Jake Freivald, vice president at the data quality, integration and analytics pioneer, Information Builders believes that the way we approach data is key to how healthcare can respond to today’s’ challenges
The Office of National Statistics has predicted that within 22 years there will be 10 million people aged over 75 – almost double the current number. People living longer with more complex conditions and shrinking NHS budgets are forcing a rethink on the way that care is delivered to patients of all ages.
When demand outstrips human capacity, societies turn to technology and automation. In a similar way, the NHS and healthcare providers around the world are exploring ways to use technology to improve the planning and delivery of care. There is a drive towards patient-centred care and using wearable technology and apps to monitor long-term conditions, with patients sharing data confidentially with medical professionals.
The Internet of Things (IoT) holds the potential for rapidly advancing the understanding of particular conditions, treatments and side effects, through real-time analysis of vital statistics. Data from hospital machines and wearables, as well as shared data from anonymised research offer healthcare providers new opportunities to diagnose conditions more quickly, use medical resources more efficiently and save costs. However, this needs to be balanced against traditional care, expertise and patient knowledge, so that insights from big data can be viewed in the context of individual patients.
Currently, many healthcare providers are still integrating and analysing data in batches, which is fine for monitoring overall trends, but could miss more granular medical events. As an example, a patient’s pulse might be recorded every 30 minutes using a heart rate monitor. However, a doctor or nurse at the patient’s side might notice a spike in heart rate that occurs 15 minutes after the patient takes a particular medication and then settles down in a matter of minutes. This information wouldn’t be recorded on the electronic medical record, but is crucial for a medical specialist, researcher, or pharmacist who needs to understand the effect of medications on patients.
As more healthcare providers realise the benefits of IoT data, we will see more demand for real-time analytics, which give a full picture of patients’ progress in response to different treatments and medications. By analysing an individual patient’s progress in conjunction with other, anonymised data sources, healthcare providers have the opportunity to speed up clinical trials and to advance treatments. Organisations have an opportunity to harness the IoT to rapidly ingest, analyse and contextualise big data generated by connected hospital devices, smart city sensors, research labs, and wearables.
Of course, not everyone using anonymised healthcare data will be a trained data scientist. As IoT-based analytics becomes the norm, we will see more use of embedded analytics that incorporate evidence-based data into everyday applications. This development will allow healthcare professionals to spot patterns in treatments and outcomes, helping them to make better decisions that benefit patients, without them having to learn new IT applications.
Providing different healthcare professionals with a single view based on the same data sources is absolutely critical for delivering best value from data. For example, electronic medical records were not designed to be used for analytics because they only provide part of the picture of the patient journey. To be able to perform adequate analysis healthcare providers need to be able to draw information from primary care, community care, adult services, pharmaceutical data and so forth.
As long as they are anonymised, data from a variety of organisations can be shared so that they can be used to provide a more complete picture of what’s happening with a population’s health. Data quality is also important because if errors are incorporated at the start, then this will impact on the quality of the inferences that can be gained from data downstream. This is why data mastering is such an important element of data analytics.
We have worked closely with St Luke’s University Health Network, a non-profit network of seven hospitals in the USA that operates more than 270 outpatient facilities, to develop Omni-HealthData Insights. This builds on our Omni-HealthData patient-centric data repository, which incorporates inpatient, ambulatory, clinical data, clinician, facility and administrative data, to deliver highly interactive analytical applications to everyone involved in care delivery. The first iteration focused on Quality and Patient Safety, Hospital Patient Experience, Physician Practice Management and Hospital Network Performance. For example, Quality and Patient Safety applies root cause analysis to clinical quality, infection control and risk management.
By integrating data on patients, medical staff, facilities, and insurance providers, into a single view, healthcare providers can gain vital clinical and operational insights that foster patient-centred care. Omni-HealthData automatically applies data quality rules to ensure that information is trustworthy and allows healthcare payers and providers to quickly gather the information they need to deliver the right care, without requiring caregivers to format data, or learn complex data analytics tools. The application is formatted to allow non-technical users to use familiar tools, such as web browsers and mobile devices, to access information on population health, practice management, care quality and patient safety.
Clinicians and administrators use Omni-HealthData Insights to monitor and improve the quality of hospital care across 180 specific event types and more than 150 core measures. Data from outside systems is incorporated with internal systems data to view the patient journey throughout the various care team touch points. These healthcare-specific analytics enable healthcare providers to obtain valuable cross-organisational insights in a matter of weeks, rather than the months taken for other health management initiatives.
Healthcare providers are engaged in a balancing act between delivering the best care and managing costs, always with an eye on the best patient outcomes. St Luke’s is using Information Builders’ data analytics platform as a progressive way of focusing on quality of care and putting people at the centre of improving the healthcare experience.
The way to derive most value from data is to develop visualisation tools, or dashboards, that allow people with different roles across the health service to use the same combination of data sources to identify key performance indicators, make decisions and take actions.
Information such as number of admissions, busiest periods, number of medical staff required to treat patients, effectiveness of outpatient services, impact of community-based care, effectiveness of patient-directed care, and local, national and international data on outcomes can be integrated to allow healthcare providers to clearly see what they are paying for and the impact on patients.
A GovLab report, Smarter Health: Boosting Analytical Capacity at NHS published with the support of NHS England in February 2017, states, ‘The need for greater analytical capacity within the NHS is evident. Over the past twenty years, the NHS has amassed increasing amounts of data. There is almost universal consensus that, when used ethically and responsibly respecting and protecting confidentiality of all patients, better use of data could bring about more high quality, accessible and effective services and better outcomes. But this requires more than just technology. The NHS needs data analytical talent, which comes in different forms and comes from a variety of disciplines.’
The challenges are great, but as we have seen with our work with St Luke’s University Health Network, when multi-disciplinary teams work together to generate better value from healthcare data, everybody benefits.
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