Dissertations / Theses on the topic 'Applications in health'

Background: This thesis aims to investigate if the use of mobile health (mHealth) applications have positive effects on health.   Objectives: This research are to provide an insight of how people are using mHealth applications but also provide an insight of the target group. Additionally, the thesis will provide an analysis of the proposed Structural Equation Model (SEM) to understand the influencing factors (constructs) for health improvement.    Method: In this research a Structural Equation Model (SEM) approach was used in which a questionnaire with closed ended questions related to each construct were provided to collect the data. The data were analyzed by the computer program IBM SPSS 25 and the SEM was made by the IBM SPSS AMOS 25.   Results: The proposed theoretical SEM model showed validity and the proposed hypotheses 1 and 2 were significant for this model. The corresponding contributed construct to improve health, were “Healthcare Service” and “mHealth App Behavior”. “New Technology” did not contribute to improvement of health directly, but it correlated strongly to “Healthcare Service” but also to “mHealth App Behavior”.   Conclusions: The target group was defined as a group of early adopters who used mobile health applications and more specifically, they used fitness apps to enhance health. People in the target group were high educated and had occupations which corresponded well with their education. Additionally, this group used their knowledge by reading and understanding health information when they needed healthcare service to improve health.  Keywords: Adoption, Health, mHealth, New Technology

As mobile devices become more prevalent in healthcare scenarios, it is becoming necessary to develop infrastructure to allow these devices to securely participate in emergency healthcare response scenarios. In this work, the scenario of an emergency response team requesting access to the health care records of a patient is analyzed. As these records may not be immediately available to the requesting party, several parties may need to be contacted to ensure to validate the identity of the requester and deliver the records. Existing works exploring this topic are briefly analyzed. Using recommendations found in these works as well as standard technologies such as SSL, X.509, and AES, a proposed protocol for such a scenario is presented. The construction of a prototype using Android as the mobile phone OS and Tomcat as the Java HTTP Servlet container and web server is discussed, focusing on the implementation decisions as well as the difficulties encountered during development. Finally, weaknesses of the proposed protocol that were realized during prototype implementation are discussed and future improvements are proposed.

Consumers with chronic conditions have access to a plethora of mobile applications (‘apps’) to manage their health. Qualitative research confirmed consumers’ willingness to engage with this technology. A checklist was designed to assess the quality and usability of health apps, and trialled 11 asthma and 17 hypertension apps, identifying variable yet generally substandard quality. A concept map incorporating blockchain technology subsequently proposed how improved functionality and connectivity can enhance use of consumers’ self-monitored health data.

Abstract Data mining is a relatively new field of research whose major objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available. On the one hand, practitioners are expected to use all this data in their work but, at the same time, such a large amount of data cannot be processed by humans in a short time to make diagnosis, prognosis and treatment schedules. A major objective of this thesis is to evaluate data mining tools in medical and health care applications to develop a tool that can help make timely and accurate decisions. Two medical databases are considered, one for describing the various tools and the other as the case study. The first database is related to breast cancer and the second is related to the minimum data set for mental health (MDS-MH). The breast cancer database consists of 10 attributes and the MDS-MH dataset consists of 455 attributes. As there are a number of data mining algorithms and tools available we consider only a few tools to evaluate on these applications and develop classification rules that can be used in prediction. Our results indicate that for the major case study, namely the mental health problem, over 70 to 80% accurate results are possible. A further extension of this work is to make available classification rules in mobile devices such as PDAs. Patient information is directly inputted onto the PDA and the classification of these inputted values takes place based on the rules stored on the PDA to provide real time assistance to practitioners.

Aquesta tesi està formada per dues parts relacionades amb l'estudi de la salut d'una regió geogràfica dividida en un conjunt de zones (àrees petites). La primera part es basa en un estudi amb informació de salut agregada per cadascuna de les àrees que formen la regió d'estudi. En concret, es tracta d'una aplicació de mapes de salut (disease mapping), que utilitza mètodes Bayesians empírics per generar un Atles de mortalitat en àrees petites de Catalunya en el període 1984-1998. La segona part utilitza una nova perspectiva basada en la integració de les dades agregades i individuals de salut per cadascuna de les zones que formen la regió d'estudi, mitjançant equacions d'estimació (estimating equations). Aquesta nova perspectiva és una extensió de la regressió geogràfica.
L'elaboració de la primera part d'aquesta tesi està justificada per diferents raons. En primer lloc, els atles de salut i en general els mapes d'indicadors de salut, ens han mostrat la seva gran utilitat per identificar les localitzacions geogràfiques de les malalties, formular hipòtesis sobre les causes de la malaltia i monitoritzar intervencions en salut pública. En segon lloc, els atles de mortalitat en àrees petites presenten la distribució del risc relatiu per les causes de mortalitat més importants utilitzant mapes amb un alt nivell de resolució geogràfica.
El primer objectiu d'aquesta tesi va ser construir un atles de mortalitat en 289 àrees petites (municipis o municipis agregats) de la Comunitat Autònoma de Catalunya i 66 àrees bàsiques de salut de la ciutat de Barcelona (l'àrea petita analitzada amb una major població) per al període 1984-1998. Per obtenir els indicadors de salut en àrees petites s'han utilitzat mètodes Bayesians. Aquests mapes presenten, en un format de doble pàgina, els riscs relatius ajustats per edat, les àrees significatives d'alt i baix risc, el risc relatiu de la ciutat de Barcelona respecte a Catalunya i internament respecte a Barcelona, el risc relatiu per grups d'edat (0-64 i 65) i addicionalment l'evolució temporal del risc relatiu en cada àrea resumida en un únic mapa. En concret, per estudiar l'evolució del risc relatiu de mortalitat s'inclou: 1) l'evolució del risc relatiu en el període d'estudi de cada àrea comparada amb la tendència global de Catalunya i 2) l'evolució absoluta del risc relatiu a cada àrea. Segons el nostre coneixement, aquesta és la primera vegada que aquests dos tipus d'informació es combinen en un únic mapa. A més, aquest és el primer Atles que presenta informació sobre la distribució geogràfica de zones que formen àrees petites de gran població, com ciutats d'un país, i inclou l'esperança de vida obtinguda amb mètodes Bayesians empírics.
La segona part d'aquesta tesi és útil per estudis epidemiològics on s'inclouen variables d'exposició i confusió que poden tenir diferents fonts de variabilitat (variabilitat dins les poblacions i entre les poblacions). Específicament, els anàlisis individuals que valoren la relació entre la malaltia i l'exposició dins d'una població són útils quan l'exposició presenta variabilitat dins la població. Quan aquesta variabilitat és limitada, la força dels anàlisis individuals es debilita. En aquesta situació, un anàlisis de dades agregades de la malaltia entre poblacions, amb una mostra de dades individuals d'exposició, pot ser eficaç en l'estimació de l'efecte d'exposició si aquest presenta gran variabilitat entre poblacions. No obstant, encara que es pugui conèixer quina de les dues variacions domina en la variable d'exposició, es poden considerar conjuntament variables d'exposició i/o confusió amb diferents tipus de variació. El segon objectiu d'aquesta tesi va ser considerar una nova perspectiva, combinació dels anàlisis de dades individuals i agregades, basat en equacions d'estimació (perspectiva population-based estimating equation (PBEE)). En funció de la variabilitat que domina en la exposició, la anàlisis proposada pren força de la perspectiva basada en dades individuals i agrades de salut, per estimar els efectes d'exposició. Es van realitzar estudis de simulació en diferents escenaris per a mostrar el poder de la perspectiva proposada en l'estimació dels efectes d'exposició d'interès.
Finalment, esperem que els mètodes i els diferents aspectes utilitzats en aquesta tesi puguin ser d'utilitat per a aquells investigadors que vulguin millorar l'estudi de la salut a l'espai i temps.
Esta tesis esta formada por dos partes relacionadas con el estudio de la salud en una región geográfica dividida en un conjunto de zonas (áreas pequeñas). La primera parte considera un estudio con información de salud agregada para cada una de las áreas que forman la región analizada. En concreto, se trata de una aplicación de mapas de salud (disease mapping), consistente en el uso de métodos Bayesianos empíricos para generar un Atlas de mortalidad en áreas pequeñas de Cataluña en el periodo 1984-1998. La segunda parte considera un nuevo enfoque que realiza una integración de los datos agregados e individuales de salud para cada una de las zonas que forman la región en estudio, mediante ecuaciones de estimación (estimating equations). Se considera que este nuevo enfoque es una extensión de la regresión geográfica.
La elaboración de la primera parte de esta tesis esta justificada por diferentes razones. Primero, los atlas de salud y en general los mapas de indicadores de salud, han mostrado su gran utilidad para identificar localizaciones geográficas de las enfermedades, formular hipótesis sobre las causas de la enfermedad y monitorizar intervenciones en salud pública. En segundo lugar, los atlas de mortalidad en áreas pequeñas presentan la distribución del riesgo relativo para las causas de mortalidad más importantes usando mapas con un alto nivel de resolución geográfica.
El primer objetivo de esta tesis fue construir un atlas de mortalidad en 289 áreas pequeñas (municipios o municipios agregados) de la Comunidad Autónoma de Cataluña y 66 áreas básicas de salud de la ciudad de Barcelona (el área pequeña analizada con mayor población) para el periodo 1984-1998. Para obtener los indicadores de salud en las áreas pequeñas se han aplicado métodos Bayesianos. Estos mapas presentan, en un formato de página doble, los riesgos relativos ajustados por edad, las áreas significativas de alto y bajo riesgo, el riesgo relativo de la ciudad de Barcelona con respecto a Cataluña e internamente con respecto a Barcelona, el riesgo relativo por grupos de edad (0-64 y 65) y adicionalmente la evolución temporal del riesgo relativo en cada área resumida en un único mapa. En concreto, para estudiar la evolución del riesgo relativo de mortalidad se incluye: 1) la evolución del riesgo relativo en el periodo de estudio de cada área comparada con la tendencia global de Cataluña y 2) la evolución absoluta del riesgo relativo en cada área. Según nuestro conocimiento, esta es la primera vez que ambos tipos de información se combinan en un único mapa. Además, este es el primer Atlas que presenta información sobre la distribución geográfica de zonas que forman áreas pequeñas de gran población, como ciudades de un país, e incluye la esperanza de vida obtenida mediante métodos Bayesianos empíricos.
La segunda parte de esta tesis es útil en estudios epidemiológicos donde se incluyen variables de exposición y confusión que pueden tener diferentes fuentes de variabilidad (variabilidad dentro de las poblaciones y entre poblaciones). Específicamente, los análisis individuales que valoran la relación entre enfermedad y exposición dentro de una población son útiles cuando la exposición presenta variabilidad dentro de la población. Cuando dicha variabilidad es limitada el poder de los análisis individuales se reduce. En esta situación, un análisis de datos agregados de enfermedad entre poblaciones, con una muestra de datos individuales de exposición, puede ser eficaz en la estimación del efecto de exposición si este presenta gran variabilidad entre poblaciones. No obstante, aunque se pueda conocer cual de las dos variaciones domina en la variable de exposición, se pueden considerar conjuntamente variables de exposición y/o confusión con diferentes tipos de variación. El segundo objetivo de esta tesis fue considerar un nuevo enfoque, combinación de los análisis de datos individuales y agregados, basado en ecuaciones de estimación (enfoque population-based estimating equation (PBEE)). Dependiendo de la variabilidad que domina en dicha exposición, el análisis propuesto toma fuerza de los enfoques basados en datos individuales y agregados de salud, para estimar los efectos de exposición. Estudios de simulación bajo diferentes escenarios fueron realizados para mostrar el poder del enfoque propuesto en la estimación de los efectos de exposición de interés.
Finalmente, esperamos que los métodos y diferentes aspectos empleados en esta tesis puedan ser de utilidad para aquellos investigadores que quieran mejorar el estudio de la salud en el espacio y en el tiempo.
This thesis consists of two related parts based on the study of health in a geographical region divided in a set of zones (small areas). The first part considers studies based on health information aggregated for each area into which the region under study has been divided. Specifically, it is a disease mapping application, based on generation of an Atlas of mortality in small areas of Catalonia over the period 1984-1998, using empirical Bayes methods. The second part considers an innovative approach, based on an integration of aggregated and individual health data in each of the zones of the region under study, using an estimating equation approach. Specifically, we consider this new approach as an extension of geographical regression.
The elaboration of the first part of this thesis is justified for different reasons. First, health atlases and the mapping of health indicators in general, has demonstrated its great utility in identifying geographical localizations of health problems, in formulation of hypotheses about disease causes, and in monitoring public health interventions. Second, most atlases of mortality at the small area level present patterns of relative mortality risk for the most important causes of death using maps with a high level of geographical resolution. The first goal of this thesis was to construct a mortality Atlas involving a decomposition of the Autonomous Community of Catalonia into 289 small areas (municipalities or aggregates thereof) and 66 primary health areas of Barcelona city (being a small area but with a large population) for the period 1984-1998. For Catalonia as a whole, these maps presented, using a double-page format, the age adjusted relative risk, significantly high and low relative risk areas, relative risk in Barcelona City with respect to Catalonia and internally with respect to Barcelona, relative risk by age group (0-64 and 65) and additionally the relative risk evolution over time in each area summarized in an single map, using spatial and temporal information modeled through Bayesian methods. Specifically, the atlas uses a strategy to include both: 1) relative risk evolution throughout the study period of each area compared to the average trend for all Catalonia and 2) the absolute relative risk evolution of each area. To our knowledge, this is the first time that both types of information have been combined in a single map. In addition, this is the first Atlas that presents information about geographical patterns in zones within small areas having a large population such as the cities of a country and includes life expectancy obtained with an empirical Bayes approach.
The second part of this thesis can be useful in epidemiological studies where we include exposure and confounding variables that may have different sources of within and between-population variability. Specifically, analyses of individual disease-exposure data within a population are useful when exposure of interest varies sufficiently within the population. When the within-population variance of exposure is limited power of the individual-data analysis within a population is reduced. In such situations, aggregated-data analyses of disease data across populations, with a sample of individual exposure data from populations, can be powerful in estimating the exposure effect if between-population variation of exposure is large. However, although we may have knowledge of which variations dominate in each variable, exposure and/or confounding variables with different types of variation can be considered jointly. The second goal of this thesis was to consider a new analytical framework that is a combination of the individual- and aggregated-data analyses, based on an estimating equation approach ("population-based estimating equation" (PBEE) approach). The proposed analysis utilizes strengths from individual and aggregated health data approaches in the estimation of the exposure effect of interest, depending on which of the exposure variations (within- vs. between-population) dominates. Simulation studies under different scenarios were performed to show the strengths of the proposed approach in the estimation of the exposure effects of interest.
Finally, we hope that some of the methods and topics employed may be of use to researchers who want to improve the study of health in space and time.

Background Genetic epidemiology is at the interface of translational and basic research and the pace of progress has been unprecedented, with findings representing some of the most robust available in the Scientific literature. However, how we can translate this high- fidelity genomic information into improvements in health of the population? Two dis¬tinct translational opportunities include personalized medicine (pharmacogenetics) and using Mendelian randomization to investigate disease aetiology to inform public health policy and develop new therapies. Objectives In this PhD thesis, I investigated the evidence base underlying the well-publicized use of the pharmacogenetic biomarker CYP2C19 genotype to predict the response to clopi¬dogrel, a widely prescribed antiplatelet drug. Second, I used Mendelian randomization to investigate the role of an endogenous biomarker, secretory phospholipase A2-IIA (sPLA2-IIA), thought to be a pro-atherogenic enzyme and a potential drug target for the prevention of cardiovascular disease (CVD). Third, I used Mendelian randomization to investigate the relationship between alcohol, an exogenous exposure, and cardiovas¬cular traits and disease events. Results CYP2C19 and cardiovascular disease I identified 32 studies of 42,016 patients reporting 3545 CVD events. Only 6 studies were set within randomized trials (“effect-modification” design) and the remaining 26 reported individuals exposed to clopidogrel (“treatment-only” design). In treatment- only studies, possession of one or more *2-*8 CYP2C19 alleles was associated with lower cytochrome P450 C19 (CYP2C19) enzyme activity and a higher risk of CVD events (RR 1.18; 95%CI:1.09, 1.28), however, there was strong evidence of small-study bias (Harbord test P=0.001) and, when restricted to large studies (≥200 events), the association of CYP2C19 *2-*8 carrier status with CVD was null (RR 0.97; 95%CI: 0.86, 1.09). In the effect-modification studies, CYP2C19 genotype did not modify the effect of clopidogrel on CVD end-points. These findings cast doubt on whether information on CYP2C19 genotype would be helpful to guide selection of the dose of clopidogrel or use of an alternative antiplatelet agent. The role of secretory phospholipase A2-IIA (sPLA2-IIA) in CVD I used Mendelian randomization to make causal inference on the role of sPLA2-IIA in CVD. I identified a single nucleotide polymorphism (SNP) in PLA2G2A (rs11573 156) that was specific for and had a very strong impact on circulating levels of the sPLA2-IIA isoform. Using data from 36 studies and over 100,000 participants, instrumental variable analysis found no association between sPLA2-IIA with incident, prevalent or recurrent CVD events. These findings suggest sPLA2-IIA is not a valid therapeutic target for CVD prevention, which was in keeping with a phase III randomized clinical trial that was halted for futility in 2012 (during this thesis). Alcohol and CVD I used a SNP in ADH1B to investigate the relationship between alcohol and coronary heart disease (CHD) in >260,000 participants. The genetic variant (ADH1B rs1229984 A-allele) showed very strong association with reduced alcohol consumption when evalu¬ated as volume of alcohol consumed, binge drinking and abstaining from alcohol. The A-allele of rs1229984 showed associations with SBP, CRP, IL-6, BMI and waist circum¬ference that were all directionally concordant with a reduced risk of CHD. Indeed, when the clinical outcome CHD was investigated, individuals carrying the A-allele (who con¬sumed less alcohol than non-carriers) had a reduced risk of CHD at all levels of alcohol consumption. No evidence of a cardioprotective association of alcohol with CHD was identified. Conclusions My investigation into use of CYP2C19 genotype as a pharmacogenetic biomarker for clopidogrel response did not identify evidence to support its clinical use and limitations were identified that could apply to other pharmacogenetic tests. Use of Mendelian randomization revealed no evidence to support a causal role of sPLA2- IIA in CVD, which paralleled findings from a phase III randomized clinical trial, and provides support for the use of Mendelian randomization studies more widely to in¬form drug development. Finally, using the ADH1B gene to interrogate the relationship of alcohol yielded findings that argue against a cardioprotective effect of alcohol con¬sumption. These findings should encourage rethinking of public health advice about the cardiovascular benefits of moderate levels of alcohol consumption.

There are such diseases that people had to live with all their lives. Such simple actions as talking on the phone, going downstairs or even determining the expiration date of milk can become difficult for people with disabilities. We present a selection of mobile applications that make life of people with disabilities easier

Developing native applications for different platforms with different resolutions and screen sizes is both time consuming and costly. If developers were able to develop one web based application which can be used on multiple platforms, yet retain the same level of security as a native application, they would be able to reduce both development time and costs. In this thesis we will investigate the possibilities of achieving a level of security in a web-based application that can equal that of a native application, as well as how to develop an application that uses the Mina Vårdkontakter (My Healthcare Contacts) framework.

This dissertation deals with three problems in health care. In the first, we consider the incentives to change prices and capital levels at hospitals, using optimal control under the assumption that private payers charge higher prices if patients consume more hospital services. The main results are that even with fixed technology, investment and prices exhibit explosive growth, and that prices and capital stock grow in proportion to one another. In the second chapter, we study the flow of nosocomial infections in an intensive care unit. We use data from Cook County Hospital, along with numerous results from the literature, to construct a discrete event simulation. This model highlights emergent properties from treating the flow of patients and pathogens in one interconnected system, and sheds light on how nosocomial infections relate to hospital costs. We find that the system is not decomposable to individual systems, exhibiting behavior that would be difficult to explain in isolation. In the third chapter, we analyze a proposed change in diversion policies at hospitals, in order to increase the number of patients served, without an increase in resources. Overcrowding in hospital emergency departments is caused in part by the inability to send patients to main hospital wards, due to limited capacity. When a hospital is completely full, the hospital often goes on ambulance diversion, until some spare capacity has opened up. Diversion is costly, and often leads to waves of diversions in systems of hospitals, a situation that is regarded as highly problematic in public health. We construct and analyze a continuous-time Markov chain model for one hospital. The intuition behind the model is that load-balancing between various hospitals in a metro area may hinder full congestion. We find that a more flexible contract may benefit all parties, through the partial diversion of federally insured patients, when a hospital is very close to full. Discrete event simulation models are run to assess the effect, using data from DeKalb Medical Center, and also to show that in a two-hospital system, more federally insured patients are served using this mechanism.

As the population ages, the use of information technology and telecommunications in healthcare delivery (often known as Connected Health, telehealth or e-health) has been proposed as a means of providing . patient-centred care to those with chronic conditions. Little research has been conducted into the involvement of community pharmacists in Connected Health delivery. This thesis aimed to investigate the potential role of community pharmacists in the delivery of Connected Health services. A systematic content analysis of print media was performed to explore reporting of Connected Health in UK and US newspapers. A qualitative interview study was conducted with community pharmacists and key stakeholders in Canada and Northern Ireland to gather their views on community pharmacist involvement in Connected Health. Informed by the latter qualitative study, an online questionnaire was distributed to community pharmacists in Northern Ireland to explore their views regarding their potential role in Connected Health. Finally, a feasibility study was carried out, in which community pharmacists sent patients mobile telephone medication reminders and remotely monitored their blood pressure . . Connected Health was positively reported by the print media in the US and the UK. Community pharmacist and key stakeholder interviewees were supportive of community pharmacist involvement in Connected Health, believing it would extend and promote ' their role. However, they had concerns regarding appropriate remuneration. Similar views were obtained from community pharmacist questionnaire respondents. The feasibility study showed that a community pharmacy-based Connected Health programme could be successfully implemented on a small scale. Participants involved were positive about community pharmacist involvement in Connected Health. Community pharmacist involvement in Connected Health has the potential to improve patient outcomes and ease pressure on the health service. However, barriers such as funding and general practitioner acceptance would need to be overcome and a sound evidence base established before routine pharmacist involvement becomes a reality.

Tekniken är en stor del av dagens samhälle. Allt fler tjänster och saker blir digitaliserade, nu även sjukvården. Denna avhandling kommer att introducera dig till e-hälsa och hur digitaliseringen av sjukvården påverkar relationen mellan doktor och patient samt vilka förtroendeproblem som kan uppstå.E-hälsopplikationerna behöver vara användarvänliga och enkla att använda för patienterna. Patienterna behöver känna sig trygga och säkra. För att undersöka användarupplevelsen i de olika kanalerna jämförde vi de två olika flödena: personligt möte med videosamtal.Det finns många olika leverantörer av e-hälsoapplikationer i Sverige, Kry och Min Doktor är två av de mest populära. Digitaliseringen av sjukvården påverkar inte bara patienterna utan läkarna är lika involverade. För att få en läkares åsikt ställde vi ett par frågor till läkare om bedömning av patienter via videosamtal. Ett frågeformulär gjordes för att samla in information om patienternas förhållande, användning och erfarenhet av e-hälsoapplikationer.Frågeformuläret visade att det finns delade åsikter om e-hälsoapplikationerna. Vissa patienter tror att e-hälsapplikationerna kommer att gynna samhället och kan själva tänka sig att använda en e-hälsoapplikation för mindre åkommor. Andra patienter är starkt emot e-hälsa och de flesta av dem instämmer i att det är ett slöseri med skattepengar. En annan vanlig orsak emot e-hälsa är att patienter tycker att deras åkommor är för komplexa eller att de inte litar på att läkaren ger dem korrekt vård genom en applikation.
Technology is a big part of today's society. At this time more things and services become digitized, now even healthcare. This thesis will introduce you to e-health and how digitized healthcare will affect the doctor-patient relationship and the trust issue that may occur.E-health applications need to be user-friendly and easy to use. The user needs to feel comfortable and safe. To investigate the cross-channel user experience we compared the two different flows: in-person appointment and video session.There are many different providers for e-health applications in Sweden, most popular are Kry and Min Doktor. This digitizing not only affects the patients, the doctors are equally involved. We questioned doctors about their approach towards assistance through an application. A questionnaire was done to gather information about the patient's relationship and usage of e-health applications.The questionnaire showed that there are some divided opinions regarding e-health applications. Some patients think that e-health applications will benefit society and may use an e-health application for minor complaints. Other patients are strongly against e-health, and most of them agree that it is a waste of tax money. Another common reason against e-health is that patients think that their complaints are too complex or that they do not trust the doctor to provide them the accurate assistance through an application.

Despite the benefits of applying methods of geographic information science (GIScience), the use of such methods in health service planning and provision remains greatly underutilized. Spread of epidemic diseases is a constant threat to mankind and the globalization of the world increases the risk for global attacks from multi-resistant bacteria or deadly virus strains. Therefore, research is needed to better understand how GIScience could be used in epidemiologic analyses and other health applications. This thesis is divided into two parts; one for epidemiologic analyses and one for neighbourhood studies. The overall objective of the epidemiologic part of this research is to understand more about the spatial spread of past pandemics and to find out if there are any common patterns. This overall objective is divided into four specific research objectives; 1) to describe the spatial spread of the Russian Influenza in Sweden, 2) to create models of propagation of the Black Death in Sweden, 3) to establish spatiotemporal characteristics common to past pandemics in Sweden and 4) to visualize the spatiotemporal occurrence of salmonella among animal herds in Sweden. This thesis also discusses some other aspects of health related to place. Are differences in neighbourhood deprivation related to the amount of presence of goods and services? Is the way cities are planned affecting the behaviour within the local population regarding spontaneous walking and physical activity? The specific research objectives for this part are to define how deprivation is related to presence of goods and services in Sweden and to create walkability indices over the city of Stockholm including a quality test of these indices. Case data reported by physicians were used for the epidemiologic studies. The pandemics discussed covered the entire world, but our data is from Sweden only and as regards the Black Death there was no case data at all. The data for the goods and services analyses are from all of Sweden, whereas the walkability indices are based on data from the city of Stockholm. Various methods have been used to clean, structure and geocode the data, including hand written reports on case data, maps of poor geometric quality, information from databases on climate, demography, diseases, goods and services, income data and more, to make this data feasible for spatial analysis, modeling and visualization. Network analysis was used to model food transports in the 14th century as well as walking in the city of Stockholm today. Proximity analysis was used to assess the spatio-temporal spread of the Russian Influenza. The impact of climatological factors on the propagation of the Asian Influenza was analyzed and geographically weighted mean (GWM) calculations were used to discover common characteristics in the spatio-temporal spread of three past pandemics. Among the results generated in the epidemiologic study the following should be noted in particular; the local peaking periods of the Asian Influenza were preceded by falling temperature, the total peaking period for the three pandemics (Russian, Asian and A(H1N1)pdm09) was approximately 10 weeks and their weekly GWM followed a path from southwest to northeast (opposite direction for the A(H1N1)pdm09). From the neighborhood studies one can note that compared to the results measured and reported by tested individuals there is a positive (small but significant) association between neighborhood walkability and physical activity outcomes. The main contribution of this work is that it gives epidemiologists and public health specialists new ideas, not only on how to formulate, model, analyze and visualize different health related research questions but also ideas on how new procedures could be implemented in their daily work. Once the data reporting is organized in a suitable manner there is a multitude of options on how to present important and critical information to officials and policy makers.

QC 20140313

The increased incidence of lifestyle related diseases, such as obesity and diabetes, across the western world is now an established fact, and presents many challenges to researchers trying to understand the determinants of poor health. Measurement of health needs and health outcomes is a fundamental component of evidence-based policy, strategy and delivery of health care services and interventions at scales from the local to the national. A central contention of this thesis is that health outcome indicators should be cognisant of factors such as personal behaviour, lifestyles, community influences, living and working conditions, accessibility to services and educational attainment which all impact upon the health of the individual and the wider community. It is therefore sensible to explore these differences by understanding both the social space comprising of different population sub-groups and the geographical within which they live. Good quality data underlie the functioning of evidence-based decisions. Data provide the building blocks for understanding the nature and composition of neighbourhoods, together with the expected health outcomes of their residents. But within the health arena there are many complicated data issues. Existing operational health data sets are often incomplete or not up-to-date and accessibility is often limited by data protection and medical confidentiality policies. They are derived from disparate sources: GP registers, Hospital Episode statistics (people who are admitted to hospital), Child Registry and Accident and Emergency records, all adhering to different data collection and storage standards and systems that vary between organisations. Cross-referencing between these datasets is technically difficult because of these issues. Frequent quality issues of operational health data limit the extent of analysis that can be carried out with confidence. Furthermore, health survey data are released at coarse geographical scales where the ecological fallacy limits the potential for exploring local variability. Given these limiting factors, the theme of this research is to extend the health inequalities research and its associated data framework to explore variability in the spatial and social domain. This enables the identification of social facts relating to health harming lifestyle choices and behaviour that contribute to 'diseases of comfort'. This is carried out by developing and exploring the usefulness of geodemographics for analysing health inequalities, thereby adding the social and spatial context to our undertanding of causes of health inequalities. This thesis presents a more straightforward yet effective alternative to exploring the measurement of health impacting behaviours and predicting health outcomes using operational health data, national health surveys and a geodemographic classification. Geodemographic analysis of health outcomes can capture different lifestyle behaviours, and has already proven useful not only in improving customer segmentation in the commercial sector, but also to better target public services (Harris et al., 2005). By applying geodemographic classifications to national health surveys and NHS operational datasets at postcode level, interesting conclusions can be drawn in terms of different health harming lifestyle behaviours at very fine scales. Furthermore it is common practice that academic research projects occur in isolation, and exploitation of research findings and best practices in local government sectors is often beset by many obstacles. Consequently, within local government the adoption of new innovative technique and tools may often be slow. An inner London Primary Care Trust (PCT) is used as a test bed for disseminating and evaluating the geodemographic framework and indicators. The concluding sections of the thesis discuss the practicalities of embedding geodemographics in particular and geography in general into a professional environment where these technologies are new and innovative.

Medical research currently involves the collection of large and complex data. One such type of data is functional data where the unit of measurement is a curve measured over a grid. Functional data comes in a variety of forms depending on the nature of the research. Novel methodologies are required to accommodate this growing volume of functional data alongside new testing procedures to provide valid inferences. In this dissertation, I propose three novel methods to accommodate a variety of questions involving functional data of multiple forms. I consider three novel methods: (1) a function-on-function regression for Gaussian data; (2) a historical functional linear models for repeated measures; and (3) a generalized functional outcome regression for ordinal data. For each method, I discuss the existing shortcomings of the literature and demonstrate how my method fills those gaps. The abilities of each method are demonstrated via simulation and data application.

Les copolymères amphiphiles dégradables à base de poly (éthylène glycol) PEG et de polyesters aliphatiques (poly(ε-caprolactone) (PCL), poly(lactide) (PLA), poly(glycolide) (PGA)) sont largement utilisés dans les applications médicales en raison de leur innocuité et leur acceptation par les autorités de santé. Cependant leur capacité à répondre aux enjeux auxquels sont confrontés les nanomédicaments (ciblage, réponse programmée etc…) est limitée du fait de l’absence de groupes fonctionnels. Pour pallier cette limitation, ce travail de thèse s’intéresse aux voies de modification post-polymérisation de copolymères amphiphiles PEG-b-PCL donnant un accès simple à des familles de copolymères à blocs double hydrophiles (DHBC) dégradables. Nous nous intéressons en particulier à la synthèse de DHBC en trois étapes incluant une étape de photoaddition thiol-yne qui permet à partir d’un même précurseur macromoléculaire la synthèse de familles de DHBC à bloc PEG et blocs PCL fonctionnalisés en chaîne latérale à caractère neutre, cationique ou anionique. Le potentiel de ces DHBC pour la formulation d’actifs au sein de nanosystèmes de libérations pH-répondants est tout d’abord évalué à l’aide d’un anti-cancéreux à large spectre d’activité antitumorale. Dans un second temps, la formulation de micelles de complexes polyioniques tripartites de siRNA pour application en thérapie génique à partir de DHBC anioniques est étudiée. Enfin, la préparation de nanocomplexes DHBC/gadolinium pour imagerie médicale par résonance magnétique nucléaire (IRM) est abordée
Biodegradable amphiphilic copolymers based on poly(ethylene glycol) PEG and aliphatic polyesters (poly(ε-caprolactone) (PCL), poly(lactide) (PLA), poly(glycolide) (PGA)) are widely used in medical applications due to their safety and their acceptance by health authorities. However, their ability to address the challenges faced by the nanomedicines (targeting, programmed response etc…) is limited due to the absence of functional groups. To overcome this limitation, this work focuses on the post-polymerization modification strategies of amphiphilic PEG-b-PCL giving easy access to families of degradable double hydrophilic block copolymers (DHBC). We are particularly interested in the three-step synthesis of DHBC including a thiol-yne photoaddition step which allows, starting from the same macromolecular precursor, the synthesis of DHBC families composed of PEG blocks and side chain functionalized PCL blocks with a neutral, cationic or anionic character. The potential of these DHBC for the formulation of active pharmaceutical ingredients within pH-responsive drug delivery nanosystems is first evaluated using an anti-cancer agent with a broad spectrum of antitumor activity. In another part, we study the formulation of tripartite polyionic complex micelles with an anionic DHBC and siRNA for applications in gene therapy. Finally, the preparation of DHBC/gadolinium nanocomplexes for medical imaging by nuclear magnetic resonance (MRI) is discussed

Ce travail de recherche porte sur la fabrication de microcapteurs de déformation sur substrat souple. Les dispositifs sont élaborés et optimisés dans l’objectif de détecter de faibles déformations en temps réel et peuvent trouver des applications en santé en particulier via l’acquisition de faibles signaux électrophysiologiques pouvant être détectés par une déformation, par exemple à la surface de la peau. Le travail comprend le développement technologique des capteurs réalisés sur des substrats souples de très faible épaisseur (Kapton de 25 µm d’épaisseur), à partir de silicium microcristallin déposé par PECVD ou par ICPCVD. Pour chaque type de dépôt, les études de contraintes mécaniques et de stress sont exposées, en particulier via la détermination du facteur de jauge. La caractérisation dynamique des capteurs est réalisée via le développement d’un banc de test spécifique pour les mesures reproductibles de déformation. Les résultats permettent de déterminer des géométries optimisées, capables de suivre en temps réel des déformations complexes allant jusqu’aux signaux de type ECG. Des matrices de capteurs sont également réalisées et testées
This work focuses on the processing of mechanical sensors on flexible substrates. The devices are designed and optimized with the objective of detecting small deformations in real time. They can be applied for health signal acquisition, in particular small electrophysiological signals that can be detected by deformation, for example on the surface of the skin. The work includes the technological development of sensors made of microcrystalline silicon deposited by PECVD or ICPCVD on very thin flexible substrates (Kapton 25 µm thick). For each type of deposition, mechanical stress studies are presented, in particular through the determination of the gauge factor. The dynamic characterization of the sensors is carried out through the development of a specific test bench for reproducible real-time deformation measurements. The results make it possible to determine optimized geometries, capable of monitoring complex deformations in real time, up to ECG-type signals. Sensor matrices are also produced and tested

This thesis developed new search engine models that elicit the meaning behind the words found in documents and queries, rather than simply matching keywords. These new models were applied to searching medical records: an area where search is particularly challenging yet can have significant benefits to our society.

La tesis combina microeconometría y teoría de la información asimétrica. La tesis tiene tres principales objetivos: el primero es comprobar la relevancia empírica de la teoría de la información asimétrica en el campo de la utilización de servicios sanitarios. El segundo es diseñar técnicas econométricas que sean útiles para este propósito y el tercero es estimar contratos óptimos de seguro sanitarios.

El primer capítulo de la tesis es una breve revisión de la literatura y enfoques utilizados hasta ahora. También se resumen los tres siguientes capítulos.

El segundo capítulo de la tesis es un análisis de la utilización de servicios sanitarios en el sistema sanitario catalán. En particular, se analiza la influencia de los incentivos que proporcionan los seguros sanitarios privados sobre la utilización de servicios sanitarios. También se estudia la existencia de selección adversa en el mercado de seguros sanitarios privados. En Cataluña, aquellos que tienen doble cobertura (disfrutan a la vez de un seguro sanitario privado y de la cobertura pública) pueden fácilmente visitar un médico especialista sin permiso del médico general o listas de espera. En el capítulo se analiza como estos incentivos no financieros pueden influir en el consumo de servicios sanitarios. La teoría de la selección adversa sugiere que las personas que compran un seguro sanitario privado son aquellos que esperan realizar un alto número de visitas al especialista. Esta hipótesis conduce a considerar la doble cobertura como una variable endógena. De no tenerse en cuenta esta endogeneidad, se podrían obtener estimaciones inconsistentes que sobrestimasen la influencia de los incentivos en el consumo de servicios sanitarios. El problema se analiza por medio de un modelo de datos de conteo (modelo donde la variable dependiente toma valores 0,1,2, etc.). La variable dependiente es el número de visitas al especialista en los últimos doce meses. Una de las variables explicativas es si el individuo tiene o no doble cobertura. Para la estimación se utiliza el Método Generalizado de los Momentos, que realiza poco supuestos sobre el término de error. Se utilizan variables instrumentales para tener en cuenta la endogeneidad de la doble cobertura. Se encuentra que los incentivos proporcionados por los seguros sanitarios privados incrementan el número de visitas al especialista en alrededor de un 27%, para el grupo de personas que no son cabeza de familia. La endogeneidad de la doble cobertura resultó relevante para el grupo de cabezas de familia. Su principal contribución es considerar la endogeneidad del seguro privado en el contexto español, así como la aplicación del modelo econométrico para tener en cuenta conjuntamente la endogeneidad y la naturaleza no lineal de la variable dependiente.

El tercer capítulo de la tesis es un trabajo conjunto con Andrés Romeu. El objetivo del capítulo es desarrollar una técnica econométrica que resulte útil para analizar problemas donde la variable dependiente toma valores 0,1,2,3 etc. y haya una variable binaria endógena. Se desarrolla un modelo que minimiza supuestos sobre la función de probabilidad de la variable dependiente. Esto se consigue realizando una expansión polinomial sobre una densidad base Poisson. La estimación se realiza por Máxima Verosimilitud. Se obtiene que el modelo propuesto es capaz de obtener un mejor ajuste a los datos que los modelos más utilizados en la literatura. En una aplicación que utiliza la 1987 Medical Expenditure Survey de los Estados Unidos se encuentra que para individuos con peor salud, el número de visitas al médico se ve poco afectada por la compra de un seguro sanitario privado adicional al Medicare.

El cuarto capítulo presenta un modelo teórico para la decisión sobre si tener tratamiento médico o no ante un episodio de enfermedad. El individuo toma la decisión comparando los beneficios del tratamiento con los costes que le suponen. Este coste está influido por el copago. El objetivo del capítulo es estimar los parámetros del modelo teórico: parámetros relacionados con la probabilidad de enfermedad y la función de coste del tratamiento. Ello permite resolver el programa principal-agente para obtener el copago óptimo. El modelo se estima por Máxima Verosimilitud usando datos del RAND Health Insurance Experiment que aleatoriamente asignó individuos a diferentes niveles de copago. Se encuentra que, bajo la hipótesis de prima actuarialmente justa, el copago óptimo es sorprendentemente bajo. Sin embargo, si las compañías de seguros cargan una prima ligeramente superior al coste esperado, se obtienen niveles de copago cercanos a los encontrados en la realidad. La mayor contribución de este artículo es la utilización de un modelo de principal-agente para responder a la pregunta del copago óptimo desde un punto de vista empírico.
The thesis combines microeconometrics and asymmetric information theory. The thesis has three main objectives. The first one is to test the empirical relevance of the theory of asymmetric information. The second one is to design econometric tools that are useful for this purpose and the third one is to estimate optimal health care insurance contracts.

The first chapter of the thesis is a brief literature review and a summary of the following three chapters.

The second chapter of the thesis is an analysis of health care utilization in the Catalonian Health System. In particular, it analyzes how much the incentives given by private medical insurance contracts influence health care consumption. It also pays attention to the existence of adverse selection in the private health insurance market. In Catalonia, those who buy a private insurance (duplicate coverage) can easily visit a specialist (without general practitioner permission, waiting lists...). The chapter analyzes how these non-financial incentives can affect health care choices. According to Adverse Selection theory, those that expect to have an intensive use of health care services are the ones that buy private insurance. This hypothesis yields us to consider insurance status as endogenous. If it was neglected, we could obtain inconsistent estimates that overestimated the influence of incentives on health care consumption. The problem is analyzed by means of a count data model, a model for which the dependent variable takes values 0,1,2,3, etc. One of the explicate variables is whether the individual had duplicate coverage or not. The model is estimated using a Generalized Method of Moments estimator, which does relatively few assumptions about the error term. In order to take into account the endogeneity of insurance status, we consider instrumental variables. We find that private insurance increases the average of visits to specialist in approximately a 27% for non-heads of households. It was relevant to consider the endogeneity (adverse selection) for the heads of households. Its main contribution is to consider the endogeneity of private insurance in the Catalonian Health System, as well as the application of the econometric model to model endogeneity of insurance status.

The third chapter of the thesis is a joint work from Andrés Romeu. The objective of the chapter is to develop an econometric model that is useful to analyze problems where the dependent variable is a count variable (takes values 0,1,2,3, etc.) and there is an endogenous binary variable. The proposed model considers a flexible specification for the count variable probability function, allowing to departure from standard Poisson and Negative Binomial assumptions. The flexibility is given by multiplying the Poisson density by a polynomial. Estimation is carried out by Maximum Likelihood. It is found that the proposed model obtains a better fit to the data than standard models found in the literature. In an application to the 1987 Medical Expenditure Survey from U.S. we find that health care utilization of those with poor health conditions is less sensitive to insurance status. Its main contribution is the econometric method that combines flexibility to model count variables and a dummy endogenous variable.

The fourth chapter presents a model where the individual decides to have treatment or not when she suffers an illness spell. The decision is taken on the basis of comparing benefits and out-of-pocket monetary costs of treatment. The aim of the paper is to obtain estimates of the theoretical model parameters: parameters related to illness probability and cost treatment function. This allows solving for the optimal copayment using a principal agent model. The framework also allows us to simulate the effects of not fair premiums in coverage decision. We use data from the RAND Health Insurance Experiment that randomly assigned individuals to different copayment levels. We find that optimal copayments in presence of a fair premium are surprisingly low. However, slight departures from the fair premium hypothesis give us copayments of the size found in real life. The main contribution of the chapter is to use the principal-agent framework to estimate the optimal copayment.

Currently, resources that may be spent in health care are limited so it is necessary to rationalize their consumption and prioritise their allocation to the options with higher health outcome and economic sustainability. It is for that reason that economic analyses are increasingly included in medicine research as an instrument for evaluating different therapeutic strategies. In this thesis, both cost and health outcome are separately and jointly evaluated to compare different therapeutic strategies to treat diseases in different and specific health areas. The challenge was adapting and implementing the methods to reflect the assessed health issue. The analyses require data, and the main sources to obtain them are clinical studies (prospective or retrospective), or simulation models. The use of simulations avoids to experiment directly to the system of interest, these methods imply a smaller time consumption and cost, and any danger can be caused by the experimentation performance. However, the simulated data always is going to be an approximation of real data. Real data of a clinical trial was used in the assessment of the adherence to antiretroviral treatment promotion program in HIV infected patients. A decision tree was used to study the cost per health gain, measured by means of clinical and health related quality of life outcomes. The simulation of a Spanish cohort of postmenopausal women and their possible osteoporotic fractures was done to assess the performance of two treatments for the prevention of vertebral and non-vertebral fractures in terms of cost-effectiveness. Simulation by means of a Markov model required that the disease evolution and the related events were simplified using a finite number of health states and the probabilities of moving from one state to another as the time go on. Markov models were adapted to reflect that the risk of suffering an event can change over time. This analytical model was applied to elucidate whether co-receptors testing is cost-effective to determine patient¿s suitability to benefit from the use of an antiretroviral treatment that includes maraviroc. All HIV strains require binding to CD4 plus at least one of the 2 co-receptors CCR5 or CXCR4 to enter human cells. Some HIV can use both co-receptors, and some individuals have a mixture of strains. Only patients with exclusively CCR5-tropic HIV are considered eligible to use the CCR5 antagonist maraviroc. A budget impact analyses to assess the economic effects of introducing eculizumab for treating the paroxysmal nocturnal hemoglobinuria was performed. Direct and indirect costs of this disease treatment were estimated and reported from the perspective of the health care system and from the societal perspective. Most of the published clinical studies are focused on measuring health in terms of efficacy and/or safety. But, sometimes the health and well-being quantification is not a direct measurement. Here, the calculation of the burden of disease for osteoporotic women who may suffer from fractures done at an individual level was presented in terms of disability adjusted life years (DALYs). Few studies of burden of diseases are available, and even less for Spanish population and performed using individual characteristics. The pharmacoeconomic studies can be useful in the health resources rationalization, and both budget impact analyses and new health measures are complementary tools. The work performed in this thesis constitutes a good example of methods application and adaptation to answer real clinical questions.
Actualment, els recursos destinats a la salut són limitats i es fa necessari racionalitzar-ne el seu consum; cal prioritzar la despesa en opcions que reportin un major benestar i que siguin sostenibles econòmicament. És per aquest motiu, que cada cop hi ha més estudis clínics que inclouen paràmetres econòmics com a instrument per triar entre diferents estratègies terapèutiques. En aquesta tesi, tant el cost com la resposta de salut s'estudien per separat i conjuntament per a comparar diferents estratègies per al tractament de malalties de diferent àrees de salut. El repte es troba en adaptar i implementar la metodologia necessària per a dur a terme el seguiment d'aquests problemas de salut. Les anàlisis requereixen dades i la majoria d'elles provenen d'estudis clínics, ja siguin prospectius o retrospectius, o bé de models de simulació. L'ús de dades simulades evita experimentar directament amb el sistema d'interès, implicant un temps menor, un cost més econòmic i un decreixement del risc d'experimentació necessaris per a l'obtenció de resultats. Per contrapartida, la simulació és una aproximació de les dades reals. D'una banda, l'avaluació d'un programa de promoció de l'adherència al tractament antiretroviral per pacients VIH+ es du a terme amb dades reals recollides en el marc d'un assaig clínic. El cost per unitat de guany en salut, mesurat amb paràmetres clínics i en qualitat de vida, es representa mitjançant un arbre de decisió. A continuació, la simulació d'una cohort de dones espanyoles post menopàusiques i les seves possibles fractures òssies permet comparar, en termes de cost-efectivitat, dos tractaments usats en la prevenció de fractures vertebrals i no vertebrals. Els models de Markov permeten simular el curs de la malaltia fent servir un nombre finit d'esdeveniments que representen els possibles estats de salut i la probabilitat de que un pacient canviï d'estat amb l'adaptació dels models de Markov per permetre que el risc de patir un esdeveniment variï en el temps permet determinar si els tests de co-receptors del VIH són cost-efectius per decidir si un pacient es pot beneficiar del tractament antiretroviral amb maraviroc. Les cadenes de VIH s'han d'unir als CD4, com a mínim, en un dels dos co-receptors possibles, CCR5 o CXCR4, per entrar a la cèl.lula. Alguns virus VIH fan servir els dos co-receptors i alguns individus tenen una mixtura de cadenes de VIH. Els pacients que es poden beneficiar de l'ús de maraviroc son aquells que estan infectats únicament per virus amb el co-receptor CCR5. Per últim, una anàlisis d'impacte pressupostari permet quantificar la despesa econòmica d'introduir eculizumab per a tractar la hemoglobinúria paroxística nocturna. En aquest cas, s'ha fet una estimació de costos directes i indirectes i es reporten des de la perspectiva del sistema sanitari i des de la perspectiva de la societat. La major part d'estudis clínics publicats es centren en la mesura de la salut en termes d'eficàcia i/o de seguretat; però moltes vegades, la salut i el benestar no es poden quantificar de manera directa. En aquest cas, la càrrega de la malaltia de l'osteoporosi en dones post menopàusiques ha estat quantificada mitjançant anys de vida viscuts amb discapacitat (DALYs) calculats a partir de dades obtingudes a nivell d'individu. Actualment es disposa de pocs estudis de càrrega de malaltia, i menys encara per a població espanyola i amb dades individuals. Els estudis farmacoeconòmics són d'utilitat en l'assignació de recursos, i els estudis d'impacte pressupostari i la generació de noves mesures per a quantificar la salut i el benestar son eines complementàries. El treball realitzat en aquesta tesis és un bon exemple d'aplicació i adaptació de l'estadística per a respondre diferents qüestions de rellevància clínica actualment.

A growing number of factors, including the costs, technological advancements, an ageing population, and medical errors are leading industrialised countries to invest in research on alternative solutions to improving their health care systems and increasing patients’ life quality. Personal Health System (PHS) solutions envision the use of information and communication technologies that enable a paradigm shift from the traditional hospital-centred healthcare delivery model toward a preventive and person-centred approach. PHS offers the means to follow patient health using wearable, portable or implantable systems that offer ubiquitous, unobtrusive bio-data acquisition, allowing remote access to patient status and treatment monitoring. Electrical Bioimpedance (EBI) technology is a non-invasive, quick and relatively affordable technique that can be used for assessing and monitoring different health conditions, e.g., body composition assessments for nutrition. EBI technology combined with state-of-the-art advances in sensor and textile technology are fostering the implementation of wearable bioimpedance monitors that use functional garments for the implementation of personalised healthcare applications. This research studies the development of a portable EBI spectrometer that can use dry textile electrodes for the assessment of body composition for the purposes of clinical uses. The portable bioimpedance monitor has been developed using the latest advances in system-on-chip technology for bioimpedance spectroscopy instrumentation. The obtained portable spectrometer has been validated against commercial spectrometer that performs total body composition assessment using functional textrode garments. The development of a portable Bioimpedance spectrometer using functional garments and dry textile electrodes for body composition assessment has been shown to be a feasible option. The availability of such measurement systems bring closer the real implementation of personalised healthcare systems.

QC 20130405

Medical record systems are used whenever caregiving is practiced. The medical records serve an important role in establishing patient safety. It is not possible to prevent honest-but-curious doctors from accessing records since it is legally required to allow doctors to access health records for emergency cases. However, it is possible to log accesses to records and mitigate malicious behaviour through rate limiting. Nevertheless, many of the records systems today are lacking good authentication, logging and auditing and existing proposals for securing medical records systems focus on the context of multiple different healthcare providers. In this thesis, an architecture for an electronic health records system for a telemedicine provider is designed. The architecture is based on several requirements from both the legal perspective and general security conventions, but also from a doctor’s perspective. Unlike the legal and general security conventions perspective, doctor requirements are more functionality and usability concerns rather than security concerns. The architecture is evaluated based on two main threat models and one secondary threat model, i.e. insider adversaries. Almost all requirements are satisfied by the solution design, but the two main threat models can not be entirely mitigated. It is found that confidentiality can be violated by the two main threat models, but the impact is heavily limited through audit logging and rate limiting.
Journalsystem är en central del inom vården och patientjournaler har en stor roll i att uppnå bra patientsäkerhet. Det är inte möjligt att förhindra läkare från att läsa särskilda journaler eftersom läkare behöver tillgång till journaler vid nödsituationer. Däremot går det att logga läkarnas handlingar och begränsa ondsint beteende. Trots det saknar många av dagens journalsystem bra metoder för autentisering, loggning och granskning. Befintliga förslag på att säkra journalsystemen fokuserar på sammanhang där flera olika vårdgivare är involverade. I den här rapporten presenteras en arkitektur för ett patientjournalsystem till en telemedicinsk leverantör. Arkitekturen utgår från flertalet krav baserade på både ett legalt perspektiv och generella säkerhetskonventioner, men även läkares perspektiv. Arkitekturen är evaluerad baserat på två huvudsakliga hotmodeller och en sekundär hotmodell. Arkitekturen uppfyller så gott som alla krav, men de två huvudsakliga hotmodellerna kan inte mitigeras helt och hållet. De två huvudsakliga hotmodellerna kan bryta sekretessen, men genom flödesbegränsning och granskning av loggar begränsas påverkan.

Previous research on augmented reality has to great extent been focusing on exploring and expanding technical possibilities without considering what users find to be desirable and useful. By using the inspirational bits method and the limitations of current AR technologies as a source of inspiration, this research makes use of the existing technical knowledge on AR for inspiring new ideas on how to use AR. The inspirational bits method aims to increase the understanding of a material by letting the participants experience a specific feature of a technology called bit and thereby making the technology more tangible. A set of inspirational bits was designed, developed and used in workshops to inspire ideas on how to use AR for future health applications. Two technical concepts were highlighted in the bits, detection of real objects and placement of digital objects in the real environment. Two types of experiences were also highlighted in one bit each; annotation experiences where additional information is attached to physical objects and visualization experiences where users interact with a virtual object. The bits were explored in workshops followed by a rapid brainstorming session to quickly get their ideas down to paper. It seems to have been easier to come up with ideas on annotation experiences compared to visualization experiences which might be due to their initial expectation that AR will be used as a tool for adding digital interactions to the real world, similar to how annotated experiences work. Since a lot of the topics used were about external objects affecting one’s body and health, annotated experiences might be more appropriate as it can be used to attach private information to public objects.
Tidigare forskning om förstärkt verklighet har i stor utsträckning fokuserat på att utforska och expandera tekniska möjligheter utan att ta hänsyn till vad användarna tycker är önskvärt och användbart. Genom att använda Inspirational Bits metoden och begränsningarna av nuvarande AR-teknik som inspirationskälla använder denna forskning den befintliga tekniska kunskapen om AR för inspirera till nya idéer om hur man kan använda AR. Inspirational Bits metoden syftar till att öka förståelsen av ett material genom att låta deltagarna uppleva en specifik egenskap hos en teknik, kallad bit, och därigenom göra tekniken mer konkret. En uppsättning Inspirational Bits har designats, utvecklats och använts i workshops för att inspirera idéer om hur man kan använda AR i framtida hälsoapplikationer. Två tekniska koncept lyfts fram, detektion av verkliga objekt och placering av digitala objekt i en verklig miljö. Två typer av upplevelser lyfts också fram; annoteringsupplevelser där ytterligare information är kopplad till fysiska objekt och visualiseringsupplevelser där användare interagerar med ett virtuellt objekt. Bitarna utforskades i workshops följt av en snabb brainstorming för att snabbt få deltagarnas idéer på papper. Det verkar ha varit lättare att komma på idéer om annoteringsupplevelser jämfört med visualiseringserfarenheter vilket kan bero på att deltagarna förväntade att AR kommer att användas som ett verktyg för att åstadkomma digitala interaktioner i den verkliga världen, liknande hur annoteringsupplevelser fungerar. Eftersom många av de hälsoämnen som togs upp handlar om externa föremål som påverkar kroppen och hälsan kan annoteringsupplevelser vara mer lämpliga eftersom det kan användas för att fästa privat information till offentliga objekt.

Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 131-142).
With data becoming increasingly available in recent years, black-box algorithms like boosting methods or neural networks play more important roles in the real world. However, interpretability is a severe need for several areas of applications, like health care or business. Doctors or managers often need to understand how models make predictions, in order to make their final decisions. In this thesis, we improve and propose some interpretable machine learning methods by using modern optimization. We also use two examples to illustrate how interpretable machine learning methods help to solve problems in health care. The first part of this thesis is about interpretable machine learning methods using modern optimization. In Chapter 2, we illustrate how to use robust optimization to improve the performance of SVM, Logistic Regression, and Classification Trees for imbalanced datasets. In Chapter 3, we discuss how to find optimal clusters for prediction. we use real-world datasets to illustrate this is a fast and scalable method with high accuracy. In Chapter 4, we deal with optimal regression trees with polynomial function in leaf nodes and demonstrate this method improves the out-of-sample performance. The second part of this thesis is about how interpretable machine learning methods improve the current health care system. In Chapter 5, we illustrate how we use Optimal Trees to predict the risk mortality for candidates awaiting liver transplantation. Then we develop a transplantation policy called Optimized Prediction of Mortality (OPOM), which reduces mortality significantly in simulation analysis and also improves fairness. In Chapter 6, we propose a new method based on Optimal Trees which perform better than original rules in identifying children at very low risk of clinically important traumatic brain injury (ciTBI). If this method is implemented in the electronic health record, the new rules may reduce unnecessary computed tomographies (CT).
by Yuchen Wang.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center

The purpose of this study was to assess user preference of three smartphone applications, My Net Diary, My Fitness Pal, and Lose It. Applications across different smartphone platforms were used. Specifically the study evaluated users' view regarding the app's (a) convenience, (b) satisfaction with the nutrient analysis reports, and (c) perceived behavior change.

Participants (n=50) were obtained from Introductory Nutrition Classes at California State University, Long Beach and assigned an app to use for a duration of2 weeks. After that time an email was sent including a link to the Survey Monkey questionnaire. The results, using ANOVAs, indicated no significant differences between the apps in users' view regarding (a) convenience, (b) satisfaction with the nutrient analysis reports, and (c) perceived behavior change. The insignificant results could be attributed to the fact that these apps are widely popular and cited on top 10 lists. Further study is warranted.

This thesis explores requirements for a health website made to support Cuba’s and its people’s development, in terms of improved health and wellbeing, through access to user-centred online health information. The study uses semi-structured interviews to investigate how health information is accessed in Cuba today, the need for certain types of health information, and the role of the currently limited internet access in Cuba. The study shows that Cubans often turn to friends, family, and contacts to access health information, due to the slow process of accessing it through the local clinics and the limited possibilities of accessing it online. The study also shows there is a demand for a wider range of health information than what is currently accessible from official sources, in addition to health information that is adapted specifically to Cuban conditions. Employing research based around health website and low-bandwidth design, the study uses the requirements established from the interviews as a basis in the production of a development proposal for a Cuban, user-centred health website.

This thesis designed and implemented efficient deep learning methods to solve classification and segmentation problems in two major health informatics domains, namely pervasive sensing and medical imaging. In the area of pervasive sensing, this thesis focuses only on food and related scene classification for health and nutrition analysis. This thesis used deep learning models to find the answer of two important two questions, “where we eat?’’ and ‘’what we eat?’’ for properly monitoring our health and nutrition condition. This is a new research domain, so this thesis presented entire scenarios from the scratch (e.g. create a dataset, model selection, parameter optimization, etc.). To answer the first question, “where we eat?”, it introduced two new datasets, ``FoodPlaces'', ``EgoFoodPlaces'' and models, “MACNet”, “MACNet+SA” based on multi-scale atrous convolutional networks with the self-attention mechanism. To answer the second question, “what we eat?”, it presented a new dataset, ``Yummly48K'' and model, ``CuisineNet'‘, designed by aggregating convolution layers with various kernel sizes followed by residual and pyramid pooling module with two fully connected pathway. The proposed models performed state-of-the-art classification accuracy on their related datasets. In the field of medical imaging, this thesis targets skin lesion segmentation problem in the dermoscopic images. This thesis introduced two novel deep learning models to accurately segment the skin lesions, “SLSDeep” and “MobileGAN” based on dilated residual with pyramid pooling network and conditional Generative Adversarial Networks (cGANs). Both models show excellent performance on public benchmark datasets.

The emerging research issues in evidence-based healthcare decision-making and explosion of comparative effectiveness research (CER) are evident proof of the effort to thoroughly incorporate the rich data currently available within the system. The flexibility of Bayesian data mining techniques lends its strength to handle the challenging issues in the biomedical and health care domains. My research focuses primarily on Bayesian data mining techniques for non-traditional data in this domain, which includes, 1. Missing data: Matched-pair studies with fixed marginal totals with application to meta-analysis of dental sealants effectiveness. 2. Data with unusual distribution: Modeling spatial repeated measures with excess zeros and no covariates to estimate U.S. county level natural fluoride concentration. 3. Highly irregular data: Assess overall image regularity in complex wavelet domain to classify mammography image. The goal of my research is to strengthen the link from data to decisions. By using Bayesian data mining techniques including signal and image processing (wavelet analysis), hierarchical Bayesian modeling, clinical trials meta-analyses and spatial statistics, this thesis resolves challenging issues of how to incorporate data to improve the systems of health care and bio fields and ultimately benefit public health.

Context. One of the challenges in requirement engineering is the ability using survey as a requirement-engineering tool towards the software to refine user’s requirements. For instance, with the development of the way of healthcare, many advances in technology transformed the way of healthcare. E-health application is one of the technologies. As more and more health information that is stored electronically, e- health applications have given rise to trust issue in the area of data sharing. Identified the relationship between trust and data sharing based on the survey method is a valid approach, but the current studies still do not give a definite guideline about how requirement engineering should use a survey method step-by-step to refine the needs of users’ trust into software attributes. Based on the mentioned situation in e-health, defining a method to design survey to elicit requirements is needed. Objective. In this paper, the aim of the study is to design a survey method for refining user’s requirements of trust in requirement engineering based on the current state-of-art. The paper present the research on data sharing in e-health application. Methods. This study presented an action research, which identified the way about how to refine user’s requirement of trust. Survey was the main approach to do investigation among the e-health applications. Three cycles of AR were conducted in this paper, and three versions of questionnaires were designed in the research process in order to identify the factors that affected user’s trust in data sharing in e-health applications. Results. Through the action research, I found out three factors that affected user’s trust in data sharing, then the factors were identified, analysis and summarized, and the relationship between trusts and the factors is describe based on analysis results of the collected data, which obtain from the improved questionnaires. To find out the relationship between trust and the factors help present the process that how to design an accurate survey to refine user’s requirements. Based on the process and results of the action research, the survey guideline to refine user’s requirements of trust is designed and described. Conclusions. Based on the results that obtained in this study, I designed a preliminary survey guideline for refining user’s requirements of trust. This study will help requirement engineering to elicit requirement of trust in e-health based on a new and specific survey method.

Dissertation (Ph.D..) -- Worcester Polytechnic Institute.
Keywords: structural health monitoring; wavelet transform; time varying vibration modes; instantaneous modal parameters. Includes bibliographical references (p.181-186).

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2008.
Includes bibliographical references (p. 123-130).
Large population health insurance claims databases together with operations research and data mining methods have the potential of significantly impacting health care management. In this thesis we research how claims data can be utilized in three important areas of health care and medicine and apply our methods to a real claims database containing information of over two million health plan members. First, we develop forecasting models for health care costs that outperform previous results. Secondly, through examples we demonstrate how large-scale databases and advanced clustering algorithms can lead to discovery of medical knowledge. Lastly, we build a mathematical framework for a real-time drug surveillance system, and demonstrate with real data that side effects can be discovered faster than with the current post-marketing surveillance system.
by Margrét Vilborg Bjarnadóttir.
Ph.D.

This thesis investigates the development of structural health monitoring systems (SHM) for aerospace applications. The work focuses on each aspect of a SHM system covering novel transducer technologies and damage detection techniques to detect and locate damage in metallic and composite structures. Secondly the potential of energy harvesting and power arranagement methodologies to provide a stable power source is assessed. Finally culminating in the realisation of smart SHM structures. 1. Transducer Technology A thorough experimental study of low profile, low weight novel transducers not normally used for acoustic emission (AE) and acousto-ultrasonics (AU) damage detection was conducted. This included assessment of their performance when exposed to aircraft environments and feasibility of embedding these transducers in composites specimens in order to realise smart structures. 2. Damage Detection An extensive experimental programme into damage detection utilising AE and AU were conducted in both composites and metallic structures. These techniques were used to assess different damage mechanism within these materials. The same transducers were used for novel AE location techniques coupled with AU similarity assessment to successfully detect and locate damage in a variety of structures. 3. Energy Harvesting and Power Management Experimental investigations and numerical simulations were undertaken to assess the power generation levels of piezoelectric and thermoelectric generators for typical vibration and temperature differentials which exist in the aerospace environment. Furthermore a power management system was assessed to demonstrate the ability of the system to take the varying nature of the input power and condition it to a stable power source for a system. 4. Smart Structures The research conducted is brought together into a smart carbon fibre wing showcasing the novel embedded transducers for AE and AU damage detection and location, as well as vibration energy harvesting. A study into impact damage detection using the techniques showed the successful detection and location of damage. Also the feasibility of the embedded transducers for power generation was assessed.

Screening to detect diseases early is attractive as it can improve the prognosis and decrease costs, but it is often a problematic concept and there are several pitfalls. Many healthy individuals have to be investigated to avoid a disease in a few, which results in a dilemma because to save a few, many are exposed to a procedure that could potentially harm them. Other examples of problems associated with screening are latent diseases and over-treating. The question of optimal design of a screening program is another source of uncertainty for decision-makers, as a screening program may potentially be implemented in very different ways. This highlights the need for structured analyses that weigh benefits against the harms and costs that occur as consequences of the screening. The aim of this thesis is, therefore, to explore, develop and implement methods for health economic evaluations of screening programs. This is done to identify problems and suggest solutions to improve future evaluations and in extension policy making. This aim was analysed using decision analytic cost-effectiveness analyses constructed as Markov models. These are well-suited for this task given the sequential management approach where all relevant data are unlikely to come from a single source of evidence. The input data were in this thesis obtained from the published literature and were complemented with data from Swedish registries and the included case studies. The case studies were two different types of screening programs; a program of screening for unknown atrial fibrillation and a program to detect colorectal cancer early. Further, the implementation of treatment with thrombectomy and novel oral anticoagulants were used to illustrate how factors outside the screening program itself have an impact on the evaluations. As shown by the result of the performed analyses, the major contribution of this thesis was that it provided a simple and systematic approach for the economic evaluation of multiple screening designs to identify an optimal design. In both the included case studies, the screening was considered costeffective in detecting the disease; unknown atrial fibrillation and colorectal cancer, respectively. Further, the optimal way to implement these screening programs is dependent on the threshold value for cost-effectiveness in the health care sector and the characteristics of the investigated cohort. This is because it is possible to gain increasingly more health benefits by changing the design of the screening program, but that the change in design also results in higher marginal costs. Additionally, changes in the screening setting were shown to be important as they affect the cost-effectiveness of the screening. This implies that flexible modelling with continuously updated models are necessary for an optimal resource allocation.

The past two decades have seen an unprecedented increase in the amount of data collected on a daily basis. While consumer-orientated internet services, such as Google and Twitter, take up a large proportion of the former, advances in mobile technology and diagnostic tools have allowed biomedical applications to reach a similar scale in variety, velocity and volume. In the past, what used to be sparse biomedical data is now complemented with feature-rich, time-dependent information. As a result, the field is forced to consider novel approaches for extracting actionable information from time-series data sets, guaranteeing reliability and scalability of associated services as well as ensuring a high-degree of compliance from data sources. This thesis focuses on providing an in-depth evaluation of time-series analyses, scalable IT infrastructure and strategies for improved user engagement. In order to reflect the breadth and broadness of biomedical applications, the topics were distilled into two distinct studies in the fields of remote symptom detection, and large scale patient monitoring.

The increased implementation of digital health technologies requires a better understanding of how to design technologies and services that enhance people's engagement with their health. This thesis contributes new knowledge about i) an increased understanding of the different ways in which people engage with digital health technologies, ii) the stages of people's engagement with digital health technologies over time, and iii) the features that support such engagement. The findings offer new directions for the digital health industry to further develop their service design. They also support people's engagement with their health goals through tailoring their services more effectively to end-users.

Användarchurn är ett stort problem för mobile applikationer, och speciellt för älsoapplikationer. Eftersom mobila applikationer är en så ny industri finns det nästan ingen forskning om churn i mobila applikationer, och ingen forskning alls om fokuserad på churn i hälsoapplikationer. Syftet med den här studien var att undersöka vilka dimensioner ett företag med en mobil hälsoapplikation måste ta hänsyn till för att analysera churn, samt att ge dem verktyg för att själva analysera churn i framtiden. Studien gjordes i for m av en case - studie på företaget Lifesum. En omfattande   litteraturstudie genomfördes för att skapa ett initia l ramverk för att analysera churn i en hälsoapplikation. Intervjuer gjordes med både användare samt anställda på Lifesum, med frågor baserade på det initiala ramverket. Resultatet av intervjuerna användes sen för att förbättra ramverket, för att ge en mer korrekt bild av churn i en mobil hälsoapplikation. Resultatet användes också för att skapa en sammanställning av churn på case - företaget Lifesum. Studien resulterade I ett ramverk med flera olika dimensioner, med flera olika kopplingar. De imensioner som främst påverkar churn är användarnöjdhet samt bytesbarriärer, och de är i  in tur influerade av andra faktorer. Analyses av churn i Lifesum - applikationen visar att churn är komplext. Användare har flera olika syften med att använda applikationen, samt ännu fler anledningar till varför de slutar använda appen. Ett diagram som kartlägg er de olika användarna presenteras, men en analys om hur applikationen behöver förändras för att passa behoven av de olika användargrupperna. En  rekommendation ges också till företag att undersöka vilken typ an användare de vill fokusera på, baserat både på vad de kan göra samt vilken riktning de vill att applikationen ska ta.
User churn is a big problem for mobile applications, and in particular for healthapplications. Because mobile applications is such a new industry there is almost no research on churn in mobile applications, and none at all regarding health. The purpose of this research was to explain what dimensions a mobile health application company need to take into account when analyzing churn, and provide them with the tools to analyze churn in the future.The study was done in the form of a case study at the mobile health company Lifesum. An extensive literature study was conducted to create an initial framework for analyzing user churn in a health application. Interviews were conducted with both users and with Lifesum employees, with questions based on the initial framework. The results of the interviews were then used to augment the initial framework, to represent a more accurate image of user churn in a mobile health application. The results of the interviews were also used to create an overview of churn in the specific case study of the Lifesum app.The outcome of the study was a framework with many different dimensions, with intricate connections between them. The main dimensions influencing user churn are user satisfaction and switching barriers, and they are in turn influenced by other factors. The analysis of churn in the Lifesum application shows that churn is complex. Users have many different purposes for using the app, and even more reasons for why they stop using the application. A diagram mapping the different users is presented, with analysis regarding how the app needs to change to cater to the different user groups. A recommendation is also given for companies to investigate which type of users they want to cater to, based on both what they can do and what direction they want the application to go.

Purpose ReadNPlay for a Bright Future develops a variety of projects aimed at promoting healthy living in families with young children in Appalachian Tennessee. The purposes of this research are to collect parents’ and caregivers’ perspectives on healthy eating for the purpose of designing a new book in the ReadNPlay children's book series to be entitled A Farmers Market Adventure and to collect the preferences of parents and guardians related to website and mobile application (app) usage to help shape the development of a new ReadNPlay My Baby Book app. Methods Anonymous clipboard surveys were administered to attendees of regional community events during July of 2014. Survey items asked parents about healthy eating in the context of their families and the role of parenting websites and mobile apps in their families. The results from these surveys were summarized using Excel. A total of 100 surveys were collected. Results It was found that when parents were asked to identify barriers to healthy eating, the most common responses were picky eaters in the household (30%) followed by lack of time (22%). When asked to identify things that have helped parents to encourage healthy eating in their families, the three most common responses were good recipes (20%), good role models (16%), and farmers markets (16%). Twenty-eight percent of parents surveyed do not use websites or apps for parenting, while those who do use parenting websites or apps identified advice from experts (20%) and advice from other parents (18%) to be the two features most commonly desired in such a resource. When asked what they do not like about website and app usage, 20% of parents indicated that these tools are “too complicated.” However, when parents are told that our group of pediatricians was developing a free mobile application for families designed to help them keep track of their baby’s growth, development, and eating habits, 75% of parents said such an app would be very helpful to them (25% said a little helpful). Conclusion These results will inform a new ReadNPlay children's book themed around healthy eating behaviors, overcoming pickiness, and shopping with families at farmers markets and a new ReadNPlay mobile app for families to use in conjunction with infant-toddler well child visits.

Introduction: Despite the method existing for centuries, uses of crowdsourcing have been rising rapidly since the term was coined a decade ago. Crowdsourcing refers to ‘outsourcing’ a problem or task to a large group of people (i.e., a crowd) rapidly and cheaply. Researchers debate over definitions of crowdsourcing, and it is often conflated with mHealth, web 2.0, or data mining. Due to the inexpensive and rapid nature of crowdsourcing, it may be particularly amenable to health research and practice, especially in a global health context, where health systems, human resources, and finances are often scarce. Indeed, one of the dominant methods of health research prioritization uses crowdsourcing, and in particular, wisdom of the crowds. This method, called the Child Health and Nutrition Research Initiative (CHNRI) method, employs researchers to generate and rank research options which are scored against pre-set criteria. Their scores are combined with weights for each criterion, set by a larger, diverse group of stakeholders, to create a ranked list of research options. Unfortunately, due to difficulties in defining and assembling a group of stakeholders that would be appropriate to each exercise, 75% of CHNRI exercises to-date did not involve stakeholders, and therefore presented unweighted ranks. Methods: First, a crowdsourcing was defined through a literature review. Benefits and challenges of crowdsourcing were explored, in addition to ethical issues with crowdsourcing. A second literature review was conducted to explore ways in which crowdsourcing has been already used in health and global health. As crowdsourcing could be a potential solution to data scarcity or act as a platform for intervention in global health settings, but its potential has never been systematically assessed, a CHNRI exercise was conducted to explore potential uses of crowdsourcing in global health and conflict. Experts from both global health and crowdsourcing participated in generation and scoring ideas. This CHNRI exercise was conducted in-line with previously described steps of the CHNRI method for setting health research priorities. As three quarters of CHNRI exercises have not utilized a larger reference group (LRG) of stakeholders, and the public was cited as the most difficult stakeholder group to involve, we conducted a survey using Amazon Mechanical Turk, an online crowdsourcing platform, that involved an international group of predominantly laypersons who, in essence, formed a public stakeholder group, scoring the most common CHNRI criteria using a 5-point Likert scale. The resulting means were converted to weights that can be used in upcoming exercises. Differences in geographic location, and whether the respondents were health stakeholders were assessed through the Fisher exact test and Wilcoxon rank-sum test, respectively. The influence of other demographic characteristics was explored through random-intercept modelling and logistic regression. Finally, an example of a national-level CHNRI exercise, which is the largest CHNRI conducted to-date, exploring research priorities in child health in India is described. Results: A comprehensive definition of crowdsourcing is given, along with its benefits, challenges, and ethical considerations for using crowdsourcing, based on a literature review. An overview of uses of crowdsourcing in health are discussed, and potential challenges and techniques for improving accuracy, such as introducing thresholds, qualifiers, introducing modular tasks and gamification. Crowdsourcing was frequently used as a diagnostics or surveillance tool. The CHNRI method was not identified in the second literature review. In re-weighting the CHNRI criteria using a public stakeholder group, we identified differences in relative importance of the criteria driven by geographic location and health status. When using random-intercept modelling to control for geographic location, we found differences due to health status in many criteria (n = 11), followed by gender (n = 10), ethnicity (n = 9), and religion (n = 8). We used the CHNRI method to explore potential uses of crowdsourcing in global health, and found that the majority of ideas were problem solving or data generation in nature. The top-ranked idea was to use crowdsourcing to generate more timely reports of future epidemics (such as in the case of Ebola), and other ideas relating to using crowdsourcing for the surveillance or control of communicable disease scored highly. Many ideas were related to the United Nations’ Sustainable Development Goals (SDGs). Finally, a national-level exercise to set research priorities in child health in India identified differential priorities for three regions (Empowered Action Group and North Eastern States, Northern States and Union Territories, and the Southern and Western States). The results will be very useful in developing targeted programmes for each region, enabling India to make progress towards SDG 3.2. Conclusion: Crowdsourcing has grown exponentially in the past decade. Integrating gamification, machine learning, simplifying tasks and introducing thresholds or trustworthiness scores increases accuracy of results. This research provides recommendations for improvements in the CHNRI method itself, and for crowdsourcing, generally. Crowdsourcing is a rapid, inexpensive tool for research, and thus, is a promising data collection method or intervention for health and global health.