Nonresponse Bias Analysis Research Articles

Advancing towards sustainable and net-zero supply chains: a comprehensive analysis of knowledge capabilities and industry dynamism

Purpose This research aims to investigate the relationship between knowledge capabilities, engagement capabilities, operational capabilities and sustainable supply chain flexibility in the steel production industry. In addition, it seeks to understand how these elements contribute toward achieving a net-zero supply chain, under the moderation of industry dynamism. Design/methodology/approach In total, 371 people have responded to the self-administered survey that the authors developed. The nonresponse bias analysis was carried out before diving into fundamental assumptions, such as homoscedasticity and normality. The data's reliability and construct validity were assessed by using confirmatory factor analysis. The hypothesized conclusions were supported by subsequent regression outputs, strengthening the body of existing academic research. Findings The research's empirical results highlight the positive relationship among knowledge capabilities, operational capabilities, sustainable supply chain flexibility and net-zero supply chain, particularly under the influence of industry dynamism. Information obtained from the steel production industry corroborates these findings. Moderation role of industry dynamism in the relationship between operational capabilities, engagement capability and sustainable supply chain flexibility was found significant. Originality/value This conceptual framework clarifies how knowledge capability, dynamic capabilities and the flexibility of a sustainable supply chain interact. It highlights how these factors collectively work together to attain a sustainable supply chain with net-zero environmental impact.

Wheeling towards sustainability: the nexus of external pressures, green innovation and circular supply chain excellence

PurposeThe study aims to investigate the firm reaction to external pressures and the subsequent transformation to green innovation (GI) and sustainability, leading to an enhanced circular supply chain performance. The research examined the effect of coercive, normative and mimetic pressures on GI within the Indian tire industry context.Design/methodology/approachThe authors have designed a self-administered questionnaire and received 283 responses. Nonresponse bias analysis was conducted first before proceeding to other assumptions such as constant variance and normality. The confirmatory factor analysis was used to check the data’s integrity and reliability. The PLS-structural equation modeling (SEM) is used to validate the constructs and test the established hypotheses.FindingsExternal regulatory pressures significantly impact the tire industry’s move towards GI. Normative pressures from societal expectations and industry standards, along with mimetic pressures where companies emulate best practices, both drive the industry toward sustainable initiatives. Further, a clear positive relationship emerges between GI and sustainable supply chain practices (SSCP). This shift emphasizes recycling, reusing and reducing waste and showcases the industry’s commitment to minimizing its environmental impact.Originality/valueUnlike existing literature that predominantly explores SSCP, the study introduces an integrated framework that intertwines institutional pressures (IP), green innovation (GI), and SSCP to elevate circular supply chain practices (CSCP). The current study highlights the relationships and practical implications within the Indian tire industry.

Impact of information system flexibility and dynamic capabilities in building net zero supply chains

PurposeThe main aim of this study is to explore the relationship between information system flexibility and dynamic capabilities to build sustainable and net zero supply chains under the influence of environmental dynamism.Design/methodology/approachWe have formulated a self-administered survey, with 359 participants contributing responses. Prior to delving into foundational assumptions, such as homoscedasticity and normality, a nonresponse bias analysis was executed. The integrity of the data, in terms of reliability and construct validity, was gauged using confirmatory factor analysis. Subsequent regression outputs corroborated all the proposed assumptions, fortifying the extant scholarly literature.FindingsThe empirical findings of this research underscore a positive correlation between Information system flexibility, dynamic capabilities and a net zero supply chain, especially in the context of environmental dynamism. Data sourced from the cement manufacturing sector support these observations. We also found that environmental dynamism moderates the relationship between data analytics capability and sustainable supply chain flexibility but does not moderate the relationship between Resource flexibility and sustainable supply chain flexibility. Additionally, this research strengthens the foundational principles of the dynamic capability theory.Originality/valueThe conceptual framework elucidates the interplay between information system flexibility, dynamic capabilities, and sustainable supply chain flexibility, emphasizing their collective contribution towards achieving sustainable chain net zero, introducing environmental dynamics as a moderating variable that augments the scholarly discourse with a nuanced layer of analytical depth.

Nonresponse Bias Analysis in Longitudinal Studies: A Comparative Review with an Application to the Early Childhood Longitudinal Study

SummaryLongitudinal studies are subject to nonresponse when individuals fail to provide data for entire waves or particular questions of the survey. We compare approaches to nonresponse bias analysis (NRBA) in longitudinal studies and illustrate them on the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (ECLS‐K:2011). Wave nonresponse with attrition often yields a monotone missingness pattern, and the missingness mechanism can be missing at random (MAR) or missing not at random (MNAR). We discuss weighting, multiple imputation (MI), incomplete data modelling and Bayesian approaches to NRBA for monotone patterns. Weighting adjustments can be effective when the constructed weights are correlated with the survey outcome of interest. MI allows for variables with missing values to be included in the imputation model, yielding potentially less biased and more efficient estimates. We add offsets in the MAR results to provide sensitivity analyses to assess MNAR deviations. We conduct NRBA for descriptive summaries and analytic model estimates in the ECLS‐K:2011 application. The strength of evidence about our NRBA depends on the strength of the relationship between the fully observed variables and the key survey outcomes, so the key to a successful NRBA is to include strong predictors.

Empirical analysis of key operational characteristics of lean six sigma and Industry 4.0 integration

PurposeTo achieve changing customer demands, organizations are striving hard to embrace cutting-edge technologies facilitating a high level of customization. Industry 4.0 (I4.0) implementation aids in handling big data that could help generate customized products. Lean six sigma (LSS) depends on data analysis to execute complex problems. Hence, the present study aims to empirically examine the key operational characteristics of LSS and I4.0 integration such as principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 technologies and performance measures.Design/methodology/approachTo stay competitive in the market and quickly respond to market demands, industries need to go ahead with digital transformation. I4.0 enables building intelligent factories by creating smart manufacturing systems comprising machines, operators and information and communication technologies through the complete value chain. This study utilizes an online survey on Operational Excellence professionals (Lean/Six Sigma), Managers/Consultants, Managing Directors/Executive Directors, Specialists/Analysts/Engineers, CEO/COO/CIO, SVP/VP/AVP, Industry 4.0 professionals and others working in the field of I4.0 and LSS. In total, 83 respondents participated in the study.FindingsBased on the responses received, reliability, exploratory factor analysis and non-response bias analysis were carried out to understand the biasness of the responses. Further, the top five operational characteristics were reported for LSS and I4.0 integration.Research limitations/implicationsOne of the limitations of the study is the sample size. Since I4.0 is a new concept and its integration with LSS is not yet explored; it was difficult to achieve a large sample size.Practical implicationsOrganizations can utilize the study findings to realize the top principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 tools and performance measures with respect to LSS and I4.0 integration. Moreover, these operational characteristics will help to assess the organization's readiness before and after the implementation of this integration.Originality/valueThe authors' original contribution is the empirical investigation of operational characteristics responsible for I4.0 and LSS integration.

Rationale, Procedures, and Response Rates for a Pilot Study to Sample Cancer Survivors for NCI’s Health Information National Trends Survey: HINTS-SEER 2021

The National Cancer Institute’s (NCI) Health Information National Trends Survey (HINTS) is a nationally representative survey of U.S. adults in which 12–17% of respondents report a cancer history. To increase representation from adult cancer survivors, in 2021, NCI sampled survivors from three Surveillance, Epidemiology, and End Results (SEER) program cancer registries: Iowa, New Mexico, and the Greater Bay Area. Sampling frames were stratified by time since diagnosis and race/ethnicity, with nonmalignant tumors and non-melanoma skin cancers excluded. Participants completed a self-administered postal questionnaire. The overall response rate for HINTS-SEER (N = 1,234) was 12.6%; a non-response bias analysis indicated few demographic differences between respondents and the pool of sampled patients in each registry. Most of the sample was 10+ years since diagnosis (n = 722; 60.2%); 392 respondents were 5 to < 10 years since diagnosis (29.6%); and 120 were < 5 years since diagnosis (10.2%). Common cancers included male reproductive (n = 304; 24.6%), female breast (n = 284; 23.0%), melanoma (n = 119; 9.6%), and gastrointestinal (n = 106; 8.6%). Tumors were mostly localized (67.8%; n = 833), with 22.4% (n = 282) regional, 6.2% (n = 72) distant, and 3.7% (n = 47) unknown. HINTS-SEER data are available by request and may be used for secondary analyses to examine a range of social, behavioral, and healthcare outcomes among cancer survivors.

Evolution of conflict management style during first year of paediatric residency.

First-year residents frequently encounter conflict during their training. Residents' conflict management strategies can influence patient safety, quality of care and perceptions of performance on competency evaluations. Existing literature inadequately describes how first-year resident conflict management styles evolve over time. The objective of this study is to assess if and how conflict management styles change during first year of paediatric residency in the United States. In 2021-2022, we conducted a non-experimental, longitudinal, survey study of first-year residents from 16 US-based paediatric residency programmes. Using the Thomas-Kilmann Conflict Mode Instrument, we scored first-year residents' use of five conflict management modes twice, 6 months apart. We calculated the percentage of first-year residents who experienced a change in predominant conflict management mode and assessed for changes in score and variance for each conflict management mode. Fifty-seven (18%) first-year residents participated in the first survey. Of those, 45 (14%) also completed the follow-up survey. Nonresponse bias analysis showed no significant difference in scores for early and late respondents or for second-survey respondents and non-respondents. Half of respondents experienced a change in predominant conflict management mode, but the distribution of predominant modes remained largely unchanged. When residents changed modes, they typically moved from one low-assertiveness mode, such as avoiding or accommodating, to the other. Only the use of the compromising conflict management mode significantly decreased. Variance did not significantly change. The overall lack of change in conflict management style may suggest the need for specific and focused educational interventions to help residents adjust their conflict handling strategies.

Interviewer-Observed Paradata in Mixed-Mode and Innovative Data Collection

In this research note, we address the potentials of using interviewer-observed paradata, typically collected during face-to-face-only interviews, in mixed-mode and innovative data collection methods that involve an interviewer at some stage (e.g., during the initial contact or during the interview). To this end, we first provide a systematic overview of the types and purposes of the interviewer-observed paradata most commonly collected in face-to-face interviews—contact form data, interviewer observations, and interviewer evaluations—using the methodology of evidence mapping. Based on selected studies, we illustrate the main purposes of interviewer-observed paradata we identified—including fieldwork management, propensity modeling, nonresponse bias analysis, substantive analysis, and survey data quality assessment. Based on this, we discuss the possible use of interviewer-observed paradata in mixed-mode and innovative data collection methods. We conclude with thoughts on new types of interviewer-observed paradata and the potential of combining paradata from different survey modes.

A Case Study of Nonresponse Bias Analysis in Educational Assessment Surveys

Nonresponse bias is a widely prevalent problem for data on education. We develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in cross-sectional studies and apply these steps to the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011. A key step is the construction of indices of nonresponse bias based on proxy pattern-mixture models for survey variables of interest. A novel feature is to characterize the strength of evidence about nonresponse bias contained in these indices, based on the strength of the relationship between the characteristics in the nonresponse adjustment and the key survey variables. Our NRBA improves the existing methods by incorporating both missing at random and missing not at random mechanisms, and all analyses can be done straightforwardly with standard statistical software.

Reporting quality of survey research articles published in the pharmacy literature

Survey research methodology is commonly used in the pharmacy literature and standards have been set forth for quality reporting. A systematic review to assess the reporting quality of survey research has only been completed for general medical literature. The objective of this study is to examine the quality of survey research reporting published in the pharmacy literature and identify reporting areas researchers can focus on for increased transparency in survey research methodology. A cross-sectional study of survey research articles published in seven key pharmacy journals in 2016 was conducted using a published 30-item checklist instrument designed for the reporting quality surveys. Each article was evaluated by two independent study investigators and assigned a final score out of 30. Out of 197 articles assessed for eligibility, 105 (53%) used survey research as the primary methodology and were included in the study. The average reporting score was 18.2±3.0 (range 10-25) out of 30, with the highest average scores reported for PharmacoEconomics (22.5), JMCP (20.4) and RSAP (19.8). Checklist items related to the quality of reporting survey research methodology with the highest compliance included: original reference cited for use of existing tools (100%), description of survey population and sample frame (90%); and reporting response rate (90%). Checklist items with low reporting included: psychometric properties for existing tools (14%); reliability and validity for new instruments (11%); analysis of nonresponse bias (8%); definition of complete versus partial responses (8%); methods of handling missing data (19%); and information about how non-respondents differ from respondents (14%). Survey research published in the pharmacy literature scored moderately on a published instrument designed for systematic appraisal of survey research reporting quality. Several areas for continued improvement exist for survey research reporting quality in the pharmacy literature.

Risk Adjustment, Mode Adjustment, and Nonresponse Bias Analysis on Quality Measures From a Long-Term Care Hospital Experience of Care Survey

ObjectivesTo develop a patient risk adjustment model for experience of care (EOC) quality measures for long-term care hospitals (LTCHs) that includes mode of survey administration. To assess presence of nonresponse bias in the adjusted facility-level scores. DesignWe tested 3 modes of collecting the EOC data: mail-only, mixed (ie, mail with telephone follow-up), and in-facility. This study used sequential modeling and impact analysis, specified a risk and mode adjustment model, and evaluated presence of nonresponse after adjustment. SettingLTCHs. ParticipantsPatients (N=1364) and 69 LTCHs. InterventionNot applicable. Main Outcome MeasuresRisk and mode adjusted responses to 28 survey questions and 6 facility-level scores derived from survey responses. ResultsMode of data collection and patient risk variables (age, sex, overall health, overall mental health, marital status, education, race, and whether a proxy responded) were included in the model. Clinical variables were not significant. The in-facility mode was associated with significantly higher performance scores than the other modes. When the recommended risk and mode adjustment model was applied, nonresponse bias was not observed in any mode. ConclusionsLTCH EOC data should be adjusted for patient risk variables including mode of data collection.

The Importance of Using Multiple Data Sources in Policy Assessments: Lessons From Two Conditional Cash Transfer Programs in New York City

The high costs of implementing surveys are increasingly leading research teams to either cut back on surveys or to rely on administrative records. Yet no policy should be based on a single set of estimates, and every approach has its weaknesses. A mixture of approaches, each with its own biases, should provide the analyst with a better understanding of the underlying phenomenon. This claim is illustrated with a comparison of employment effect estimates of two conditional cash transfer programs in New York City using survey and administrative unemployment insurance (UI) data. This article explores whether using administrative data and survey data produce different impact estimates and investigates the source of differential effects between data sources. The results of a survey nonresponse bias analysis and an analysis of characteristics of non-UI-covered job characteristics using data collected on 6,000 families who enrolled in either the Family Rewards or Work Rewards evaluation are presented. In both evaluations, survey data showed positive employment effects, while administrative data showed no statistically significant employment effects. Family Rewards increased employment mostly in non-UI-covered jobs, while the positive survey impact estimates in Work Rewards were partially due to survey nonresponse bias. Despite cost pressures leading researchers to collect and analyze only administrative records, the results suggest that survey and administrative records data both suffer from different kinds of sample attrition, and researchers may need to triangulate data sources to draw accurate conclusions about program effects. Developing more economical data collection practices is a major priority.

Accuracy of Internet-Based Patient Self-Report of Postdischarge Health Care Utilization and Complications Following Orthopedic Procedures: Observational Cohort Study.

BackgroundThe accuracy of patient self-report of health care utilization and complications has yet to be determined. If patients are accurate and engaged self-reporters, collecting this information in a manner that is temporally proximate to the health care utilization events themselves may prove valuable to health care organizations undertaking quality improvement initiatives for which such data are often unavailable.ObjectiveThe objective of this study was to measure the accuracy of patient self-report of health care utilization and complications in the 90 days following orthopedic procedures using an automated digital patient engagement platform.MethodsWe conducted a multicenter real-world observational cohort study across 10 orthopedic practices in California and Nevada. A total of 371 Anthem members with claims data meeting inclusion criteria who had undergone orthopedic procedures between March 1, 2015, and July 1, 2016, at participating practices already routinely using an automated digital patient engagement platform for asynchronous remote guidance and telemonitoring were sent surveys through the platform (in addition to the other materials being provided to them through the platform) regarding 90-day postencounter health care utilization and complications. Their self-reports to structured survey questions of health care utilization and complications were compared to claims data as a reference.ResultsThe mean age of the 371 survey recipients was 56.5 (SD 15.7) years, 48.8% (181/371) of whom were female; 285 individuals who responded to 1 or more survey questions had a mean age of 56.9 (SD 15.4) years and a 49.5% (141/285) female distribution. There were no significant differences in demographics or event prevalence rates between responders and nonresponders. With an overall survey completion rate of 76.8% (285/371), patients were found to have accuracy of self-report characterized by a kappa of 0.80 and agreement of 0.99 and a kappa of 1.00 and agreement of 1.00 for 90-day hospital admissions and pulmonary embolism, respectively. Accuracy of self-report of 90-day emergency room/urgent care visits and of surgical site infection were characterized by a kappa of 0.45 and agreement of 0.96 and a kappa of 0.53 and agreement of 0.97, respectively. Accuracy for other complications such as deep vein thrombosis, hemorrhage, severe constipation, and fracture/dislocation was lower, influenced by low event prevalence rates within our sample.ConclusionsIn this multicenter observational cohort study using an automated internet-based digital patient engagement platform, we found that patients were most accurate self-reporters of 90-day hospital admissions and pulmonary embolism, followed by 90-day surgical site infection and emergency room/urgent care visits. They were less accurate for deep vein thrombosis and least accurate for hemorrhage, severe constipation, and fracture/dislocation. A total of 76.8% (285/371) of patients completed surveys without the need for clinical staff to collect responses, suggesting the acceptability to patients of internet-based survey dissemination from and collection by clinical teams. While our methods enabled detection of events outside of index institutions, assessment of accuracy of self-report for presence and absence of events and nonresponse bias analysis, low event prevalence rates, particularly for several of the complications, limit the conclusions that may be drawn for some of the findings. Nevertheless, this investigation suggests the potential that engaging patients in self-report through such survey modalities may offer for the timely and accurate measurement of matters germane to health care organizations engaged in quality improvement efforts post discharge.

A Nonresponse Bias Analysis of the Health Information National Trends Survey (HINTS)

We conducted a nonresponse bias analysis of the Health Information National Trends Survey (HINTS) 4, Cycles 1 and 3, collected in 2011 and 2013, respectively, using three analysis methods: comparison of response rates for subgroups, comparison of estimates with weighting adjustments and external benchmarks, and level-of-effort analysis. Areas with higher concentrations of low socioeconomic status, higher concentrations of young households, and higher concentrations of minority and Hispanic populations had lower response rates. Estimates of health information seeking behavior were higher in HINTS compared to the National Health Interview Survey (NHIS). The HINTS estimate of doctors always explaining things in a way that the patient understands was not significantly different from the same estimate from the Medical Expenditure Panel Survey (MEPS); however, the HINTS estimate of health professionals always spending enough time with the patient was significantly lower than the same estimate from MEPS. A level-of-effort analysis found that those who respond later in the survey field period were less likely to have looked for information about health in the past 12 months, but found only small differences between early and late respondents for the majority of estimates examined. There is some evidence that estimates from HINTS could be biased toward finding higher levels of health information seeking.

Practitioner and Practice Characteristics of Certified Professional Midwives in the United States: Results of the 2011 North American Registry of Midwives Survey.

No data describing certified professional midwives (CPMs) currently exist in the literature, although CPMs attend the majority of home births in the United States. This study addresses this gap by assessing the demographics, education levels, routes to certification, and practice characteristics of currently practicing CPMs. Data were collected from a survey of CPMs conducted by the North American Registry of Midwives (NARM) between July and October 2011. In order to assess generalization to the entire population of practicing CPMs, we also completed a nonresponse bias analysis. We examined midwives' demographic, education, certification, and practice characteristics using descriptive and nonparametric, bivariable statistics. More than 90% of the 568 respondents attended at least some college, and 47.1% hold a bachelor's degree or greater. CPMs spent a median of 3 years (interquartile range, 2-5 years) in training before attending births as a primary midwife. However, 38.9% of currently practicing CPMs had less than 3 years of training. Regarding pathways to certification, 48.5% utilized the portfolio evaluation process (PEP); 36.9% graduated from a Midwifery Education and Accreditation Council (MEAC)-accredited school; 14.5% were already licensed by a state as a direct-entry midwife; and 0.7% were already a certified nurse-midwife or certified midwife, although many CPMs reported a blended education pathway. One-fifth (21%) of respondents identified as midwives of color. Whereas nearly one-third (31.8%) of CPM respondents reported that 95% or more of their clients were white, 5.2% serve populations that are 90% or more nonwhite. CPMs of color are significantly more likely to serve clients of color (P < .001). Training and nonmidwifery education levels of most CPMs practicing in the United States align with the Global Standards for Midwifery Education established by the International Confederation of Midwives, although there are still clear areas for improvement.

What we don't know can hurt us: Nonresponse bias assessment in birth defects research.

Nonresponse bias assessment is an important and underutilized tool in survey research to assess potential bias due to incomplete participation. This study illustrates a nonresponse bias sensitivity assessment using a survey on perceived barriers to care for children with orofacial clefts in North Carolina. Children born in North Carolina between 2001 and 2004 with an orofacial cleft were eligible for inclusion. Vital statistics data, including maternal and child characteristics, were available on all eligible subjects. Missing 'responses' from nonparticipants were imputed using assumptions based on the distribution of responses, survey method (mail or phone), and participant maternal demographics. Overall, 245 of 475 subjects (51.6%) responded to either a mail or phone survey. Cost as a barrier to care was reported by 25.0% of participants. When stratified by survey type, 28.3% of mail respondents and 17.2% of phone respondents reported cost as a barrier. Under various assumptions, the bias-adjusted estimated prevalence of cost as barrier to care ranged from 16.1% to 30.0%. Maternal age, education, race, and marital status at time of birth were not associated with subjects reporting cost as a barrier. As survey response rates continue to decline, the importance of assessing the potential impact of nonresponse bias has become more critical. Birth defects research is particularly conducive to nonresponse bias analysis, especially when birth defect registries and birth certificate records are used. Future birth defect studies which use population-based surveillance data and have incomplete participation could benefit from this type of nonresponse bias assessment. Birth Defects Research (Part A) 103:603-609, 2015. © 2015 Wiley Periodicals, Inc.

Abstract 373: Participation Rates, Process Monitoring, and Quality Improvement Among United States Cardiac Rehabilitation Programs: A National Survey

Background: Cardiac Rehabilitation (CR) is an effective but highly underutilized treatment for heart disease. Prior studies have demonstrated that the use of strategies such as systematic referral (as part of an order set that does not depend on physician initiative or memory, usually with an opt-out option), liaison facilitated referral (a specific staff member who discusses the program, encourages attendance, and facilitates referral), an early appointment (&lt; 2 weeks), and telephone appointment reminder calls can all improved enrollment rates. However, it is unclear how frequently these strategies are utilized across the United States, how often CR programs monitor their participation rates, and how often quality improvement (QI) projects designed to improve participation rates are performed. Methods: We surveyed all CR program directors in the American Association of Cardiovascular and Pulmonary Rehabilitation’s (AACVPR) database. We assessed basic program features, use of systematic referral, liaison facilitated referral, early appointments, and telephone reminder calls and QI projects. We also assessed self-reported referral, enrollment, and completion rates. Results: Response rate was 36% (290/812). Non-response bias analysis showed reasonable survey representativeness. Over the past 5 years, 49% of programs measured hospital referral, 21% office/clinic referral, 71% program enrollment, and 74% program completion rates. Self-reported rates (interquartile range) were 68 [32 to 90]% for hospital referral, 35 [15 to 60]% for office/clinic referral, 70[46 to 80]% for program enrollment, and 75[62 to 82]% for program completion. Programs reported utilizing a hospital-based systematic referral, liaison facilitated referral, or inpatient CR program 64%, 68%, and 60% of the time, respectively. Early appointments (&lt; 2 weeks) were utilized by 35% and consistent phone call appointment reminders were utilized by 50%. Over the past 5 years, the percent or programs performing QI projects were 62% for hospital referral, 42% for clinic referral, 60% for program enrollment, and 57% for program completion. Measurement of participation rates was highly correlated with performing QI projects (p &lt; 0.0001.) Conclusions: Although programs are aware of participation rate gaps, the monitoring of participation rates is suboptimal, quality improvement initiatives are infrequent, and proven strategies for increasing patient participation are inconsistently utilized. Awareness in outpatient clinical settings is particularly low. These issues likely contribute to the national CR participation gap and may prove to be useful targets for national QI initiatives.

Estimating the Effect of Nonresponse Bias in a Survey of Hospital Organizations

Nonresponse bias in survey research can result in misleading or inaccurate findings and assessment of nonresponse bias is advocated to determine response sample representativeness. Four methods of assessing nonresponse bias (analysis of known characteristics of a population, subsampling of nonresponders, wave analysis, and linear extrapolation) were applied to the results of a postal survey of U.K. hospital organizations. The purpose was to establish whether validated methods for assessing nonresponse bias at the individual level can be successfully applied to an organizational level survey. The aim of the initial survey was to investigate trends in the implementation of radiographer abnormality detection schemes, and a response rate of 63.7% (325/510) was achieved. This study identified conflicting trends in the outcomes of analysis of nonresponse bias between the different methods applied and we were unable to validate the continuum of resistance theory as applied to organizational survey data. Further work is required to ensure established nonresponse bias analysis approaches can be successfully applied to organizational survey data. Until then, it is suggested that a combination of methods should be used to enhance the rigor of survey analysis.

Is patient assessment of asthma care delivery associated with publicly reported performance measures?

Objective: To determine the association between patient assessment of healthcare delivery and publicly reported asthma performance measures. Methods: We identified individuals 5–50 years old who had asthma quality measures reported to the Minnesota Community Measurement© (MCM©) by their clinic and sent them a postal survey which included within it the Patient Assessment of Chronic Illness care (PACIC), a validated measure of patient perception of the quality of healthcare delivery. We performed a multivariable analysis to examine the association between PACIC scores and achievement of asthma care quality measures. Results: The response rate for the ACS was 102/367 (28%); a non-response bias analysis revealed no differences between responders and non-responders for age, gender and asthma control. Most responders (73%) reported taking asthma medications daily and most (71%) had poorly controlled asthma. The PACIC score was not associated with any of the asthma quality measures based on the data reported to MCM© by the clinic. A higher PACIC score was, however, associated with having an asthma action plan based on patient-reported data in the ACS (p < 0.0001) but not with patient-reported asthma control or emergency department/hospitalizations for asthma. Conclusions: Patient assessment of high quality asthma care delivery was associated with patient self-report of having an asthma action plan but was not associated with any of the publicly reported asthma performance measures.

The 2013 National Nursing Workforce Survey of Registered Nurses

The 2013 National Nursing Workforce Survey of Registered Nurses