An investigation of analytics and business intelligence applications in improving healthcare organization performance: a mixed methods research

The healthcare ecosystem in the US is currently undergoing series of refinement and reformation due to the need to (i) improve quality of care and (ii) reduce cost. To achieve their key objective, healthcare organizations (HCOs) currently face a fundamental challenge: how to best use or optimize limited resources while providing better care and services to patients? The answer to this question might lie within HCO’s massive data and the ability to identify and apply appropriate analytics and business intelligence (A&BI) techniques and technologies to discern and extract relevant information and knowledge from that data. However, despite the increasing interest in the implementation and utilization of A&BI techniques and technologies by various organizations to improve operational efficiencies and financial performance, HCOs still lag behind other sectors in the adoption and use of A&BI capabilities. Motivated by the “data rich but information poor” syndrome currently facing HCOs, this dissertation applies a mixed method research–case study (interpretivist) and survey (positivist) – to investigate how healthcare organizations can leverage A&BI techniques and technologies to improve their overall performance. In achieving this objective, I illustrate an exemplar of how A&BI techniques and technologies can effectively be applied by specifically answering this high-level research question (RQ): How can A&BI techniques, methods, and technologies be developed and leveraged to improve performance in healthcare organizations? This high-level RQ has been broken down into four sub-questions that will be answered in two different studies in this dissertation. In the first study, I investigate what combination of A&BI techniques and technologies HCOs are currently applying to create value. This study was conducted by using content/literature analysis and case study methods in a large healthcare organization. The second study builds on the first study to investigate, using both interview and survey data, how A&BI capabilities can be developed, cultivated and nurtured as a core competency or capability that significantly helps improve healthcare organizations’ overall performance (such as cost reduction, quick access to providers and treatment, effective diagnostics, etc.). I found very novel and interesting results in both studies that not only address the research questions, but also provide significant theoretical and practical contributions. Major contributions of study 1 include: revising and remodeling of an outdated healthcare value chain (HCVC) framework that is more realistic and applicable to current care delivery practices in the healthcare industry and mapping of A&BI capabilities to the different domains of the revised HCVC framework. Study 2 provides theoretical contribution to the existing literature by conceptualizing and empirically validating A&BI capability as a third-order multi-dimension construct and its significant influence on performance

Emerg Infect Dis

Emerging Infectious Diseases is providing access to these abstracts on behalf of the ICEID 2022 program committee (http://www.iceid.org), which performed peer review. ICEID is organized by the Centers for Disease Control and Prevention and Task Force for Global Health, Inc.Emerging Infectious Diseases has not edited or proofread these materials and is not responsible for inaccuracies or omissions. All information is subject to change. Comments and corrections should be brought to the attention of the authors.Suggested citation: Authors. Title [abstract]. International Conference on Emerging Infectious Diseases 2022 poster and oral presentation abstracts. Emerg Infect Dis. 2022 Sep [date cited]. http://www.cdc.gov/EID/pdfs/ICEID2022.pdf2022PMC94238981187

A Grounded Theory of Patient Flow Management within the Emergency Department

Background: Emergency department (ED) crowding is an urgent threat to patient safety and negatively impacts healthcare staff and institutions. Patient flow researchers have employed a range of methods to address this crisis, including an increase in the use of operations research and operations management strategies. However, identified patient flow solutions are inadequate. Research describing the complexities of patient flow processes and investigating the work and contributions of ED nurses is needed. Purposes: The purposes of this study were to explore how ED nurses perform patient flow management and to develop a constructivist grounded theory of patient flow management within the ED. Methods: A conceptual foundation for patient flow management was first established using evolutionary concept analysis and expanded concept analysis approaches. This study then employed constructivist grounded theory and situational analysis methodologies to examine the work of ED nurses. Data was collected through 29 focus groups and interviews with 27 participants and 64 hours of participant observations across four EDs. Data analysis relied on coding, constant comparative analysis, and memo-writing to identify emergent themes and develop a substantive theory. Findings: Concept analyses defined patient flow management as the application of ED experience, holistic perspectives, dynamic data, and complex considerations of multiple priorities by ED nurses to promote patient safety within their scope of responsibility. The study offers three main contributions: a theoretical model of the work of ED patient flow management, a theoretical framework to describe holistic considerations of factors that impact departmental capacity and nurse engagement in patient flow management, and a grounded theory of patient flow management capacity and engagement that describes how ED nurses adapt patient flow management strategies according to patient burden. Conclusion: This study offers a new conceptual and theoretical foundation to understand the work of patient flow management. This novel perspective centralizes the work of ED nurses as active agents in patient flow processes and describes their strategies and contributions to meet patient care needs. Several practical considerations are offered to engage and support nurses in their roles as patient flow managers, improve patient flow processes, and further investigate ED nurse patient flow management

Environmental risk factors in infectious diseases: studies in waterborne disease outbreaks, Ebola, and Lyme disease

Thesis (Ph.D.)--Boston UniversityThe resurgence of infectious diseases and global climate change's potential impact on them has refocused public health's attention on the environment's role in infectious disease. The studies in this dissertation utilize the increased availability of satellite image-derived data sets with fine temporal and geographic granularity and the expansion of epidemiologic methods to explore the relationship between the environment and infectious disease in three settings. The first study employed a novel study design and analytic methods to investigate the hypothesis that heavy rainfall is an independent risk factor for waterborne disease outbreaks (WBDOs). We found that a location experiencing a heavy rainfall event had about half the odds of a WBDO two or four weeks later than did a location without a heavy rainfall event. The location-based case-crossover study design utilized in this study may help to expand the research methods available to epidemiologists working in this developing field. The second study employed a location-based case-crossover study design to evaluate standardized differences from historic average of weekly rainfall in locations with a recorded introduction of Ebola into a human. For each 1.0 unit z-score decrease in total rainfall, the odds of an Ebola introduction three weeks later increased by 75%. Given the severity of Ebola outbreaks and the dearth of knowledge about indicators of increased risk, this finding is an important step in advancing our understanding of Ebola ecology. The third study used GIS methods on remote sensing data to estimate the association between peridomestic forest/non-forest interface within 100, 150, 250 meters and Lyme-associated peripheral facial palsy (LAPFP) among pediatric facial palsy patients. After adjustment for sex, age, and socio-economic status, children with the highest level of forest edge in the three radii of analysis had 2.74 (95% CI 1.15, 6.53), 4.58 (1.84, 11.41), and 5.88 (2.11, 16.4) times the odds of LAPFP compared to children with zero forest edge in those radii. This study is the first to examine environmental risk factors for LAPFP. Each of these studies advances the techniques used to investigate environmental risk factors for infectious disease through study design, case definition, data used, or exposure definitions

Frailty in hospitalized adults

The purpose of this cross-sectional, retrospective, descriptive study was to characterize frailty in hospitalized adults 55 years of age and older admitted to medical units at one large academic medical center during a 15-month time frame and determine if level of frailty on admission predicted length of stay (LOS) and 30-day readmission. Frailty is a syndrome characterized by multisystem physiologic dysregulation due to intrinsic and extrinsic stressors resulting in decreased compensatory reserve and ability to effectively respond to destabilizing health events. Stressors associated with hospitalization may increase risk for frailty or accelerate its development. Frailty is a significant concern as it is associated with morbidity, functional decline, long LOS, readmission, institutionalization, and mortality. There is scant research on frailty in acutely-ill hospitalized adults, especially those ¡Ý 65 years of age. Understanding frailty in this population is imperative because frailty is potentially preventable, treatable, and reversible. Frailty was operationalized as 14 evidence-based frailty components defined by 26 indicator variables. Frailty components were Nutrition, Weakness, Fatigue, Chronic Pain, Dyspnea, Falls, Vision, Depression, Cognition, Social Support, low Hemoglobin, low Albumin, high C-reactive protein (CRP) or hs-CRP, and abnormal WBC count. Each frailty component was scored as one point if at least one indicator variable was present on admission, and summed to derive a Frailty Score, where a higher Frailty Score suggests greater level of frailty (range, 0 to 14). Sociodemographic, clinical, and laboratory data were retrieved from the electronic medical record through web-based data query tools and record review (N = 278). Mean age was 70.2 (SD = 1.3; range, 55¨C98), slightly over half were female, 64% were White, one-third were Black. The mean comorbidity count was 13 (SD = 4.56; range. 1¨C26) and medication count was 12 (SD = 5.2; range, 0¨C31). The most prevalent frailty components (> 81%) were Fatigue, Weakness, Nutrition, Hemoglobin, Albumin, and CRP or hs-CRP. The mean Frailty Score was 9.03 (SD = 1.98; range, 2¨C13). Multiple linear regression was performed with 20 predictor variables and the Frailty Score and then with 14 of the 20 predictor variables that were significant in bivariate linear regression with the Frailty Score using the ENTER and STEPWISE method. All multiple regression models yielded seven significant predictor variables. Six predictors were common to all models: comorbidity, acute pain, ADL assistance, urinary incontinence, Braden Scale score, current tobacco use. In multiple regression with 20 predictors, age was a significant predictor however in multiple regression using ENTER and STEPWISE for 14 predictors, female gender was significant but not age. Results from STEPWISE regression yielded seven significant predictors that explained 27% of the variance in the Frailty Score (adj. R2 = .266, df (14, 263), F = 8.163, p = .000). Mean LOS was 9.92 days (SD = 9.58; range, 1¨C72; median, 7; mode, 5). Simple linear regression for the Frailty Score and log10 transformed LOS was statistically significant (adj. R2 = .090, df (1, 276), F = 29.293, p = .000). Twelve percent experienced 30-day readmission. Logistic regression conducted for the Frailty Score and 30-day readmission was not statistically significant (X 2 = 4.121, df (5), p = .532; ¦Â coefficient = .100, df (1), 95% CI = .913¨C1.1337, p = .307). The Frailty Score characterized this hospitalized population as acutely ill with high comorbidity, symptom burden, nutrition deficits and evidence of physiologic vulnerability and inflammation. Study findings have implications for nursing practice, interdisciplinary collaboration, education, research, and public policy

Graduate course catalog (Florida International University). [2016-2017]

This catalog contains a description of the various policies, graduate programs, degree requirements, and course offerings at Florida International University during the 2016-2017 academic year.https://digitalcommons.fiu.edu/catalogs/1072/thumbnail.jp