Elsevier

Preventive Medicine

Volume 66, September 2014, Pages 167-172
Preventive Medicine

Review
Aligning health information technologies with effective service delivery models to improve chronic disease care

https://doi.org/10.1016/j.ypmed.2014.06.017Get rights and content

Highlights

  • US health reform is driving practice redesign and health information technology use.

  • Health information capabilities should align with effective clinical care models.

  • Five key principles guide collaborative care, an effective model of chronic care.

  • Health information technology can support implementation of each principle.

  • Leveraging technology can extend evidence-based care beyond clinical settings.

Abstract

Objective

Healthcare reforms in the United States, including the Affordable Care and HITECH Acts, and the NCQA criteria for the Patient Centered Medical Home have promoted health information technology (HIT) and the integration of general medical and mental health services. These developments, which aim to improve chronic disease care, have largely occurred in parallel, with little attention to the need for coordination. In this article, the fundamental connections between HIT and improvements in chronic disease management are explored. We use the evidence-based collaborative care model as an example, with attention to health literacy improvement for supporting patient engagement in care.

Method

A review of the literature was conducted to identify how HIT and collaborative care, an evidence-based model of chronic disease care, support each other.

Results

Five key principles of effective collaborative care are outlined: care is patient-centered, evidence-based, measurement-based, population-based, and accountable. The potential role of HIT in implementing each principle is discussed. Key features of the mobile health paradigm are described, including how they can extend evidence-based treatment beyond traditional clinical settings.

Conclusion

HIT, and particularly mobile health, can enhance collaborative care interventions, and thus improve the health of individuals and populations when deployed in integrated delivery systems

Introduction

In the wake of national health care reform in the United States, numerous state and federal initiatives have begun to implement integrated care approaches for chronic diseases into primary care medicine. These initiatives are meant to increase access to high quality care for patients and to assist clinicians in improving quality of care for chronic diseases. Nearly two decades ago, Wagner et al. articulated the need to organize services for more effective delivery of care for chronic conditions, by outlining key elements of the “chronic care model” (Wagner et al., 1996). The collaborative care model is one example of how these elements have been operationalized and implemented with an emphasis on improving care for common mental disorders such as depression in primary care (Katon et al., 1995, Unutzer et al., 2002).

With the expansion of health insurance through the Affordable Care Act, the anticipated demand from newly insured patients with needs related to chronic medical and mental health conditions will present a significant challenge for healthcare systems. Collaborative care can effectively leverage limited mental health specialty resources and address this need in high risk patients. Such patients often have combinations of comorbid medical and mental health conditions, limited health literacy, and inadequate provider–patient communication, all factors that can impede effective chronic disease care (Barnett et al., 2012, Benjamin, 2010, Kutner et al., 2006, Nielsen-Bohlman et al., 2004, Ratanawongsa et al., 2013, U.S. Department of Health and Human Services, 2010). Health information technology (HIT) can play an important role in addressing these potentially modifiable factors in the context of delivery models such as collaborative care.

HIT, defined as “the application of information processing involving both computer hardware and software that deals with the storage, retrieval, sharing, and use of health care information, data, and knowledge for communication and decision making” (p. 38) Thompson & Brailer, 2004, encompasses a variety of electronic tools including electronic and personal health records, patient registries, mobile health (mHealth) applications, and remote monitoring devices (U.S. Department of Health and Human Services, 2011). Consumer health technologies have greatly expanded in the last 5 years and have the potential for mitigating some critical barriers to quality care. For example, nearly 100,000 mHealth applications are now available for consumers to download (Pelletier, 2012, research2guidance, 2013). Although evidence for their effectiveness lags far behind (Ehrenreich et al., 2011, Free et al., 2013), some mHealth applications are already in widespread use by the general public (Ziobro, 2013). With this growth, mHealth is emerging rapidly with the potential to become a significant component of HIT and of health service delivery and an important tool in extending the population impact of traditional clinical services, including among underserved patients and those with limited health literacy (U.S. Department of Health and Human Services, 2010, California Pan-Ethnic Health Network (CPEHN) et al., 2013).

Despite the increasing availability of many mHealth technologies, several factors may limit their adoption and subsequent impact on chronic disease management. Older adults, who are frequently the target of chronic disease management programs, are less likely to have access to portable devices (Fox & Duggan, 2012) and may have limited literacy in health technologies. Both older adults and those with limited financial resources may be unable or unwilling to pay for equipment or access fees (such as broadband internet access), and patients in rural areas may not even have such services available. Individuals with cognitive impairments (Plassman et al., 2008) or mental health issues might be unwilling to use novel approaches to disease management. While it is important to consider potential limitations such as these, their actual impact remains uncertain. Among primary care patients, recent data suggests that mHealth use is less common among older adults but not related to such factors as the presence of chronic diseases, depression, or health literacy limitations (Bauer et al., 2014). Web-based and mobile technologies have been successfully designed and deployed in research settings among individuals with serious mental illness and their use has not been hampered by cognitive impairments or limited general or health literacy (Ben-Zeev et al., 2013, Ben-Zeev et al., 2014, Druss et al., 2014). Home-based monitoring systems and video game interventions have been used among older adults, including those with cognitive impairments and chronic diseases, with some evidence for overall healthcare cost-savings associated with home monitoring (Anguera et al., 2013, Baker et al., 2011, Kaye et al., 2014, Weintraub et al., 2010). Importantly, in order to be adopted, any technology for health improvement must meet the user's specific needs and people with chronic diseases may have other more pressing personal or social needs which preclude attention to health improvement (Thielke et al., 2012). If users are not interested or motivated, then mHealth technologies, no matter how well-designed, will have no benefits for them, and thus will not be used.

In light of the opportunities and limitations, this paper addresses how HIT can support the implementation of evidence-based collaborative care models and in particular how programs that leverage HIT can potentially ease concerns health care systems and providers have regarding the anticipated volume of newly insured patients as coverage expands. Digital health tools and information management systems for providers and patients are reviewed, including how their integration into health systems can address mental health, health literacy and communication barriers to effective care. The collaborative care model of integrating mental health into primary care is used to illustrate the need to align HIT to appropriate health service delivery models; however, these principles may be relevant for care management for chronic conditions more generally and may also have relevance outside the United States among systems that have implemented similar models for organizing chronic disease care.

Section snippets

What is collaborative care (CC)?

The collaborative care (CC) model is one of the most widely researched and disseminated models for delivering evidence-based mental health services in primary care settings (Archer et al., 2012, Gilbody et al., 2006, Katon et al., 1995, Katon et al., 1999, Katon et al., 2010, Thota et al., 2012, Unutzer et al., 2002). The empirical support for the model is clear: there are more than 79 randomized controlled trials that demonstrate the effectiveness of this model for improving outcomes for

Health information technology supports effective collaborative care

The delivery of effective CC is based on 5 key principles: care is patient-centered, evidence-based, measurement-based, population-based, and accountable (University of Washington AIMS Center, 2014). Effective HIT is vital to the delivery of effective CC. The key principles of effective CC, the associated clinical processes, and the corresponding HIT tools that can support these activities are described in detail below and summarized in Table 1.

Effective clinical care models support appropriate health information technology

Federal initiatives and information technology development are creating new opportunities to improve health services and expand the reach of evidence-based practices beyond traditional clinical settings. Research to date suggests that patient-facing HIT tools are less effective when they are provided as stand-alone interventions, rather than in the context of a relationship with a counselor or healthcare provider (Kelders et al., 2012, Mohr et al., 2013, Spring et al., 2013). Human support may

Conclusion

Transformations in US healthcare fueled by the Affordable Care and HITECH Acts are driving practice redesign and the adoption of HIT in parallel. These transformations coincide with advances in consumer technologies and shifts toward patient empowerment and shared decision-making in managing health. The most promising opportunities for progress emerge from the alignment of HIT functions with effective clinical models, such as the evidence-based collaborative care model. Such alignment of

Conflict of interest

Amy M. Bauer, MD MS has no financial disclosures.

Stephen M. Thielke, MD MSPH MA has no financial disclosures.

Wayne Katon, MD has no financial disclosures.

Jürgen Unützer, MD MPH MA has no financial disclosures.

Patricia Areán PhD has no financial disclosures.

Acknowledgments

This publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health (KL2TR000421) and the National Institute of Mental Health (K24 2MH074717 and R34 MH100466). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

References (67)

  • A.M. Bauer et al.

    Implementation of collaborative depression management at community-based primary care clinics: an evaluation

    Psychiatr. Serv.

    (2011)
  • A.M. Bauer et al.

    Primary care patients' use of mobile health (mHealth) tools

  • R. Benjamin

    Health literacy improvement as a national priority

    J. Health Commun.

    (2010)
  • D. Ben-Zeev et al.

    Development and usability testing of FOCUS: a smartphone system for self-management of schizophrenia

    Psychiatr. Rehabil. J.

    (2013)
  • D. Ben-Zeev et al.

    Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia

    Schizophr. Bull.

    (2014 Mar 19)
  • M.N.K. Boulos et al.

    How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX

    Biomed. Eng. Online

    (2011)
  • California Pan-Ethnic Health Network (CPEHN) et al.

    Equity in the digital age: How health information technology can reduce disparities

  • C. Chen et al.

    Making sense of mobile health data: an open architecture to improve individual- and population-level health

    J. Med. Internet Res.

    (2012)
  • C.M. Desroches et al.

    Adoption of electronic health records grows rapidly, but fewer than half of US hospitals had at least a basic system in 2012

    Health Aff.

    (2013)
  • B.G. Druss et al.

    Randomized trial of an electronic personal health record for patients with serious mental illnesses

    Am. J. Psychiatry

    (2014)
  • B. Ehrenreich et al.

    Are mobile phones and handheld computers being used to enhance delivery of psychiatric treatment? A systematic review

    J. Nerv. Ment. Dis.

    (2011)
  • F.K.J. Ehsani et al.

    Speech to speech translation for nurse patient interaction

  • K. Ell et al.

    Collaborative care management of major depression among low-income, predominantly Hispanic subjects with diabetes: a randomized controlled trial

    Diabetes Care

    (2010)
  • D. Estrin et al.

    Health care delivery. Open mHealth architecture: an engine for health care innovation

    Science

    (2010)
  • S. Fox et al.

    Mobile Health 2012

    (2012)
  • C. Free et al.

    The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review

    PLoS Med.

    (2013)
  • S. Gilbody et al.

    Collaborative care for depression: a cumulative meta-analysis and review of longer-term outcomes

    Arch. Intern. Med.

    (2006)
  • E.M. Hunkeler et al.

    A web-delivered care management and patient self-management program for recurrent depression: a randomized trial

    Psychiatr. Serv.

    (2012)
  • Institute of Medicine

    Crossing the Quality Chasm: A New Health System for the 21st Century

    (2001)
  • W. Katon et al.

    Collaborative management to achieve treatment guidelines. Impact on depression in primary care

    JAMA

    (1995)
  • W. Katon et al.

    Stepped collaborative care for primary care patients with persistent symptoms of depression: a randomized trial

    Arch. Gen. Psychiatry

    (1999)
  • W. Katon et al.

    The Depression Helpbook

    (2008)
  • W.J. Katon et al.

    Collaborative care for patients with depression and chronic illnesses

    N. Engl. J. Med.

    (2010)
  • Cited by (0)

    View full text