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PubMed1998

Physician profiling using outpatient pharmacy data as a source for case mix measurement and risk adjustment.

Pharmacy data are a potential source of information on the health risks of members in a managed care organization (MCO). Reasons why these data can serve as a basis for case mix measurement of MCO populations are reviewed. Several pharmacy-based case mix measurement systems (CDS, KPARx) are summarized. Applications of pharmacy-based case mix systems for profiling of primary physician panels in an MCO are discussed and illustrated with several examples.

Diagnosis-Related Groups↗
PubMed2003

Baseline adjustments for binary data in repeated cross-sectional cluster randomized trials.

Analysis of covariance models, which adjust for a baseline covariate, are often used to compare treatment groups in a controlled trial in which individuals are randomized. Such analysis adjusts for any baseline imbalance and usually increases the precision of the treatment effect estimate. We assess the value of such adjustments in the context of a cluster randomized trial with repeated cross-sectional design and a binary outcome. In such a design, a new sample of individuals is taken from the clusters at each measurement occasion, so that baseline adjustment has to be at the cluster level. Logistic regression models are used to analyse the data, with cluster level random effects to allow for different outcome probabilities in each cluster. We compare the estimated treatment effect and its precision in models that incorporate a covariate measuring the cluster level probabilities at baseline and those that do not. In two data sets, taken from a cluster randomized trial in the treatment of menorrhagia, the value of baseline adjustment is only evident when the number of subjects per cluster is large. We assess the generalizability of these findings by undertaking a simulation study, and find that increased precision of the treatment effect requires both large cluster sizes and substantial heterogeneity between clusters at baseline, but baseline imbalance arising by chance in a randomized study can always be effectively adjusted for.

Cluster Analysis↗
PubMed2006

Differences in fertility by HIV serostatus and adjusted HIV prevalence data from an antenatal clinic in northern Uganda.

OBJECTIVES: To estimate differences in fertility by HIV serostatus and to validate an adjustment method for estimating the HIV prevalence in the general female population using data from an antenatal clinic. METHODS: We used Cox regression models to retrospectively estimate the age-specific relative fertility (RF) of HIV-positive compared to HIV-negative women among 3314 antenatal clinic attenders in northern Uganda. RF and the age distribution of women in the general female population were used to extrapolate the antenatal clinic-based HIV prevalence. This procedure was indirectly validated by comparing the adjusted estimate with those based on standard adjustment factors derived from general female populations in Uganda and Tanzania. RESULTS: HIV-positive women reported a lower fertility than HIV-negative women [age-adjusted RF=0.83, 95% confidence interval (CI): 0.75-0.93]. Except for girls aged 15-19 (RF=0.96, 95% CI: 0.74-1.24) HIV-positive women in all age groups were less fertile (20-24 year: RF=0.83, 95% CI: 0.67-1.01; 25-29 years: RF=0.79, 95% CI: 0.62-1.00; 30-49 year: RF=0.79, 95% CI: 0.65-0.96]. Adjusting the antenatal clinic-based HIV prevalence (11.6%) for these differences yields a higher estimate (13.8%) that is lower than those based on standard adjustment factors derived from general female populations (from 14.6% to 17.7%). CONCLUSIONS: The age-specific pattern of differential fertility by HIV serostatus derived from antenatal clinic data is consistent with findings from population-based studies conducted in Africa. However, differences in fertility between HIV positive and HIV-negative clients underestimate those in the general female population yielding inaccurate estimates when used to extrapolate the HIV prevalence.

Adolescent↗
PubMed2004

Risk adjustment for injured patients using administrative data.

BACKGROUND: Risk adjustment methods are needed for population-based studies of injured patients. METHODS: Data were obtained from National Hospital Discharge Surveys, 1996 to 2000. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnoses were used to categorize Abbreviated Injury Scale score, Injury Severity Score, ICD-9-CM Injury Severity Score, injury mechanisms, and comorbidities. Regression models for weighted survey data were constructed from combinations of these classifications, plus age and sex, to predict mortality, length of stay (LOS), or discharge to long-term care (LTC). RESULTS: Increased Abbreviated Injury Scale score, increased Injury Severity Score, or decreased ICD-9-CM Injury Severity Score were similarly associated with mortality, prolonged LOS, or more frequent LTC, as was increased age. Penetrating or burn mechanisms were associated with mortality and longer LOS; penetrating or vehicle mechanisms were associated with less frequent LTC. Different comorbidities affected LOS and LTC. Men had shorter LOS and less frequent LTC than women. CONCLUSION: Hospital outcomes after injury are predictable from age, sex, and standard diagnosis groupings. Anatomic scales gave similar results when adjusted for other factors.

Age Distribution↗
PubMed2005

The effects of incremental brightness and contrast adjustments on radiographic data: a quantitative study.

OBJECTIVES: To determine the border level of brightness and contrast changes in order to prevent the loss of originality of the quantitative data on digital dental radiographs. METHODS: After measuring the baseline mean grey values (MGVs) of a fixed region of interest on the alveolar bone and an aluminium step wedge, incremental brightness and contrast adjustments were performed on a digital periapical radiograph. The distribution of the data was analysed to investigate the significance of the changes on radiodensitometric data after incremental increase of brightness and contrast. RESULTS: The original MGVs were easily retrieved after brightness adjustments; however, the contrast increase led to more complicated density changes. The originality of the data was saved up to 50 units of contrast increase, but further than this limit, significant radiodensitometric changes occurred. CONCLUSIONS: Contrast adjustments should be performed cautiously when making quantitative analyses on the digital radiographs.

Absorptiometry, Photon↗
PubMed1994

Potential for bias in severity adjusted hospital outcomes data: analysis of patients with rheumatic disease.

OBJECTIVE: To examine the predictive validity of MedisGroups, a widely used method of measuring severity of illness, among patients with rheumatic disease and identify determinants of hospital outcomes, after adjusting for severity of illness. METHODS: Adult medical and surgical patients with rheumatic disease (5421) admitted to an academic medical center in 1988-90 were studied using a retrospective cohort design. Sociodemographic, clinical, and financial data were obtained from computerized hospital information systems. Severity of illness on admission was determined for each patient using MedisGroups, which classifies patients into groups of increasing severity. RESULTS: MedisGroups admission severity groups were highly related (p < 0.001) to inhospital mortality rates, which were 0.4, 0.8, 5.1 and 16.1%, respectively among patients in 4 groups of increasing severity. Controlling for MedisGroups admission severity using logistic regression, age, admission from the emergency room, and transfer from an acute care hospital were found to be additional independent predictors of mortality. MedisGroups severity groups were also directly related (p < 0.001) to length of stay and total hospital charges. Controlling for admission severity using linear regression, length of stay, and charges were independently related to several other variables; for example, length of stay was greater for patients admitted from the emergency room or transferred from other hospitals and for nonwhites, women, and older patients. Finally, within common individual diagnoses, these factors substantially increased the amount of variance in length of stay and charges explained by MedisGroups alone. CONCLUSIONS: Our findings demonstrate that after adjusting for severity of illness using MedisGroups, several other easily measured variables were associated with hospital outcomes in patients with rheumatic disease. Thus, generic severity systems, such as MedisGroups, may not adequately adjust outcomes among patients with rheumatic disease. Comparative hospital data based on these systems may be subject to bias.

Adult↗
PubMed2001

Risk adjustment using administrative data: impact of a diagnosis-type indicator.

OBJECTIVES: To determine the frequency with which commonly coded clinical variables are complications, as opposed to baseline comorbidities, and to compare the results of 2 risk-adjusted outcome analyses for coronary artery bypass graft surgery for which we either (a) ignored, or (b) used the available "diagnosis-type indicator." DESIGN: Analysis of existing administrative data. SETTING: Twenty-three Canadian hospitals. PATIENTS: A total of 50,357 coronary artery bypass graft surgery cases. MEASUREMENTS AND MAIN RESULTS: Among 21 clinical variables whose definitions involve the diagnosis-type indicator, 14 were predominantly (> or =97%) baseline risk factors when present. Seven variables were often complication diagnoses: renal disease (when present, 13% coded as complications), recent myocardial infarction (15%), peptic ulcer disease (15%), congestive heart failure (17%), cerebrovascular disease (26%), hemiplegia (34%), and severe liver disease (35%). The results of risk adjustment analyses predicting in-hospital mortality differed when the diagnosis-type indicator was either used or ignored, and as a result, adjusted hospital mortality rates and rankings changed, often dramatically, with rankings increasing for 10 hospitals, decreasing for 9 hospitals, and remaining the same for only 4 hospitals. CONCLUSIONS: The results of analyses performed using the diagnosis-type indicator in Canadian administrative data differ considerably from analyses that ignore the indicator. The widespread introduction of such an indicator should be considered in other countries, because risk-adjustment analyses performed without a diagnosis-type indicator may yield misleading results.

Canada↗
PubMed2003

Data quality and adjusted Hispanic mortality in the United States, 1989-1991.

OBJECTIVES: Hispanics appear to live longer compared to other ethnic groups in the United States. Our main objective was to determine whether data quality biases mortality statistics. We calculated the impact of misclassification of ethnicity on death certificates in order to create adjusted mortality estimates. METHODS: We used the National Mortality Follow-Back Survey of 1993 (NMFS) for our assessment of ethnicity misclassification. We then created misclassification estimates for 10-year age-sex groups, and used these to correct mortality estimates for 1989-1991. RESULTS: The overall predictive value positive (PV+) and sensitivity were 0.981 and 0.805, respectively, for men; and 0.994 and 0.902, respectively, for women. Age-specific adjustment for misclassification on death rates caused Hispanic male life expectancy to go from a 1.01 year advantage over White non-Hispanics, to a 1.83 year deficit, with a similar pattern found for females. CONCLUSIONS: The apparent Hispanic advantage in life expectancy is influenced by misclassification of ethnicity. Misclassification of ethnicity on death certificates biases Hispanic mortality downward, thereby falsely inflating life expectancy.

Death Certificates↗
PubMed2006

Adjusting batch effects in microarray expression data using empirical Bayes methods.

Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to combine microarray data sets is advantageous to researchers to increase statistical power to detect biological phenomena from studies where logistical considerations restrict sample size or in studies that require the sequential hybridization of arrays. In general, it is inappropriate to combine data sets without adjusting for batch effects. Methods have been proposed to filter batch effects from data, but these are often complicated and require large batch sizes ( > 25) to implement. Because the majority of microarray studies are conducted using much smaller sample sizes, existing methods are not sufficient. We propose parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples. We illustrate our methods using two example data sets and show that our methods are justifiable, easy to apply, and useful in practice. Software for our method is freely available at: http://biosun1.harvard.edu/complab/batch/.

Bayes Theorem↗
PubMed1997

Estimating social adjustment following spinal trauma--II: Population trends and effects of compensation on adjustment.

Adaptation to, or acceptance of, acquired spinal cord injury is accepted as an essentially longitudinal process. Changes in an individual's social, financial and domestic positions in turn affect issues concerning quality of life and self-image. The responses of 302 individuals with spinal cord injury in the United Kingdom and United States of America are presented to produce individual profiles of social adjustment. The differences between the UK and USA groups are presented, together with a combined analysis which addresses, in particular, the effects which being involved in litigation has on the process of social adjustment. Individual data concerning social adjustment, provided through a scale developed by the authors, and the utility of graphical presentation of the data is also presented. Such presentation has been found to have particular importance in clinical interview, situations by providing a framework for further exploration of individual adjustment difficulties, and in legal settings.

Adult↗
PubMed2003

Normalization of cDNA microarray data.

Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.

DNA, Complementary↗
PubMed2002

Prescription duration after drug copay changes in older people: methodological aspects.

OBJECTIVES: Impact assessment of drug benefits policies is a growing field of research that is increasingly relevant to health care planning for older people. Some cost-containment policies are thought to increase noncompliance. This paper examines mechanisms that can produce spurious reductions in drug utilization measures after drug policy changes when relying on pharmacy dispensing data. Reference pricing, a copayment for expensive medications above a fixed limit, for angiotensin-converting enzyme(ACE) inhibitors in older British Columbia residents, is used as a case example. DESIGN: Time series of 36 months of individual claims data. Longitudinal data analysis, adjusting for autoregressive data. SETTING: Pharmacare, the drug benefits program covering all patients aged 65 and older in the province of British Columbia, Canada. PARTICIPANTS: All noninstitutionalized Pharmacare beneficiaries aged 65 and older who used ACE inhibitors between 1995 and 1997 (N = 119,074). INTERVENTION: The introduction of reference drug pricing for ACE inhibitors for patients aged 65 and older. MEASUREMENTS: Timing and quantity of drug use from a claims database. RESULTS: We observed a transitional sharp decline of 110% t a standard error of 30% (P = .02) in the overall utilization rate of all ACE inhibitors after the policy implementation; five months later, utilization rates had increased, but remained under the predicted prepolicy trend. Coinciding with the sharp decrease, we observed a reduction in prescription duration by 31% in patients switching to no-cost drugs. This reduction may be attributed to increased monitoring for intolerance or treatment failure in switchers, which in turn led to a spurious reduction in total drug utilization. We ruled out the extension of medication use over the prescribed duration through reduced daily doses (prescription stretching) by a quantity-adjusted analysis of prescription duration. CONCLUSION: The analysis of prescription duration after drug policy interventions may provide alternative explanations to apparent short-term reductions in drug utilization and adds important insights to time trend analyses of drug utilization data in the evaluation of drug benefit policy changes.

Age Factors↗
PubMed2003

A space-variant filter model of texture segregation: parameter adjustment guided by psychophysical data.

This article presents a space-variant version of a standard spatial filter model of texture segregation of the "back-pocket" type (i.e., two filter layers with an intermediate pointwise nonlinearity). The model was tested with psychophysical data from experiments with line textures in which target lines differed in orientation from background lines. The textures were presented briefly and then masked. Segregation performance was evaluated along the horizontal meridian up to retinal eccentricities of about 10 deg. Data are reported from two experiments with different line densities (Kehrer 1989) and two experiments with different orientation contrasts between target lines and background lines (Kehrer 1990). Segregation performance proved to depend strongly on these texture variations, and it peaked several degrees from fixation in all cases. The filter model provided satisfactory predictions of experimental data when model parameters were adjusted appropriately. It is concluded (1) that filter models defined in strictly spatial terms (i.e., without temporal properties) offer a sufficient framework to account for the psychophysical data and (2) that the particular course of the performance curve (i.e., the performance peak outside the central region) must be attributed to the characteristics of second-layer filters.

Humans↗
PubMed1990

Estimating familial effects on age at onset and liability to schizophrenia. II. Adjustment for censored data.

Genetic studies of disorders with adult onset often contain individuals who have not completed their age at risk when last observed. Without correction for such censoring, correlation in ages at onset among relatives is substantially underestimated. Moreover, without correction for the effect of correlated ages at onset, the relationship between age at onset in the proband and liability in relatives is substantially overestimated. The present paper describes methods for correcting the effects of censoring on these estimates. In a companion paper [Kendler and MacLean, Genet Epidemiol 7:409-417, 1990] these methods are applied to a large family study of schizophrenia.

Adolescent↗
PubMed2003

Brain perfusion SPECT in patients with corticobasal degeneration: analysis using statistical parametric mapping.

We sought to determine the characteristics of brain perfusion in patients with corticobasal degeneration (CBD) using single photon emission computed tomography (SPECT) and statistical parametric mapping (SPM). Thirteen patients with CBD and 10 age-matched healthy volunteers were examined using brain perfusion SPECT and (99m)Tc-ethyl cysteinate dimer (ECD). Regional cerebral blood flow (rCBF) measurements were performed noninvasively using a graphic analysis method. Both the absolute rCBF data (raw data) and the adjusted rCBF data (global CBF normalized to 50 ml/100 g/min) were used in the SPM analysis. A significant decrease in the absolute rCBF was observed in extended areas of the brain in CBD patients compared to the control group. These areas included the frontal, parietal, and temporal cortices; basal ganglia; thalamus; and pontocerebellar regions. Our results suggest that the extent of the reduced rCBF region in CBD patients is more widespread than previously reported.

Aged↗