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Society faces significant challenges caring for people with urgent mental health needs. General hospitals are well equipped for dealing with medical emergencies, but much less skilled in managing mental health problems. Ambulance and policing staff frequently encounter such individuals, with transport to Emergency Department often the only care pathway. In the UK, no evidence existed on general hospital patterns prior to suicide, or on outcomes for pre-hospital mental health emergencies. This thesis contains five papers, consisting of four research studies and one protocol. Three papers report innovative quantitative approaches using linked datasets. Using 30 years of Scottish hospital data, I showed that 10,907 people who died by suicide with hospital records were 3.1 times more frequently last discharged from general, not psychiatric hospital; 24% within three months of last discharge, of whom 58% were from general hospital. Using national deaths registrations, I reported that cohorts of men born around 1965-70 had been at greater vulnerability to suicide in the 1990s, with stark differences in suicide rates between Scotland, and England & Wales. Analyses of data on unscheduled care revealed that within one year of paramedic attendances for 6,802 people with 'psychiatric emergency', 297 had died, 35% of whom were deaths by suicide. Paramedics were in contact with 8% of people in the year before they died by suicide. Police officers encountering people with mental health concerns have no formal means of vulnerability assessment to support triaging. A review of the evidence found no consensus definition for vulnerability or means of assessing vulnerability, a lack of congruence in terminology across policing and health, and a likely barrier to accessing services. Finally, a protocol was published outlining methods for an analysis of childhood adversity as seen in national hospital datasets. This thesis provides evidence to support redesign of more integrated services, highlights areas for suicide prevention, and closes with an impact generation exemplar.

This paper used web scraping and data mining to analyze 831 health informatics job advertisements on indeed.com. Results showed that 87% of jobs explicitly required a college degree in a related field, 41% of jobs preferred a graduate degree, while 29% preferred or required professional certification. The analysis showed that preferred skills were analytics problem solving, communication skills, oral communication, interpersonal skills, project management, statistics, and critical thinking. The analysis also showed that college degrees, certifications, and the above-mentioned skill set are in high demand for working in the field of health informatics, especially in states with large populations and strong economies. Our results inform curriculum development of health informatics programs in higher education, which helps map knowledge units across the curricula to bridge the skills gap and meet employers’ expectations. At the same time, the results help job seekers familiarize themselves with what employers seek in a successful candidate.

Handoff is the process by which the care of a patient is transferred from the responsibility of one provider (or team of providers) to another. Handoff that occurs between physicians in training, or resident physicians, has become the focus of numerous quality and safety initiatives, especially since the introduction of work-hour restrictions for resident physicians that have increased the number of handoffs taking place during a hospitalization. The Handoff Note is the (traditionally paper) artifact accompanying the Handoff Process, and in its most basic form consists of the names of patients being transferred from the care of one clinician to another. Other data is often included, such as demographic data, room number, and a brief summary. Increasingly, Handoff Notes are becoming integrated into the Electronic Health Record (EHR). However, there remains no universally accepted standard for EHR-Integrated Handoff Note content, nor standards for what content is appropriate for automatic entry from the EHR versus manual entry by providers. Further, there have been few efforts to elucidate resident physician preferences for Handoff Note content, structure, or format, despite being the principal users of these tools. Although many data elements can be automatically entered into the Handoff Note by the EHR, certain key elements will likely remain manually entered by clinicians as narrative text. Analysis of these free text elements in Handoff Notes may reveal important insights for informaticians, safety and quality experts, and those involved in graduate medical education. In the first part of this study we look to key stakeholders for standards surrounding optimal Handoff Note content, and after choosing one with greatest buy-in, compare it to content contained in individual EHR-Integrated Handoff Notes described in the literature. The chosen standard covered 67% of Content Headings described in the literature, and thirteen more unique Content Headings were found in the literature to add to this standard. Using these findings from the literature and guided by prior semi-structured interviews with resident physicians, we performed a large-scale survey on resident physician preferences for Handoff Note content, structure, and format. We found that some of the most important and trustworthy elements of the Handoff Note were narrative text data manually entered by other clinicians, including “Plan”, “Illness Severity”, and “Patient Summary”. Based on these insights, we then designed and implemented an EHR-Integrated Handoff Note within our institution. Years after implementation we found that nearly all “primary” service teams and many “consult” service teams continued to utilize the Handoff Note, including resident physicians is such different specialties as medicine, pediatrics, behavioral health, obstetrics/gynecology, neurology, surgery, and critical care. Analysis of the narrative text portions of the Handoff Note showed that “Patient Summary” and “To Do” text boxes were updated 1.0 and 1.6 times per day, respectively. The majority of these updates occurred between 12 pm – 5:59 pm, likely indicating preparation of the Handoff Note for the evening Handoff Process. However, many changes also take place between 6 am – 11:59 am, indicating possible use of the Handoff Note to aid team rounding activities. We also analyzed narrative text for errors, using progress notes and other data from the EHR as gold standard. We found at least one error in 65% of Handoff Notes. The majority of errors were related to the omission of key data, rather than the entry of incorrect data. Increased errors were found with increasing hospital day, as well as with authors in early stages (medical students, PGY-1 physicians) and later stages (>PGY-4 or attending physician) of training. While the integration of the Handoff Note within the EHR and the automatic entry of many data elements into the note will prove useful, manual entry of certain narrative text continues to be critical. Future work on the parts of informatics and usability experts should focus on ways to make composing and updating these notes easier and encourage accuracy and frequency of updates. Members of the graduate medical education community should also make it a priority to formalize training surrounding accurate and complete Handoff Note composition as an important adjunct to existing training surrounding the Handoff Process. These tools have the potential to greatly improve patient safety and quality of care.

This research paper focuses on the barriers that parents and caregivers of special-needs children patients face with leveraging technology and informatics as they attempt to communicate with their child’s healthcare specialists regarding specialized and critical oversight and management of complex medical conditions and the need for empowerment for this population of parents and caregivers. The literature suggests that the age and socioeconomic status of the individual has a big impact on the use of electronic applications. A review of the literature showed that the special needs population has not been represented. This study surveys a range of parents and caregivers to include a various age ranges, genders, education and socioeconomic statuses to identify the barriers this unique population has encountered.

This hermeneutical study examined the lived experiences of health information managers with 20+ years of experience in the complex and ever-changing environment of healthcare. The purpose of this research was to gain a deeper understanding of the experiences of credentialed health information managers with 20+ years of experience who have experienced moving from a paper-based medical record system to an electronic health record system. Eight credentialed health information managers were interviewed. They shared their experiences over the past 20+ years in the health information management profession. I conducted individual interviews of each participant. Four themes emerged and were emailed to the participants for verification. Four major themes were agreed upon: 1). Commitment to Data Quality, 2). Managing a Workforce in the Electronic Health Record environment, 3). Gender and Sexual Orientation Bias Experiences, and 4). Commitment to Collaboration. The knowledge gained in this study may help practitioners who are implementing electronic health record systems, other healthcare personnel who are implementing electronic health records, human resource development practitioners working in healthcare environments, and educators working with students in accredited health information management programs.

A paradigm in the field of Heath Informatics which has been taken for granted up until this point may be disappearing and a new paradigm may begin to take shape as paper-based medical record (PMR) systems are changing to the electronic health record (EHR) systems. Although the PMR has played a critical role in recording patient's clinical information, now many studies report that EHR systems improve quality of care beyond PMRs. For this reason, the governments across the world have initiated various approaches accelerating EHR adoption, use, and interoperability. However, there has been a paucity of studies explaining which factors affect EHR adoption, use, and interoperability in hospitals. The objective of this study is to predict and investigate those factors. This study used a non-experimental, retrospective, cross-sectional study design to measure hospitals' internal features. Specifically, this study conducted a nationwide EHR survey with the IT departments in South Korean hospitals by using online surveys from April 10 to August 3, 2009. It used Generalized Estimating Equations, an extension of the Generalized Linear Model, to interpret EHR system adoption and interoperability, and General Linear Mixed Model for the use of EHR systems. With respect to EHR system adoption, this study found that 1) the likelihood of EHR adoption increases as a hospital's task complexity - measured by the number of medical specialties - IT infrastructure, and organic structural characteristics, and environmental complexity - measured by the number of hospitals within the local area - increases and 2) there were significant interaction effects between task complexity and structural features. Assuming that a hospital adds additional medical specialties, the likelihood of adopting an EHR system of the hospital increases under the decentralized decision-making system, but decreases under the centralized decision-making system. The likelihood decreases under a high level of IT infrastructure, but increases under a lower level of IT infrastructure. For the hospitals' EHR use, there was not any relationship between EHR use and proposed hospital's internal features. Thus, alternative measures of EHR use and internal features were suggested. For EHR interoperability, this study found that 1) the likelihood of having EHR interoperability increases as task complexity and organic managerial features increases, and 2) two interaction effects were reported. Assuming that a hospital adds additional medical specialties, the likelihood of having EHR interoperability of the hospital increases at a high level of IT staff specialization, but decreases at a lower level of IT staff specialization. At a high level of environmental complexity with more than average number of hospitals within the local area, the likelihood of having EHR interoperability of the hospitals located in the area increases as IT staff specialization increases. However, the likelihood decreases as IT staff specialization increases at a lower level of environmental complexity with less than average number of hospitals within the local area. In conclusion, this study verified that hospitals' task, structure, and environmental features were critical factors affecting the EHR system adoption and interoperability. However, these factors did not affect EHR use. Different approaches measuring EHR use and hospitals' various internal features were recommended. This study's results can provide health informaticians, hospital IT managers, and health politicians with new information about EHR system adoption, use, and interoperability for their innovative decision-making.