Communication is a critical aspect of clinical work. In 2010, the Joint Commission (JC) found that gaps in communication were among leading factors contributing to medical errors. Healthcare processes, such as patient discharge, depend on interdisciplinary communication to be successful. Electronic health records (EHRs) have the potential to facilitate communication and information sharing between interdisciplinary care team members; however, challenges remain in designing tools for team-based care and questions remain in understanding how EHRs impact interdisciplinary team communication. This dissertation focuses on understanding how EHRs can be designed to support communication and information sharing within interdisciplinary patient care teams. The first aim of the dissertation investigated how EHRs impact interdisciplinary clinical teams’ communication, shared mental models, and information sharing activities. The results showed that implementing new EHR tools appeared to have little impact on communication and shared mental models, but new information sharing activities mediated by EHR developed. These changes and lack thereof suggest that new EHR tools will be specifically needed to facilitate interdisciplinary team information sharing activities. The second aim of the dissertation investigates the information sharing activities and information needs of interdisciplinary team members during patient discharge. The results showed that the information clinicians sought out during discharge depended on the roles that person played as well as the progress of the discharge process. Future EHR tools should be aware of how patient care teams are progressing through the patient discharge process in order to provide information contextualized to their current tasks. In conclusion, interdisciplinary team communication and information sharing remain poorly supported by current EHRs and new tools designed specifically for interdisciplinary teams should provide information based on the completion of team activities.

The last decade has been defined by the forced displacement of an unprecedented number of people, on a scale not seen since World War II. As of 2018, more than 71 million people across the globe have been forced to migrate as a result of conflict, natural disasters, drought and famine. More than 19 million crossed international borders seeking safety, and were formally registered as refugees. Forced migration has placed stress and pressure on surrounding low-and middle-income countries. This has been most notable in the Middle East and North Africa as a result of the crisis in Syria. Host countries in the Middle East and North Africa are overwhelmed by this rapid influx, particularly by the healthcare needs of this population. Stakeholders face difficulties providing health services to refugees, owing to the increased number of refugees in urban settings, the large demands on host country health systems and the epidemiologic transition towards non-communicable diseases (NCDs). Health challenges have been exacerbated by weaknesses in the global humanitarian architecture, that result in a fragmented and competitive sector that is unprepared for the current context. Few comparative analyses have examined the diversity of policies and practices aimed at improving services for urban-based refugees with NCDs in the MENA region. Furthermore, a variety of quantitative studies examined NCD incidence, prevalence and service utilization. However, these studies have quickly become outdated and do not explore, in adequate depth, the refugee experience and perspective on accessing NCD services in urban settings. Lastly, numerous NCD interventions have been recommended for LMICs. However, very little guidance exists to support actors addressing these health concerns in crisis-affected contexts. As a result, this dissertation is presented in three papers and responds to these gaps in the literature. Each paper focuses on a specific aim and research question and together they identify and provide recommendations for improvement to service delivery and policy formulation. Paper 1 identifies policies and practices, implemented by host countries and humanitarian actors, aimed at improving access to NCD services for urban refugees in the Middle East and North Africa. Paper 2 examines, using qualitative methods, the healthcare access experience of urban-based Syrian refugees who have been diagnosed with NCDs in Jordan. The third portion of this dissertation (Paper 3) is a policy series that provides recommendations for the government of Jordan and humanitarian actors to improve healthcare access for urban-based refugees with NCDs. It is anticipated that this series of publications will be relevant to traditional and non-traditional actors that respond to the health needs of refugees in urban settings in the MENA region.

Healthcare fraud is a major problem within the healthcare industry. The study examined medical fraud, its laws, and punishments on federal and state levels. It compared medical fraud to non-fraud crimes done in the healthcare industry. This comparison will be done on a state level. The study attempted to analyze the severity of fraud against non-fraud and that doctors would commit fraud offenses more often than non-fraud offenses.

This study examined if physician assistants (PAs) are cost-beneficial to employers. In an era of cost accountability, questions arise about whether a visit to a PA for an episode of care differs from a visit to a physician, and if PAs erode their cost-effectiveness by the manner in which they manage patients. Four common acute medical conditions seen by PAs and physicians within a large health maintenance organization were identified to study. An episode approach was undertaken to identify all laboratory, imaging, medication and provider costs for these diagnoses. Over 12,700 medical office visits were analyzed and assigned to each type of provider and medical department. Patient variables included age, gender, and health status. A multivariate analysis identified significant cost differences in each cohort of patients. In every condition managed by PAs, the total cost of the visit was less than that of a physician in the same department. This was significant for episodes of shoulder tendinitis, otitis media, and urinary tract infections. In no instance were PAs statistically different from physicians in use of laboratory and imaging costs. In each instance the total cost of the episode was less when treated by a PA. Sometimes PAs ordered fewer laboratory tests than physicians. There were no differences in the rate of return visits for a diagnosis between physicians and PAs. Patient differences were held constant for age, gender, and health status. This study affirms that PAs are not only cost-effective from a labor standpoint but are also cost-beneficial to those who employ them. In most cases, they order resources for diagnosis and treatment in a manner similar to physicians for an episode of care, but the cost of an episode of an illness is more economical overall when the P A delivers the care. This study validates the federal policy of support for primary care P A education and suggests that PA employment should be expanded in many sectors of the health care system. These findings and the results of this cost-benefit model are evidence of its validity in predicting health care costs.

Socioeconomic status (SES) is inversely related to health status. Disparities in health status among races and ethnic groups are partly attributable to differences in SES, but the indirect pathways by which SES may influence health status are not widely studied. Using the Health and Retirement Study (HRS) data, this dissertation examined the pathways by which SES, via social, psychological, and behavioral factors predicted physical impairment and overnight hospitalization, and asked whether these indirect relationships differed by race/ethnicity. The HRS is a nationally representative multistage area probability sample administered biennially to respondents over the age of 51 and their spouses. Data collected between 2002 and 2010, covering five waves of the original HRS cohort born between the years 1931 and 1941, were used. Two analysis approaches, Structural Equation Modeling (SEM) and Reconstructability Analysis (RA), were used. Adjustments for the complex survey design were made in the SEM analysis, whereas, data were matched for the RA method using propensity scores. Results of the SEM analyses supported most of the hypothesized indirect relationships between SES variables and physical impairment via social and psychological factors, but the indirect effect of SES on physical impairment via behavioral factors was weak. Multiple group analyses of path equality using nested chi-square tests indicated that the indirect effect of SES on physical impairment status did not vary by race/ethnicity. Social, psychological and behavioral factors were weakly related to overnight hospitalization, and SES was not indirectly related to overnight hospitalization. While these results supported several hypothesized indirect relationships between SES variables and physical health status, the indirect effect sizes were small. However, because this study examined predictive paths across groups rather than compare mean differences, and because indirect effects are products of individual path coefficients, small effect sizes are not uncommon in mediation analysis. Moreover, over a lifetime, small effects may gradually add up increasing group differences in health status with greater benefits accruing to higher SES individuals via social and psychological factors, as observed in this study. The RA results showed that indirect relationships between SES and physical impairment were similar across races/ethnicities for identical variables with a few exceptions. In several cases, however, selected SES variables related to social and psychological variables were different for different groups. Cross-sectional indirect relationships were stronger than longitudinal indirect relationships. As in the SEM study, SES was not related to physical impairment via behavioral factors; and, across groups, SES was also not related to overnight hospitalization either directly or via social, psychological or behavioral factors. Variables predicting physical impairment exhibited differences across groups; these differences were detected because RA, unlike SEM, used disaggregated social, psychological and behavioral factors. Where predictive variables overlapped, the effects of identical independent variable (IV) states on physical impairment were similar across groups with a few exceptions. In summary, both the SEM and RA results indicated that SES was indirectly related to physical impairment via social and psychological factors, and results from both methods also showed that SES was not indirectly related to overnight hospitalization via these factors. SEM did not find that these indirect effects varied by race/ethnicity; RA found a few differences.

The number of elderly in the U.S. (i.e., individuals age 65 years or older) is growing at a rapid rate. While the current proportion of elderly persons living in U.S. is estimated to be little over 14%, it will soon reach up to 20% in next 10 years. In addition, it is anticipated that the elderly population will soon outnumber the younger generations, for the first time in U.S. history. With the rapid shift we are witnessing in the U.S. population, the World Health Organization (WHO) informs that the leading cause of death in U.S. has also shifted: from infections to chronic illnesses. The majority of elderly individuals will suffer from at least one chronic illness, and many will live longer than ever, with complex multiple healthcare needs. The demands for specialized end of life (EoL) care among frail elderly will continue to rise, and it is among the top research priorities to identify best practices in EoL care and understand how best to facilitate patient-centered care in healthcare settings. In order to increase awareness in the importance of quality care provided to those who are near EoL, the Institute of Medicine (IOM; now the National Academy of Medicine) recommended a nation-wide implementation of an advance care planning tool, the POLST (Physician Orders for Life-Sustaining Treatment). Designed specifically for frail individuals living with serious illnesses, the POLST program is used to elicit care preferences and deliver goal-concordant care. Making patients’ specific care wishes actionable and transferrable, it aims to preserve one’s autonomy, and to allow them to die with dignity. This dissertation aims to evaluate the POLST program, from its effectiveness, dissemination, to outcomes associated with its maturity status. The first chapter provides background information on the aging population the importance of advance care planning among frail elderly persons. The POLST program is introduced and I lay out the three research aims and the significance of each topic. Chapter 2 contains a systematic review of scientific evidence on the concordance between documented care wishes and actual care delivered to the POLST users. It explains specific care interventions that yielded high concordant care, as well as ones that had mixed results. In chapter 3, an environmental scan of a state-specific POLST program across all U.S. states and Washington D.C. is presented; the scan examined maturity status, specific care options mentioned/ absent as well as descriptive statistics on the association between presence of infection/pain-related care options and the POLST program maturity status. In chapter 4, a quantitative analysis aimed at examining the impacts of the POLST program maturity status on a patient-level outcome (i.e., nursing home death) is presented. In it, multiple large datasets were used to generate a representative sample of the U.S. nursing home population. I then applied multivariate logistic regression modeling to estimate associations. Lastly, chapter 5 synthesizes the findings of this dissertation as well as strengths and limitations. It then shares recommendations for policy, clinical practice and future research.

Background: Cancer treatment and management require complicated clinical decision making to provide the highest quality of care for an individual patient. This is facilitated in part with ever-increasing availability of medications and treatments but hindered due to barriers such as access to care, cost of medications, clinician knowledge, and patient preferences or clinical factors. Although guidelines for cancer treatment and many symptoms have been developed to inform clinical practice, implementation of these guidelines into practice is often delayed or does not occur. Informatics-based approaches, such as clinical decision support, may be an effective tool to improve guideline implementation by delivering patient-specific and evidence-based knowledge to the clinician at the point of care to allow shared decision making with a patient and their family. The large amount of data in the electronic health record can be utilized to develop, evaluate, and implement automated approaches; however, the quality of the data must first be examined and evaluated. Methods: This dissertation addresses gaps the literature about clinical decision making for cancer care delivery. Specifically, following an introduction and review of the literature for relevant topics to this dissertation, the researcher presents three studies. In Study One, the researcher explores the use of clinical decision support in cancer therapeutic decision making by conducting a systematic review of the literature. In Study Two, the researcher conducts a quantitative study to describe the rate of guideline concordant care provided for prevention of acute chemotherapy-induced nausea and vomiting (CINV) and to identify predictors of receiving guideline concordant care. In Study Three, the researcher conducts a mixed-methods study to evaluate the completeness, concordance, and heterogeneity of clinician documentation of CINV. The final chapter of this dissertation is comprised of key findings of each study, the strengths and limitations, clinical and research implications, and future research. Results: In Study One, the systematic review, the researcher identified ten studies that prospectively studied clinical decision support systems or tools in a cancer setting to guide therapeutic decision making. There was variability in these studies, including study design, outcomes measured, and results. There was a trend toward benefit, both in process and patient-specific outcomes. Importantly, few studies were integrated into the electronic health record. In Study Two, of 180 patients age 26 years or less, 36% received guideline concordant care as defined by pediatric or adult guidelines, as appropriate. Factors associated with receiving guideline concordant care included receiving a cisplatin-based regimen, being treated in adult oncology compared to pediatric oncology, and solid tumor diagnosis. In Study Three, of the 127 patient records reviewed for the documentation of chemotherapy-induced nausea and vomiting, 75% had prescriber assessment documented and 58% had nursing assessment documented. Of those who had documented assessments by both prescriber and nurse, 72% were in agreement of the presence/absence of chemotherapy-induced nausea and vomiting. After mapping the concept through the United Medical Language System and developing a post-coordinated expression to identify chemotherapy-induced nausea and vomiting in the text, 85% of prescriber documentation and 100% of nurse documentation could be correctly categorized as present/absent. Further descriptors of the symptoms, such as severity or temporality, however, were infrequently reported. Conclusion: In summary, this dissertation provides new knowledge about decision making in cancer care delivery. Specifically, in Study One the researcher describes that clinical decision support, one potential implementation strategy to improve guideline concordant care, is understudied or under published but a promising potential intervention. In Study Two, I identified factors that were associated with receipt of guideline concordant care for CINV, and these should be further explored to develop interventions. Finally, in Study Three, I report on the limitations of the data quality of CINV documentation in the electronic health record. Future work should focus on validating these results on a multi-institutional level.

Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2018. / Healthcare facilities in South Africa accumulate big data, daily. However, this data is not being utilised to its full potential. The healthcare sector still uses traditional methods to store, process, and analyse data. Currently, there are no big data analytics tools being used in the South African healthcare environment. This study was conducted to establish what factors hinder the effective use of big data in the South African healthcare environment. To fulfil the objectives of this research, qualitative methods were followed. Using the case study method, two healthcare organisations were selected as cases. This enabled the researcher to find similarities between the cases which drove them towards generalisation. The data collected in this study was analysed using the Actor-Network Theory (ANT). Through the application of ANT, the researcher was able to uncover the influencing factors behind big data analytics in the healthcare environment. ANT was essential to the study as it brought out the different interactions that take place between human and non-human actors, resulting in big data. From the analysis, findings were drawn and interpreted. The interpretation of findings led to the developed framework in Figure 5.5. This framework was developed to guide the healthcare sector of South Africa towards the selection of appropriate big data analytics tools. The contribution of this study is in twofold; namely, theoretically and practically. Theoretically, the developed framework will act as a useful guide towards the selection of big data analytics tools. Practically, this guide can be used by South African healthcare practitioners to gain better understanding of big data analytics and how they can be used to improve healthcare service delivery.

This dissertation examines how debates about racial susceptibility to asthma changed from 1880 to 1990 alongside a growing disparity in Black and white asthma morbidity. At the turn of the century, doctors believed asthma was exclusive to whites, due to the stresses of urban life on their delicate constitution. But by 1960, the first year the CDC’s National Center for Health Statistics collected asthma data, the rate of asthma mortality in Blacks was nearly twice that in whites. After neglecting asthma in Black communities for sixty years, doctors scrambled to articulate its manifestation in urban communities of color. In those decades, the urban American landscape dramatically evolved, as the Great Migration brought six million African-Americans to Northern cities, but segregation and other racist policies created black metropolises laden with dilapidated public housing, high rates of unemployment, and environmental toxins from garbage dumps, waste plants, train tracks, and bus depots. Growing racial tensions and expanded funding opportunities during the Civil Rights Movement spurred an overwhelming production of research on asthma and race, with explanations ranging from meteorological episodes, environmental pollution, and indoor allergens to biological, genetic, and even psychological factors. Although research primarily focused on psychosomatic, environmental, and genetic causes, Black activists and community leaders used asthma data to mobilize for social equality in housing, neighborhoods, health, and education. At the cross-section of the history of medicine, social history, and environmental justice history, this dissertation examines the changing debates on racial susceptibility to asthma, the effects of the Great Migration and segregation on Black health, and both tensions and alliances between doctors, patients, and activists battling asthma in Black urban communities.

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