Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance.

Healthcare Outlier Payment Costs

The purpose of this project is to determine the cost of healthcare per individual depending on the amount of care needed.

Healthcare Costs: How Much Could a Hospital Make on Outlier Patients in Montana?

This poster illustrates hospital cost for outlier patients in Montana.

Strategic Emergency department design: An approach to capacity planning in healthcare provision in overcrowded emergency rooms

Healthcare professionals and the public have increasing concerns about the ability of emergency departments to meet current demands. Increased demand for emergency services, mainly caused by a growing number of minor and moderate injuries has reached crisis proportions, especially in the United Kingdom. Numerous efforts have been made to explore the complex causes because it is becoming more and more important to provide adequate healthcare within tight budgets. Optimisation of patient pathways in the emergency department is therefore an important factor. This paper explores the possibilities offered by dynamic simulation tools to improve patient pathways using the emergency department of a busy university teaching hospital in Switzerland as an example.

The lower quality of preventive care among forced migrants in a country with universal healthcare coverage

OBJECTIVE To assess the association between socio-demographic factors and the quality of preventive care and chronic care of cardiovascular (CV) risk factors in a country with universal health care coverage. METHODS Our retrospective cohort assessed a random sample of 966 patients aged 50-80years followed over 2years (2005-2006) in 4 Swiss university primary care settings (Basel/Geneva/Lausanne/Zürich). We used RAND's Quality Assessment Tools indicators and examined recommended preventive care among different socio-demographic subgroups. RESULTS Overall patients received 69.6% of recommended preventive care. Preventive care indicators were more likely to be met among men (72.8% vs. 65.4%; p<0.001), younger patients (from 71.0% at 50-59years to 66.7% at 70-80years, p for trend=0.03) and Swiss patients (71.1% vs. 62.7% in forced migrants; p=0.001). This latter difference remained in multivariate analysis adjusted for gender, age, civil status and occupation (OR 0.68; 95% CI 0.54-0.86). Forced migrants had lower scores for physical examination and breast and colon cancer screening (all p≤0.02). No major differences were seen for chronic care of CV risk factors. CONCLUSION Despite universal healthcare coverage, forced migrants receive less preventive care than Swiss patients in university primary care settings. Greater attention should be paid to forced migrants for preventive care.

High proportion of healthcare-associated urinary tract infection in the absence of prior exposure to urinary catheter: a cross-sectional study

Exposure to urinary catheters is considered the most important risk factor for healthcare-associated urinary tract infection (UTI) and is associated with significant morbidity and substantial extra-costs. In this study, we assessed the impact of urinary catheterisation (UC) on symptomatic healthcare-associated UTI among hospitalized patients.

Telemedicine Distance Mentoring of Healthcare Students

The healthcare system is facing a challenge similar to other industries in maintaining an adequately trained home care workforce in a time when government funding for educational geriatrics programs is limited, and academic centers are emphasizing faculty productivity that may limit their time dedicated to teaching and training healthcare students. [See PDF for complete abstract]

CHARACTERIZING, ASSESSING AND IMPROVING HEALTHCARE REFERRAL COMMUNICATION

Similar to other health care processes, referrals are susceptible to breakdowns. These breakdowns in the referral process can lead to poor continuity of care, slow diagnostic processes, delays and repetition of tests, patient and provider dissatisfaction, and can lead to a loss of confidence in providers. These facts and the necessity for a deeper understanding of referrals in healthcare served as the motivation to conduct a comprehensive study of referrals. The research began with the real problem and need to understand referral communication as a mean to improve patient care. Despite previous efforts to explain referrals and the dynamics and interrelations of the variables that influence referrals there is not a common, contemporary, and accepted definition of what a referral is in the health care context. The research agenda was guided by the need to explore referrals as an abstract concept by: 1) developing a conceptual definition of referrals, and 2) developing a model of referrals, to finally propose a 3) comprehensive research framework. This dissertation has resulted in a standard conceptual definition of referrals and a model of referrals. In addition a mixed-method framework to evaluate referrals was proposed, and finally a data driven model was developed to predict whether a referral would be approved or denied by a specialty service. The three manuscripts included in this dissertation present the basis for studying and assessing referrals using a common framework that should allow an easier comparative research agenda to improve referrals taking into account the context where referrals occur.

A PROCESS FOR ACHIEVING COMPARABLE DATA FROM HETEROGENEOUS DATABASES

The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, collected for different purposes and represented differently, that are presently impossible to share or analyze in toto. The greatest challenge for large-scale and meaningful analyses of health-related data is to achieve a uniform data representation for data extracted from heterogeneous source representations. Based upon an analysis and categorization of heterogeneities, a process for achieving comparable data content by using a uniform terminological representation is developed. This process addresses the types of representational heterogeneities that commonly arise in healthcare data integration problems. Specifically, this process uses a reference terminology, and associated "maps" to transform heterogeneous data to a standard representation for comparability and secondary use. The capture of quality and precision of the “maps” between local terms and reference terminology concepts enhances the meaning of the aggregated data, empowering end users with better-informed queries for subsequent analyses. A data integration case study in the domain of pediatric asthma illustrates the development and use of a reference terminology for creating comparable data from heterogeneous source representations. The contribution of this research is a generalized process for the integration of data from heterogeneous source representations, and this process can be applied and extended to other problems where heterogeneous data needs to be merged.

Towards a Hybrid Method to Categorize Interruptions and Activities in Healthcare

Objective Interruptions are known to have a negative impact on activity performance. Understanding how an interruption contributes to human error is limited because there is not a standard method for analyzing and classifying interruptions. Qualitative data are typically analyzed by either a deductive or an inductive method. Both methods have limitations. In this paper a hybrid method was developed that integrates deductive and inductive methods for the categorization of activities and interruptions recorded during an ethnographic study of physicians and registered nurses in a Level One Trauma Center. Understanding the effects of interruptions is important for designing and evaluating informatics tools in particular and for improving healthcare quality and patient safety in general. Method The hybrid method was developed using a deductive a priori classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. Results The categories of activities and interruptions were organized into a three-tiered hierarchy of activity. Validity and reliability of the categories were tested by categorizing a medical error case external to the study. No new categories of interruptions were identified during analysis of the medical error case. Conclusions Findings from this study provide evidence that the hybrid model of categorization is more complete than either a deductive or an inductive method alone. The hybrid method developed in this study provides the methodical support for understanding, analyzing, and managing interruptions and workflow.

Towards a hybrid method to categorize interruptions and activities in healthcare.

OBJECTIVE: Interruptions are known to have a negative impact on activity performance. Understanding how an interruption contributes to human error is limited because there is not a standard method for analyzing and classifying interruptions. Qualitative data are typically analyzed by either a deductive or an inductive method. Both methods have limitations. In this paper, a hybrid method was developed that integrates deductive and inductive methods for the categorization of activities and interruptions recorded during an ethnographic study of physicians and registered nurses in a Level One Trauma Center. Understanding the effects of interruptions is important for designing and evaluating informatics tools in particular as well as improving healthcare quality and patient safety in general. METHOD: The hybrid method was developed using a deductive a priori classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. RESULTS: The categories of activities and interruptions were organized into a three-tiered hierarchy of activity. Validity and reliability of the categories were tested by categorizing a medical error case external to the study. No new categories of interruptions were identified during analysis of the medical error case. CONCLUSIONS: Findings from this study provide evidence that the hybrid model of categorization is more complete than either a deductive or an inductive method alone. The hybrid method developed in this study provides the methodical support for understanding, analyzing, and managing interruptions and workflow.