Law & Governance

Law & Governance 14(10) February 2011

Rethinking Our Approach to Disease Management: Technology and Information Flow Considerations

Zun Lee and Myrna Francis


[This article was originally published in Electronic Healthcare 9(4)]

Health information technology has been moving away from its provider-centric origins and toward sharing timely and relevant information along the care continuum in a collaborative manner. Disease Management (DM) information solutions are receiving increased attention because of their role in connecting care teams and patients to produce better care and outcomes and a more efficient use of resources. To achieve these improvements, we need an effective and efficient way for sharing information among increasingly mobile patients and clinicians that enables DM and fundamentally changes how care is managed. This article proposes three principles to guide decision makers in choosing a health information approach that will result in improved workflow across the continuum of care. The first involves a truly integrated information platform, encompassing clinical as well as administrative data to provide a full picture of health system performance and operations, without complicating the day-to-day workflow of clinicians. The second involves tailoring the solution to the needs of an increasingly mobile clinician workforce. Clinicians need the "right" information at the right time in the right context; making all information for all patients available all the time is counterproductive for successful DM enablement. Similarly, alerts must be selected judiciously; too many leads to their being ignored. The third involves "smart" use of smartphones to optimize an increasingly mobile workflow. Embedding voice, SMS, chat tools and other social media capabilities into the clinical workflow can make the Smartphone a true mobile unified communications hub and significantly enhance the time value of information.

Executive Summary

Health information technology (HIT) has traditionally been provider-centric. The push toward unlocking content from siloed repositories was primarily driven by the information needs of acute care providers and managers. However, the old ways are being superseded by a movement toward sharing health information along the care continuum in a timely, accurate, relevant and collaborative manner. Among a variety of cross-continuum HIT initiatives, Disease Management (DM) solutions are receiving increasing attention because of their role in connecting patients and care teams to achieve better, more proactive care, better outcomes and more efficient use of resources.

What is still missing, however, is an effective and efficient way for the right information to be shared among increasingly mobile patients and clinicians to enable DM and fundamentally change how care is managed. This article proposes three guiding principles when considering the optimal deployment and integration of DM and other cross-continuum solutions:

  • Minimizing the implementation of multiple disparate solutions for cross-continuum initiatives by leveraging a single platform wherever possible
  • Tailoring the amount and type of clinical information needed at a given point of care and with the appropriate context
  • Taking full advantage of mHealth (mobile health) device and application capabilities to maximize opportunities for new workflows and care collaboration

In our view, these principles will serve as a valuable guide for decision makers in choosing their HIT approach and solutions and will result in better meeting the workflow demands across the care continuum.

Disease Management – Where Are We?

The burden of chronic disease is rapidly becoming a global focus for health systems as well as for mainstream media. The increasing incidence and prevalence of chronic diseases illustrate the reason for this concern. More than 50% of North American adults have at least one chronic disease. Chronic disease is related to 80% of family practice visits and is the cause of 60% of hospitalizations. More than two thirds of all medical costs can be attributed to chronic disease (Rapoport et al. 2004). The prevention and management of chronic disease is beginning to define the healthcare challenge in the twenty-first century.

The concept of DM has been discussed for several decades (Bodenheimer 1999; Bodenheimer et al. 2002). A number of DM models have now been established as the gold standard throughout literature and practice (Lewis and Dixon 2004). The Chronic Care Model (CCM), also known as the Wagner Model, has become popular in the United States (US) and internationally (National Coalition on Healthcare 2002). It is rooted in the premise that improved outcomes for DM are established through the interaction between informed, activated patients and a prepared, proactive care team. Several supporting components of the CCM sustain this interaction: Self-management support, delivery system design, and decision support and clinical information systems. In Canada, the Expanded Chronic Care Model (ECCM) has gained significant traction (Barr et al. 2003). The ECCM expands the CCM to stress the importance of prevention and social determinants of health in influencing health outcomes.

Although several jurisdictions have spearheaded DM efforts, implementation is still in its early stages in most geographies, and the focus is often limited to a select range of conditions, known as the "Big Five" – asthma, diabetes, chronic obstructive pulmonary disease (COPD), cardiovascular disease and arthritis. Given the clinical and economic challenges and benefits, there is clearly a need for more widespread adoption of DM throughout our healthcare systems. So why has this not occurred?

Even though many local and regional DM success stories now exist, implementing DM on a broader scale is a much more complex endeavour that requires coordination between policy, operations, IT and diverse stakeholder groups.

By far the biggest barrier to more pervasive adoption of DM has been the continued fragmentation of operations and information technology across health systems. Our ability to share health information across the care continuum is still limited, at best. After several years of ongoing structural reform, healthcare delivery is still fragmented along the fault lines of primary care, home and community care, acute care and other care settings (MacKinnon and MacDonald 2000). In addition, health systems are saddled with legacy IT environments that largely mirror the fragmented operational landscape. Most health IT applications and data models were built as "point solutions," designed to address the episodic care needs of provider institutions, but not capture the longitudinal nature of the patient journey across the care continuum.

Operational and IT Fragmentation Persists

Many initiatives are under way to consolidate health information currently sitting in disparate systems and to make it seamlessly accessible via portals and other technologies. Better remote monitoring solutions make the provision of real-time data exchange between patients and their care teams a tangible reality. Mobile device technology is increasingly enabling patients and providers to action care interventions "on the go."

However, many health systems have not yet taken full advantage of these capabilities to drive large-scale implementation of DM. The pace of automating and integrating cross-continuum workflows with health IT remains too slow to enable optimal care coordination. A recent US health information technology survey revealed that only 23% of respondents consider their organizations' health information systems fully integrated and interoperable with other external IT applications, with only the same percentage of organizations having gone fully paperless to support care management (Carneal et al. 2010).

Our collective thinking around health IT systems integration has certainly become more "big picture." However, while we are now moving toward integrating vertical silos to share patient information across the continuum, the plethora of independent care-continuum solutions and projects gives reason for pause: Are we at risk of repeating the same silo approach, only this time horizontally?

Key Considerations

As we move away from an emphasis on acute episodic care to a longitudinal cross-continuum approach for DM, our view of the big picture has to evolve accordingly, or we run the danger of repeating past patterns of creating islands of technologies, albeit in different ways. We propose three focus areas for consideration when conceptualizing optimal deployment and integration of cross-continuum solutions. They speak to changes in the way we architect information access, in the way we contextualize the information accessed, and finally, in the way we mobilize and deliver the right information:

Moving toward Single Platform for Cross-continuum Workflow

There is only one care continuum. While the above-mentioned focus on the Big Five for DM is a great starting point, do we really need separate initiatives and applications for different conditions? Similarly, do we need separate applications for various stages along the care continuum (e.g., cancer screening, management of various wait time segments, e-referral, etc.)? Assuming adherence to interoperability standards, there really is no need to enable each of these initiatives on its own through stand-alone applications. Aside from lower integration and expansion costs, a single platform for these initiatives also has crucial implications for the holistic management of patients with co-morbidities: The single-patient context remains intact, allowing key data points to be available globally across all appropriate care pathways, rather than as separate instances in siloed records. A truly integrated information view could even cast a wider net to integrate not only clinical information via a single platform, but also administrative data (scheduling, billing, logistics, etc.) to provide a full picture of health system performance and operations without complicating the day-to-day workflow of clinicians. There are well-documented single-platform solution examples already operational in jurisdictions around the globe. For example, several instances of the AxSys Excelicare (AxSys Technology Ltd., Paisley, Scotland) platform are in widespread use in the United Kingdom on a local, regional and national level to support multidisciplinary, collaborative care and pathway management for a variety of conditions.

Minimizing the "Drinking from the Firehose" Syndrome

DM solutions should be optimized to tailor the amount, specificity and context of health information based on what provides the most value to an increasingly mobile clinician workforce. A key focus of past electronic healthcare record (EHR) projects has been consolidating (or virtually integrating) clinical information silos to achieve a seamless "look and feel of one" via portal technology. This resulted in a drive to make all information for all patients available all the time, which is counterproductive for successful DM enablement. Similarly, alert fatigue is a well-documented issue for the adoption of computerized physician order entry (CPOE) and decision support systems; practitioners are already inundated with such an amount of information that a great percentage of alerts are being overridden or ignored, regardless of severity (Baker 2009). This does not bode well for DM, as alerts and triggers are seen as a key ingredient to successful outcomes. Alert content and frequency should be able to be intelligently tailored based on clinician/patient context so that alerts become more relevant and meaningful. For example, a DM system should not automatically trigger alerts based every abnormal lab result for a patient whose results are already known to be out of range based on past results and disease history.

Enabling the "Smart" in Smartphone to Optimize Increasingly Mobile Workflow

The concept of DM has been around for decades. But have our concepts of IT enablement of DM kept pace with the advances of technology? Let's consider the suitability of current mHealth solutions for clinicians, whose day-to-day work essentially happens on the go. Today, even in more traditional acute care environments, physicians on call easily walk several miles per shift (Parshuram at al. 2004). Nurses remaining in their units still log an average of two to three miles per day (Henrich and Chow 2008). With greater focus on DM, the need for interactive care collaboration will only intensify clinician mobility, which in turn will increase the need to access key clinical information on smartphones and other mobile devices. With more and more clinicians using smartphones to access medical information (Malkary 2010), mHealth appears to be well suited for DM because of its ability to mobilize data, automate messaging, and provide greater opportunity for patient–clinician interaction in a timely and personalized manner. That said, mobile device and application ergonomics should not be neglected: Many mHealth applications use the smartphone as a mere access point to one or many clinical data repositories, a smaller-screen adjunct to a laptop or desktop. Accessing a lot of clinical data doesn't necessarily result in useful information to inform better care management. Further, few solutions fully leverage the depth and breadth of a device's native communications capabilities to augment clinician productivity. Simply using the device browser to view information will not add much value in a world where care collaboration is impeded by too many delays. Embedding voice, SMS, chat tools and other social media capabilities into the clinical workflow makes the device a true mobile unified communications hub and enhances the time value of information significantly. The smaller device screen is therefore not necessarily a limitation: mHealth highlights a natural overlap between DM and virtual collaboration. In the context of DM, mHealth requires a different workflow, different user experience and different ways of interacting with health information. We see this difference as analogous to "tweeting" versus "e-mailing."


Health IT has traditionally focused on diagnosis and treatment in a provider-centric way. Unlocking and integrating content from as many data repositories as possible became the mantra of the day. As health systems struggle with sustainability, the old ways are superseded by a movement toward sharing of health information along the care continuum in a timely, accurate, relevant, and collaborative manner. Among a variety of cross-continuum IT initiatives, DM solutions receive a lot of attention due to their role in connecting patients and care teams to achieve better, more proactive care; better outcomes and more efficient use of resources.

While progress has been made in integrating DM concepts with business and clinical IT platforms to increase care collaboration, several challenges remain on the path toward enabling holistic information flow for optimal care management. Simply integrating disparate systems or replacing old with new technology is not enough. To accelerate progress, careful consideration must be taken to avoid a replication of past "silo thinking" and to take full advantage of new technologies such as mHealth.

Decision makers should ask themselves a number of questions prior to choosing an IT solution to support DM or other cross-continuum initiatives:

  • Can we use a single solution platform to support not only select but all applicable chronic conditions?
  • Can we leverage the identified solution to address other cross-continuum initiatives?
  • Does it meet the "80/20 rule"? That is, does it provide easy alerting/access to the select amount of clinical information that is really needed at a given point in time?
  • Is the approach and user experience in keeping with the workflow needs of an increasingly mobile clinical workforce?
  • Does the solution leverage all the communication modalities available to support a collaborative care approach?

In our view, the way information is collected, consolidated and disseminated must go beyond the traditional integration philosophies entrenched in today's e-Health landscape in order to effectively support the way care will be delivered in the future. With overall trends toward greater clinician mobility and information access that is tailored to the right care context, single-platform technologies, innovative information models and mobile device ergonomics must be considered when designing DM initiatives on a broader scale.

Just as technology and the proliferation of communication tools like social networking are dramatically transforming our day-to-day lives, so must health IT in order to support collaborative care across the care continuum. The good news is that the appropriate software and device technology exists today to drive that transformation. The challenge will be in applying this technology pervasively beyond showcase pilot projects to achieve true system-wide change.

About the Author(s)

Zun Lee, MD MBA, is the Director of e-health for CGI's Healthcare Centre of Excellence, providing thought leadership and expertise in the areas of e-health, clinical transformation and chronic disease management to a variety of healthcare organizations. He can be reached at

Myrna Francis, PhD, is the Vice-President of Global Marketing for the health industry at CGI, with responsibility for supporting the IT and e-health needs of government health departments and healthcare providers.


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