Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Data Adjustment”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22Linked to original sources
PubMed2003

The volume-outcome relationship: from Luft to Leapfrog.

Numerous reports have documented a volume-outcome relationship for complex medical and surgical care, although many such studies are compromised by the use of discharge abstract data, inadequate risk adjustment, and problematic statistical methodology. Because of the volume-outcome association, and because valid outcome measurements are unavailable for many procedures, volume-based referral strategies have been advocated as an alternative approach to health-care quality improvement. This is most appropriate for procedures with the greatest outcome variability between low-volume and high-volume providers, such as esophagectomy and pancreatectomy, and for particularly high-risk subgroups of patients. Whenever possible, risk-adjusted outcome data should supplement or supplant volume standards, and continuous quality improvement programs should seek to emulate the processes of high-volume, high-quality providers. The Leapfrog Group has established a minimum volume requirement of 500 procedures for coronary artery bypass grafting. In view of the questionable basis for this recommendation, we suggest that it be reevaluated.

Hospital Mortality↗
PubMed2004

Microarray Data Analysis Toolbox (MDAT): for normalization, adjustment and analysis of gene expression data.

SUMMARY: We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression based on five statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY: MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at http://microarray.omrf.org/publications/2004/knowlton/MDAT.zip.

Algorithms↗
PubMed2006

Microwave spectra, ab initio calculations, and r0 structural parameters for (methylamino)thiophosphoryl difluoride.

The microwave spectra of (methylamino)thiophosphoryl difluoride, CH(3)NHP(=S)F(2), and two deuterated species, CH(3)NDP(=S)F(2) and CD(3)NHP(=S)F(2), have been investigated in the region from 26.5 to 39.0 GHz. The rotational constants of the ground vibrational state have been determined and have been shown to be only consistent with the trans conformer (CH(3) group antiperiplanar to the P=S bond) with C(s) symmetry. The a-type R branch transitions have been assigned for the trans conformer for the three isotopomers on the basis of the rigid rotor model. Near-trans and near-cis forms without molecular planes of symmetry are predicted by all ab initio calculations with the near-trans form being more stable. However, the double-well potentials governing the interchange between the two enantiomeric near-trans as well as the two near-cis forms are too shallow to accommodate the zero-point energies of the nu(24) asymmetric torsion. Thus, the trans conformation with C(s) symmetry may be more accurate in explaining the microwave experimental data. The "adjusted" r(0) structural parameters have been obtained by systematically adjusting the ab initio MP2(full)/6-311+G(d,p) structure of the trans conformer with C(s) symmetry to fit the microwave rotational constants. The determined heavy atom distances are r(C-N) = 1.459(5), r(P-N) = 1.621(5), r(P=S) = 1.879(5), and r(P-F) = 1.550(5) A, and the heavy atom angles are angleCNP = 124.7(5) degrees , angleNPS = 118.3(5) degrees , angleNPF = 103.2(5) degrees , angleFPS = 117.0(5) degrees , and angleFPF = 94.6(5) degrees . The adjusted r(0) parameters have also been obtained for aminodifluorophosphine, H(2)NPF(2), with a slightly pyramidal -PNH(2) moiety. The results indicate that the previously reported short distance of 0.981(5) A for the N-H(o)(outer) bond from the microwave study is too short, and the adjusted r(0) value of 1.007(3) A is obtained from the combined data. Adjusted r(0) parameters are also reported for (dimethylamino)difluorophosphine, (CH(3))(2)NPF(2), with C(s) symmetry with the PNC(2) portion of the molecule being planar. The previously reported C-H distances from the electron diffraction study are too long, and the anglePNC(i) and angleC(o)NC(i) angles are also found to be in error. These results provide a reasonable explanation why the microwave and electron diffraction results differ for the structures of these latter two molecules.

Journal Article↗
PubMed2005

[Impact of risk adjustment with insurance claims data on cesarean delivery rates of healthcare organizations in Korea].

OBJECTIVES: To propose a risk-adjustment model from insurance claims data, and analyze the changes in cesarean section rates of healthcare organizations after adjusting for risk distribution. METHODS: The study sample included delivery claims data from January to September, 2003. A risk-adjustment model was built using the 1st quarter data, and the 2nd and 3rd quarter data were used for a validation test. Patients' risk factors were adjusted using a logistic regression analysis. The c-statistic and Hosmer-Lemeshow test were used to evaluate the performance of the risk-adjustment model. Crude, predicted and risk-adjusted rates were calculated, and compared to analyze the effects of the adjustment. RESULTS: Nine risk factors (malpresentation, eclampsia, malignancy, multiple pregnancies, problems in the placenta, previous Cesarean section, older mothers, bleeding and diabetes) were included in the final risk-adjustment model, and were found to have statistically significant effects on the mode of delivery. The c-statistic (0.78) and Hosmer-Lemeshow test (chi2=0.60, p=0.439) indicated a good model performance. After applying the 2nd and 3rd quarter data to the model, there were no differences in the c-statistic and Hosmer-Lemeshow chi2. Also, risk factor adjustment led to changes in the ranking of hospital Cesarean section rates, especially in tertiary and general hospitals. CONCLUSION: This study showed a model performance, using medical record abstracted data, was comparable to the results of previous studies. Insurance claims data can be used for identifying areas where risk factors should be adjusted. The changes in the ranking of hospital Cesarean section rates implied that crude rates can mislead people and therefore, the risk should be adjusted before the rates are released to the public. The proposed risk-adjustment model can be applied for the fair comparisons of the rates between hospitals.

Cesarean Section↗
PubMed2006

Nonparametric estimation of sojourn time distributions for truncated serial event data--a weight-adjusted approach.

In follow-up studies, survival data often include subjects who have had a certain event at recruitment and may potentially experience a series of subsequent events during the follow-up period. This kind of survival data collected under a cross-sectional sampling criterion is called truncated serial event data. The outcome variables of interest in this paper are serial sojourn times between successive events. To analyze the sojourn times in truncated serial event data, we need to confront two potential sampling biases arising simultaneously from a sampling criterion and induced informative censoring. In this study, nonparametric estimation of the joint probability function of serial sojourn times is developed by using inverse probabilities of the truncation and censoring times as weight functions to accommodate these two sampling biases under various situations of truncation and censoring. Relevant statistical properties of the proposed estimators are also discussed. Simulation studies and two real data are presented to illustrate the proposed methods.

Accidents↗
PubMed2001

Age-adjusted death rates: trend data based on the year 2000 standard population.

Age-adjusted death rates are routine mortality risk measures used to compare rates over time or between groups such as those living in different geographic areas. This type of measure eliminates differences that would be caused because one population is older than another. Beginning with mortality data for 1999, the standard population used by the Centers for Disease Control and Prevention's National Center for Health Statistics (NCHS) to calculate age-adjusted death rates based on the Year 2000 estimated population distribution replacing that of 1940 used previously. Comparisons of 1999 mortality data with that of 1998 and earlier years cannot be made unless age-adjusted death rates are based on the same standard population. Changing the standard population generally changes the magnitude of an age-adjusted death rate and may change the magnitude of the differential between two groups. Typically, the change in standard makes relatively little difference in the mortality trend but it can when age-specific rates have divergent patterns. This publication provides age-adjusted death rates by race and sex based on the year 2000 population standard and directs readers to the NCHS Web site for age-adjusted death rates by selected causes.

Age Distribution↗
PubMed2004

Characterization of biological types of cattle (Cycle VI): carcass, yield, and longissimus palatability traits.

Carcass (n = 568) and longissimus thoracis palatability (n = 460) traits from F1 steers obtained from mating Hereford (H), Angus (A), and U.S. Meat Animal Research Center (MARC) III cows to H, A, Norwegian Red (NR), Swedish Red and White (RW), Friesian (F), or Wagyu (W) sires were compared. Data were adjusted to constant age (471 d), carcass weight (356 kg), fat thickness (1.0 cm), percentage of fat trim (24%), and marbling (Small35) end points. For Warner-Bratzler shear force and trained sensory panel traits, data were obtained on longissimus thoracis steaks stored at 2 degrees C for 14 d postmortem. The following comparisons were from the age-constant end point. Carcasses from H- and A-sired steers (377 and 374 kg, respectively) were the heaviest (P < 0.05) and carcasses from W-sired steers (334 kg) were the lightest (P < 0.05). A greater (P < 0.05) percentage of carcasses from A- and W-sired steers graded USDA Choice (88 and 85%, respectively) than carcasses from other sire breeds (52 to 71%). Adjusted fat thickness for carcasses from A-sired steers (1.3 cm) was highest (P < 0.05), followed by H-sired steers (1.1 cm) and W- and F-sired steers (0.9 cm); NR- and RW-sired steers (0.8 cm) had the lowest (P < 0.05) adjusted fat thickness. Longissimus thoracis area was not different (P > 0.05) among sire breeds (mean = 80.6 cm2). Carcass yield of boneless, totally trimmed retail product was least (P < 0.05) for A-sired steers (60.1%), intermediate for H-sired steers (61.5%), and similar (P > 0.05) for all other sire breeds (62.5 to 62.8%). Longissimus thoracis steaks from carcasses of A- (3.7 kg) and W-sired (3.7 kg) steers had lower (P < 0.05) shear force values than longissimus thoracis steaks from other sire breeds (4.1 to 4.2 kg). Trained sensory panel tenderness, juiciness, or beef flavor intensity ratings for longissimus thoracis steaks did not differ (P > 0.05) among the sire breeds. Sire breed comparisons were affected by adjusting data to other end points. Heritability estimates for various carcass, yield, and palatability traits ranged from very low (h2 = 0.06 for percentage of kidney, pelvic, and heart fat) to relatively high (h2 = 0.71 for percentage of retail product yield). Relative to the other sire breeds, W-sired steers had the highest percentage of USDA Choice, Yield grade 1 and 2 carcasses, but their carcasses were the lightest.

Adipose Tissue↗
PubMed2006

Evaluation of average daily gain prediction by level one of the 1996 National Research Council beef model and development of net energy adjusters.

Two data sets were developed to evaluate and refine feed energy predictions with the beef National Research Council (NRC, 1996) model level 1. The first data set included pen means of group-fed cattle from 31 growing trials (201 observations) and 17 finishing trials (154 observations) representing over 7,700 animals fed outside in dirt lots. The second data set consisted of 15 studies with individually fed cattle (916 observations) fed in a barn. In each data set, actual ADG was compared with ADG predicted with the NRC model level 1, assuming thermoneutral environmental conditions. Next, the observed ADG (kg), TDN intake (kg/d), and TDN concentration (kg/kg of DM) were used to develop equations to adjust the level 1 predicted diet NEm and NEg (diet NE adjusters) to be applied to more accurately predict ADG. In both data sets, the NRC (1996) model level 1 inaccurately predicted ADG (P < 0.001 for slope = 1; intercept = 0 when observed ADG was regressed on predicted ADG). The following nonlinear relationships to adjust NE based on observed ADG, TDN intake, and TDN concentration were all significant (P < 0.001): NE adjuster = 0.7011 x 10(-0.8562 x ADG) + 0.8042, R2 = 0.325, s(y.x) = 0.136 kg; NE adjuster = 4.795 10(-0.3689 x TDN intake) + 0.8233, R2 x = 0.714, s(y.x) = 0.157 kg; and NE adjuster = 357 x 10(-5.449 x TDN concentration) + 0.8138, R2 = 0.754, s(y.x) = 0.127 kg. An NE adjuster < 1 indicates overprediction of ADG. The average NE adjustment required for the pen-fed finishing trials was 0.820, whereas the (P < 0.001) adjustment of 0.906 for individually fed cattle indicates that the pen-fed environment increased NE requirements. The use of these equations should improve ADG prediction by the NRC (1996) model level 1, although the equations reflect limitations of the data from which they were developed and are appropriate only over the range of the developmental data set. There is a need for independent evaluation of the ability of the equations to improve ADG prediction by the NRC (1996) model level 1.

Animal Nutritional Physiological Phenomena↗
PubMed1997

Growth in weight, recumbent length, and head circumference for preterm low-birthweight infants during the first three years of life using gestation-adjusted ages.

Data from 867 preterm low-birthweight participants in the Infant Health and Development Program (IHDP) were used to develop reference data for growth status at an age and for increments from term to 36 month gestation-adjusted age (GAA). Weight, length and head circumference were recorded at 4 month intervals in the first year and at 6 month intervals in the second and third years. Selected percentiles for values at an age (status values) and increments for age intervals are presented in graphs separately for VLBW infants (< or = 1500 g at birth) and for LBW infants (1501-2500 g at birth). Percentiles of weight increments are presented beginning shortly before term for 1 month intervals to 6 month GAA, for 2 month intervals to 12 month GAA, and for 3-month intervals to 36 month GAA. Percentiles for length and head circumference increments are presented from term to 6 months for 2-month intervals, and to 36 month GAA for 3 month intervals. Among LBW infants, boys, had larger status and increment values than girls (P < 0.05), but there were no significant sex-associated differences in VLBW infants for status or increments. The mean status values and increments in weight and head circumference of the LBW infants were larger than those of VLBW infants, but the differences in length were not significant.

Aging↗
PubMed2006

A bootstrap test for the analysis of microarray experiments with a very small number of replications.

In microarray studies it is common that the number of replications (i.e. the sample size) is small and that the distribution of expression values differs from normality. In this situation, permutation and bootstrap tests may be appropriate for the identification of differentially expressed genes. However, unlike bootstrap tests, permutation tests are not suitable for very small sample sizes, such as three per group. A variety of different bootstrap tests exists. For example, it is possible to adjust the data to have a common mean before the bootstrap samples are drawn. For small significance levels, which can occur when a large number of genes is investigated, the original bootstrap test, as well as a bootstrap test suggested for the Behrens-Fisher problem, have no power in cases of very small sample sizes. In contrast, the modified test based on adjusted data is powerful. Using a Monte Carlo simulation study, we demonstrate that the difference in power can be huge. In addition, the different tests are illustrated using microarray data.

Algorithms↗
PubMed2006

Present-at-admission diagnoses improved mortality risk adjustment among acute myocardial infarction patients.

OBJECTIVE: Hospital mortality outcomes for acute myocardial infarction (AMI) patients are a focus of quality improvement programs conducted by government agencies. AMI mortality risk-adjustment models using administrative data typically adjust for baseline differences in mortality risk with a limited set of common and definite comorbidities. In this study, we present an AMI mortality risk-adjustment model that adjusts for comorbid disease and for AMI severity using information from secondary diagnoses reported as present at admission for California hospital patients. STUDY DESIGN AND SETTING: AMI patients were selected from California hospital administrative data for 1996 through 1999 according to criteria used by the California Hospital Outcomes Project Report on Heart Attack Outcomes, a state-mandated public report that compares hospital mortality outcomes. We compared results for the new model to two mortality risk-adjustment models used to assess hospital AMI mortality outcomes by the state of California, and to two other models used in prior research. RESULTS: The model using present-at-admission diagnoses obtained substantially better discrimination between predicted survival and inpatient death than the other models we considered. CONCLUSION: AMI mortality risk-adjustment methods can be meaningfully improved using present-at-admission diagnoses to identify comorbid disease and conditions related closely to AMI.

California↗
PubMed2007

Enhancement of claims data to improve risk adjustment of hospital mortality.

CONTEXT: Comparisons of risk-adjusted hospital performance often are important components of public reports, pay-for-performance programs, and quality improvement initiatives. Risk-adjustment equations used in these analyses must contain sufficient clinical detail to ensure accurate measurements of hospital quality. OBJECTIVE: To assess the effect on risk-adjusted hospital mortality rates of adding present on admission codes and numerical laboratory data to administrative claims data. DESIGN, SETTING, AND PATIENTS: Comparison of risk-adjustment equations for inpatient mortality from July 2000 through June 2003 derived by sequentially adding increasingly difficult-to-obtain clinical data to an administrative database of 188 Pennsylvania hospitals. Patients were hospitalized for acute myocardial infarction, congestive heart failure, cerebrovascular accident, gastrointestinal tract hemorrhage, or pneumonia or underwent an abdominal aortic aneurysm repair, coronary artery bypass graft surgery, or craniotomy. MAIN OUTCOME MEASURES: C statistics as a measure of the discriminatory power of alternative risk-adjustment models (administrative, present on admission, laboratory, and clinical for each of the 5 conditions and 3 procedures). RESULTS: The mean (SD) c statistic for the administrative model was 0.79 (0.02). Adding present on admission codes and numerical laboratory data collected at the time of admission resulted in substantially improved risk-adjustment equations (mean [SD] c statistic of 0.84 [0.01] and 0.86 [0.01], respectively). Modest additional improvements were obtained by adding more complex and expensive to collect clinical data such as vital signs, blood culture results, key clinical findings, and composite scores abstracted from patients' medical records (mean [SD] c statistic of 0.88 [0.01]). CONCLUSIONS: This study supports the value of adding present on admission codes and numerical laboratory values to administrative databases. Secondary abstraction of difficult-to-obtain key clinical findings adds little to the predictive power of risk-adjustment equations.

Clinical Laboratory Information Systems↗
PubMed1987

Inter-area variations in age-adjusted health status.

Data from the 1980 to 1981 National Health Interview Survey on morbidity, principally bed-disability days, was age standardized and indexed by region of the United States and metropolitan and nonmetropolitan residence within region. There were substantial differences in both age-specific and age-adjusted morbidity by place of residence. Age-specific hospital days as a percent of bed-disability days also showed striking differences by geographic area. Age- and morbidity-adjusted data on hospital use for the 31 largest standard metropolitan statistical areas (SMSAs) add considerably to the little information available on inter-city differences in health status and hospital use. Indirectly age-standardized data for the 31 SMSAs show large variations in both bed-disability days and the proportion of such days occurring in hospitals. These data seriously challenge the premise that age is a reliable proxy for health status when comparing hospital (or surgical) use of populations residing in different locales (e.g., small area variations in health care use). Dependence on age instead of health status to identify high and low hospital use areas will systematically favor areas where the population has low morbidity (age adjusted) and be adverse to areas that have high morbidity.

Adolescent↗
PubMed2004

Adjustment of systematic microarray data biases.

MOTIVATION: Systematic differences due to experimental features of microarray experiments are present in most large microarray data sets. Many different experimental features can cause biases including different sources of RNA, different production lots of microarrays or different microarray platforms. These systematic effects present a substantial hurdle to the analysis of microarray data. RESULTS: We present here a new method for the identification and adjustment of systematic biases that are present within microarray data sets. Our approach is based on modern statistical discrimination methods and is shown to be very effective in removing systematic biases present in a previously published breast tumor cDNA microarray data set. The new method of 'Distance Weighted Discrimination (DWD)' is shown to be better than Support Vector Machines and Singular Value Decomposition for the adjustment of systematic microarray effects. In addition, it is shown to be of general use as a tool for the discrimination of systematic problems present in microarray data sets, including the merging of two breast tumor data sets completed on different microarray platforms. AVAILABILITY: Matlab software to perform DWD can be retrieved from https://genome.unc.edu/pubsup/dwd/

Algorithms↗