Observation "services" and observation "care"--one word can mean a world of difference.
Ontology highlight
ABSTRACT:
SUBMITTER: Venkatesh AK
PROVIDER: S-EPMC4239839 | biostudies-literature | 2014 Aug
REPOSITORIES: biostudies-literature
Publications
Observation "services" and observation "care"--one word can mean a world of difference.
Venkatesh Arjun K AK Suter Lisa G LG
Health services research 20140801 4
Similar Datasets
Project description:IntroductionThe use of observation units (OUs) following emergency departments (ED) visits as a model of care has increased exponentially in the last decade. About one-third of U.S. hospitals now have OUs within their facilities. While their use is associated with lower costs and comparable level of care compared to inpatient units, there is a wide variation in OUs characteristics and operational procedures. The objective of this research was to explore the variability in the initial costs of care of placing patients with non-specific chest pain in observation units (OUs) and the one-year outcomes.MethodsThe author retrospectively investigated medical insurance claims of 22,962 privately insured patients (2009-2011) admitted to 41 OUs. Outcomes included the one-year chest pain/cardiovascular related costs and primary and secondary outcomes. Primary outcomes included myocardial infarction, congestive heart failure, stroke or cardiac arrest, while secondary outcomes included revascularization procedures, ED revisits for angina pectoris or chest pain and hospitalization due to cardiovascular diseases. The author aggregated the adjusted costs and prevalence rates of outcomes for patients over OUs, and computed the weighted coefficients of variation (WCV) to compare variations across OUs.ResultsThere was minimal variability in the initial costs of care (WCV=2.2%), while the author noticed greater variability in the outcomes. Greater variability were associated with the adjusted cardiovascular-related costs of medical services (WCV=17.6%) followed by the adjusted prevalence odds ratio of patients experiencing primary outcomes (WCV=16.3%) and secondary outcomes (WCV=10%).ConclusionHigher variability in the outcomes suggests the need for more standardization of the observation services for chest pain patients.
| S-EPMC4427210 | biostudies-literature
Project description:Methods for random-effects meta-analysis require an estimate of the between-study variance, τ2 . The performance of estimators of τ2 (measured by bias and coverage) affects their usefulness in assessing heterogeneity of study-level effects and also the performance of related estimators of the overall effect. However, as we show, the performance of the methods varies widely among effect measures. For the effect measures mean difference (MD) and standardized MD (SMD), we use improved effect-measure-specific approximations to the expected value of Q for both MD and SMD to introduce two new methods of point estimation of τ2 for MD (Welch-type and corrected DerSimonian-Laird) and one WT interval method. We also introduce one point estimator and one interval estimator for τ2 in SMD. Extensive simulations compare our methods with four point estimators of τ2 (the popular methods of DerSimonian-Laird, restricted maximum likelihood, and Mandel and Paule, and the less-familiar method of Jackson) and four interval estimators for τ2 (profile likelihood, Q-profile, Biggerstaff and Jackson, and Jackson). We also study related point and interval estimators of the overall effect, including an estimator whose weights use only study-level sample sizes. We provide measure-specific recommendations from our comprehensive simulation study and discuss an example.
| S-EPMC6916299 | biostudies-literature
Project description:BackgroundObservation services are provided in greatly variant settings. The aim of this study was to reexamine the effectiveness of observation services compared to inpatient units for patients with nonspecific chest pain.HypothesisPatients admitted to observation units have similar outcomes to patients admitted to inpatient wards.MethodsWe conducted a claim-based retrospective study for 7549 patients who were admitted to observation and inpatient units. Both models of care were evaluated using the 1-year costs related to chest pain/cardiovascular diseases, and primary and secondary outcomes. Primary outcome was a composite of myocardial infarction, congestive heart failure, stroke, or cardiac arrest, whereas secondary outcomes included revascularization procedures, emergency room revisits, and hospitalization due to cardiovascular diseases.ResultsTwo-thirds (65.7%, n = 4962) of patients in the sample had observation services, and 34.3% (n = 2587) were admitted to inpatient care. Of the inpatient group, 4.9% experienced a total of 167 primary outcomes, whereas 14.1% experienced a total of 571 secondary outcomes. In comparison, 3.8% of the observation group experienced 238 primary outcomes, and 10.3% experienced 737 secondary outcomes. After adjusting for baseline characteristics using Cox proportional hazard and quantile regression models, no differences between the 2 groups were detected in the 1-year costs of cardiovascular services and primary or secondary outcomes. Patients who had observation services were 79% (95% confidence interval: 1.24-2.58) more likely to have revascularization procedures compared to those admitted to inpatient care.ConclusionsPatients who had observation services had similar outcomes and 1-year costs compared to patients admitted to inpatient wards.
| S-EPMC6649531 | biostudies-literature
Project description:This paper seeks to summarize the impact of the one-step International Association of Diabetes and Pregnancy Study Groups (IADPSG) versus the two-step gestational diabetes mellitus (GDM) criteria with regard to prevalence, outcomes, healthcare delivery, and long-term maternal metabolic risk.Studies demonstrate a 1.03-3.78-fold rise in the prevalence of GDM with IADPSG criteria versus baseline criteria. Women with GDM by IADPSG criteria have more adverse pregnancy outcomes than women with normal glucose tolerance (NGT). Treatment of GDM by IADPSG criteria may be cost effective. Use of the fasting glucose as a screen before the 75-g oral glucose tolerance test to rule out GDM with fasting plasma glucose (FPG) < 4.4 (80 mg/dl) and rule in GDM with FPG ≥ 5.1 mmol/l (92 mg/dl) reduces the need for OGTT by 50% and its cost and inconvenience. The prevalence of postpartum abnormal glucose metabolism is higher for women with GDM diagnosed by IADPSG criteria versus that for women with NGT. Data support the use of IADPSG criteria, if the cost of diagnosis and treatment can be controlled and if lifestyle can be optimized to reduce the risk of future diabetes.
| S-EPMC5552830 | biostudies-other
Project description:ObjectiveTo demonstrate regression to the mean bias introduced by matching on preperiod variables in difference-in-differences studies.Data sourcesSimulated data.Study designWe performed a Monte Carlo simulation to estimate the effect of a placebo intervention on simulated longitudinal data for units in treatment and control groups using unmatched and matched difference-in-differences analyses. We varied the preperiod level and trend differences between the treatment and control groups, and the serial correlation of the matching variables. We assessed estimator bias as the mean absolute deviation of estimated program effects from the true value of zero.Principal findingsWhen preperiod outcome level is correlated with treatment assignment, an unmatched analysis is unbiased, but matching units on preperiod outcome levels produces biased estimates. The bias increases with greater preperiod level differences and weaker serial correlation in the outcome. This problem extends to matching on preperiod level of a time-varying covariate. When treatment assignment is correlated with preperiod trend only, the unmatched analysis is biased, and matching units on preperiod level or trend does not introduce additional bias.ConclusionsResearchers should be aware of the threat of regression to the mean when constructing matched samples for difference-in-differences. We provide guidance on when to incorporate matching in this study design.
| S-EPMC6232412 | biostudies-literature
Project description:Meta-analyses of a treatment's effect compared with a control frequently calculate the meta-effect from standardized mean differences (SMDs). SMDs are usually estimated by Cohen's d or Hedges' g. Cohen's d divides the difference between sample means of a continuous response by the pooled standard deviation, but is subject to nonnegligible bias for small sample sizes. Hedges' g removes this bias with a correction factor. The current literature (including meta-analysis books and software packages) is confusingly inconsistent about methods for synthesizing SMDs, potentially making reproducibility a problem. Using conventional methods, the variance estimate of SMD is associated with the point estimate of SMD, so Hedges' g is not guaranteed to be unbiased in meta-analyses. This article comprehensively reviews and evaluates available methods for synthesizing SMDs. Their performance is compared using extensive simulation studies and analyses of actual datasets. We find that because of the intrinsic association between point estimates and standard errors, the usual version of Hedges' g can result in more biased meta-estimation than Cohen's d. We recommend using average-adjusted variance estimators to obtain an unbiased meta-estimate, and the Hartung-Knapp-Sidik-Jonkman method for accurate estimation of its confidence interval.
| S-EPMC7770064 | biostudies-literature
Project description: Not available
| S-EPMC6236467 | biostudies-literature
Project description: Not available
| S-EPMC8084725 | biostudies-literature
Project description:In randomized controlled trials (RCTs) with time-to-event outcomes, the difference in restricted mean survival times (RMSTD) offers an absolute measure of the treatment effect on the time scale. Computation of the RMSTD relies on the choice of a time horizon, $\tau$. In a meta-analysis, varying follow-up durations may lead to the exclusion of RCTs with follow-up shorter than $\tau$. We introduce an individual patient data multivariate meta-analysis model for RMSTD estimated at multiple time horizons. We derived the within-trial covariance for the RMSTD enabling the synthesis of all data by borrowing strength from multiple time points. In a simulation study covering 60 scenarios, we compared the statistical performance of the proposed method to that of two univariate meta-analysis models, based on available data at each time point and based on predictions from flexible parametric models. Our multivariate model yields smaller mean squared error over univariate methods at all time points. We illustrate the method with a meta-analysis of five RCTs comparing transcatheter aortic valve replacement (TAVR) with surgical replacement in patients with aortic stenosis. Over 12, 24, and 36 months of follow-up, those treated by TAVR live 0.28 [95% confidence interval (CI) 0.01 to 0.56], 0.46 (95% CI $-$0.08 to 1.01), and 0.79 (95% CI $-$0.43 to 2.02) months longer on average compared to those treated by surgery, respectively.
| S-EPMC7846118 | biostudies-literature