficiency, improve accessibility, and enhance the quality of care.

The types of technologies influencing the healthcare industry continue to evolve at breakneck speed. Not only that, new use cases for existing technologies are being discovered and iterated upon every day.

From various types of artificial intelligence to telemedicine, today’s healthcare technologies provide numerous opportunities to improve patient care, while creating efficiencies and enhancing healthcare accessibility.

While both benefits and challenges of technology in healthcare exist, for most healthcare providers, the benefits far outweigh any potential challenges.

Curious to learn why that is? We invite you to read about our top three benefits of advanced technology in healthcare (with examples) to see exactly why adopting them might just be the best decision you haven’t yet made.

1. Efficiency

Technologies like artificial intelligence are being applied to healthcare in new ways daily. Such is the case for medical diagnosis and research software and AI/ML-enhanced hospital management systems. New healthcare technologies such as these are key drivers of efficiency (and accuracy) for healthcare providers.

For instance, say you want to upgrade your hospital management system.

Adopting an advanced HMS could streamline or even automate administrative processes like patient registration and billing. It could also help consolidate patient data, leading to faster access to key information.

An advanced HMS might also streamline communication between key personnel while making it easier to make data-driven decisions that better benefit patients.

This is just one example: there are countless other healthcare technologies driving efficiency every day, from predictive analytics to mobile health apps and more.

2. Accessibility of Care

Speaking of mobile health apps, they are one of the key healthcare technologies making care more accessible. Along with other telehealth technologies including connected wearables, mobile health apps make it easier for the elderly or those living in rural areas with a lack of quality care to access the care resources they need to survive and thrive.

Thankfully, making it easier for patients to access the care they need also offers huge financial benefits, as telehealth presents a $247 billion opportunity for the healthcare industry.

Here’s an example of how leveraging custom telehealth technology can improve the accessibility of care.

AI transcription service Target Robot came to us wondering how we could partner with them to come up with a viable, flexible application that can automate the transcription of telehealth appointments, while ensuring documentation and billing needs.

We designed and developed a scalable application to reduce documentation time and compliance risk while increasing both ROI and usage of evidence-based care.

3. Quality of Care

Various technologies, like wearables, directly benefit the quality of care healthcare providers are equipped to offer. AI-powered diagnostic tools help too, improving both diagnostic accuracy and efficiency.

But the benefits of using technology in healthcare aren’t only direct. Think about what not upgrading your healthcare facility’s technologies could lead to.

Imagine the process of improving your healthcare operations with new technologies like a dieter eating to gain weight, maintain weight, or lose weight.

What if your healthcare organization is aiming to create efficiencies and improve patient care (“lose weight”), but you’re already behind the eight-ball and are actually hemorrhaging money or operating inefficiently, maybe without realizing it? This was the case for Communicare before working with us. In this situation, your organization could see immediate benefits of implementing new technologies simply by going from red to black, or going from “gaining” to “maintaining.”

Of course, for organizations who are already operating “in the black,” further improvements are still not only possible, but extremely likely! It’s much easier to focus on enhancing quality of care in a healthy business, after all.

How Can We Help You?

Hiring a healthcare tech consultant is like hiring a personal trainer: doing so can help you understand your organization’s unique strengths, weaknesses, and opportunities to improve your tech stack to deliver more efficient, more accessible, higher-quality care.

We work by asking the right questions to help you continue what you’re doing right and find strategic opportunities to leverage new healthcare technologies and use existing technologies in new ways.

See how we can help you drive revenue, decrease costs, and improve quality of care now: explore our healthcare solutions.

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In 2024, the healthcare industry continues to develop thanks to innovations that promise to redefine patient care and streamline medical operations. From the precision of AI diagnostics to the limitless potential of 3D printing, these advancements are reshaping the industry and setting new standards for what’s possible in healthcare.

Staying informed about these trends is crucial for anyone involved in the field, as they offer opportunities to enhance patient outcomes and improve the overall healthcare experience.

In this blog, we’ll explore five key healthcare technology trends that are driving this transformation.

Healthcare is experiencing a technological renaissance in 2024, with groundbreaking innovations poised to transform how we approach patient care, optimize operations, and elevate overall health outcomes.

The future of medicine is being rewritten by emerging trends, from AI diagnostics to 3D-printed organs, ushering in new paradigms that continually reshape the industry. It’s essential for everyone involved in healthcare—providers, organizations, and patients—to stay abreast of these developments as we embrace a more technologically advanced future to improve operations and provide the best experience possible.

Here are 5 technological advancements in healthcare that you should be aware of.

1. Artificial Intelligence

Various types of AI are transforming healthcare through their diverse, wide-ranging applications, from early disease detection and diagnosis support to personalized treatment plans and assistance in minimally invasive surgeries.

AI technologies like natural language processing and machine learning, for instance, are leading to more precise diagnoses and customized treatments, not to mention improvements in patient monitoring and even predictive maintenance of medical devices.

Learn more about five examples of AI in healthcare here.

The smart and careful use of AI in healthcare promises not only improved patient outcomes but also optimized processes, opening up numerous possibilities to further improve the care model and create efficiencies.

2. Telehealth & Remote Patient Monitoring

At the ATA Nexus event, we learned about the future of telehealth as a key driver of healthcare innovation. Key takeaways from the event include:

• Telehealth’s Critical Role in Improving Care: Telehealth continues to improve the quality of patient care, especially in rural areas where access to healthcare services is challenging.
• Artificial Intelligence + RPM in Lockstep: AI + telehealth technologies are allowing for real-time remote patient monitoring insights and predictive capabilities, helping prevent health complications before they arise and driving more personalized and proactive healthcare.
• Legislative Efforts to Secure Telehealth’s Future: Ongoing legislative efforts aim to extend telehealth services permanently beyond the 2024 election cycle, largely by integrating AI and new technologies into existing healthcare frameworks.
• The Promise of a More Connected Healthcare System: There is hope for the future from most providers and industry insiders who understand that telehealth and AI are central to creating a more connected, efficient, and equitable healthcare system.

3. Precision Medicine

The continued ability to tailor medicines to exact issues due to advancements in targeting specific disease states and biomarkers is likely to attract continued interest from providers, patients, and investors alike.

More investments into genetic editing and precision medicine will be made in the coming year, according to Mark Melton, VP of scientific operations and development at Slope.

And partially because of these inflows, it’s likely that researchers will continue to pursue more personalized forms of treatment.

Here’s an example. Say a group of people has stomach cancer. Precision medicine asks us to think about what differentiates one patient from the next and how to target these differences for the best course of treatment instead of treating everyone the same.

4. 3D Printing & Bioprinting

One of the most promising and exciting advancements in healthcare technology is 3D printing, which offers limitless potential to create physical medical devices as well as:

• Biotissues
• Regenerative heart valves
• Artificial limbs
• Retinal cells
• And more

While we’re a long way away from printing ready-to-use organs, this new technology in healthcare stands to speed up development and decrease costs.

The pharmaceutical industry is also leveraging 3D printing, with FDA-approved 3D-printed drugs available since 2015

5. UI/UX Focus

UX design focuses on creating intuitive, accessible, and efficient user interactions with healthcare products and services, like electronic health records and patient apps.

Compared to UI design, which focuses only on the user interface, UX design encompasses the overall experience, significantly impacting patient satisfaction, trust, and outcomes.

Good UX design in healthcare can streamline workflows for professionals, improve patient engagement, and prevent critical errors, making it an important area of focus.

Achieving effective UX design in healthcare can be challenging, however, so healthcare providers seeking to enhance user experience should consider partnering with specialized UX designers to ensure patient satisfaction and business success.

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The breakneck speed of developments in new technology in healthcare can sometimes seem difficult to keep up with if you are a provider organization — be that a hospital, a managed care facility, or an individually-owned medical practice. However, it’s important to stay on the cutting edge. This is especially true if you aim to provide the best patient experience and highest quality care possible.

That said, here are three of the most impactful technologies influencing healthcare today.

1. Artificial Intelligence & Machine Learning

Artificial intelligence and machine learning (AI/ML) are two of the most transformative technologies shaping all industries and sectors today, including healthcare.

While there are many challenges in implementing AI/ML tech in a healthcare setting to be sure, there are just as many if not more benefits of AI in healthcare.

For instance, generative AI can help health systems manage financial and operational challenges by improving efficiency and patient care.

Revenue-focused healthcare organizations can address their financial hurdles by driving more focused and practical innovations, such as leveraging AI to optimize workflows and reduce costs.

What’s more, AI converges with other healthcare technologies such as remote patient monitoring and robotic process automation to further streamline operational efficiency and increase the quality of care for healthcare organizations that use it wisely.

Here are five more examples of how AI is being used already in healthcare today:

1. Early detection and diagnostics assistance
2. Individualized treatment plans and decision making
3. Assistance with minimally invasive procedures
4. Patient support and patient monitoring
5. Predictive maintenance of medical equipment

2. Telemedicine

The Internet of Things (IoT) makes it easier for healthcare providers to deliver telemedicine solutions to patients.

With that comes a number of benefits, including:

• More Accessible Care: By enabling remote consultations, telemedicine eliminates geographical barriers, enabling care to happen anywhere, anytime. This can be especially beneficial for patients with mobility issues, chronic illnesses, or limited access to transportation.
• Improved Patient Engagement: Telemedicine is associated with more frequent and flexible touchpoints between patients and healthcare providers. This may lead to patients taking a more active role in their health management and, by extension, improved adherence to treatment plans and better health outcomes.
• Potential for Reduced Costs: Providers often benefit from lower overhead and operating expenses. Patients often benefit from reduced travel, childcare, and fewer potential days of missed income.

3. Wearables, Smart Device Monitoring, & Remote Patient Monitoring

Remote patient monitoring is closely associated but not exactly the same as telemedicine. Whereas telemedicine deals with treating conditions and illnesses, up to and including having virtual visits, remote patient monitoring is an ongoing process that extends past appointment times.

The IoT and other healthcare technologies now allow providers to monitor patients from the comfort of their own homes. Not only is this convenient for patients, especially those who are home-bound, but it’s also potentially life-saving.

Remote patient monitoring can be used in the prevention and early detection stages of treatment. Smart device monitoring, which is related, can be especially beneficial for keeping tabs on patients with chronic conditions.

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Whether you’re a clinician or a hospital manager or administrator, see how your healthcare establishment could benefit from our healthcare consulting and solutions, including mobile app development, Software as a Medical Device (SAMD), data engineering, Medical AI, and more.

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Health technologies, as defined by the WHO, refer to “medicines, medical devices, assistive technologies, techniques and procedures developed to solve health problems and improve the quality of life.”

Meanwhile, healthcare technologies include health technologies, but also “any technology, including medical devices, IT systems, algorithms, artificial intelligence (AI), cloud and blockchain, designed to support healthcare organizations.”

As you can imagine, there’s a lot to unpack here. What’s more, as healthcare technology advances with new devices being developed regularly, not to mention the progression of AI/ML solutions, the list only grows bigger.

But the purpose of this blog post is for you to gain a foundational, rather than exhaustive, understanding of what healthcare technology is and how it might be able to help providers like you as well as your patients.

3 Key Subcategories of Healthcare Technology

1. Health Information Systems (HIS) & Electronic Health Records (EHR)

Electronic health records (EHR), sometimes also referred to as personal health records (PHR), are so much more than digital versions of patient charts. They’re an important component of a healthcare organization’s overarching healthcare information system.

One key benefit of EHRs is that they simplify collaboration between providers since access privileges can be adjusted to allow for a variety of doctors or medical professionals to be granted secure access.

Other benefits of EHR include:

• Lowered expenses for transcription
• Decreased costs associated with chart retrieval, storage, and re-filing
• Enhanced documentation and automated coding features
• Minimized medical errors due to improved access to patient data and error prevention alerts
• Elevated patient health and quality of care through superior disease management and patient education

2. Medical Devices & Equipment (Health Technology)

Connected devices and the Internet of Things (IoT) are being used in the medical industry in new ways every day. For some time now, they’ve facilitated the transition from an in-person-only managed care model to hybrid and in some cases fully remote managed-care models.

High-quality personalized care relies on the extraction of meaningful and accurate patient data, and gathering that is made much easier as health technologies for patients advance.

From connected wearables to remote-managed lockboxes that enable seniors aging in place to access medication at their front door, the ways in which medical devices and equipment continue to provide superior patient care abound.

What’s more, continued innovations in health technology make it easier for healthcare providers to operate under a value-based care model.

3. Clinical Decision Support Systems (CDSS)

Clinical decision support systems (CDSS) include a wide range of tools designed to improve decision-making within the clinical workflow such as:

• Computerized alerts and reminders for healthcare providers and patients
• Clinical guidelines
• Condition-specific order sets
• Targeted patient data reports and summaries
• Documentation templates
• Diagnostic support tools
• Contextually relevant reference information

CDS systems represent an often-glazed-over but nevertheless extremely impactful type of healthcare technology that has the power to:

• Increase quality of care and enhance health outcomes
• Reduce the probability of errors and adverse events
• Improve efficiency for providers
• Lead to increased provider and patient satisfaction

How Healthcare Technologies Impact Patients & Providers

Whether you are a healthcare provider or a patient, you stand to benefit from upgrading your healthcare technologies.

Most patients have directly experienced the improved quality of care that often accompanies the integration of healthcare and technology.

Most providers are already utilizing various technologies in their practice or healthcare facility to operate more efficiently.

Still, the rapid pace of technological advancement means that even those familiar with these innovations still have much to learn and many potential benefits to discover.

From extended reality applied to pain management and mental health to D2C genetic testing and 3D bioprinting, there’s so much healthcare technology innovation on the horizon, and each type offers an as-yet-untold number of benefits.

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Below, we’ll uncover the answer to that question before diving into some of the ways it can be applied to enable more efficient and more appropriate decision making which ultimately leads to improved outcomes for both patients and providers.

Big Data in Healthcare: What is It?

Medical professionals have been using data collection and analysis in some form to drive their decisions since before the inception of the Hippocratic oath. After all, diagnosing and treating everything from the common cold to chronic conditions requires understanding what a patient is experiencing and then addressing whatever that may be with evidence-based treatments.

On a basic level, collecting data, both about conditions and treatments, therefore, is in many ways what makes it possible to cure what ails us.

The better the data, the better the decisions medical professionals can make.

Big data analytics in a healthcare context refers to “collecting, analyzing, and leveraging consumer, patient, physical, and clinical data that is too vast or complex to be understood by traditional means of data processing. Instead, big data is often processed by machine learning algorithms and data scientists.”

As the complexity of making healthcare decisions has increased, big data analytics has become more widely used to, among other things, help us develop a more complete view of consumers, patients, and providers from the systemic level down to the individual level.

Armed with this data, providers are better equipped to implement a value-based care model, improving the quality of care for their patients. Another benefit of big data in healthcare is to reduce costs incurred by providers and paid by patients.

Types of Big Data Analytics in Healthcare

Healthcare organizations leverage a wide array of data sources to collect “big data”, including structured information like databases and reports, as well as unstructured sources such as emails, documents, and even sensor data.

Public databases, transaction records, and data from medical devices are frequently utilized also.

To streamline data analysis, many facilities employ integrated hospital systems (HIS) and electronic patient records.

There are four main types of big data analytics used in the healthcare industry:

1. Descriptive Analytics: Answers “What happened?” by providing insights into past events through trends and patterns in data, helping organizations understand their operations and outcomes.
2. Diagnostic Analytics: Explains “Why did it happen?” by identifying causes behind events and uncovering factors that affect key performance indicators, improving decision-making and problem-solving.
3. Predictive Analytics: Forecasts “What is likely to happen?” by using historical data to predict future trends and risks, allowing healthcare systems to prepare for potential scenarios and outcomes.
4. Prescriptive Analytics: Advises “What should be done?” by analyzing data to suggest actions that can optimize outcomes, using advanced tools to provide strategies for improving performance and achieving goals.

5 Big Data Examples in Healthcare

There are many ways providers are applying big data analytics in healthcare to drive innovation and improve the quality of care. Here are five:

1. Patient Outcomes: Big data in healthcare can identify trends at both individual and community levels, aiding in the development of better treatment plans and predicting at-risk patients.
2. Staffing and Operations: Analytics can forecast patient admission trends at specific times, allowing for optimal staff scheduling during peak and slow periods.
3. Product Development: Utilizing big data, healthcare can drive innovation and expedite the process of bringing new products, like prescription medications, to market.
4. Strategic Planning: Analytics can compare chronic disease prevalence and population growth in different neighborhoods to identify problem areas and plan additional services.
5. Fraud Prevention: Big data analytics streamline insurance claims processes, enabling providers to detect fraud more easily and ensuring faster payments to patients.

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• Navigating cloud HIPAA compliance is crucial for healthcare organizations’ protected health information (PHI) and avoid legal repercussions.
• This blog outlines the shared responsibilities between cloud providers and healthcare organizations, emphasizing the need for Business Associate Agreements (BAAs) and robust security measures. It also highlights key requirements for choosing a HIPAA-compliant cloud service, such as encryption and access controls.
• Understanding these elements ensures both efficiency and compliance in a digitized healthcare environment.
• For further expert guidance, consider Digital Scientists’ HIPAA-compliant cloud solutions.

The growing digitization of healthcare solutions offers numerous benefits to both providers and patients. Providers benefit from efficiency, scalability, and cost savings. Patients benefit from increased convenience and flexibility. But all of this comes at a potential cost.

The healthcare industry’s growing reliance on cloud services for storing and processing sensitive patient data also raises critical concerns about protected health information (PHI) under the Health Insurance Portability and Accountability Act (HIPAA).

Don’t be caught off guard or open your organization up to potential legal action. While this blog is not in any way intended to provide legal advice ─ only general information ─ we hope it helps you understand what HIPAA compliant cloud development solutions are on a foundational level and some of what they include.

Understanding HIPAA Compliant Cloud Computing

No cloud environment is inherently HIPAA compliant. That’s because, as Cloud Security Alliance notes, “compliance comes not from having a certain kind of technology or platform, but rather from configuring the platform in the appropriate ways.”

Establishing and maintaining appropriate levels of cloud security is a major component of ensuring a HIPAA-compliant cloud environment. According to the shared responsibility model, which is an AWS paradigm that has been adopted by other cloud providers, both security and compliance are shared responsibilities of both cloud provider and cloud customer.

The cloud provider is responsible for the security of the cloud infrastructure, while the healthcare provider is responsible for securing data within the cloud. This blog focuses mostly on the former, namely, choosing a HIPAA compliant cloud solution. However, as a healthcare provider, you must also understand your own responsibilities when it comes to digital security and protecting patient PHI.

When it comes specifically to choosing a cloud solution provider that is configured in such a way as to be compliant, here’s what to know.

5 Key Requirements for HIPAA Compliant Cloud Services

The U.S. Department of Health and Human Services has released a helpful HIPAA and cloud computing guide with key insights and answers to the most frequently-asked questions about cloud HIPAA compliance.

The entire guide is worth a read, to be sure, but some key takeaways you should be aware of are as follows:

1. HIPAA Applies to the Cloud: HIPAA regulations extend to the cloud environment, and covered entities/business associates must ensure their CSPs are compliant.
2. BAA is Legally Necessary: A Business Associate Agreement is mandatory when a CSP handles ePHI, outlining the responsibilities of both parties for data protection.
3. Security is Paramount: Robust security measures, including encryption, access controls, and incident response plans, are crucial for maintaining HIPAA compliance in the cloud.
4. Shared Responsibility: Both covered entities/business associates and CSPs share the responsibility for protecting ePHI, and their actions (or inactions) can affect each other’s compliance.
5. Due Diligence: Thorough risk assessments and careful selection of reputable CSPs are essential steps in navigating the complexities of HIPAA compliance in the cloud.

Include Service Level Agreements in Your BAAs

Business associate agreements (BAAs) are, as you now know, legally necessary per HIPAA rules when HIPAA covered entities and business associates work together to store patient data in the cloud. While service level agreements (SLA) may not be, they can be extremely beneficial as inclusions in BAAs.

Here’s Why: “SLAs can include provisions that address HIPAA concerns such as system availability and reliability, back-up and data recovery, how data will be returned to the customer after service use termination, security responsibility and use, retention and disclosure limitations,” according to the AMA’s blog post “5 things to know about HIPAA and cloud computing.”

Choose Digital Scientists’ HIPAA Compliant Cloud Solutions

Looking for more information about how to choose a HIPAA compliant cloud provider or a software developer that is well-versed in all of the above and more? You need someone who has experience with custom development, healthcare, HIPAA compliance, and security.

With 15+ years of experience helping healthcare providers remain compliant while operating in a SaaS environment, Digital Scientists and our Digital Health Solutions are here to help.

The post How to Navigate Cloud HIPAA Compliance as a Healthcare Organization appeared first on Digital Scientists.