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1.
    

Objectives

To model the steps involved in preparing for and carrying out propensity score analyses by providing step-by-step guidance and Stata code applied to an empirical dataset.

Study Design

Guidance, Stata code, and empirical examples are given to illustrate (1) the process of choosing variables to include in the propensity score; (2) balance of propensity score across treatment and comparison groups; (3) balance of covariates across treatment and comparison groups within blocks of the propensity score; (4) choice of matching and weighting strategies; (5) balance of covariates after matching or weighting the sample; and (6) interpretation of treatment effect estimates.

Empirical Application

We use data from the Palliative Care for Cancer Patients (PC4C) study, a multisite observational study of the effect of inpatient palliative care on patient health outcomes and health services use, to illustrate the development and use of a propensity score.

Conclusions

Propensity scores are one useful tool for accounting for observed differences between treated and comparison groups. Careful testing of propensity scores is required before using them to estimate treatment effects.  相似文献   

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Objective

To examine the impact of electronic health record (EHR) deployment on Surgical Care Improvement Project (SCIP) measures in a tertiary-care teaching hospital.

Data Sources

SCIP Core Measure dataset from the CMS Hospital Inpatient Quality Reporting Program (March 2010 to February 2012).

Study Design

One-group pre- and post-EHR logistic regression and difference-in-differences analyses.

Principal Findings

Statistically significant short-term declines in scores were observed for the composite, postoperative removal of urinary catheter and post–cardiac surgery glucose control measures. A statistically insignificant improvement in scores for these measures was noted 3 months after EHR deployment.

Conclusion

The transition to an EHR appears to be associated with a short-term decline in quality. Implementation strategies should be developed to preempt or minimize this initial decline.  相似文献   

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Objective

Health services research is a field of study that brings together experts from a wide variety of academic disciplines. It also is a field that places a high priority on empirical analysis. Many of the questions posed by health services researchers involve the effects of treatments, patient and provider characteristics, and policy interventions on outcomes of interest. These are causal questions. Yet many health services researchers have been trained in disciplines that are reluctant to use the language of causality, and the approaches to causal questions are discipline specific, often with little overlap. How did this situation arise? This paper traces the roots of the division and some recent attempts to remedy the situation.

Data Sources and Settings

Existing literature.

Study Design

Review of the literature.  相似文献   

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To evaluate the performance of different approaches for identifying live births using Transformed Medicaid Statistical Information System Analytic Files (TAF).  相似文献   

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Objective. Describe the evaluation performed of the patient safety initiative operated by the Agency for Healthcare Research and Quality (AHRQ).
AHRQ Patient Safety Initiative. When patient safety became a national priority in 2000, Congress charged and funded AHRQ to improve health care safety. Over the next 6 years, AHRQ funded more than 300 research projects and other activities, addressing diverse patient safety issues and practices.
The Patient Safety Evaluation. AHRQ contracted with RAND in 2002 to perform a 4-year evaluation of the initiative, which was completed in 2006. This formative evaluation used the CIPP program evaluation model, which emphasizes multiple stakeholders' interests (e.g., patients, providers, funded researchers). We monitored the progress of the patient safety initiative and provided AHRQ annual feedback that assessed each year's activities, identifying issues and offering suggestions for actions by AHRQ. Given the size and complexity of the initiative, the evaluation needed to examine key individual components and synthesize results across them, and it also had to be responsive to changes in the initiative over time. We used a conceptual framework to bring together the disparate pieces to synthesize overall findings. The remaining articles in this issue describe selected results from this evaluation.  相似文献   

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Objective: To describe the practical issues that need to be overcome to conduct national data linkage projects in Australia and propose recommendations to improve efficiency. Methods: Review of the processes, documentation and applications required to conduct national data linkage in Australia. Results: The establishment of state and national data linkage centres in Australia has placed Australia at the forefront of research linking health‐related administrative data collections. However, improvements are needed to reduce the clerical burden on researchers, simplify the process of obtaining ethics approval, improve data accessibility, and thus improve the efficiency of data linkage research. Conclusions: While a sound state and national data linkage infrastructure is in place, the current complexity, duplication and lack of cohesion undermines any attempts to conduct research involving national record linkage in a timely manner. Implications: Data linkage applications and Human Research Ethics Committee approval processes need to be streamlined and duplication removed, in order to reduce the administrative and financial burden on researchers if national data linkage research is to be viable.  相似文献   

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In many settings, an analysis goal is the identification of a factor, or set of factors associated with an event or outcome. Often, these associations are then used for inference and prediction. Unfortunately, in the big data era, the model building and exploration phases of analysis can be time‐consuming, especially if constrained by computing power (ie, a typical corporate workstation). To speed up this model development, we propose a novel subsampling scheme to enable rapid model exploration of clustered binary data using flexible yet complex model set‐ups (GLMMs with additive smoothing splines). By reframing the binary response prospective cohort study into a case‐control–type design, and using our knowledge of sampling fractions, we show one can approximate the model estimates as would be calculated from a full cohort analysis. This idea is extended to derive cluster‐specific sampling fractions and thereby incorporate cluster variation into an analysis. Importantly, we demonstrate that previously computationally prohibitive analyses can be conducted in a timely manner on a typical workstation. The approach is applied to analysing risk factors associated with adverse reactions relating to blood donation.  相似文献   

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In response to the poor performance of its public health care provision, Burkina Faso decided, to implement results‐based financing (RBF). This strategy relies on a strategic purchase of the quantity and quality of services provided by health workers, monitored by a set of indicators. However, there is a lack of evidence on its effects. The objective of this article is to appreciate the effect of RBF on a set of maternal and child health (MCH) indicators in Burkina Faso. The study design is quasi‐experimental comparative with a control group before and after the implementation of the RBF. To estimate the effect of RBF, we used two methods of analysis: (1) the segmented regression to measure the effect of RBF in the health districts (HD) implementing RBF (RBF HD) and (2) the difference‐in‐difference test to estimate the effect of RBF considering the differences in mean between RBF HD and HD that did not implement RBF (non–RBF HD). We found among five indicators studied that only the postnatal consultation coverage in RBF HD was significantly higher (7.68%; P = 0.04) than in the non–RBF HD. Overall, our findings do not clearly demonstrate the effectiveness of RBF in improving MCH indicators in Burkina Faso.  相似文献   

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Objective

The aim of the study was to estimate the effect of the state-based reinsurance programs through the section 1332 State Innovation Waivers on health insurance marketplace premiums and insurer participation.

Data Source

2015 to 2022 Robert Wood Johnson Foundation Health Insurance Exchange Compare Datasets.

Study Design

An event study difference-in-differences (DD) model separately for each year of implementation and a synthetic control method (SCM) are used to estimate year-by-year effects following program implementation.

Data Collection/Extraction Methods

Not applicable.

Principal Findings

Reinsurance programs were associated with a decline in premiums in the first year of implementation by 10%–13%, 5%–19%, and 11%–17% for bronze, silver, and gold plans (p < 0.05). There is a trend of sustained declines especially for states that implemented their programs in 2019 and 2020. The SCM analyses suggest some effect heterogeneity across states but also premium declines across most states. There is no evidence that reinsurance programs affected insurer participation.

Conclusion

State-based reinsurance programs have the potential to improve the affordability of health insurance coverage. However, reinsurance programs do not appear to have had an effect on insurer participation, highlighting the need for policy makers to consider complementary strategies to encourage insurer participation.  相似文献   

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Objective

Evaluate the accuracy of an algorithm at identifying ethnic minorities from administrative claims for enrollment into a clinical trial.

Data Sources/Study Setting

Claims data from a health benefits company.

Study Design

We compared results of a three-step algorithm to self-reported race/ethnicity.

Data Collection/Extraction Methods

Using the algorithm, we identified subjects with high probability of being minority and ascertained self-reported race/ethnicity.

Principal Findings

We identified 164 subjects as likely minority based on our algorithm. Of these, 94 completed the survey and 87 identified themselves as black or Hispanic. The positive predictive value of the algorithm was 93 percent (CI: 85–97).

Conclusions

Claims data can be used to efficiently identify minorities for participation in clinical trials.  相似文献   

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