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Healthcare utilizations are typically measured independently of each other; neglecting the interdependencies between services. An episode of care is suitable for measuring healthcare utilizations of patients with complex health conditions because it tracks all contacts throughout the healthcare system. The overall goal of this research was to construct an episode of care data system to study healthcare utilizations and costs of chronic obstructive pulmonary disease (COPD) exacerbations. To achieve this goal, four related studies were undertaken. The first study (Chapter 2) evaluated the agreement between emergency department (ED) data and hospital records for capturing transitions between the two care settings. Using the κ statistic as a measure of concordance, we found good agreement between the two data sources for intra-facility transfers; but only fair agreement for inter-facility transfers. The results show that linking multiple data sources would be important to identify all related healthcare utilization across care settings. The second study (Chapter 3) linked hospital data, ED data, physician billing claims, and outpatient drug records to construct an episode of care data system for COPD patients. Latent class analysis was used to identify COPD patient groups with distinct healthcare pathways. Pathways were associated with outcomes such as mortality and costs. A few individuals followed complex pathways and incurred high costs. Building on the previous study, the next one (Chapter 4) predicted whether high-cost patients in one episode also incurred high costs in subsequent episodes. Using logistic regression models, we found that patient information routinely collected in administrative health data could satisfactorily predict those who become persistent high users. The final study (Chapter 5) used a cross-validation approach to compare the performance of eight alternative linear regression models for predicting costs of episodes of COPD exacerbations. The results indicate that the robust regression model, a model not often considered for cost prediction, was among the best models for predicting episode-based costs. Overall, this research demonstrated how population-based administrative health databases could be linked to construct an episode of care data system for a chronic health condition. The resulting data system supported novel investigations of healthcare system-wide utilizations and costs. / May 2016

The present study assessed the relationship between Body Mass Index (BMI) and healthcare cost, utilization and health-related quality of life (HRQoL) of type 2 diabetes patients using the Medical Expenditure Panel Survey (MEPS) database. Study subjects were at least 18 years of age, diagnosed with diabetes and taking ≥1 oral antidiabetic medication. Data were extracted over a 5-year period (01/01/2006-12/31/2010). The main study outcomes were healthcare costs and utilization and HRQoL. The study covariates were age, gender, race, smoking status, census region of residence, marital status, insurance status, Charlson comorbidity index score and additional bed days. Study objectives were addressed using generalized linear model, negative binomial and multivariate regression analyses. A final un-weighted sample size of 7,003 patients was obtained. Mean age (±SE) was 61.2 (±0.24) years, mean BMI (±SE) was 32.2 (±0.12), and 50.4% were males. The majority was white (77.4%), did not smoke (84.5%), and were married (60.4%). Based on BMI categories, 12.6% had normal weight (BMI: 18.0-24.9); 29.2% were overweight (BMI: 25.0-29.9); 45.6% were obese (BMI: 30.0-39.9), and 12.6% were morbidly obese (BMI≥ 40.0). Compared to normal-weight patients; overweight, obese or morbidly obese patients had significantly higher (p<0.05) diabetes-related direct medical costs. However, overweight patients had significantly lower (p=0.021) all-cause direct medical costs. Furthermore, compared to normal weight patients, obese patients had a significantly higher (p=0.009) number of ambulatory care visits, while overweight patients had a significantly lower (p=0.035) number of emergency department visits. In addition, being obese or morbidly obese was associated with a significantly higher (p<0.0001) number of prescribed medicines compared to normal-weight patients. Compared to normal-weight patients; being obese or morbidly obese was also significantly (p<0.0001) associated with lower physical component summary (PCS-12) scores (i.e., worse quality of life) while being overweight was significantly (p=0.038) associated with higher mental component summary (MCS-12) scores (i.e., better quality of life). In conclusion, the present study suggests that among type 2 diabetes patients, being obese may be associated with negative consequences (in terms of healthcare costs, utilization and outcomes). Hence, there is the need to address obesity among type 2 diabetes patients in order to improve their health outcomes and significantly reduce healthcare costs and resource utilization. / text

Submitted by ANA PAULA RODRIGUES ROCHA null (rodrigues.anarocha@gmail.com) on 2017-10-24T13:08:34Z No. of bitstreams: 1 Dissertação.pdf: 1885406 bytes, checksum: 39f3136fdfcc9492b50e2d6b81990a29 (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-10-26T18:03:40Z (GMT) No. of bitstreams: 1 rocha_apr_me_prud.pdf: 1885406 bytes, checksum: 39f3136fdfcc9492b50e2d6b81990a29 (MD5) / Made available in DSpace on 2017-10-26T18:03:40Z (GMT). No. of bitstreams: 1 rocha_apr_me_prud.pdf: 1885406 bytes, checksum: 39f3136fdfcc9492b50e2d6b81990a29 (MD5) Previous issue date: 2017-08-21 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / As doenças crônicas geram impacto substancial nos custos públicos de saúde. A prática de exercício físico tem potencial de redução de concentrações circulantes de diversos biomarcadores inflamatórios, entretanto, não foram encontrados informações sobre o impacto de marcadores inflamatórios nos custos com saúde. Objetivo: Verificar se existe associação entre as concentrações de citocinas pró-inflamatórias e custo com saúde. Metodologia: Estudo transversal, conduzido em Presidente Prudente – SP. A amostra foi composta por homens e mulheres com idade maior que 50 anos, atendidos por Unidades Básicas de Saúde. Os participantes foram submetidos a avaliações que incluem as seguintes variáveis: i) pratica de atividade física habitual, ii) marcadores de inflamação, iii) perfil glicêmico e lipídico, iv) custos com o tratamento ambulatorial, v) excesso de peso e obesidade, vi) pressão arterial, vii) histórico de doença pessoal e familiar, viii) hábito de tabagismo e consumo alcoólico. A estatística descritiva foi composta por valores de média, desvio padrão, mediana, intervalo interquartil. O teste de Mann Whitney estabeleceu comparações entre os grupos formados, e as comparações significativas foram reanalisadas pela análise de covariância (ANCOVA). A significância estatística foi pré-fixada em valores inferiores a 5%, o software utilizado foi o BioEstat. Resultados: Nas comparações entre obesos e não obesos, foi possível identificar significância com valores superiores em obesos de concentrações de insulina (p-valor=0,039), do índice HOMA-IR (p-valor=0,016) e de leptina (p-valor=0,001), mesmo após ajuste. Da mesma forma, esses grupos apresentaram diferença estatisticamente significativa, nos custos com consulta médica (p=0,004), medicamentos (p-valor=0,038), custo total (p-valor=0,026) e custo total adicional (p-valor=0,024), sendo que custo de medicamentos (p-valor=0,007), custo total (p-valor=0,014) e custo total adicional (p-valor =0,017) foram mantidos após ajuste. Nas comparações entre ativos e inativos, foi possível identificar significância estatística com valores superiores para concentrações de glicose (p-valor=0,009) para os inativos e valores superiores para concentrações de TG (p-valor=0,031) para os ativos, no domínio exercício; somente TG (p-valor=0,040) se manteve significativo após o ajuste. Nos custos com saúde, foi possível identificar valores significativamente inferiores, para os participantes considerados ativos no domínio ocupacional, para custos com medicamentos (p=0,001), custo total (p=0,004) e custo total adicional (p-valor=0,008). Na correlação entre marcadores metabólicos e inflamatórios e custos de saúde, pode-se observar relação positiva e significante, ajustado por IMC e AFH, entre concentrações de glicose e custos de exames (r=0,343; p-valor=0,007) e custo total (r=261; p-valor=0,043); índice HOMA-IR e custo de exames (r=0,267; p-valor=0,038); IL-10 e custo com consulta médica (r=0,297; p-valor=0,020). Ajustado por %GC e AFH, custo de exame e concentrações de glicose (r=0,338; p-valor=0,008) e HOMA-IR (r=0,262; pvalor=0,042); custo total e glicose (r=0,295; p-valor=0,021); custo de consulta médica e IL-10 (r=0,297; p-valor=0,020). Conclusão: Com essa pesquisa foi possível concluir que marcadores metabólicos e inflamatórios estão relacionados com custos de consultas e exames, independentemente de IMC, %GC e AFH. Além disso, a obesidade esteve associada à concentração de insulina, HOMA-IR e leptina, bem como concentração de glicose foi menor em praticantes de atividade física. / Chronic diseases have a substantial impact on public health costs. The practice of physical exercise with the potential to reduce circulating concentrations of several inflammatory biomarkers, however, did not find information on the impact of inflammatory markers on health costs. Cross-sectional study, conducted in Presidente Prudente - SP. The sample consisted of men and women over 50 years old, attended by Basic Health Units. The sample consisted of men and women aged over 50, attended by basic health units of Presidente Prudente. Participants underwent evaluations that included the following variables: i) habitual physical activity, ii) markers of inflammation, iii) glycemic and lipid profile, iv) costs of outpatient treatment, v) excess weight, vi) blood pressure, vii) history of personal and family illness, viii) smoking habit and. Statistical analysis: The descriptive statistics were composed of mean values, standard deviation, median, interquartile range. The Mann Whitney test established comparisons between the groups formed, and significant comparisons were reanalysed by covariance analysis (ANCOVA). Statistical significance was set at values lower than 5%, the software used was BioEstat. Results: In the comparisons between obese and non-obese subjects, it was possible to identify higher values in obese subjects with insulin (p-value = 0.039), HOMA-IR (p-value = 0.016) and leptin (p-value = 0.001 ), even after adjustment. In the same way, these groups presented a statistically significant difference in the costs of medical consultation (p = 0.004), medication (p-value = 0.038), total cost (p-value = 0.026) and additional total cost ), with drug costs (p-value = 0.007), total cost (p-value = 0.014) and additional total cost (p-value = 0.017) were maintained after adjustment. In the comparisons between active and inactive, it was possible to identify statistical significance with higher values for glucose concentrations (p-value = 0.009) for the inactive and higher values for TG concentrations (p-value = 0.031) ; only TG (p-value = 0.040) remained significant after adjustment. In the health costs, it was possible to identify significantly lower values for the participants considered active in the occupational domain, for costs with medicines (p = 0.001), total cost (p = 0.004) and additional total cost (p-value = 0.008). In the correlation between metabolic and inflammatory markers and health costs, we can observe a positive and significant relationship, adjusted for BMI and AFH, between glucose concentrations and exam costs (r = 0.343, p-value = 0.007) and total cost r = 261; p-value = 0.043); HOMA-IR index and cost of exams (r = 0.267; p-value = 0.038); IL-10 and cost with medical consultation (r = 0.297; p-value = 0.020). Adjusted for% GC and AFH, examination cost and glucose concentrations (r = 0.338, p-value = 0.008) and HOMAIR (r = 0.262; p-value = 0.042); total cost and glucose (r = 0.295; p-value = 0.021); cost of medical consultation and IL-10 (r = 0.297; p-value = 0.020). Conclusion: This research it was possible to conclude that metabolic and inflammatory markers are related to the costs of consultations and examinations, independently of BMI,% GC and AFH. In addition, obesity was associated with insulin concentration, HOMA-IR and leptin, as well as glucose concentration was lower in physical activity practitioners. / FAPESP: 2015/12102-8 / FAPESP: 2014/09645-7 / FAPESP: 2015/13543-8 / CNPq: 401178/2013-7

Class of 2011 Abstract / OBJECTIVES: The overall purpose of this study was to describe comorbidities, charges, and mortality associated with inpatient, adult traumatic brain injury (TBI) cases in the United States (US) for the year 2007. METHODS: This was a retrospective cohort analysis of discharge records located in the National Emergency Department Sample (NEDS) of the Healthcare Cost and Utilization Project (HCUP). Descriptive statistics are provided for comorbidities, charges, and mortality. Logistic regression was performed to find characteristics associated with mortality while multiple regression was used to assess charges. Independent variables included age, injury severity, procedures used, location of TBI, and primary payer. RESULTS: A total of 639,698 TBI cases were found which were associated with 267,061 hospital admissions, over $17 billion in hospital charges, and 20,620 deaths in the year 2007.Most common comorbidities were essential hypertension, sprains and strains of the back, tobacco use, fluid and electrolyte disorders, and alcohol-related disorders. Characteristics associated with increased mortality and charges included New Injury Severity Score (NISS) over 10, involvement of a firearm, falls, motor vehicle traffic, and intubation. CONCLUSION: The current study gives the most current picture of inpatient adult TBI cases throughout the US. Future research is warranted to ensure that optimal outcomes are being attained in this vulnerable patient population.

Class of 2011 Abstract / OBJECTIVES: The purpose of this study was to analyze the impact of patient and hospital characteristics as well as selected comorbidities on inpatient mortality and charges in pediatric HSCT. We have determined the top 25 comorbidities reported during all inpatient stays for HSCT as well as for those stays ending in mortality. METHODS: All data was extracted from the AHRQ KID databases for the years 1997, 2000, 2003, and 2006. Two regression analyses were performed to determine the contribution of various independent variables on mortality and charges. Subjects of this study included all cases of HSCT reported in the Healthcare Cost and Utilization Project (HCUP) KID as ICD-9 41.XX. RESULTS: Factors accounting for larger increases in cost included death during hospital stay, the development of disseminated intravascular coagulation (DIC), pneumonia, and length of stay (LOS). The largest decreases in charges were seen for patients coming from a small or “micropolitan” location, patients cared for in teaching hospitals, and in hospitals with large bedsizes. Variables associated with increased risk of mortality on linear regression included development of DIC, sepsis, or pneumonia. CONCLUSION: Further study relating to HSCT is necessary to determine the contribution of specific comorbidities to mortality and charges. Importantly, DIC is associated with both greater risk of mortality and greater charges. It would be prudent to recommend increased monitoring and early treatment for DIC based on these results.

[pt] Empresas do ramo da Saúde vêm evoluindo seus modelos de gestão, desenvolvendo programas proativos para melhorar a qualidade e a eficiência dos seus serviços considerando informações históricas. Estratégias proativas buscam prevenir e detectar doenças precocemente e também melhorar os resultados das internações. Nesse sentido, uma tarefa desafiadora é identificar quais pacientes devem ser incluídos em programas proativos de saúde. Para isso, a previsão e a modelagem de variáveis relacionadas aos custos estão entre as abordagens mais amplamente utilizadas, uma vez que essas variáveis sào potenciais indicadores do risco, da gravidade e do consumo de recursos médicos de uma internação. A maioria das pesquisas nesta área têm como foco modelar variáveis de custo em uma perspectiva geral e prever variações de custos para períodos específicos. Por outro lado, este trabalho se concentra na previsão dos custos de um evento específico. Em particular, esta dissertação prescreve uma solução para a predição de internações de alto custo, visando dar apoio a gestores de serviços em saúde em suas ações proativas. Para esse fim, foi seguida a metodologia de pesquisa Design Science Research (DSR), aliada ao ciclo de vida de projeto de Ciência de Dados, sobre um cenário real de uma empresa de consultoria em saúde. Os dados fornecidos descrevem internações de pacientes através de suas características demográficas e do histórico de consumo de recursos médicos. Diferentes técnicas estatísticas e de Aprendizado de Máquina foram aplicadas, como Ridge Regression (RR), Least Absolute Shrinkage and Selection Operator (LASSO), Classification and Regression Trees (CART), Random Forest (RF) e Extreme Gradient Boosting (XGB). Os resultados experimentais evidenciaram que as técnicas RF e XGB apresentaram o melhor desempenho, atingindo AUCPR de 0,732 e 0,644, respectivamente. O modelo de predição da técnica RF foi capaz de detectar até 72 porcento, em média, das internações de alto custo com 33 porcento de precisão, o que representa 78,7 porcento do custo total gerado por tais internações. Além disso, os resultados monstraram que o uso de custo prévio e variáveis agregadas de consumo de recursos aumentaram a capacidade de predição do modelo / [en] Healthcare providers are evolving their management models, developing proactive programs to improve the quality and efficiency of their health services, considering the available historical information. Proactive strategies seek not only to prevent and detect diseases but also to enhance hospitalization outcomes. In this sense, one of the most challenging tasks is to identify which patients should be included in proactive health programs. To this end, forecasting and modeling cost-related variables are among the most widely used approaches for identifying such patients, since these variables are potential indicators of the patients hospitalization risk, their severity, and their medical resources consumption. Most of the existing research works in this area aim to model cost variables from an overall perspective and predict cost variations for specific periods. In contrast, this work focuses on predicting the costs of a particular event. Specifically, this thesis prescribes a solution for identifying high-cost hospitalizations, to support health service managers in their proactive actions. To this end, the Design Science Research (DSR) methodology was combined with the Data Science life cycle in a real scenario of a health consulting company. The data provided describes patients hospitalizations through their demographic characteristics and their medical resource consumption. Different statistical and Machine Learning techniques were used to predict high-cost hospitalizations, such as Ridge Regression (RR), Least Absolute Shrinkage and Selection Operator (LASSO), Classification and Regression Trees (CART), Random Forest (RF), and Extreme Gradient Boosting (XGB). The experimental results showed that RF and XGB presented the best performance, reaching an Area Under the Curve Precision-Recall (AUCPR) of 0.732 and 0.644, respectively. In the case of RF, the model was able to detect, on average, 72 percent of the high-cost hospitalizations with a 33 percent of Precision, which represents 78.7 percent of the total cost generated by the high-cost hospitalizations. Moreover, the obtained results showed that the use of prior cost and aggregated variables of resource consumption increased the model s ability to predict high-cost hospitalizations.

Many studies have reported that the training for practitioners does not stimulate reflexes that contribute to the tenets of teamwork and collaboration. No studies were found to investigate relational intelligence (RQ) in pharmacist-physician relationships as a catalyst for collaborative and hence cost effective quality care. This study addressed the role and potential opportunity to promote RQ as a critical leadership skill in the collaboration between pharmacists and physicians. Using RQ as the conceptual framework, this phenomenological study explored how pharmacists and physicians in a hospital setting perceive RQ as a leadership skill when working collaboratively. A total of 10 participants (5 pharmacists and 5 physicians) from a 443-bed comprehensive hospital in Michigan were selected using purposive sampling. Pharmacists and physicians included had at least 4 years of hospital experience. Data were collected through semistructured in-depth interviews and analyzed using the hierarchical approach. Results indicated interest among both pharmacists and physicians to use RQ as a leadership skill to work collaboratively. Further findings highlighted the need for face-to-face communication between pharmacists and physicians, better collaboration, accountability, feedback, focus and alignment, promotion of positive relationships, and a leadership position directed by a PhD-prepared practitioner with expertise in RQ. These findings bring awareness to both pharmacists and physicians of barriers to collaboration; these findings also suggest the need for multidisciplinary training that incorporates RQ theory as a foundation for both pharmacists and physicians, which may decrease health care costs while improving communication, trust, mutual understanding, collaboration, and quality care.

Class of 2012 Abstract / Specific Aims: This study was aimed to evaluate inpatient clinical treatment characteristics associated with the use of intracranial implantation of chemotherapeutic wafers for malignant brain neoplasms within United States, and assess inpatient mortality and total charges regarding treatment with wafer versus without. Methods: A retrospective cohort investigation was conducted utilizing inpatient discharge records from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample from 2005 to 2009. From this nationally-representative sample, 9,455 adults aged 18 years or older were identified with malignant neoplasms of the brain treated with implantable chemotherapeutic wafers. Outcomes of inpatient mortality and charges were assessed via multivariate regression analysis, controlling for patient characteristics, hospital structure, comorbidities, and clinical complications. Main Results: The average age of patients with brain neoplasms was 56.6 (±16.5) years, and of those patients, 42.9% were female. The odds ratio for inpatient mortality of patients treated with implantable chemotherapeutic wafers was OR=0.380 (P<0.001), and patients that received wafer treatment had increased charges exp(b)=2.147 (P<0.001). Conclusions: Multiple factors were associated with inpatient mortality and charges among the 247,829 patients that were diagnosed with malignant brain neoplasms from 2005-2009. With regards to these patients, implantable chemotherapeutic wafers were associated with increased inpatient survival and increased charges.