Objective: To describe the implementation of technological support important for optimizing clinical management of the COVID-19 pandemic.
Materials and Methods: Our health system has confirmed prior and current cases of COVID-19. An Incident
Command Center was established early in the crisis and helped identify electronic health record (EHR)-based tools to support clinical care.
Results: We outline the design and implementation of EHR-based rapid screening processes, laboratory testing, clinical decision support, reporting tools, and patient-facing technology related to COVID-19.
Discussion: The EHR is a useful tool to enable rapid deployment of standardized processes. UC San Diego Health built multiple COVID-19-specific tools to support outbreak management, including scripted triaging, electronic check-in, standard ordering and documentation, secure messaging, real-time data analytics, and telemedicine capabilities. Challenges included the need to frequently adjust build to meet rapidly evolving requirements, communication, and adoption, and to coordinate the needs of multiple stakeholders while maintaining high-quality, prepandemic medical care.
Conclusion: The EHR is an essential tool in supporting the clinical needs of a health system managing the COVID-19 pandemic
Writing the proposal of a research work in the present era is a challenging task due to the constantly evolving trends in the qualitative research design and the need to incorporate medical advances into the methodology. The proposal is a detailed plan or ‘blueprint’ for the intended study, and once it is completed, the research project should flow smoothly. Even today, many of the proposals at post‑graduate evaluation committees and application proposals for funding are substandard. A search was conducted with keywords such as research proposal, writing proposal and qualitative using search engines, namely, PubMed and Google Scholar, and an attempt has been made to provide broad guidelines for writing a scientifically appropriate research proposal.
Background: A personal health record (PHR) system encourages patients to engage with their own health care by giving them the ability to manage and keep track of their own health data. Of the numerous PHR systems available in the market, many are Web-based patient portals and a few are mobile apps. They have mainly been created by hospitals and electronic health record (EHR) vendors. One major limitation of these hospital-created PHR systems is that patients can only view specific health data extracted from their EHR. Patients do not have the freedom to add important personal health data they collect in their daily lives into their PHR. Therefore, there is an information gap between clinical visits. Objective: The aim of this study was to develop and evaluate a new mobile PHR app that can be easily used to manage various types of personal health data to fill the information gap. Methods: A user-centered approach was used to guide the development and evaluation of the new mobile PHR app. There were three steps in this study: needs assessment, app design and development, and conducting a usability study. First, a large-scale questionnaire study was conducted with the general population to gain an understanding of their needs and expectations with regard to a mobile PHR app. A mobile PHR app for personal medical data tracking and management was then created based on the results of the questionnaire study. End users were actively involved in all stages of the app development. Finally, a usability study was performed with participants to evaluate the usability of the mobile PHR app, which involved asking participants to finish a set of tasks and to respond to a usability questionnaire. Results: In the questionnaire study for needs assessment, there were 609 participants in total. The answers from these participants revealed that they wanted to manage various types of personal health data in a mobile PHR app. Participants also reported some features they desired to have in the app. On the basis of the needs assessment findings, a new mobile PHR app (PittPHR) was created with 6 major modules: health records, history, trackers, contacts, appointments, and resources. This app allows users to customize the trackers according to their needs. In the usability study, there were 15 participants. The usability study participants expressed satisfaction with the app and provided comments and suggestions for further development. Conclusions: This new mobile PHR app provides options for users to manage a wide range of personal health data conveniently in one place. The app fills the information gap between clinical visits. The study results indicated that this new mobile PHR app
meets the need of users and that users welcome this app.
Preventing potential drug-drug interactions through alerting decision support systems: A clinical context based methodology-2019
The effectiveness of the clinical decision support systems (CDSSs) is hampered by frequent workflow interruptions and alert fatigue because of alerts with little or no clinical relevance. In this paper, we reported a methodology through which we applied knowledge from the clinical context and the international recommendations to develop a potential drug-drug interaction (pDDI) CDSS in the field of kidney transplantation. Methods: Prescriptions of five nephrologists were prospectively recorded through non-participatory observations for two months. The Medscape multi-drug interaction checker tool was used to detect pDDIs. Alongside the Stockley’s drug interactions reference, our clinicians were consulted with respect to the clinical relevance of detected pDDIs. We performed semi-structured interviews with five nephrologists and one informant nurse. Our clinically relevant pDDIs were checked with the Dutch “G-Standard”. A multidisciplinary team decided the design characteristics of pDDI-alerts in a CDSS considering the international recommendations and the inputs from our clinical context. Finally, the performance of the CDSS in detecting DDIs was evaluated iteratively by a multidisciplinary research team. Results: Medication data of 595 patients with 788 visits were collected and analyzed. Fifty-two types of interactions were most common, comprising 90% of all pDDIs. Among them 33 interactions (comprising 77% of all pDDIs) were rated as clinically relevant and were included in the CDSS’s knowledge-base. Of these pDDIs, 73% were recognized as either pseudoduplication of drugs or not a pDDI when checked with the Dutch G-standard. Thirty-three alerts were developed and physicians were allowed to customize the appearance of pDDI-alerts based on a proposed algorithm. Conclusion: Clinical practice contexts should be studied to understand the complexities of clinical work and to learn the type, severity and frequency of pDDIs. In order to make the alerts more effective, clinicians’ points of view concerning the clinical relevance of pDDIs are critical. Moreover, flexibility should be built into a pDDI-CDSS to allow clinicians to customize the appearance of pDDI-alerts based on their clinical context.
Background: To have an optimal hospital information system, performance indicators used for evaluation must be recognized. Since defining proper performance indicators is one of the important principles in benchmarking. This study aimed to identify key indicators of hospital information system performance benchmarking. Methods: This qualitative content analysis study was conducted in 2016-2017. The study population consisted of experts working in hospital Information Technology and data processing units in Tehran Province Social Security Hospitals (110). The present study was conducted in 3 stages using interview and focused group discussion. In the first stage, a review of the literature was carried out to collect the benchmarking indexes of the hospital information system. Then performance indicators were identified using the targeted snowball sampling. The experts were selected and identified by performance indicators. The data analysis method was conducted as a qualitative content analysis in the interview. The results of the third stage indicated confirmation of the identified main themes and sub- themes in the first stage and categorization of indicators. Results: The identified indicators for optimization and benchmarking of hospital information system were classified into 9 main themes and 121 sub-themes in three key groups of structure, process and results. The data analysis method was conducted as a qualitative content analysis in the interview. In the last stage, the results were organized and classified into 3 main categories of structure, process and results through focused group discussion. Conclusion: The results of this study can be used as a basis for quality improvement in evaluation process of hospital information systems. By planning to improve the indicators, it is expected to have quality improvement and productivity in the system.
Background: Nutrition and diet apps represent today a popular area of mobile health (mHealth), offering the possibility of delivering behavior change (BC) interventions for healthy eating and weight management in a scalable and cost-effective way. However, if commercial apps for pediatric weight management fail to retain users because of a lack of theoretical background and evidence-based content, mHealth apps that are more evidence-based are found less engaging and popular among consumers. Approaching the apps development process from a multidisciplinary and user-centered design (UCD) perspective is likely to help overcome these limitations, raising the chances for an easier adoption and integration of nutrition education apps within primary care interventions. Objective: The aim of this study was to describe the design and development of the TreC-LifeStyle nutrition education app and the results of a formative evaluation with families. Methods: The design of the nutrition education intervention was based on a multidisciplinary UCD approach, involving a team of BC experts, working with 2 nutritionists and 3 pediatricians from a primary care center. The app content was derived from evidence-based knowledge founded on the Food Pyramid and Mediterranean Diet guidelines used by pediatricians in primary care. A formative evaluation of the TreC-LifeStyle app involved 6 families of overweight children (aged 7-12 years) self-reporting daily food intake of children for 6 weeks and providing feedback on the user experience with the mHealth intervention. Analysis of the app’s usage patterns during the intervention and of participants’ feedback informed the refinement of the app design and a tuning of the nutrition education strategies to improve user engagement and compliance with the intervention. Results: Design sessions with the contribution of pediatricians and nutritionists helped define the nutrition education app and intervention, providing an effective human and virtual coaching approach to raise parents’ awareness about children’s eating behavior and lifestyle. The 6 families participating in the pilot study found the app usable and showed high compliance with the intervention over the 6 weeks, but analysis of their interaction and feedback showed the need for improving some of the app features related to the BC techniques “monitoring of the behavior” and “information provision.” Conclusions: The UCD and formative evaluation of TreC-LifeStyle show that nutrition education apps are feasible and acceptable solutions to support health promotion interventions in primary care.
Background: The current landscape of a rapidly aging population accompanied by multiple chronic conditions presents numerous challenges to optimally support the complex needs of this group. Mobile health (mHealth) technologies have shown promise in supporting older persons to manage chronic conditions; however, there remains a dearth of evidence-informed guidance to develop such innovations.
Objectives: The purpose of this study was to conduct a scoping review of current practices and recommendations for designing, implementing, and evaluating mHealth technologies to support the management of chronic conditions in community-dwelling older adults. Methods: A 5-stage scoping review methodology was used to map the relevant literature published between January 2005 and March 2015 as follows: (1) identified the research question, (2) identified relevant studies, (3) selected relevant studies for review, (4) charted data from selected literature, and (5) summarized and reported results. Electronic searches were conducted in 5 databases. In addition, hand searches of reference lists and a key journal were completed. Inclusion criteria were research and nonresearch papers focused on mHealth technologies designed for use by community-living older adults with at least one chronic condition, or health care providers or informal caregivers providing care in the home and community setting. Two reviewers independently identified articles for review and extracted data. Results: We identified 42 articles that met the inclusion criteria. Of these, described innovations focused on older adults with specific chronic conditions (n=17), chronic conditions in general (n=6), or older adults in general or those receiving homecare services (n=18). Most of the mHealth solutions described were designed for use by both patients and health care providers or health care providers only. Thematic categories identified included the following: (1) practices and considerations when designing mHealth technologies; (2) factors that support/hinder feasibility, acceptability, and usability of mHealth technologies; and (3) approaches or methods for evaluating mHealth technologies. Conclusions: There is limited yet increasing use of mHealth technologies in home health care for older adults. A user-centered, collaborative, interdisciplinary approach to enhance feasibility, acceptability, and usability of mHealth innovations is imperative. Creating teams with the required pools of expertise and insight regarding needs is critical. The cyclical, iterative process of developing mHealth innovations needs to be viewed as a whole with supportive theoretical frameworks. Many barriers to implementation and sustainability have limited the number of successful, evidence-based mHealth solutions beyond the pilot or feasibility stage. The science of implementation of mHealth technologies in home-based care for older adults and self-management of chronic conditions are important areas for further research. Additionally, changing needs as cohorts and technologies advance are important considerations. Lessons learned from the data and important implications for practice, policy, and research are discussed to inform the future development of innovations.
Background: To design and test a web-based self-management tool for patients with type 2 diabetes for its usability and feasibility. Methods: An evidence-based, theory-driven website was created for patients with type 2 diabetes. Twenty-three patients with type 2 diabetes aged ≥ 25 years were recruited from 2 diabetes care centers in Toronto, Canada. We employed focus group methodology to assess acceptability, sustainability, strengths and weaknesses of the self-management website. Based on these results, revisions were made to the website. Three cycles of individual usability testing sessions using cognitive task analysis were conducted with patients with type 2 diabetes. Revisions to the website were made based on results from this testing. Results: We identified five themes concerning participants’ experiences of health care and related unmet needs: 1) Desire for information and for greater access to timely and personalized care to gain a sense of control of their disease; 2) Desire for community (sharing experiences with others) to fulfill practical and emotional needs; 3) Potential roles of an online self-management website in self-empowerment, behavior change, self-management and health care delivery; 4) Importance of a patient-centered perspective in presenting content (e.g. common assumptions, medical nomenclature, language, messaging, sociocultural context); 5) Barriers and facilitators to use of a self-management website (including perceived relevance of content, incorporation into usual routine, availability for goal-directed use, usability issues). Conclusions: Participants outlined a series of unmet health care needs, and stated that they wanted timely access to tailored knowledge about their condition, mechanisms to control and track their disease, and opportunities to share experiences with other patients. These findings have implications for patients with type 2 diabetes of diverse ages, socioeconomic backgrounds, and disease severity, as well as to the design of other computer-based resources for chronic disease management.
Background: Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods: 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results: Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions: Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.
Abstract. Model driven software engineering (MDSE) is an emerging methodology for software development, targeting productivity, exibility and reliability of systems; metamodelling is at the core of most MDSE approaches. Due to their complexity and plethora of requirements placed upon them, healthcare systems so far have not been adequately modeled; as a result the software developed for them suffers from high develop- ment costs and lack of exibility, and its reliability is at risk. Here we propose a metamodelling approach that captures the complexity of these systems by using a metamodelling hierarchy, built from ve metamod- els, one each for user access modelling, health process modelling, process monitoring, user interface modelling and modelling of the data sources. These metamodels are coordinated with morphisms. Such a hierarchy allows us to adequately reflect the behavior and complexities of systems and how they interact with different stakeholders. We give details of some of the metamodels and present some suggestions for some different interfaces intended for two different users: the clinicians and the patients.
Care process monitoring is needed to provide performance management reporting to measure how quality of care goals are being met for a specific care process. There are special challenges faced when monitoring community care processes, especially if one wants to manage performance for community care across an entire geographic region. In this paper, we evaluate an application meta-model for defining a care process monitoring application (CPMA) previously developed for monitoring care processes in a hospital, to determine its effectiveness for addressing community care processes. A case study developed in collaboration with a regional health authority is used.
Background and objective: Patients undergoingweight loss treatment require follow-up as part of the treatment process. E-health solutions may be used for this purpose. We have used an iterative design approach to develop a patient-centred e-health solution for patients undergoing weight loss treatment. Our objective is to describe and report on the design process and suggest implications for human-centred design of such systems. Methods: Human-centred design methods were assessed as part of the design process. The process involved a field study to gain domain knowledge, followed by needs assessment through a series of participatory design workshops, and system evaluation through a workshop and a number of usability tests before system implementation. Results: By using an iterative design approach and by involving patients and healthcare professionals throughout the process, letting them hold the roles as informants, design partners, testers and users, we could reveal important aspects throughout the design process that are crucial for system realization and user acceptance. We found that weight loss patients are vulnerable, requiring that designers take special care when involving them in the design process. Our findings imply that involving stakeholders separately during specific human-centred activities is important in order to capture subtle, but critical aspects of the users’ requirements. Conclusion: Applying human-centred methods in the design of e-health solutions requires that designers must take particular considerations when patients and healthcare professionals are involved in the design process.
Abstract: An increase in the use of digital images in medicine and medical research has resulted in petabytes of digital images acquired each year. As more information is collected, there is a greater need to store, share, and retrieve images from various medical imaging modalities. Web-based medical image data management systems have been created to solve many issues caused by the Picture Archiving and Communication System (PACS). Five such medical image database systems are reviewed in this work. Though these systems have various features, they seem to fail to capture experimental design specifications necessary for the proper interpretation of the associated images. We summarize the paper by indicating a wish list of the features that are missing from these systems.
A health information system (HIS) is the intersection of between healthcare’s business process, and information systems to deliver better healthcare services. The nature of healthcare industry, which is highly influenced by economic, social, politic, and technological factors, has changed over time. This paper will address some important concepts of healthcare and related terminologies to provide a holistic view for HIS. Related technological milestones and major events are briefly summarized. The trends and rapid development of health information technologies are also discussed.
Background and objectives: The expansion of evidence-based practice across sectors has lead to an increasing variety of review types. However, the diversity of terminology used means that the full potential of these review types may be lost amongst a confusion of indistinct and misapplied terms. The objective of this study is to provide descriptive insight into the most common types of reviews, with illustrative examples from health and health information domains. Methods : Following scoping searches, an examination was made of the vocabulary associated with the literature of review and synthesis (literary warrant). A simple analytical framework—Search, AppraisaL, Synthesis and Analysis (SALSA)—was used to examine the main review types. Results : Fourteen review types and associated methodologies were analysed against the SALSA framework, illustrating the inputs and processes of each review type. A description of the key characteristics is given, together with perceived strengths and weaknesses. A limited number of review types are currently utilized within the health information domain. Conclusions : Few review types possess prescribed and explicit methodologies and many fall short of being mutually exclusive. Notwithstanding such limitations, this typology provides a valuable reference point for those commissioning, conducting, supporting or interpreting reviews, both within health information and the wider health care domain.