Smart Interventions for Effective Medication Adherence

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes

Smart Interventions for Effective Medication Adherence

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes

Mind the gulfs: An analysis of medication-related cognitive artifacts used by older adults with heart failure

Medication management is a patient health-related activity characterized by poor performance in older adults with chronic disease. Interventions focus on educating and motivating the patient with limited long-term effects. Cognitive artifacts facilitate cognitive tasks by making them easier, faster, and more effective and can potentially improve medication management performance. This study examined how older adult patients with heart failure use cognitive artifacts and how representational structure and physical properties facilitated or impeded medication-related tasks and processes. Interview, observation, medical record, and photographic data of and about older patients with heart failure (N = 30) and their informal caregivers (N=14) were content analyzed for cross-cutting themes about patient goals, representations, and actions. Results illustrated patient artifacts designed from a clinical rather than patient perspective, disparate internal and external representations threatening safety, and incomplete information exchange between patients and clinicians. Implications for design were the need for bridging artifacts, automatic information transfer, and cognitive artifacts designed from the perspective of the patient

How Disease Burden Influences Medication Patterns for Medicare Beneficiaries: Implications for Policy

Provides benchmarks for assessing the quality of pharmaceutical care under the Medicare Part D prescription drug benefit. Examines how the beneficiaries? medication regimens evolve in the context of multiple chronic conditions and accumulating morbidity

The Feasibility of a Using a Smart Button Mobile Health System to Self-Track Medication Adherence and Deliver Tailored Short Message Service Text Message Feedback

BACKGROUND: As many as 50% of people experience medication nonadherence, yet studies for detecting nonadherence and delivering real-time interventions to improve adherence are lacking. Mobile health (mHealth) technologies show promise to track and support medication adherence. OBJECTIVE: The study aimed to evaluate the feasibility and acceptability of using an mHealth system for medication adherence tracking and intervention delivery. The mHealth system comprises a smart button device to self-track medication taking, a companion smartphone app, a computer algorithm used to determine adherence and then deliver a standard or tailored SMS (short message service) text message on the basis of timing of medication taking. Standard SMS text messages indicated that the smartphone app registered the button press, whereas tailored SMS text messages encouraged habit formation and systems thinking on the basis of the timing the medications were taken. METHODS: A convenience sample of 5 adults with chronic kidney disease (CKD), who were prescribed antihypertensive medication, participated in a 52-day longitudinal study. The study was conducted in 3 phases, with a standard SMS text message sent in phases 1 (study days 1-14) and 3 (study days 46-52) and tailored SMS text messages sent during phase 2 (study days 15-45) in response to participant medication self-tracking. Medication adherence was measured using: (1) the smart button and (2) electronic medication monitoring caps. Concordance between these 2 methods was evaluated using percentage of measurements made on the same day and occurring within ±5 min of one another. Acceptability was evaluated using qualitative feedback from participants. RESULTS: A total of 5 patients with CKD, stages 1-4, were enrolled in the study, with the majority being men (60%), white (80%), and Hispanic/Latino (40%) of middle age (52.6 years, SD 22.49; range 20-70). The mHealth system was successfully initiated in the clinic setting for all enrolled participants. Of the expected 260 data points, 36.5% (n=95) were recorded with the smart button and 76.2% (n=198) with electronic monitoring. Concordant events (n=94), in which events were recorded with both the smart button and electronic monitoring, occurred 47% of the time and 58% of these events occurred within ±5 min of one another. Participant comments suggested SMS text messages were encouraging. CONCLUSIONS: It was feasible to recruit participants in the clinic setting for an mHealth study, and our system was successfully initiated for all enrolled participants. The smart button is an innovative way to self-report adherence data, including date and timing of medication taking, which were not previously available from measures that rely on recall of adherence. Although the selected smart button had poor concordance with electronic monitoring caps, participants were willing to use it to self-track medication adherence, and they found the mHealth system acceptable to use in most cases

Medication-related cognitive artifacts used by older adults with heart failure

OBJECTIVE: To use a human factors perspective to examine how older adult patients with heart failure use cognitive artifacts for medication management. METHODS: We performed a secondary analysis of data collected from 30 patients and 14 informal caregivers enrolled in a larger study of heart failure self-care. Data included photographs, observation notes, interviews, video recordings, medical record data, and surveys. These data were analyzed using an iterative content analysis. RESULTS: Findings revealed that medication management was complex, inseparable from other patient activities, distributed across people, time, and place, and complicated by knowledge gaps. We identified fifteen types of cognitive artifacts including medical devices, pillboxes, medication lists, and electronic personal health records used for: 1) measurement/evaluation; 2) tracking/communication; 3) organization/administration; and 4) information/sensemaking. These artifacts were characterized by fit and misfit with the patient's sociotechnical system and demonstrated both advantages and disadvantages. We found that patients often modified or "finished the design" of existing artifacts and relied on "assemblages" of artifacts, routines, and actors to accomplish their self-care goals. CONCLUSIONS: Cognitive artifacts are useful but sometimes are poorly designed or are not used optimally. If appropriately designed for usability and acceptance, paper-based and computer-based information technologies can improve medication management for individuals living with chronic illness. These technologies can be designed for use by patients, caregivers, and clinicians; should support collaboration and communication between these individuals; can be coupled with home-based and wearable sensor technology; and must fit their users' needs, limitations, abilities, tasks, routines, and contexts of use

Activity Theory Analysis of Heart Failure Self-Care

The management of chronic health conditions such as heart failure is a complex process emerging from the activity of a network of individuals and artifacts. This article presents an Activity Theory-based secondary analysis of data from a geriatric heart failure management study. Twenty-one patients' interviews and clinic visit observations were analyzed to uncover eight configurations of roles and activities involving patients, clinicians, and others in the sociotechnical network. For each configuration or activity pattern, we identify points of tension and propose guidelines for developing interventions for future computer-supported healthcare systems

Designing an Artifact to Support Incentives for Medication Adherence

This research is motivated by the current trend towards utilization of mobile technology in healthcare interventions. Despite academic and practitioner efforts, lack of medication adherence continues to be a leading indicator of poor health outcomes and increased hospitalizations worldwide. There are several possible incentive systems that remain relatively unexplored in the field of medication adherence. Our analysis of the current academic research and existing medication adherence applications indicates a research gap and an opportunity to create a significant contribution through the design of an application (app) addressing the complex problem of medication adherence. Therefore, we propose the design of an app to positively influence patient behavior through incentives to improve medication adherence. The contribution of this research is a novel design utilizing multiple incentive types to improve medication adherence

Leveraging Knowledge-Based Approaches to Promote Antiretroviral Toxicity Monitoring in Underserved Settings

As access and use of antiretroviral therapy continue to increase, the need to improve antiretroviral toxicity monitoring becomes more critical. This is particularly so in underserved settings, where patterns of antiretroviral toxicities possibly alter the need for and frequency of antiretroviral toxicity monitoring. However, barriers such as few skilled healthcare providers and poor infrastructure make antiretroviral toxicity monitoring in underserved settings difficult. The purpose of this dissertation was to investigate how standard clinical guidelines, knowledge-based clinical decision support, and task delegation could be leveraged to overcome barriers to antiretroviral toxicity monitoring in underserved settings. The strategy adopted in this dissertation was guided by the Design Science Research Methodology that emphasizes the generation of scientific knowledge through building novel artifacts. Two qualitative descriptive studies were conducted to characterize the contextual factors associated with antiretroviral toxicity monitoring in underserved settings. Supported by the findings from these studies, a knowledge-based software application prototype that implements clinical practice guidelines for antiretroviral toxicity monitoring was developed. Next, a quantitative validation study was used to evaluate the structure and behavior of the prototype’s knowledge base. Lastly, a quantitative usability study was conducted to assess lay health worker perceptions of the satisfaction and mental effort associated with the use of checklists generated by the prototype. This dissertation research produced empirical evidence about the broad motives and strategies for promoting medication adherence, safety, and effectiveness in underserved settings. It also identified barriers and facilitators of antiretroviral toxicity monitoring within ambulatory HIV care workflows in underserved settings. Additionally, it provided evidence about the extent to which antiretroviral toxicity domain knowledge could be implemented in a knowledge-based application for supporting point-of-care antiretroviral toxicity monitoring. Lastly, the research provided previously unavailable empirical evidence about the perceptions of lay peer health workers on the use of checklists for the documentation of antiretroviral toxicities

A Systems-Based Patient Aid Design Artifact for Active Medication Management in Type 2 Diabetes

In this dissertation, I explore the use of the Abstraction-Decomposition Space (ADS) alongside Hierarchical Task Analysis (HTA) to guide the design of a minimalist patient aid for active medication management in type 2 diabetes. The goal is to address a practical problem, but in addition, this study seeks to address a theoretical problem that is prevalent in design research in Information Systems (IS) today. The practical problem concerns the need for IT-based care delivery models to support patients in the interim period between in-person visits. In this vein, I present a bare-minimum design that focuses on the most essential functionality required to achieve remote insulin titration using the ADS and HTA. The theoretical problem, on the other hand, pertains to the limitations resulting from taking a tool-focused view in design research which inhibits our ability to produce generalized knowledge about IT systems in their contexts. The study proposes an alternative view based on work systems. The overarching thesis is that a work systems view provides for knowledge at a more abstract and generalizable level, yielding contributions beyond mere software packages. Moreover, the study highlights the artifact-building methodology used to delineate the rationale behind the design and to balance evaluation-dominant design research. In this vein, I conducted document analysis and semi-structured interviews with patients and care providers to develop the ADS, then used it alongside HTA to develop and test the usability of twelve user scenarios implemented on a large mobile form factor