Yes / Background The patient transition from a hospital to a post-discharge healthcare setting has potential to disrupt continuity of medication management and increase the risk of harm. “Connect with Pharmacy” is a new electronic web-based transfer of care initiative employed by Leeds Teaching Hospitals NHS Trust. This allows the sharing of discharge information between the hospital and a patient’s chosen community pharmacy. Objective We investigated whether the timely sharing of discharge information with community pharmacies via “Connect with Pharmacy” reduced hospital readmission rates in older patients. Method To evaluate intervention efficacy, hospital admission data was retrospectively collected. For primary analysis, admission rates were tracked 6-months prior (baseline) and 6-months post-intervention. Secondary measures included effect on total length of stay if readmitted, emergency department attendance and duration, and impact of polypharmacy. Main outcome measure The rate of non-elective hospital readmissions, 6-months post-intervention. Results In the sample (n = 627 patients; Mean age = 81 years), emergency readmission rates following the intervention (M = 1.1, 95% CI [0.98, 1.22]) reduced by 16.16% relative to baseline (M = 1.31, 95% CI [1.21, 1.42]) (W = 54,725; p < 0.001). There was no reduction in total length of stay. Subsidiary analysis revealed a post-intervention reduction in number of days spent in hospital lasting more than three days (χ2 = 13.37, df = 1, p < 0 .001). There were no statistically reliable differences in the remaining secondary measures. Conclusion The results showed a reduction in readmissions and potential post-intervention length of stay, indicating there may be further benefits for our older patients’ experiences and hospital flow.

The efforts to improve health care delivery usually involve studies and analysis of patient populations and healthcare systems. In this dissertation, I present the research conducted in the following areas: identifying patient groups, improving treatments for specific conditions by using statistical as well as data mining techniques, and developing new operation research models to increase system efficiency from the health institutes’ perspective. The results provide better understanding of high risk patient groups, more accuracy in detecting disease’ correlations and practical scheduling tools that consider uncertain operation durations and real-life constraints.

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The U.S. healthcare system is facing many public health challenges that affect population health, societal well-being, and quality of healthcare. Infant mortality, opioid overdose death, and hospital readmission after stroke are some of these important public health concerns that can impact the effectiveness and outcomes of the healthcare system. We analyze these problems through the industrial engineering and data analytics lens. The major goal of this dissertation is to enhance understanding of these three challenges and related interventions using different levels of analysis to improve the health outcomes. To attain this objective, I introduced three stand-alone papers to answer the related research questions. In essay 1, we focused on the performance of the state's healthcare systems in reducing unfavorable birth outcomes such as infant mortality, preterm birth, and low birthweight using Data Envelopment Approach. We constructed a unique state-level dataset to answer this main research question: what does make a healthcare system more successful in improving the birth outcomes? Our results indicated that socioeconomic and demographic factors may facilitate or obstruct health systems in improving their outcomes. We realized that states with a lower rate of poverty and African-American women were more successful in effectively reduce unfavorable birth outcomes. In the second essay, we looked into the trends of the opioid overdose mortalities in each state from 2008 to 2017. We investigated the effect of four state laws and programs that have been established to curb the epidemic (i.e., dose and duration limitations on the initial prescription, pain management clinic laws, mandated use of prescription drug monitoring programs, and medical cannabis laws) in short and long-term, while we controlled for several protentional risk factors. The results of fixed-effect regression and significant tests indicated that state policies and laws were unlikely to result in an immediate reduction in overdose mortalities and comprehensive interventions were needed to restrain the epidemic. The third essay investigated the risk factors of 30-day readmission in patients with ischemic stroke at an individual level. We aimed to identify the main risk factors of stroke readmissions and prioritized them using machine learning techniques and logistic regression. We also introduced the most effective predictive model based on different performance metrics. We used the electronic health records of stroke patients extracted from two stroke centers within the Geisinger Health System from 2015 to 2018. This data set included a comprehensive list of clinical features, patients' comorbidities, demographical characteristics, discharge status, and type of health insurance. One of the major findings of this study was that stroke severity, insert an indwelling urinary catheter, and hypercoagulable state were more important than generally known diagnoses such as diabetes and hypertension in the prediction of stroke 30-day readmission. Furthermore, machine learning-based models can be designed to provide a better predictive model. Overall, this dissertation provided new insights to better understand the three major challenges of the U.S. healthcare system and improve its outcomes. / Doctor of Philosophy / The major goal of a healthcare system can be summarized in three main objectives: preventing preterm birth and premature mortality, advancing the quality of life, and preparing for a good death. Despite all the national efforts to achieve these goals, the U.S. healthcare system still faces many obstacles and crises and suffers from inefficiencies. The U.S. infant mortality rate is still higher than any other comparable advanced country. The opioid overdose death rate has been steadily increasing since 1999 and has risen exponentially in recent years. Hospital readmissions especially in stroke patients impose a substantial cost burden on the healthcare system in the U.S. Also, readmitted stroke patients are at higher risk of mortality compared to the first admission. I believe that industrial engineering and data analytics approaches can help in advancing the understanding of these health challenges, their important risk factors, and effective interventions. In this dissertation, the main focus was on the performance, trends, variations, and processes of the healthcare systems. We applied innovative methods to provide answers to the following questions in three essays: What does make a healthcare system more successful in improving the birth outcomes? What factors do explain mortality from opioid painkillers? What are the determinants of state variations in mortalities from an opioid overdose? What is the impact of states' laws and programs and opioid prescription rates and overdose mortality rates? What are the most important contributors to stroke readmissions? The results of the first essay showed that not all the state's healthcare systems perform the same in terms of reducing unfavorable birth outcomes. States with lower people in poverty and lower African American women were more successful in improving their birth outcomes. The second study revealed that states with a higher share of uninsured people and binge drinkers were suffering from higher opioid overdose deaths. Also, our results implied that in addition to upstream prevention policies, states need to implement downstream programs to curb the epidemic. Finally, the third study showed that the top predictors of stroke readmissions within 30 days consist of the severity of the stroke, insert an indwelling urinary catheter, being overweight, and malnourished. The results of this dissertation can help to educate policymakers and practitioners at state and organizational level in a way to better serve the society and ultimately enhance the population health, quality of healthcare, and societal well-being.

This research examines the safety and cost effectiveness of an institutional policy on discharge of preterm infants with Apnea of Prematurity (AOP) from the Virginia Commonwealth University Medical Center Newborn Intensive Care Unit (VCUNC NICU) with caffeine therapy and a cardiorespiratory monitor. This practice policy was developed over a decade ago as a cost containment measure in neonatal care and continues to be implemented today despite the lack of a formal evaluation. The secondary objective was to examine through a review of the literature the psychosocial impact of premature birth on the family and the potential effect on the infant's hospital discharge. The evaluation of this policy is based on the conceptual framework of effectiveness, efficiency, and equity in health care. Results were used to generate policy recommendations.This is a retrospective case study of 933 infants admitted to the VCU Medical Center and the community hospital NICU between 1993 and 2002 diagnosed with Apnea of Prematurity. Data was obtained from the Neonatal Information System database at Virginia Commonwealth University Health System (VCUHS), the Virginia Department of Health, and the VCUHS hospital information system. In this mixed methods study, the infants were divided into two groups: 1) those discharged from the hospital on caffeine citrate therapy, and a cardiorespiratory monitor for continued management of apnea; and 2) those that were hospitalized until resolution of apnea. Data was analyzed for differences in mortality and morbidity, hospital readmissions and cost of hospital care from birth to 1 year of age. Interviews were conducted with NICU clinicians to obtain a qualitative perspective on this policy. No significant differences were found in the mortality rate between the two groups (p=.65), and the causes of the four deaths were unrelated to Apnea of Prematurity. Mean hospital costs were approximately $58,000 in both groups. Bronchiolitis was the leading cause for hospital readmission and there was no difference in the rate of hospital readmissions. Based on interviews with NICU clinicians, the policy works well and early discharge is advantageous to the infant and family. Therefore, we find no reason to not continue this policy. Study results support the importance and direction for further research on early discharge of infants with AOP and enhanced epidemiologic surveillance of this population.

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Hospital readmissions are a major burden for patients with end stage renal disease (ESRD). On average, one in three hospital discharges among patients with ESRD are followed by a readmission within 30 days. Currently, dialysis facilities are held accountable for readmissions via the ESRD Quality Incentive Program standardized readmission ratio (SRR) clinical measure. However, little is known about facility-level factors associated with readmission. Additionally, unlike other standardized measures of quality in the dialysis setting, incident patients within their first 90-days of dialysis are included in the performance calculation. This study analyzed CMS Dialysis Facility Report data from 2013 to 2016 to examine dialysis facility and incident patient factors associated with SRR using multivariate mixed models. Among 5,419 dialysis facilities treating 104,768 incident patients, the mean SRR remained stable across all four study years at 0.99. Factors significantly associated with a lower SRR (p<0.0001) included Western geographic region and higher patient care technician ratios. Several incident patient pre-dialysis nephrology care characteristics were associated with lower SRRs including higher percentages of patients with a fistula present at first dialysis treatment, higher percentages of patients receiving 6-12 months or greater than 12 months of nephrology care prior to dialysis and higher facility average hemoglobin. Factors significantly associated with a higher SRR (p<0.0001) included Northeastern geographic region, higher registered nurse ratios, higher percentage of incident patients, and higher facility average GFR. Understanding facility-level and patient-level factors associated with higher SRRs may inform interventions to reduce 30-day hospital readmission among patients receiving dialysis.

Heart failure (HF) is a serious public health problem associated with high mortality rates, hospital readmissions, and health care costs. Transitional care has emerged as a disease management model used to reduce readmissions for hospital-discharged patients with HF. However, the efficacy of an advanced practice nurse (APN)-led transitional care program (TCP) in readmission reduction is under debate. The practice question for this project examined the extent to which an APN-led TCP was effective in reducing 30-day all-cause readmissions for hospital-discharged HF patients. The logic model was the framework guiding this program evaluation. An analysis of quality improvement HF data from September 2015 to August 2016 was reviewed for one hospital in southern California. The APN-led TCP included 47 patients and had 7 patients with 30-day readmissions. The physicians' group included 298 patients and had 53 patients with 30-day readmissions. The results of chi-square analysis revealed a nonsignificant association between 30-day readmissions and post-discharge care providers [Ï? 2 (1, N = 345) = 0.236, p = 0.627], and the HF 30-day readmission rates were the same between two groups. The APN-led TCP served a large proportion of Medi-Cal patients (48.94%) who had less primary care access, while the majority of patients in the physicians' group were Medicare (51%) who had primary care providers. This project highlights the positive social changes that advanced practice nurses affect via their critical leadership and clinical roles in increasing care access for the low-income population. Further studies on payer sources and readmissions are recommended on the efficacy of APN-led TCP in readmission reduction.