|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.
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.
Original publication: April 24, 2013.
Original publication indicates the date the profile was first posted to the Innovations Exchange.
Last updated: July 31, 2013.
Last updated indicates the date the most recent changes to the profile were posted to the Innovations Exchange.