Efficacy

Theories summarize the state of cumulative knowledge. They specify key constructs and relationships and the underlying scientific explanations of the processes of change and link behavior change to constructs in a systematic way. They describe how, when and why change occurs. They allow investigators to understand why and how interventions succeed or fail. Rigorous testing of theoretical principles forms a basis for future interventions. Thus, theories are fundamental in designing behavior change interventions.

Investigation of theory to support the problem domain is a central exercise in design science research. Key frameworks for designing and evaluating behavior change interventions (Collins et al. 2011; Craig et al. 2008) emphasize the importance of using theory to inform intervention design as well as specifying interventions using component behavior change techniques(BCTs). Behavior may refer to simple, specific actions, for example, swallowing a pill; about health, it is used to refer to a more complex sequence of actions. Behavior change techniques (BCTs) are observable and replicable components of behavior change interventions. They are the smallest component compatible with retaining the proposed mechanisms of change, and can be used alone or in combination with other BCTs (Easthall et al. 2013; Michie and Johnston 2012). Precise specification of BCTs may also enhance the intervention.

Dombrowski et al. (2012) found using a BCT coding scheme that instruction, self-monitoring, and practice were effective techniques. Taylor et al. (2012) also found that the extent to which

interventions were explicitly based on theory predicted their effectiveness; a finding consistent with a similar analysis of collaborative interventions (Webb et al. 2010).

The existing electronic reminder systems have been available for decades, yet there is very small improvement in the medication adherence behavior. Most of these systems rely on simple alarms and do not consider another determinant of health-related behavior. Besides the

technology enablement, it is important to consider the personal traits of the patient entrusted with the prescribed self-administered medication regimen.

For both scientific and practical reasons, it is essential that behavior change interventions develop a sound scientific basis. In practice, the science will inform the technology (i.e. the techniques and methods) required to deliver effective, replicable interventions with guidance on their delivery to ensure use of effective interventions. A science of behavior change needs both good theory and reliable technology.

In this research, we develop a model to improve medication adherence from information systems and health IT perspective. Health IT enabled intervention is based on the notion of collaborative care as it leverages the patient-provider relationship and can help those who are willing to be helped. When a prescribed medication is self-administered, the choice rests with the patients and their motivation to take the medicine. An intervention is a mechanism to try and modify the behavior of the patient, in the best interests of the patient, when the concordance between patient and the provider breaks.

This research examines the problem with the lens of health behavior change theories to predict “when” and “what” intervention is required to improve the medication adherence behavior of patients, thereby making the interventions “smart interventions.” Appendix A3.2 discusses different health behavior change theories as adapted from Revere and Dunbar (2001)

For the purpose of this research, we are interested in a theory that can support a health IT artifact for affecting a behavior change. The simplest of BCTs that finds prevalence in system design are reminders, a component of both Health Belief Model and Stages-of-Change Model. We also identify effective medication adherence ‘EMA’ as a ‘Goal’ for the patient. Stages-of- Change Model and Theory of Planned Behavior and Theory of Reasoned Action support setting goals and steering of the patient towards the goal. As the theories listed in Appendix A3.2 support BCTs, we utilize the BCTs to leverage in the theory based model for effective

medication adherence. We focus on when and what reminder (Cues to action/maintenance) to administer to the patient as smart intervention for improving medication adherence.

Figure 14. Generalized model based on the BCTs affecting medication behavior

Figure 14 shows a generalized theoretical model supporting the health IT system. The most prevalent Behavior Change Techniques leveraged in the development of the health IT system model are Action planning, Prompt/cues, Self-monitoring, and Feedback on behavior. These four techniques are based on the health behavior change theories of Stages-of-Change Model, Health Belief Model and Theory of Planned Behavior/Theory of Reasoned Action and specifically are focused on behavior changes tied to Goals and Reminders (Morrissey et al. 2015).

Action Planning: Prompt, detailed planning of performance of the behavior (must include at least one of context, frequency, duration, and intensity); context may be environmental or

internal. An example is setting a reminder to take medication at a specific time every day

Prompt/cues: Introduce or define environmental or social stimulus for the purpose of

prompting or cueing the behavior; the prompt or cue would normally occur at the time or place of performance. A reminder alarm ringing to prompt the user to take medication is a prompt/cue BCT.

Self-monitoring: Establish a method for the person to monitor and record their behavior(s)

as part of a behavior change strategy. A dialog box that allows users to record whether they took or skipped their medication is a self-monitoring BCT.

Feedback on behavior: Monitor and provide informative or evaluative feedback on the

performance of the behavior. An example is a log or graph that displays the user’s adherence levels.

As shown in the generalized model based on the BCTs affecting Medication Behavior, we see that patient’s medication behavior is a dynamic state that keeps changing, from the

interventions provided by the system, and continuously feeds to the knowledge base of

interacting dimensions of medication behavior. These medication behaviors are examined using the health behavior change theories. Such examinations can lead to an expansion of the existing theories or to postulate new theories for explaining a new or changed behavior encountered, and subsequently to identify new BCTs.