Technology is at the centre of the journey from integration to population health and precision medicine. Some organisations are making the leap from integration to full interoperability while others are well on their way to precision medicine.
1. Run to the cloud!
Eric Schmidt, former Google CEO opened HIMSS18 this year sending a clear message – “run to the cloud!”
The case for healthcare organisations to move from private data centres to the cloud has become a business imperative to support next generation technology for precision medicine and population health. With advances in security and compliance, the cloud will enable healthcare to take advantage of new levels of infrastructure agility and scale, enhanced lifecycle management and an easier interoperability with the digital healthcare ecosystem, including care partners and consumers.
One of Orion Health’s speakers at HIMSS Steve Crusenberry, SVP SaaS Product and Cloud Operations, shared his advice to organisations considering a move to the cloud:
- Evaluate your success criteria: Is it to save costs, technology agility, enhanced organisation capabilities? Understand the financial costs of migration and the total value to the business.
- Understand your capability: Do you have experience on staff? What systems or applications can be moved quickly to the cloud? What resources can you devote to the journey?
- Identify timing and approach: When should you start new initiatives in the cloud? Do you start with a one-cloud or multi-cloud approach?
2. The Power of Prediction
Every year in the U.S alone, a third of expenditure, more than $1 trillion is wasted in healthcare on costly administration and avoidable hospital readmissions. With the pressure to portray real value and results mounting for providing care, healthcare organisations are altering their approach to allow technology to play a more integral role. Data analysis combined with the rise of machine learning can help minimise this wastage with predictive analysis. It was the talk of the conference, yet few have tangible examples of machine learning and predictive analysis in play.
Orion Health announced its new machine learning service, Amadeus Intelligence to help the health sector reduce operating costs and improve patient care. Led by ground-breaking research by Precision Driven Health (PDH), a New Zealand partnership between Orion Health, University of Auckland and Waitemata District Health Board (Hospitals), the company is exploring meaningful ways to minimise wastage in the healthcare sector and help clinicians make more accurate decisions at the point of care.
One example where predictive analysis could have an immediate impact on costs for healthcare organisations is readmission rates. With 17.6% of hospitalisations in the U.S. resulting in a re-hospitalisation within 30 days, an estimated 76% of those re-hospitalisations are potentially avoidable, costing $30 billion. PDH research used a breadth of data types and applied machine learning models to achieve greater predictive accuracy, calculating potential savings four times higher than current predictive models. By using machine learning techniques, organisations can expect larger reductions in avoidable readmission rates, achieved in a far more cost-effective manner.
While still in its infancy, data analysis combined with the move to the cloud and the rise of machine learning, will provide meaningful clinical and financial insights to accelerate precision medicine, improve personalised treatments and maximise cost effectiveness of interventions.
3. Integration is still a headache for healthcare organisations
While the last decade has been about digitising healthcare organisations and Electronic Health Records, many are still challenged with bringing data together from multiple systems, devices and facilities. With the massive increase in the amount and sources of data that is becoming available, this puts heavy demand on integration. Even Schmidt admitted the data and interconnections were still lacking.
Today’s lack of interoperability is most evident in hospitals that are still using paper notes. It ultimately compromises patient safety and adds to the wastage in the healthcare system, but it’s a very difficult problem to resolve. Different systems need to talk and connect to each other – exchanging data, within the correct context is critical. Without the correct context, medical professionals can overlook information.
Orion Health has been in the integration space for many years with the Rhapsody Integration Engine. Recently announced as a cloud offering as well, Rhapsody as a Service achieves rapid interoperability between healthcare systems in a cloud environment, enabling connected solutions in less time and at a lower cost. It eliminates or reduces expensive hardware and maintenance of on premise systems, saving costs and time. It also enables fast deployments, and services in the cloud can recover from failures automatically therefore minimising downtime. Rhapsody as a Service joins the Amadeus SaaS Platform, Analytics and Population Health Management systems in the cloud.
Today most data sharing is based on sharing some data fields with contextual integration or sharing view-only document summaries. Industry standards have been developed to make data sharing less clumsy but a non-uniform approach to the application of these standards remains a hurdle for interoperability.
Interoperability is crucial to deliver the business capabilities that we need in healthcare – inside and outside healthcare organisations – such as an electronic health record, automatic alerts and notifications by text, seamlessly transferring information between and within care settings, delivering remote care, analysing data for population health management and resource optimisation.
4. FHIR will accelerate innovation
FHIR® expert and Orion Health Product Strategist Dr David Hay spoke to a full house at HIMSS18 about how ‘ecosystem’ thinking, based on FHIR or Fast Healthcare Interoperability Resources APIs, has the potential to accelerate innovation in the health IT space. Dr Hay’s blog explains that ‘ecosystem’ thinking gives us the ability to achieve a truly open healthcare data system, by enabling healthcare information to be made available where and when it is needed.
FHIR is a healthcare IT standard that will help to improve the day to day running of community medical practices and hospitals. FHIR can contribute to improved patient care by providing timely access to their electronic health record. It is one of the next generation HL7® standards in healthcare data integration, and is focused on decreasing interoperability costs and unlocking innovation in healthcare. FHIR represents a major standard upgrade that will increase access to health information and support ambitious plans for an app store for the health sector. FHIR aims to speed application development and interoperability, plus boost information sharing in healthcare, especially on mobile platforms.
David said, “Electronic health information is made accessible through the collection and manipulation of data, but it has also created complexity. This is evident with the amount and type of data that is available, the growing number of sources where it is captured and stored, and the more specialised ways in which it is being used. There is the emergence of personalised medicine, where advanced analytics can be applied to this information – including the person’s genome – giving management advice that is tailored to the individual rather than what has previously worked within a similar population. Following that advice often requires access to highly specialised services, but finding them can be a challenge.”
For more information read the blog here
5. We’re just at the beginning
Technological breakthroughs are starting to solve some of the real issues of healthcare. From virtual doctor appointments to smarter hospitals, the tech industry is resolving problems using massive datasets, bots and machine learning.
Technology is at the centre of the journey from integration to population health and precision medicine. Some organisations are making the leap from integration to full interoperability while others are well on their way to precision medicine. Advancements in the cloud are enabling secure real-time access to patient information, predictive analytics are integrating within provider’s workflows, and machine learning is making headway into surgery and payment pathways. It is only just beginning.