A look at how smart technologies save more lives and improve patients’ experience.
by Raymond Kang
Come 2030, Asia will be home to more than 60 per cent of the total population aged 65 years or older worldwide.1 Among the changes in the Asia-Pacific healthcare industry in response to an aging population is the move towards providing coordinated continuum of care — which integrates prevention, diagnosis, consulting, nursing and rehabilitation — for better management of chronic diseases.
Another transition is the emphasis on patient-centric care. Medical professionals are increasingly more focused on patient outcomes rather than measuring quantitative performance. This brings about new challenges such as increasing patient satisfaction, ensuring compliance, in addition to keeping abreast with technological advances in disease treatment.
With all the buzz around smart technology and Artificial Intelligence (AI), what do these innovations mean for the healthcare industry? How could the hospital physical infrastructure and built environment benefit from AI-enabled technologies? Could patients benefit from connected technologies without comprising data protection?
Making Sense of Aggregated Data
The healing experience begins when a patient enters a medical facility. In the era of electronic medical records and bedside infotainment, next generation smart hospitals come with unique characteristics to allow building occupants – doctor, nurses and patients – interact with their environment.
It takes a complex integration of various technologies for this to happen. The ability to have systems “speak” to one another while absorbing and reacting to data is essential. Disparate clinical, IT and facility technologies such as heating, ventilation, cooling, energy, fire prevention, nurse call, patient wards, operating theaters, security, and telephony must work together for smart hospitals to be instruments of care.
But integration for integration’s sake – without due consideration to the needs of the facility – is meaningless. Doing so could lead to alert fatigue, poor workflow and unnecessary complexity for nurses, doctors, and patients. If the collected data is not interpreted in the right context for proactive and meaningful action, they merely create noise, with no coherence or identifiable value.
Given today’s focus on quality patient care, smart hospitals need to meet some immediate needs to address productivity through better time management. For instance, nurses could spend less time finding equipment and more time with patients. Another improvement could be to ensure operating theaters are readily available, thereby improving efficiency and ease of use.
By integrating building data and systems, we could create a streamlined and seamless response to a patient’s needs. Let’s say there is a code-blue event in a patient’s room which in turn triggers a sequence of actions on both the hospital staff and the infrastructure. We could now ensure that the bed rises appropriately, the blinds close, the lights turn on, the temperature is optimized, the location-system finds the doctor, the crash-cart is made available and – in short – everything is ready to resuscitate the patient. In the event of an operation, the integrated system would then prepare the operating theater and the elevators for speedy transfer of the patient.
Such an integrated emergency response system has produced dramatic results in real life. Deployed in a Southeast Asia-based medical facility, the system has seen a threefold increase in the survival rate of patients with cardiac arrest. Comprising of ICU doctors, a nurse and a respiratory therapist, the code blue team carries special access cards for intercepting elevators and bypassing unnecessary floors to reach a patient needing resuscitation in under 3 minutes. Furthermore, the integrated system also enhanced the monitoring of patients who show signs of deterioration up to 6 to 8 hours before they go into cardiac arrest, allowing medical help to get to them faster and improving the chance of survival.
AI in Healthcare
AI is fast becoming a part of our healthcare ecosystem, as highlighted by PwC.2 Some AI-enabled transformations include early detection of diseases such as cancer; consumer health apps that encourage individuals to lead proactive healthier lifestyles; and the use of predictive analytics to support clinical decision-making.
The healthcare institutions in Singapore are just getting started with harnessing AI. Several AI projects have been shortlisted3 by the Ministry of Health to transform the delivery of healthcare management of chronic diseases such as diabetes, hypertension and high cholesterol. A recent survey4 showed that our healthcare professionals were trailing behind their contemporaries in Saudi Arabia and China in the use of AI to improve diagnostic accuracy; with AI technologies mostly employed for administrative tasks such as staffing and scheduling patient appointments in local facilities.
In the built environment, machine learning (ML) is an application of AI that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. It’s based on the idea that we can give machines access to data, and they can use that data to learn for themselves. Many consumers will have their first interaction with AI in the built environment through voice commands given to a smart home device such as those made by Amazon, Google or Apple.
In smart hospitals, ML could be applied in energy management and predictive energy optimization. Facilities managers could leverage internal and external data to benchmark building performance, monitor building equipment, ensure occupant comfort and forecast operational budgets. Predictive analytics could be applied to manage heating, ventilation, air conditioning (HVAC), lighting, appliances and devices for fault detection and diagnosis, so potential issues could be addressed before it escalates.
ML is also fundamental to biometric recognition-based systems that control physical access. For instance, hospitals could use cameras equipped with modern AI algorithms to identify staff with very high accuracy. The combination of facial recognition and the traditional card access provides a higher level of assurance for secure access to sensitive areas, while minimizing disruption for the users.
What Should Your Smart Hospital Be?
It is critical to begin with the end in mind. Be it building a new medical facility or retrofitting an existing one, all departments of the hospital must be considered in technology-related initiatives. Some considerations could be: What are the real needs of patients? What would help doctors and nurses perform their duties better? How would processes be optimized?
An industry survey5 revealed that front-end technologies were deemed as more important functions of smart hospitals. An overwhelming majority of hospital administrators, doctors, nurses, and patients believed that front-end applications and services (such as online registration, diagnostic services, patient care and treatment) were the most important functions of smart hospitals.
However, without the support of unified and stable backend platforms – such as infrastructure, process and data – the front-end applications would be isolated, disconnected and unreliable. If too much attention is focused on front-end applications, while neglecting back-end platforms, then smart hospitals would face problems from the onset which would exacerbate with time.
A smart hospital should be built with an accurate understating of the needs of its medical staff and patients – but, that’s not always the case. The same survey showed a gap between what hospital administrators perceived to be the needs of patients, doctors, and nurses, and the needs that these groups expressed. For instance, environmental comfort and order, which are generally the priorities of doctors and nurses, are not highly ranked by hospital administrators. Such a gap in perceived and actual needs may result in insufficient investment in addressing the true needs of the users.
Building-Wide Systems Integration Is Imperative
There is no one-size-fits-all solution for an effective smart hospital. For such facilities to work, an enterprise-wide perspective is imperative to manage the planning, design, supply, installation, integration, commissioning and services of systems and clinical solutions like nurse calls and supporting infrastructure. At the core is the delivery of patient-centered care through strategic integration of these building subsystems and devices.
Successful integration requires systems convergence at two levels. At the physical level, convergence ensures different systems such as networks and severs, share the same infrastructure. At the logical level, convergence ensures systems exchange data in the same operational process or workflow. The outcome is an environment where each connected device becomes “self-aware,” or “talks” with other devices by sharing data and acts or adjusts based on what it learns. Security and privacy of the data is protected since all data is encrypted at rest and in transit using industry-leading protocols, and the platform, by an access control system.
Unfortunately, the construction industry has yet to kept pace with advances in technology; while IT integrators often lack expertise in construction such as core building systems, job site coordination or construction scheduling. Different systems are installed in silos and by different subcontractors. Such fragmentation hinders the delivery of optimized environments to meet the needs of smart hospitals.
Finding the right systems integrator partner is key to realizing the full potential of smart hospitals. Such self-conscious, self-healing buildings can be instruments of care if the facilities, business, security and clinical systems are integrated in the right way. [APBN]
About the Author
Raymond Kang, Director, Building Technologies and Solutions, Singapore, Johnson Controls