Article | February 22, 2021
The criteria of patient satisfaction have changed dramatically. The priority of your healthcare business is to provide patients the right treatment. But nowadays, you cannot excel in your service and win the hearts of the patients just by providing the right treatment. You will also have to focus on delivering a great patient experience. Thus, a comprehensive healthcare marketing strategy should be designed accordingly.
In this digital age, along with their healthcare requirements, people are already overwhelmed with all the necessary information they need regarding their work and life-related issues. This has turned them into customers, rather than just being patients. And has led them to want and expect more. According to a study done by McKinsey, people expect from healthcare companies the same way they expect from other non-healthcare companies. Your patients now expect:
• Your deliverance on their expectations
• Great customer service
• Great value
• To make their life easier with the service they get from you
They look for whether your healthcare services provide these benefits through online resources. A Kantar Health Report says that around 60% of millennials depend upon online information as the best resource for healthcare information. They also consider word-of-mouth referrals trustful. This makes it vital for you to put in place the right digital healthcare marketing strategies. It is necessary to avoid your prospects going to your competitors whenever they search for effective medical services online.
The need for a robust Healthcare Marketing Strategy
Creating an effective healthcare marketing strategy is part of the inbound marketing process. The strategy can include and utilize all the resources to bring in opportunities. The resources also can confront the threats that come your way to hinder your healthcare business. The resources can be in any form of original content such as articles, blog posts, podcasts, interviews on medical topics, informational videos, e-books, case studies, press releases, white papers, etc. These resources deal with threats and opportunities that are concerned with persuading prospects to come to you.
Healthcare marketing strategy is a vision statement. It lays down the healthcare marketing plan in detail for some time. It should include objectives and plans for exceeding the current performance of your particular healthcare business. It should talk about competition analysis, target marketing, budgets, marketing tactics, and SWOT analysis, which are essential elements of an effective healthcare marketing strategy. Having the right healthcare marketing strategy in place will help you increase patient inflow and lower your marketing budget, which increases your return on investment (ROI).
Benefits of Having an Effective Healthcare Marketing Strategy
The right healthcare marketing strategy focuses on two main things; bringing in more patients to your hospital or clinic and maximizing your ROI. ROI can be maximized by minimizing expenses on both inbound and outbound marketing strategies. It is called ROI based marketing plan or strategy.
There are many benefits to having an effective healthcare marketing strategy in place for your medical practices. They include anticipating and assessing threats and opportunities, prepare to make a road map to counter the threats in time effectively, and find out creative ways to enhance your outcome. Below are some of the other benefits of having a healthcare marketing strategy:
Goals and Objectives
A sound healthcare marketing strategy, as discussed earlier, helps you to understand what you are going to achieve in a scheduled time frame. This keeps you focused on your goals without getting diverted. Moreover, it provides you a clear picture of your business's growth and makes you aware of how far you can go with your business in the target market.
Healthcare marketing strategy helps you create a detailed operation budget in advance for your business. By knowing your expected future costs, expenses, and forecasted income over the year, you can make better plans for all the expected and unexpected challenges of your business.
Service Line Decisions
When you compare your result with your expected results, you will understand where it worked well and the areas you need to improve. By knowing the areas in which you failed, you can improve them and yield better results on the next run by improving your line of services.
In business, risk management includes forecasting and evaluating the financial risks and identifying solutions to minimize or eliminate their impact. A clear healthcare marketing strategy in place allows you to manage these aspects of your healthcare business efficiently.
A marketing strategy provides you a clear idea of how to process your budgeting resources for your organization's future. It is possible with both short-term and long-term plans.
Developing an effective healthcare marketing strategy
Creating goals and defining objectives or benefits that you intend to achieve is the first step to the creation of a healthcare brand strategy. Once all these things are set, you may assess all the required and available resources. Then devise a final strategy on when and how to fulfill these goals.
Healthcare digital marketing is unique as it is the most cost-effective way to reach out to your most relevant prospect at the right time. It ensures thatyou reach your patients in the time of their need. Here is a step-by-step healthcare marketing strategy for you. It is designed keeping in mind all the aspects of your healthcare business, including your competitors and prospective patients.
Establish Your Target Customers
The first step starts with identifying the most relevant target market for you. A comprehensive online and offline research would help you with it. The research can be based on demographic, geographic, behavioral, and psychographic information.
Then concentrate on all the marketing resources you have, in order to attract relevant customers. Clarity about your target audience ensures you create the right content for the right people. It also adds to the efficiency and effectiveness of your digital healthcare strategy.
Study Your Competition
Your competitors also target the same audience. So, identify competitive influences and issues to have a proactive strategy and plan. It helps you stay ahead of your competition with your healthcare marketing strategy. Use internet, TV and Radio commercials, referrals, data analysis, billboards, or other media to research your competition.
Internal and External Evaluation
To evaluate your external and internal environment, conduct a SWOT analysis of your healthcare business. Thorough knowledge of your strengths, weaknesses, opportunities, and threats will make you determine how to use your resources for better results effectively.
Decide Your Long-term and Short-term Goals
Most businesses conceive their marketing plans and strategies for a year. However, the best healthcare marketing strategy is the one, which is aligned with both the long-term and short-term goals of your brand. Evaluating, prioritizing, and organizing various combinations of specific marketing tactics and strategies will suit you the best in pursuing your business goals.
Plan Your Marketing Budget
Protecting and generating sources of revenue is generally a significant concern in marketing. Creating a task budget and clear objectives to work towards realizing the exact goals and outcomes you expect from your business is very important. For this, you may have to specify your measurable and quantifiable goals. Define your marketing tactics and strategies, including advertising, brand development and enhancement, networking and public relations, etc.
You also have to evaluate profitability, launching plan, and marketing plan. Moreover, monitor and track closely to adjust tactics and strategies necessary for achieving, maintaining, or exceeding your expected profit level.
The best part of having an effective healthcare marketing strategy in place is that it makes you focus your energy and time on improving your healthcare practice. The digital marketing team will work according to the strategy for realizing both your long-term and short-term goals.
Doing all of it alone may be challenging. We, at Media 7, help healthcare companies, especially healthcare technology providers, with healthcare marketing strategies, which are proactive and profit-oriented. We help you attract prospects, convert them, and make them your customers. To know more about us, visit the Media 7 website.
Frequently Asked Questions
What are marketing strategies for health tech marketers?
Health tech marketers can effectively use many marketing strategies, including engaging customers in social media platforms, video marketing, creating content for niche communities, email marketing, paid media advertising, event marketing, and content marketing.
What are the tips for creating the strategy for health tech marketing?
Updating your organization’s mission, vision, and values, conducting a business and operational analysis, developing strategic options, selecting strategic growth objectives, developing the strategy execution plan can be included in your health tech marketing strategy.
What are the best social marketing strategies for health tech?
Start using chatbots, create a personalized experience for your customers, create an efficient content marketing strategy, create a community for your audience, and create profiles on the relevant channels that can be the best social media strategies for health tech companies.
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"text": "Updating your organization’s mission, vision, and values, conducting a business and operational analysis, developing strategic options, selecting strategic growth objectives, developing the strategy execution plan can be included in your health tech marketing strategy."
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"text": "Start using chatbots, create a personalized experience for your customers, create an efficient content marketing strategy, create a community for your audience, and create profiles on the relevant channels that can be the best social media strategies for health tech companies."
Article | February 24, 2020
Technology is only as useful as the value it helps us deliver. For us to get to the next phase of this evolution, technology must fit into a patient-centric care model. When I shifted my role from a full-time practicing physician to a healthcare administrator 20 years ago, there were no national standards on quality measurements, let alone for performance-based payment or value-based payment models. Today, value-based initiatives are shifting care delivery from compensating volume to compensating value and redefining financial incentives toward better patient outcomes. In this model, providers must think about the entire patient experience across all care settings and between episodic visits. On top of this, consumer behavior is changing the way patients choose and receive care. Patients are increasingly embracing convenient options for their healthcare that match their lifestyle, but still want the peace of mind that comes with support from a consistent primary care provider or care team.
Article | September 4, 2020
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):
Clinical communication and collaboration
Next-generation nurse call
Alarms and notifications
Integrated patient room
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.
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.
Article | March 27, 2020
The key concerns of healthcare management today are data processing and data security. Patients don’t have full ownership of their medical records, and are unable to control how their information is updated. There isn’t enough transparency to the process. There are also significant concerns related to data security, especially in the areas of personalized medicine and the rise of wearables. Patients and medical staff need secure and straightforward ways to record data, send it over networks, and receive advice without security concerns. Blockchain technology can help solve these problems. Introduced in 2008 as a means of recording cryptocurrency transactions, blockchain is a distributed cloud-based ledger that offers the ability to verify the origin of data and prevent breaches. When a user wants to make a transaction, they issue a request signed with their private key. The network verifies its authenticity by using a public key. If the verification is successful, the transaction is broadcast to the network and included in a block. The network of “miners” solves the block to get a reward, and once the block is revealed, it is added to the blockchain, making it permanent. It’s impossible to introduce new information in a block unnoticed, because that would change the structure of the entire chain. This feature makes the system safe and transparent.