How big data is aiding patient care
One of the greatest challenges facing healthcare organisations around the world is the need to provide effective and accessible healthcare. With emerging pathogens becoming resistant to drugs and clinicians often diagnosing without sufficient data, the industry has become a fertile ground for technology development.
The digital health market is one that is predicted to grow exponentially in 2018 and beyond. According to a research from Statista, the number of wearables used for medical purposes – either biosensors worn by the patient or installed in their home – is projected to hit 34mn by 2022, showcasing great potential for data collection and analysis.
The digitisation of scientific information and patient data has marked a new stage in healthcare, which is now transitioning from reactive to proactive methodologies. Seemingly desparate information can be cross correlated to better inform diagnoses and help researchers keep up with the evolution of diseases. The following sections will illustrate how advancements in analytics are propelling a radical modernisation in the healthcare sector.
Defeating cancer with big data
DNA is made up of three billion base pairs in human body. When it comes to effectively fighting cancer, each patient requires a very personalised treatment due to how the disease mutates and reacts to various genetic make-ups. Although cancer treatment has been around since 1500 BC, it is essential to identify those mutations at the root of each tumour and map their genetic evolution in order to make progress in the battle against cancer.
By analysing large amounts of data, developments in genomic analysis have come a long way. By accessing the data that comes with the analysis of human genetics, organisations can now categorise it and analyse it in a way that would help researchers and scientists make sense of it, whilst relate it accordingly to necessary medical care. This has paved the way to new cancer therapy targets and discoveries, ultimately leading to better treatment.
Researchers are now able to perform more precise cost-effective analyses and predictions, combining genomic data with other sources such as demographics, trial outcomes and real-time patient responses for better patient outcomes.
Oncologists have been put in a better position to access previously unattainable insights to make important medical decisions, leading to better care and prevention. Other practitioners can easily access protocols about specific cancer treatments and learn which drugs are likely to be more effective for patients across the genetic spectrum and enabling decision making at the patient bedside.
Real-time patient monitoring for cheaper, more reliable services
Historically, caregivers have been responding to problems reactively as opposed to acting promptly with the most successful treatment.
In a typical hospital setting, nurses and doctors are trained to monitor patients’ vital signs. They may visit each bed every few hours, but the patient’s condition may decline between the time of scheduled visits. This is even harder to achieve if the patient has been discharged. He/she may skip their medications or ignore dietary and self-care instructions given by their doctor after leaving the hospital.
Real-time monitoring and body sensors have now become a valuable asset to provide a more personalised treatment to enhance patient outcomes with the potential of lowering costs of hospital care.
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Wireless sensors can capture and transmit patient vitals far more frequently than human beings can visit the bedside, and these measurements can be analysed in real time for advanced care. Diagnosis times are shortened and treatments are prescribed quicker. Doctors can be fed better data at the right time, meaning that a life-threatening situation could be averted much faster than if a patient was waiting for a doctor to visit on his rounds.
This can be the case of a patient suffering from congestive heart failure, a condition that is known to be leading to water weight gain. Patients no longer need to attend clinics for regular weigh-ins, as they can do it at home through one of many Internet-connected wireless scales to monitor water-weight gain.
Algorithms running in a data repository can determine unsafe weight gain thresholds and alert a physician accordingly. Furthermore, diabetic patients can benefit from remote glucose monitoring devices, allowing for the collection and analysis of data to promptly remediate a hyper glucose status.
The future of healthcare rests in predictive analytics
This collection of patients’ data through wireless sensors is paving the way for a newer form of healthcare. With hundreds of patients in any given hospital, the amount of data associated with each person can easily reach colossal amounts, giving practitioners a more comprehensive view of the patient at any given time.
Historical medical records can now be cross-referenced with other real-time information, such as heart rate, body temperature, glucose level and rate of breathing coming from sensors, enabling the clinician to access information that wouldn’t normally be immediately accessible. This paradigm has become a true game changer, allowing healthcare providers to get on the front foot and anticipate how a certain condition is likely to affect the patient in the long run.
The benefits brought by predictive analytics are uncountable, affecting not just the wellbeing of the individual but the way hospitals and research labs operate. A smarter way of anticipating issues and the ability to address a condition remotely, is leading towards a more effective use of hospital resources, resulting in less queuing and increased efficiency.
What is the future for big data in healthcare industry?
With a growing and aging population, as well as outbreaks of sudden and unexpected diseases, the healthcare industry will continuously demand effective and innovative solutions from governments and healthcare professionals. Luckily, developments in technology are fast progressing and big data analytics have the potential to radically change how healthcare services are delivered and improve care and patient’s health.
Researchers are able to identify mutations in the tumour genome, leading to the discoveries of more effective cancer therapies and the development of extremely targeted therapies. The lower cost of biosensors is resulting in massive amounts of information being collected and transmitted leading the ability to accurately predict outbreaks of epidemics, improve operational efficiency and people’s health in general.
The future of the healthcare industry is predicted to be bright, as long the data flooding resulting from this modernisation is adequately analysed and a robust data management strategy is implemented. Through the advancements in big data and analytics, all healthcare professionals and organisations can leverage data to its most advantage to make healthcare more affordable by reducing costs, also improve overall quality of patient’s care and treatment, and minimize the risks of future diseases.
How UiPath robots are helping with the NHS backlog
The COVID-19 pandemic has caused many hospitals to have logistical nightmares, as backlogs of surgeries built up as a result of cancellations. The BMJ has estimated it will take the UK's National Health Service (NHS) a year and a half to recover.
However software robots can help, by automating computer-based processes such as replenishing inventory, managing patient bookings, and digitising patient files. Mark O’Connor, Public Sector Director for Ireland at UiPath, tells us how they deployed robots at Mater Hospital in Dublin, saving clinicians valuable time.
When Did Mater Hospital implement the software robots - was it specifically to address the challenges of the pandemic?
The need for automation at Mater Hospital pre-existed the pandemic but it was the onset of COVID-19 that got the team to turn to the technology and start introducing software robots into the workflow of doctors and nurses.
The pandemic placed an increased administrative strain on the Infection Prevention and Control (IPC) department at Mater Hospital in Dublin. To combat the problem and ensure that nurses could spend more time with their patients and less time on admin, the IPC deployed its first software robots in March 2020.
The IPC at Mater plans to continue using robots to manage data around drug resistant microbes such as MRSA once the COVID-19 crisis subsides.
What tasks do they perform?
In the IPC at Mater Hospital, software robots have taken the task of reporting COVID-19 test results. Pre-automation, the process created during the 2003 SARS outbreak required a clinician to log into the laboratory system, extract a disease code and then manually enter the results into a data platform. This was hugely time consuming, taking up to three hours of a nurse’s day.
UiPath software robots are now responsible for this task. They process the data in a fraction of the time, distributing patient results in minutes and consequently freeing up to 18 hours of each IPC nurse’s time each week, and up to 936 hours over the course of a year. As a result, the healthcare professionals can spend more time caring for their patients and less time on repetitive tasks and admin work.
Is there any possibility of error with software robots, compared to humans?
By nature, humans are prone to make mistakes, especially when working under pressure, under strict deadlines and while handling a large volume of data while performing repetitive tasks.
Once taught the process, software robots, on the other hand, will follow the same steps every time without the risk of the inevitable human error. Simply speaking, robots can perform data-intensive tasks more quickly and accurately than humans can.
Which members of staff benefit the most, and what can they do with the time saved?
In the case of Mater Hospital, the IPC unit has adopted a robot for every nurse approach. This means that every nurse in the department has access to a robot to help reduce the burden of their admin work. Rather than spending time entering test results, they can focus on the work that requires their human ingenuity, empathy and skill – taking care of their patients.
In other sectors, the story is no different. Every job will have some repetitive nature to it. Whether that be a finance department processing thousands of invoices a day or simply having to send one daily email. If a task is repetitive and data-intensive, the chances are that a software robot can help. Just like with the nurses in the IPC, these employees can then focus on handling exceptions and on work that requires decision making or creativity - the work that people enjoy doing.
How can software robots most benefit healthcare providers both during a pandemic and beyond?
When the COVID-19 outbreak hit, software robots were deployed to lessen the administrative strain healthcare professionals were facing and give them more time to care for an increased number of patients. With hospitals around the world at capacity, every moment with a patient counted.
Now, the NHS and other healthcare providers face a huge backlog of routine surgeries and procedures following cancellations during the pandemic. In the UK alone, 5 million people are waiting for treatment and it’s estimated that this could cause 6,400 excess deaths by the end of next year if the problem isn’t rectified.
Many healthcare organisations have now acquired the skills needed to deploy automation, therefore it will be easier for them to build more robots to respond to the backlog going forwards. Software robots that had been processing registrations at COVID test sites, for example, could now be taught how to schedule procedures, process patient details or even manage procurement and recruitment to help streamline the processes associated with the backlog. The possibilities are vast.
The technology, however, should not be considered a short-term, tactical and reactive solution that can be deployed in times of crisis. Automation has the power to solve systematic problems that healthcare providers face year-round. Hospital managers should consider the wider challenge of dealing with endless repetitive work that saps the energy of professionals and turns attention away from patient care and discuss how investing in a long-term automation project could help alleviate these issues.
How widely adopted is this technology in healthcare at the moment?
Automation was being used in healthcare around the world before the pandemic, but the COVID-19 outbreak has certainly accelerated the trend.
Automation’s reach is wide. From the NHS Shared Business Service in the UK to the Cleveland Clinic in the US and healthcare organisations in the likes of Norway, India and Canada, we see a huge range of healthcare providers deploying automation technology.
Many healthcare providers, however, are still in the early stages of their journeys or are just discovering automation’s potential because of the pandemic. I expect to see the deployment of software robots in healthcare grow over the coming years as its benefits continue to be realised globally.
How do you see this technology evolving in the future?
If one thing is certain, it’s that the technology will continue to evolve and grow over time – and I believe there will come a point in time when all processes that can be automated, will be automated. This is known as the fully automated enterprise.
By joining all automation projects into one enterprise-wide effort, the healthcare industry can tap into the full benefits of the technology. This will involve software robots becoming increasingly intelligent in order to reach and improve more processes. Integrating the capabilities of Artificial Intelligence and Machine Learning into automation, for example, will allow providers to reach non-rule-based processes too.
We are already seeing steps towards this being taken by NHS Shared Business Service, for example. The organisation, which provides non-clinical services to around two-thirds of all NHS provider trusts and every clinical commissioning organisation in the UK, is working to create an entire eco-system of robots. It believes that no automation should be looked at in isolation, but rather the technology should stretch across departments and functions. As such, inefficiencies in the care pathway can be significantly reduced, saving healthcare providers a substantial amount of time and money.