Active and Engaged Patients: Promising Methods To Improve Health Outcomes
By Holly Jimison, PhD, Associate Professor of Medical Informatics and
Clinical Epidemiology, Oregon Health & Science University
A confluence of factors has made it increasingly important to focus on
new approaches to health care that address escalating costs associated
with chronic conditions and conditions of the elderly. Health care
reform and new models of reimbursement will align incentives with
techniques that foster self-management in patients with chronic
conditions.
The Institute of Medicine’s seminal report1 Crossing the Quality Chasm
focused on fostering self-management in patients. Two of the
initiatives focused on patient-centered care and informatics. The goal
of patient-centered care is to inform and involve patients and their
families in decision-making and self-management, coordinate and
integrate care, provide physical comfort and emotional support,
understand patients' concepts of illness and their cultural beliefs, and
understand and apply principles of disease prevention and behavioral
change appropriate for diverse populations.
Communications technology and informatics are useful in facilitating self-management and patient-centered care2.
With advances in new sensor technology for monitoring activities in the
home and environment, and an increasing array of options for wireless
communications devices, patients can receive just-in-time support to
cope with routine care tasks while they manage chronic conditions in the
home and workplace. Interactive consumer health information technology
has the potential to engage and support consumers in self-care by
integrating their health information needs and preferences into
information systems. Such technologies can provide targeted or tailored
health information to help patients manage their health. We know from
previous research that tailored information and interventions are more
effective at improving patient outcomes, confidence, and satisfaction
with care3,4.
The service delivery innovation
profiled here is a great example of using technology to facilitate
patients’ self-management and insight into the course of their disease.
The intervention aimed at managing Crohn’s disease, explores how health
behaviors clearly affect health outcomes over time. Weight, sleep
quality, and physical activity, which are important issues found in
nearly all chronic conditions, are examined over time. Because Crohn’s
disease is sufficiently common and complex, it is a useful test case for
monitoring and feedback technologies for facilitating self-management.
Patients used a tablet computer to report six observations of daily
living (ODLs), while automated sensor data collection measured weight,
sleep time, and physical activity. The data was reported back to the
patient in a graphical format showing how health outcomes such as
abdominal pain, energy level, and stress level varied over time and in
relationship to medication dosage, lab results, and health behaviors
(weight, sleep, activity).
The convenience of electronic data entry and immediate graphical
feedback of trends over time, and linkages between changes in health
behaviors and outcomes are new and extremely important for both patient
insight and motivation. In the past, clinicians could not clearly see
what happened with their patients at home and how the health behaviors
linked to outcomes for individuals. This type of intervention will have a
dramatic impact on quality of care and patient-physician communication.
In a recent evidence report for AHRQ on the Barriers and Drivers of Health Information Technology Use for the Elderly, Chronically Ill, and Underserved,
the most important and consistent finding regarding the effectiveness
of these technology interventions was that it was important that the
systems provided a complete feedback loop that included some assessment
of current patient status, interpretation of this status information in
light of established treatment goals or plans, and communication back to
the patient with tailored recommendations or advice. Interactive
consumer health IT that provided only one or a subset of these functions
was less consistently effective5.
The innovation for patients with Crohn’s disease meets these criteria
for success. The system is interactive with specific feedback on health
behaviors that clearly relates to health outcome goals. Clinicians are
“in the loop” and able to modify advice and medications. An additional
characteristic that fits with the findings of the evidence report is
that the tablet-based system is easy to use, convenient, and a device
that can be used in routine day-to-day activities. Previous research has
shown that these factors increase the usage of health technologies by
patients5.
The Crohn’s disease innovation also represents a successful approach to
the care of chronic conditions. It makes use of new sensor developments
and information technologies to bring continuous care to the home where
self-management of chronic conditions takes place. The convenience of
data entry on important health behaviors and symptoms makes it possible
to provide just-in-time feedback and support for patients. In addition,
clinicians now have the needed information to optimize continuous care
in a timely way, and not wait for an arbitrarily timed office visit.
The intervention also represents a new trend in caring for chronic
conditions. These health technology systems will provide the means for
continuous improvement through repeated refinement or adjustment of the
management of the patient according to their current condition. It is
important to note, however, that perhaps the most challenging issue will
be a required workflow shift on the part of clinicians-–moving away
from relying on traditional physician office visits toward distributed
team-based care that includes remote care managers, informal caregivers,
and most importantly, the active and engaged patient themselves.
About the Author
Holly Jimison, PhD is Associate Professor of Medical Informatics &
Clinical Epidemiology at Oregon Health & Science University, and
also on loan part time to NIH’s Office of Behavioral & Social
Science Research. Her research is focused on developing new methods of
team-based care delivery that include patients and informal caregivers
as active and informed participants. Her approaches use computational
models to interpret sensor monitoring data and provide just-in-time
feedback and guidance. Dr. Jimison was formerly affiliated with the
Oregon Evidence-based Practice Center and co-authored the evidence
report, Barriers and Drivers of Health Information Technology Use for the Elderly, Chronically Ill, and Underserved.5
Disclosure Statement: Dr. Jimison reported having no financial
interests or professional/business affiliations relevant to the work
described in this article.
References
1. Committee on Quality Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington D.C.: Institute of Medicine; 2001.
2. Rao S, Brammer C, McKethan A, Buntin MB. Health information
technology: transforming chronic disease management and care
transitions. Prim Care. 2012 Jun;39(2):327-44.
3. Kreuter MW, Strecher VJ, Glassman B. One size does not fit all: the
case for tailoring print materials. Ann Behav Med. 1999
Fall;21(4):276-83.
4. Lustria MLA, Cortese J, Noar SM, Glueckauf RL. Computer-tailored
health interventions delivered over the web: Review and analysis of key
components. Patient Education and Counseling. 2009 Feb:74(2):156-173.
5. Jimison H, Gorman P, Woods S, Nygren P, Walker M, Norris S, Hersh W.
Barriers and Drivers of Health Information Technology Use for the
Elderly, Chronically Ill, and Underserved. Evidence Report/Technology
Assessment No. 175 (Prepared by the Oregon Evidence-based Practice
Center under Contract No. 290-02-0024). AHRQ Publication No. 09-E004.
Rockville, MD: Agency for Healthcare Research and Quality. November
2008. |
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Original publication: April 24, 2013.
Original publication indicates the date the profile was first posted to the Innovations Exchange.
Last updated: April 24, 2013.
Last updated indicates the date the most recent changes to the profile were posted to the Innovations Exchange.
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