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Enterprise imaging – radiology positioned to drive new wave
Informed, data-driven decision-making is crucial for delivering quality healthcare and efficiency. However, data in a health facility is often scattered across multiple sites and may not be available as and when needed by clinicians. For example, many have different departmental systems, such as the Radiology Information System (RIS), Picture Archive and Communication System (PACS), Cardiovascular Information System (CVIS), Laboratory Information System (LIS) etc..Data in such systems is dispersed and often inaccessible, due to the presence of multiple IT silos. However, to permit the best use of healthcare resources and deliver the highest quality of care, all of them will need to interact mutually, and do so with the electronic medical record, too. This remains a major challenge. Healthcare data remains fragmented and heterogeneous. Given the sheer volume of imaging data in a hospital, enterprise imaging is being seen as the way to begin address such challenges.
Historical advantages of radiology
Experts generally consider radiology to be one of the best-placed clinical specialities to drive the integration of healthcare data at an enterprise level.
Radiology has some historical advantages for this mission. It has been the early adopter as far as advances in imaging technology and workflow are concerned.
Secondly, most radiology facilities have long since been digital and standards-compliant via protocols such as DICOM (digital imaging and communications in medicine). Given that radiology data is a critical component of a patient’s medical file, RIS and PACS can be appropriate launch pads for reconciling patient information, synchronizing order data and exchanging diagnostic results.
Many radiologists see themselves at the forefront of enterprise imaging by driving the agenda at the hospital management level and engaging with other image producers in their facility.
Need to cope with new demands
However, several issues have to also be taken into consideration.
The current generation of department PACS, in terms of their core architecture and workflow components, dates to the mid-2000s. They had been designed for use by a single physician in the imaging department. As a result, healthcare organizations now have multiple PACS systems. These aim to provide a common standard of care. As care benchmarks evolve, the PACS must cope with ever-new demands.
Given the presence of disparate systems across different departments, an enterprise imaging strategy seeks to harmonize medical imaging across an entire network or organization. Until recently, many healthcare facilities used a ‘forklift’ approach to implement an enterprise PACS design across all departments. However, its limits soon became apparent – especially in terms of lengthy implementation procedures, mission creep and change management, as well as price. Most experts now propose an architectural design which accounts for multi-vendor integration. This is not only cost-effective but also minimizes the impact of radical change management across multiple sites.
Vendor neutral archives
In recent years, vendor neutral archive (VNA) technology has emerged to address challenges posed by proprietary systems. VNA refers to an enterprise data storage and workflow solution. Its goal is to manage and share out large flows of information and address workflow challenges.
Data in a VNA is stored in non-proprietary formats, which permit open interchange. As a result, VNA permits sharing of DICOM and non-DICOM data.
VNA, coupled to the closely-related concept of Universal Viewer, allows healthcare facilities to store, distribute and view any electronically stored images without restrictions.
IHE frameworks
Making such developments even more pertinent is the availability of best practices- and standards-based frameworks from the Integrated Healthcare Enterprise (IHE) – which draws heavily on existing best-practices and processes – for example, the very specific needs of a cardiology or orthopedic department, or the time-critical processes at an emergency department (ED).
IHE frameworks merge customization with a standards-based approach, to allow for rapid integration of systems and sub-systems and accelerate the adoption of information sharing across what were previously silos.
By avoiding information duplication and workflow disruption, IHE also achieves its goals without extra overhead and cost. Indeed, one of the biggest barriers to system integration has consisted of disruption to an established care workflow.
On the other side, the integration of imaging workflow, from ordering through acquisition to reporting and billing, is considered to be a key factor to ensure that those viewing an image remotely are fully cognizant of both its context and presentation.
PACS 3.0
Next-generation PACS systems (or PACS 3.0) are likely to incorporate enterprise workflow/worklist applications, based on VNA, according to a noted US imaging technology expert, Michael Gray.
Plug-ins to the VNA, in Mr. Gray’s view, will feature diagnostic display applications used by different imaging departments, whether or not the images are in DICOM. Non-DICOM applications would deploy a front-end application to create the study from individual images and associate the proper patient and study metadata to the study.
In PACS 3.0, individual physician worklists present a list of specific studies to be consulted, while the underlying workflow launches the most appropriate display application, based on a physician’s pre-defined choices and the study selected from the list. In effect, the enterprise workflow/worklist application becomes the shared entry point for all interpreting physicians in every imaging department while the VNA is the data repository.
Beyond radiology
Enterprise imaging is nevertheless targeted well beyond the requirements of the radiology department alone. A large (and increasing) number of images are generated and interpreted in other departments – for example, from an orthopedic procedure.
There also are certain kinds of images which are not formally considered imaging studies, for example during a dermatology consultation or during the course of wound care treatment. This kind of data is, however, becoming of clinical significance in areas such as personalized medicine, where it is an important part of the medical record of a patient.
Such images need to be shared, sometimes immediately. For example, pre-surgical imaging of a complicated ankle fracture in the emergency department could require transmission to not only an orthopedic surgeon but also of a vascular surgeon – with regard to blood flow in the poorly-vascularized talus. In such a case, instant access to previous images of ankle fractures would clearly enable an emergency department to best interpret new images.
Such circumstances are also apparent in the case of patients who present at different providers, since a second provider is at a disadvantage without access to earlier images.
Enterprise imaging and patient care
Acquiring data from a range of systems in different departments demands a buy from the top echelons of management and a commitment by all concerned members of the healthcare facility.
One argument for such alignment is the role of physicians – to provide the best-available patient care. Good enterprise imaging ensures that this is made possible by providing physicians with the most efficient tools and resources.
Indeed, it is not rare for the patient experience to get lost in the context of technology paradigm shifts or major process overhauls such as enterprise image/data integration. To avoid this and ensure maximum effectiveness, healthcare organization need to closely focus on both the individual patient as well as the complete continuum of care.
From EMRs to image lifecycle management
Drivers of enterprise imaging also come from the side of the electronic medical record. Hospitals have been seeking to stretch the frontiers of the latter by enhancing communication of both data as well as images. Enterprise platforms, once looked at as no more than a storage medium, are now being geared up to give a comprehensive view of a patient’s medical history.
One challenge here is the rapid growth in the volume of imaging data. This is compounded by fragmentation and an ad-hoc approach to image management. As storage requirements have grown, data has also become more distributed in terms of multi-site PACS as well as storage tiers, based on clinical urgency or relevance as well as legal and regulatory requirements.
Benefits from enterprise imaging solutions aim at better control of the lifecycle of a medical image – not least by providing better control over storage capacities and aligning storage costs with operational priorities.
Hospital managers who are renewing or upgrading to a newer PACS system usually seek some degree of future proofing, in the form of scalable solutions and methods to manage a growing corpus of images, many of which are dated. Identifying older images which can be compressed or deleted saves on storage space.
The Enterprise Imaging Program at Cleveland Clinic
The prestigious Cleveland Clinic in Ohio provides a good definition of enterprise imaging strategy as means to address the overarching need “for standardization of clinical image acquisition, management, storage and access.”
The Cleveland Clinic enterprise imaging program incorporates all producers into its clinical image library, which is connected to electronic medical records. In total, this includes images from 11 different healthcare service lines, in addition to radiology images. By the end of 2016, according to one report, 440 different image-generating devices residing outside the radiology service had been integrated.
Commercial solutions
Today’s marketplace already offers a range of enterprise imaging solutions for healthcare enterprises.
Typical examples include diagnostic-quality images provided to clinicians on demand, as well as interfaces with third-party applications to enhance programmes. Some focus on providing a comprehensive view of the healthcare workflow. Others improve image routing and support telemedicine services.
Emergence of artificial intelligence
One of the latest additions in the enterprise imaging arsenal is artificial intelligence (AI).
In recent years, as radiologists have been forced to cope with the explosion in medical imaging procedures and storage capacity, AI seems to be showing early promise. AI is also being used to directly help the care delivery process.
Some medical technology vendors have showcased AI applications integrated with their enterprise imaging platforms. These typically consist of imaging analytics software that assists radiologists diagnose diseases before symptoms occur, and more accurately interpret findings. For example, machine vision AI algorithms pinpoint anomalies within images in real time, alerting radiologists to incidental findings. Physicians could then screen patients further for what may still be asymptomatic conditions – but could develop into a major disease.
No one doubts that radiologists will work increasingly in the future with AI, both to improve the technology itself and to reduce routine, repetitive tasks such as confirming line placements and looking at scans to find nodules. On its part, AI is also likely to become increasingly smarter, to improve efficiency, for example by prioritizing cases, putting thresholds on data acquisition, improving workflow by escalating cases with critical findings to the worklist of a radiologist and providing automatic alerts to both radiologists and other concerned clinicians. Such steps would not only free up resources for additional testing but also improve patient care, thereby making radiologists even more integral in the care management process. These perspectives are of course central to a robust enterprise imaging strategy.
The tele-ICU and robotics – solution for high ICU telemedicine cost ?
Healthcare, like other services, requires getting appropriate expertise to the place where it is needed at the right time. Requirements like these become critical when a patient faces a sudden and unpredictable life-threatening condition. The latter is a near-routine occurrence in a hospital’s intensive care unit (ICU). Still, a host of factors make it impossible for clinicians to be present at every point in the ICU, all the time.
Early acceptance of robotic telepresence
Such shortcomings are sought to be addressed by ICU robots, one of the latest applications in the emerging field of ‘robotic telepresence’. The use of ICU robots, also referred to as teleoperated medical devices, is growing rapidly as a supplement for patient care in the ICU. In its early stages, healthcare providers were overwhelmingly convinced of their potential. In September 2012, for example, a survey of over 10,000 ICU robotic interventions in the journal ‘Telemedicine journal and e-health’ found 100 percent of practitioners considered the robot to improve both patient care and patient satisfaction.
Autonomous, optimised for ICU, hospital environment
ICU robots essentially provide access for physicians and other specialists to implement a variety of medical procedures round-the-clock, while reducing delays for difficult admissions or procedures.
The robots can be pre-programmed to drive on their own around an ICU, or this mode can be overridden and controlled by an individual, located on the premises, at a facility near by or thousands of kilometres away, via a keyboard or joystick.
The robotic sensors are optimized to perform in a hospital environment, enabling the robot to identify and avoid things like IV lines, cables and glass doors.
Plug-and-play for medical devices
The robot itself contains combinations of display types, microphones, speakers and cameras; these have pan-tilt and zoom capabilities, and are powerful and manoeuvrable enough to permit physicians to view fine details and listen to the smallest sounds.
Typical accessories in an ICU robot include an integrated electronic stethoscope to allow physicians to listen remotely to heart and lung sounds using earbuds. However, most Class II medical devices can be plugged into the robot, which streams data back in real time. On the other side, robots can also access digitized medical records of patients.
Recent innovations include a smartphone application, enabling physicians to access the robot’s camera. Another is ‘point and click’ navigation, by virtue of which a user can simply click somewhere on a map of the hospital and the robot gets itself there.
UCLA pioneers ICU robot
The history of ICU robotics dates to 2005, when the University of California at Los Angeles (UCLA) Medical Center became the world’s first hospital to introduce a robot in its neurosurgery intensive care unit under a US military-funded pilot project. The UCLA pilot saw intensivists (clinicians specialized in the care of critically ill patients) monitoring patients from their homes and offices.
The robot was RP-6, developed by California-based InTouch, a company known for its ‘auto-drive’ robotics technology used in defence and public safety. Controlled by a webcam and joystick over a broadband connection, the 65 inch (166 cm) wheeled robot boasted 8-hour runtime from a single charge. Onwards from 2006, InTouch offered hospitals an option to rent the RP-6 for USD 4,000 a month, or buy it outright for USD 120,000. Its earliest customers included Detroit Medical Center and Baltimore’s Sinai Hospital.
The iRobot-InTouch Health Alliance
Meanwhile, another US company iRobot (vendor of the robotic household vacuum, Roomba) set up a Healthcare Robotics division in 2009.
In 2011, iRobot and InTouch Health announced an alliance targeting healthcare. The next year they unveiled the RP-VITA (Remote Presence Virtual + Independent Telemedicine Assistant), a robot which went beyond simply providing remote interactive capability between a clinician and patients to a hugely-enhanced navigation capability, based on sophisticated mapping and obstacle detection and avoidance technologies tailored to a hospital environment. Its aim was to free the clinician for clinical tasks.
FDA clearance
The most revolutionary capability of RP-VITA was autonomous navigation, which was submitted to the the US Food and Drug Administration (FDA) for 510(k) approval. In January 2013, the FDA cleared RP-VITA, making it the first autonomously navigating telepresence robot in healthcare, with clearance for use before, during and after surgery and for cardiovascular, neurological, prenatal and psychological as well as critical care.
Demand driven by range of factors
The key drivers of demand for ICU robots today include time factors (urgency in ICU cases) and access (unavailability of ICU expertise) in remote areas. Both these are compounded by staff shortages.
There are fewer than 6,000 practising intensivists in the United States today and more than 5 million patients admitted to ICUs annually. A few years ago, Teresa Rincon, chair of the Tele-ICU Committee of the Society of Critical Care Medicine (SCCM) noted that the number of intensivists in the US was “not enough for each hospital to have one.” Indeed, it is estimated that only about 37 percent of ICU patients in the US receive intensivist care, although trained intensivists in the ICU correlates to better outcomes and decreased length of stay – both in the ICU and hospital.
The challenge of coma
In terms of urgency, the SCCM notes that up to 58% of emergency department admissions in the US result in an ICU admission.
Following admission, one of the major drivers of demand for ICU robots is coma. The reliable assessment of comatose patients is always critical. A hospital needs to quickly identify clinical status changes in order to determine and implement appropriate interventions.
In January 2017, the prestigious Mayo Clinic published results from a 15-month study of 100 patients, which is reported as the first to look specifically at telemedicine in assessing patients in coma. The results suggest that patients with depressed levels of consciousness can be assessed reliably through telemedicine.
Another urgent complication is delirium. Delirium incidence has been estimated at over 80% in critically ill patients. This is accompanied by a threefold increase in mortality risk, according to an oft-cited study in an April 2004 issue of the ‘Journal of the American Medical Association’.
Clinician availability
Medical emergencies like coma and delirium require the presence of highly qualified clinicians, but as discussed previously, real-life constraints limit their availability round-the-clock.
Access is another crucial consideration. Most hospitals simply lack the patient volume to employ full-time intensivists in fields like neonatology, while their availability is limited for the same reason in remote rural locations.
The tele-ICU
The first attempts to address such challenges were centred on telemedicine or Tele-ICU care, involving continuous surveillance and interactive care by offsite clinicians. This was achieved by video observation of the patient and interrogation of equipment, along with instructions conveyed to other ICU staff.
Although more studies are needed, there is evidence of an association of the Tele-ICU with lower mortality and shorter length of stay in both the ICU as well as the hospital. Another benefit is that a Tele-ICU enables stricter adherence to guidelines.
US leads the way
Europe was a relative latecomer to ICU telemedicine, with a near-total focus on teleconsultation and almost-total reliance on the US experience.
For example, Britain’s NHS refers extensively to US studies on ICU telemedicine in its own Technology Enabled Care Services (TECS) Evidence Database, while the University of Pittsburgh Medical Center has opened a Tele-ICU centre in Italy, which allows US physicians to perform remote consults for Italian ICU patients.
From telemedicine to robotics: business model turned around
In many senses, ICU robotics have been a natural successor to the Tele-ICU, albeit with a significant reversal in its operating model.
The Tele-ICU functions centrally. Rooms are hard-wired with high-resolution cameras and transmit data to a remote command centre staffed by an intensivist (tele-intensivist). The intensivist, who typically covers multiple ICUs, has access to the same clinical information (e.g. vital signs, lab values, notes, physician orders etc.) as the ICU bedside team consisting of nurses, respiratory therapists, non-ICU physician and transfers instructions to them via a two-way communication link. Robotics, driven by advances in technology and mobility, have made it possible for the Tele-ICU care model to become decentralized. The ICU robot is controlled wirelessly by the tele-intensivist, who is freed from a dedicated command centre, and can indeed be just about anywhere. The robot moves from room to room, examining patients based on instructions from the intensivist and interacting as required with staff. The latter interaction is now seen to be far more efficient, since it occurs only after the intensivist has given instructions on the procedures which need to be performed on a patient.
The cost factor
ICU robots seem to also address another major limitation of Tele-ICU, namely cost. Most studies on Tele-ICU have found that though the technologies deployed have been adequate, they have also been much too expensive.
In the US, some hospitals collided with reality, quickly and harshly, “removing tele-ICUs after outcomes failed to justify the costs.” A study in December 2009, in the prestigious ‘Journal of the American Medical Association’ also questioned a key maxim of the Tele-ICU, pointing to evidence that remote monitoring of patients in ICUs was not associated with an overall improvement in the risk of death or length of stay in the ICU or hospital.
Perspectives have been similar in Europe. For example, a Dutch study published in 2011 in the ‘Netherlands Journal of Critical Care’ concluded that hospitals were unlikely to see the “enormous” investment entailed by a tele-ICU as being cost-effective. Concerns about Tele-ICUs were also echoed the same year in Canada, where critical care clinicians, writing in the ‘Journal of Critical Care’ expressed scepticism regarding the ability of a Tele-ICU to address challenges of human resource limitation or even deliver quality care.
The personal touch
While a conclusive answer to the question of cost-effectiveness of OCU robots will require a larger user base, one powerful advantage seems to be the ability to target the eventual subject of the healthcare process, the patient. According to Paul Vespa, a neurosurgeon at UCLA’s David Geffen School of Medicine patients “interact with the robot as if it is a person.”
Steps to realize full potential
Before there is growth in numbers of ICU robots, some of the factors which will need to be addressed have been identified in a ‘Journal of Critical Care’ article in December 2013 by the Center for Comprehensive Access and Delivery Research and Evaluation, Iowa City, US.
These consist of formal training and orientation, identification of roles, responsibilities, and expectations, needs assessment, and administrative support and organization. Failure to adopt these, say the authors, will mean ICU robots may not see their full potential realized.
21st Century hospitals – pressures for transformation
New service and business models are challenging the traditional role of a hospital – as a place where sick people are taken to get better. Instead, a growing body of evidence suggests that the key mission of future hospitals will be to help people to avoid falling ill, and to manage those that do in fundamentally different ways than at present. Such processes are principally driven by economic pressures and the promise of new technologies. However, patients are also playing a major role.
Patients more proactive
It has indeed been apparent for some time that patients are far less passive than they were in the past. In Britain, a study by the King’s Fund think-tank found patients wished to be far more involved in healthcare decisions. In addition, the study reported that patient satisfaction depended not just on medical outcomes, but also on being treated with dignity and respect.
Emerging technologies are seen as one way to enhance the patient experience, and several popular apps show how rapidly patients have moved to centre-stage. In the US, Heal, a smartphone app, lets patients search for physicians in a manner similar to Uber’s connecting passengers to drivers. Zocdoc, another tool for finding doctors, has added an artificial intelligence-powered Insurance Checker feature which lets patients select and verify insurance information as they are booking appointments. An app called Welloh goes beyond doctors to give users information about hospitals, pharmacies, care centres and other facilities. Clinical trials are also opening up to volunteers, thanks to an app called TrialReach, which helps patients find open clinical trials for specific medical conditions.
These new health access paradigms resonate strongly with younger patients. According to a report from Salesforce, over 70 percent want their physicians to adopt mobile health applications.
Apple integrating health apps
Evidence of the opportunities arising from enhanced patient participation comes from Apple, which plans to bring the current clutter of healthcare apps under one roof. Its new Health Records feature will allow users to see their records of allergies, immunizations, lab results, medications and other conditions in a single window and send notifications when any data is updated.
Big Data
One of the most promising and best known tools in the emerging technology arsenal is computing giant IBM’s Watson, which deploys artificial intelligence (AI) to collect and interpret vast amounts of data from medical literature in order to advise on best treatment options. Scores of other tools provide personalized treatment plans for cancer patients using the genetic background of their tumours, accompanied by analysis from tens of thousands of other, similar cases.
These kinds of innovations count on assimilating and interpreting what has come to be known as Big Data. The sources for this data, whose volume continues to grow by leaps and bounds, are many. They include clinical studies, prescriptions, radiological images and a host of other healthcare information.
The Internet of Things
One new source of data is from the Internet of Things. Connected medical devices such as insulin pumps and pacemakers pick up signals and automatically transmit information to networked computers, which allow physicians (and patients) to perform real-time monitoring.
An array of wearable devices to track vital signs are another fast-growing source of medical data. On an individual basis, this may not amount to much. However, when the data is provided by millions of users, its size becomes staggering, as does its potential for providing insights.
Cloud computing
Such a burgeoning mass of data is being generated asynchronously, processed and stored by different machines on multiple platforms. Making it usable is hardly simple.
One promising answer to such a challenge lies in cloud computing technology, which has dramatically reduced the cost of data storage, as well as the time required to process and transfer the data to multiple users at different locations. For patients needing to visit a lot of specialists, the accessibility of their data from a variety of locations can be indispensable.
The Electronic Health Record
One of cloud computing’s biggest areas of impact may be the electronic health record (EHR), one of whose goals was in fact to address the above challenge – patient data access in real time by different specialists.
The EHR has generally failed to meet expectations (and over-expectations). In both Europe and the US, the EHR’s key technical/operational limitation was that clinical and financial data could not be easily shared and exchanged among providers – as many had assumed or otherwise hoped for. In the US, EHRs have generally also failed to meet levels of reporting that support the ‘meaningful use’ requirements of pay-for-performance programmes.
Cloud computing seems likely to give a new lease of life to the EHR. Server-based EHRs always run the risk of system failure, which would prevent access to critical patient data until the server has been restored. Such a scenario does not concern cloud-based EHRs. In addition, cloud services are encrypted and provide security. Cloud-based EHRs also reduce entry barriers to adoption by transferring responsibility for confidential patient information to specialized vendors.
Design and hospital re-purposing
The impact of such developments are reaching into the very design of a hospital. Christopher Shaw, Chair of a professional organization called Architects for Health and founder of the design firm Medical Architecture, believes there is a growing mismatch between the physical infrastructure of a hospital and the nature of activities expected to be required over the coming decades.
One key question here is the future of hospital buildings – whether to renovate and incrementally redesign structures or start afresh. Indeed, even as popular imagination associates future hospitals with robotic doctors, another equally beguiling scenario consists of individualized medicine, extending to some forms of surgery, carried out at home.
Hub-and-spoke models
The reality may lie in between, at least in the foreseeable future. One of the most likely scenarios might be a hub-and-spoke hospital model. Its inside tier would consist of academic medical centres serving larger populations and focused on acute care. The middle tier would be an intermediate-care hospital, located in smaller cities or larger towns and providing longer-term rehabilitation and nursing support. The outer tier would be comprised of polyclinics for outpatient diagnostics and elective care, referred from primary care physicians. At the periphery would be the patient’s home, with telemedicine treatment, and possibly some form of tele-surgery assisted by paramedical professionals on the scene. Some of the latter may well be robots.
Telehealth
After many false starts, telehealth technology is now on the edge of take-off – helping allocate care to patients more efficiently, by eliminating the need to visit hospitals, when they do not have a need to access concentrated multi-disciplinary expertise.
Telehealth is also seen as a means to bring patients back more quickly to their homes. Indeed, there is a considerable body of evidence which suggests that the sooner patients begin recovery at home, the more quickly they heal.
Telehealth is not only being pushed by technology but also pulled by economics. In the US, for example, healthcare providers of diabetic patient care have to contend with value-based measures. As a result, they are becoming increasingly dependent on real-time data from remote glucose monitors. Telehealth allows patients to be more engaged, and participate with physicians in ensuring better outcomes, by adhering to insulin or other medications.
Emerging models – examples
The challenge facing the emerging healthcare model lies in the best way to integrate resources, delivery and support mechanisms, and the need to avoid duplication. However, there are encouraging signs from several parts of the world.
In the US, Westchester Medical Center Health Network (WMC Health), is an example of the emerging hub-and-spoke hospital model. The core of the system consists of a 1,500-bed facility headquartered in Valhalla, New York, which is the only facility for complex interventions and procedures. Buttressing this are six (intermediate) hospitals, as well as several polyclinics and medical campuses. The system covers a population of more than 3 million people spread over 15,000 square kilometres.
In Europe, there are several efforts to redefine hospital design. In a variation of hub and spoke, Guy’s Hospital at London has developed its cancer centre as a stack of ‘villages’, one atop another, with each providing a different service (radiotherapy, chemotherapy, etc.).
Certain hospitals have sought to move in the opposite direction, bringing a full range of services to patients in one room or area. In Veldhoven, the Netherlands, a new Woman-Mother-Child Center at Maxima Hospital provides prenatal, delivery, postnatal and breastfeeding support services from one room.
UMC+ in Maastricht, NL
Some of the most radical efforts to address the redefinition of the hospital are being explored in the Netherlands, at Medical University Centre+ (UMC+) in Maastricht.
In late 2009, the departments of Dermatology and Orthopedics at UMC+ started out on separate tracks of what is called ‘design thinking’. Each department independently developed and implemented new care and financing systems, closely adapted to what they saw as the real needs of their patients, and combining specialities, which had been traditionally separated.
The key mission at UMC+ is to avoid pushing strategy down individual departments, which have highly specific patient groups, processes and technologies, and instead build strategy bottom up, involving inputs from across the staffing chain.
Nevertheless, the aim of design thinking is to also generate organizational change. Over time, several other departments began applying the methodologies pioneered by Dermatology and Orthopedics, creating a new hospital healthcare model.
Over time, the UMC+ model is transforming healthcare focused on rehabilitation, to preventive public health and development. The shift has also changed the role of the Board. Directors no longer set out strategies, but make communication possible between different departments. The Board aims to ensure that different departments do not seek to reinvent the wheel, and instead continuously develop and implement internal best practices.
The challenge of demographics
Nevertheless, many challenges still lie ahead. While Internet- and smartphone-friendly millennials are clearly going to benefit from new hospital care models, the bulk of hospital and healthcare needs for the next decade or two lie in the elderly. According to a Partners HealthCare study in 2016, few seniors obtain information or accomplish healthcare-related tasks online. Only 16 percent of seniors said they used the Internet to obtain health information, while just 7 percent contacted physicians online.