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Daniel H Solomon

Publications and source records attributed to Daniel H Solomon.

At least 37 records · Page 2Linked to original sources
PubMed2006

Interactive voice response telephone calls to enhance bone mineral density testing.

OBJECTIVE: Bone mineral density (BMD) testing is a key tool used to diagnose and treat osteoporosis. We assessed the rate of scheduling BMD tests among health plan members at risk for osteoporosis who received interactive voice response (IVR) calls. STUDY DESIGN: Cohort study. METHODS: Study patients included persons age 45 years with either a prior fracture or 90 days of glucocorticoid use and all women age 65 years during the 2-year baseline period. The IVR call provided educational content and then offered members an opportunity to transfer to schedule a BMD test. The primary outcome was scheduling a BMD test. RESULTS: We targeted 1402 health plan members, and 708 (50%) were successfully contacted. Of 54 patients who transferred to schedule a BMD test, only 3 actually did so. Because so few patients scheduled a BMD test, predictors of transfer were examined as a secondary end point. In a multivariate model, only self-reported intention to schedule a BMD test was a significant predictor (odds ratio = 4.4, 95% confidence interval = 2.2, 8.8). Members' age, sex, history of a prior fracture, self-report of a BMD test in the previous 2 years, acknowledgement of barriers to BMD testing, and discussion of BMD testing with one's physician were not related to transferring to schedule a BMD test. CONCLUSION: A letter and an IVR call prompted few to schedule a BMD test. More interventions to improve BMD testing should be developed and tested.

Aged↗
PubMed2005

Risk of death in elderly users of conventional vs. atypical antipsychotic medications.

BACKGROUND: Recently, the Food and Drug Administration (FDA) issued an advisory stating that atypical antipsychotic medications increase mortality among elderly patients. However, the advisory did not apply to conventional antipsychotic medications; the risk of death with these older agents is not known. METHODS: We conducted a retrospective cohort study involving 22,890 patients 65 years of age or older who had drug insurance benefits in Pennsylvania and who began receiving a conventional or atypical antipsychotic medication between 1994 and 2003. Analyses of mortality rates and Cox proportional-hazards models were used to compare the risk of death within 180 days, less than 40 days, 40 to 79 days, and 80 to 180 days after the initiation of therapy with an antipsychotic medication. We controlled for potential confounding variables with the use of traditional multivariate Cox models, propensity-score adjustments, and an instrumental-variable analysis. RESULTS: Conventional antipsychotic medications were associated with a significantly higher adjusted risk of death than were atypical antipsychotic medications at all intervals studied (< or =180 days: relative risk, 1.37; 95 percent confidence interval, 1.27 to 1.49; <40 days: relative risk, 1.56; 95 percent confidence interval, 1.37 to 1.78; 40 to 79 days: relative risk, 1.37; 95 percent confidence interval, 1.19 to 1.59; and 80 to 180 days: relative risk, 1.27; 95 percent confidence interval, 1.14 to 1.41) and in all subgroups defined according to the presence or absence of dementia or nursing home residency. The greatest increases in risk occurred soon after therapy was initiated and with higher dosages of conventional antipsychotic medications. Increased risks associated with conventional as compared with atypical antipsychotic medications persisted in confirmatory analyses performed with the use of propensity-score adjustment and instrumental-variable estimation. CONCLUSIONS: If confirmed, these results suggest that conventional antipsychotic medications are at least as likely as atypical agents to increase the risk of death among elderly persons and that conventional drugs should not be used to replace atypical agents discontinued in response to the FDA warning.

Aged↗
PubMed2005

Compliance with osteoporosis medications.

BACKGROUND: Long-term compliance with pharmacologic treatments for many asymptomatic conditions may be suboptimal, but little is known about compliance with medications used for osteoporosis. This study was undertaken to assess the level and determinants of compliance with drugs prescribed for osteoporosis. METHODS: This retrospective cohort study used pharmacy claims data from US Medicare and filled prescriptions from a state pharmaceutical benefits program. We included persons 65 years or older who initiated use of a medication for osteoporosis (alendronate sodium, calcitonin, hormone therapy, raloxifene hydrochloride, or risedronate) from January 1, 1996, through December 31, 2002. The outcome of interest was suboptimal medication compliance, defined as equal to or less than 66% of days with medication during a 60-day period. RESULTS: One year after initiating treatment for osteoporosis, 45.2% of the 40,002 patients were not continuing to fill prescriptions. Five years after initiation, 52.1% of patients were not continuing to fill prescriptions for an osteoporosis medication. Several characteristics independently predicted compliance: female sex, younger age, fewer comorbid conditions, using fewer nonosteoporosis medications, bone mineral density testing before and after initiating a medication, a fracture before and after initiating a medication, and nursing home residence during the 12 months before initiating a medication. However, models adjusted for the significant patient variables explained only 6% of the variation in compliance. CONCLUSIONS: Most patients who initiate a medication for osteoporosis do not continue to take it as prescribed. Although several patient characteristics significantly correlated with compliance, adjusted models explained little of the variation.

Age Distribution↗
PubMed2005

Explained variation in a model of therapeutic decision making is partitioned across patient, physician, and clinic factors.

BACKGROUND AND OBJECTIVE: Data on therapeutic decision making have a multilevel structure that can include patient-, provider-, and facility-level variables. A statistical method is presented for attributing explained variation in patient care to different levels of aggregation in a multilevel model with the aim of prioritizing and targeting quality improvement interventions. STUDY DESIGN AND SETTING: The proposed method is used in an analysis of adherence to evidence-based guidelines for the care of patients at risk of osteoporosis. Explained variation from a multilevel model of appropriate care is partitioned across patient-, physician-, and clinic-level factors. RESULTS: The combination of patient, physician, and clinic factors explained 20.0% of the variation in patient care. Individual physician effects explained 14.0% of the variation in the data; however, more than half of this explained variation could have been attributed to the individual clinic effect. Patient fixed effects alone explained 13.4% of the variation in the observed clinical decisions. CONCLUSION: The proposed approach is an intuitive and statistically valid method for attributing explained variation in a multilevel analysis of therapeutic decision making.

Administration, Oral↗
PubMed2005

Nonsteroidal antiinflammatory drugs and nonunion of humeral shaft fractures.

OBJECTIVE: To analyze the relationship between nonunion of humeral shaft fractures and nonsteroidal antiinflammatory drug (NSAID) exposure in older adults. METHODS: A cohort of 9,995 patients with humeral shaft fractures was identified using diagnosis and procedure codes from a Medicare database of >500,000 patients. Prescription NSAID as well as prescription opioid use was assessed from pharmacy claims data for 3 30-day periods immediately after the initial fracture. Nonunion was defined by the presence of procedure codes for repair of nonunion 90-365 days after the index fracture. We examined the association between NSAIDs and nonunion using multivariate Cox proportional hazards models. RESULTS: Of the 9,995 humeral shaft fractures, 105 patients developed nonunions (1.1%), and 1,032 (10.3%) were exposed to NSAIDs in the 90 days after fracture. NSAID exposure within the first 90 days was significantly associated with nonunion (relative risk [RR] 3.7, 95% confidence interval [95% CI] 2.4-5.6). When indicators for exposure to NSAIDs during each of the 3 30-day windows were placed into the same multivariate model, only the period 61-90 days post-fracture was significantly associated with nonunion (RR 3.9, 95% CI 2.0-6.2). We observed a similar association between opioids and nonunion, with exposure to opioids between 61 and 90 days associated with nonunion (RR 2.7, 95% CI 1.5-5.2), but exposure to opioids during neither of the 2 earlier 30-day periods significantly associated with nonunion. CONCLUSION: We found that exposure to nonselective NSAIDs or opioids in the period 61-90 days after a humeral shaft fracture was associated with nonunion. Although these associations may be causal, they are more likely to reflect the use of analgesics by patients with painful nonhealing fractures.

Aged↗
PubMed2005

Development and assessment of indicators of rheumatoid arthritis severity: results of a Delphi panel.

OBJECTIVE: To develop a set of indicators for assessing the severity of rheumatoid arthritis (RA) through medical records. METHODS: A list of 47 potential indicators of RA was reviewed by an expert Delphi panel of 6 rheumatologists. The Delphi method is a formal approach for gathering expert opinion. The 47 potential indicators included items from the following 5 categories: radiologic and laboratory findings, clinical and functional status measures, extraarticular manifestations, prior surgical history, and medications. The panelists rated the potential indicators' relationship to RA disease severity. Each panelist rated each indicator on a scale of 0-6, in which 0 indicated no relationship at all with severe RA and 6 indicated a perfect relationship with severe RA. After a baseline set of ratings, a literature review was distributed to the panelists along with the panel's initial mean ratings and the ranges. The panelists then met to discuss the literature and rerate all indicators. RESULTS: After repeat ratings and review of relevant literature, the panel rated 28 of 47 (60%) potential indicators as having a strong or very strong relationship to severe RA. These 28 indicators were drawn from all 5 categories of potential indicators. There was agreement among the panelists on ratings for 41 of 47 indicators. Agreement was defined as a range of scores among the panelists </=3. CONCLUSION: A Delphi panel of rheumatologists agreed that data generally available in medical records may serve as potential indicators of severe RA.

Antirheumatic Agents↗
PubMed2005

Osteoporosis action: design of the healthy bones project trial.

Although osteoporosis is common in older adults, it is often under-diagnosed and under-treated. We developed community-based patient- and physician-directed interventions for fracture prevention and compared them in a 2 x 2 factorial randomized controlled trial. The study population included older adults who were enrolled in a state-run pharmacy benefits program (The Pharmaceutical Assistance Contract for the Elderly in Pennsylvania) for Medicare beneficiaries. We randomly assigned 826 primary care physicians and their 31,715 patients to one of four trial arms--no patient and no physician intervention, patient but no physician intervention, physician but no patient intervention, both patient and physician interventions. The patient intervention consisted of targeted communication about fall and fracture prevention and osteoporosis diagnosis and treatment. It was delivered through several mailings. The physician intervention entailed one-on-one academic detailing encounters covering the same topics. The composite primary endpoint consisted of use of osteoporosis medication or a bone mineral density test. Other endpoints included patient's knowledge and attitudes towards fractures and osteoporosis, use of lower extremity strengthening to prevent falls, and the occurrence of fractures. All outcomes will be analyzed using random effects models accounting for clustering of subjects within physicians' practices.

Aged↗
PubMed2005

Educational outreach (academic detailing) regarding osteoporosis in primary care.

BACKGROUND: Academic detailing utilizes educators trained in social marketing to conduct one-on-one visits with physicians using evidence-based data. Academic detailing programs have improved physician's prescribing behaviors; however, the feasibility of large-scale programs across a large, geographically disperse state is unclear. METHODS: The study team collaborated with a state-run pharmacy benefits program for low-income elderly in a trial to improve osteoporosis management. Community-practicing physicians who saw a minimum of 25 patients enrolled in the benefits program were randomized to receive academic detailing or not. Fourteen educators were trained in the principles of academic detailing as well as osteoporosis epidemiology, diagnosis, and treatment. From September 2003 to January 2004, they attempted to meet with physicians or an allied health professional to discuss osteoporosis and fracture prevention. RESULTS: The physician population was 356 and 148 (41.6%) visits were completed-100 with physicians, 38 with allied health professionals, and 10 with both the physician and an allied health professional. In mixed multivariable models, there were no physician characteristics associated with completed encounters, including gender, training, geographic location, years since medical school, and number of study patients (all p-values > 0.11). The detailer's gender, professional training, and professional experience were not statistically significant correlates of completed encounters (all p-values > 0.28). Number of years since a detailer's professional training was a predictor of a completed encounter, OR = 1.43 per 5 years (95%CI 1.05, 1.96). CONCLUSIONS: A moderate rate of completed encounters was achieved. There was only one predictor of completed encounters.

Allied Health Personnel↗
PubMed2005

Statin lipid-lowering drugs and bone mineral density.

BACKGROUND: HMG Co-A reductase inhibitors (statin lipid-lowering drugs) have been associated with a reduced rate of fractures in some studies, but not in others. We examined the relationship between statin use and bone density among postmenopausal women. METHODS: We conducted a cross-sectional survey at one academic medical center. Postmenopausal women who underwent bone densitometry and agreed to a telephone interview were surveyed about osteoporosis risk factors, use of hormone replacement therapy and osteoporosis medications and statin exposure. We then developed linear regression models adjusting for known counfounders to assess the relationship between statin use and bone mineral density (BMD). RESULTS: Of 339 women studied, 162 were current or past users of statins, and 177 were not. Statin users and non-users were similar with respect to age, race, prior fracture history, the presence of medical conditions associated with osteoporosis, use of medications for osteoporosis, use of tobacco and use of oral glucocorticoids. Statin users had significantly higher body mass index (BMI) and rates of thiazide use, and were more likely to abstain from alcohol. After adjusting for important confounders, we found that statin use was associated with a significantly higher t-score at the total hip (-0.53 +/- 0.17) compared with non-users (-0.83 +/- 0.18; p = 0.02). At the lumbar spine, there was a trend toward higher t-scores in statin users (-0.91 +/- 0.24) compared with non-users (-1.21 +/- 0.23; p = 0.08). CONCLUSIONS: These results support the hypothesis that statin use is associated with higher BMD. While it is unclear whether their relationship is causal, further controlled studies examining bone formation and resorption would help determine the clinical implications of these findings.

Bone Density↗
PubMed2005

Lipid levels and bone mineral density.

PURPOSE: There has been considerable debate about the potential relationship between the use of statin lipid-lowering drugs and fracture risk; several observational studies suggest a protective effect but no randomized controlled trials have confirmed such a benefit. Because statins are given preferentially to persons with hyperlipidemia, if lipid levels were associated with bone mineral density, this could explain the discrepancy between epidemiological observations and randomized controlled trials. The aim of this study was to examine the relationship between lipid levels and bone mineral density. SUBJECTS AND METHODS: We included the 13592 participants in the National Health and Nutritional Examination Survey (NHANES) III who had bone mineral density and lipid levels measured; participants who reported the use of a lipid-lowering therapy were excluded. We examined the unadjusted bone mineral density across quintiles of total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL). We then constructed multivariable models, including age, sex, body mass index, and other potential confounders. RESULTS: In crude analyses, higher total cholesterol and LDL levels were associated with lower bone mineral densities (both P values for trend <.001), whereas higher HDL levels were associated with higher bone mineral densities (P value for trend <.001). However, in fully adjusted models, there was no significant relationship between total cholesterol, LDL, or HDL levels and bone mineral density (all P values for trend >.1). CONCLUSIONS: These results do not support a relationship between lipid levels and bone mineral density.

Adolescent↗
PubMed2005

Bone mineral density in subjects using central nervous system-active medications.

PURPOSE: Decreased bone mineral density defines osteoporosis according to the World Health Organization and is an important predictor of future fractures. The use of several types of central nervous system-active drugs, including benzodiazepines, anticonvulsants, antidepressants, and opioids, have all been associated with increased risk of fracture. However, it is unclear whether such an increase in risk is related to an effect of bone mineral density or to other factors, such as increased risk of falls. We sought to examine the relationship between bone mineral density and the use of benzodiazepines, anticonvulsants, antidepressants, and opioids in a representative US population-based sample. SUBJECTS AND METHODS: We analyzed data on adults aged 17 years and older from the Third National Health and Nutrition Examination Survey (NHANES III, 1988-1994). Total femoral bone mineral density of 7114 male and 7532 female participants was measured by dual-energy x-ray absorptiometry. Multivariable linear regression models were used to quantify the relation between central nervous system medication exposure and total femoral bone mineral density. Models controlled for relevant covariates, including age, sex, and body mass index. RESULTS: In linear regression models, significantly reduced bone mineral density was found in subjects taking anticonvulsants (0.92 g/cm2; 95% confidence interval [CI]: 0.89 to 0.94) and opioids (0.92 g/cm2; 95% CI: 0.88 to 0.95) compared with nonusers (0.95 g/cm2; 95% CI: 0.95 to 0.95) after adjusting for several potential confounders. The other central nervous system-active drugs--benzodiazepines or antidepressants--were not associated with significantly reduced bone mineral density. CONCLUSION: In cross-sectional analysis of NHANES III, anticonvulsants and opioids (but not benzodiazepines or antidepressants) were associated with significantly reduced bone mineral density. These findings have implications for fracture-prevention strategies.

Adolescent↗
PubMed2005

A Medicare database review found that physician preferences increasingly outweighed patient characteristics as determinants of first-time prescriptions for COX-2 inhibitors.

OBJECTIVE: Although innovative drugs may be underprescribed by some physicians, it is possible that rapid adoption after market introduction may lead to prescribing such drugs to patients without a clear indication. We sought to quantify the relative contributions of patient vs. physician factors to the decision to prescribe selective cyclooxygenase-2 (COX-2) inhibitors during the first 2 years of their availability. METHODS: A cohort of 37,957 Medicare beneficiaries who were enrolled in the Pharmaceutical Assistance Contract for the Elderly in Pennsylvania was identified. All patients had started using nonselective nonsteroidal anti-inflammatory drugs (NSAIDs) or selective COX-2 inhibitors between January 1, 1999, and December 31, 2000, and had no prior NSAID use. All had full prescription drug coverage, including NSAIDs and selective COX-2 inhibitors. Subsequent prescriptions were not considered. We quantified the amount of variation in first-time COX-2 prescribing that could be explained by predictors of gastrointestinal (GI) toxicity, other patient characteristics, or physician preferences. Explained variation was calculated as the R(2) (standardized to range from 0 to 1) from unconditional logistic regression and random intercept mixed effects logistic regression, fitted separately in each of eight consecutive 3-month periods. RESULTS: COX-2 inhibitors were adopted as the preferred NSAID by 55% of physicians within 180 days after they were marketed. In new NSAID users, COX-2 prescribing was twice as dependent on physician prescribing preferences (R(2)=60%) as on the combined predictors of GI toxicity (R(2)=3%) and other patient factors (R(2)=30%). The ratio of COX-2 prescribing explained by physician preferences over the contribution of patient factors increased from 2 to more than 10 over a 24-month period. CONCLUSIONS: First-time COX-2 inhibitor prescribing was somewhat dependent on patient factors in the first quarter of marketing, but the proportional influence of physician preferences increased substantially over the following 2 years, raising the question of why physician factors and not patient risk factors influence COX-2 inhibitor prescribing.

Aged↗
PubMed2005

Identification of individuals with CKD from Medicare claims data: a validation study.

BACKGROUND: Medicare claims data might provide an efficient source for outcomes research in patients with chronic kidney disease (CKD). However, in the absence of laboratory data, one would need to identify patients with CKD from diagnosis codes associated with health care claims. The validity of this approach to identify patients with CKD has not been sufficiently studied. METHODS: From chart abstraction, we obtained the first serum creatinine measurement of 1,852 elderly Medicare beneficiaries upon hospitalization for myocardial infarction and estimated each patient's glomerular filtration rate. We then searched all Medicare claims of the preceding year for the presence of a diagnosis code for diabetic nephropathy, hypertensive nephropathy, chronic renal insufficiency, acute renal failure, and miscellaneous other renal diseases. Using the gold standard of an estimated glomerular filtration rate less than 60 mL/min/1.73 m2 (<1.00 mL/s/1.73 m2) for definition of CKD, we calculated the sensitivity, specificity, and positive and negative predictive values for each of these diagnoses and combinations of these diagnoses. RESULTS: The sensitivity of individual diagnosis algorithms ranged from 2.7% for diabetic nephropathy to 17.5% for miscellaneous. However, miscellaneous had a lower specificity (95.5%) than all other individual diagnosis algorithms (all > or =99%). Using combinations of these algorithms improved sensitivity up to 26.6%, but at the cost of lower specificity. Positive predictive values generally were high (85.7% to 97.5%), but negative predictive values were low (32.4% to 37.4%). CONCLUSION: High positive predictive values indicate that Medicare claims data can be used to accurately identify patients with CKD for study. However, the utility of such databases for comparison of patients with CKD versus lesser degrees of CKD is limited.

Aged↗
PubMed2005

Adjusting for unmeasured confounders in pharmacoepidemiologic claims data using external information: the example of COX2 inhibitors and myocardial infarction.

BACKGROUND: Large health care utilization datasets are frequently used to analyze the incidence of rare adverse events from medications. However, possible confounders are typically not measured in such datasets. We show how to assess the impact of confounding by factors not measured in Medicare claims data in a study of the association between selective COX2 inhibitors and acute myocardial infarction (MI). METHODS: Using the Medicare Current Beneficiary Survey, we assessed the association between use of selective COX2 inhibitors and 5 potential confounders not measured in Medicare claims data: body-mass index, aspirin use, smoking, income, and educational attainment. For 8,785 participants > or =65 years, we estimated the prevalence of selective COX2 inhibitor use and also of each confounder, as well as the association between drug exposure and confounders. Estimates of the confounder-disease associations from the medical literature were used to calculate the extent of residual confounding bias for each potential confounder. RESULTS: Selective COX2 inhibitor users were less likely to be smokers (8% versus 10%) than nonselective NSAID users, while the prevalence of obesity was comparable (24%). Aspirin use was also balanced among all drug exposure categories. Failure to adjust for 5 potential confounders led to a small underestimation of the association between selective COX2 inhibitors and MI; comparing selective COX2 inhibitors with NSAIDs, the net bias was estimated to be -1.0% of the unknown true effect size (maximum range: -6% to 0%). CONCLUSIONS: In this example of the relationship between selective COX2 inhibitors and MI, not adjusting for 5 potential confounders in Medicare claims data analyses tended to slightly underestimate the association, but is unlikely to cause important bias.

Aged↗
PubMed2005

Medication use patterns for osteoporosis: an assessment of guidelines, treatment rates, and quality improvement interventions.

OBJECTIVE: To assess current osteoporosis treatment guidelines, studies of osteoporosis treatment, and interventions to improve osteoporosis treatment. METHODS: We searched the medical literature for articles published between January 1, 1992, and December 31, 2003, and assessed all relevant articles using a structured data abstraction process. Because of substantial heterogeneity in study design, no attempt was made to summarize the data using meta-analytic techniques. RESULTS: Seventy-six articles met criteria for inclusion. Eighteen practice guidelines were studied. Most guidelines were consistent in key treatment recommendations. Among 18 studies of treatment rates in patients who had fractures, the weighted average varied from 22% for nonhormonal treatment to 19% for calcium. We found slightly higher treatment rates for patients taking oral glucocorticoids or for those older than 65 years. There were no consistent correlates of which patients received treatment. Six studies that examined treatment frequencies after bone densitometry all found that patients with lower bone mineral density were more likely to receive treatment. Most of the 8 interventions designed to improve osteoporosis treatment showed improvement in treatment rates; however, only 3 were randomized, and these showed the smallest effects. CONCLUSIONS: Frequency of treatment of osteoporosis in at-risk populations is low. However, our assessment of the literature revealed no clear and consistent predictors of undertreatment. Few carefully controlled interventions have been reported.

Adult↗