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M. Tech. (Department of Process Control and Computer System, Faculty of Engineering and Technology), Vaal University of Technology. / Personal health record system (PHRS) is a tool that is used in maintaining the health and wellness of an individual as well as helping with illness of an individual. PHRS gives the individual access to a wide range of credible health information, data, and knowledge. Individuals can use that access to improve their health and manage their diseases. Patients with chronic illness can track and manage their health in conjunction with their health provider, this will promote early intervention when they encounter an abnormality or complications. Continuous monitoring and storing of health information has been a challenge for patients and health providers. Personal health data monitoring and retrieval system for health providers was designed and implemented. The main aim of this study was to develop an accurate, secure and flexible personal health data monitoring and retrieval system for health providers (PHRS). This was achieved. The research showed that when a patient health information (Electrocardiogram (ECG) and temperature) was monitored, the heartbeat (ECG) sensor output the value as an analog value to the signal processing (NodeMCU) which was then converted to a digital value. The temperature sensor used in this research is a digital sensor which lowers the amount of ADC conversion that was done. The digital values are displayed on LCD, its send to a personal health data storage system which was designed for health information storage purposes. It also sends the value to a retrieval system which is an android application that is connected to the data storage system to display health information to the health providers from a remote location. Personal health data storage and the retrieval system are secure due to the Message queuing telemetry transport (MQTT) protocol used in the application layer. The MQTT protocol is secure due to the secure socket layer (SSL) which is an encryption based on presentation layer embedded inside the MQTT protocol. After the comparison of the software simulation and the prototype test, the differences in the value for the heartbeat and temperature sensor indicate 0.04 BPM and 0.04 oC which shows the accuracy of the sensing circuit. Personal health data monitoring and retrieval system developed is applicable and useful to multiple entities in and around South Africa such as; Ministry of health, hospitals, sport and recreations.

Our population is becoming older and with that, the development of chronic diseasesis is also expected to increase. A chronic illness is a long-term illness which lasts throughout a lifetime, or at least for a very long time. A large part of healthcare resources is already devoted to treating chronically ill patients. These patients are often dependent of both care and medication to maintain a meaningful life. To gain a holistic view of these patients health condition by one/two appointments with physicians yearly is not sufficient in order to conclude a certain health-state. The course of disease for these patients changes daily and require follow-up on disease progression continuously to adapt an appropriate treatment plan. Collecting patient-generated health data (PGHD) facilitates in the process of retrieving moreevidence for better assessment of the disease development. While there is obvious importance and benefit of using of PGHD, this data is not commonly used in healthcare.  Further investigation is needed to understand how PGHD can be more useful. This pilot study provides knowledge of the success and failure factors of using PGHD for mainly chronically ill patients, but can be applied to other patient-groups as well. The aim of this thesis work was to collect information about what suppliers, governmental organizations and healthcare professionals require for using PGHD in healthcare setting in a greater extent in the future. Methods used to gather information were participatory interviews in combination with qualitative interview questions. Pattern recognition has been created through a thematic analysis andcluster mapping. The data collection resulted in four areas of improvement; patient behaviour, healthcare organization, digitized health data and equipment. The result shows overall a positive attitude towards the concept of PGHD by all sectors asked in this project. Stakeholders agree on that PGHD can generate positive outcomes for chronically ill patients. The belief of improving workflow in healthcare with PGHD was also positive. The valuable possibilities generated with PGHD are tailored careflows, improved evaluation of disease status and enhanced quality of care and well-being among others. Additionally, several ongoing projects are taking place, which demonstrate great interest in the area. However, before PGHD can be prescribed by healthcare, studies have to be performed including development of national guidelines for reporting PGHD, building a secure infrastructure and introducing new work routines. Future work will be applying AI-analysis of reported PGHD to facilitate the work of caregivers and development of secure storing solutions for instance with block-chain technology. / Vår befolkning blir äldre och med det förväntas utvecklingen av kroniska sjukdomar också att öka. En kronisk sjukdom kallas också för en långvarig sjukdom som varar under hela livet eller åtminstonde under mycket lång tid. En stor del av vårdresurserna ägnas redan åt att behandla kroniskt sjuka patienter. Dessa patienter är ofta beroende av både vård och medicinering för att upprätthålla ett meningsfullt liv. För att få en helhetssyn på dessa patienters hälsotillstånd krävs mer än en eller två möten med sjukvården årligen. Ett fåtal möten per år är inte tillräckligt för att konstatera en rättvis bild av hälsotillståndet. Sjukdomsförloppet för dessa patienter förändras dagligen och kräver fortlöpande uppföljning av sjukdomsutvecklingen för att förstå och anpassa en lämplig behandlingsplan. Insamling av patientgenererad hälsodata (PGHD) underlättar och hjälper till i denna process. Det finns uppenbarliga fördelar med PGHD, men datan används inte vanligtvis i sjukvården. Ytterligare forskning behövs för att förstå hur PGHD kan vara mer användbart. Denna pilotstudie ger kunskap om inflytelserika faktorer för att använda PGHD för huvudsakligen kroniskt sjuka patienter, men kan också tillämpas på andra patientgrupper. Syftet med detta avhandlingsarbete var att samla in information om vad leverantörer, statliga organisationer och vårdpersonal kräver för att använda PGHD i vårdmiljö i framtiden. Metoder som använts för att samla in information var deltagande intervjuer i kombination med kvalitativa intervjufrågor. Resultatet har genomgått en klusterkartläggning och tematisk analys för att skapa mönsterigenkänning. Datainsamlingen resulterade i fyra områden; patientbeteende,vårdorganisation, digitaliserad hälsodata och utrustning. Resultatet visar en positiv inställning till PGHD enligt alla deltagare i studien.Deltagarna är överens om att PGHD kan generera positiva resultat för kroniskt sjuka patienter. Tron att förbättra arbetsflödet inom hälso-och sjukvård med PGHD var också positiv. De värdefulla möjligheterna som genereras med PGHD är bl.a. skräddarsydda vårdflöden, förbättrad utvärdering av sjukdomstatus och förbattradk valitet på vård och välmående bland andra. Dessutom pågår flera pågående projekt som visar stort intresse för området. Innan PGHD kan börja förskrivas av hälsovården måste det utföras fler studier som inkluderar framtagning av nationellariktlinjer för rapportering av PGHD, byggandet av en säker infrastruktur och introduktion av nya arbetsrutiner. Framtida arbete kvarstår dår tillämpning av AI analysmodeller på rapporterad PGHD samt utveckling av säkra lagringslösningar, förslagsvis med blockkedjeteknik, bör vidareutvecklas.

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-09-28T13:43:00Z No. of bitstreams: 1 ANTÔNIO DIAS DOS SANTOS JÚNIOR - DISSERTAÇÃO PPGCC 2013..pdf: 8158081 bytes, checksum: 790c106478af0576230e745f36a8b2d2 (MD5) / Made available in DSpace on 2018-09-28T13:43:00Z (GMT). No. of bitstreams: 1 ANTÔNIO DIAS DOS SANTOS JÚNIOR - DISSERTAÇÃO PPGCC 2013..pdf: 8158081 bytes, checksum: 790c106478af0576230e745f36a8b2d2 (MD5) Previous issue date: 2013-03-15 / Capes / Os avanços alcançados na área de tecnologia da informação e comunicação trouxeram a possibilidade de realizar em casa o monitoramento da saúde, o que antes só podia ser feito em locais especializados, como clínicas e hospitais. O monitoramento realizado no conforto da casa dos indivíduos permite prover serviços para um maior número de pessoas, otimizando o uso de recursos humanos e financeiros. Porém, este sistema de monitoramento enfrenta problemas, sendo o principal deles a dificuldade de uso e a falta de motivação dos usuários. Embora já exista a possibilidade e viabilidade em usar sensores para monitoramento, essa é uma atividade que ainda não está integrada ao cotidiano das pessoas. Para resolver o problema de falta de motivação nos usuários, jogos eletrônicos vêm sendo fortemente utilizados como ferramenta motivadora. Entretanto, os jogos que tentam motivar o jogador a exercitar-se ou a ser monitorado geralmente requerem que o jogador habitue-se com um estilo de jogo que não é parte de seu cotidiano. As ações realizadas dentro do jogo não são parte de seus jogos preferidos. Neste trabalho apresenta-se um arcabouço de software para monitorar dados de saúde através de jogos eletrônicos. Sua forma de captura de dados permite criar jogos para monitoramento ainda mantendo a jogabilidade. A validação do arcabouço se deu com o desenvolvimento de dois jogos, os quais foram testados com 18 pessoas na faixa de idade de 19 a 27 anos do Laboratório Embedded, da Universidade Federal de Campina Grande, e do Instituto Federal de Alagoas. Os resultados indicaram que os jogos foram considerados divertidos pela maioria das pessoas, que também declararam que os incluiriam em sua rotina diária. Além disso, foi possível coletar os dados de saúde de maneira a utilizá-los para a detecção de doenças motoras. / Health monitoring, which could only be done in specialized places, such as clinics and hospitais, can now be performed at home thanks to the advances in Information and Communication Technologies. Monitoring health data in the comfort of one's homes allows the provision of services to a greater number of people, optimizing human and financial resources. However, this system faces problems such as difficulty of use and lack of motivation in users. Although it is feasible to use sensors to monitor people, this is still something not easy to integrate to their daily lives. To tackle the lack of motivation among people who need to be monitored, electronic games have been extensively used as a motivational tool. However, games that intend to motivate the player to exercise or to be monitored usually have a different gameplay than what the player would enjoy. This work presents a software framework to monitor health data through electronic games, allowing it to be acquired while keeping the playability. The framework was used for the development of two games, tested by 18 people with ages ranging from 19 to 27, from the Embedded Laboratory at the Federal University of Campina Grande, and Federal Institute of Alagoas. Results showed that most people found the games to be funny, and also stated that they would include the games in their daily routine. Also, it was possible to collect health data to be used in the detection of motor diseases.

我國於2015年底通過新修正之個人資料保護法（以下簡稱「個資法」），將病歷納入特種個人資料中保護。目前個資法第六條特種個人資料列舉包含病歷、醫療、基因、性生活、健康檢查及犯罪前科之個人資料。雖然該條文係取法自國際賦予敏感性個人資料特別保護的模式，惟在個人相關健康資料保護部分，我國個資法不若歐盟一般資料保護規則（EU General Data Protection Regulation, GDPR）保護寬廣，納入資料之類型仍較國際立法例狹窄。尤其此次GDPR修法擴大特種個人資料空間，增列基因資料、生物性資料和性傾向，檢視我國特種個人資料列舉類型是否符合現今科技社會需求有其必要性。 過去研究針對健康資料個資法適用問題較少。大數據資料來源來自各處，以一般健康保健物聯網模式為例，自行操作之檢查數據或穿戴式裝置所蒐集之資料，若非須由醫師或其他之醫事人員施以檢查，而可由一般民眾自行測量之行為，該民眾自行測量之結果應不屬於個資法所謂之病歷、醫療或健康檢查個人資料，即非為特種個人資料。 惟大數據分析技術進步之環境下，健康資料亦攸關資料主體生理健康之敏感性，且容易連結並識別個人，考量健康資料敏感性提升，蒐集、處理、利用健康資料易侵犯到個人隱私，因此有加強保護之需求。將來可刪除個資法第六條第一項各種個人資料例示之「醫療」、「病歷」與「健康」資料，並新增「健康」或「與健康相關」之列舉項目。 但解釋「與健康相關」資料之內涵時不能無限上綱，在適用時應考量情境說，依據不同使用情境判斷是否為係作為特種個人資料利用，以排除一般性描述健康的使用情境。 / The change to the regulation of special categories of data (sensitive data) in the Taiwan Personal Information Protection Act (PIPA) in 2015 comes with the inclusion of medical records. The definition of sensitive data in the PIPA Article 6(1) refers to personal information of medical records, medical treatment, genetic information, sexual life, health examination and criminal records. However, the list of sensitive data in PIPA do not contain categories as broad as foreign legislation such as EU General Data Protection Regulation (GDPR). It is important to review the continuing relevance of existing categories of sensitive data in the light of change in social structures and advances in technology. Differ from “medical data” such as medical records, medical treatment and health examination, the collection, process and use of “health data” which is measured from wearable device, is not included in the sensitive data. Concerning the development of big data analysis, the “health data” which sensitivity enhanced is easy to identify an individual. It needs to give a higher level of protection to “health data” under PIPA. Therefore, this thesis suggests that medical records, medical treatment and health examination in PIPA Article 6(1) should be consolidated and amended to health records or data concerning health. However, this is not to say that the processing of all kinds of medical and health data should be regarded as the processing of sensitive data. But data, under certain contexts/circumstances may be treated as the processing of sensitive data.

The exponential rise in the generation of data has introduced many new areas of research including data science, data engineering, machine learning, artificial in- telligence to name a few. It has become important for any industry or organization to precisely understand and analyze the data in order to extract value out of the data. The value of the data can only be realized when it is put into practice in the real world and the most common approach to do this in the technology industry is through software engineering. This brings into picture the area of privacy oriented software engineering and thus there is a rise of data protection regulation acts such as GDPR (General Data Protection Regulation), PDPA (Personal Data Protection Act), etc. Many organizations, governments and companies who have accumulated huge amounts of data over time may conveniently use the data for increasing business value but at the same time the privacy aspects associated with the sensitivity of data especially in terms of personal information of the people can easily be circumvented while designing a software engineering model for these types of applications. Even before the software engineering phase for any data processing application, often times there can be one or many data sharing agreements or privacy policies in place. Every organization may have their own way of maintaining data privacy practices for data driven development. There is a need to generalize or categorize their approaches into tactics which could be referred by other practitioners who are trying to integrate data privacy practices into their development. This qualitative study provides an understanding of various approaches and tactics that are being practised within the industry for privacy preserving data science in software engineering, and discusses a tool for data usage monitoring to identify unethical data access. Finally, we studied strategies for secure data publishing and conducted experiments using sample data to demonstrate how these techniques can be helpful for securing private data before publishing. / Graduate

This project aimed to enhance communication and collaboration among care providers in Stockholm Region and Stockholm Municipality by analyzing health data in various medical record systems and identifying the data that needs to be shared to support elderly individuals with multi-morbidity. Interviews with health experts, caregivers, and policymakers, as well as a literature review, were conducted to gather data. The findings indicated that caring for multi-morbid elderly individuals poses many challenges, including managing multiple chronic conditions, the risk of adverse drug interactions, physical and emotional burden, reduced functional ability, social isolation, and economic consequences. A holistic approach to care is needed, including coordinating care across multiple specialities, addressing social and psychological factors, and providing support for caregivers. Additionally, health data sharing could help with the challenges of ageing and multi-morbidity, but barriers to accessing relevant health data exist. The barriers include a lack of measurement values, different systems used in different healthcare facilities, outdated systems and a large amount of health data existing as free-text notes which make it difficult to extract useful information. Therefore, new HIE solutions are needed to improve patient safety and better integrate existing systems. Future work should focus on improving the accessibility and usability of health data, addressing security and privacy issues, and promoting standardization and interoperability. / Målet med detta projekt var att förbättra kommunikationen och samarbetet mellan vårdgivare i Stockholmsregionen och Stockholm kommun genom att analysera hälsodata i olika medicinska journalsystem och identifiera de data som behöver delas för att stödja multi-sjuka äldre. Intervjuer med hälsoexperter, vårdgivare och beslutsfattare samt en litteraturstudie genomfördes för att samla in data. Resultaten visade att vården för äldre personer med flera sjukdomar innebär många utmaningar, inklusive hantering av flera kroniska tillstånd, risken för biverkningar från läkemedel, fysisk och emotionell belastning, minskad funktionell förmåga, social isolering och ekonomiska konsekvenser. En helhetssyn på vården krävs, inklusive samordning av vården över olika specialiteter, beaktande av sociala och psykologiska faktorer och stöd till vårdgivare. Dessutom kan delning av hälsodata hjälpa till med utmaningarna med åldrande och flera sjukdomar, men det finns hinder för att få tillgång till relevant hälsodata. Hindren inkluderar brist på mätvärden, olika system som används i olika vårdinrättningar, föråldrade system och en stor mängd hälsodata som finns som anteckningar, vilket gör det svårt att extrahera användbar information. Därav, behövs nya lösningar för hälsodata-utbyte för att förbättra patientens säkerhet och bättre integrera befintliga system. Framtida arbete bör fokusera på att förbättra tillgängligheten och användbarheten hos hälsodata, hantera säkerhets- och integritetsfrågor och främja standardisering och interoperabilitet.

Health practitioners collect health data on a daily basis at health facility levels in order to monitor and evaluate the performance of priority national health programmes (District Health Plan 2012:6). Routine data quality for health programmes monitoring need a collective intervention to ensure clear understanding for what data to be collected at primary health care setting. The aim of the study is to explore the understanding of routine health data, determine the use of routine data and feedback mechanism at primary health care clinic setting. Quantitative descriptive research design was used to answer the research question on this research study. Structured data collection questionnaire was used for the study to accomplish the research purpose and reach the study objectives. A total of 400 participants was sampled, and 247 responded. One of the findings was that the understanding of routine health data by Health Practitioners was at 82.6% (% = f/n*100, f= 3242 and n= 3926). / Health Studies

Health practitioners collect health data on a daily basis at health facility levels in order to monitor and evaluate the performance of priority national health programmes (District Health Plan 2012:6). Routine data quality for health programmes monitoring need a collective intervention to ensure clear understanding for what data to be collected at primary health care setting. The aim of the study is to explore the understanding of routine health data, determine the use of routine data and feedback mechanism at primary health care clinic setting. Quantitative descriptive research design was used to answer the research question on this research study. Structured data collection questionnaire was used for the study to accomplish the research purpose and reach the study objectives. A total of 400 participants was sampled, and 247 responded. One of the findings was that the understanding of routine health data by Health Practitioners was at 82.6% (% = f/n*100, f= 3242 and n= 3926). / Health Studies