How informatics supports increased productivity, better outcomes and improved experiences in healthcare

One thing that all healthcare stakeholders agree on is that our global health systems are near breaking point. The aging population and increasing incidence of chronic disease has led to an unsustainable cost explosion, and it is unsurprising that the pressure is mounting.

The statistics make difficult and conclusive reading. Global healthcare spending is projected to increase at an annual rate of 5.4% in 2017–2022, from USD $7.724 trillion to USD $10.059 trillion [1]. Next to rising demand for healthcare, this is exasperated by high levels of clinical waste and unexplained variance in treatment and outcomes. It is estimated that $3 trillion goes to waste every year in healthcare with the USA alone accounting for $1 trillion [2]. Adding to the challenge is worryingly high staff burnout rates, administrative complexity and excessive and widely varying prices. 

Transforming healthcare delivery and financing has gone from important to essential

If you have recently received medical treatment or supported a family member or friend to engage the healthcare system, you will probably have experienced this wastefulness first-hand. Repeat procedures, gaps in information and long waiting times tell the story of overburdened and under-resourced hospitals. 

You may also have noticed that our healthcare systems tend to place their focus on acute and emergency episodes. Advanced prevention and disease management strategies are struggling to make inroads. Add access constraints and increasingly unhealthy lifestyles to this mix, and you will understand that we are in the midst of a global crisis.

As a priority, the global healthcare community is urgently seeking strategies and solutions to rebalance the status quo. And despite these challenges, we have many reasons to be optimistic. Day-by-day, the healthcare community is collaborating to transition away from siloed and wasteful care delivery to more patient-centric and productive healthcare. But we still need to act faster!

The answer lies in value-based care

First originating as a framework by Harvard Economist Michael Porter, value-based care is a delivery framework to improve health outcomes at lower cost. It focuses on what patients value and allocates resources according to the health outcomes delivered by the system. Therefore, when put into practice, to drive efficiency and raise quality standards, value-based care attaches incentives and payments according to results, not system workload. 

As a result, it encourages elements like quality, safety, the patient experience and their participation in decisions to be prioritized by the care team. Most importantly, value-based care seeks to avoid unnecessary diagnostic and therapeutic interventions. With the right execution, it supports cost-effective care delivery while still being compliant with evidence-based guidelines. 

Compare this with the traditional fee-for-service model where every time you see a doctor or undergo a medical test or procedure, you (or your insurance provider) pay for every step in the process. This payment (or reward) happens regardless of whether a diagnosis or procedure is successful or not, and whether or not the steps taken are high-quality or even considered as best practice. In other words, traditional healthcare is not necessarily working in the best interests of the patient.

Value-based care seeks to address this contradiction by reorganizing healthcare around patient values, not volumes. However, we should not overlook that access to care is also an important part of the equation. The Philips Future Health Index accounts for this in a “value measure” [3] that assesses care delivery against the Quadruple Aim: better patient outcomes, improved patient experience, improved staff satisfaction, and a lower cost of care.

Breakthrough technologies supporting value-based care

Meantime, aside from accelerating value-based care, health informatics and digital innovation is enabling vital data aggregation and analytics that is literally changing the ways in which healthcare is accessed and experienced by patient and staff.

Artificial Intelligence (AI) is an undeniably exciting trend. Whilst I believe we are still a number of years away from unstructured or ‘’true” AI in healthcare, AI applications are already helping clinicians and health systems to quantify and make sense of more data than ever before. In this respect, I am convinced that – in tandem with health informatics platforms – AI will continue to make healthcare more personal, predictive and precise.

Here is a brief summary of the informatics and AI-enabled health technology solutions that I am so optimistic about:

• Personal health coaching – thanks to increasingly sophisticated medical devices and sensors linked to health apps, patients can better understand and proactively manage their own health and wellness. There have been impressive advances since the first generation pedometers and heart rate monitors that generated so much buzz when they first came to market. Providers can now support behavioral and clinical-grade insights across a number of challenging health spaces, including diabetes, heart health and elderly care. As a case study, the Philips DreamMapper provides daily feedback and coaching to sleep apnea patients. The solution and app supports users to track and improve their therapy progress over time. Moreover, across its global user base, Philips has collected over 2.7 billion nights of sleep data for analysis in the cloud [4]. As valuable population health data, this helps stratify and continuously improve Philips innovation in sleep and respiratory care. As the technology continues to improve, I expect this kind of delivery and access model to proliferate.

• Precision diagnosis and treatments – access to affordable genome profiling is another trend bringing positive disruption as health systems challenge themselves to deliver first-time right precision diagnosis and treatments. Take cancer diagnosis as an example: clinicians can build a “complete view” of the patient by integrating a patient’s genetic information alongside the patient’s history and data from multiple modalities and specialisms like image acquisition, digital pathology and immunology. Whilst supporting more accurate diagnosis and increased collaboration between clinical departments and care teams, this kind of oncology informatics also aids research in personalized treatment selection by honing algorithms on specific disease states. It is a promising field, but to help make this kind of healthcare more inclusive, we must ensure that research teams have access to large volumes of high quality and secure patient data. 
  
  
• Predictive monitoring – data aggregation and analytics is another key innovation theme in high acuity patient monitoring. For example, in high dependency wards, nursing staff can find themselves as overburdened as they track patient progress against a number of vital metrics – blood pressure, heart rate, temperature and so on. With algorithmic analysis, solutions like the Philips IntelliVue Guardian can help to combine, identify and predict deviations in a patient's vital signs. Verifying the accuracy of the trend, the solution then translates this information to an early warning score that notifies caregivers in the event of concerning deterioration. A 2017 solution study showed a reduction in severe adverse effects by 35%, cardiac arrest by 86% and ICU readmission rate by 24%[5] in the general ward.
  
  
• Telehealth – as the underlying technology supporting “hospital to home” and care delivery in lower cost settings, telehealth is a fast growing field helping to expand access to high quality and specialized healthcare. Relying on powerful digital communications networks and remote monitoring capabilities, telehealth is also transforming care inside the hospital. Take the eICU where centralized patient monitoring and care coordination can raise quality and efficiency for the most vulnerable patients. Meantime, in ambulatory settings, secondary prevention is another promising telehealth innovation area. For example, monitoring and treating at-risk patients at home – like those living with multiple morbidities. Typically, this patient subset accounts for disproportionate costs and drain system resources, but remote monitoring and telehealth consultations can help patients better manage their condition. This can reduce emergency episodes and limit hospitalizations in a more proactive and sustainable approach.

Key barriers and enablers for value-based care

Given this potential, I firmly believe that we can innovate ourselves out of the current crisis and towards a more promising global outlook for healthcare. But we should not lose sight of the fact that there is still a huge amount of work to be done to bring seamless digital solutions and value-based care to reality. 

In spite of a growing pool of pilots and visible pockets of excellence, health systems are proceeding with caution. A recent survey of 364 healthcare executives in the United States reported that just one third are experimenting with some form of value-based reimbursements [6]. 

If we are to really accelerate and bring scale to value-based care, there are clear priorities to tackle:

1. Clearly defined outcomes and measurement standards – the industry needs to settle on clear definitions for patient-reported outcomes, and also agree on common protocols for measuring performance to then identify and eliminate variance. This is a baseline requirement. Pre-competitive agreements between all healthcare stakeholders will help to enable the automatic capture of outcome data from multiple sources, whilst also boosting the sharing of data among systems. This will allow differentiated reimbursement according to quality to be administered with consistency and transparency.
   
   
2. Open data standards – interoperable and secure data platforms are the basis for high impact and scalable health informatics, also fueling further innovation and research. The transparent capture and reporting of data between systems, processes and stakeholders is vital for value-based care. Moreover, the challenge and stakes are so significant that it requires a full-ecosystem approach. To accelerate adoption, open and vendor-neutral digital networks must become the rule, not the exception.
   
   
3. Reimbursements reform – one of the most significant barriers to value-based care is that an incremental move away from the fee-for-service model that providers, clinicians and system payers have come to rely on is required. Given the unmet potential and pressing need to make healthcare more sustainable, we must seek out and experiment with innovative payments that share the risk and align incentives across care pathways and providers. Health insurance providers and government payers have a major role to play in expanding value-based care from pilot projects into an operational model that can be quickly scaled up. 

Ultimately, the widespread adoption of value-based care requires openness, trust and strong collaboration and partnerships between all healthcare stakeholder groups. Technology and IT deployments, legal and regulatory frameworks, clinical skills, training and payment reform must each be managed in a comprehensive and progressive approach to healthcare reform. It is a demanding and long road ahead, but it is vital that we seize the opportunity before us. I am convinced that we have what it takes!

[1] https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-hc-outlook-2019.pdf 

[2] Sahni, N R, et al. How the U.S. Can Reduce Waste in Health Care Spending by $1 Trillion. Harvard Business Review. October 13, 2015. https://hbr.org/2015/10/how-the-u-s-can-reduce-waste-in-health-care-spending-by-1-trillion 

[3] https://www.philips.com/a-w/about/news/future-health-index/value-measure.html 

[4] Based on snapshot data from Philips Encore Anywhere database. Total nights of sleep therapy data stored within Encore Anywhere for US companies  = 2,791,991,652 as of January 2018

[5] Subbe et al. Effect of an automated notification system for deteriorating ward patients on clinical outcomes. Critical Care (2017)

[6] https://www.washingtonpost.com/sf/brand-connect/philips/transforming-healthcare/