A Guide to Observable Differences in Stated Preference Evidence.

BACKGROUND AND OBJECTIVE: In health preference research, studies commonly hypothesize differences in parameters (i.e., differential or joint effects on attribute importance) and/or in choice predictions (marginal effects) by observable factors. Discrete choice experiments may be designed and conducted to test and estimate these observable differences. This guide covers how to explore and corroborate various observable differences in health preference evidence. METHODS: The analytical process has three steps: analyze the exploratory data, analyze the confirmatory data, and interpret and disseminate the evidence. In this guide, we demonstrate the process using dual samples (where exploratory and confirmatory samples were collected from different sources) on 2020 US COVID-19 vaccination preferences; however, investigators may apply the same approach using split samples (i.e., single source). RESULTS: The confirmatory analysis failed to reject ten of the 17 null hypotheses generated by the exploratory analysis (p < 0.05). Apart from demographic, socioeconomic, and geographic differences, political independents and persons who have never been vaccinated against influenza are among those least likely to be vaccinated (0.838 and 0.872, respectively). CONCLUSIONS: For all researchers in health preference research, it is essential to know how to identify and corroborate observable differences. Once mastered, this skill may lead to more complex analyses of latent differences (e.g., latent classes, random parameters). This guide concludes with six questions that researchers may ask themselves when conducting such analyses or reviewing published findings of observable differences.

Does the U.S. Navy's reliance on objective standards prevent discrimination in promotions and retentions?

To prevent discrimination, the U.S. Navy enlisted-personnel promotion process relies primarily on objective measures. However, it also uses the subjective opinion of a sailor's superior. The Navy's promotion and retention process involves two successive decisions: The Navy decides whether to promote an individual, and conditional on that decision, the sailor decides whether to stay. Using estimates of these correlated decision-making processes, we find that during 1997-2008, Blacks and Hispanics were less likely to be promoted than Whites, especially during wartime. The Navy's decision-making affects Blacks' differential promotion rates by twice as much as differences in the groups' characteristics. However, Nonwhite retention probabilities, even when not promoted, are higher than for Whites, in part because they have fewer opportunities in the civilian market. Females have lower promotion rates than males and slightly lower retention rates during wartime.

Modeling Preference and Willingness to Pay for Drought Tolerance (DT) in Maize in Rural Zimbabwe.

Maize plays a leading role in the food security of millions in southern Africa, yet it is highly vulnerable to the moisture stress brought about by the erratic rainfall patterns that characterize weather systems in the area. Developing and making drought-tolerant maize varieties available to farmers in the region has thus long been a key goal on the regional development agenda. Farm-level adoption of these varieties, however, depends on local perceptions of the value they add, along with willingness to pay (WTP) for it. Focusing on Zimbabwe, this research aimed at estimating the implicit prices farmers are willing to pay for drought tolerance in maize compared to other preferred traits. Using a choice experiment framework, we generated 12,600 observations from a random sample of 1,400 households in communal areas within 14 districts of Zimbabwe. Taste parameters and heterogeneities were estimated using the generalized multinomial logit model (G-MNL). The results reveal drought tolerance, grain yield, covered cob tip, cob size, and semi-flint texture to be the most preferred traits by farm households in Zimbabwe. The WTP estimates show that farmers are willing to pay a premium for drought tolerance equal to 2.56, 7, 3.2, and 5 times higher than for an additional ton of yield per acre, bigger cob size, larger grain size, and covered cob tip, respectively. We suggest designing and implementing innovative ways of promoting DT maize along with awareness-raising activities to enhance contextual understandings of drought and drought risk to speed adoption of new DT maize varieties by risk-prone farming communities. Given the high level of rural literacy and the high rate of adoption of improved maize, trait-based promotion and marketing of varieties constitutes the right strategy.

Exploring direct and indirect influences of physical work environment on job satisfaction for early-career registered nurses employed in hospitals.

We explored direct and indirect influences of physical work environment on job satisfaction in a nationally representative sample of 1,141 early-career registered nurses. In the fully specified model, physical work environment had a non-significant direct effect on job satisfaction. The path analysis used to test multiple indirect effects showed that physical work environment had a positive indirect effect (p < .05) on job satisfaction through ten variables: negative affectivity, variety, workgroup cohesion, nurse-physician relations, quantitative workload, organizational constraints, distributive justice, promotional opportunity, local and non-local job opportunities. The findings make important contributions to the understanding of the relationship between physical work environment and job satisfaction. The results can inform health care leaders' insight about how physical work environment influences nurses' job satisfaction.

Computation of standard errors.

OBJECTIVES: We discuss the problem of computing the standard errors of functions involving estimated parameters and provide the relevant computer code for three different computational approaches using two popular computer packages. STUDY DESIGN: We show how to compute the standard errors of several functions of interest: the predicted value of the dependent variable for a particular subject, and the effect of a change in an explanatory variable on the predicted value of the dependent variable for an individual subject and average effect for a sample of subjects. EMPIRICAL APPLICATION: Using a publicly available dataset, we explain three different methods of computing standard errors: the delta method, Krinsky­Robb, and bootstrapping. We provide computer code for Stata 12 and LIMDEP 10/NLOGIT 5. CONCLUSIONS: In most applications, choice of the computational method for standard errors of functions of estimated parameters is a matter of convenience. However, when computing standard errors of the sample average of functions that involve both estimated parameters and nonstochastic explanatory variables, it is important to consider the sources of variation in the function's values.

Increasing demands for quality measurement.

Measurement of health care quality and patient safety is rapidly evolving, in response to long-term needs and more recent efforts to reform the US health system around "value." Development and choice of quality measures is now guided by a national quality strategy and priorities, with a public-private partnership, the National Quality Forum, helping determine the most worthwhile measures for evaluating and rewarding quality and safety of patient care. Yet there remain a number of challenges, including diverse purposes for quality measurement, limited availability of true clinical measures leading to frequent reliance on claims data with its flaws in determining quality, fragmentation of measurement systems with redundancy and conflicting conclusions, few high-quality comprehensive measurement systems and registries, and rapid expansion of required measures with hundreds of measures straining resources. The proliferation of quality measures at the clinician, hospital, and insurer level has created challenges and logistical problems. Recommendations include raising the bar for qualtiy measurements to achieve transformational rather than incremental change in the US quality measurement system, promoting a logical set of measures for the various levels of the health system, leaving room for internal organizational improvement, harmonizing the various national and local quality measurement systems, anchoring on National Quality Forum additions and subtractions of measures to be applied, reducing reliance on and retiring claims-based measures as quickly as possible, promoting comprehensive measurement such as through registries with deep understanding of patient risk factors and outcomes, reducing attention to proprietary report cards, prompt but careful transition to measures from electronic health records, and allocation of sufficient resources to accomplish the goals of an efficient, properly focused measurement system.

A multidisciplinary approach to reduce central line-associated bloodstream infections.

BACKGROUND: Stony Brook University Hospital (SBUH) joined a Critical Care Learning Collaborative in fall 2004. The collaborative incorporated application of central line and ventilator bundles, multidisciplinary rounding, and daily goal sheets to improve patient outcomes. In a two-year period, the initiative spread to the medical, pediatric, cardiac, and neonatal ICUs. METHODS: Despite some success, the goal of eliminating central line-associated bloodstream infections (CLABSIs) was not initially realized. In response, SBUH developed a standardized central line insertion credentialing program for residents. After further review of the residual central line infection data, it was evident that many of the lines became infected after day 7 of insertion. Evaluation of the line maintenance process revealed that nursing staff were not accessing the lines using the same level of sterile technique as used during insertion. As a result, a central line maintenance protocol was developed and deployed. RESULTS: After cumulative efforts were undertaken, SBUH's overall CLABSI rate decreased by 59% in a five-year period and by more than 80% in the most recent 12 months. CONCLUSIONS: A critical feature of the approach that SBUH followed was to establish buy-in and oversight from the SICU leadership through a multidisciplinary team, which became the "learning laboratory" for many of the subsequent changes in practice. Also, the fundamental role of the Continuous Quality Improvement (CQI) Department's quality management practitioner as facilitator cannot be overstated. "Hardwiring" of process changes augmented sustainability of improvements, as did a change in the health care team's perception of central line infections--that is, from an "unavoidable complication" to "a failure."

Translating frontiers into practice: taking the next steps toward improving hospital efficiency.

Frontier techniques, including data envelopment analysis (DEA) and stochastic frontier analysis (SFA), have been used to measure health care provider efficiency in hundreds of published studies. Although these methods have the potential to be useful to decision makers, their utility is limited by both methodological questions concerning their application, as well as some disconnect between the information they provide and the insight sought by decision makers. The articles in this special issue focus on the application of DEA and SFA to hospitals with the hope of making these techniques more accurate and accessible to end users. This introduction to the special issue highlights the importance of measuring the efficiency of health care providers, provides a background on frontier techniques, contains an overview of the articles in the special issue, and suggests a research agenda for DEA and SFA.

Registered nurse staffing mix and quality of care in nursing homes: a longitudinal analysis.

PURPOSE: To examine the relationship between registered nurse (RN) staffing mix and quality of nursing home care measured by regulatory violations. DESIGN AND METHODS: A retrospective panel data study (1999-2003) of 2 groups of California freestanding nursing homes. One group was 201 nursing homes that consistently met the state's minimum standard for total nurse staffing level over the 5-year period. The other was 210 nursing homes that consistently failed to meet the standard over the period. All facility and market variables were drawn from California's cost report data and state licensing and certification data, as well as 3 other databases. RESULTS: The RN to total nurse staffing ratio was negatively related to serious deficiencies in nursing homes that consistently met the staffing standard, whereas the ratio was negatively associated with total deficiencies in nursing homes that consistently failed to meet the standard over the 5-year period. As the RN to licensed vocational nurse ratios increased, total deficiencies and serious deficiencies decreased in both groups of nursing homes. IMPLICATIONS: A higher RN mix is positively related to quality of care, but the relationship is affected by overall nurse staffing levels in nursing homes. Further studies are necessary for a better understanding of RNs' unique contributions to the quality of care in nursing homes.

University HealthSystem Consortium quality performance benchmarking study of the insertion and care of central venous catheters.

We report data from an observational benchmarking study of adherence to recommended practices for insertion and maintenance of central venous catheters at a heterogeneous group of academic medical centers. These centers demonstrated a need for significant improvement in implementation and documentation of quality performance measures for the prevention of catheter-related bloodstream infections.