Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization.

BACKGROUND AND PURPOSE: The Centers for Medicare & Medicaid Services publicly reports a hospital-level stroke mortality measure that lacks stroke severity risk adjustment. Our objective was to describe novel measures of stroke mortality suitable for public reporting that incorporate stroke severity into risk adjustment. METHODS: We linked data from the American Heart Association/American Stroke Association Get With The Guidelines-Stroke registry with Medicare fee-for-service claims data to develop the measures. We used logistic regression for variable selection in risk model development. We developed 3 risk-standardized mortality models for patients with acute ischemic stroke, all of which include the National Institutes of Health Stroke Scale score: one that includes other risk variables derived only from claims data (claims model); one that includes other risk variables derived from claims and clinical variables that could be obtained from electronic health record data (hybrid model); and one that includes other risk variables that could be derived only from electronic health record data (electronic health record model). RESULTS: The cohort used to develop and validate the risk models consisted of 188 975 hospital admissions at 1511 hospitals. The claims, hybrid, and electronic health record risk models included 20, 21, and 9 risk-adjustment variables, respectively; the C statistics were 0.81, 0.82, and 0.79, respectively (as compared with the current publicly reported model C statistic of 0.75); the risk-standardized mortality rates ranged from 10.7% to 19.0%, 10.7% to 19.1%, and 10.8% to 20.3%, respectively; the median risk-standardized mortality rate was 14.5% for all measures; and the odds of mortality for a high-mortality hospital (+1 SD) were 1.51, 1.52, and 1.52 times those for a low-mortality hospital (-1 SD), respectively. CONCLUSIONS: We developed 3 quality measures that demonstrate better discrimination than the Centers for Medicare & Medicaid Services' existing stroke mortality measure, adjust for stroke severity, and could be implemented in a variety of settings.

Accuracy of weight perception among urban early adolescents with uncontrolled asthma and their caregivers.

BACKGROUND: Obesity is associated with poor asthma outcomes; weight loss improves such outcomes. Inaccurate recognition of obesity may impede weight control. PURPOSE: We examined perception of weight by early adolescents with uncontrolled asthma and their caregivers, and tested the relationship between medical visit frequency and accuracy of perceived weight status. METHODS: A total of 373 adolescents and their caregivers reported the adolescent's height/weight and weight perception; caregivers reported healthcare utilization. We measured height/weight. Logistic regression modeled accuracy of weight perception. RESULTS: A total of 43.7 % of the overweight/obese adolescents and caregivers accurately perceived weight status. BMI percentile [odds ratio (OR) = 1.19, confidence interval (CI) = 1.10-1.28] and total medical visits (OR = 1.18, CI = 1.05-1.33) were associated with higher accuracy in caregivers. Total medical visits (OR = 0.84, CI = 0.74-0.96) was associated with lower accuracy in adolescents. CONCLUSIONS: Accurate perception of weight status was poor for overweight adolescents with uncontrolled asthma and their caregivers. Frequent medical visits were associated with improved caregivers' but not adolescents' perceptions.

Higher infant body fat with excessive gestational weight gain in overweight women.

OBJECTIVE: Gestational weight gain (GWG) is positively associated with birthweight and maternal prepregnancy body mass index (BMI) is directly related to infant fat mass (FM). This study examined whether differences exist in infant body composition based on 2009 GWG recommendations. STUDY DESIGN: Body composition was measured in 306 infants, and GWG was categorized as appropriate or excessive. Analysis of covariance was used to investigate the effects of GWG and prepregnancy BMI and their interaction on infant body composition. RESULTS: Within the appropriate group, infants from obese mothers had greater percent fat (%fat) and FM than offspring from normal and overweight mothers. Within the excessive group, infants from normal mothers had less %fat and FM than infants from overweight and obese mothers. A difference was found for %fat and FM within the overweight group between GWG categories. CONCLUSION: Excessive GWG is associated with greater infant body fat and the effect is greatest in overweight women.

Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models.

Importance: Present-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting. Objective: To assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS). Design, Setting, and Participants: This comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020. Main Outcomes and Measures: Changes in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment. Results: Data from a total of 6 027 988 index admissions were included for analysis, ranging from 491 366 admissions (269 209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1 395 870 admissions (677 158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure). Conclusions and Relevance: The findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients' risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.

Do self- or parent-reported dietary, physical activity, and sedentary behaviors predict worsening obesity in children?

OBJECTIVE: To determine whether information gathered during routine healthcare visits regarding obesity related risk factors and risk behaviors predicts increases in BMI z-score over time among overweight and obese children. STUDY DESIGN: Medical records from 168 overweight and 441 obese patients seen for repeated visits between September 2003 and April 2006 were examined for reported dietary, physical activity, and sedentary behaviors, family history of obesity and diabetes mellitus, documented Acanthosis nigricans, and BMI values. Random-effects regression analysis was done to determine whether demographic, familial, or behavioral data predicted changes in BMI z-score over time. RESULTS: The presence of A nigricans and a family history of obesity were associated with an increase in BMI z-score (beta=0.56, SE=0.09, P<.001 and beta=0.31, SE=0.13, P=.021). These risk factors explained 8% and 7% of the variation in BMI z-score respectively. Self- or parent-reported dietary and physical activity behaviors did not predict change in BMI z-score. CONCLUSIONS: Our findings suggest that the risk factors and self- or parent-reported risk behaviors routinely assessed by pediatric clinicians have limited ability to predict future growth trends, demonstrating the difficulty in determining which patients have the greatest risk of progression of obesity.

Comparative Effectiveness of New Approaches to Improve Mortality Risk Models From Medicare Claims Data.

Importance: Risk adjustment models using claims-based data are central in evaluating health care performance. Although US Centers for Medicare & Medicaid Services (CMS) models apply well-vetted statistical approaches, recent changes in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding system and advances in computational capabilities may provide an opportunity for enhancement. Objective: To examine whether changes using already available data would enhance risk models and yield greater discrimination in hospital-level performance measures. Design, Setting, and Participants: This comparative effectiveness study used ICD-9-CM codes from all Medicare fee-for-service beneficiary claims for hospitalizations for acute myocardial infarction (AMI), heart failure (HF), or pneumonia among patients 65 years and older from July 1, 2013, through September 30, 2015. Changes to current CMS mortality risk models were applied incrementally to patient-level models, and the best model was tested on hospital performance measures to model 30-day mortality. Analyses were conducted from April 19, 2018, to September 19, 2018. Main Outcomes and Measures: The main outcome was all-cause death within 30 days of hospitalization for AMI, HF, or pneumonia, examined using 3 changes to current CMS mortality risk models: (1) incorporating present on admission coding to better exclude potential complications of care, (2) separating index admission diagnoses from those of the 12-month history, and (3) using ungrouped ICD-9-CM codes. Results: There were 361 175 hospital admissions (mean [SD] age, 78.6 [8.4] years; 189 225 [52.4%] men) for AMI, 716 790 hospital admissions (mean [SD] age, 81.1 [8.4] years; 326 825 [45.6%] men) for HF, and 988 225 hospital admissions (mean [SD] age, 80.7 [8.6] years; 460 761 [46.6%] men) for pneumonia during the study; mean 30-day mortality rates were 13.8% for AMI, 12.1% for HF, and 16.1% for pneumonia. Each change to the models was associated with incremental gains in C statistics. The best model, incorporating all changes, was associated with significantly improved patient-level C statistics, from 0.720 to 0.826 for AMI, 0.685 to 0.776 for HF, and 0.715 to 0.804 for pneumonia. Compared with current CMS models, the best model produced wider predicted probabilities with better calibration and Brier scores. Hospital risk-standardized mortality rates had wider distributions, with more hospitals identified as good or bad performance outliers. Conclusions and Relevance: Incorporating present on admission coding and using ungrouped index and historical ICD-9-CM codes were associated with improved patient-level and hospital-level risk models for mortality compared with the current CMS models for all 3 conditions.

Development and Testing of Improved Models to Predict Payment Using Centers for Medicare & Medicaid Services Claims Data.

Importance: Predicting payments for particular conditions or populations is essential for research, benchmarking, public reporting, and calculations for population-based programs. Centers for Medicare & Medicaid Services (CMS) models often group codes into disease categories, but using single, rather than grouped, diagnostic codes and leveraging present on admission (POA) codes may enhance these models. Objective: To determine whether changes to the candidate variables in CMS models would improve risk models predicting patient total payment within 30 days of hospitalization for acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Design, Setting, and Participants: This comparative effectiveness research study used data from Medicare fee-for-service hospitalizations for AMI, HF, and pneumonia at acute care hospitals from July 1, 2013, through September 30, 2015. Payments across multiple care settings, services, and supplies were included and adjusted for geographic and policy variations, corrected for inflation, and winsorized. The same data source was used but varied for the candidate variables and their selection, and the method used by CMS for public reporting that used grouped codes was compared with variations that used POA codes and single diagnostic codes. Combinations of use of POA codes, separation of index admission diagnoses from those in the previous 12 months, and use of individual International Classification of Diseases, Ninth Revision, Clinical Modification codes instead of grouped diagnostic categories were tested. Data analysis was performed from December 4, 2017, to June 10, 2019. Main Outcomes and Measures: The models' goodness of fit was compared using root mean square error (RMSE) and the McFadden pseudo R2. Results: Among the 1 943 049 total hospitalizations of the study participants, 343 116 admissions were for AMI (52.5% male; 37.4% aged ≤74 years), 677 044 for HF (45.5% male; 25.9% aged ≤74 years), and 922 889 for pneumonia (46.4% male; 28.2% aged ≤74 years). The mean (SD) 30-day payment was $23 103 ($18 221) for AMI, $16 365 ($12 527) for HF, and $17 097 ($12 087) for pneumonia. Each incremental model change improved the pseudo R2 and RMSE. Incorporating all 3 changes improved the pseudo R2 of the patient-level models from 0.077 to 0.129 for AMI, from 0.042 to 0.129 for HF, and from 0.114 to 0.237 for pneumonia. Parallel improvements in RMSE were found for all 3 conditions. Conclusions and Relevance: Leveraging POA codes, separating index from previous diagnoses, and using single diagnostic codes improved payment models. Better models can potentially improve research, benchmarking, public reporting, and calculations for population-based programs.

An algorithm for identifying physical activity patterns from motion data.

An algorithm was developed to describe how physical activity (PA) patterns relate to overall motion counts. Thirty-five children wore an accelerometer (7-days). Each motion count was compared with the mean of surrounding counts within 21 min. Counts per minute similar to the mean were grouped into bouts. Counts that differed by more than 20% of the coefficient of variations (based on the mean and SD of the 21 min period) indicated transitions between bouts. Children with more daily motion had more and longer moderate (MPA) and vigorous (VPA) bouts, higher counts during MPA bouts, and more transitions from VPA to VPA bouts. In addition to differences in PA levels, highly active and less active children perform PA differently.

Variation in the Diagnosis of Aspiration Pneumonia and Association with Hospital Pneumonia Outcomes.

RATIONALE: National efforts to compare hospital outcomes for patients with pneumonia may be biased by hospital differences in diagnosis and coding of aspiration pneumonia, a condition that has traditionally been excluded from pneumonia outcome measures. OBJECTIVES: To evaluate the rationale and impact of including patients with aspiration pneumonia in hospital mortality and readmission measures. METHODS: Using Medicare fee-for-service claims for patients 65 years and older from July 2012 to June 2015, we characterized the proportion of hospitals' patients with pneumonia diagnosed with aspiration pneumonia, calculated hospital-specific risk-standardized rates of 30-day mortality and readmission for patients with pneumonia, analyzed the association between aspiration pneumonia coding frequency and these rates, and recalculated these rates including patients with aspiration pneumonia. RESULTS: A total of 1,101,892 patients from 4,263 hospitals were included in the mortality measure analysis, including 192,814 with aspiration pneumonia. The median proportion of hospitals' patients with pneumonia diagnosed with aspiration pneumonia was 13.6% (10th-90th percentile, 4.2-26%). Hospitals with a higher proportion of patients with aspiration pneumonia had lower risk-standardized mortality rates in the traditional pneumonia measure (12.0% in the lowest coding and 11.0% in the highest coding quintiles) and were far more likely to be categorized as performing better than the national mortality rate; expanding the measure to include patients with aspiration pneumonia attenuated the association between aspiration pneumonia coding rate and hospital mortality. These findings were less pronounced for hospital readmission rates. CONCLUSIONS: Expanding the pneumonia cohorts to include patients with a principal diagnosis of aspiration pneumonia can overcome bias related to variation in hospital coding.

Diagnosis, evaluation, and treatment of childhood obesity in pediatric practice.

OBJECTIVE: To determine rates of diagnosis and treatment, and types of treatment, among overweight children in clinical practice. DESIGN: Six hundred randomly selected records were reviewed. SETTING: Two community-based and 2 hospital-based clinics in New Haven. PARTICIPANTS: Children aged 3 to 17 years with a health maintenance visit from January 1, 1999, to December 31, 2000. Children classified according to body mass index (BMI) (calculated as weight in kilograms divided by the square of height in meters) lower than the 85th percentile were designated as nonoverweight; 85th to 94th percentile, at risk of overweight; and 95th percentile or greater, overweight. MAIN OUTCOME MEASURES: We examined the text of the encounter note for documentation of BMI, corresponding diagnosis regarding overweight, examination for comorbid disease, and treatment for overweight. RESULTS: Among 600 patients, 52.6% were male, 34.5% were black, 35.1% were Latin American, 57.2% were in single-parent households, and 84.0% received Medicaid. Overall, 39.8% were at risk of overweight (n = 107; range across sites, 14.7%-20.0%) or were overweight (n = 132; range across sites, 18.0%-28.0%). The BMI was documented in 0.5% (n = 3) of medical records. Among the 239 children at risk of overweight or overweight, 20.5% had a documented diagnosis (range, 12%-37%) and 16.9% had documented treatment (range, 6%-34%). The most common strategies among the 41 subjects with documented treatment (overweight and at risk of overweight patients) were diet (74%) and increased activity (49%). Treatment recommendations were often limited to general advice (eg, "recommended diet" [n = 19] or "increase exercise" [n = 16]). CONCLUSION: Despite a high burden of overweight, routine screening with BMI was not documented and few children received a formal diagnosis or treatment.

Lymph node cytology.

Lymph node cytology is quick, easy, and rewarding. Cytologic samples of peripheral and/or internal lymph nodes may be collected by fine-needle aspiration biopsy (FNAB) or nonaspiration fine-needle biopsy techniques. In addition, imprints or scrapings may be made from lymph nodes that have been surgically removed or at necropsy. Lymph node cytology is an excellent way to evaluate a lymphadenopathy whether it is a single node enlarged, multiple nodes enlarged, or a generalized lymphadenopathy. If multiple lymph nodes are enlarged, more than one should be sampled. A lymph node away from the mouth or any site of inflammation should be aspirated as well as any lymph node close to a site of inflammation. Generally, if no lymph nodes are enlarged, lymph node cytology is not helpful.

Sleep problems in urban, minority, early-school-aged children more prevalent than previously recognized.

OBJECTIVES: To use the children's sleep habits questionnaire (CSHQ) to characterize sleep problems in a group of 5- to 6-year-old minority children living in urban communities and to compare our findings with data from 5- to 6-year-old children in the original CSHQ validation study. METHODS: A cross-sectional study design was used to collect sleep data from parents using the CSHQ. RESULTS: The CSHQ was completed by 160 parents; 150 (94%) scored ≥41, indicating a sleep problem. The prevalence of having sleep problems for our minority community sample was significantly higher than the original community sample (94% vs. 23%, P < .001). The minority sample also had significantly higher mean total CSHQ scores (51.5 vs 37.9, P < .001) and higher scores across all 8 subscales of the CSHQ (P < .001 for all comparisons). CONCLUSIONS: The results suggest that sleep problems may be more prevalent in urban, early-school-aged minority children than previously reported.

The Relationship between Asthma and Obesity in Urban Early Adolescents.

Asthma and obesity, which have reached epidemic proportions, impact urban youth to a great extent. Findings are inconsistent regarding their relationship; no studies have considered asthma management. We explored the association of obesity and asthma-related morbidity, asthma-related health care utilization, and asthma management in urban adolescents with uncontrolled asthma. We classified 373 early adolescents (mean age=12.8 years; 82% Hispanic or Black) from New York City public middle schools into 4 weight categories: normal (body mass index [BMI]<85th percentile); overweight (85th percentile≤BMI<95th percentile); obese (95th percentile≤BMI<97th percentile); and very obese (BMI≥97th percentile). We compared sample obesity prevalence to national estimates, and tested whether weight categories predicted caregiver reported asthma outcomes, adjusting for age and race/ethnicity. Obesity prevalence was 37%, with 28% of the sample being very obese; both rates were significantly higher than national estimates. We found no significant differences in asthma-related health care utilization or asthma management between weight categories, and a few differences in asthma-related morbidity. Relative to normal weight and obese youth, overweight youth had higher odds of never having any days with asthma-related activity limitations. They also had higher odds of never having asthma-related school absences compared with obese youth. Overweight youth with asthma-related activity limitations had more days with limitations compared with normal weight youth. Overweight, but not obese youth, missed more school due to asthma than normal weight youth. Overweight and obesity prevalence was very high in urban, Hispanic, and Black adolescents with uncontrolled asthma, but not strongly associated with asthma-related morbidity, asthma-related health care utilization, or asthma management practices.

Patterns of moderate and vigorous physical activity in obese and overweight compared with non-overweight children.

OBJECTIVE: We determined whether overweight and obese children performed less combined moderate and vigorous physical activity (MVPA), less vigorous physical activity (VPA) alone, and had distinct patterns of sustained MVPA or VPA compared with non-overweight children. METHODS: We monitored 106 children (aged 8 to 10 years) for 7 consecutive days using accelerometers. Differences in mean daily MVPA and VPA were assessed by comparing non-overweight (NOW) with overweight and obese (OW/OB) participants using descriptive statistics and regression analysis. We used an algorithm to identify periods of consecutive minutes where MVPA or VPA was continuous, called bouts. We then compared the bouts performed by NOW versus OW and OB participants with respect to the mean of the counts·minute(-1) for the minutes included in the bout, their mean length in minutes, and the number of MVPA bouts performed in sequence. RESULTS: The non-overweight group averaged 143 minutes of MVPA per day versus 120 minutes among the OW/OB (p=0.004). The OW/OB group had fewer MVPA bouts per day compared with the NOW (11.6 versus17.6, p=0.012). Fewer VPA bouts were associated with greater body mass index z-score (p<0.001). The NOW children had more intense body motion during MVPA bouts and performed a greater proportion of MVPA bouts in sequences of five or more consecutive bouts, compared with the OW/OB (p=0.05 and p=0.002, respectively). CONCLUSIONS: In addition to performing less physical activity, we found that obese and overweight children had distinct patterns of MVPA and VPA bouts compared with non-overweight peers.

Greater lean tissue and skeletal muscle mass are associated with higher bone mineral content in children.

BACKGROUND: To compare the relationship of skeletal muscle mass with bone mineral content in an ethnically diverse group of 6 to 18 year old boys and girls. METHODS: 175 healthy children (103 boys; 72 girls) had assessments of body mass, height, and Tanner stage. Whole body bone mineral content, non-bone lean body mass (nbLBM), skeletal muscle mass, and fat mass were assessed using dual-energy X-ray absorptiometry (DXA). Muscle mass was estimated from an equation using appendicular lean soft tissue measured by DXA, weight and height. Estimates of skeletal muscle mass and adipose tissue were also assessed by whole body multi-slice magnetic resonance imaging (MRI). Linear regression was used to determine whether skeletal muscle mass assessed by DXA or by MRI were better predictors of bone mineral content compared with nbLBM after adjusting for sex, age, race or ethnicity, and Tanner stage. RESULTS: Greater skeletal muscle mass was associated with greater bone mineral content (p < 0.001). The skeletal muscle mass assessed by MRI provided a better fitting regression model (determined by R2 statistic) compared with assessment by DXA for predicting bone mineral content. The proportion of skeletal muscle mass in nbLBM was significantly associated with greater bone mineral content adjusted for total nbLBM. CONCLUSIONS: This study is among the first to describe and compare the relationship of skeletal muscle to bone using both MRI and DXA estimates. The results demonstrate that the use of MRI provides a modestly better fitting model for the relationship of skeletal muscle to bone compared with DXA. Skeletal muscle had an impact on bone mineral content independent of total non-bone lean body mass. In addition, Hispanics had greater bone mineral content compared to other race and ethnic groups after adjusting for sex, age, adipose tissue, skeletal muscle mass, and height.

Applying practice recommendations for the prevention and treatment of obesity in children and adolescents.

To describe pediatric clinicians' adherence to practice recommendations for obesity prevention and treatment, we conducted a cross-sectional analysis of 227 medical records of 3- to 18-year-old patients (seen from September 2003 to April 2004) and a longitudinal analysis of data from 632 overweight and obese patients (followed through March 2006). The cross-sectional analysis showed that early practice adopters (n = 3) more frequently recorded BMI (91% of patients), a diagnosis (89%), and counseling (82%) compared with late adopters (n = 9; 34%, 51%, and 48% of patients, respectively; P < .001). The longitudinal analysis showed that among overweight and obese patients, documentation of BMI dropped from 96% at the first clinic visit to 27% by the fifth visit; documentation of individual risk behaviors fell from >or=72% at the first visit to