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

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Quantifying Quality of Life

Describes technological methods and tools for objective and quantitative assessment of QoL Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods This open access book presents the rise of technology-enabled methods and tools for objective, quantitative assessment of Quality of Life (QoL), while following the WHOQOL model. It is an in-depth resource describing and examining state-of-the-art, minimally obtrusive, ubiquitous technologies. Highlighting the required factors for adoption and scaling of technology-enabled methods and tools for QoL assessment, it also describes how these technologies can be leveraged for behavior change, disease prevention, health management and long-term QoL enhancement in populations at large. Quantifying Quality of Life: Incorporating Daily Life into Medicine fills a gap in the field of QoL by providing assessment methods, techniques and tools. These assessments differ from the current methods that are now mostly infrequent, subjective, qualitative, memory-based, context-poor and sparse. Therefore, it is an ideal resource for physicians, physicians in training, software and hardware developers, computer scientists, data scientists, behavioural scientists, entrepreneurs, healthcare leaders and administrators who are seeking an up-to-date resource on this subject

Английский язык для биологии и медицины: бакалавров и магистров

Терминология в условиях ускорения научно-технического прогресса приобретает особое значение. Она является источником получения информации, инструментом освоения специальности. Любая область науки и техники находит своё выражение в терминах. Практически нет ни одной области знания, которая изучается, не владея терминологией. Медицинская терминология является одним из специфических пластов лексики, которая в силу особенностей структурно-семантического, словообразовательного и стилистического характера отличается от общеупотребительных слов и занимает особое место в лексической системе языка. Медицинская терминология – это пласт лексического фонда со своими специфическими особенностями, ибо в каждом профессиональном подъязыке существует номенклатурная лексика, соотносимая с определенными реалиями и объектами. Особенность словарного состава терминологии заключается в том, что её номены представлены в ней шире, многообразнее, чем в других лексических подсистемах. Выбор английского языка в качестве второго языка сопоставительного исследования обусловлен его все возрастающей коммуникативной ролью в мировом сообществе, популярностью, сегодняшней жизненной необходимостью. Учебник предназначен для бакалавров и магистров в сфере биологии и медицины. Он состоит из 4 глав и параграфов. В каждой главе дается целый ряд основных лексических номенов, помогающие понять сложные тексты из неадаптированных источников этой сферы. Также прилагается несколько десятков упражнений для лучшего понимания и усвоения данного материала. Красочные иллюстрации наглядно демонстрируют основные положения и понятия в сфере биологии и медицины

Bowdoin Orient v.133, no.1-25 (2001-2002)

https://digitalcommons.bowdoin.edu/bowdoinorient-2000s/1002/thumbnail.jp

Bowdoin Orient v.137, no.1-25 (2007-2008)

https://digitalcommons.bowdoin.edu/bowdoinorient-2000s/1008/thumbnail.jp