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1.  Impact of Specific Glucose-Control Strategies on Microvascular and Macrovascular Outcomes in 58,000 Adults With Type 2 Diabetes 
Diabetes Care  2013;36(11):3510-3516.
OBJECTIVE
Comparative effectiveness research methods are used to compare the effect of four distinct glucose-control strategies on subsequent myocardial infarction and nephropathy in type 2 diabetes.
RESEARCH DESIGN AND METHODS
A total of 58,000 adults with type 2 diabetes and A1C <7% (53 mmol/mol) while taking two or more oral agents or basal insulin had subsequent A1C ≥7% (53 mmol/mol) to 8.5% (69 mmol/mol). Follow-up started on date of first A1C ≥7% and ended on date of a specific clinical event, death, disenrollment, or study end. Glucose-control strategies were defined as first intensification of glucose-lowering therapy at A1C ≥7, ≥7.5, ≥8, or ≥8.5% with subsequent control for treatment adherence. Logistic marginal structural models were fitted to assess the discrete-time hazards for each dynamic glucose-control strategy, adjusting for baseline and time-dependent confounding and selection bias through inverse probability weighting.
RESULTS
After adjustment for age, sex, race/ethnicity, comorbidities, blood pressure, lipids, BMI, and other covariates, progressively more aggressive glucose-control strategies were associated with reduced onset or progression of albuminuria but not associated with significant reduction in occurrence of myocardial infarction or preserved renal function based on estimated glomerular filtration rate over 4 years of follow-up.
CONCLUSIONS
In a large representative cohort of adults with type 2 diabetes, more aggressive glucose-control strategies have mixed short-term effects on microvascular complications and do not reduce the myocardial infarction rate over 4 years of follow-up. These findings are consistent with the results of recent clinical trials, but confirmation over longer periods of observation is needed.
doi:10.2337/dc12-2675
PMCID: PMC3816858  PMID: 23877990
2.  A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research 
Pharmacoepidemiology and drug safety  2013;22(11):1139-1145.
This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias.
doi:10.1002/pds.3506
PMCID: PMC4190055  PMID: 24006330
covariate selection; confounding; comparative effectiveness research; propensity scores; backwards selection; stepwise selection; bias; nonexperimental methods
3.  Migraine prevalence, socioeconomic status, and social causation 
Neurology  2013;81(11):948-955.
Objective:
To determine whether the known higher prevalence of migraine in lower household (HH) income groups is explained by a higher incidence rate or a lower remission rate.
Methods:
We used data from the American Migraine Prevalence and Prevention Study, a US national sample of 132,674 females (with a 64.3% response rate) and 124,665 males (with a 62.0% response rate) 12 years of age and older. Data were previously collected on migraine symptoms, onset age, and demographics. Previously validated methods applied to the American Migraine Prevalence and Prevention Study data were used to simulate a cohort study. Incidence and remission rates were estimated within 3 sex-specific HH income groups (<$22,500, $22,500–$59,999, and ≥$60,000). The χ2 test was used to determine whether the incidence or remission rates differed by HH income group as an explanation for differences in migraine prevalence by HH income.
Results:
Migraine prevalence increased as HH income decreased for females (χ2, p < 0.01) and males (χ2, p < 0.01). Differences were not explained by race and other known confounders. Variation in prevalence was explained, in large part, by a higher incidence rate in the lower HH income groups for both females (χ2, p < 0.01) and males (χ2, p < 0.01). Migraine remission rates did not differ by HH income.
Conclusions:
The higher incidence of migraine in lower HH income groups is compatible with the social causation hypothesis. Once initiated, migraine remission is independent of HH income. Onset and remission may have etiologically distinct causes.
doi:10.1212/WNL.0b013e3182a43b32
PMCID: PMC3888198  PMID: 23990405
4.  Super learning to hedge against incorrect inference from arbitrary parametric assumptions in marginal structural modeling 
Journal of clinical epidemiology  2013;66(8 0):S99-S109.
Objective
Clinical trials are unlikely to ever be launched for many Comparative Effectiveness Research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called Super Learning to avoid reliance on arbitrary parametric assumptions in CER.
Study Design and Setting
Using the electronic health records data from adults with new onset type 2 diabetes, we implemented MSM with inverse probability weighting estimation to evaluate the effect of three oral anti-diabetic therapies on the worsening of glomerular filtration rate.
Results
Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, i.e., time-dependent measurements of hemoglobin A1c. Super Learning was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms.
Conclusion
Erroneous IPW inference about clinical effectiveness due to arbitrary and incorrect modeling decisions may be avoided with Super Learning.
doi:10.1016/j.jclinepi.2013.01.016
PMCID: PMC3713501  PMID: 23849160
super learning; marginal structural model; inverse probability weighting; comparative effectiveness research; time-dependent confounding; selection bias
5.  The Association of Health Literacy with Adherence and Outcomes in Moderate-Severe Asthma 
Background
Low health literacy is associated with poor outcomes in asthma and other diseases but the mechanisms governing this relationship are not well-defined.
Objective
To assess whether literacy is related to subsequent asthma self-management, measured as adherence to inhaled steroids, and asthma outcomes.
Methods
In a prospective longitudinal cohort study, numeric (Asthma Numeracy Questionnaire (ANQ)) and print literacy (Short Test of Functional Health Literacy in Adults (S-TOFHLA)) were assessed at baseline in adults with moderate or severe asthma for their impact on subsequent electronically monitored adherence and asthma outcomes (asthma control, asthma-related quality of life, and FEV1) over 26 weeks, using mixed-effects linear regression models.
Results
284 adults participated: 48±14 years, 71% female, 70% African American, 6% Latino, mean FEV1 66% ± 19%, 86 (30%) with hospitalizations and 148 (52%) with ED visits for asthma in the prior year. Mean ANQ score (range 0–4) was 2.3 ± 1.2; mean S-TOFHLA score 31 ± 8 (range 0–36). In unadjusted analyses numeric and print literacy were associated with better adherence (p=0.01, p=0.08), asthma control (p=0.005, p <0.001), and quality of life (p<0.001, p<0.001). After controlling for age, sex, and race/ethnicity, the associations diminished and only quality of life (numeric: p=0.03, print p=0.006) and asthma control (print p=0.005) remained significantly associated with literacy. Race/ethnicity, income, and educational attainment were correlated (p<0.001).
Conclusion
While the relationship between literacy and health is complex, interventions which account for and address the literacy needs of patients may improve asthma outcomes.
Clinical Implications/Key Summary
In adults with moderate or severe asthma, higher health literacy scores were associated with better subsequent quality of life and asthma control.
doi:10.1016/j.jaci.2013.02.014
PMCID: PMC3745278  PMID: 23591273
health literacy; numeracy; print literacy; asthma; adherence; adults; inner city asthma; inhaled corticosteroids; asthma-related quality of life; asthma control
6.  Feasibility, acceptability, and preliminary effectiveness of patient advocates for improving adult asthma outcomes 
Background
Asthmatic adults from low-income urban neighborhoods have inferior health outcomes which in part may be due to barriers accessing care and with patient-provider communication. We adapted a patient advocate (PA) intervention to overcome these barriers.
Objective
To conduct a pilot study to assess feasibility, acceptability, and preliminary evidence of effectiveness.
Methods
A prospective randomized design was employed with mixed methods evaluation. Adults with moderate or severe asthma were randomized to 16 weeks of PA or a minimal intervention (MI) comparison condition. The PA, a nonprofessional, modeled preparations for a medical visit, attended the visit, and confirmed understanding. The PA facilitated scheduling, obtaining insurance coverage, and overcoming barriers to implementing medical advice. Outcomes included electronically-monitored inhaled corticosteroid adherence, asthma control, quality of life, FEV1, ED visits, and hospitalizations. Mixed-effects models guided an intention-to-treat analysis.
Results
100 adults participated: age 47±14 years, 75% female, 71% African American, 16% white, baseline FEV1 69% ± 18%, 36% experiencing hospitalizations and 56% ED visits for asthma in the prior year. Ninety-three subjects completed all visits; 36 of 53 PA-assigned had a PA visit. Adherence declined significantly in the control (p= 0.001) but not significantly in the PA group (p=.30). Both PA and MI groups demonstrated improved asthma control (p=0.01 in both) and quality of life (p=0.001, p=0.004). Hospitalizations and ED visits for asthma did not differ between groups. The observed changes over time tended to favor the PA group, but this study was underpowered to detect differences between groups.
Conclusion
The PA intervention was feasible and acceptable and demonstrated potential for improving asthma control and quality of life.
doi:10.3109/02770903.2013.812655
PMCID: PMC4118639  PMID: 23800333
7.  Empiric Potassium Supplementation and Increased Survival in Users of Loop Diuretics 
PLoS ONE  2014;9(7):e102279.
Background
The effectiveness of the clinical strategy of empiric potassium supplementation in reducing the frequency of adverse clinical outcomes in patients receiving loop diuretics is unknown. We sought to examine the association between empiric potassium supplementation and 1) all-cause death and 2) outpatient-originating sudden cardiac death (SD) and ventricular arrhythmia (VA) among new starters of loop diuretics, stratified on initial loop diuretic dose.
Methods
We conducted a one-to-one propensity score-matched cohort study using 1999–2007 US Medicaid claims from five states. Empiric potassium supplementation was defined as a potassium prescription on the day of or the day after the initial loop diuretic prescription. Death, the primary outcome, was ascertained from the Social Security Administration Death Master File; SD/VA, the secondary outcome, from incident, first-listed emergency department or principal inpatient SD/VA discharge diagnoses (positive predictive value = 85%).
Results
We identified 654,060 persons who met eligibility criteria and initiated therapy with a loop diuretic, 27% of whom received empiric potassium supplementation (N = 179,436) and 73% of whom did not (N = 474,624). The matched hazard ratio for empiric potassium supplementation was 0.93 (95% confidence interval, 0.89–0.98, p = 0.003) for all-cause death. Stratifying on initial furosemide dose, hazard ratios for empiric potassium supplementation with furosemide <40 and ≥40 milligrams/day were 0.93 (0.86–1.00, p = 0.050) and 0.84 (0.79–0.89, p<0.0001). The matched hazard ratio for empiric potassium supplementation was 1.02 (0.83–1.24, p = 0.879) for SD/VA.
Conclusions
Empiric potassium supplementation upon initiation of a loop diuretic appears to be associated with improved survival, with a greater apparent benefit seen with higher diuretic dose. If confirmed, these findings support the use of empiric potassium supplementation upon initiation of a loop diuretic.
doi:10.1371/journal.pone.0102279
PMCID: PMC4100893  PMID: 25029519
8.  Severe Cutaneous Reactions requiring Hospitalization in Allopurinol Initiators: a Population-based Cohort Study 
Arthritis care & research  2013;65(4):578-584.
Background
Rare but potentially life-threatening cutaneous adverse reactions have been associated with allopurinol, but population-based data on incidence and mortality of such reactions is scarce.
Methods
We conducted a propensity score-matched cohort study to evaluate incidence rate (IR) and in-hospital mortality of hospitalization for severe cutaneous adverse reactions (SCARs) in allopurinol initiators compared to non-allopurinol users, using data from five large Medicaid programs. The primary outcome was identified by the principal discharge diagnosis code 695.1. Cox proportional hazards model evaluated the relative risk of SCARs associated with use of allopurinol and determined the relative risk of SCARs associated with allopurinol dose.
Results
During a follow-up period of 65,625 person-years for allopurinol initiators, 45 were hospitalized with SCARs. The crude IR was 0.69 (95% CI 0.50–0.92) per 1,000 person-years. All 45 cases occurred within 365 days and 41 (91.1%) within 180 days after initiating treatment with allopurinol. Twelve (26.7%) patients died during the hospitalization. The crude IR in non-allopurinol users was 0.04 (95% CI 0.02–0.08) per 1,000 person-years. The risk of SCARs was increased in allopurinol initiators vs. non-users (HR 9.67, 95% CI 4.55–20.57). Among allopurinol initiators, the HR for the high- (>300mg/day) vs. low-dose allopurinol was 1.30 (95% CI 0.31–5.36) after adjusting for age, comorbidities and recent diuretic use.
Conclusions
Among allopurinol initiators, SCARs were found to be rare but often fatal and occurred mostly in the first 180 days of treatment. The risk of SCARs was ten times as high in allopurinol initiators compared to allopurinol non-users.
doi:10.1002/acr.21817
PMCID: PMC3502684  PMID: 22899369
9.  Bayesian Inference for the Causal Effect of Mediation 
Biometrics  2012;68(4):1028-1036.
Summary
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects through a mediator in the setting of a continuous mediator and a binary response. Several conditional independence assumptions are introduced (with corresponding sensitivity parameters) to make these effects identifiable from the observed data. We suggest strategies for eliciting sensitivity parameters and conduct simulations to assess violations to the assumptions. This approach is used to assess mediation in a recent weight management clinical trial.
doi:10.1111/j.1541-0420.2012.01781.x
PMCID: PMC3927554  PMID: 23005030
10.  The Art versus Science of Predicting Prognosis: Can a Prognostic Index Predict Short-Term Mortality Better than Experienced Nurses Do? 
Journal of Palliative Medicine  2012;15(6):703-708.
Abstract
Objective
To determine whether a prognostic index could predict one-week mortality more accurately than hospice nurses can.
Method
An electronic health record-based retrospective cohort study of 21,074 hospice patients was conducted in three hospice programs in the Southeast, Northeast, and Midwest United States. Model development used logistic regression with bootstrapped confidence intervals and multiple imputation to account for missing data. The main outcome measure was mortality within 7 days of hospice enrollment.
Results
A total of 21,074 patients were admitted to hospice between October 1, 2008 and May 31, 2011, and 5562 (26.4%) died within 7 days. An optimal predictive model included the Palliative Performance Scale (PPS) score, admission from a hospital, and gender. The model had a c-statistic of 0.86 in the training sample and 0.84 in the validation sample, which was greater than that of nurses' predictions (0.72). The index's performance was best for patients with pulmonary disease (0.89) and worst for patients with cancer and dementia (both 0.80). The index's predictions of mortality rates in each index category were within 5.0% of actual rates, whereas nurses underestimated mortality by up to 18.9%. Using the optimal index threshold (<3), the index's predictions had a better c-statistic (0.78 versus 0.72) and higher sensitivity (74.4% versus 47.8%) than did nurses' predictions but a lower specificity (80.6% versus 95.1%).
Conclusions
Although nurses can often identify patients who will die within 7 days, a simple model based on available clinical information offers improved accuracy and could help to identify those patients who are at high risk for short-term mortality.
doi:10.1089/jpm.2011.0531
PMCID: PMC3409445  PMID: 22583382
11.  Primary Caregiver Characteristics and Transitions in Community-Based Care 
Objectives.
To identify informal primary caregiver characteristics associated with care transitions of community-dwelling older persons with impairments in daily living activities.
Method.
Data for this study were pooled to observe transitions from Wave 1–Wave 2 and Wave 2–Wave 3 of the Second Longitudinal Survey on Aging (LSOA II). The sample includes respondents with at least one impairment in daily living activities and with an informal caregiver at baseline of each transition period (n = 2,990). Primary caregiver transitions to another informal caregiver, to formal care, to a nursing home, or to no care were modeled using multinomial logistic regression.
Results.
More than half (54%) of the surviving respondents experienced a care transition for a period of 2 years. Multivariate results indicate that husband and son primary caregivers are more likely to transfer care than wives and daughters, although children caring for same-gender parents were less likely to transfer out of the primary caregiver role than children caring for parents of the opposite sex. Respondents with primary caregivers who are “other” relatives or nonrelatives, who are not coresident with the care receiver, or who are assisted by secondary helpers were at elevated risk for care transitions over the 2-year study period.
Discussion.
The results of this study suggest that older persons’ care transitions result from complex informal network dynamics, with primary caregiver gender and relationship to the care receiver playing key roles.
doi:10.1093/geronb/gbs032
PMCID: PMC3325088  PMID: 22492069
Caregiving; Community-based care; Disability
12.  The Effectiveness of CBT in 3–7 Year Old Anxious Children: Preliminary Data 
Introduction:
While CBT has been found to be an effective treatment for anxious older children, it has not been empirically validated in children younger than 8 years. In this study we report on an open pilot trial to establish whether a modified form of CBT can benefit young children.
Methods:
Participants were 37 anxious children aged 37–89 months attending a university anxiety specialty clinic. Symptom severity and functioning were assessed before and after treatment by independent evaluators. Feasibility and acceptability of the intervention were high. Parents attended part of each treatment session and were considered part of the treatment team.
Results:
Patients exhibited significant improvement from pre – to post-treatment assessments after an average of 8.3 treatment sessions, using the Strengths and Difficulties Questionnaire (SDQ) and the Global Assessment of Functioning Scale (GAF) ratings.
Conclusions:
A modified form of CBT with active parent involvement may be a useful tool in treating anxiety disorders in preschool and early school aged children.
PMCID: PMC2868557  PMID: 20467547
anxiety; preschool; CBT; anxiété; âge préscolaire; TCC
13.  Risk Factors for Umbilical Venous Catheter-Associated Thrombosis in Very Low Birth Weight Infants 
Pediatric blood & cancer  2009;52(1):75-79.
Background
Thrombosis in neonates is a rare but serious occurrence, usually associated with central catheterization. The objective of this study was to investigate the risk factors associated with catheter related thrombosis in very low birth weight (VLBW) infants.
Procedure
The present retrospective study was performed using data from a randomized trial of duration of umbilical venous catheters (UVC) placement among infants <1250 g birth weight. Twenty-two cases of UVC-associated thrombosis were identified in this sample. The remaining study sample (n=188) served as the comparison group. Data on thrombosis, platelets, gestational age, birth weight, hematocrit, serum sodium, maternal preeclampsia, blood group, infant of diabetic mother and demographic factors were collected using database and record review.
Results
Among the total subjects (n=210), 112 (53%) were males and 126 (60%) were Caucasians, with mean gestational age of 27.7 ± 2.1 weeks (standard deviation) and mean birth weight of 923 ± 195 grams. Bivariate analysis revealed significant association of thrombosis with hematocrit >55% in the first week (odds ratio [OR] 5.4; 95% confidence interval [CI] 2.0-14.6; p=0.0003), being small for gestational age (OR, 2.9; 95% CI, 1.2-7.4; p=0.02) and maternal preeclampsia (OR, 3.97; 95% CI, 1.6-9.84; p=0.0017). In multivariate logistic regression analysis, only hematocrit >55% was independently associated with thrombus (OR, 3.7; 95% CI 1.1-11.8; p=0.03).
Conclusions
This study demonstrates a significant, independent association between elevated hematocrit and development of UVC-associated thrombosis. Careful monitoring for catheter-associated thrombosis may be indicated in VLBW infants who have hematocrit >55% in the first week of life.
doi:10.1002/pbc.21714
PMCID: PMC2585148  PMID: 18680150
neonate; thrombosis; risk factors; umbilical venous catheters
14.  A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times 
Biometrics  2007;64(2):538-545.
Summary
In this article we consider the problem of fitting pattern mixture models to longitudinal data when there are many unique dropout times. We propose a marginally specified latent class pattern mixture model. The marginal mean is assumed to follow a generalized linear model, whereas the mean conditional on the latent class and random effects is specified separately. Because the dimension of the parameter vector of interest (the marginal regression coefficients) does not depend on the assumed number of latent classes, we propose to treat the number of latent classes as a random variable. We specify a prior distribution for the number of classes, and calculate (approximate) posterior model probabilities. In order to avoid the complications with implementing a fully Bayesian model, we propose a simple approximation to these posterior probabilities. The ideas are illustrated using data from a longitudinal study of depression in HIV-infected women.
doi:10.1111/j.1541-0420.2007.00884.x
PMCID: PMC2791415  PMID: 17900312
Bayesian model averaging; Incomplete data; Latent variable; Marginal model; Random effects
15.  The Quality of the Quality Indicator of Pain Derived from the Minimum Data Set 
Health Services Research  2005;40(4):1197-1216.
Objective
To examine facility variation in data quality of the level of pain documented in the minimum data set (MDS) as a function of level of hospice enrollment in nursing homes (NHs).
Data Source
Clinical assessments on 3,469 nonhospice residents from 178 NHs were merged with On-line Survey Certification and Reporting data of 2000, Medicare Claims data of 2000 and the MDS of 2000–2002.
Study Design
Using the same assessment protocol, NH staff and study nurses independently assessed 3,469 nonhospice residents. Study nurses' assessments being gold standard, we quantified and compared quality of NH staff's pain rating across NHs with high, medium, or low hospice use. Multilevel models were built to assess the effect of NH hospice use levels on the occurrence of false positive (FP) and false negative (FN) errors in NH-rated “severe pain.”
Principal Findings
Of 178 NHs, 25 had medium and 41 high hospice use. NHs with higher hospice use had lower sensitivities. In multilevel analysis, we found a significant facility-level variation in the probability of FP and FN errors in facility-rated “severe pain.” Resident characteristics only explained 4 and 0 percent of the facility variation in FP and FN, respectively; characteristics and locations (state) of NHs further explained 53 and 52 percent of the variance. After controlling for resident and NH characteristics, staff in NHs with medium or high hospice use were less likely to have FP or FN errors in their MDS documentation of pain than were staff in NHs with low or no hospice use.
Conclusions
The examination of data quality of pooled MDS data from multiple NHs is insufficient. Multilevel analysis is needed to elucidate sources of heterogeneity in the quality of MDS data across NHs. Facility characteristics, e.g., hospice use or NH location, are systematically associated with overrated/underrated pain and may bias pain quality indicator (QI) comparisons. To ensure the integrity of QI comparison in the NH setting, the government may need to institute regular audits of MDS data quality.
doi:10.1111/j.1475-6773.2005.00400.x
PMCID: PMC1361186  PMID: 16033500
Multilevel analysis; nursing home; minimum data set; pain; hospice; quality indicator; reliability
16.  Inter-rater reliability of nursing home quality indicators in the U.S 
Background
In the US, Quality Indicators (QI's) profiling and comparing the performance of hospitals, health plans, nursing homes and physicians are routinely published for consumer review. We report the results of the largest study of inter-rater reliability done on nursing home assessments which generate the data used to derive publicly reported nursing home quality indicators.
Methods
We sampled nursing homes in 6 states, selecting up to 30 residents per facility who were observed and assessed by research nurses on 100 clinical assessment elements contained in the Minimum Data Set (MDS) and compared these with the most recent assessment in the record done by facility nurses. Kappa statistics were generated for all data items and derived for 22 QI's over the entire sample and for each facility. Finally, facilities with many QI's with poor Kappa levels were compared to those with many QI's with excellent Kappa levels on selected characteristics.
Results
A total of 462 facilities in 6 states were approached and 219 agreed to participate, yielding a response rate of 47.4%. A total of 5758 residents were included in the inter-rater reliability analyses, around 27.5 per facility. Patients resembled the traditional nursing home resident, only 43.9% were continent of urine and only 25.2% were rated as likely to be discharged within the next 30 days.
Results of resident level comparative analyses reveal high inter-rater reliability levels (most items >.75). Using the research nurses as the "gold standard", we compared composite quality indicators based on their ratings with those based on facility nurses. All but two QI's have adequate Kappa levels and 4 QI's have average Kappa values in excess of .80. We found that 16% of participating facilities performed poorly (Kappa <.4) on more than 6 of the 22 QI's while 18% of facilities performed well (Kappa >.75) on 12 or more QI's. No facility characteristics were related to reliability of the data on which Qis are based.
Conclusion
While a few QI's being used for public reporting have limited reliability as measured in US nursing homes today, the vast majority of QI's are measured reliably across the majority of nursing facilities. Although information about the average facility is reliable, how the public can identify those facilities whose data can be trusted and whose cannot remains a challenge.
doi:10.1186/1472-6963-3-20
PMCID: PMC280691  PMID: 14596684

Results 1-16 (16)