Amazon Web Services (AWS): Innovating Healthcare Technologies
Organisations large and small, regardless of location or industry are highly likely to use Amazon Web Services (AWS), given their global reach as a provider of cloud solutions. The AWS Marketplace is a digital catalogue with a dizzying range of solutions designed to improve business operations. Categorised by industry, we are only concerned with their solutions in the ‘Healthcare and Life Sciences’ category. By using AWS, healthcare organisations can ensure business continuity, optimise processes, provide tools to enhance clinical care, diagnostics and treatment and use new analytics capabilities and machine learning technologies. This is achieved while meeting both regional and global security and privacy requirements. Broadly speaking, AWS healthcare solutions are broken down into the following categories: Core operations and business continuity Care Coordination Health Analytics Patient Engagement Clinical Information Systems Storage and Archiving Compliance Each category is important, of course, but it’s important to remember that there is no one-size-fits-all solution for your organisation. After all, there are more than 1600 software vendors in the AWS Marketplace, covering everything from analytics and telehealth solutions to real-time robotic assistants in surgical training scenarios. For brainstorming purposes, why not read up on some of the available use cases that could be applied to your situation? Note that there is some expertise required to set up, configure and maintain AWS solutions, the majority of which are pay-as-you-go. However, with a trusted partner, you do not need a high level of technical expertise, even to incorporate healthcare data analytics. The extraction of useful insights from medical data is complicated by the fact that much of it is free-form text (such as handwritten doctor’s notes, clinical trial results and medical records), none of which are easily catalogued by traditional means. However, with AWS Comprehend Medical, all this data is easily manipulated for maximum results, compiling a viewable set of data by treatment, medication dosages and any other variables you’d like defined. Such information is key to population health analytics, clinical research and pharmacological analysis and the extracted data can then be linked to electronic health records if necessary. AND, all of this is achieved without hiring data scientists to refine algorithms or create new ones. In conclusion, we highly recommend AWS to our clients and utilise some of their solutions when rolling out innovative and fully-compliant healthcare solutions for the Australian market. Byte IQ is proud to be an AWS partner as well as an AWS client. Our technologies including Healthcare data lakes, AI/ML, and security tools are all built on AWS cloud technologies.
What is a Predictive Algorithm and Can it Predict Who Will be Sick and When?
In the computing world, an algorithm is a set of instructions, or steps, required to get from one situation to another. It could be as simple as providing directions to exit a building from a fixed starting point to a defined fire exit. Your GPS uses algorithms to take you to your destination using the shortest viable route, for example. But what would make the same GPS algorithms predictive? A predictive algorithm would provide a different outcome, based on previously stored data. In the GPS analogy, this stored data could consist of breaking news bulletins, social media alerts and historical traffic information. In order words, based on all available data, your GPS could offer a different route because: A pattern of traffic jams has been established for the time you are traveling. A news bulletin or social media alert indicates that there is a traffic jam due to an accident or natural disaster. The normal route is closed for repairs. Clearly, even with GPS, predictive algorithms offer benefits, but there is one key element necessary before use. Historical or even updated real-time data is necessary before predictions are possible, given that data scientists are not psychic and all predictions are based on extracted patterns. Therefore, in a healthcare environment, data sets are necessary, as these will allow actionable insights that are not apparent using traditional means. Data analytics and predictive algorithms go hand in hand. You cannot have one without the other. AND predictive algorithms evolve, given their link to machine learning and artificial intelligence (AI). Let’s assume your healthcare organisation has all the necessary data (even if currently free-form and/or unstructured). With the right tools, insights are extracted to highlight patterns that are not obvious, even to the keenest researcher. The potential for preventative care is limitless as risk factors/ adverse reactions for patients taking multiple medications become apparent. In a unified environment, threats to population health are identified as infections increase in what are now recognisable patterns across jurisdictions, hospitals and clinics. In a world now recovering from a global pandemic, can we really afford not to invest in healthcare analytics?
What is Big Data & Will it Solve Our Healthcare Problems?
In its simplest form, Big Data refers to large volumes of data that is impossible to extract insights from manually or using standard computing techniques. Volume data can be structured (in a database, for example) or unstructured (composed of everything from Individual text files, marketing material or even social media messages and internet voice calls). Big Data Is Not ENOUGH Additional techniques are necessary to make sense of all the data and this where data scientists and machine learning experts come into the picture. Having Big Data is one thing but without analytics (where data scientists create algorithms to sort and extract actionable insights from previously nonsensical information) it’s pointless. Trained professionals create unique algorithms for the non-technical to visualise their data or tools to allow automated searches useful to your healthcare organisation. In addition to standard analytics, it’s also possible to generate predictions based on historical data, both of which aid clinicians in preventative care by age, gender, family history or other risk factors. We’re Medical Professionals Not Technologists Clearly, Big Data has the potential to solve many healthcare problems but is not a cure-all. Clinicians are concerned with diagnosis and medical care. They are not technology experts and don’t need to be. However, advanced tools and resources are needed, as mentioned previously. Implemented correctly, a healthcare big data solution can improve efficiency by identifying bottlenecks, reduce fraud such as identity theft, can improve preventative care by analysing risk factors and can improve research capabilities by identifying data that would have been missing using standard methods. To take a grand real-world example, how about population health, whether your community or the country as a whole? If everyone’s health information was centralised and anonymised correctly (patient privacy is a major consideration when implementing systems of this nature), it makes it easy to identify patterns using analytics. Let’s Improve Would Covid-19 have caused so much turmoil around the world if each country had a comprehensive healthcare data solution to compare a surge or similar symptoms in their patients, regardless of location? I don’t believe so. In the meantime, individual healthcare organisations can embrace technology and use analytics to extract valuable operational and indeed medical insights from data they already have inhouse. As the drive towards digitisation and value-based care (including telehealth) continues, why not take advantage of the benefits?
New Clinics Need Tools to Scale and Become Process Driven Yet They Need Clinical Insights to Benchmark Progress
Opening a new clinic is an exciting time for all involved and requires a lot of preparation work to ensure a quick integration into the community. Processes and the tools and equipment necessary to carry them out are obvious but rolling them out in a way that fosters growth is easier said than done. This is especially true of data as you are starting with a clean slate, given that there is no central repository that new clinics can use to acquire foundational data. You are essentially on your own in the start-up phase. It will take time to build up your patient and clinical data. You want solutions for your practice and not someone else’s. How can you maximise your data capabilities in these early days? Choose Wisely Unfortunately, there is no single blueprint for setting up a clinic and organising the necessary data entry, organisation and subsequent analytics. Every clinic is different, with different specialities, objectives and processes. You need tools and solutions that reflect your clinic, your requirements and your procedures. Admittedly, you will have some building blocks to integrate into your data acquisition schedule (such as electronic health records (EHRs) but by and large, the tools you select are defined by your workflows. In an ideal world, the software you want will seamlessly handle your workflows but this is rarely the case and customisation is necessary. Investing in developers and data scientists is unlikely, even for large clinics and hospitals so the best approach is to outsource to a trustworthy partner, one who understands the healthcare industry and the finer points of clinic management. Integrate and Analyse In consultation with your provider, outline your processes and define the metrics you need to measure. These can be volume-based (number of patients, appointments, treatment rooms etc.) financial or any other metric you want to track, including patient feedback, remote monitoring, collaboration etc. Let your provider set up your clinic dashboard in the selected practice management solution– where you can easily view data in graph, pie chart or desired option. You define the clinical insights you require from the data and the provider automates the process as much as possible. Let’s say you want to monitor the use of a certain medication and the related clinical outcomes or you need to maximise traffic in treatment rooms. Or you wish to engage with patients based on their risk factors due to age, gender or other demographic–scheduling ECGs for older adults to screen for heart disease, or regular check-ups for older patients. The possibilities are truly endless and determined by your clinical knowledge rather than expectations of a service provider. Maximise the success of your new clinic by choosing the right tools at the start. There’s no point in investing in features you will never use. Equally, there is no point in abandoning all the advantages offered by a growing data set. Have an informal chat with our team to discuss your options before investing in costly tools that fail to consider future growth..
Clinics & Covid-19, Will Data Help Control the Next Pandemic?
Covid-19 was an eyeopener for the global health community and effectively demonstrated how, apart from a few countries, ill-prepared we were to handle a pandemic. The siloed and decentralised nature of all healthcare data became the biggest stumbling block to identifying it and getting it under control. Next time, we are sure to do better… Data is Key Covid-19 presented with many of the symptoms of flu, which complicated early diagnosis, as many ER doctors and GPs would treat it as flu, discharging the patient and treating the common symptoms in the usual manner. Once identified in China, analysis led to identification of Covid-19 and the full gene sequence was released to the WHO and other organisations. China locked down its border and the source of the identified outbreak, introducing nationwide monitoring in every location. This involved temperature checks and contact tracing, both of which involved big data projects and helped prevent further spread. Data vs. Privacy Covid-19 has demonstrated that data usage is the primary way to predict, detect and control any pandemic. However, privacy advocates rightly state that anonymising all healthcare data is necessary, even in a pandemic situation, even if a public health emergency is declared. That said, data allowed Covid-19 vaccine creation in record time, allowed researchers to identify variants as they arose and allowed public health authorities to identify clusters and outbreaks as they occurred. Global collaboration allowed supply chain improvements for protective equipment and equipment such as respirators. Many nations introduced apps to allow contact tracing and isolation of possible carriers once the infection was detected. With experts predicting future pandemics, it’s clear that data will have a major role to play in the next one. Is your organisation ready to protect your community and help identify it?
What is population health and how will it change the healthcare service delivery model?
The term ‘population health’ is used throughout the healthcare industry and its definition seems flexible, depending on the viewpoint or activity of the person supplying the definition. Some focus on measurement of outcomes, while others emphasise the contribution of healthcare providers or technological innovations to health improvement. What all seem to agree on is that population health is an overall conclusion based on the health condition of a defined group i.e., the population, whether is the entire country, a subset or even a single community. This is not the same as public health where a society attempts to offer optimum living conditions that are free from influences that negatively impact health. This can include pollution, hazards such as asbestos in older buildings, national immunisation programs, food safety and many other areas including unexpected pandemics. Despite a lack of a single definition, what is clear is that population health is worth thinking about and its also worth considering the improvement of the healthcare service delivery model, whether it relates to health administration, consulting, academics and research and even insurance. Modern clinics and practices are no longer solely in the business of reactive diagnosis and treatments but are more focused on preventative care i.e., diagnosing health issues before they become life-threatening or acute. If technology is used to improve other industries, there is no reason for healthcare to drag its heels in this area. To take aged care as an example, the focus is now on quality of life rather than just prolonging life. Australia has one of the highest life expectancies in the world (81.5 years) and the aged population is growing, with many suffering from several chronic long-term conditions such as arthritis and hypertensive disease. Retirees suffer from Type 2 diabetes at higher rates than before. The list goes on and the fact is that there are many conditions or issues that are age, gender or environmentally connected. Patients are now more concerned about their health and welcome the use of technology to improve their wellbeing, with fitness wearables and other devices to monitor their vitals. The data from these devices acts as a useful diagnostic tool for medical professions. In an age where telemedicine, data analytics and practice management tools are readily available, the entire healthcare service delivery model is due for disruption. Can you afford to ignore it, when future models involve the elimination of information silos between medical service providers?
Are Primary Care Clinics Suffering from Too Much Tech and Information Overload?
A 2019 article in Healthcare IT News speculated that electronic health records (EHRs) was a contributing factor to physician burnout and, it must be said, there is some truth to this. Technological advances, beneficial or not, often require training and are ‘disruptive’ by nature. The old way of doing things must be abandoned in favour of new innovations, some of which are provided by tech leaders with no practical experience in healthcare. This complicates matters even more. Today’s clinics are expected to perform like their mainstream business counterparts, with patient engagement, social media outreach, and a wide variety of technical expectations to satisfy modern healthcare shoppers or ‘consumers.’ This can include remote consultations, telehealth monitoring or simply colleague collaboration on the move. It’s easy for healthcare professionals to become overwhelmed in such a technical environment, although some healthcare professionals are more eager to adapt than others. Practical Training If we take a small clinic in the early 2000s, as an example, we find that most will have an IT presence. Perhaps they have a part-time IT resource who visits a few times a week or (in later years) IT support is provided remotely to keep the network up and running. The doctors and nurses did not concern themselves with It as they are only concerned with clinical tasks. Today’s healthcare pros should only concern themselves with the relevant aspects of new technologies and adopt only those that aid value. There may be many advanced aspects to EHR usage but are they all necessary? It’s no surprise that both doctors and patients become frustrated at all the questions requiring completion. Delegate! Of course, doctors understand that learning never stops in the world of medicine and constantly attend courses to update their training. I believe they cannot be expected to do the same in technology, especially if this technology is indirectly related to their core activities, diagnostic medicine and treatment or referral to a specialist. That is what delegation or outsourcing is for. Are clinics expected to hire data scientists (a scarce and expensive undertaking) to manage data extraction and analytics, for example? Rather than listen to endless sales pitches on what they claim you need, why not consult with our healthcare-focused team and determine how we can simplify your technological needs in a way that complements your processes? This will allow your clinic to focus on effective healthcare, your core area of expertise.
Deliver Growth in Your Clinic By Transitioning from an Operational To Strategic Mindset
Whether involved in primary or secondary care, clinics act as businesses. While profit is not the primary motivation, it is certainly a motivating factor for business continuity. Technological advances, not least of which is digital transformation have changed the healthcare landscape forever. Resistance is futile as your patients now treat healthcare like any other service, as consumers where competition is available. AND yes, likely there is an app for it. Under this new patient-centric model, clinics can no longer afford to treat patients as before. Preventative care is the focus, requiring a whole new playbook, one where strategic growth is the aim rather than merely processing patients as they arrive. Clinic Processes While mainstream businesses have embraced business process management (BPM)for years, healthcare is often resistant to change, given that clinical care is the primary focus. However, thanks to the nationwide push for electronic health records (EHRs) and other digital health initiatives such as Telehealth and the Healthcare Identifiers Service, clinical process management has become more important. Those who fail to evolve with the times lose out to competitors or fail to qualify for programs such as Medicaid. Like it or not, this is the age of ‘on-demand’ healthcare and clinics must move with the times. Why ‘Strategic Thinking’ is Essential Operational thinking is the same as administration. You record the data necessary to satisfy existing processes or enter data as required by law to update EHRs, complete prescriptions or schedule appointments, for example. It deals with the present and rarely considers the future. Strategic thinking, on the other hand, involves creating new processes or improving existing ones in a manner that can solve future needs i.e., tomorrow’s consumer. Success or failure involves measuring outcomes and then implementing a final strategy that benefits both patients and your clinic operations. Examples of strategic planning could include remote consultations, social media outreach to potential patients, new preventative care programs aimed at the aged or at risk in your community and leveraging the power of your existing data to improve overall efficiency. It is possible to work on your business rather than simply work in it. Interested in hearing more? Consult with one of our team for customised solutions for your clinic.
Practice metrics which highlight growth, risk and opportunity
Whether you call them ‘metrics’ or key performance indicators (KPI), modern clinics and practices use them to satisfy primary healthcare demands in a professional and efficient manner. Of course, there is no need to go overboard and identify every possible metric, only the essential ones that will encourage growth, identify potential risk and identify areas of opportunity. Such metrics will likely vary according to clinic area, size or location but three primary areas include financial, operational/business and internal metrics. Other categories with possible metrics include public health (number of vaccinations, for example), emergency care metrics (wait times by process step, for example) and communications (which could including marketing, patient satisfaction with clinic process and paperwork or indeed patient turnover). Let us look at a few metrics for each of the primary categories: Financial The financial wellbeing of your clinic or practice is of course of paramount concern and providers of primary healthcare solutions must remain solvent, just like any other business. Key metrics include, average treatment cost, cost of permanent staff and average insurance claim processing and related cost. Operations/Business Operational metrics refer to the functional processes of the business, whether it’s patient wait time, average number of beds or treatment areas in use at a given time or indeed staff to patient ratio. Bed or room turnover is an important one, for example, and such metrics are useful can help optimise revenue. Perhaps patients of a certain age or gender could utilise screening options on specific days or those with underlying conditions that require regular visits could be seen during off-peak hours. With operational metrics the aim is to improve efficiency and maximise all clinic specialties. Internal Internal metrics could include staff trainings per department or number of practice error events. Can you currently calculate the following vital metrics without poring over Excel sheets or wasting hours on busy work? Patient Encounter Value (PEV) – What is the value of your patients to your practice, whether it’s dollars per patients, per clinical resource or per time period? Appointment Utilisation – What’s your current and projected clinic load based on appointment schedules? Whatever metrics you choose, your aim is to focus on clinical duties but not on complex reporting. You wish to improve the practice and provide solutions that exceed your competitors in what is now a service-oriented space. The automation and improvement of these metrics is possible, with full customisation using an AI platform we call Huddle. Contact us to arrange a no-fee no-obligation demo.
How Practice Managers Drive Your Clinic’s Growth & Efficiency Using Data
Practice managers, by definition, manage the practice to make sure it runs effectively. They do this using a variety of tools to organise clinic data, ranging from practice management software to electronic health records (EHRs) and even doctor’s handwritten notes. Their aim is to maximise patient engagement and retention before, during and after patient visits. The old ‘as needed’ relationship between patient and healthcare provider is no longer enough post-digital transformation. Today’s patients are used to digital solutions and interaction, expecting a more consumer-based approach to healthcare than before. Luckily practice managers can achieve a higher standard of care and improve clinic efficiency by leveraging clinic data. The versatility of Data Regardless of the practice management tools selected by your clinic, most will have an easy learning curve, with a healthcare dashboard for easy visualisation of key metrics. With visualisation available, it is easy to identify problem areas and resolve them as need or budget allows. It’s important to avoid identifying all metrics, given the volume of clinic data generated. Common key metrics include but are not limited to: Volume metrics–the number of patient visits, by frequency, by department and even my treatment room or specialist. Appointment times and durations. Number of referrals and who from. Such metrics allow you to assess current services, treatment capacity and estimate future projections. Revenue leakage metrics–missed or cancelled appointments and rescheduled appointments due to overcapacity. Such metrics allow treatment optimisation or appointment scheduling improvement. Utilisation or treatment metrics–Identify the most common clinical services and their frequency. Are all resources used effectively? Quality metrics–Very important, contains information on patient and employee satisfaction as well as post-treatment data such as clinical outcomes and outpatient wait times. Financial metrics–linked to clinic efficiency. To remain viable, clinics must generate sufficient revenue and these metrics allow revenue vs. expense visualisation for all aspects of the clinic. Clearly, clinic data is vitally important to practice managers, helping to drive growth, reduce billing errors and deliver solutions in line with your services and patient base. Doing so effectively requires data extraction and visualisation for later decision-making. If you need help in this area, contact our team for viable and cost-effective solutions to take your data to the next level.