<p>Chronic low back pain is the second most prevalent chronic condition in Canadian primary care settings. The treatment and diagnosis of chronic pain is challenging for primary care clinicians. Their main challenges are lack of knowledge and their approach toward assessing and treating pain. Evidence based guidelines have been developed for neuropathic pain and low back pain.</p> <p>CDSSs for chronic diseases are becoming popular in primary care settings as a mean to implement CPGs. A CDSS prototype for diagnosis and treatment of chronic, non-cancer pain in primary care was developed at McMaster University. It is evident that poor usability can hinder the uptake of health information technologies.</p> <p>The objective of this study was to test the usability of Pain Assistant using think aloud protocols with SUS scores in 2 iterations. In this study 13 primary care providers including family physicians, nurse practitioners and residents used Pain Assistant to complete 3 different patient case scenarios. Participants were asked to comment on both barriers and facilitators of usability of Pain Assistant. Additionally time to complete patient case scenarios was calculated for each participant. A comparison questionnaire gathered user preference between introducing CPGs in paper format and computerized decision support system.</p> <p>This study showed that iterative usability testing of the Pain Assistant with participation of real-end users has the potential to uncover usability issues of the Pain Assistant. Problems of user interface were the main usability barrier in first testing iteration following by problems of content. Changes were made to system design for second round based on the issues came up in the first iteration. However, because of time constrains not all the changes were implemented for second round of testing. Most of the refinements were to resolve user interface issues. In the second iteration, the problems with the content of Pain Assistant were the major barrier. The changes to the system design were successful in resolving user interface problems since the changed issues did not come up again in second round. Pain Assistant had an above the average usability score however no significant changes seen in SUS score. The time needed to complete tasks remained identical in both iterations. In addition, participants preferred to have CPGs in electronic formats than paper. Further study after implementing all the system changes needed to determine the effectiveness of system refinements.</p> / Master of Science (MSc)

The current dissertation provides an examination of health information technology (HIT) by analyzing big datasets. It contains two separate essays focused on: (1) the evolving intellectual structure of the healthcare informatics (HI) and healthcare IT (HIT) scholarly communities, and (2) the impact of social support exchange embedded in social interactions on health promotion outcomes associated with online health community use. Overall, this dissertation extends current theories by applying a unique combination of methods (natural language processing, machine learning, social network analysis, and structural equation modeling etc.) to the analyses of primary datasets. The goal of the first study is to obtain a full understanding of the underlying dynamics of the intellectual structures of HI and its sub-discipline HIT. Using multiple statistical methods including citation and co-citation analysis, social network analysis (SNA), and latent semantic analysis (LSA), this essay shows how HIT research has emerged in IS journals and distinguished itself from the larger HI context. The research themes, intellectual leadership, cohesion of these themes and networks of researchers, and journal presence revealed in our longitudinal intellectual structure analyses foretell how, in particular, these HI and HIT fields have evolved to date and also how they could evolve in the future. Our findings identify which research streams are central (versus peripheral) and which are cohesive (as opposed to disparate). Suggestions for vibrant areas of future research emerge from our analysis. The second part of the dissertation focuses on comprehensively understanding the effect of social support exchange in online health communities on individual members’ health promotion outcomes. This study examines the effectiveness of online consumer-to-consumer social support exchange on health promotion outcomes via analyses of big health data. Based on previous research, we propose a conceptual framework which integrates social capital theory and social support theory in the context of online health communities and test it through a quantitative field study and multiple analyses of a big online health community dataset. Specifically, natural language processing and machine learning techniques are utilized to automate content analysis of digital trace data. This research not only extends current theories of social support exchange in online health communities, but also sheds light on the design and management of such communities.

Radio frequency identification (RFID) technology is a useful technology that has myriad applications in technology, retail, manufacturing, and healthcare settings. Not dependent upon line-of-sight, RFID can scan devices in their proximity and report the information to connected (wired or other wireless) information systems. Once touted as the panacea for home healthcare, RFID devices can add benefit to patients in remote settings. RFID devices have been used to optimize systems in areas such as manufacturing and healthcare to expose inefficiencies in a system or process. Unlike manufacturing, however, RFID in healthcare settings presents security and privacy concerns to the people being tracked by the devices – particularly healthcare workers including nurses and doctors. This research presented a theoretical model that assessed the effect of five independent variables, namely, cognitive factors, of privacy concerns regarding surveillance and RFID devices and trust in the electronic medium, subjective norm, existence of security policy, and persistence of data on a dependent variable - intention to use RFID. The theoretical model presented in this research is based on the technology acceptance model and the extended theory of planned behavior. The research showed significant relationships between the cognitive factors of privacy concerns regarding surveillance and RFID devices, and trust and the electronic medium and perception of external control on intention to use. The theoretical model used in this research can be refined to better understand intention to use RFID in hospital environments.

This research examined if there is a relationship between engagement in quality improvement (QI) and health information technology (HIT) for local health departments (LHDs) controlling for workforce, finance, population, and governance structure. This was a cross-sectional study that analyzed data obtained from the Core questions and Module 1 in the NACCHO 2010 Profile of LHDs. Descriptive statistics, bivariate analyses, and logistic regression analyses were conducted. Findings suggest that LHD engagement in QI has a relationship with utilization of HIT including electronic health records, practice management systems, and electronic syndromic surveillance systems. This study provides baseline information about the HIT use of LHDs. LHDs and their system partners (hospitals, federally qualified health centers, and primary care providers) that utilize HIT as part of their QI decision making may have an easier time of using data to support evidence-based decision making and implementing the provisions of the Patient Protection and Affordable Care Act of 2010 in order to achieve population health for all.

The intention of implementing technology into healthcare practices is to reduce opportunity for errors in the delivery of providing health care. However, errors still occur, and many times are preventable. Configurations of health information technology systems should match clinical workflows to promote usage as intended. The purpose of this quality improvement project was to evaluate the impact of revised system configurations and use of a blood product transfusion system for the administration of blood products after one year of implementation. The method of heuristic evaluation is a usability engineering method for finding problems in a user interface design with the input of a small workgroup of subject matter experts. The project site had experienced reported incidents of blood product administration error as well as problems with systems communication since the implementation of the blood transfusion system. There were 31 nurse clinical educator staff users of the system who completed a survey evaluation of their perceptions of the blood transfusion system before and after configuration changes. The findings revealed that the mean quality and productivity score after the system configuration occurred was significantly higher than the mean score prior to the system configuration change, t (30) = -7.93, p < .001. The correlation between the one survey was also statistically significant, r = .46, p = .009. This project supports positive social change by reducing the potential for error for system users in the process of the blood administration process through heuristic evaluation through the implementation of changes to the technological system.

Racial/ethnic disparities in cancer care are well documented in the research literature; however, less is known about the extent and potential source of cancer care disparities in the Veterans Health Administration (VA). In my first paper, I use logistic regression and hospital fixed effects models to examine racial disparities in 20 cancer-related quality measures and the extent to which racial differences in site of care explain VA cancer care disparities. I found evidence of racial disparities in 7 out of 20 cancer-related quality measures. In general, these disparities were primarily driven by racial differences in care for black and white patients within the same VA hospital, rather than racial differences in site of care.

This thesis research contributes to national health Information Management/Information Technology (IM/IT) planning and therefore strategy development and implementation research, as well as to health information science. An examination into the national health IM/IT plans of several countries provides knowledge into identifying the typical IM/IT priorities that selected countries are focusing upon for healthcare improvement. Second, a systematic literature review of the current challenges, barriers and/or issues (referred to as ‘challenges’ hereafter) facing IM/IT priority implementation in healthcare settings provides insight on where nations should perhaps be focusing their attention, in order to enable more successful healthcare IM/IT implementations. Lastly, a study on national health IM/IT priorities contributes to the body of evidence that national level IM/IT direction is necessary for better patient care and health system reform across the world. In this investigation, the national health IM/IT priorities, which are reflected in the national health IM/IT strategic plans of five countries were assessed. To this end, the study: 1) Developed a set of measures to select four countries to study in addition to Canada; 2) Described the national health IM/IT priorities of Canada and four other countries; 3) Performed a systematic literature review of the challenges to overcome for successful implementation of IM/IT into healthcare settings; 4) Developed and administered a questionnaire where participants were asked to give their opinions on the progress their country has achieved in dealing with such challenges; and 5) Performed an analysis of the questionnaire results with respect to the countries’ national health IM/IT priorities. The systematic literature review uncovered a large number of challenges that the health informatics and healthcare community face when attempting to implement IM/IT into healthcare settings. iii The priority comparison highlighted that there is no right or wrong answer for what countries should focus their national health IM/IT energies upon. The findings indicate that nations focus their resources (time, money, personnel etc.) on the priorities they feel they should, whether those stem from needs analyses or politics. However, by learning about what other nations are prioritizing, a country can use that knowledge to help focus their own national health IM/IT priorities. The questionnaire results drew attention to the most frequently encountered challenges the five countries face in moving their national health IM/IT agendas forward. The feedback from the respondents provided individual reflections on how IM/IT implementations are actually progressing in their country, where problems are being encountered, including the nature of those problems, and in some cases, respondents offered insight on how to better deal with the challenges they face. The findings indicate that nations encounter similar problems in implementing IM/IT into healthcare settings. Currently, the world is facing many of the same healthcare system issues: shortages of healthcare processionals, long surgical and diagnostic imaging waitlists, ‘skyrocketing’ pharmaceutical drug pricing, healthcare funding practices, and challenges with implementing healthcare IM/IT priorities to name a few. If countries are facing similar health system problems, then it would be logical to assume that solutions to deal with such problems would be similar across nations. Thus, it is recommended that international fora and conferences be held to further discuss the types of health system IM/IT priorities that countries are implementing at a nation scale, the kinds of challenges they face and the solutions or conclusions that they have formulated in response to these challenges.

A novel, interactive Android app has been developed that monitors the health of type 2 diabetic patients in real-time, providing patients and their physicians with real-time feedback on all relevant parameters of diabetes. The app includes modules for recording carbohydrate intake and blood glucose; for reminding patients about the need to take medications on schedule; and for tracking physical activity, using movement data via Bluetooth from a pair of wearable insole devices. Two machine learning models were developed to detect seven physical activities: sitting, standing, walking, running, stair ascent, stair descent and use of elliptical trainers. The SVM and decision tree models produced an average accuracy of 85% for these seven activities. The decision tree model is implemented in an app that classifies human activity in real-time.

Ensuring the objectivity of systematic reviews and meta-analyses (SRMA) begins with comprehensive searches into diverse resources mining primary studies. Guidelines for systematic reviews recommend authors to routinely search of trial registries to identify unpublished studies. In this dissertation, I investigated the utilization of ClinicalTrials.gov (CTG), the world’s largest clinical trial registry that contains data from clinical trials of products that are subject to United States Food and Drug Administration (FDA) regulation, as an information resource in SRMAs. First, I examined the use of various information resources including CTG in SRMAs published from 2005-2016, and identified the factors associated with their use. Thereafter, to determine the accuracy of trial safety data reported at CTG, I compared the data at CTG with that in corresponding journal articles and FDA drug reviews. I found that trial safety data at both CTG and articles differed frequently from FDA drug reviews, but the differences were modest in magnitude. Finally, I repeated published meta-analysis (conducted using data from primary study articles) with data at CTG to find that most meta-analysis results were reproduced using CTG data. Taken together, this work suggests that CTG should not only be searched more often to find primary research for systematic reviews, but that data at CTG can also be used to conduct quantitative data synthesis.

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.