Blog

By byteIQ

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?

By byteIQ

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?

By byteIQ

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.

By byteIQ

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.

By byteIQ

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.

By byteIQ

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.

By byteIQ

Healthcare data is valuable and a favorite target of cyber criminals globally. Data privacy and security standards apply to all who handle healthcare information and rightly so. Unfortunately, when every clinic, hospital, and primary care provider stores all their data in isolation, insights into overall population health become near impossible to find. There is no central repository, even for data with personally identifiable data (PII) stripped away. This in turn stifles innovation, whether in the form of clinical drug development, research, or product development and innovation for the healthcare industry. Despite this, even at a single location, there is a place for healthcare analytics. If you cannot analyse nationally, by state, or even by city, it is still possible for each healthcare provider to use analytics to enhance patient care and maximise their profit margins. Let’s look at how healthcare analytics can aid operation goals. Operations The purpose of collecting administrative health data include but are not limited to: Managing individual patients and continuity of care Streamlining healthcare service delivery at all levels, and maximising treatment room turnover Managing and administering hospital and healthcare service delivery Keeping track of healthcare costs including billing for goods and services delivered Informing and evolving the health system policies Ensuring reliable and consistently high quality of care. Other Applications While analytics can improve efficiency, it is also used to identify patterns in healthcare data that go far beyond the per-patient clinical diagnosis. Telehealth monitoring devices can identify stress triggers in those with high blood pressure or diagnose those with intermittent cardio problems. Wearable devices such as fitness trackers are added to the mix and can act as diagnostic tools, with primary care providers referring to specialists as needed. Risk factors such as age, genetic predisposition, demographic, location and environment are introduced (in the form of algorithms) to provide preventative care to patients, and ideally before symptoms present. In conclusion, while data isolation is a problem for Australia as a whole, primary care providers can use their own data to enhance patient care and increase operational efficiency. There is no doubt that the use of data analytics will continue to grow along with electronic medical records (EMRs) and trials of new solutions (such as medication management by Box Hill Hospital) will only aid widespread adoption of future innovation in analytics. In the meantime, can you afford to cling to legacy systems while your competitors adopt analytics?

By byteIQ

With the combined global market in healthcare data analytics predicted to exceed $43m by the end of 2022, it’s no surprise to discover that there are many companies seeking to dominate the area. You have the usual big players such as IBM (pioneer of the Watson AI) and SAS. Others, such as Ayasdi and Digital Reasoning Services develop AI-based solutions to transform multiple industries, including healthcare. You have Linguamatics, focused on healthcare and offer solution to many of the global pharma companies. IoT-based solutions to enable analytics are offered by Telit and care syntax. Others include Lumiata, Roam Analytics and Enlitic. After that, there are hundreds of other companies, all vying for your consideration. Why? Because healthcare data is useful and valuable, and not just for cybercriminals. The aims of healthcare data analytics include but are not limited to: Reducing administrative costs. Forecasting supply & demand – anything from facilities traffic to supply chain requirements. Improving patient care – supporting evidence-based decisions, for example. Improve drug discovery in clinical trials. Predict patient responses to medications. Insurance companies can assess risk before quoting. Choose YOUR Analytics Provider The decision to invest in healthcare data analytics is not one taken lightly. Before you do, consider what’s needed, your location, your data complexity and quality and identify any potential challenges. It’s one thing to plump for a big player and discover you need a data scientist to make sense of it. Or that your selection has little knowledge of the medical industry or Australian data and privacy laws. Let’s be honest… As a medical professional, you want to maintain your existing role and not get bogged down with technical requirements, issues with poor quality data or analytics challenges that require advanced skills to remove. It’s for that very reason that you need a trusted partner, based in Australia, with intimate knowledge of the industry and the pressures facing healthcare professionals. It’s a fact that providers who focus on complex analytics fail yet those vendors who provide relevant, simple and to the point metrics are being adopted by the industry. Why not talk to us to discover the practical benefits of data analytics in healthcare?