This study is a qualitative research on the faciliating and impeding factors that influence Hong Kong citizen's adoption of Electronic Health Record Sharing System (eHRSS), the principal electronic health record (EHR) system in Hong Kong.  A majority of the previous studies of EHR among information systems (IS) literature either focused within the institutional or technological perspectives, or on the perspectives of healthcare institutions or healthcare professionals. Little research has been done from citizens' perspective on factors of their adoption of EHR. There is also little research specific to Hong Kong's circumstances. This research aims to provide an enhanced understanding on the factors that influence citizens' EHR adoption through looking into eHRSS adoption in Hong Kong. It aims to provide contributions to bridge the knowledge gaps by providing a better understanding on adoption factors from citizens' perspective, and investigate into whether there are any unique factors applicable to Hong Kong. In this study, semi-structured interviews had been performed on participants covering various age groups to collect their views and opinions concering their adoption of eHRSS. With reference to theoretical constructs on user acceptance and adoption, this study identifies four facilitating factors for citizens' adoption of eHRSS, namely (i) knowledge, (ii) trust, (iii) perceived potential health benefits and (iv) flexibility and "stickiness" of continual use. Four impeding factors for citizens' non-adoption were also identified, namely (i) difficulty in registration, low level/lack of trust in EHR implementation, (iii) negativity on acceptance of new technology and (iv) perceived difficulty in usage.  In the concluding remarks, way forward for future research has been outlined. Practical recommendations have also been formulated for reference by relevant authorities in administering eHRSS in Hong Kong.

The introduction of federal initiatives and incentives regarding health information technology fostered a movement towards the adoption of electronic health records (EHR). Implementation of EHRs sparked discussions among healthcare providers, patients, and others about the benefits or challenges of the move from the traditional paper method to the electronic version in healthcare settings. A knowledge gap in research involving the usefulness of EHRs and their impact to the delivery of care in other settings exists. The purpose of this qualitative study was to explore public health providers' perceptions of the meaningful use of EHRs in a disaster setting. Study participants were public health providers from Louisiana recruited via criterion sampling and snowball sampling. A qualitative, phenomenological design was used to gain understanding of the public health providers' experiences with and perceptions of EHRs in a disaster setting. Data were collected from 7 public health providers using in-depth interviews and reflective journal notes. The data were analyzed for patterns and themes using the hermeneutic circle method. The study findings indicate that individuals want to be involved in designing their system and adjusting workflow in the workplace setting. The majority of participants concluded that EHR systems are beneficial in the disaster setting, but there were no impacts to improving health outcomes. The findings provide policymakers, public health departments, healthcare providers, emergency managers, and communities needed information on the potential impact of EHRs in the disaster setting on improving safe and effective care.

Information technology (IT) has been rapidly integrated into the healthcare industry, including nursing, and has the ability to reduce errors, cut cost, and enhance patient care. However, approximately 45% of the current nurse workforce lacks adequate training in computer skills, which may hinder the adoption of health-related IT in the workplace. Characteristics of Rogers's diffusion of innovation (relative advantage, compatibility, complexity, trialability, and observability) guided this project. This project was conducted to address the problem of IT adoption on a local level and was designed to assess whether simulation training on a generic electronic health record (EHR) system would improve the knowledge, skill, and attitude of nurses with little or no experience with EHR. A convenience sample of nurses (n = 13) unfamiliar with EHR was obtained by posting flyers in long-term care or home health agencies. The nurses completed the P.A.T.C.H. assessment scale v. 3 (2011) before and after participating in the one-time simulation training on EHR. Scores on the P.A.T.C.H. were calculated according to the established scoring system and revealed a positive increase nurses' attitude and self-efficacy toward the EHR system. Posttest scores yielded an increase ranging from 0.5 to 5 points from pretest scores, with an average pretest score of 54.23 on a scale of 0-100. The results of this project are consistent with the literature and current research and illustrate the importance of addressing the need for interactive training. This project contributes to social change in practice by enhancing the awareness of EHR in nurses who are new users of IT and promoting the adoption of technology in healthcare.

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Patient portals facilitate patients' access to their electronic health care records, and may also include features such as patient-clinician messaging, prescription renewal, and educational resources. There is evidence that portals support patient empowerment, therapeutic communication, adherence to treatment, and satisfaction with care. Nonetheless, patient portals are underutilized in mental health settings, with policies in some health care organizations restricting all access to mental health records through patient portals. A qualitative evidence synthesis was conducted to explore the perspectives of clinicians and patients on portal use in the mental health care context represented in the current literature. A systematic search of relevant databases, followed by citation and article screening, yielded 24 qualitative and mixed-methods studies for inclusion, and a thematic synthesis was performed. The synthesis yielded five themes: impacts to the efficiency of mental health care delivery; effects on therapeutic relationships between clinicians and patients; changes to the patient-clinician power balance; the suitability of patient portals for patients with mental illness; and the complexities of information management in mental health care. Ultimately, both clinicians and patients acknowledged numerous potential benefits of patient portals, but there were also concerns about their use specific to the mental health context. These concerns were voiced primarily by clinicians, and originated in part from concern for patient safety, but also from stigmatizing attitudes and the perceived threats of portals to clinicians' workloads and control over the record. This systematic review of qualitative studies highlights opportunities for organizations to support their clinicians through the implementation of recovery-oriented initiatives like patient portals, and to support patients with mental illness by ending discriminatory policies limiting access to their records.

Medical health providers use electronic health records (EHRs) to store information about patient treatment to support patient care management and securely share health information among healthcare organizations. EHRs have also been used in healthcare research in problems such as patient phenotyping, health risk prediction, and medical entity extraction. In this thesis, we focus on several important issues: (1) how to convert natural text from medical notes to vector representations suitable for deep learning algorithms, (2) how to help healthcare researchers select a patient cohort from EHRs, and (3) how to use EHRs to identify patient diagnoses and treatments. In the first part of the thesis, we present a new method for learning vector representations of medical terms. Learning vector representations of words is an important pre-processing step in many natural language processing applications. For example, EHRs contain clinical notes that describe patient health conditions and course of treatment in a narrative style. The notes contain specialized medical terminology and many abbreviations. Learning good vector representations of specialized medical terms can improve the quality of downstream data analysis tasks on EHR data. However, the traditional approaches struggle to learn vector representations of rarely used medical terms. To overcome this problem, we developed a neural network-based approach, called definition2vec, that uses external knowledge contained in medical vocabularies. We performed quantitative and qualitative analysis to measure the usefulness of the learned representations. The results demonstrate that definition2vec is superior to the state-of-the-art algorithms. In the second part of the thesis, we describe a new visual interface that helps healthcare researchers select patient cohorts from EHR data. Process of identifying patients of interest for observational studies from EHR data is known as cohort selection, a challenging research problem. We considered a problem of cohort selection from medical claim data, which requires identifying a set of medical codes for selection. However, there are tens of thousands of unique medical codes, and it becomes very difficult for any human to decide which codes identify patients of interest. To help users in defining a set of codes for cohort identification, we developed an interactive system, called Medical Claim Visualization system (MedCV), which visualizes medical code representations. MedCV analyzes a medical claim database and allows users to reason about medical code relationships and define inclusion rules for the selection by visualizing medical codes, claims, and patient timelines. Evaluation of our system through a user study indicates that MedCV enables domain experts to define inclusion rules efficiently and with high quality. The third part of the thesis is a study of the definition of acute kidney injury (AKI), which is a condition where kidneys suddenly cannot filter waste from the blood. AKI is a major cause of patient death in intensive care units (ICU) and it is critical to detect it early. Recently published KDIGO medical guideline proposed a clinical definition of AKI using blood serum creatinine and urine output. The KDIGO definition was developed based on the expert knowledge, but very little is known about how well it matches the medical practice. In this study, we investigated publicly available EHR data from 47,499 ICU admissions to determine the concordance between the KDIGO definition and AKI determination by the medical provider. We show that it is possible to find a formula using machine learning with much higher concordance with the medical provider AKI coding than KDIGO and discuss the medical relevance of this finding. / Computer and Information Science

Purpose:The thesis will shed light on the overall need of CDSSs in the Swedish health care system,  and  it  will  also  present  a  specific  efficiency  problem  that  could  be  solved  by implementing a CDSS. The need for a CDSS is where an implementation would improve patient outcome, by delivering the right care at the right time, and where the CDSS could reduce the cost of the delivered care. A better understanding of the current need could help eliminate the existing empirical gap and ultimately lead to better and more efficient health care in Sweden. The research question was formulated as: Where within Swedish health care can a need for increased efficiency be met through the implementation of a realistic CDSS system? Design and methodology: The  thesis  is  a  case  study  where qualitative data, collected through a literature review and interviews, was used to answer the research question. The methodology used was tailored to the unique setting of the research and in accordance to the purpose of the study. The method was divided into five phases. (1) Finding an area of focus, such as a specific diagnosis, within the health care system where the need for a CDSS system is deemed high. (2) Mapping the care chain of the identified area of interest. (3) Developing hypotheses concerning where in the care chain challenges could be solved using a clinical decision support system. (4) Confirming or rejecting the proposed hypotheses through interviews with relevant experts. (5) Presenting the specific efficiency problem that could be solved using a CDSS and a presentation of the design of said CDSS. Findings: The efficiency problem that could be solved using a CDSS was identified to be within the area of heart failure treatment. There were a multitude of areas of improvement found along the care chain and a number of them could be solved by developing and using specific CDSSs. A CDSS that could help physicians, within the primary care system, to identify patients that  could benefit from  being  assessed  by  cardiology specialist was  proposed  as  the  most beneficial  CDSS  system.  The  proposed  CDSS  would  be  both  beneficial  and  realistically implementable. / Syftet med uppsatsen är att belysa det övergripande behovet av kliniska beslutsstödssystem inom den svenska vården och slutligen finna det mest trängande behovet. En bättre förståelse för detta behov kan hjälpa att minska det existerande empiriska gapet och slutligen leda till en bättre och mer effektiv vård i Sverige. Forskarfrågan formulerades som uppdraget att finna ett behov för ökad effektivitet inom svensk sjukvård, som kan lösas genom implementering av ett realistiskt kliniskt beslutsstöd. Design och metodologi: Uppsatsen är en casestudie där kvalitativ data, samlad genom en litteraturstudie samt intervjuer, användes för att besvara forskningsfrågan. Metodologin som brukades var anpassad efter den unika naturen för forskningen, samt i enighet med syftet av studien. Metoden delades in i fem faser. (1) Finna ett fokusområde, exempelvis en specifik diagnos, där behovet av ett kliniskt beslutsstöd bedömdes högt. (2) Kartlägga vårdkedjan för den identifierade diagnosen. (3) Utveckla hypoteser angående var inom vårdkedjan som  utmaningar skulle kunna lösas med ett kliniskt beslutsstöd. (4) Bekräfta eller förkasta ypoteserna genom intervjuer med relevanta experter. (5) Presentera problemet med det mest trängande behovet efter ett kliniskt beslutsstöd och hur ett sådans skulle utformas. Fynd: Effektivitetsproblemet som kunde lösas bäst via ett kliniskt beslutsstöd identifierades att vara inom området hjärtsviktsbehandling. Det fanns flertalet områden med utvecklingspotential som urskiljdes ur vårdkedjan för hjärtsviktspatienter, och vissa av dessa utmaningar kunde lösas genom utveckling och implementering av specifika kliniska beslutsstöd. Det kliniska beslutsstöd som skulle lösa det mest trängande behovet inom vården idag föreslås vara ett system som hjälper läkare inom vårdcentralerna att identifiera patienter som skulle gagnas av en remiss till en kardiolog. Det föreslagna kliniska beslutsstödet skulle vara både fördelaktigt för vårdpersonal samt patienter samt är realistiskt implementerbart.

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