Digital Healthcare
Article | November 29, 2023
Healthcare marketing, for a healthcare provider, is challenging as a lot of technologies are emerging in the market. What matters is choosing the right healthcare marketing techniques and technology to market your products and services. The global digital health market size was USD 51.3 billion in 2015. According to Global Market Insights, this is expected to have a compound annual growth rate (CAGR) of 25.9% from 2016 to 2025. However, to compete with your opponents and to face the challenges of increasing patients buying your products and services, you need an excellent and well-designed marketing strategy with the latest healthcare marketing trends.
As we have entered a new decade, healthcare providers should look into developments in the healthcare marketing brought out by the year 2020. The global pandemic has changed all the practices in the industry, including the style of healthcare marketing and technology. Since the turn of the century, online marketing has been a part and parcel of healthcare marketing. However, healthcare marketing is witnessing a new era. This can be attributed to the increasing integration of various smart devices in the everyday lives of people and the introduction of artificial intelligence algorithms. Are you ready to leverage these technological transformations and changes?
This article discusses some of the major healthcare marketing trends to be integrated into your healthcare marketing strategies.
Reviews Matter
One of the important healthcare marketing trends that you can use is online reviews from happy patients. Healthcare providers have largely relied upon these online reviews— the patient sentiment—to establish a reputation and acquire new patients. These reviews are widespread across multiple online platforms and anyone can easily access them.
A study conducted by Binary Fountain in 2019 claimed that 60% of people use online reviews to choose a healthcare provider. It also claimed that 75% are influenced by online feedback when they go for a healthcare provider. This shows how influential this healthcare marketing trend is. Thus, in 2021, healthcare providers should concentrate on acquiring positive reviews and replying to both good and bad reviews and feedback. It is crucial to respond to negative reviews for your online reputation management, as 70% of patients consider it important to address patient concerns publicly.
Content is King
Content marketing is yet another healthcare marketing trend that healthcare providers should focus on. Producing educational, entertaining, engaging, and high-quality content is crucial in increasing your online brand visibility and patient engagement. This aspect of online marketing came into existence ever since Google became the king in the search engine market and established their ever-evolving algorithms.
To leverage this healthcare marketing trend, healthcare providers should have a plan for creating content holistically and publishing it on multiple platforms in different forms. All content that goes online should be well-produced and authoritative. All forms of text-based content, such as articles, blogs, press releases, white papers, and case studies, should be well-written and have high-quality links. It is also good to add images to your content to increase engagement.
Within this healthcare marketing trend, video marketing is considered to be the most effective one because online visual content appeals to users more than any other form of content. To make the most out of your videos, you can run video ads on YouTube, share them on your social media pages, and post them on websites and landing pages.
Responsive, Fast Loading Websites
Among the online healthcare marketing techniques, it is very important to have a very responsive and fast loading website. Also, the navigation on the site should be smooth and easy. This is because the websites with these features win more patients.
Websites of healthcare providers with ads and pop-ups, navigation issues, and slow loading will make users leave the site in no time. This will be much realized in 2021 as patients expect websites to load instantly on all their devices, including their smartphones.
To increase patient acquisition, you may have to streamline and optimize your website for both mobile and desktop viewing. Here are some quick tips to make your website loading fast and navigation easy:
• Decrease image size on your website
• Switch to a faster web host
• Clean up unnecessary code.
Growing Influence of Social Media
Having a strong presence on all social media platforms is an effective digital healthcare marketing tactic. The online presence of your healthcare organization should not be limited to your website. To maximize your brand’s reach and to have an impact in 2021, you may have to make full use of all social media platforms. In terms of lead generation, engagement, marketing, and reputation management, Twitter, Facebook, and Instagram, among others, are turning more influential nowadays. According to Statista, social media has 2.82 billion active users. More specifically, according to Hootsuite, as of 2020, 90% of older adults use social media to seek or share healthcare information.
This most influential healthcare digital marketing trend can be effectively used by creating and promoting targeted ads on all these platforms. Also, by interacting with users through likes, comments, and shares and publishing content regularly, you can increase your organic reach. For any healthcare provider and marketer of 2021 and beyond, it is a massive mistake to neglect the power of social media.
Data-Driven Healthcare Marketing
In 2021, to personalize outreach campaigns, healthcare providers and marketers will have data and tools. Adhering to HIPAA regulations, healthcare providers can design various marketing materials according to key demographics, such as key health concerns, income levels, age range, etc. This is the more granular approach to reach new patients and to keep your regular and current patients loyal to your brand. This personalized healthcare marketing technique will make patients feel that they are treated well and slowly build up trust in your brand.
A customer relationship management (CRM) tool, which is reliable and healthcare-specific, can store relevant patient data. To optimize your marketing strategy, insights from the stored data can be considered. Thus, this important healthcare marketing technique—data-driven healthcare marketing—helps you personalize your healthcare marketing campaigns.
Turning to Telemedicine Technology
Demanding physical processes and spatial barriers are not yet a big restriction for healthcare providers. Artificial intelligence, telemedicine, automated systems, and IOT contribute a lot to make healthcare more efficient and accessible. Highlighting these features in healthcare also becomes an effective healthcare marketing technique.
Using telemedicine software, healthcare can be provided remotely, which eliminates the need for an in-house visit. Although this breakthrough happened at the start of the century, it will become more accessible, viable, reliable, and will be used widely than ever before in 2021. Patients with mobility and transportation issues prefer using remote healthcare services and adding these facilities to your services can be considered a part of healthcare marketing tactics. So start offering remote healthcare services, if you have not started yet. This will eventually increase your brand reputation and build up trust.
Self-Serving Technologies- Patient Profiles, Chatbots, and Appointment-Scheduling Modules
As part of healthcare marketing plan and strategy, patient profiles, chatbots, and appointment-scheduling modules are incorporated by providers in their websites. These additions provide more awareness and control of their health to the patients. Updating your website to include these self-serving technology will help you improve the patient experience online.
Look forward to the new developments in healthcare marketing technology to improve your healthcare marketing, which is suitable for you. Embracing all of these changes and transformation in healthcare marketing strategy will help you stay ahead of your competitors with effective healthcare marketing campaigns strategies.
Frequently Asked Questions
What are technological advances in healthcare?
The year 2020 witnessed a lot of technological advancements in the healthcare industry due to the pandemic. Some of the major ones among them are personalized medicine, telemedicine, blockchain, artificial intelligence, and machine learning.
What technology is used in healthcare marketing?
Blockchain, artificial intelligence (AI), chatbots, voice search, and augmented reality are some of the major technologies used in treatment and marketing in healthcare in 2021. However, the technology in healthcare marketing is ever-evolving as new trends are set every moment.
Why is technology important in marketing?
Technology is very important in businesses and marketing as technology helps businesses grow. It also creates relationships and it is necessary for communication between the customer and the organizations. Technology is an essential part of any business for development and growth.
What is the most effective healthcare marketing technology?
There are many existing and emerging healthcare marketing technologies in the global market. However, the most effective marketing technique is social media; generating leads through social media and websites.
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Health Technology, Digital Healthcare
Article | August 21, 2023
“Health care is different, the data here is emotional! If you tell me you were buying a fishing rod online and were emotional about it, I’d say you are lying. But I do frequently see people helpless and confused when it comes to receiving health care, managing its costs, making sense of its data.”
- Senior Product Leader inOptum Global Solutions Pvt. Ltd.
Yes, health care is different, and so is product management in it. This piece highlights the top 4 product management trends that are specific to health care and serve beyond being just a list of technologies making their way into health care.
Health care consumerism
Lance broke his ankle in a bicycle accident and is now in hospital waiting for surgery. Which of these words would describe him more aptly— a ‘patient’ or a ‘health care consumer’? The fact that Lance holds a high-deductible health plan, manages an interactive relationship with his primary doctor, keenly monitors his fitness through his smartwatch, and learns about healthier diet plans and recipes online — I can say he isn’t just receiving health care, but making active choices on how to pay for and manage his health. This choice and responsibility that people demand, is ‘health care consumerism’. This trend has been growing since 2015 when value-based care started picking up in the US.
What does this imply for products/PMs?
These are challenging and exciting times to be a product manager (PM) in health tech. This is because people are now demanding an experience equivalent to what they’re used to from other products in their lives, such as e-commerce, streaming platforms, and digital payments, to name a few. Any consumer-facing product (a mobile app, a web-based patient portal, a tech-enabled service) needs to meet high expectations. Flexible employer-sponsored health plans options, health reimbursement arrangements, price transparency products for drugs and medical expenses, remote health care services, and government's push to strengthen data and privacy rights — all point to opportunities for building innovative products with ‘health care consumerism’ as a key product philosophy.
Wellness
COVID-19 has tested health care systems to their limits. In most countries, these systems failed disastrously in providing adequate, timely medical assistance to many infected people. Prevention is of course better than cure, but people were now forced to learn it the hard way when cure became both inaccessible and uncertain. With lockdowns and social isolation, prevention, fitness, diet, and mental wellbeing all took center stage.
Wellness means taking a ‘whole-person approach’ to health care — one where people recognize the need to improve and sustain health, not only when they are unwell, but also when they’re making health care decisions that concern their long-term physical and mental health. A McKinsey study notes that consumers look at wellness from 6 dimensions beyond sick-care— health, fitness, nutrition, appearance, sleep, and mindfulness. Most countries in the study show that wellness has gained priority by at least 35% in the last 2–3 years. And wellness services like nutritionists, care managers, fitness training, psychotherapy consultants contribute 30% of the overall wellness spend.
So, what do health-tech PMs need to remember about wellness?
The first principle is, “Move to care out of the hospital, and into people’s homes”. A patient discharged after knee surgery has high chance of getting readmitted if he/she has high risk of falling in his/her house, or is unable to afford post-discharge at-home care with a physiotherapist. This leads us PMs to build products that recognize every person’s social determinants of health and create support systems that consider care at the hospital and care at home as a continuum.
The second principle is, “Don’t be limited by a narrow view of ‘what business we are in’, as wellness is broad, and as a health tech company, we are in health-care, not sick-care”. Wellness products and services include — fitness and nutrition apps, medical devices, telemedicine, sleep trackers, wellness-oriented apparel, beauty products, and meditation-oriented offerings, to name just a few. Recent regulations in many countries require health care providers to treat behavioural health services at par with treating for physical conditions, and this is just a start.
Equitable AI
Last month, WHO released a report titled “Ethics and Governance of Artificial Intelligence for Health”. The report cautions researchers and health tech companies to never design AI algorithms with a single population in mind. One example I read was, “AI systems that are primarily trained on data collected from patients in high-income settings will not perform as effectively for individuals in low or middle-income communities.” During COVID-19, we came across countless studies that talked about the disproportionate impact on minorities in terms of infections, hospitalizations, and mortality. A student at MIT discovered that a popular out-of-the-box AI algorithm that projects patient mortality for those admitted in hospitals, makes significantly different predictions based on race — and this may have adversely moved hospital resources away from some patients who had higher risks of mortality.
How should I think about health equity as an AI health-tech PM?
Health equity means that everyone should have a fair chance at being healthy. As a PM, it’s my job to make sure that every AI-assisted feature in my product is crafted to be re-iterative and inclusive, to serve any community or subpopulation, and is validated across many geographies. To prevent any inequitable AI from getting shipped, it is important to ensure that the underlying AI model is transparent and intelligible. This means knowing what data goes into it, how it learns, which features does it weigh over others, and how does the model handles unique features that characterize minorities.
Integrated and interoperable
In every article that I read on topics such as digital platforms, SaaS, or connectivity with EMRs, I always find the words: ‘integrated’ and ‘interoperable’ therein. Most large and conventional health tech companies started by offering point-solutions that were often inextensible, monolithic, and worked with isolated on-prem servers and databases. To give a consistent user experience, leverage economies of scope, and scale products to meet other needs of their customers, started an exodus from fragmented point-solutions to interoperable, integrated solutions. The popularization of service-oriented architectures (SOAs) and cloud vendors like AWS, Azure, and GCP has also helped.
The what and how of integrated-interoperable solutions for PMs:
Integrated solutions (IS), as I see them, are of two kinds — one, in which as a health tech company, we help our customers (health systems, insurance companies, direct to consumers) accomplish not just one, but most/all tasks in a business process. For example, a B2B IS in value-based care contract management would mean that we help our customers and health systems by giving an end-to-end solution that helps them enter into, negotiate, plan for, manage, get payments for their value-based contracts with health plans.
In the second type of IS, we offer products that can be easily customized to different types of customers. For example, a health management app that people can subscribe to for different programs such as obesity, diabetes, hypertension, cholesterol management, as needed. The app works with different datasets for these programs and uses different analyses and clinical repositories in its backend, but still delivers a consistent user experience across programs to a user who enrolled in multiple programs, say diabetes and weight management.
‘Interoperable’ simply means that one product should be able to talk to other products both in and out of the company. For example, if product-A can alert a doctor about any drug-drug interactions or allergies a patient might have, while she is writing prescriptions for the patient in product-B (an EMR), then product-A does talk to product-B, and hence, is interoperable. This trend is picking up further with the growth of IoT devices, and industry-wide participation in adopting common standards for data exchange.
Conclusion
Though the article derives much of its context from US health care, I have tried to keep a global lens while choosing these topics. For developing economies like India, digitization is the number one trend as much of the health system is still moving from manual records to digitally store patient and medical data in EMRs. The good news is that India is booming with health-tech innovation and that is where consumerism, wellness, and equitable AI make sense. Once companies develop enough point-solutions for different health system needs and use-cases, Indian health tech will see a move towards creating integrated, interoperable (IGIO) systems as well.
There are some other trends such as — use of non-AI emerging tech such as Blockchain in health information management, cloud infrastructure for health tech innovation, big data and analytics to improve operational efficiency in areas such as claims management and compliance reporting, Agile product management for co-developing with and continuously delivering to clients etc. — but I see them either as too nascent, or too old to feature in this list.
Finally, as a health tech product manager, you can use the following questions to assess your products against the above trends — (Consumerism) do the products that I manage, empower consumers with choice, information, and actionability? (Wellness) Does my product emphasize keeping them out-of-hospitals and healthy in the first place? (Equitable AI) Am I sure that my product doesn’t discriminate against individuals belonging to underserved populations? (IGIO) And finally, is my product scalable, integrated and interoperable to expand to a platform, in the true sense?
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Health Technology, Digital Healthcare
Article | September 8, 2023
A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is a model that mirrors a unique physical object, process, organization, person or other abstraction. For healthcare providers, digital twins provide an abstraction of the healthcare ecosystem’s component characteristics and behaviors. These are used in combination with other real-time health system (RTHS) capabilities to provide real-time monitoring, process simulation for efficiency improvements, population health and long-term, cross-functional statistical analyses.
Digital twins have the potential to transform and accelerate decision making, reduce clinical risk, improve operational efficiencies and lower cost of care, resulting in better competitive advantage for HDOs. However, digital twins will only be as valuable as the quality of the data utilized to create them. The digital twin of a real-world entity is a method to create relevance for descriptive data about its modeled entity. How that digital twin is built and used can lead to better-informed care pathways and organizational decisions, but it can also lead clinicians and executives down a path of frustration if they get the source data wrong. The underlying systems that gather and process data are key to the success for digital twin creation. Get those systems right and digital twins can accelerate care delivery and operational efficiencies.
Twins in Healthcare Delivery
The fact is that HDOs have been using digital twins for years. Although rudimentary in function, digital representations of patients, workflow processes and hospital operations have already been applied by caregivers and administrators across the HDO. For example, a physician uses a digital medical record to develop a treatment plan for a patient. The information in the medical record (a rudimentary digital twin) along with the physician’s experience, training and education combine to provide a diagnostic or treatment plan. Any gaps in information must be compensated through additional data gathering, trial-and-error treatments, intuitive leaps informed through experience or simply guessing. The CIO’s task now is to remove as many of those gaps as possible using available technology to give the physician the greatest opportunity to return their patients to wellness in the most efficient possible manner.
Today, one way to close those gaps is to create the technology-based mechanisms to collect accurate data for the various decision contexts within the HDO. These contexts are numerous and include decisioning perspectives for every functional unit within the enterprise. The more accurate the data collected on a specific topic, the higher the value of the downstream digital twin to each decision maker (see Figure 1).
Figure 1: Digital Twins Are Only as Good as Their Data Source
HDO CIOs and other leaders that base decisions on poor-quality digital twins increase organizational risk and potential patient care risk. Alternatively, high-quality digital twins will accelerate digital business and patient care effectiveness by providing decision makers the best information in the correct context, in the right moment and at the right place — hallmarks of the RTHS.
Benefits and Uses
Digital Twin Types in Healthcare Delivery
Current practices for digital twins take two basic forms: discrete digital twins and composite digital twins. Discrete digital twins are the type that most people think about when approaching the topic. These digital twins are one-dimensional, created from a single set or source of data. An MRI study of a lung, for example, is used to create a digital representation of a patient that can be used by trained analytics processes to detect the subtle image variations that indicate a cancerous tumor. The model of the patient’s lung is a discrete digital twin. There are numerous other examples of discrete digital twins across healthcare delivery, each example tied to data collection technologies for specific clinical diagnostic purposes. Some of these data sources include vitals monitors, imaging technologies for specific conditions, sensors for electroencephalography (EEG) and electrocardiogram (ECG). All these technologies deliver discrete data describing one (or very few) aspects of a patient’s condition.
Situational awareness is at the heart of HDO digital twins. They are the culmination of information gathered from IoT and other sources to create an informed, accurate digital model of the real-world healthcare organization. Situational awareness is the engine behind various “hospital of the future,” “digital hospital” and “smart patient room” initiatives. It is at the core of the RTHS.
Digital twins, when applied through the RTHS, positively impact these organizational areas (with associated technology examples — the technologies all use one or more types of digital twins to fulfill their capability):
Care delivery:
Clinical communication and collaboration
Next-generation nurse call
Alarms and notifications
Crisis/emergency management
Patient engagement:
Experiential wayfinding
Integrated patient room
Risks
Digital Twin Usability
Digital twin risk is tied directly to usability. Digital twin usability is another way of looking at the issue created by poor data quality or low data point counts used to create the twins. Decision making is a process that is reliant on inputs from relevant information sources combined with education, experience, risk assessment, defined requirements, criteria and opportunities to reach a plausible conclusion. There is a boundary or threshold that must be reached for each of these inputs before a person or system can derive a decision. When digital twins are used for one or many of these sources, the ability to cross these decision thresholds to create reasonable and actionable conclusions is tied to the accuracy of the twins (see Figure 2).
Figure 2: Digital Twin Usability Thresholds
For example, the amount of information about a patient room required to decide if the space is too hot or cold is low (due to a single temperature reading from a wall-mounted thermostat). In addition, the accuracy or quality of that data can be low (that is, a few degrees off) and still be effective for deciding to raise or lower the room temperature. To decide if the chiller on the roof of that patient wing needs to be replaced, the decision maker needs much more information. That data may represent all thermostat readings in the wing over a long period of time with some level of verification on temperature accuracy. The data may also include energy load information over the same period consumed by the associated chiller.
If viewed in terms of a digital twin, the complexity level and accuracy level of the source data must pass an accuracy threshold that allows users to form accurate decisions. There are multiple thresholds for each digital twin — based on twin quality — whether that twin is a patient, a revenue cycle workflow or hospital wing. These thresholds create a limit of decision impact; the lower the twin quality the less important the available decision for the real-world entity the twin represents.
Trusting Digital Twins for HDOs
The concept of a limit of detail required to make certain decisions raises certain questions. First, “how does a decision maker know they have enough detail in their digital twin to take action based on what the model is describing about its real-world counterpart?” The answer lies in measurement and monitoring of specific aspects of a digital twin, whether it be a discrete twin, composite twin or organization twin.
Users must understand the inputs required for decisions and where twins will provide one or more of the components of that input. They need to examine the required decision criteria in order to reach the appropriate level of expected outcome from the decision itself. These feed into the measurements that users will have to monitor for each twin. These criteria will be unique to each twin. Composite twins will have unique measurements that may be independent from the underlying discrete twin measurement.
The monitoring of these key twin characteristics must be as current as the target twin’s data flow or update process. Digital twins that are updated once can have a single measurement to gauge its appropriateness for decisioning. A twin that is updated every second based on event stream data must be measured continuously.
This trap is the same for all digital twins regardless of context. The difference is in the potential impact. A facilities decision that leads to cooler-than-desired temperatures in the hallways pales in comparison to a faulty clinical diagnosis that leads to unnecessary testing or negative patient outcomes.
All it takes is a single instance of a digital twin used beyond its means with negative results for trust to disappear — erasing the significant investments in time and effort it took to create the twin. That is why it is imperative that twins be considered a technology product that requires constant process improvement. From the IoT edge where data is collected to the data ingestion and analytics processes that consume and mold the data to the digital twin creation routines, all must be under continuous pressure for improvement.
Recommendations
Include a Concise Digital Twin Vision Within the HDO Digital Transformation Strategy
Digital twins are one of the foundational constructs supporting digital transformation efforts by HDO CIOs. They are digital representations of the real-world entities targeted by organizations that benefit from the advances and efficiencies technologies bring to healthcare delivery. Those technology advances and efficiencies will only be delivered successfully if the underlying data and associated digital twins have the appropriate level of precision to sustain the transformation initiatives.
To ensure this attention to digital twin worthiness, it is imperative that HDO CIOs include a digital twin vision as part of their organization’s digital transformation strategy. Binding the two within the strategy will reinforce the important role digital twins play in achieving the desired outcomes with all participating stakeholders.
Building new capabilities — APIs, artificial intelligence (AI) and other new technologies enable the connections and automation that the platform provides.
Leveraging existing systems — Legacy systems that an HDO already owns can be adapted and connected to form part of its digital platform.
Applying the platform to the industry — Digital platforms must support specific use cases, and those use cases will reflect the needs of patients, employees and other consumers.
Create a Digital Twin Pilot Program
Like other advanced technology ideas, a digital twin program is best started as a simple project that can act as a starting point for maturity over time. Begin this by selecting a simple model of a patient, a department or other entity tied to a specific desired business or clinical outcome. The goal is to understand the challenges your organization will face when implementing digital twins.
The target for the digital twin should be discrete and easily managed. For example, a digital twin of a blood bank storage facility is a contained entity with a limited number of measurement points, such as temperature, humidity and door activity. The digital twin could be used to simulate the impact of door open time on temperature and humidity within the storage facility. The idea is to pick a project that allows your team to concentrate on data collection and twin creation processes rather than get tied up in specific details of the modeled object.
Begin by analyzing the underlying source data required to compose the digital twin, with the understanding that the usability of the twins is directly correlated to its data’s quality. Understand the full data pathway from the IoT devices through to where that data is stored. Think through the data collection type needed for the twin, is discrete data or real-time data required? How much data is needed to form the twin accurately? How accurate is the data generated by the IoT devices?
Create a simulation environment to exercise the digital twin through its paces against known operational variables. The twin’s value is tied to how the underlying data represents the response of the modeled entity against external input. Keep this simple to start with — concentrate on the IT mechanisms that create and execute the twin and the simulation environment.
Monitor and measure the performance of the digital twin. Use the virtuous cycle to create a constant improvement process for the sample twin. Experience gained through this simple project will create many lessons learned and best practices to follow for complex digital twins that will follow.
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Digital Healthcare
Article | June 4, 2022
As the cost of care continues to rise, many hospitals are looking for long-term solutions to minimize inpatient services. Learn how technology and health care delivery will merge to influence the future of hospital design and the patient experience across the globe in this report developed by Deloitte US.
Five use cases for the digital hospital of the future
The future of health care delivery may look quite different than the hospital of today. Rapidly evolving technologies, along with demographic and economic changes, are expected to alter hospitals worldwide. A growing number of inpatient health care services are already being pushed to home and outpatient ambulatory facilities. However, many complex andv very ill patients will continue to need acute inpatient services.
With aging infrastructure in some countries and increased demand for more beds in others, hospital executives and governments should consider rethinking how to optimize inpatient and outpatient settings and integrate digital technologies into traditional hospital services to truly create a health system without walls.
To learn what this future of health care delivery may look like, the Deloitte Center for Health Solutions conducted a crowdsourcing simulation with 33 experts from across the globe. Participants included health care CXOs, physician and nurse leaders, public policy leaders, technologists, and futurists. Their charge was to come up with specific use cases for the design of digital hospitals globally in 10 years (a period that can offer hospital leaders and boards time to prepare).
The crowdsourcing simulation developed use cases in five categories
Redefined care delivery
Emerging features including centralized digital centers to enable decision making (think: air traffic control for hospitals), continuous clinical monitoring, targeted treatments (such as 3D printing for surgeries), and the use of smaller, portable devices will help characterize acute-care hospitals.
Digital patient experience
Digital and artificial intelligence (AI) technologies can help enable on-demand interaction and seamless processes to improve patient experience.
Enhanced talent development
Robotic process automation (RPA) and AI can allow caregivers to spend more time providing care and less time documenting it.
Operational efficiencies through technology
Digital supply chains, automation, robotics, and next-generation interoperability can drive operations management and back-office efficiencies.
Healing and well-being designs
The well-being of patients and staff members—with an emphasis on the importance of environment and experience in healing—will likely be important in future hospital designs.
Many of these use-case concepts are already in play. And hospital executives should be planning how to integrate technology into newly-built facilities and retrofit it into older ones.
Technology will likely underlie most aspects of future hospital care. But care delivery—especially for complex patients and procedures—may still require hands-on human expertise.
Laying the foundation for the digital hospital of the future
Building a digital hospital of the future can require investments in people, technology, processes, and premises. Most of these investments will likely be upfront. In the short term, hospital leadership may not see immediate returns on these investments. In the longer term, however—as digital technologies improve care delivery, create operational efficiencies, and enhance patient and staff experience—the return result can be in higher quality care, improved operational efficiencies, and increased patient satisfaction.
These six core elements of an enterprise digital strategy can help you get started as you begin to push your hospital into the future
Create a culture for digital transformation
It is essential that senior management understands the importance of a digital future and drives support for its implementation at all organizational levels.
Consider technology that communicates
Digital implementation is complex. Connecting disparate applications, devices, and technologies—all highly interdependent—and making certain they talk to each other can be critical to a successful digital implementation.
Play the long game
Since digital technologies are ever evolving, flexibility and scalability during implementation can be critical. The planning team should confirm that project scope includes adding, modifying, or replacing technology at lower costs.
Focus on data
While the requirements of data interoperability, scalability, productivity, and flexibility are important, they should be built upon a solid foundation of capturing, storing, securing, and analyzing data.
Prepare for Talent 2.0
As hospitals invest in exponential technologies, they should provide employees ample opportunities to develop corresponding digital strategies.
Maintain cybersecurity
With the proliferation of digital technologies, cyber breaches can be a major threat to hospitals of the future. Executives should understand that cybersecurity is the other half of digital implementation and allocate resources appropriately.
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