What Is Digital Transformation in Healthcare? Why Is It Important?

Digital transformation in healthcare refers to the implementation of digital technologies, mostly by care providers but also across the industry. This transformation has accelerated as the various underlying technologies have matured and organizations have overcome their initial cultural resistance to new systems and processes. The goals include improving patient care and health outcomes, lowering costs, simplifying workforce processes (in part to reduce burnout), and adhering to ever-evolving government regulations. Challenges such as system interoperability and security remain top priorities.

The global healthcare IT market will grow from US$94.5 billion in 2021 to US$172.3 billion by 2026, according to estimates from industry IT group HIMSS. Broadly, investments in cybersecurity and AI are driving much of that growth in the form of enhanced capabilities for electronic health records, data analytics, telemedicine, and other systems.

What Is Digital Transformation?

Digital transformation is the strategic integration of digital technologies fueled by cloud computing, embedded AI, and data intelligence to fundamentally change how organizations operate, deliver value to customers, and adapt to evolving market demands. Digital transformation can also involve changing organizational culture to help employees adapt to and embrace new work processes and technology tools.

What Is Digital Transformation in Healthcare?

Digital transformation in healthcare refers to the integration of advanced digital technologies into every aspect of healthcare delivery and operations. Many providers have already adopted electronic health records (EHRs) and are exploring clinical decision support systems, telemedicine, and patient monitoring systems. Digital transformation in healthcare can also involve the automation of manual tasks such as patient scheduling and intake, clinical documentation, revenue cycle management, diagnostic imaging, regulatory compliance, and claims management.

Cloud computing and AI are the next steps for many providers. Although nearly 70% of US-based healthcare businesses have adopted some form of cloud computing, adoption rates remain low in doctors’ offices and dental practices. And even some hospitals, where cloud adoption rates are reaching 90%, aren’t fully realizing its true value, according to research cited by KPMG. AI holds even more potential. For example, only about 30% of UK-based health and social care providers use AI tools, according to research published in Health Tech Digital, but there are enormous opportunities for organizations to adopt them to reduce administrative burdens, assist in patient documentation, and streamline and consolidate patient data. Among the goals? Enhancing clinical decision-making, extending access to care, boosting operational efficiency, and ultimately improving the financial health of providers and health outcomes for patients.

Providers that successfully plan and implement digital transformation programs must focus on creating an environment that fosters personalized, timely, and coordinated care while helping staff adjust to new processes and tools.

Key Takeaways:

• Digital transformation benefits include real-time data accessibility, automation of administrative workflows, and personalized treatment plans, driven by advances such as AI and system interoperability.
• Despite its many advantages, digital transformation faces challenges, including data privacy concerns, high implementation costs, staff resistance, legacy system integration, and regulatory hurdles.
• As healthcare organizations transition from siloed legacy systems to interconnected ones that give clinicians a holistic view of a patient’s health status and history, the industry will likely see costs fall and patient outcomes and experiences improve.

Digital Transformation in Healthcare Explained

As indicated earlier, digital transformation in healthcare is the process of applying digital technologies to fundamentally reshape the way healthcare organizations operate, deliver patient care, and manage data. The aim is to enhance efficiency, reduce costs, and improve patient outcomes by sharing information, automating workflows, and making better, data-informed decisions.

One example is the widespread adoption of telemedicine platforms, which let patients consult with their healthcare providers remotely through secure videoconferencing. Spiking in popularity during the COVID-19 pandemic, telemedicine not only increases access to care, especially for those in remote or underserved areas, but also reduces wait times and eliminates the risk of infections spread at office visits.

At a diagnostic level, AI-powered tools can quickly and accurately analyze medical images, such as X-rays and mammograms, supporting clinicians’ own diagnoses.

Another key aspect of healthcare digital transformation is enhancing patient engagement and experiences. Online patient portals, for example, let individuals view their medical records and securely communicate with their providers, enabling them to become more active participants in managing their health. Meantime, such portals reduce providers’ administrative burden and costs.

Why Is Digital Transformation in Healthcare So Important?

Digital transformation in healthcare is so important that organizations that sit on the sidelines or prioritize the wrong areas are unlikely to remain viable as businesses. Healthcare provider operating margins are razor thin. A PwC analysis puts the 2024 median operating margin of the top 20 US health systems at just 1.5%. In addition to helping improve patient diagnoses and care, digital transformation initiatives can also help elevate providers’ financial viability in many ways.

EHRs embedded with AI, for example, can help improve clinician efficiency. HR solutions can help reduce employee turnover and the associated costs of hiring new staff in a highly competitive market. AI-powered supply chain systems can optimize inventory levels by recommending reorder timing and quantities, allowing providers to avoid holding expensive excess inventory while ensuring critical supplies are always available. Automation of administrative tasks can reduce redundancies and manual errors, saving time and money. Telemedicine and remote monitoring devices can reduce the need for in-person visits. Data analytics software can analyze large healthcare data sets, allowing providers to identify trends, predict disease outbreaks, and pinpoint cost-saving opportunities across every department.

Which Technologies Are Driving Digital Transformation in Healthcare?

Healthcare organizations are applying the following technologies and systems to optimize resources, serve patients, and help deliver better health outcomes.

• Artificial intelligence (AI). Rapid progress in predictive and generative AI is already elevating the way clinicians, researchers, and administrators across the healthcare ecosystem operate, with even greater advances on the horizon. AI is helping them uncover critical insights from vast data sets, enhancing diagnostic accuracy through advanced image analysis, and driving operational efficiencies that can reduce costs. For example, providers are using AI-powered imaging platforms to assist radiologists in detecting early signs of cancer and other diseases. AI analytics tools can forecast patient admissions, flag patients at risk for complications, and identify opportunities for preventive interventions, helping clinicians refine care delivery. Software that leverages AI can also handle routine administrative tasks, such as appointment scheduling, billing, and insurance claims processing, freeing up staff for higher-value work.
• Machine learning (ML). The healthcare sector stands to gain significant value from integrating machine learning (ML) across its operations. Unlike rules-based AI systems, EHRs equipped with ML, a subset of AI that learns and improves as it consumes more data, can help providers uncover patterns and trends that humans (or rules-based AI systems) might miss. This lets hospitals identify hidden inefficiencies without needing to define every possible scenario in advance. Since ML models continuously improve and adapt as new data is collected, data around patient admissions, staffing needs, and ICU transfers become more accurate over time, enabling dynamic resource allocation that minimizes overstaffing, reduces overtime, and improves use of beds and equipment. ML systems can flag abnormal billing patterns, operational exceptions, or infrequent adverse events in massive streams of data. This reduces both costs related to fraud or waste and the need for extensive manual review.
• Machine vision. Machine vision technology enables systems to “see,” process, and understand visual information, much like human vision, but often at greater speed and precision. Healthcare providers are using machine vision to automate analysis of medical images, observe bedridden patients to detect irregular movement or falls, and visually verify that a clinician is delivering the correct medications and dosages. Machine vision devices can also monitor medical supply levels and generate alerts when stocks run low, reducing waste from overstocking and the amount of expired inventory while helping ensure that the care facility has sufficient supplies on hand.
• Natural language processing (NLP). NLP is a branch of AI that enables computers to understand, generate, and shape human language, both spoken and written. Systems with NLP capabilities can extract information, understand sentiment, and identify topics in written documents and convert spoken language into text. NLP tools can also uncover relevant information from large sets of unstructured data, such as document repositories or the internet.
  
  In healthcare, NLP makes it possible to analyze unstructured data in EHRs, such as discharge summaries and patient/provider messages, to identify patient history details that can help improve diagnoses. NLP tools can help providers lower costs in several ways, including by locating relevant data related to billing in order to improve coding accuracy and speed up claims processing. NLP-powered chatbots can answer patients’ routine questions, schedule appointments, and provide automated medication and appointment reminders.
• LLMs. Large language models (LLMs) are AI models trained on vast and diverse sets of data, often pulled from the internet and other repositories, to generate plain language responses to queries or “prompts.” Healthcare providers can use LLMs trained on medical data to help summarize information in medical journals. LLMs can streamline the creation and updating of patient records by scanning physician notes, discharge summaries, and lab reports and converting audio notes into structured data to extract key patient information that can be inserted into EHRs. These capabilities can support clinical decision-making with evidence-based recommendations.
• Internet of Things (IoT). With IoT sensors attached to assets such as wheelchairs and medical devices, hospital staff can quickly locate and deploy resources when needed. For example, sensors attached to a hospital’s wheelchairs can be tracked from an IoT asset-monitoring application so anyone looking for a wheelchair can quickly find the nearest one. Sensors embedded in ventilators and even hospital beds make it possible to monitor and adjust the equipment remotely to enhance patient safety and get early warnings about equipment malfunctions. IoT sensors make it possible to log equipment check-ins, checkouts, and transfers, ensuring that valuable devices are accounted for and the receiving department is charged when items are moved to a new department or location.
• Telemedicine platforms. Telemedicine platforms, whether via Zoom or other secure videoconferencing links, are expanding access to care, letting patients connect with providers regardless of location and reducing the need for in-person visits. This option can be more convenient and even healthier for patients (to the extent that sick people who stay at home don’t spread their germs), as well as more efficient for clinicians. Telemedicine platforms can also enhance care coordination by automatically creating digital records of physician-patient consultations.
• Electronic health records (EHRs). EHRs contain data on individuals’ care histories, including diagnoses, treatment plans, prescriptions, test results, surgery details, and referrals. They can connect to other providers’ EHRs to access data from a patient’s treatments outside that particular hospital system or practice. Such data sharing can improve the accuracy of diagnoses and treatments and avoid duplication of tests. The latest EHRs incorporate data analytics tools to further support clinical decision-making.
• Analytics. Data analytics is being applied to both clinical and operations data in a number of ways, both to lower costs and improve patient care. The sheer volume of medical and operational data generated daily—from patient records, payments, claims, supply chain transactions, and other sources—can be overwhelming. AI data analytics tools can analyze and learn from this data and detect patterns and relationships that may otherwise go unnoticed. For example, analytics tools can help identify patients with complex needs or chronic conditions. Providers can develop targeted care management programs to proactively support these patients, reducing unnecessary hospitalizations and emergency visits. These tools can also help track inventory usage, minimize waste, and optimize purchasing, ensuring that supplies and medications are available when needed. As value-based care (VBC) becomes more prevalent, the ability to use analytics tools to track key performance indicators, patient satisfaction, and quality metrics will become essential, both to establish continuous improvement initiatives and to provide payers with the data they need to measure compliance with VBC contract terms.
• Cloud computing. Cloud computing is the foundation of digital transformation in healthcare, offering a scalable, secure, cost-effective technology platform for all manner of systems and applications. Using cloud-based infrastructure and applications, health organizations can share patient data, access the latest medical research, provide remote care, and deploy new system features (including those enhanced by AI) more easily than with on-premises systems.
• Blockchain. Blockchain—a shared, immutable digital ledger of transactions among multiple parties—can serve as a secure and transparent way for healthcare providers to manage and share sensitive data. Its decentralized and tamper-resistant framework helps ensure data integrity and privacy, building trust among patients, providers, and payers. Blockchain also supports regulatory compliance with its granular access controls and tamper-proof audit trails.
• 5G connectivity. 5G can deliver ultrafast, low-latency mobile communication for the transfer of medical images and other files, remote diagnostics, telemedicine, and even remote surgeries. For example, 5G-connected ambulances let paramedics transmit vital signs and other patient data and video in real time to emergency departments, helping hospitals prepare for incoming cases more effectively. 5G networks can also seamlessly connect IoT devices and mobile health applications.
• Virtual reality (VR) and augmented reality (AR). Healthcare providers are using virtual reality and augmented reality to create highly immersive training environments, as well as for surgical planning and patient education. These simulated, computer-generated 3D environments allow clinicians to rehearse complex procedures, visualize anatomical details, and explain treatment plans to patients with greater clarity, helping improve their skills, precision, and engagement with patients.

11 Benefits of Digital Transformation in Healthcare

The benefits of digital transformation extend across clinical care, operational processes, and patient experiences. Read on for our top 11.

1. Improved patient outcomes. The goal of many healthcare digital transformation efforts is to improve patient outcomes, either directly by supporting more informed clinical decisions and developing patient care plans, or indirectly by, for example, automating mundane processes so providers can devote more resources to patient care. Providers need to measure their digital transformation programs partly on their ability to identify patient health risks and improve coordination among all members of a patient’s care team.
2. Enhanced data accessibility and sharing. The ability to integrate disparate healthcare systems is allowing clinicians and staff to access up-to-date patient data from their EHR system. This improved data accessibility and sharing enhances collaboration, simplifies clinical workflows, and supports more informed decision-making. And it’s not just patient data that’s shared. EHRs are also connecting to clinical trial opportunities, medical research results, and population health data.
3. Increased operational efficiency. Automating routine processes, such as patient scheduling and claims management, can reduce administrative bottlenecks and alleviate manual workloads. With integrated workflows and advanced analytics, healthcare providers can more effectively allocate material resources, optimize staffing, and deliver timely patient care.
4. Reduced medical errors. Medical errors are a serious and growing public health problem and the third leading cause of death in the US in 2024, according to research published in the National Library of Medicine. Healthcare providers are gaining new digital tools that can help reduce or eliminate medical errors. For example, new, interoperable EHRs can centralize patient data from multiple sources, including from outside providers or specialists, helping reduce errors caused by incomplete records. These EHRs give clinicians quick access to updated information, improving the accuracy of diagnoses and treatments. Embedded intelligence can flag potentially dangerous drug interactions, abnormal test results, and missed follow-up visits or vaccinations. Remote monitoring tools allow for continuous patient observation and follow-up, helping care teams address deteriorating conditions or abnormal readings early and reducing errors caused by delayed interventions.
5. Enhanced care plans. Healthcare providers can now aggregate and analyze vast amounts of data on individual patients, regardless of where they’ve received care. That data includes their medical histories, biometrics, and physical traits such as fingerprints and iris scans used for identification. It also includes health indicators such as patients’ diets, substance use, physical activity, and stress levels. This comprehensive data on each patient helps clinicians design personalized care plans.
6. Streamlining clinical decision-making. Clinicians are enhancing their clinical decision-making by taking advantage of advanced imaging technologies, data analytics, and AI-powered tools integrated into their workflows.
7. Better patient engagement and experiences. User-friendly patient portals, mobile apps, and virtual care options make it easy for patients to communicate with clinicians, schedule appointments, and help manage their own care.
8. Cost reduction. Digital investments can help healthcare organizations reduce costs in many ways, including automating routine administrative tasks, supporting telemedicine programs, managing inventories, scheduling staff, and supporting preventive care measures. Most comprehensive digital transformation programs involve the implementation of predictive analytics tools, which can help identify at-risk patients, analyze data from EHRs to recommend patient care plans and preventive measures, and forecast patient volume and staffing needs, all of which support more efficient care delivery.
9. Enhanced community health outcomes. Community healthcare managers need access to longitudinal and community health records as well as population-level reports to determine the best timing and location for the programs they initiate, such as mobile health clinics and vaccination campaigns. Effective population health tools can help improve health outcomes, elevate patient experiences, identify inefficiencies and care gaps, and control care costs. But to be effective, population health tools need secure access to vast amounts of accurate, near real-time data from multiple sources.
10. Expanded access to care. Healthcare providers can use secure telemedicine platforms and remote patient monitoring technologies to deliver care outside conventional hospital and office settings. These capabilities can expand access to medical services and support care continuity regardless of the patient’s location.
11. Simplified administrative processes. Automating processes such as appointment and staff scheduling, billing, and claims management reduces manual effort and the potential for errors. The increased efficiency can lower costs, improve productivity and staff morale, and allow providers to allocate more resources to patient care.

Challenges to Digital Transformation in Healthcare

As healthcare providers pursue digital transformation, they may encounter a number of challenges. Here are some of the most common ones.

• Data privacy and security. To safeguard patient privacy and maintain compliance with regulatory standards such as HIPAA, healthcare providers must protect patient data from security breaches and unauthorized access. These risks can slow the adoption of new digital technologies.
• High implementation costs. Already financially strapped healthcare organizations may struggle to find the money to invest in new technologies, training, and ongoing maintenance. These financial constraints can delay project timelines, limit the scope of innovation, and impact the long-term success and sustainability of digital initiatives.
• Resistance to change from staff. Employees are typically hesitant to adopt unfamiliar technologies and workflows, especially in healthcare, where they may be concerned about replacing or disrupting workflows and routines that are deeply ingrained in clinical practice. Employees also worry about increased workloads during the learning stage. This resistance can slow down technology implementation timelines, reduce productivity, and undermine the overall success of digital modernization initiatives.
• Interoperability issues. Providers, payers, and government regulators all face the challenge of connecting their fragmented systems, dismantling data silos, and ensuring their data is complete, accurate, and trustworthy. Connecting disparate systems that contain unprecedented amounts of data is a foundation of digital transformation in any industry, but especially in healthcare.
• Legacy system integration. Healthcare providers saddled with decades-old on-premises systems that are often unable to connect and share data face significant hurdles when integrating new technologies such as AI monitoring tools, biometric devices, and telehealth platforms with those systems. Outdated systems can impede interoperability and data consolidation, increase costs, and slow the uptake of innovative digital health solutions.
• Regulatory and compliance barriers. Healthcare organizations must navigate complex regulations, such as HIPAA, GDPR, and regional frameworks, that govern data security and privacy, telemedicine reimbursement, use of AI clinical tools, and data breach notifications. These regulations can prolong approval processes and increase administrative burdens.
• Insufficient digital literacy. Employees, especially those who’ve used the same systems and followed the same processes for years, may lack the skills required to effectively use new digital technologies. This skills gap can lead to slower adoption rates, increased training needs, and errors.
• Inconsistent data quality. Inconsistent data quality can undermine digital transformation efforts in healthcare by introducing errors and inefficiencies into critical workflows. No physician wants to make clinical decisions based on bad data.
• Infrastructure limitations. Outdated computer hardware, insufficient network capacity, and lack of system interoperability can limit the impact of digital transformation initiatives when they lead to system downtime, data silos, and slow system performance.

Examples of Digital Transformation in Healthcare

To understand the potential of digital innovation in healthcare, it’s helpful to explore examples of where it’s making a significant impact.

• Electronic health records: centralized patient data access. EHRs incorporating generative AI give doctors summaries of patients’ charts and lab results, filtering information pertinent to a patient’s current medical issue. They’ll also support the shift to value-based care plans that reward physicians for completing courses of treatment under budget and meeting specific quality metrics showing how patients fare over time.
• Telemedicine: remote consultations and care. Telemedicine has allowed patients in remote areas or those unable to travel to an office to connect with physicians and other caregivers via secure videoconferencing links. Even patients who live close to their care provider are starting to embrace telemedicine, especially to consult with their clinicians about minor conditions and for chronic disease management. Telemedicine conferencing also lets hospital clinicians triage nonemergency cases so onsite staff can focus on patients who need in-person care.
• AI-enabled image review. AI agents can help clinicians review anomalies in X-rays, MRIs, and CT scans and streamline the sending of images to specialists for review.
• Wearables and IoT devices: real-time patient monitoring technologies. AI agents can track health data from wearable devices and other at-home medical equipment to produce notifications when blood pressure, glucose, and other variables reach certain levels. Even more important, they can sift through the huge volumes of data that many medical devices generate to give healthcare providers only the information they need to improve short- and long-term patient care.
• Robotic surgery: precision and minimally invasive procedures. AI-powered robotic surgical systems that use cameras, mechanical hands, and instruments are considered minimally invasive because the instruments and camera are inserted through tiny cuts. In many cases, a surgeon controlling mechanical hands can operate with greater precision than a doctor using hand-held instruments, potentially leading to fewer complications, less bleeding, and faster recovery times. AI algorithms can also help plan robotic surgical steps, position instruments, and classify medical images.
• Mobile health apps: patient engagement and self-care. Mobile health applications let patients with chronic conditions track their vital signs and medication adherence and share data with their care teams. For example, a healthcare system can monitor released patients while they’re recovering from surgery via a wearable device that connects to a smart phone app, enabling clinicians to intervene early when there are issues and thus helping avoid hospital readmissions. These apps also help patients actively participate in their healthcare by tracking symptoms, medications, vital signs, and disease progression.
• Virtual reality: Pain management and medical training. Virtual reality (VR) provides medical professionals with 3D simulations of complex procedures so they can train for them in a safe, controlled environment. VR can also support more effective pain management by immersing patients in a calming, 3D environment that distracts from pain and reduces anxiety. For example, the US Veterans Health Administration is offering patients an in-home VR platform to help alleviate chronic pain.
• Chatbots: 24/7 patient support and triage. AI-powered virtual health assistants can help answer patients’ queries, provide them with health guidance and reminders, and track their health data. Generally available on a mobile app or website, the chatbots communicate with patients through natural language interfaces and access large health data sets to provide patients with answers that are accurate and up to date. These health assistants can also recommend lifestyle or dietary changes and prompt patients to schedule and prepare for appointments. Additionally, they can triage patients by asking for symptoms and providing either self-care recommendations, scheduling a telemedicine appointment, or directing the patient to urgent care for non-life-threatening conditions or the ER for critical care.
• Predictive analytics: identifying at-risk patients, allocating resources. Predictive analytics tools review data on patient health, gender, lifestyle, and medical history, and even genomic data, to help streamline clinical workflows to help flag patients at risk for certain diseases, complications, or hospital readmission. Providers can use these same tools to analyze data on, for example, community prevalence of illnesses such as influenza or COVID-19 and immunization gaps to forecast patient volumes and bed occupancy rates so they can optimize staff levels and inventories of medicines and supplies.

The Future of Healthcare

The biggest challenge facing the healthcare industry is managing soaring costs while improving care quality. Healthcare providers are exploring innovative new technologies, including AI-powered imaging, care coordination that spans multiple departments and providers, and prior authorization systems that allow physicians to prescribe drugs and recommend procedures that work under a payer’s coverage rules. Healthcare organizations will move from legacy systems, where data that can help clinicians treat a patient is locked in the databases of multiple providers and other parties, to interconnected systems that give clinicians a holistic view of a patient’s health status, treatments, prescriptions, and other relevant factors.

Transform the Healthcare Experience with Oracle Health

Oracle Health provides a comprehensive set of systems and applications designed to support every step of the clinical journey, from patient referrals through care and follow-ups. At the core is Oracle Health EHR,* which makes it possible for clinicians to receive contextually relevant information about a patient before and during an appointment, helping them make more efficient and informed clinical decisions.

Digital Transformation in Healthcare FAQs

What is an example of digital transformation?
One example of digital transformation in healthcare is the use of EHR platforms, which allow providers to securely access and share patient information.

How has digital technology changed healthcare?
Digital technology has changed healthcare by enabling providers to gather and analyze far more data than they ever could before on patients’ medical histories, the latest treatments and procedures, population health trends, and other factors to enhance patient care.

What is a digital-first strategy?
A digital-first strategy is an organizational approach that prioritizes the use of digital technologies to improve efficiency and enhance customer experiences.