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How Practice Managers Drive Your Clinic’s Growth & Efficiency Using Data

Written by byteIQNovember 22, 2021

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.

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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?