The ongoinging demographic change will increase the demands on health care with an increase of old people suffering from long-term conditions in need of care. One way of meeting this increasing demand is to combine the use of modern technology and the involvement of patients by letting patients monitor their health themselves.  The use of patient-generated health data (PGHD) can benefit both patients and the health care and is an area that is being studied internationally. In this thesis work, two parts of the area of using PGHD in health care have been studied. First eleven professionals from the field of health care (both medical professionals, strategists and project leaders) were interviewed regarding their opinions on PGHD. They were generally positive to the phenomena and mentioned several types of measurements they found to be suited for PGHD. Among these measurement types were blood pressure, weight, blood glucose, electrocardiogram (ECG), peak expiratory flow (PEF), blood oxygen saturation and a variety of blood tests. The professionals found the greatest benets of PGHD to be the increased freedom and quality of life it offers to patients and the increased engagement to their own care it may lead to. The greatest concerns were related to technology problems and the patients using the measurement devices incorrectly. The second part of the work investigated how measurements of weight, blood pressure and ECG would be transferred from the device used by the patient to the electronic health record (EHR) in a standardized way. For the transfer being standardized, the study followed the Continua design guidelines (CDG), which are based on international standards and aim to achieve plug-and-play interoperability among health care devices and systems. This part of the study was carried out by studying the CDG documents as well as the standards to which they refer. The measurement data from the three device types were all described to be handled as numeric values, but in different formats. The weight is a single value, the blood pressure is a compound of values: systolic, diastolic and mean arterial pressure, and the ECG is an array of values. All measurement data is contained in a specic message together with additional data such as device type, device manufacturer, a reference ID and the date and time of the measurement. The data message is transferred from the measurement device to an application hosting device (AHD) with either a touch area network interface (using Near-Field Communications), personal area network interface (using USB or Bluetooth communication) or local area network interface (using ZigBee communication). From the AHD the data transfer chain continues until the data reaches the EHR.

The act of people collecting their health data through health apps on their smartphones is becoming increasingly popular. Still, it is difficult for healthcare providers to use this patient-generated health data since health apps cannot easily share its data with the health care providers’ Electronic Health Records (EHR). Simultaneously, it is becoming increasingly popular to use low-code platforms for software development. This thesis explored using low-code platforms to create applications intended to collect patient-generated health data and send it to EHRs by creating a web application prototype with the low-code platforms Mendix and Better EHR Studio. During the web application prototype development, the developer conducted a diary to capture their impressions of Mendix to show how a developer experiences developing in a low-code platform compared to traditional programming. The result shows that it is impractical to create applications intended to collect patient-generated health data with the two low-code platforms chosen. The analysis of the conducted diary showed that using a low-code platform is straightforward but also challenging for an experienced software developer.

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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.