IT-based Patient Interventions for Opioid Abuse: Evaluation using Analytical Model

The number of people in the US with opioid abuse exceeds 2 million and the total cost is approximately $100B per year. In this study, we focus on patient-level interventions and present three IT-based interventions: (a) mobile reminders, (b) electronic monitoring, and (c) composite intervention. We have developed an analytical model for evaluating interventions using Return-on-Investment (ROI). The interventions are cost-effective for higher values of intervention effectiveness, hospital, and emergency room cost. However, with QoL improvement, cost-effectiveness improves significantly. We also explored the use of financial incentives for increasing the adoption of interventions. These results will help patients, healthcare professionals, decision-makers, and family members to choose the most suitable intervention to address opioid abuse

Opioid Use Disorder: Studying Quality of Life with IT-based Interventions

Opioid Use Disorder (OUD) has become a major public health challenge. There have been several interventions, including those based on health-IT, proposed recently. There is a major need to study these interventions. We are interested in exploring how different IT-based interventions impact opioid related Quality of Life. We developed a model using Markov chain for three different states in OUD. The model and results can lead to better decision making by healthcare professionals, patients and insurance companies. More specifically, the proposed model and results can help in (a) whether to prescribe opioids to different types of patients, (b) what IT-based interventions are suitable with an opioid prescription, and (c) how patients and healthcare professionals can select an intervention out of multiple available interventions

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

The role of mobile technologies in health care processes:The case of cancer supportive care

Background: Health care systems are gradually moving towards new models of care based on integrated care processes, shared by different care givers, and on an empowered role of the patient. Mobile technologies are assuming an emerging role in this scenario. This is particularly true in care processes where the patient has a particularly enhanced role, as is the case of cancer supportive care. Objective: This paper aims to review existing studies on the actual role and use of mobile technology during the different stages of care processes, with particular reference to cancer supportive care. Methods: We carried out a review of literature with the aim of identifying studies related to the use of mhealth in cancer care and cancer supportive care. The final sample size consists in 106 records. Results: There is scant literature concerning the use of mhealth in cancer supportive care. Looking more generally at cancer care, we found that mhealth is mainly used for self management activities carried out by patients. The main tools used are mobile devices like smartphones and tablets, but remote monitoring devices also play an important role. SMS technologies have a minor role with the exception of middle income-countries where SMS plays a major role. Tele-health technologies are still rarely used in cancer care processes. If we look at the different stages of health care processes, we can see that mhealth is mainly used during the treatment of patients, especially for self management activities. It is also used for prevention and diagnosis, although to a lesser extent, whereas it appears rarely used for decision-making and follow-up activities. Conclusions: Since mhealth only seems to be employed for limited uses and during limited phases of the care process, it is unlikely that it can really contribute to the creation of new care models. This under-utilization may depend on many issues, including the need for it to be embedded into broader information systems. If the purpose of introducing mhealth is to promote the adoption of integrated care models, using mhealth should not be limited to some activities or to some phases of the health care process. Instead, there should be a higher degree of pervasiveness at all stages and in all health care delivery activities

The performance of mHealth in cancer supportive care:A research agenda

Background: Since the advent of smartphones, mhealth has risen to the attention of all actors in the health care system as something that could radically change the way health care has been thought of, managed, and delivered to date. This is particularly relevant for cancer, as it is one of the leading causes of death worldwide, and for cancer supportive care (CSC) since patients and care givers have a key role in managing side effects: given adequate knowledge, they are able to expect appropriate assessments and interventions. In this scenario, mhealth has great potential for linking patients, care givers, and health care professionals, for enabling early detection and intervention, for lowering costs and achieving better quality of life. Given its great potential, it is important to evaluate the performance of mhealth. This can be considered from several perspectives, of which organizational performance is a particularly relevant dimension, since mhealth may increase the productivity of health care providers and as a result even the productivity of health care systems. Objective: This paper aims to review studies on the evaluation of the performance of mhealth, with particular focus on cancer care and cancer supportive care processes, concentrating on its contribution to organizational performance, and identifying some indications for a further research agenda. Methods: We carried out a review of literature, aimed at identifying studies related to the performance of mhealth in general or focusing on cancer care and cancer supportive care. Results: Our analysis revealed that studies are almost always based on a single dimension of performance. Any evaluations of the performance of mhealth are based on very different methods and measures, with a prevailing focus on issues linked to efficiency. This fails to consider the real contribution that mhealth can offer for improving the performance of health care providers, health care systems, and the quality of life in general

Determinants of Primary Nonadherence to Medications Prescribed by General Practitioners Among Adults in Hungary: cross-Sectional Evaluation of Health Insurance Data

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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

Transactions of 2019 International Conference on Health Information Technology Advancement Vol. 4 No. 1

The Fourth International Conference on Health Information Technology Advancement Kalamazoo, Michigan, October 31 - Nov. 1, 2019. Conference Co-Chairs Bernard T. Han and Muhammad Razi, Department of Business Information Systems, Haworth College of Business, Western Michigan University Kalamazoo, MI 49008 Transaction Editor Dr. Huei Lee, Professor, Department of Computer Information Systems, Eastern Michigan University Ypsilanti, MI 48197 Volume 4, No. 1 Hosted by The Center for Health Information Technology Advancement, WM