Jonathan P Weiner

Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States

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Publications (85)405.83 Total impact

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    ABSTRACT: Health care quality is frequently described with measures representing the overall performance of a health care system. Despite the growing attention to overuse of health care resources, there is little experience with aggregate measures of overuse. To identify a set of possible indicators of overuse that can be operationalized with claims data and to describe variation in these indicators across the hospital referral regions (HRRs). Using an environmental scan, we identified published descriptions of overused procedures. We assessed each procedure's feasibility for measurement with claims and developed algorithms for occurrences of procedures in patients unlikely to benefit. Using a 5% sample of Medicare claims from 2008, we calculated summary statistics to illustrate variance in the use across HRRs. A total of 613 procedures were identified as overused; 20 had abundant frequency and variance to be possible measures of systematic overuse. These included 13 diagnostic tests, 2 tests for screening, 1 for monitoring, and 4 therapeutic procedures. The usage varied markedly across HRRs. For illustration, 1 HRR used computed tomography for rhinosinusitis diagnosis in 80 of 1000 beneficiaries (mean usage across HRRs was 14/1000). Among 1,451,142 beneficiaries, 14% had at least one overuse event (range, 8.4%-27%). We identified a set of overused procedures that may be used as measures of overuse and that demonstrate significant variance in their usage. The implication is that an index of overuse might be built from these indicators that would reveal systematic patterns of overuse within regions. Alternatively, these indicators may be valuable in the quality improvement efforts.
    Medical care 12/2013; · 3.24 Impact Factor
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    ABSTRACT: Background: Because laboratory test results are less available to researchers than claims data, a claims-based indicator of diabetes improvement would be valuable. Objectives: To determine whether a decrease in medication use for diabetes parallels clinical improvement in glycemic control. Study Design: This was a retrospective cohort study using up to 3.5 years of pharmacy and laboratory data from 1 private insurer. Data included 104 patients with diabetes who underwent bariatric surgery and had at least 1 glycated hemoglobin (A1C) test before and after surgery. Methods: We assigned each A1C test to a 90-day interval before or after surgery. Medication availability was noted for the midpoint of the interval (on insulin, on oral medications, count of medications). Each subject could contribute 1 presurgery and up to 3 postsurgery observations. We recorded the changes in A1C test results and medication use from the presurgery to the postsurgery period. Using the A1C test as the reference standard, positive and negative predictive values of medication-based indicators were calculated. Results: After bariatric surgery, A1C test values decreased by more than 1% and the count of unique medications decreased by 0.6. All 3 medication-based indicators had high positive predictive values (0.85) and low negative predictive values (0.20), and count of medications had better performance than the other indicators. Conclusions: Without clinical information, a decrease in use of medications can serve as a proxy for clinical improvement. Validation of results in other settings is needed.
    The American journal of managed care 07/2013; 19(7):572-8. · 2.12 Impact Factor
  • Christine Butorff, Sean R Tunis, Jonathan P Weiner
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    ABSTRACT: Objectives: One of the main goals of the Affordable Care Act (ACA) is to control the costs of US healthcare. Channeling patients toward more effective services is one of many approaches being used to control costs while improving health outcomes. This paper reviews value-based insurance design (VBID) concepts and discusses options for states to encourage these designs in the new health insurance exchanges (HIEs). Methods: We reviewed the literature on VBID as well as the text of the ACA for descriptions of how VBID might be encouraged through the new state health insurance exchanges. Results: States, under healthcare reform, are allowed to promote the use of VBID designs in their exchanges. There are 4 broad approaches a state HIE could pursue with regard to VBID, ranging from establishing a process for recommending high- or low-value services and requiring plans to adhere to the recommendations, to offering no guidance to plans. The evidence surrounding how well VBID designs work is growing, but it is still limited. To date there is no evidence that reducing or eliminating copays for preventive services cuts costs in the long term. However, modeling does suggest the potential for such long-term savings,so states should proceed with caution. Conclusions: Modifying copays, even in small amounts, can send signals to patients about the relative value of drugs and services. However, long-term savings will likely result from higher copays on low-value services. The leadership of each exchange has a unique opportunity to reshape the insurance benefit landscape in its state to improve value and invest in prevention.
    The American journal of managed care 07/2013; 19(7):593-600. · 2.12 Impact Factor
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    ABSTRACT: To develop and provide initial validation for a multivariate, claims-based prediction model for disability status (DS), a proxy measure of performance status (PS), among older adults. The model was designed to augment information on health status at the point of cancer diagnosis in studies using insurance claims to examine cancer treatment and outcomes. We used data from the 2001-2005 Medicare Current Beneficiary Survey (MCBS), with observations randomly split into estimation and validation subsamples. We developed an algorithm linking self-reported functional status measures to a DS scale, a proxy for the Eastern Cooperative Oncology Group (ECOG) PS scale. The DS measure was dichotomized to focus on good [ECOG 0-2] versus poor [ECOG 3-4] PS. We identified potential claims-based predictors, and estimated multivariate logistic regression models, with poor DS as the dependent measure, using a stepwise approach to select the optimal model. Construct validity was tested by determining whether the predicted DS measure generated by the model was a significant predictor of survival within a validation sample from the MCBS. One-tenth of beneficiaries met the definition for poor DS. The base model yielded high sensitivity (0.79) and specificity (0.92); positive predictive value=48.3% and negative predictive value=97.8%, c-statistic=0.92 and good model calibration. Adjusted poor claims-based DS was associated with an increased hazard of death (HR=3.53, 95% CI 3.18, 3.92). The ability to assess DS should improve covariate control and reduce indication bias in observational studies of cancer treatment and outcomes based on insurance claims.
    Journal of Geriatric Oncology 04/2013; 4(2):157-165. · 1.12 Impact Factor
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    ABSTRACT: IMPORTANCE Acute pancreatitis has significant morbidity and mortality. Previous studies have raised the possibility that glucagonlike peptide 1 (GLP-1)-based therapies, including a GLP-1 mimetic (exenatide) and a dipeptidyl peptidase 4 inhibitor (sitagliptin phosphate), may increase the risk of acute pancreatitis. OBJECTIVE To test whether GLP-1-based therapies such as exenatide and sitagliptin are associated with an increased risk of acute pancreatitis. We used conditional logistic regression to analyze the data. DESIGN Population-based case-control study. SETTING A large administrative database in the United States from February 1, 2005, through December 31, 2008. PARTICIPANTS Adults with type 2 diabetes mellitus aged 18 to 64 years. We identified 1269 hospitalized cases with acute pancreatitis using a validated algorithm and 1269 control subjects matched for age category, sex, enrollment pattern, and diabetes complications. MAIN OUTCOME MEASURE Hospitalization for acute pancreatitis. RESULTS The mean age of included individuals was 52 years, and 57.45% were male. Cases were significantly more likely than controls to have hypertriglyceridemia (12.92% vs 8.35%), alcohol use (3.23% vs 0.24%), gallstones (9.06% vs 1.34), tobacco abuse (16.39% vs 5.52%), obesity (19.62% vs 9.77%), biliary and pancreatic cancer (2.84% vs 0%), cystic fibrosis (0.79% vs 0%), and any neoplasm (29.94% vs 18.05%). After adjusting for available confounders and metformin hydrochloride use, current use of GLP-1-based therapies within 30 days (adjusted odds ratio, 2.24 [95% CI, 1.36-3.68]) and recent use past 30 days and less than 2 years (2.01 [1.37-3.18]) were associated with significantly increased odds of acute pancreatitis relative to the odds in nonusers. CONCLUSIONS AND RELEVANCE In this administrative database study of US adults with type 2 diabetes mellitus, treatment with the GLP-1-based therapies sitagliptin and exenatide was associated with increased odds of hospitalization for acute pancreatitis.
    JAMA Internal Medicine 02/2013; · 13.25 Impact Factor
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    ABSTRACT: IMPORTANCE Bariatric surgery is a well-documented treatment for obesity, but there are uncertainties about the degree to which such surgery is associated with health care cost reductions that are sustained over time. OBJECTIVE To provide a comprehensive, multiyear analysis of health care costs by type of procedure within a large cohort of privately insured persons who underwent bariatric surgery compared with a matched nonsurgical cohort. DESIGN Longitudinal analysis of 2002-2008 claims data comparing a bariatric surgery cohort with a matched nonsurgical cohort. SETTING Seven BlueCross BlueShield health insurance plans with a total enrollment of more than 18 million persons. PARTICIPANTS A total of 29 820 plan members who underwent bariatric surgery between January 1, 2002, and December 31, 2008, and a 1:1 matched comparison group of persons not undergoing surgery but with diagnoses closely associated with obesity. MAIN OUTCOME MEASURES Standardized costs (overall and by type of care) and adjusted ratios of the surgical group's costs relative to those of the comparison group. RESULTS Total costs were greater in the bariatric surgery group during the second and third years following surgery but were similar in the later years. However, the bariatric group's prescription and office visit costs were lower and their inpatient costs were higher. Those undergoing laparoscopic surgery had lower costs in the first few years after surgery, but these differences did not persist. CONCLUSIONS AND RELEVANCE Bariatric surgery does not reduce overall health care costs in the long term. Also, there is no evidence that any one type of surgery is more likely to reduce long-term health care costs. To assess the value of bariatric surgery, future studies should focus on the potential benefit of improved health and well-being of persons undergoing the procedure rather than on cost savings.
    JAMA surgery. 02/2013;
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    ABSTRACT: OBJECTIVES: . To determine if access to medical services differed by regions and to demonstrate the extent of the differences of adopting a claims-based risk-adjustment system versus a demographic model for regional resource allocation. METHODS: . The claims of a 1% random sample of Taiwan's National Health Insurance enrollees (N = 173 175) in 2002 was used. The number of visits and morbidity-adjusted resource consumption were calculated individually then collapsed regionally. Regional expected resource allocation was compared with actual consumption. RESULTS: . After controlling for diagnosis-based health measures, the average numbers of visits were stable across regions. Two models were consistent in showing over- or underutilization; the overall difference between two models in resource allocation was 5.8% at the district level. We observed strong urban overutilization and rural underutilization. CONCLUSIONS: . Access to medical services is similar across regions. The adoption of a diagnosis-based model over a demographic-adjusted budgeting method would affect resource allocation considerably.
    Asia-Pacific Journal of Public Health 01/2013; · 1.06 Impact Factor
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    ABSTRACT: OBJECTIVE: Negative interactions with healthcare providers may lead patients to switch physicians or "doctor shop." We hypothesized that overweight and obese patients would be more likely to doctor shop, and as a result, have increased rates of emergency department (ED) visits and hospitalizations as compared to normal weight nonshoppers. DESIGN AND METHODS: We combined claims data from a health plan in one state with information from beneficiaries' health risk assessments. The primary outcome was "doctor shopping," which we defined as having outpatient claims with ā‰„5 different primary care physicians (PCPs) during a 24-month period. The independent variable was standard NIH categories of weight by BMI. We performed multivariate logistic regression to evaluate the association between weight categories and doctor shopping. We conducted multivariate zero-inflated negative binominal regression to evaluate the association between weight-doctor shopping categories with counts of ED visits and hospitalizations. RESULTS: Of the 20,726 beneficiaries, the mean BMI was 26.3 kg m(-2) (SD 5.1), mean age was 44.4 years (SD 11.1) and 53% were female. As compared to normal weight beneficiaries, overweight beneficiaries had 23% greater adjusted odds of doctor shopping (OR 1.23, 95%CI 1.04-1.46) and obese beneficiaries had 52% greater adjusted odds of doctor shopping (OR 1.52, 95%CI 1.26-1.82). As compared to normal weight non-shoppers, overweight and obese shoppers had higher rates of ED visits (IRR 1.85, 95%CI 1.37-2.45; IRR 1.83, 95%CI 1.34-2.50, respectively), which persisted during within weight group comparisons (Overweight IRR 1.50, 95%CI 1.10-2.03; Obese IRR 1.54, 95%CI 1.12-2.11). CONCLUSION: Frequently changing PCPs may impair continuity and result in increased healthcare utilization.
    Obesity 11/2012; · 3.92 Impact Factor
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    ABSTRACT: Objectives: To test the validity of the adapted Diabetes Complications Severity Index (aDCSI), which does not include laboratory test results, as an indicator of diabetes severity. Study Design: Retrospective cohort study using 4 years of claims data from 7 health insurance plans. Methods: Individuals with diabetes mellitus and continuous enrollment were study subjects (N = 138,615). The 2 independent variables-the aDCSI score (sum of 7 diabetes complications graded by severity as 0, 1, or 2; range 0-13) and the aDCSI diabetes complication count (sum of 7 diabetes complications without severity grading; range 0-7)-were generated using only claims data. We evaluated the numbers of hospitalizations attributable to the aDCSI with Poisson regression models, both categorically and linearly. Results: The aDCSI score (risk ratio 1.39 to 6.10 categorically and 1.41 linearly) and diabetes complication count (risk ratio 1.67 to 9.11 categorically and 1.65 linearly) were both significantly positively associated with the number of hospitalizations over a 4-year period. Risk ratios from the aDCSI score were very similar to the risk ratios previously reported for the Diabetes Complications Severity Index (DCSI); the absolute difference between risk ratios ranged from 0.01 to 1.6 categorically and was 0.05 linearly. Conclusions: The aDCSI is a good measure of diabetes severity, given its ability to explain hospitalizations and its similar performance to the DCSI.
    The American journal of managed care 11/2012; 18(11):721-6. · 2.12 Impact Factor
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    ABSTRACT: This article examines the potential benefits of enhanced use of advanced practice registered nurses (APRNs) given health care workforce projections that predict an inadequate supply of certain types of providers. The conclusions of a systematic review comparing the effectiveness of care provided by APRNs with that of physicians alone or teams without APRNs indicate the viability of this approach. Allowing APRNs to assume roles that take full advantage of their educational preparation could mitigate the shortage of primary care physicians and improve care processes. The development of health care policy should be guided by patient-centric evidence rather than how care has been delivered in the past.
    Policy Politics &amp Nursing Practice 08/2012; 13(2):81-9.
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    Jonathan P Weiner
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    ABSTRACT: The digital revolution will have a profound impact on how physicians and health care delivery organizations interact with patients and the community at-large. Over the coming decades, face-to-face patient/doctor contacts will become less common and exchanges between consumers and providers will increasingly be mediated by electronic devices.In highly developed health care systems like those in Israel, the United States, and Europe, most aspects of the health care and consumer health experience are becoming supported by a wide array of technology such as electronic and personal health records (EHRs and PHRs), biometric & telemedicine devices, and consumer-focused wireless and wired Internet applications.In an article in this issue, Peleg and Nazarenko report on a survey they fielded within Israel's largest integrated delivery system regarding patient views on the use of electronic communication with their doctors via direct-access mobile phones and e-mail. A previous complementary paper describes the parallel perspectives of the physician staff at the same organization. These two surveys offer useful insights to clinicians, managers, researchers, and policymakers on how best to integrate e-mail and direct-to-doctor mobile phones into their practice settings. These papers, along with several other recent Israeli studies on e-health, also provide an opportunity to step back and take stock of the dramatic impact that information & communication technology (ICT) and health information technology (HIT) will have on clinician/patient communication moving forward.The main goals of this commentary are to describe the scope of this issue and to offer a framework for understanding the potential impact that e-health tools will have on provider/patient communication. It will be essential that clinicians, managers, policymakers, and researchers gain an increased understanding of this trend so that health care systems around the globe can adapt, adopt, and embrace these rapidly evolving digital technologies.
    Israel journal of health policy research. 08/2012; 1(1):33.
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    ABSTRACT: BACKGROUND: Improving care coordination is a national priority and a key focus of health care reforms. However, its measurement and ultimate achievement is challenging. OBJECTIVE: To test whether patients whose providers frequently share patients with one another-what we term 'care density'-tend to have lower costs of care and likelihood of hospitalization. DESIGN: Cohort study PARTICIPANTS: 9,596 patients with congestive heart failure (CHF) and 52,688 with diabetes who received care during 2009. Patients were enrolled in five large, private insurance plans across the US covering employer-sponsored and Medicare Advantage enrollees MAIN MEASURES: Costs of care, rates of hospitalizations KEY RESULTS: The average total annual health care cost for patients with CHF was $29,456, and $14,921 for those with diabetes. In risk adjusted analyses, patients with the highest tertile of care density, indicating the highest level of overlap among a patient's providers, had lower total costs compared to patients in the lowest tertile ($3,310 lower for CHF and $1,502 lower for diabetes, pā€‰<ā€‰0.001). Lower inpatient costs and rates of hospitalization were found for patients with CHF and diabetes with the highest care density. Additionally, lower outpatient costs and higher pharmacy costs were found for patients with diabetes with the highest care density. CONCLUSION: Patients treated by sets of physicians who share high numbers of patients tend to have lower costs. Future work is necessary to validate care density as a tool to evaluate care coordination and track the performance of health care systems.
    Journal of General Internal Medicine 06/2012; · 3.28 Impact Factor
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    ABSTRACT: In 2014, an estimated 15 million individuals who currently do not have health insurance, including many with chronic mental illness, are expected to obtain coverage through state insurance exchanges. The authors examined how two mechanisms in the Affordable Care Act (ACA), namely, risk adjustment and reinsurance, might perform to ensure the financial solvency of health plans that have a disproportionate share of enrollees with mental health conditions. Risk adjustment is an ACA provision requiring that a federal or state exchange move funds from insurance plans with healthier enrollees to plans with sicker enrollees. Reinsurance is a provision in which all plans in the state contribute to an overall pool of money that is used to reimburse costs to individual market plans for expenditures of any individual enrollee that exceed a high predetermined level. Using 2006--2007 claims data from a sample of private and public health plans, the authors compared expected health plan compensation under diagnosis-based risk adjustment with actual health care expenditures, under different assumptions for chronic mental health and medical conditions. Analyses were conducted with and without the addition of $100,000 reinsurance. Risk adjustment performed well for most plans. For some plans with a high share of enrollees with mental health conditions, underpayment was substantial enough to raise concern. Reinsurance appeared to be helpful in addressing the most serious underpayment problems remaining after risk adjustment. Risk adjustment performed similarly for health plan cohorts that had a disproportionate share of enrollees with chronic mental health and medical conditions. Cost models indicate that the regulatory provisions in the ACA requiring risk adjustment and reinsurance can help protect health plans covering treatment for mentally ill individuals against risk selection. This model analysis may be useful for advocates for individuals with mental illness in considering their own state's insurance exchange.
    American Journal of Psychiatry 05/2012; 169(7):704-9. · 14.72 Impact Factor
  • Jonathan P Weiner, Jinnet B Fowles, Kitty S Chan
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    ABSTRACT: Measures of provider success are the centerpiece of quality improvement and pay-for-performance programs around the globe. In most nations, these measures are derived from administrative records, paper charts and consumer surveys; increasingly, electronic patient record systems are also being used. We use the term 'e-QMs' to describe quality measures that are based on data found within electronic health records and other related health information technology (HIT). We offer a framework or typology for e-QMs and describe opportunities and impediments associated with the transition from old to new DATA SOURCES: If public and private systems of care are to effectively use HIT to support and evaluate health-care system quality and safety, the quality measurement field must embrace new paradigms and strategically address a series of technical, conceptual and practical challenges.
    International Journal for Quality in Health Care 04/2012; 24(3):200-5. · 1.79 Impact Factor
  • Medical care 03/2012; · 3.24 Impact Factor
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    Klaus W Lemke, Jonathan P Weiner, Jeanne M Clark
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    ABSTRACT: Hospitalizations are costly for health insurers and society. To develop and validate a predictive model for acute care hospitalization from administrative claims for a population including all age groups. We constructed a retrospective cohort study using a US health plan claims database, including annual person-level files with demographic markers, and morbidity and utilization measures. We developed and validated the model using separate data. The validation sample included 4.7 million persons enrolled for at least 6 months in 2006 and 1 or more months in 2007. Risk factors and outcome variables were obtained from administrative claims data using the Adjusted Clinical Group (ACG) system. Utilization variables were added, and models were fitted with multivariate logistic regression. A 3.2% of patients had a hospitalization during a 1-year period, and 20% of patients who had been hospitalized during the previous year were rehospitalized. Effect sizes of risk factors were modest with odds ratios <1.5. Odds ratios were greater than 1.5 for age ā‰„80 years, 3+ prior hospitalizations, 3+ emergency room visits, 20 ACG morbidity categories, and 40 diseases including high impact neoplasms, bipolar disorder, cerebral palsy, chromosomal anomalies, cystic fibrosis, and hemolytic anemia. Model performance of ACG hospitalization models was good (AUC=0.80) and superior to a prior hospitalization model (AUC=0.75) and a Charlson comorbidity hospitalization model (AUC=0.78). A validated population-based predictive model for hospital risk estimates individual risk for future hospitalization. The model could be useful to health plans and care managers.
    Medical care 02/2012; 50(2):131-9. · 3.24 Impact Factor
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    Jonathan P Weiner, Erin Trish, Chad Abrams, Klaus Lemke
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    ABSTRACT: The Affordable Care Act calls for the establishment of state-level health insurance exchanges. The viability and success of these exchanges will require effective risk-adjustment strategies to compensate for differences in enrollees' health status across health plans. This article describes why the Affordable Care Act could lead to favorable or adverse risk selection across plans. It reviews provisions in the act and recent proposed regulations intended to mitigate the problem of risk selection. We performed a simulation that showed that under the premium rating restrictions in the law, large incentives for insurers to attract healthier enrollees will be likely to persist-resulting in substantial overpayment to plans with very healthy enrollees and underpayment to plans with very sick members. We conclude that risk adjustment based on patients' diagnoses, such as will be in place from 2014 on, will yield payments to insurers that will be more accurate than what will come solely from the age-adjusted and other rating allowed by the act. We also describe additional challenges of implementing risk adjustment.
    Health Affairs 02/2012; 31(2):306-15. · 4.64 Impact Factor
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    ABSTRACT: Bariatric surgery is the most effective weight loss treatment, yet few studies have reported on short- and long-term outcomes postsurgery. Using claims data from seven Blue Cross/Blue Shield health plans serving seven states, we conducted a non-concurrent, matched cohort study. We followed 22,693 persons who underwent bariatric surgery during 2003-2007 and were enrolled at least 6 months before and after surgery. Using logistic regression, we compared serious and less serious adverse clinical outcomes, hospitalizations, planned procedures, and obesity-related co-morbidities between groups for up to 5 years. Relative to controls, surgery patients were more likely to experience a serious [odds ratio (OR) 1.9; 95% confidence interval (CI) 1.8-2.0] or less serious (OR 2.5, CI 2.4-2.7) adverse clinical outcome or hospitalization (OR 1.3, CI 1.3-1.4) at 1 year postsurgery. The risk remained elevated until 4 years postsurgery for serious events and 5 years for less serious outcomes and hospitalizations. Some complication rates were lower for patients undergoing laparoscopic surgery. Planned procedures, such as skin reduction, peaked in postsurgery year 2 but remained elevated through year 5. Surgery patients had a 55% decreased risk of obesity-related co-morbidities, such as type 2 diabetes, in the first year postsurgery, which remained low throughout the study (year 5: OR 0.4, CI 0.4-0.5). While bariatric surgery is associated with a higher risk of adverse clinical outcomes compared to controls, it also substantially decreased obesity-related co-morbidities during the 5-year follow-up.
    Obesity Surgery 01/2012; 22(5):749-63. · 3.10 Impact Factor
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    ABSTRACT: To test the usefulness of the Diabetes Complications Severity Index (DCSI) without laboratory test results in predicting healthcare costs, for potential use in disease management programs. Retrospective cohort study using up to 2 years of claims data from 7 health insurance plans. Individuals with diabetes mellitus and continuous enrollment were study subjects. The DCSI (sum of 7 diabetes complications graded by severity as 0, 1, or 2; range 0-13) and count of diabetes complications (sum of 7 diabetes complications without severity grading; range 0-7) were the main independent variables and were generated using only diagnostic codes. We analyzed 5 types of healthcare costs (ie, total costs, inpatient costs, hospital other costs, pharmacy costs, and professional costs) attributable to the DCSI and the complication count with linear regression models, both concurrently and prospectively. The DCSI without laboratory data was a better predictor of costs than was complication count (adjusted R2 of total costs: 0.095 vs 0.080). The DCSI explained concurrent costs better than future costs (adjusted R2 of total costs: 0.095 vs 0.019). There were important differences in healthcare utilization among people stratifi ed by DCSI scores: 5-fold and 3-fold differences in concurrent and prospective total costs, respectively, across 4 DCSI groups. The DCSI without laboratory data may be useful for stratifying individuals with diabetes into morbidity groups, which can be used for selection into disease management programs or for matching in observational research.
    The American journal of managed care 01/2012; 18(4):213-9. · 2.12 Impact Factor

Publication Stats

1k Citations
405.83 Total Impact Points

Institutions

  • 2004–2013
    • Johns Hopkins Bloomberg School of Public Health
      • Department of Health Policy and Management
      Baltimore, MD, United States
  • 1993–2013
    • Johns Hopkins University
      • • Department of Medicine
      • • Department of Surgery
      Baltimore, Maryland, United States
  • 2012
    • Johns Hopkins Medicine
      • Department of Health Policy and Management
      Baltimore, MD, United States
  • 2009–2012
    • Case Western Reserve University
      • Center for Health Care Research and Policy
      Cleveland, OH, United States
    • The Children's Hospital of Philadelphia
      • Department of Pediatrics
      Philadelphia, PA, United States
  • 2011
    • Sunnybrook Health Sciences Centre
      • Department of Evaluative Clinical Sciences
      Toronto, Ontario, Canada
    • University of Maryland, Baltimore
      Baltimore, Maryland, United States
    • University of Haifa
      • Faculty of Social Welfare and Health Sciences
      Haifa, Haifa District, Israel
  • 2003
    • Park Nicollet Health Services
      Minneapolis, Minnesota, United States
  • 2002
    • HealthPartners Institute for Education and Research
      Bloomington, Minnesota, United States
  • 1995
    • Harvard University
      Cambridge, Massachusetts, United States
    • Minneapolis Medical Research Foundation
      Minneapolis, Minnesota, United States
  • 1994–1995
    • Brandeis University
      • Schneider Institute for Health Policy
      Waltham, MA, United States