Distributed analyses of disease risk and association across networks of de-identified medical systems

Health information networks continue to expand under the Affordable Care Act yet little research has been done to query and analyze multiple patient populations in parallel. Differences between hospitals relating to patient demographics, treatment approaches, disease prevalences, and medical coding practices all pose significant challenges for multi-site analysis and interpretation. Furthermore, numerous methodological issues arise when attempting to analyze disease association in heterogeneous health care settings. These issues will only continue to increase as greater numbers of hospitals are linked. To address these challenges, I developed the Shared Health Research Informatics Network (SHRINE), a distributed query and analysis system used by more than 60 health institutions for a wide range of disease studies. SHRINE was used to conduct one of the largest comorbidity studies in Autism Spectrum Disorders. SHRINE has enabled population scale studies in diabetes, rheumatology, public health, and pathology. Using Natural Language Processing, we de-identify physician notes and query pathology reports to locate human tissues for high-throughput biological validation. Samples and evidence obtained using these methods supported novel discoveries in human metabolism and paripartum cardiomyopathy, respectively. Each hospital in the SHRINE network hosts a local peer database that cannot be overridden by any federal agency. SHRINE can search both coded clinical concepts and de-identified physician notes to obtain very large cohort sizes for analysis. SHRINE intelligently clusters phenotypic concepts to minimize differences in health care settings. I then analyzed a statewide sample of all Massachusetts acute care hospitals and found diagnoses codes useful for predicting Acute Myocardial Infarction (AMI). The AMI association methods selected 96 clinical concepts. Manual review of PubMed citations supported the automated associations. AMI associations were most often discovered in the circulatory system and were most strongly linked to background diabetic retinopathy, diabetes with renal manifestations, and hypertension with complications. AMI risks were strongly associated with chronic kidney failure, liver diseases, chronic airway obstruction, hemodialysis procedures, and medical device complications. Learning the AMI associated risk factors improved disease predictions for patients in Massachusetts acute care hospitals

Unplanned readmission rates, length of hospital stay, mortality, and medical costs of ten common medical conditions: a retrospective analysis of Hong Kong hospital data

<p>Abstract</p> <p>Background</p> <p>Studies on readmissions attributed to particular medical conditions, especially heart failure, have generally not addressed the factors associated with readmissions and the implications for health outcomes and costs. This study aimed to investigate the factors associated with 30-day unplanned readmission for 10 common conditions and to determine the cost implications.</p> <p>Methods</p> <p>This population-based retrospective cohort study included patients admitted to all public hospitals in Hong Kong in 2007. The sample consisted of 337,694 hospitalizations in Internal Medicine. The disease-specific risk-adjusted odd ratio (OR), length of stay (LOS), mortality and attributable medical costs for the year were examined for unplanned readmissions for 10 medical conditions, namely malignant neoplasms, heart diseases, cerebrovascular diseases, pneumonia, injury and poisoning, nephritis and nephrosis, diabetes mellitus, chronic liver disease and cirrhosis, septicaemia, and aortic aneurysm.</p> <p>Results</p> <p>The overall unplanned readmission rate was 16.7%. Chronic liver disease and cirrhosis had the highest OR (1.62, 95% confidence interval (CI) 1.39-1.87). Patients with cerebrovascular disease had the longest LOS, with mean acute and rehabilitation stays of 6.9 and 3.0 days, respectively. Malignant neoplasms had the highest mortality rate (30.8%) followed by aortic aneurysm and pneumonia. The attributed medical cost of readmission was highest for heart disease (US$3 199 418, 95$2 579 443-803 393).</p> <p>Conclusions</p> <p>Our findings showed variations in readmission rates and mortality for different medical conditions which may suggest differences in the quality of care provided for various medical conditions. In-hospital care, comprehensive discharge planning, and post-discharge community support for patients need to be reviewed to improve the quality of care and patient health outcomes.</p

Hospitalization for COPD in Puglia: the role of hospital discharge database to estimate prevalence and incidence

Background and aim. Chronic Obstructive Pulmonary Disease (COPD), although largely preventable, is a great health burden in all the countries worldwide. Statistics of morbidity and mortality of COPD show the need for correct management of the disease. Chronic Obstructive Respiratory Diseases (DRG 88) are in 9th place for discharge in in-patient hospital admission. It is necessary to establish specific indicators which are efficacious and relevant for the patient, the doctor and the health manager. This study will analyse the information in respect of hospital admissions (Hospital discharge database) in Puglia for the period 2000-2005. Methods. The analysis was carried out utilising the Puglia Region hospital patient discharge database, selecting those patients with admission for chronic respiratory disease as principal or secondary diagnosis. Results. Chronic respiratory diseases are more frequent in males and in people over 45 years old with frequency increasing with age. Geographical distribution shows that there are greater rates of hospitalisation in big cities and in the neighbourhood of industrial areas. Although the trend over time is slight. A higher percentage of re-admission has been found for patients with COPD, and the interval between the two admissions occurs within one or two months; the diagnosis at the second admission is the same as for the first. 10.6% of discharge forms report one diagnosis, especially in patients older than 65 years of age. Little could be said about diagnostic procedures because these are not reported on the discharge form. Conclusion. Hospitalisation data confirms expectations regarding age and sex of patients. The high hospitalisation rates indicate that in-patients care still remains the only viable treatment for COPD and other chronic respiratory diseases. The high number of exacerbations reflect the absence of out-patients service or community care, and the same diagnosis in more than one episode shows the lack of efficiency of health services and disease management. This data is necessary to understand disease distribution and the modification of disease management in order to reduce health care costs, to increase efficacy in disease control and to limit repeated exacerbation and so to obtain the maximum benefit for the patients

Using Administrative Healthcare Records to Identify Determinants of Amputee Residuum Outcomes

In the United States, the number of major limb amputees is predicted to exceed several million in the coming decades. For those amputees using a prosthesis, their quality of life (QoL) is often modulated by residuum limb problems resultant from its use. Multiple factors preclude quality evidence-based medicine (EBM) research in the field of prosthetics, leading to greater health risk from prosthetic prescription ambiguity. Positive social change is integral to good QoL; studies support administrative healthcare (AHc) as useful to support such, especially in the absence of EBM. This study utilized Veterans Healthcare Administration (VHA) AHc data to discriminate determinants of residual limb skin problem severity (RLSPS), relative to the artificial limb configuration (ALC) used through a retrospective, longitudinal study of a cohort of U.S.Veteran dysvascular amputees. The dataset was derived from multiple archival VHA AHc databases from which 279 Cohort members were identified who underwent amputation surgery during the fiscal year (FY) 2007 were dispensed a prosthesis, and had clinical records through FY 2011. ICD-9-CM and HCPCS codes were used to identify categories of RLSPS and ALC, respectively, with generalized estimating equations modeling to identify likelihood associations of parameters. Derivation of the study cohort dataset was encumbered by data integrity issues and coding system limitations; significant associations were detected for RLSPS with chronic obstructive pulmonary disease, substance use disorder, and major depressive disorder, regardless of the ALC dispensed. The findings support the utility of an amputee-prosthesis AHc database to drive product, policy, and medical decisions toward an improved QoL for this vulnerable population

Simvastatin is associated with a reduced incidence of dementia and Parkinson's disease

<p>Abstract</p> <p>Background</p> <p>Statins are a class of medications that reduce cholesterol by inhibiting 3-hydroxy-3-methylglutaryl-coenzyme A reductase. Whether statins can benefit patients with dementia remains unclear because of conflicting results. We hypothesized that some of the confusion in the literature might arise from differences in efficacy of different statins. We used a large database to compare the action of several different statins to investigate whether some statins might be differentially associated with a reduction in the incidence of dementia and Parkinson's disease.</p> <p>Methods</p> <p>We analyzed data from the decision support system of the US Veterans Affairs database, which contains diagnostic, medication and demographic information on 4.5 million subjects. The association of lovastatin, simvastatin and atorvastatin with dementia was examined with Cox proportional hazard models for subjects taking statins compared with subjects taking cardiovascular medications other than statins, after adjusting for covariates associated with dementia or Parkinson's disease.</p> <p>Results</p> <p>We observed that simvastatin is associated with a significant reduction in the incidence of dementia in subjects ≥65 years, using any of three models. The first model incorporated adjustment for age, the second model included adjusted for three known risk factors for dementia, hypertension, cardiovascular disease or diabetes, and the third model incorporated adjustment for the Charlson index, which is an index that provides a broad assessment of chronic disease. Data were obtained for over 700000 subjects taking simvastatin and over 50000 subjects taking atorvastatin who were aged >64 years. Using model 3, the hazard ratio for incident dementia for simvastatin and atorvastatin are 0.46 (CI 0.44–0.48, <it>p </it>< 0.0001) and 0.91 (CI 0.80–1.02, <it>p </it>= 0.11), respectively. Lovastatin was not associated with a reduction in the incidence of dementia. Simvastatin also exhibited a reduced hazard ratio for newly acquired Parkinson's disease (HR 0.51, CI 0.4–0.55, <it>p </it>< 0.0001).</p> <p>Conclusion</p> <p>Simvastatin is associated with a strong reduction in the incidence of dementia and Parkinson's disease, whereas atorvastatin is associated with a modest reduction in incident dementia and Parkinson's disease, which shows only a trend towards significance.</p

Hospitalisation for COPD in Puglia: the role of hospital discharge database to estimate prevalence and incidence

Background and aim. Chronic Obstructive Pulmonary Disease (COPD), although largely preventable, is a great health burden in all the countries worldwide. Statistics of morbidity and mortality of COPD show the need for correct management of the disease. Chronic Obstructive Respiratory Diseases (DRG 88) are in 9th place for discharge in in-patient hospital admission. It is necessary to establish specific indicators which are efficacious and relevant for the patient, the doctor and the health manager. This study will analyse the information in respect of hospital admissions (Hospital discharge database) in Puglia for the period 2000-2005. Methods. The analysis was carried out utilising the Puglia Region hospital patient discharge database, selecting those patients with admission for chronic respiratory disease as principal or secondary diagnosis. Results. Chronic respiratory diseases are more frequent in males and in people over 45 years old with frequency increasing with age. Geographical distribution shows that there are greater rates of hospitalisation in big cities and in the neighbourhood of industrial areas. Although the trend over time is slight. A higher percentage of re-admission has been found for patients with COPD, and the interval between the two admissions occurs within one or two months; the diagnosis at the second admission is the same as for the first. 10.6% of discharge forms report one diagnosis, especially in patients older than 65 years of age. Little could be said about diagnostic procedures because these are not reported on the discharge form. Conclusion. Hospitalisation data confirms expectations regarding age and sex of patients. The high hospitalisation rates indicate that in-patients care still remains the only viable treatment for COPD and other chronic respiratory diseases. The high number of exacerbations reflect the absence of out-patients service or community care, and the same diagnosis in more than one episode shows the lack of efficiency of health services and disease management. This data is necessary to understand disease distribution and the modification of disease management in order to reduce health care costs, to increase efficacy in disease control and to limit repeated exacerbation and so to obtain the maximum benefit for the patients

Diagnosis Code Assignment Using Sparsity-Based Disease Correlation Embedding

© 1989-2012 IEEE. With the latest developments in database technologies, it becomes easier to store the medical records of hospital patients from their first day of admission than was previously possible. In Intensive Care Units (ICU), modern medical information systems can record patient events in relational databases every second. Knowledge mining from these huge volumes of medical data is beneficial to both caregivers and patients. Given a set of electronic patient records, a system that effectively assigns the disease labels can facilitate medical database management and also benefit other researchers, e.g., pathologists. In this paper, we have proposed a framework to achieve that goal. Medical chart and note data of a patient are used to extract distinctive features. To encode patient features, we apply a Bag-of-Words encoding method for both chart and note data. We also propose a model that takes into account both global information and local correlations between diseases. Correlated diseases are characterized by a graph structure that is embedded in our sparsity-based framework. Our algorithm captures the disease relevance when labeling disease codes rather than making individual decision with respect to a specific disease. At the same time, the global optimal values are guaranteed by our proposed convex objective function. Extensive experiments have been conducted on a real-world large-scale ICU database. The evaluation results demonstrate that our method improves multi-label classification results by successfully incorporating disease correlations

Reassessing the impact of smoking on preeclampsia/eclampsia: Are there age and racial differences?

To investigate the association between cigarette use during pregnancy and pregnancy-induced hypertension/preeclampsia/eclampsia (PIH) by maternal race/ethnicity and age.This retrospective cohort study was based on the U.S. 2010 natality data. Our study sample included U.S. women who delivered singleton pregnancies between 20 and 44 weeks of gestation without major fetal anomalies in 2010 (n = 3,113,164). Multivariate logistic regression models were fit to estimate crude and adjusted odds ratios and the corresponding 95% confidence intervals.We observed that the association between maternal smoking and PIH varied by maternal race/ethnicity and age. Compared with non-smokers, reduced odds of PIH among pregnant smokers was only evident for non-Hispanic white and non-Hispanic American Indian women aged less than 35 years. Non-Hispanic Asian/Pacific Islander women who smoked during pregnancy had increased odds of PIH regardless of maternal age. Non-Hispanic white and non-Hispanic black women 35 years or older who smoked during pregnancy also had increased odds of PIH.Our study findings suggest important differences by maternal race/ethnicity and age in the association between cigarette use during pregnancy and PIH. More research is needed to establish the biologic and social mechanisms that might explain the variations with maternal age and race/ethnicity that were observed in our study