From data acquisition to data fusion : a comprehensive review and a roadmap for the identification of activities of daily living using mobile devices

This paper focuses on the research on the state of the art for sensor fusion techniques, applied to the sensors embedded in mobile devices, as a means to help identify the mobile device user’s daily activities. Sensor data fusion techniques are used to consolidate the data collected from several sensors, increasing the reliability of the algorithms for the identification of the different activities. However, mobile devices have several constraints, e.g., low memory, low battery life and low processing power, and some data fusion techniques are not suited to this scenario. The main purpose of this paper is to present an overview of the state of the art to identify examples of sensor data fusion techniques that can be applied to the sensors available in mobile devices aiming to identify activities of daily living (ADLs)

Personalized data analytics for internet-of-things-based health monitoring

The Internet-of-Things (IoT) has great potential to fundamentally alter the delivery of modern healthcare, enabling healthcare solutions outside the limits of conventional clinical settings. It can offer ubiquitous monitoring to at-risk population groups and allow diagnostic care, preventive care, and early intervention in everyday life. These services can have profound impacts on many aspects of health and well-being. However, this field is still at an infancy stage, and the use of IoT-based systems in real-world healthcare applications introduces new challenges. Healthcare applications necessitate satisfactory quality attributes such as reliability and accuracy due to their mission-critical nature, while at the same time, IoT-based systems mostly operate over constrained shared sensing, communication, and computing resources. There is a need to investigate this synergy between the IoT technologies and healthcare applications from a user-centered perspective. Such a study should examine the role and requirements of IoT-based systems in real-world health monitoring applications. Moreover, conventional computing architecture and data analytic approaches introduced for IoT systems are insufficient when used to target health and well-being purposes, as they are unable to overcome the limitations of IoT systems while fulfilling the needs of healthcare applications. This thesis aims to address these issues by proposing an intelligent use of data and computing resources in IoT-based systems, which can lead to a high-level performance and satisfy the stringent requirements. For this purpose, this thesis first delves into the state-of-the-art IoT-enabled healthcare systems proposed for in-home and in-hospital monitoring. The findings are analyzed and categorized into different domains from a user-centered perspective. The selection of home-based applications is focused on the monitoring of the elderly who require more remote care and support compared to other groups of people. In contrast, the hospital-based applications include the role of existing IoT in patient monitoring and hospital management systems. Then, the objectives and requirements of each domain are investigated and discussed. This thesis proposes personalized data analytic approaches to fulfill the requirements and meet the objectives of IoT-based healthcare systems. In this regard, a new computing architecture is introduced, using computing resources in different layers of IoT to provide a high level of availability and accuracy for healthcare services. This architecture allows the hierarchical partitioning of machine learning algorithms in these systems and enables an adaptive system behavior with respect to the user's condition. In addition, personalized data fusion and modeling techniques are presented, exploiting multivariate and longitudinal data in IoT systems to improve the quality attributes of healthcare applications. First, a real-time missing data resilient decision-making technique is proposed for health monitoring systems. The technique tailors various data resources in IoT systems to accurately estimate health decisions despite missing data in the monitoring. Second, a personalized model is presented, enabling variations and event detection in long-term monitoring systems. The model evaluates the sleep quality of users according to their own historical data. Finally, the performance of the computing architecture and the techniques are evaluated in this thesis using two case studies. The first case study consists of real-time arrhythmia detection in electrocardiography signals collected from patients suffering from cardiovascular diseases. The second case study is continuous maternal health monitoring during pregnancy and postpartum. It includes a real human subject trial carried out with twenty pregnant women for seven months

Malnutrition is associated with six-month mortality in older patients admitted to the emergency department with hip fracture

Background: Hip fractures in older people are a common health problem often associated with malnutrition that might affect outcomes. Screening for malnutrition is not a routine examination in emergency departments (ED). This analysis of the EMAAge study, a prospective, multicenter cohort study, aimed to evaluate the nutritional status of older patients (>= 50 years) with hip fracture, factors associated with malnutrition risk, and the association between malnutrition and the six-months mortality. Methods: Risk of malnutrition was evaluated using the Short Nutritional Assessment Questionnaire. Clinical data as well as data on depression and physical activity were determined. Mortality was captured for the first six months after the event. To assess factors associated with malnutrition risk we used a binary logistic regression. A Cox proportional hazards model was used to assess the association of malnutrition risk with six-month survival adjusted for other relevant risk factors. Results: The sample consisted of N = 318 hip fracture patients aged 50 to 98 (68% women). The prevalence of malnutrition risk was 25.3% (n = 76) at the time of injury. There were no differences in triage categories or routine parameters measured in the ED that could point to malnutrition. 89% of the patients (n = 267) survived for six months. The mean survival time was longer in those without malnutrition risk (171.9 (167.1-176.9) days vs. 153.1 (140.0-166.2) days). The Kaplan Meier curves and the unadjusted Cox regression (Hazard Ratio (HR) 3.08 (1.61-5.91)) showed differences between patients with and patients without malnutrition risk. In the adjusted Cox regression model, risk of death was associated with malnutrition risk (HR 2.61, 1.34-5.06), older age (70-76 years: HR 2.5 (0.52-11.99); 77-82 years: HR 4.25 (1.15-15.62); 83-99 years: HR 3.82 (1.05-13.88)) and a high burden of comorbidities (Charlson Comorbidity Index >= 3: HR 5.4 (1.53-19.12)). Conclusion: Risk of malnutrition was associated with higher mortality after hip fracture. ED parameters did not differentiate between patients with nutritional deficiencies and those without. Therefore, it is particularly important to pay attention to malnutrition in EDs to detect patients at risk of adverse outcomes and to initiate early interventions

Information technologies for pain management

Millions of people around the world suffer from pain, acute or chronic and this raises the importance of its screening, assessment and treatment. The importance of pain is attested by the fact that it is considered the fifth vital sign for indicating basic bodily functions, health and quality of life, together with the four other vital signs: blood pressure, body temperature, pulse rate and respiratory rate. However, while these four signals represent an objective physical parameter, the occurrence of pain expresses an emotional status that happens inside the mind of each individual and therefore, is highly subjective that makes difficult its management and evaluation. For this reason, the self-report of pain is considered the most accurate pain assessment method wherein patients should be asked to periodically rate their pain severity and related symptoms. Thus, in the last years computerised systems based on mobile and web technologies are becoming increasingly used to enable patients to report their pain which lead to the development of electronic pain diaries (ED). This approach may provide to health care professionals (HCP) and patients the ability to interact with the system anywhere and at anytime thoroughly changes the coordinates of time and place and offers invaluable opportunities to the healthcare delivery. However, most of these systems were designed to interact directly to patients without presence of a healthcare professional or without evidence of reliability and accuracy. In fact, the observation of the existing systems revealed lack of integration with mobile devices, limited use of web-based interfaces and reduced interaction with patients in terms of obtaining and viewing information. In addition, the reliability and accuracy of computerised systems for pain management are rarely proved or their effects on HCP and patients outcomes remain understudied. This thesis is focused on technology for pain management and aims to propose a monitoring system which includes ubiquitous interfaces specifically oriented to either patients or HCP using mobile devices and Internet so as to allow decisions based on the knowledge obtained from the analysis of the collected data. With the interoperability and cloud computing technologies in mind this system uses web services (WS) to manage data which are stored in a Personal Health Record (PHR). A Randomised Controlled Trial (RCT) was implemented so as to determine the effectiveness of the proposed computerised monitoring system. The six weeks RCT evidenced the advantages provided by the ubiquitous access to HCP and patients so as to they were able to interact with the system anywhere and at anytime using WS to send and receive data. In addition, the collected data were stored in a PHR which offers integrity and security as well as permanent on line accessibility to both patients and HCP. The study evidenced not only that the majority of participants recommend the system, but also that they recognize it suitability for pain management without the requirement of advanced skills or experienced users. Furthermore, the system enabled the definition and management of patient-oriented treatments with reduced therapist time. The study also revealed that the guidance of HCP at the beginning of the monitoring is crucial to patients' satisfaction and experience stemming from the usage of the system as evidenced by the high correlation between the recommendation of the application, and it suitability to improve pain management and to provide medical information. There were no significant differences regarding to improvements in the quality of pain treatment between intervention group and control group. Based on the data collected during the RCT a clinical decision support system (CDSS) was developed so as to offer capabilities of tailored alarms, reports, and clinical guidance. This CDSS, called Patient Oriented Method of Pain Evaluation System (POMPES), is based on the combination of several statistical models (one-way ANOVA, Kruskal-Wallis and Tukey-Kramer) with an imputation model based on linear regression. This system resulted in fully accuracy related to decisions suggested by the system compared with the medical diagnosis, and therefore, revealed it suitability to manage the pain. At last, based on the aerospace systems capability to deal with different complex data sources with varied complexities and accuracies, an innovative model was proposed. This model is characterized by a qualitative analysis stemming from the data fusion method combined with a quantitative model based on the comparison of the standard deviation together with the values of mathematical expectations. This model aimed to compare the effects of technological and pen-and-paper systems when applied to different dimension of pain, such as: pain intensity, anxiety, catastrophizing, depression, disability and interference. It was observed that pen-and-paper and technology produced equivalent effects in anxiety, depression, interference and pain intensity. On the contrary, technology evidenced favourable effects in terms of catastrophizing and disability. The proposed method revealed to be suitable, intelligible, easy to implement and low time and resources consuming. Further work is needed to evaluate the proposed system to follow up participants for longer periods of time which includes a complementary RCT encompassing patients with chronic pain symptoms. Finally, additional studies should be addressed to determine the economic effects not only to patients but also to the healthcare system

Dynamic microsimulation of health care demand, health care finance and the economic impact of health behaviours: survey and review

This paper reviews the issues to be faced in attempting to create a microsimulation of health care demand, health care finance and the economic impact of health behaviour. These issues identified via an in-depth review of seven dynamic microsimulation models, selected from an initial set of 27 models in order to highlight the main differences in approaches and modelling options currently adopted. After presenting a brief description of each of the seven selected models, the main modelling approaches are summarized and critically appraised using five main distinguishing criteria. These criteria are the use of alignment techniques, model complexity (as reflected in the range of variables used), theoretical foundations, type of starting population, and the extent and detail of financial issues covered. Building upon this appraisal, the paper goes on to show how the ‘12 SAGE lessons’ apply in the field of health care microsimulation. The trade-off between complexity and predictive power is shown to be key. Finally an appendix summarises the main features of all 27 of the dynamic microsimulation models originally surveyed.health care, microsimulation

Creating the Organizational Capacity to Serve Families with Parental Mental Illness: The Implementation of Family Options

Summary: The purpose of this presentation is to present preliminary findings describing the organizational context of a traditionally adult-serving community mental health program, Employment Options, Inc., as they implement a family-centered, strengths-based intervention for families living with parental mental illness

Comparing total expenditures by source of long-term services and supports.

This study compares total expenditures between beneficiaries enrolled in traditional Long-Term Care (LTC) and beneficiaries enrolled in Home and Community Based Services (HCBS) in a Quasi-Experimental Simple Ex Post Facto study utilizing multiple linear regression with inverted propensity score weighting. The results demonstrated, during the two years of the study period, that total expenditures were on average $14,565.03 (with a p-value oflessfor the total two years of the study, for HCBS beneficiaries when compared to their LTC counterparts. There remains today a belief that expenditures of elderly, dual beneficiaries electing to age-in-place for supported self-care expend less than that of elderly, dual beneficiaries electing traditional institutional LTC. Of forty-one peer reviewed periodicals, there is one that supports that belief, all other literature supports a counter-intuitive reality that LTC is less costly. In, Q4 of 2013 Florida’s Medicaid agency, the Agency for Health Care Administration (AHCA) in collaboration with the state’s Department of Elder Affairs (DOEA) consolidated its six aging/elderly programs[1] into their new Statewide Medicaid Managed Care (SMMC)-Long-Term Care (LTC) program. AHCA outsourced these programs through competitive procurement to managed care organizations. Compared to previous studies this study has three unique distinctions: Composition of expenditure categories–Nine of the eleven other studies compared only LTC costs directly to only HCBS costs. This study includes seven expenditure categories: Ancillary; Institutional–Acute; Institutional–Other; LTSS; Miscellaneous; Pharmaceutical; and, Professional. Managed care programs–Florida’s SMMC-LTC program is MLTSS with reimbursement methodologies including capitated payment schedules, FFS, pay-for-performance and risk/value agreements; and, Application of a Domicile Adjustment–In an attempt to adjust for Medicaid’s ‘room and board’ benefit differences between the two cohorts’, a domicile adjustment of -$831.00 was developed and applied to each month of enrollment for each LTC beneficiary. [1] The State of Florida had six different aging/elderly programs that were consolidated into the SMMC_LTC program, those six programs were: Nursing Facilities, Aged and Disabled Adult waiver, Assisted Living waiver, Nursing Home Diversion waiver, Channeling waiver and Frail Elder option

Development And Validation Of A Predictive Model For Oncology Hospital-At-Home

Background: Hospital-at-Home (HaH) is a unique care model that allows for the provision of inpatient level care in the patient’s home. HaH has been used to facilitate early discharge from inpatient care or to substitute entirely for an inpatient admission. Hospital-at-Home has been shown to have similar clinical outcomes to inpatient care, while reducing cost and complications associated with inpatient admission. Application of the HaH model to patients with oncologic disease is a promising avenue to reduce healthcare costs while improving patients’ quality of life by increasing time spent at home. A major challenge to implementing a Hospital-at-Home program for cancer patients is the lack of validated criteria to inform the selection of admissions most suitable for home-based hospital level care. Methods and Results: Admissions to the Yale New Haven Smilow Cancer Hospital’s medical oncology floor in New Haven from Jan 2015- Jun 2019 were included in the analysis (N=3,322). The analysis focused entirely on patients with solid tumors hospitalized for unplanned admissions. The definition of suitability for HaH was based on a substitutive model and identified admissions that did not receive any services that would be difficult to deliver or were inconsistent with safe care in the home. Twenty-seven-point-three percent of admissions were identified as suitable for HaH, accounting for 908 admissions during the study period. Admissions that were suitable for HaH were shorter in duration (2.79 vs 6.41 days), more likely to result in discharge home rather than to other healthcare facility (87.5% vs 69.5%), and less likely to be readmitted in the following 30 days (25.3% vs 31.5%). A predictive logistic model constructed using a purposeful selection process identified 13 statistically significant predictors for suitability for HaH: Black/African American race (vs all other), observation status, patient evaluated in the emergency department (ED) or oncology extended care center (vs admitted directly from clinic), primary admission diagnosis of secondary malignancy, primary admission diagnosis of fever, primary admission diagnosis of digestive diseases, oncology diagnosis of secondary or unknown malignancy, initial pre-admission respiratory rate \u3e20 breaths/min, final pre-admission systolic blood pressure \u3c100 mmHg, final pre-admission temperature \u3e100o F, Sodium \u3c 135 mmol/L, hemoglobin \u3c10 g/dL and ED visit in the previous 90 days. The predictive model had moderate discrimination (c-statistic 0.686) and was well calibrated in the validation cohort (Hosmer-Lemeshow P-value \u3e0.05). Conclusion: We describe the first predictive model of suitability for Hospital-at-Home in oncology patients. This model serves as a starting point to creating selection criteria and can be further refined and tested in prospective validation and pilot studies. The modest discrimination of the model indicates that much of the variability that allows for accurate prediction is still unaccounted for and would benefit from larger studies and inclusion of clinician judgement

From Gatekeeping to Engagement: A Multicontextual, Mixed Method Study of Student Academic Engagement in Introductory STEM Courses.

The lack of academic engagement in introductory science courses is considered by some to be a primary reason why students switch out of science majors. This study employed a sequential, explanatory mixed methods approach to provide a richer understanding of the relationship between student engagement and introductory science instruction. Quantitative survey data were drawn from 2,873 students within 73 introductory science, technology, engineering, and mathematics (STEM) courses across 15 colleges and universities, and qualitative data were collected from 41 student focus groups at eight of these institutions. The findings indicate that students tended to be more engaged in courses where the instructor consistently signaled an openness to student questions and recognizes her/his role in helping students succeed. Likewise, students who reported feeling comfortable asking questions in class, seeking out tutoring, attending supplemental instruction sessions, and collaborating with other students in the course were also more likely to be engaged. Instructional implications for improving students' levels of academic engagement are discussed

Evolving reablement through occupational perspectives and welfare technology in home care

Rationale: Sweden is encountering dual societal challenges characterised by a rapidly ageing population and a diminishing home care workforce, leading to strained resources, which potentially can impact the quality of care. This situation poses a considerable risk to the health and overall well-being of older adults and home care staff. Innovative strategies are necessary to restructure the provision of home care services that promote healthy ageing and enable older adults to age in place. Reablement, as a rehabilitation approach, is recognized in other countries but is relatively new in Sweden. However, despite increased research, knowledge gaps and ambiguities persist regarding reablement’s theoretical foundation and key components. This knowledge is needed to increase transferability and facilitate successful implementations, thereby advancing the evolution of reablement. Aim: This thesis aims to contribute to the evolution of reablement in home care, using theory, occupational perspectives, and welfare technology to promote healthy ageing in place. Method: The four studies included in this thesis applied various methods to gain knowledge about different perspectives and prerequisites for reablement to evolve. Study I applied a quantitative approach where a questionnaire was sent out to 467 home care staff containing questions about their perceived psychosocial work environment and job strain. Data was analysed with descriptive and inferential statistics. Study II is a quasi-experimental, mixedmethod feasibility study of the reablement program ASSIST 1.0. Seven older adults and three home care staff participated in the program, and ten older adults participated in the control group and received ordinary home care. Quantitative data from clinical outcome measures were analysed with descriptive and inferential statistics, and interviews and field notes were transcribed and analysed according to a qualitative content analysis. Study III is a qualitative study containing nine interviews conducted with the three home care staff involved in ASSIST 1.0 to explore how theories and concepts can evolve the understanding of reablement. The interviews were analysed with Braun & Clarke’s reflexive thematic analysis. Study IV applies a mixed-method design to evaluate the usability and user experience of an information and communication technology system within a home care organization. Quantitative data consisted of test-based usability assessments and self-reported questionnaires, analysed with descriptive statistics. Qualitative data consisted of transcribed material from one focus group interview with six home care staff and three individual interviews with managers from the home care agency. Conclusion: The outcomes from the four studies lay the foundation for the discussion of this thesis, focusing on current reablement discourses and delving into three areas contributing to the evolution of reablement. The first two areas critically reflect on theories that can underpin reablement, strengthen the person-centred and holistic approach, and discuss why and how occupational perspectives can provide new outlooks for reablement. Combined, these two areas contribute to an evolved definition of reablement. The third area addresses why welfare technology is essential for enhancing the interprofessional and person-centred approach in reablement. Finally, it is proposed why reablement should be implemented in Sweden, advocating for a change in policies and guidelines for how home care can be reconstructed to facilitate healthy ageing in place