Background: Religious involvement is widespread and may influence patient engagement with their healthcare (patient activation) and health outcomes. This dissertation examined the association between religiosity and patient activation, changes in health-related quality of life (HRQOL), readmissions, and survival after hospitalization for acute coronary syndrome (ACS). Methods: We recruited 2,174 patients hospitalized for ACS in Georgia and Central Massachusetts (2011-2013) in a prospective cohort study. Participants self-reported three items assessing religiosity – strength/comfort from religion, petition prayers for health, and awareness of intercessory prayers by others. Patient activation was measured using the 6-item Patient Activation Measure. Generic HRQOL was assessed with the SF-36®v2 physical and mental component summary scores. Disease-specific HRQOL was evaluated with the Seattle Angina Questionnaire Quality of Life subscale. Unscheduled readmissions were validated from medical records. Mortality status was obtained from national and state vital statistics. Results: After adjustment for several sociodemographic, psychosocial, and clinical variables, reports of strength/comfort from religion and receipt of intercessions were associated with high activation. Praying for one’s health was associated with low activation. Prayers for health were associated with clinically meaningful increases in disease-specific and physical HRQOL. Neither strength/comfort from religion, petition, nor intercessory prayers were significantly associated with unscheduled 30-day readmissions and two-year all-cause mortality. Conclusions: Most ACS survivors acknowledge religious practices for their health. Religiosity was associated with patient activation and changes in HRQOL. These findings suggest that religiosity may influence patient engagement in their healthcare and recovery after a life-threatening illness, buttressing the need for holistic approach in patient management.

Because parental alcohol misuse is associated with numerous negative outcomes for drinkers and other family members, it is important to examine factors predictive of alcohol misuse patterns among parents living with at least one child under the age of 18. Two possible factors include economic insecurity and poverty. This study sought to address whether measures of economic insecurity (i.e., housing and/or food insecurity in the past 12 months) and a dichotomous measure of poverty predict parental binge drinking and parental heavy alcohol consumption in a large population-based sample. It was hypothesized that economic insecurity and poverty, analyzed separately, would predict both occurrence of parental alcohol misuse and amount of alcohol consumed. Results did not support hypotheses; rather, where significant, they indicated that measures of economic insecurity and poverty negatively predicted parental alcohol misuse. However, effect sizes were small and preclude practical application. Findings are discussed and future research directions are identified.

Background: The mood stabilizer lithium has long been reported to be associated with reduced suicide risks, but many studies reporting associations between lithium and reduced suicide risks also have been nonrandomized and lacked adjustment for many potential confounders, active controls, uniform follow-up, or intent-to-treat samples. Concerns also have been raised that medications being considered as potential suicide preventative might increase risks of nonsuicide mortality while reducing risks of suicide. Methods: Three studies of Veterans Health Administration (VHA) patients were conducted combining high-dimensional propensity score matching with intent-to-treat analyses to examine the associations between lithium and valproate and one-year suicide and nonsuicide mortality outcomes. Results: In intention-to-treat analyses, initiation of lithium, compared to valproate, was associated with increased suicide mortality over 0-365 days among patients with bipolar disorder (Hazard Ratio (HR) 1.50 [95% Confidence Interval 1.05, 2.15]) Nonsuicide mortality among VHA patients with or without bipolar disorder was not significantly associated with the initiation of lithium compared to valproate ( HR 0.92 [0.82-1.04]). Rates of treatment discontinuation, however, were very high (≈ 92%). Longitudinal analyses revealed that the increased suicide risks associated with initiating lithium among patients with bipolar disorder occurred exclusively after discontinuation of lithium vii treatment. In secondary analyses restricted to patients still receiving their initial treatment, there was no difference in suicide risk between the initiation of lithium or valproate. Conclusions: Significantly increased risks of suicide were observed at one year among VHA patients with bipolar disorder initiating lithium compared to valproate, related to risks observed after the discontinuation of lithium treatment Since these studies are nonrandomized, confounding may account for some or all of our findings, including the risks observed after lithium discontinuation. Nevertheless, these results suggest that health systems and providers consider steps to minimize any potential lithium discontinuation-associated risk. Approaches might include educating patients about possible risks associated with discontinuation and closely monitoring patients after discontinuation if feasible. Given the obvious importance of any substantive difference between lithium and valproate in suicide or nonsuicide mortality risk, our studies also suggest that further research is needed, especially research that can further minimize the potential for confounding.

Background. AHA guidelines have been established to reduce Acute Coronary Syndrome (ACS)-related morbidity, mortality and recurrent events post-discharge. These recommendations emphasize the patient as an engaged member of the health care team in secondary prevention efforts. Patients with high levels of activation are more likely to perform activities that will promote their own health and are more likely to have their health care needs met. Despite evidence and strong expert consensus supporting patients as active collaborators in their own ACS care, the complexity and unexpected realities of self-managing one’s care at home are often underestimated. This study seeks to examine the correlates of patient activation at hospital discharge and then identifies activation trajectories in this same cohort in subsequent months. Lastly, this study examines the association between patient activation and health care utilization in the year subsequent to an ACS event. Methods. This study incorporates three aims: Aim 1, identification of the correlates of low patient activation post-discharge; Aim 2, identification of patient activation trajectories among this same cohort in the months following hospitalization; and Aim 3, examination of the association between patient activation and health utilization, post-discharge. Results. Fifty-nine percent of ACS patients identified as being at the lowest two activation stages at the time of hospital discharge. Perceived stress (pidentified post-discharge: low, stable (T1), high, sharp decline (T2), and sharp improvement (T3). The majority of patients (67%) identified as being in T1. Those patients of older age (OR: 2.22; CI 1.4- 3.5), identifying as Black in race (OR: 2.14: CI 1.1- 4.3), and reporting moderate/high perceived stress (OR: 2.54: CI 1.4- 4.5) had increased odds of being in the low, stable trajectory. The bivariate analysis indicated a significant association (P=0.008) between low patient activation and self-reported hospital readmissions in the months following discharge. In the final model, moderate to severe depression (OR: 1.60; CI 1.1- 2.3) was the strongest predictor of readmissions in the 12 months subsequent to discharge. Conclusions: Patients reported low activation at hospital discharge after an ACS event indicated that these patients were not prepared to take an active role in their own care. Correlates of low activation at discharge include moderate to high perceived stress, depression, and low social support. Furthermore, in the months following hospital discharge, the majority of these patients followed either a low/stable or a sharp decline activation trajectory. Hence, these results suggest that over time patients feel less and less confident to take an active role in self-management. Lastly, we found that patient activation may impact healthcare utilization in the year subsequent to hospital discharge, although patient self-reported depression appears to be the strongest predictor of utilization in the subsequent year. Future research is needed to better understand the relationship(s) among patient activation, depression, and health care utilization.

Background: Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in the U.S. Acute myocardial infarction (AMI), with or without ST-segment elevation, is a common presentation of coronary heart disease and affected more than 800,000 American adults in 2010. The overall goal of this dissertation was to examine decade-long trends in the extent of delay in the receipt of a primary percutaneous coronary intervention (PCI) among patients hospitalized with ST-segment elevation myocardial infarction (STEMI), 30-day hospital readmission rates in patients having survived an AMI, and multiple decade long trends in 1-year post-hospital all-cause mortality, as well as factors associated with these outcomes, among patients hospitalized with AMI. Methods: Data from the Worcester Heart Attack Study, a population-based chronic disease surveillance project that has been carried out among adult residents of the Worcester, MA, metropolitan area, hospitalized with AMI on a biennial basis from 1975 through 2009 at all medical centers in central MA, were used for this dissertation. Results: Between 1999 and 2009, among patients hospitalized with STEMI, the likelihood of receiving a primary PCI within 90 minutes after emergency department arrival increased dramatically from 1999/2001 (11.6%) to 2007/2009 (70.5%). Between 1999 and 2009, among hospital survivors of an AMI, the 30-day all-cause rehospitalization rates decreased from 1999/2001 (20.3%) to 2007/2009 (16.7%). The overall cause-specific 30-day rehospitalization rates due to CVD, non-CVD, and AMI were 10.1%, 7.1%, and 1.8%, respectively, during the years under study. Between 1975 and 2009, among hospital survivors for a first AMI, the 1-year post-discharge mortality rates remained relatively stable from 1975-1984 (12.9%) to 1986-1997 (12.5%), but increased during 1999-2009 (15.8%). We identified several demographic, clinical and in-hospital treatment factors associated with an increased risk of failing to receive a primary PCI within 90 minutes after emergency department arrival, 30-day readmissions, and 1-year post-discharge mortality. Conclusions: Our findings can hopefully lead to the enhanced development of innovative, patient-centered, intervention strategies which can further improve the treatment and transitions of care, as well as short and long-term prognosis, of men and women hospitalized with AMI.

The spread of pandemic influenza A (2009 H1N1 influenza) virus resulted in a global influenza pandemic in 2009. During the early stages of the pandemic, population surveillance was crucial. However, officials around the world realized that many of our surveillance and reporting systems were not prepared to respond in a coordinated, integrated way, which made informed public health decision-making very difficult. More accurate estimates of the total number of hospitalized 2009 H1N1 influenza cases were required to calculate population-based 2009 H1N1 influenza-associated mortality, morbidity and hospitalization rates. For instance, how many people were hospitalized with 2009 H1N1 influenza in Massachusetts? Of these, how many were admitted to the ICU and how many died? Compared to seasonal influenza, were some race/ethnic and age groups affected more than others, and what types of characteristics led to more severe manifestations of 2009 H1N1 influenza among these groups in Massachusetts? To address the above questions, I proposed a retrospective cohort study using data from the Hospital Discharge Database (HDD), which contains data for all inpatients discharged from 76 acute care hospitals in Massachusetts, as well as Census information to provide a measure of socioeconomic status (SES). My specific aims are as follows: 1. Develop methods to identify influenza cases precisely and describe characteristics of those hospitalized with ILI in MA between April 26-Sept 30, 2009; 2. Conduct analyses to identify race/ethnicity-related trends in reference to 2009 H1N1 influenza-related hospitalizations; 3. Conduct analyses to identify age-related trends in reference to 2009 H1N1 influenza-related hospitalizations. First, I established influenza case selection criteria using hospital discharge data. I addressed limitations in the published methods on defining cases of influenza using administrative databases, and evaluated ICD-9 codes that correspond with common and relatively serious respiratory infections and influenza using a ‘maximum’ and ‘minimum’ approach. Results confirmed that 2009 H1N1 influenza affected a younger population, and disproportionately affected racial minorities in Massachusetts. There were also higher rates of ICU admission compared to seasonal influenza. I then presented epidemiological data indicating race/ethnic disparity among 2009 H1N1 influenza cases in Massachusetts. I found that Hispanics had significantly lower odds of 2009 H1N1 influenza-related ICU stay. SES gradients calculated using five-digit zip code information did not account for these differences. Within race/ethnic strata, Hispanics Finally, I presented epidemiological data indicating differences among 2009 H1N1 influenza cases by age group in Massachusetts. I calculated measures of Diagnostic Cost Group (DxCG) comorbidity for the study population to provide a comorbidity measure at baseline. Main results indicate that although comorbidity scores were similar between the 2009 H1N1 influenza and seasonal influenza groups, 2009 H1N1 influenza caused more severe disease in younger age groups. This is the first study to report population-based statewide outcomes in all acute care centers in MA. In this dissertation I address challenges surrounding influenza surveillance to create case selection criteria within an administrative database. Using my case selection criteria, I then provide data related to fatality and severity of 2009 H1N1 influenza in Massachusetts in reference to sociodemographic variables such as racial/ethnicity and age groups, and provide evidence for patient-level interventions to those hardest hit by influenza. These findings provide valuable information about using large administrative databases to describe pandemic influenza cases and guide resource allocation to reduce disparities in relation to pandemic influenza preparedness.

Objective: Chronic obstructive pulmonary disease (COPD) is a common comorbidity in patients with heart failure, yet little is known about the impact of this condition in patients with acute decompensated heart failure (ADHF), especially from a more generalizable, community-based perspective. The primary objective of this study was to describe the in-hospital and post discharge mortality and treatment of patients hospitalized with ADHF according to COPD status. Methods: The study population consisted of patients hospitalized with ADHF at all 11 medical centers in central Massachusetts during 4 study years: 1995, 2000, 2002, and 2004. Results: Of the 9,748 patients hospitalized with ADHF during the years under study, 35.9% had a history of COPD. The average age of this population was 76.1 years, 43.9% were men, and 93.3% were white. At the time of hospital discharge, patients with COPD were less likely to have received evidence-based heart failure medications, including beta-blockers and ACE inhibitors/angiotensin receptor blockers, than patients without COPD. Multivariable adjusted in-hospital death rates were similar for patients with and without COPD. However, among patients who survived to hospital discharge, patients with COPD had a significantly higher risk of dying at 1 (adjusted RR 1.10; 95% CI 1.06, 1.14) and 5-years (adjusted RR 1.40; 95% CI 1.28, 1.42) after hospital discharge than patients who were not previously diagnosed with COPD. Conclusions: COPD is a common co-morbidity in patients hospitalized with ADHF and is associated with a worse long-term prognosis. Further research is required to understand the complex interactions of these diseases and to ensure that patients with ADHF and COPD receive optimal treatment modalities.

In recent years, the transplant community has explored and adopted tools for quantifying clinical insight into illness severity and frailty. This dissertation work explores the interplay between objective and subjective assessments of physical health status and the implications for liver transplant candidate and recipient outcomes. The first aim characterizes national epidemiologic trends and the impact of Centers for Medicare and Medicaid quality improvement policies on likelihood of waitlist removal based on the patient being too frail to benefit from liver transplant (“too sick to transplant”). This aim includes more than a decade (2002–2012) of comprehensive national transplant waitlist data (Scientific Registry of Transplant Recipients (SRTR)). The second aim will assess and define objective parameters of liver transplant patient frailty by measuring decline in lean core muscle mass (“sarcopenia”) using abdominal CT scans collected retrospectively at a single U.S. transplant center between 2006 and 2015. The relationship between these objective sarcopenia measures and subjective functional status assessed using the Karnofsky Functional Performance (KPS) scale are described and quantified. The third aim quantifies the extent to which poor functional status (KPS) pre-transplant is associated with worse post-transplant survival and includes national data on liver transplantations conducted between 2005 and 2014 (SRTR). The results of this dissertation will help providers in the assessment of frailty and subsequent risk of adverse outcomes and has implications for strategic clinical management in anticipation of surgery. This research will also to serve to inform national policy on the design of transplant center performance measures.

Background: Overtreatment of localized prostate cancer (PCa) is a concern as many men die of other causes prior to experiencing a treatment benefit. This dissertation characterizes the need for assessing other cause mortality (OCM) risk in older men with PCa and informs efforts to identify patients most likely to benefit from definitive PCa treatment. Methods: Using the linked Surveillance Epidemiology and End Results-Medicare Health Outcomes Survey database, 2,931 men (mean age=75) newly diagnosed with clinical stage T1a-T3a PCa from 1998-2009 were identified. Survival analysis methods were used to compare observed 10-year OCM by primary treatment type. Age and health factors predictive of primary treatment type were assessed with multinomial logistic regression. Predicted mortality estimates from Social Security life tables (recommended for life expectancy evaluation) and two OCM risk estimation tools were compared to observed rates. An improved OCM prediction model was developed fitting Fine and Gray competing risks models for 10-year OCM with age, sociodemographic, comorbidity, activities of daily living, and patient-reported health data as predictors. The tools’ ability to discriminate between patients who died and those who did not was evaluated with Harrell’s c-index (range 0.5-1), which also guided new model selection. Results: Fifty-four percent of older men with localized PCa underwent radiotherapy while 13% underwent prostatectomy. Twenty-three percent of those treated with radiotherapy and 12% of those undergoing prostatectomy experienced OCM within 10 years of treatment and thus were considered overtreated. Health factors indicative of a shorter life expectancy (increased comorbidity, worse physical health, smoking) had little to no association with radiotherapy assignment but were significantly related to reductions in the likelihood of undergoing prostatectomy. Social Security life tables overestimated mortality risk and discriminated poorly between men who died and those who did not over 10 years (c-index=0.59). Existing OCM risk estimation tools were less likely to overestimate OCM rates and had limited but improved discrimination (c-index=0.64). A risk model developed with self-reported age, Charlson comorbidity index score, overall health (excellent-good/fair/poor), smoking, and marital status predictors had improved discrimination (c-index=0.70). Conclusions: Overtreatment of older men with PCa is primarily attributable to radiotherapy and may be reduced by pretreatment assessment of mortality-related health factors. This dissertation provides a prognostic model which utilizes a set of five self-reported characteristics that better identify patients likely to die of OCM within 10 years of diagnosis than age and comorbidity-based assessments alone.

Background: Traumatic injury remains a major cause of mortality in the US. Older Americans experience lower rates of injury and higher rates of death at lower injury severity than their younger counterparts. The objectives of this study were to explore pre-injury factors and injury patterns that are associated with post-discharge mortality among injured elderly surviving index hospitalization. Methods: We queried a 5% random sample of Medicare beneficiaries (n=2,002,420) for any hospitalization with a primary ICD-9 diagnosis code for injury. Patients admitted without urgent/emergent admission were excluded, as well as patients presenting from inpatient hospitalization or rehabilitation. The primary endpoint was all-cause mortality. Patients were categorized into three mortality groups: death within 0-30 days, 31-90 days, or 91- 365 days post-discharge from the index hospitalization. These groups were compared with those who survived greater than one year post-discharge. Univariate tests of association and multivariable logistic regression models were utilized to identify factors associated with mortality during the 3 examined periods. Results: 83,439 elderly patients (4.2%) were admitted with new injuries. 63,628 met inclusion criteria. 1,936 patients (3.0%) died during their index hospitalization, 2,410 (3.8%) died within 0-30 days, 3,084 (4.8%) died within 31-90 days, and 5,718 (9.0%) died within 91- 365 days after discharge. In multivariable adjusted models, advanced age, male sex, and higher Elixhauser score were associated with post-discharge mortality. The presence of critical injury had the greatest effect on mortality early after injury (0-30 days, OR 1.81, CI 1.64-2.00). Discharge to anywhere other than home without services was associated with an increased odds of dying. Conclusions: Socio-demographic characteristics, disposition, and co-morbid factors were the strongest predictors of post-discharge mortality. Efforts to reduce injury-related mortality should focus on injury prevention and modification of co-morbidities.