Case study 2 mindset: a mobile Health (mHealth) Management Information Decision-Support Epilepsy Tool Ross Shegog and Charles Begley University of Texas Health Science Center at Houston School of Public Health Acknowledgement

This research was funded by Special Interest Project Grants (SIP07-006, SIP09-012, and SIP12-057) from the Centers for Disease Control and Prevention (CDC) (Managing Epilepsy Well [MEW] Collaborating Center). We would like to extend our deepest appreciation to the patients and clinicians who participated in the development of MINDSET and to our colleagues in the MEW Research Network for their consultation. Appreciation is also extended to Zsolt L. Levai, MD, for his contribution to facilitating manuscript development. This research received human research approval from the local human subject research internal review boards at the University of Texas and the Harris County Hospital District (Harris Health).

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  Describe the use of community-based planning methods
  
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  Develop theory- and empirically based performance objectives for chronic disease (epilepsy) self-management
  
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  Describe the translation of change objectives into a functional clinic-based decision-support system
  
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  Describe components of a mobile health, clinic-based decision-support system for epilepsy self-management
  
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  Describe usability and feasibility evaluation protocols for clinic-based interventions
  

Epilepsy is a neurological condition characterized by recurrent unprovoked seizures. An estimated 2.3 million people in the U.S. are affected by epilepsy and approximately 181,000 new cases of epilepsy are diagnosed each year (Epilepsy Foundation, 1999). Epilepsy may start at any age, although incidence rates peak before the ages of 5 and after 60. In addition, seizures that begin during adolescence may have greater psychosocial impact than seizures beginning at a younger age. The social burden of epilepsy has been well documented in terms of incidence and prevalence, quality of life, health care use, and costs. Epilepsy impacts a wide range of social, physical, and psychological aspects of life and may have a devastating impact on a person's economic and social future. The direct costs of epilepsy care were estimated to range from $8,412 and $9,287 in 2013 and were markedly higher for sub-populations with uncontrolled or refractory epilepsy, or comorbidity (Begley and Durgin, 2015).

The clinic-based, mobile health (mHealth) Management Information Decision Support Epilepsy Tool (MINDSET) has been developed to address the need to facilitate the engagement of patients and their healthcare providers (HCPs) in managing therapy and lifestyle issues to prevent seizures and maximize quality of life (IOM, 2012), the need for structured approaches to address and document patient-centric quality indicators for care of patients with epilepsy (Pugh, Berlowitz, Montouris, Bokhour, Cramer, Bohm, Bollinger, Helmers, Ettinger, Meador, Fountain, Boggs, Tatum, Knoefel, Harden, Mattson, Kazis, 2007; Pugh, Berlowitz, Rao, Shapiro, Avetisyan, Hanchate, Jarrett, Tabares, Kazis, 2011), and the need to provide easy-to-understand management instructions (USDHHS, 2013). MINDSET is a theoretically and empirically based decision-support system designed to increase patient and provider awareness of the patient's epilepsy self-management behavior (i.e., seizure history and management, medication adherence, and the physical and social interactions related to lifestyle), enhance the quality of communication between them during the clinic visit (with focus on important self-management goals and strategies consistent with the patient's needs), and increase the patient's confidence to achieve those goals. In this case study, we will describe how the Intervention Mapping (IM) process was used to develop, implement, and evaluate MINDSET to provide real-time self-management decision-support to patients and health care providers in specialty neurology clinics.
PERSPECTIVES

MINDSET provides an example of chronic disease management support, patient and provider participation in a clinic-based intervention, and the use of mHealth decision-support as an intervention channel.

Chronic Disease Management

People with epilepsy may undergo relatively benign or difficult courses, but as with all chronic diseases, they are challenged to self-manage their treatment and lifestyle to maintain the highest quality of life possible with their condition. The Managing Epilepsy Well (MEW) Network defines epilepsy self-management as the sum of processes a person uses to optimize seizure control, to minimize the effects of having a seizure disorder, and to maximize quality of life in partnership with their healthcare provider (DiIorio, 1997; Dilorio, Bamps, Edwards, Escoffery, Thompson, Begley, Shegog, Clark, Selwa, Stoll, Fraser, Ciechanowski, Johnson, Kobau, Price, 2010). This comprises self-management that is specific to epilepsy and chronic care self-management that is applicable to most chronic conditions (IOM, 2012). Epilepsy specific self-management encompasses treatment management (e.g., adhering to anti-seizure medication and clinical visit regimens), seizure management (e.g., preparation for and response to seizure episodes), safety management (e.g., assessing and avoiding risks in the environment), and management of comorbid conditions (e.g., anxiety, depression). Chronic care self-management encompasses lifestyle management (e.g., altering behaviors to avoid seizure onset and/or adverse consequences of seizures), active partnership with the healthcare team (e.g., conveying and sharing information about seizures and epilepsy), and independent living (e.g., eliciting needed support, resources, and services) (IOM, 2012; Buelow, 2001). Important factors associated with epilepsy self-management behavior include the patient's knowledge about epilepsy self-management and how to perform self-management behaviors, and self-efficacy or confidence to perform self-management behavior (DiIorio et al., 2010; DiIorio, Faherty, Manteuffel, 1994; Dilorio, Faherty, Manteuffel, 1992; Tedman, Thornton, Baker, 1995; Begley, Shegog, Iyagba, Chen, Talluri, Dubinsky, Newmark, Ojukwu, Friedman, 2010). Comorbidities including depression, anxiety, and cognitive dysfunction can compromise self-management practice as well as act directly as internal precipitants of seizures (IOM, 2012, Jones, Hermann, Woodard, Barry, Gilliam, Kanner, Meador, 2005; Ramaratnam, Baker, Goldstein, 2005).

The Institute of Medicine (IOM) report, “Epilepsy Across the Spectrum,” calls for the promotion of patient-centered and collaborative approaches to the care of epilepsy and comorbid health conditions (IOM, 2012). An important aspect of patient self-management information and training is an active partnership between the HCP (including clinicians, nurse educators, and community health workers), the patient, and the patient's family or significant others to aid in adherence to treatment and improve seizure and lifestyle management. With the emerging recognition of the importance of self-management, HCPs are increasingly being asked to assist their patients in meeting their self-management needs as part of the patient-centered model of caring for people with a chronic disease (IOM, 2012). Discrepancy between the patient and HCP regarding the patient's attitudes about epilepsy and their self-management abilities and/or poor communication between the two can undermine the adoption of self-management behavior. Conversely, reinforcement of patients in self-management can impact commitment to recognizing at-risk practices and making improvements (DiIorio, Shafer, Letz, Henry, Schomer, Yeager, 2004; Rothert, 1991). Challenges to effectively incorporating self-management assistance in clinical care include the time and ability to assess a patient’s self-management needs and to adequately address them in the context of a brief clinical visit (DiIorio, 1997; Escoffery, DiIorio, Yeager, McCarty, Robinson, Reisinger, Henry, Koganti, 2008; Prinjha, Chapple, Herxheimer, McPherson., 2005).

The IOM report also recognized the need to investigate new screening and decision-support tools for self-management (IOM, 2012). Such tools are being developed in the medical field (i.e., written materials or videos) to assist providers and patients with complex decision-making and to ensure that such decisions reflect patient values and preferences (IOM, 2012; Oshima Lee E, Emanuel EJ, 2013; AHRQ, 2009; NINDSa, 2009a; NINDS, 2009b; CDC, 2009; American Epilepsy Society, 2003). The emergence of electronic health (eHealth) applications to support patients in their daily self-management monitoring and decision-making is contributory to impacting epilepsy self-management (Shegog, Bamps, Patel, Kakacek, Escoffery, Johnson, Ilozumba, 2013). mHealth (mobile health) is a subset of eHealth that pertains to the practice of medicine and public health supported by mobile devices such as mobile phones, tablet computers, and PDAs (Adibi, 2015).

Clinic-based decision support systems for epilepsy have primarily centered on diagnostic and pharmacologic support (Harding, 2011; Holden, Grossman, Nguyen, Gunter, Grebosky, Von Worley, Nelson, Robinson, Thurman, 2005; Vassilakis, Vorgia, Micheloyannis, 2002; Smeets, Talmon, Meinardi, Hasman, 1999a, 1999b; Korpinen, Pietilä, Peltola, Peltola, Nissilä, Keränen, Touvinen, et al., 1994; Mishra, 1992). This is consistent with the general application of such systems in medicine that focus on the technical aspects of care, in contrast to the personal or social concerns of patients (Bernabeo, Holmboe, 2013). Preceding MINDSET, no epilepsy-specific electronic decision support systems had existed that were dedicated to facilitating dual HCP and patient decision-making regarding patient self-management.

IM STEP 1: LOGIC MODEL OF THE PROBLEM

In this section we describe the process for creating a logic model of the problem that includes establishing a planning group, conducting a needs assessment informed by the PRECEDE planning model that outlines the factors associated with the problem, defining the context of the intervention in terms of population, setting, and community, and stating program goals.

MINDSET development took place in conjunction with the Kelsey Seybold Epilepsy Education and Research Program and the MEW National Network and at three epilepsy specialty clinics in Houston, Texas, that provided heterogeneity of clinic type, patient population, and clinician experience.

It is important to involve the target population in a formative capacity in the developmental process. A patient-provider advisory group (PPAG) was formed and incorporated into the research and planning team from the commencement of development work. The PPAG was consulted on every phase of MINDSET development and testing including reviewing content (e.g., constructs, scales, and threshold scores for identifying “at-risk” patients), assessing the functionality and “look and feel,” testing usability, and reviewing evaluation plans. Patients for the advisory group were invited to join the PPAG by co-investigator clinicians and nurses on the basis of their being representative of the patient population, over 18 years of age, English speaking, engaged in epilepsy management issues, interested in contributing to the field, and able to complete the screening tool (i.e., no motor disorders, for example, hemiplagia or quadriplegia), learning difficulties and psychiatric behavioral problems (e.g., autism or attention deficit disorders) that would impinge the patient’s ability to contribute to focus group and formative evaluation discussion and review of prototypes, or engage in self-management practice activities. Providers taking part in the PPAG included neurologists, specialists, and a nurse educator. The PPAG met in a conference room at the KSC. Patient members of the PPAG received an incentive payment of $30 per meeting

The Kelsey-Seybold Neurology Clinic (KS clinic) is part of a large multi-specialty medical organization in Houston with 21 clinics and over 300 physicians. Care is provided to an ethnically diverse population of more than 325,000 patients: white (55%), African-American (23%), Hispanic (19%), and Asian (3%). Patients are largely middle-class, employed people or their dependents with private insurance coverage primarily through HMO- or PPO-type plans. Adult and adolescent patients with epilepsy seeking neurologic care are referred to the centralized neurology clinic location (KS clinic) where there are five general neurologists, one epileptologist, and a nurse epilepsy specialist. The neurology department cares for about 400 patients aged three and older with epilepsy per year.

The Ben Taub Epilepsy Clinic (BT clinic) was originally located at Ben Taub General Hospital, one of three public hospitals in Houston. During MINDSET development the clinic moved to the Smith clinic at Harris Health. Patients in the neurology clinic are primarily Hispanic (40%), low-income, uninsured, and covered by Medicaid, and are referred from one of the 12 community health centers operated by the public hospital system throughout Harris County. The clinic is staffed by faculty, residents, and medical students from the Baylor College of Medicine. About 30–40 patients are seen on a typical clinic day by medical residents and students who rotate through the clinic under the supervision of attending faculty.

The University of Texas Physicians-Neurology Clinic (UT clinic) is a large multi-specialty neurology clinic located in the Texas Medical Center (central Houston). The clinic is a tertiary care referral center for neurological disorders, including the diagnosis of epilepsy and the management of difficult epilepsy. The patients are diverse in terms of economic status and financial coverage for healthcare and are classified as follows: 58% commercially managed care, 7% Medicaid, 31% Medicare, 2% self-pay, and 2% others (i.e., worker's comp). The race/ethnicity breakdown for established patients with epilepsy is 14% African-American, 56% white, 4% Hispanic, 0.2% Asian, and 27% other or unknown. There are five epileptologists out of a faculty of 27 neurologists at the clinic. The patients are referred in from surrounding suburbs but also come from surrounding cities in Texas and from nearby states.

Information was gathered to inform the development of MINDSET including challenges for epilepsy self-management, the application of technology to epilepsy management, an understanding of methods and applications that might best be applied, and how this might best be implemented in the field. This knowledge had immediate pragmatic application in informing the development of matrices of program objectives (Step 2 of IM). Knowledge acquisition comprised deductive and inductive approaches. Deductive approaches included a review of the literature and consideration of theories and models amenable to informing self-management intervention in chronic disease. Inductive approaches included empirical investigation of the association of self-management antecedents with people with epilepsy in Houston clinics, ongoing qualitative and quantitative enquiry with the patient-provider advisory group, and clinic-based system task analysis (described in Step 4).

To develop a decision support tool for identifying patient self-management needs based on clinical, behavioral, and psychosocial variables we needed to identify clinical, behavioral, and psychosocial antecedents related to poor self-management and low medical adherence as well as to identify what other instruments/tools might be in use in the field. The research team developed appropriate problem statements, identified relevant databases, formulated database search strategies, and recommended an approach to synthesizing the literature. Data abstraction forms were developed and pilot-tested before they were used to abstract data from the identified relevant studies. Abstracted data were used to create evidence and information tables for expert review.