Explore the vast range of titles available.

ABSTRACT BACKGROUND Suicide prevention is a public health priority, but no data on the health care individuals receive prior to death are available from large representative United States population samples. OBJECTIVE To investigate variation in the types and timing of health services received in the year prior to suicide, and determine whether a mental health condition was diagnosed. DESIGN Longitudinal study from 2000 to 2010 within eight Mental Health Research Network health care systems serving eight states. PARTICIPANTS In all, 5,894 individuals who died by suicide, and were health plan members in the year before death. MAIN MEASURES Health system contacts in the year before death. Medical record, insurance claim, and mortality records were linked via the Virtual Data Warehouse, a federated data system at each site. KEY RESULTS Nearly all individuals received health care in the year prior to death (83 %), but half did not have a mental health diagnosis. Only 24 % had a mental health diagnosis in the 4-week period prior to death. Medical specialty and primary care visits without a mental health diagnosis were the most common visit types. The individuals more likely to make a visit in the year prior to death ( p  < 0.05) tended to be women, individuals of older age (65+ years), those where the neighborhood income was over $40,000 and 25 % were college graduates, and those who died by non-violent means. CONCLUSIONS This study indicates that opportunities for suicide prevention exist in primary care and medical settings, where most individuals receive services prior to death. Efforts may target improved identification of mental illness and suicidal ideation, as a large proportion may remain undiagnosed at death.

Andrey Rzhetsky and colleagues analyze electronic medical records from over one-third of the US population to estimate disease heritability and to determine the genetic and environmental contributions to disease variance. They obtain 84 new heritability estimates and find that the genetic correlation values for disease pairs differ from their environmental correlation values. In this study, we used insurance claims for over one-third of the entire US population to create a subset of 128,989 families (481,657 unique individuals). We then used these data to (i) estimate the heritability and familial environmental patterns of 149 diseases and (ii) infer the genetic and environmental correlations for disease pairs from a set of 29 complex diseases. The majority (52 of 65) of our study's heritability estimates matched earlier reports, and 84 of our estimates appear to have been obtained for the first time. We used correlation matrices to compute environmental and genetic disease classifications and corresponding reliability measures. Among unexpected observations, we found that migraine, typically classified as a disease of the central nervous system, appeared to be most genetically similar to irritable bowel syndrome and most environmentally similar to cystitis and urethritis, all of which are inflammatory diseases.

The identification of death is critical for epidemiological research. Despite recent developments in health insurance claims databases, the quality of death information in claims is not guaranteed because health insurance claims are collected primarily for reimbursement. We aimed to examine the usefulness and limitations of death information in claims data and to examine methods for improving the quality of death information for aged persons. We used health insurance claims data and enrollment data (as the gold standard) from September 2012 through August 2015 for nondependent persons aged 65–74 years enrolled in Japanese workplace health insurance. Overall, 3,710,538 insured persons were registered in the database during the study period. We analyzed 45,441 eligible persons. Inpatient and outpatient deaths were identified from the discharge/disease status in the claims, with sensitivities of 94.3% and 47.4%, specificities of 98.5% and 99.9%, and PPVs of 96.3% and 95.7%, respectively, using enrollment data as the gold standard. For outpatients, death defined as a combination of disease status and charge data for terminal care still indicated low sensitivity (54.7%). The validity of death information in inpatient claims was high, suggesting its potential usefulness for identifying death. However, given the low sensitivity for outpatient deaths, the use of death information obtained solely from records in outpatient claims is not recommended.

ObjectivesTo investigate oral antibiotic prescribing patterns and identify factors associated with antibiotic prescriptions, with the aim of guiding future interventions to reduce inappropriate prescribing.DesignRetrospective cohort study.SettingDatabase of public health insurance claims in Kumamoto prefecture (Japan).ParticipantsBeneficiaries of the national or late elders’ health insurance system between April 2012 and March 2013.Main outcome measuresOf the 7 770 481 outpatient visits, 682 822 had a code for antibiotics (860 antibiotic prescriptions per 1000 population). Third-generation cephalosporins (35%), macrolides (32%) and quinolones (21%) were the most frequently prescribed. Acute respiratory tract infections (ARTIs), including viral upper respiratory infections (URI) (22%), pharyngitis (18%), bronchitis (11%) and sinusitis (10%) were the most frequently diagnosed for antibiotic prescribing, followed by gastrointestinal (9%), urinary tract (8%) and skin, cutaneous and mucosal infections (5%). Antibiotic prescribing rates for viral URI, pharyngitis, bronchitis, sinusitis and gastrointestinal infections were 35%, 54%, 53%, 57% and 30%, respectively. In multivariable analysis for ARTIs and gastrointestinal infections, patient age (10–19 years especially), patient sex (male) and facility scale (free-standing clinics or small-scale hospital-based clinics) were associated with increased antibiotic prescribing.ConclusionsBroad-spectrum antibiotics constituted 88% of oral outpatient antibiotic prescriptions. Approximately 70% of antibiotics were prescribed for ARTIs and gastroenteritis with modest benefit from antibiotic treatment. The quality of antibiotic prescribing needs to be improved. Antimicrobial stewardship interventions should target ARTIs and gastroenteritis, as well as young patients and small-scale institutions.

Rationale: Moving patients from low-performing hospitals to highperforming hospitals may improve patient outcomes. These transfers may be particularly important in critical care, where small relative improvements can yield substantial absolute changes in survival. Objective: To characterize the existing critical care network in terms of the pattern of transfers. Methods: In a retrospective cohort study, the nationwide 2005 Medicare fee-for-service claims were used to identify the interhospital transfer of critically ill patients, defined as instances where patients used critical care services in 2 temporally adjacent hospitalizations. Measurements: We measured the characteristics of the interhospital transfer network and the extent to which intensive care unit patients are referred to each hospital in that network--a continuous quantitative measure at the hospital- level known as centrality. We evaluated associations between hospital centrality and organizational, medical, surgical, and radiologic capabilities. Results: There were 47,820 transfers of critically ill patients among 3308 hospitals. 4.5% of all critical care stays of any length involved an interhospital critical care transfer. Hospitals transferred out to a mean of 4.4 other hospitals. More central hospital positions were associated with multiple indicators of increased capability. Hospital characteristics explained 40.7% of the variance in hospitals' centrality. Conclusions: Critical care transfers are common, and traverse an informal but structured network. The centrality of a hospital is associated with increased capability in delivery of services, suggesting that existing transfers generally direct patients toward better resourced hospitals. Studies of this network promise further improvements in patient outcomes and efficiency of care.

Using interrupted time-series analysis and National Health Insurance data between January 2000 and August 2003, this study assessed the impacts of the severe acute respiratory syndrome (SARS) epidemic on medical service utilization in Taiwan. At the peak of the SARS epidemic, significant reductions in ambulatory care (23.9%), inpatient care (35.2%), and dental care (16.7%) were observed. People’s fears of SARS appear to have had strong impacts on access to care. Adverse health outcomes resulting from accessibility barriers posed by the fear of SARS should not be overlooked.

Background Overuse is a leading contributor to the high cost of health care in the United States. Overuse harms patients and is a definitive waste of resources. The Johns Hopkins Overuse Index (JHOI) is a normalized measure of systemic health care services overuse, generated from claims data, that has been used to describe overuse in Medicare beneficiaries and to understand drivers of overuse. We aimed to adapt the JHOI for application to a commercially insured US population, to examine geographic variation in systemic overuse in this population, and to analyze trends over time to inform whether systemic overuse is an enduring problem. Methods We analyzed commercial insurance claims from 18 to 64 year old beneficiaries. We calculated a semiannual JHOI for each of the 375 Metropolitan Statistical Areas and 47 rural regions of the US. We generated maps to examine geographic variation and then analyzed each region’s change in their JHOI quintile from January 2011 to June 2015. Results The JHOI varied markedly across the US. Across the country, rural regions tended to have less systemic overuse than their MSA counterparts ( p  < 0.01). Regional systemic overuse is positively correlated from one time period to the next ( p  < 0.001). Between 2011 and 2015, 53.7% ( N  = 226) of regions remained in the same quintile of the JHOI. Eighty of these regions had a persistently high or persistently low JHOI throughout study duration. Conclusions The systemic overuse of health care resources is an enduring, regional problem. Areas identified as having a persistently high rate of systemic overuse merit further investigation to understand drivers and potential points of intervention.

To permit research that could improve health care system functioning, some states have established all-payer claims databases. Though a March 2016 Supreme Court decision prohibited state-mandated reporting from self-insured employer plans, it suggested a path forward. Health care spending is approaching 20% of the U.S. gross domestic product, yet spending on research to improve the functioning of the health care system has been limited. What is worse, we generally lack a unified source of data to study all persons and the services they receive. Medicare data are national in scope but are limited primarily to people over age 65 and are not representative of behaviors or spending for the commercially insured. 1 Furthermore, since Medicare’s prices are set administratively, its data cannot be used to study issues such as market power and competition. Data from commercial health . . .

BACKGROUND:Overuse can be defined as use of a service when the risk of harm exceeds its likely benefit. Yet, there has been little work with composite measures of overuse. OBJECTIVE:Our goal was to create a composite measure of overuse with claims data. DESIGN:Observational study using 5% of Medicare claims from 2008. SETTING:All inpatient and outpatient settings of care, excluding nursing homes. PARTICIPANTS:Older Americans receiving health care services in hospitals or outpatient settings. MEASURES:We applied algorithms to identify specific cases of overuse across 20 previously identified procedures and used multilevel modeling techniques to examine variation in overuse across all procedures. Included in the model were patient-level factors and both procedure and regional fixed effects for the 306 hospital referral regions (HRR). These estimated regional fixed effects, representing the systematic, region variation in overuse across all measures, was then normalized compared with the overall average to generate a Z score for each HRR. The resulting “Overuse Index” was then compared with total costs, 30-day postdischarge mortality, and total mortality at the HRR level, graphically, and associations were tested using Spearman ρ. RESULTS:The Overuse Index varied markedly across regions, but 23 were higher than the average (P<0.05). The Index was positively associated with total costs (ρ=0.28, P<0.0001). It was positively correlated with 30-day postdischarge mortality (ρ=0.18 P≤0.005), and neither positively or negatively correlated with total mortality. CONCLUSIONS:This study confirms previous research hypothesizing that systematic regional variation in overuse exists and is measurable. Addition research is needed to validate index and to test its predictive and concurrent validity in panel data.

Medication nonadherence is a common precipitant of heart failure (HF) hospitalization and is associated with poor outcomes. Recent analyses of national data focus on long-term medication adherence. Little is known about adherence of patients with HF immediately after hospitalization. Hospitalized patients with HF were identified from the Atherosclerosis Risk in Communities study. Atherosclerosis Risk in Communities data were linked to Medicare inpatient and part D claims from 2006 to 2009. Inclusion criteria were a chart-adjudicated diagnosis of acute decompensated or chronic HF; documentation of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB), β blocker (BB), or diuretic prescription at discharge; and Medicare part D coverage. Proportion of ambulatory days covered was calculated for up to twelve 30-day periods after discharge. Adherence was defined as ≥80% proportion of ambulatory days covered. We identified 402 participants with Medicare part D: mean age 75, 30% men, and 41% black. Adherence at 1, 3, and 12 months was 70%, 61%, and 53% for ACEI/ARB; 76%, 66%, and 62% for BB; and 75%, 68%, and 59% for diuretic. Adherence to any single drug class was positively correlated with being adherent to other classes. Adherence varied by geographic site/race for ACEI/ARB and BB but not diuretics. In conclusion, despite having part D coverage, medication adherence after discharge for all 3 medication classes decreases over 2 to 4 months after discharge, followed by a plateau over the subsequent year. Interventions should focus on early and sustained adherence.