Engaging Payors and Primary Care Physicians Together in Improving Diabetes Prevention.

BACKGROUND: Type 2 diabetes can be prevented through lifestyle programs like the Diabetes Prevention Programs (DPP), but few people with prediabetes participate in them, in part because their insurance does not reliably cover DPPs. Prior studies have not focused on payor-level barriers. OBJECTIVE: To understand barriers to DPP uptake that exist and intersect at different levels (patients, PCPs, and payors) to inform strategies to improve diabetes prevention in primary care settings through interviews with PCPs and payors. DESIGN: From May 2020 to October 2021, we conducted remote, semi-structured interviews with PCPs and payors. PARTICIPANTS: PCPs were from primary care practices affiliated with one mid-Atlantic academic system. Payor leaders were from regional commercial, Medicare, and Medicaid plans. APPROACH: Using a standardized interview guide focused on barriers, facilitators, and potential intervention components, interviews were audio-recorded using Zoom and professionally transcribed. Two reviewers double-coded transcripts using the framework analytic approach. KEY RESULTS: We interviewed 16 PCPs from 13 primary care clinics and 7 payor leaders representing 6 insurance plans. Two themes emerged from PCP reports of patient-level barriers: (1) lack of programs and insurance coverage of resources to address nutrition and exercise and (2) inadequate resources to address social determinants of health that impact diabetes prevention. Among barriers PCPs faced, we identified two themes: (1) low PCP knowledge about DPPs and misperceptions of insurance coverage of DPPs and (2) inadequate clinical staff to address diabetes prevention. Barriers common to PCPs and payors included (1) absence of prediabetes quality measures and (2) inadequate engagement of PCPs and patients with payors. CONCLUSIONS: Discussions with PCPs and payors revealed systemic barriers that suggest important priorities to improve prediabetes clinical care, including universal coverage of DPPs, clarity about coverage benefits, data reporting and outreach by payors to PCPs, and adoption of appropriate prediabetes quality measures.

Racial/ethnic and socioeconomic disparities in the use of newer diabetes medications in the Look AHEAD study.

Background: Among patients with type 2 diabetes, minority racial/ethnic groups have a higher burden of cardiovascular disease, chronic kidney disease, and hypoglycaemia. These groups may especially benefit from newer diabetes medication classes, but high cost may limit access. We examined the association of race/ethnicity with the initiation of newer diabetes medications (GLP-1 receptor agonists, DPP-4 inhibitors, SGLT-2 inhibitors). Methods: We conducted a secondary analysis of the Look AHEAD (Action for Health in Diabetes) trial including participants with at least one study visit after April 28, 2005. Cox proportional hazards models were used to estimate the association between race/ethnicity and socioeconomic factors with time to initiation of any newer diabetes medication from April 2005 to February 2020. Models were adjusted for demographic and clinical characteristics. Findings: Among 4,892 participants, 63.6%, 15.7%, 12.6%, 5.2%, and 2.9% were White, Black, Hispanic, American Indian or Alaskan Native (AI/AN), or other race/ethnicity, respectively. During a median follow-up of 8.3 years, 2,180 (45.2%) participants were initiated on newer diabetes medications. Race/ethnicity was associated with newer diabetes medication initiation (p=.019). Specifically, initiation was lower among Black (HR 0.81, 95% CI 0.70 -0.94) and AI/AN participants (HR 0.51, 95% CI 0.26-0.99). Yearly family income was inversely associated with initiation of newer diabetes medications (HR 0.78, 95% CI 0.62-0.98) comparing the lowest and highest income groups. Findings were mostly driven by GLP-1 receptor agonists. Interpretation: These findings provide evidence of racial/ethnic disparities in the initiation of newer diabetes medications, independent of socioeconomic factors, which may contribute to worse health outcomes.

Development of a Mobile App for Ecological Momentary Assessment of Circadian Data: Design Considerations and Usability Testing.

BACKGROUND: Collecting data on daily habits across a population of individuals is challenging. Mobile-based circadian ecological momentary assessment (cEMA) is a powerful frame for observing the impact of daily living on long-term health. OBJECTIVE: In this paper, we (1) describe the design, testing, and rationale for specifications of a mobile-based cEMA app to collect timing of eating and sleeping data and (2) compare cEMA and survey data collected as part of a 6-month observational cohort study. The ultimate goal of this paper is to summarize our experience and lessons learned with the Daily24 mobile app and to highlight the pros and cons of this data collection modality. METHODS: Design specifications for the Daily24 app were drafted by the study team based on the research questions and target audience for the cohort study. The associated backend was optimized to provide real-time data to the study team for participant monitoring and engagement. An external 8-member advisory board was consulted throughout the development process, and additional test users recruited as part of a qualitative study provided feedback through in-depth interviews. RESULTS: After ≥4 days of at-home use, 37 qualitative study participants provided feedback on the app. The app generally received positive feedback from test users for being fast and easy to use. Test users identified several bugs and areas where modifications were necessary to in-app text and instructions and also provided feedback on the engagement strategy. Data collected through the mobile app captured more variability in eating windows than data collected through a one-time survey, though at a significant cost. CONCLUSIONS: Researchers should consider the potential uses of a mobile app beyond the initial data collection when deciding whether the time and monetary expenditure are advisable for their situation and goals.

Within-Trial Cost-Effectiveness of a Structured Lifestyle Intervention in Adults With Overweight/Obesity and Type 2 Diabetes: Results From the Action for Health in Diabetes (Look AHEAD) Study.

OBJECTIVE: To assess the cost-effectiveness (CE) of an intensive lifestyle intervention (ILI) compared with standard diabetes support and education (DSE) in adults with overweight/obesity and type 2 diabetes, as implemented in the Action for Health in Diabetes study. RESEARCH DESIGN AND METHODS: Data were from 4,827 participants during their first 9 years of study participation from 2001 to 2012. Information on Health Utilities Index Mark 2 (HUI-2) and HUI-3, Short-Form 6D (SF-6D), and Feeling Thermometer (FT), cost of delivering the interventions, and health expenditures was collected during the study. CE was measured by incremental CE ratios (ICERs) in costs per quality-adjusted life year (QALY). Future costs and QALYs were discounted at 3% annually. Costs were in 2012 U.S. dollars. RESULTS: Over the 9 years studied, the mean cumulative intervention costs and mean cumulative health care expenditures were $11,275 and $64,453 per person for ILI and $887 and $68,174 for DSE. Thus, ILI cost $6,666 more per person than DSE. Additional QALYs gained by ILI were not statistically significant measured by the HUIs and were 0.07 and 0.15, respectively, measured by SF-6D and FT. The ICERs ranged from no health benefit with a higher cost based on HUIs to $96,458/QALY and $43,169/QALY, respectively, based on SF-6D and FT. CONCLUSIONS: Whether ILI was cost-effective over the 9-year period is unclear because different health utility measures led to different conclusions.

You are What You Think Your Social Network Eats: Public Housing, Social Networks, and Fast-Food Consumption.

High-sodium diets (e.g., fast-food intake, FF) may contribute to increased hyper-tension risk among low-income populations. We examined the association between FF intake and perceived social-network member FF intake among Baltimore public housing residents. We analyzed 2014-2015 cross-sectional data. Our dependent variable was FF intake (eating FF weekly versus not), and our independent variable was perceiving one or more network member eating FF weekly. We used multivariable Poisson regression with robust variance, adjusted for individual and network covariates. The 266 public housing residents had mean age 44.5 years: 86.1% women, 95.5% African American, 56.8% hypertension, and 42.8% who ate FF weekly. Residents were significantly more likely to eat FF weekly if they perceived that their network contained one or more members who consumed FF weekly (relative risk 1.50, 95%CI 1.05-2.14, p=.02). Given the association between personal and social network consumption of FF weekly, further investigation may be warranted of novel social network interventions for dietary behavior change.

Cost of behavioral weight loss programs implemented in clinical practice: The POWER trial at Johns Hopkins.

Obesity presents an important public health problem that affects more than a third of the U.S. adult population and that is associated with increased morbidity, mortality, and costs. Previously, we documented that two primary care-based weight loss interventions were clinically effective. To encourage the implementation of and reimbursement for these interventions, we evaluated their relative cost-effectiveness. We performed a cost analysis of the Practice-based Opportunities for Weight Reduction (POWER) trial, a three-arm trial that enrolled 415 patients with obesity from six primary care practices. Trial participants were randomized to a control arm, an in-person support intervention, or a remote support intervention; in the two intervention arms, behavioral interventions were delivered over 24 months, in two phases. Weight loss was measured at 6, 12, and 24 months. Using timesheets and empirical data, we evaluated the cost of the in-person and remote support interventions from the perspective of a health care system delivering the interventions. A univariate sensitivity analysis was conducted to evaluate uncertainty around model assumptions. All comparisons were tested using independent t-tests. Cost of the in-person intervention was higher at 6 months ($113 per participant per month and $117 per kg lost) than the remote support intervention ($101 per participant per month and $99 per kg lost; p < .001). Costs were also higher for the in-person support intervention at 24 months ($73 per participant per month and $342 per kg lost) than for the remote support intervention ($53 per participant per month and $275 per kg lost; p < .001). In the sensitivity analyses, cost ranged from $274/kg lost to $456/kg lost for the in-person support intervention and from $218/kg to $367/kg lost for the remote support intervention. A primary care weight loss intervention administered remotely was relatively more cost-effective than an in-person intervention. Expanding the scope of reimbursable programs to include other cost-effective interventions could help ensure that a broader range of patients receive the type of support needed.

Understanding Primary Care Patients' Self-weighing Habits: Cohort Analysis from the PaTH Clinical Data Research Network.

BACKGROUND: Greater than 60% of adults have overweight or obesity. Self-weighing is an effective weight loss and weight maintenance tool. However, little is known about self-weighing habits among the primary care patient population. Our objective was to examine the frequency of patient-reported self-weighing, and to evaluate the associations of self-weighing with demographic characteristics and self-monitoring behaviors. METHODS: We conducted an analysis of survey data collected as part of the PaTH Clinical Data Research Network, which recruited a cohort of 1,021 primary care patients at 4 academic medical centers. Patients of all body mass index (BMI) categories were included. RESULTS: Response rate of 6-month survey was 727 (71%). The mean age was 56 years, and most were female (68%), White (78%), college graduates (66%), and employed/retired (85%). The mean BMI was 30.2 kg/m2, 80% of participants had a BMI â‰§ 25 kg/m2. Of patients with BMI â‰§ 25 kg/m2, 35% of participants self-weighed weekly and 23% daily. Participants who reported self-weighing at least weekly were more likely to be older (59 vs 54 years, p < 0.01), married (p = 0.01), college graduates (p = 0.03), White (p < 0.01), and employed vs disabled/unemployed (p < 0.01). Patients who self-weighed daily had a lower BMI (29 kg/m2 vs 31 kg/m2, p = 0.04). Patients who tracked exercise or food intake were more likely to self-weigh daily (p < 0.01), as were patients wanting to lose or maintain weight (p < 0.01). CONCLUSIONS: Despite its potential for primary and secondary obesity prevention, only 35% of primary care patients with overweight or obesity engage in self-weighing weekly and less than a quarter (23%) self-weigh daily. Socioeconomic status appears to be a factor influencing regular self-weighing in this population, potentially contributing to greater health disparities in obesity rates. Patients who self-weighed daily had a lower BMI, suggesting that it may play a role in primary prevention of obesity. More work is needed to explore self-weighing among patients.

Influence of subsidies and promotional strategies on outcomes in a beneficiary-based commercial weight-loss programme.

To determine whether initial engagement, continued participation, and weight loss vary by subsidy and promotional strategies in a beneficiary-based, commercial weight-loss programme. We conducted a retrospective analysis of data from 2013 to 2016. Our dependent variables included initial engagement (≥1 calls; ≥2 weights), coach calls and weight change. Our independent variables were subsidy strategy (total subsidy (n = 9) vs cost sharing (n = 3)) and combination of promotional-subsidy strategies (mixed campaign + total subsidy (n = 6) vs mass media + total subsidy (n = 3)). We used logistic and linear regression analyses adjusted for beneficiary factors and clustering by organization. From 12 participating organizations, 26 068 beneficiaries registered of which 6215 initially engaged. Cost sharing was associated with significantly greater initial engagement as compared to total subsidy (OR 3.73, P < 0.001); however, no significant between-group differences existed in calls or weight change. Mass media + total subsidy group had significantly greater calls and weight loss at 12 months compared to mixed campaign + total subsidy (-2.6% vs -1.8%, P = 0.04). Cost sharing may promote greater initial engagement, although does not contribute to better participation or weight loss relative to total subsidy. If organizations elect total subsidy, then pairing this strategy with a mass media campaign may promote greater participation and weight loss among beneficiaries.

Sex Differences Among Career Development Awardees in the Attainment of Independent Research Funding in a Department of Medicine.

BACKGROUND: National data suggest that women are overall less likely than men to attain independent research funding. However, it remains unclear whether such sex differences are also observed in academic institutions that have integrated diversity in the workplace as a priority. METHODS: During 1999-2008, all National Institutes of Health (NIH) Career Development (K01, K08, or K23) awardees in the Department of Medicine at Johns Hopkins University School of Medicine were identified to investigate differences in the attainment of independent funding by sex, including NIH Research Project Grant (R01) or equivalent awards, (U01, P01, P50), and any R award (also R03, R21, R34) through 2012. RESULTS: A similar number of men (n = 49) and women (n = 43) received a K award. There were no significant sex differences in attaining an R01/equivalent award or any R award. The median time to attaining the first R01/equivalent award was similar for men and women (5.6 vs. 5.3 years, p = 0.93). The actuarial rate of R01/equivalent award attainment at 10 years was 64% overall (56% among men vs. 74% among women; log-rank p = 0.41). For any R award, the rate was 72% overall (70% among men vs. 76% among women; log-rank p = 0.63). In Cox proportional hazards models, adjusting for race/ethnicity, age, Doctor of Medicine (MD) degree, and funding period, sex was not an independent predictor of R01/equivalent or any R award attainment. Interestingly, black race and/or Hispanic ethnicity significantly predicted any R award attainment (adjusted hazard ratio [HR] = 2.34, 95% confidence interval [CI] 1.02-5.37). CONCLUSIONS: No sex differences were found in the attainment of independent funding by K awardees in our study. Future studies to investigate the impact of specific diversity initiatives on subsequent success in attaining independent research funding are needed.

Willingness to pay for continued delivery of a lifestyle-based weight loss program: The Hopkins POWER trial.

OBJECTIVE: In behavioral studies of weight loss programs, participants typically receive interventions free of charge. Understanding an individual's willingness to pay (WTP) for weight loss programs could be helpful when evaluating potential funding models. This study assessed WTP for the continuation of a weight loss program at the end of a weight loss study. METHODS: WTP was assessed with monthly coaching contacts at the end of the two-year Hopkins POWER trial. Interview-administered questionnaires determined the amount participants were willing to pay for continued intervention. Estimated maximum payment was calculated among those willing to pay and was based on quantile regression adjusted for age, body mass index, race, sex, household income, treatment condition, and weight change at 24 months. RESULTS: Among the participants (N=234), 95% were willing to pay for continued weight loss intervention; the adjusted median payment was $45 per month. Blacks had a higher adjusted median WTP ($65/month) compared to Non-Blacks ($45/month), P=0.021. CONCLUSIONS: A majority of participants were willing to pay for a continued weight loss intervention with a median monthly amount that was similar to the cost of commercial weight loss programs.

Impact of an intensive lifestyle intervention on use and cost of medical services among overweight and obese adults with type 2 diabetes: the action for health in diabetes.

OBJECTIVE: To assess the relative impact of an intensive lifestyle intervention (ILI) on use and costs of health care within the Look AHEAD trial. RESEARCH DESIGN AND METHODS: A total of 5,121 overweight or obese adults with type 2 diabetes were randomly assigned to an ILI that promoted weight loss or to a comparison condition of diabetes support and education (DSE). Use and costs of health-care services were recorded across an average of 10 years. RESULTS: ILI led to reductions in annual hospitalizations (11%, P = 0.004), hospital days (15%, P = 0.01), and number of medications (6%, P < 0.001), resulting in cost savings for hospitalization (10%, P = 0.04) and medication (7%, P < 0.001). ILI produced a mean relative per-person 10-year cost savings of $5,280 (95% CI 3,385-7,175); however, these were not evident among individuals with a history of cardiovascular disease. CONCLUSIONS: Compared with DSE over 10 years, ILI participants had fewer hospitalizations, fewer medications, and lower health-care costs.

Utilization of primary and obstetric care after medically complicated pregnancies: an analysis of medical claims data.

BACKGROUND: Because pregnancy complications, including gestational diabetes mellitus (GDM) and hypertensive disorders in pregnancy, are risk factors for diabetes and cardiovascular disease, post-delivery follow-up is recommended. OBJECTIVE: To determine predictors of post-delivery primary and obstetric care utilization in women with and without medical complications. RESEARCH DESIGN: Five-year retrospective cohort study using commercial and Medicaid insurance claims in Maryland. SUBJECTS: 7,741 women with a complicated pregnancy (GDM, hypertensive disorders and pregestational diabetes mellitus [DM]) and 23,599 women with a comparison pregnancy. MEASURES: We compared primary and postpartum obstetric care utilization rates in the 12 months after delivery between the complicated and comparison pregnancy groups. We conducted multivariate logistic regression to assess the association between pregnancy complications, sociodemographic predictor variables and utilization of care, stratified by insurance type. RESULTS: Women with a complicated pregnancy were older at delivery (p < 0.001), with higher rates of cesarean delivery (p < 0.0001) and preterm labor or delivery (p < 0.0001). Among women with Medicaid, 56.6% in the complicated group and 51.7% in the comparison group attended a primary care visit. Statistically significant predictors of receiving a primary care visit included non-Black race, older age, preeclampsia or DM, and depression. Among women with commercial health insurance, 60.0% in the complicated group and 49.5% in the comparison group attended a primary care visit. Pregnancy complication did not predict a primary care visit among women with commercial insurance. CONCLUSIONS: Women with pregnancy complications were more likely to attend primary care visits post-delivery compared to the comparison group, but overall visit rates were low. Although Medicaid expansion has potential to increase coverage, innovative models for preventive health services after delivery are needed to target women at higher risk for chronic disease development.

Change in claims-based diabetes medications is a diabetes improvement indicator.

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.

Impact of bariatric surgery on health care costs of obese persons: a 6-year follow-up of surgical and comparison cohorts using health plan data.

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.

Development and validation of a model for predicting inpatient hospitalization.

BACKGROUND: Hospitalizations are costly for health insurers and society. OBJECTIVES: To develop and validate a predictive model for acute care hospitalization from administrative claims for a population including all age groups. RESEARCH DESIGN: 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. PARTICIPANTS: The validation sample included 4.7 million persons enrolled for at least 6 months in 2006 and 1 or more months in 2007. MEASURES: 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. RESULTS: 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 ≥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). CONCLUSIONS: 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.

Impact of bariatric surgery on health care utilization and costs among patients with diabetes.

BACKGROUND: The effect of bariatric surgery on health care utilization and costs among individuals with type 2 diabetes remains unclear. OBJECTIVE: To examine health care utilization and costs in an insured cohort of individuals with type 2 diabetes after bariatric surgery. RESEARCH DESIGN: Cohort study derived from administrative data from 2002 to 2008 from 7 Blue Cross Blue Shield Plans. PARTICIPANTS: Seven thousand eight hundred six individuals with type 2 diabetes who had bariatric surgery. MEASURES: Cost (inpatient, outpatient, pharmacy, and others) and utilization (number of inpatient days, outpatient visits, specialist visits). RESULTS: Compared with presurgical costs, the ratio of hospital costs (excluding the initial surgery), among beneficiaries who had any hospital costs, was higher in years 2 through 6 of the postsurgery period and increased over time [post 1: odds ratio (OR)=0.58; 95% confidence interval (CI), 0.50-0.67; post 6: OR=3.43; 95% CI, 2.60-4.53]. In comparison with the presurgical period, the odds of having any health care costs was lower in the postsurgery period and remained relatively flat over time. Among those with hospitalizations, the adjusted ratio of inpatient days was higher after surgery (post 1: OR=1.05; 95% CI, 0.94-1.16; post 6: OR=2.77; 95% CI, 1.57-4.90). Among those with primary care visits, the adjusted OR was lower after surgery (post 1: OR=0.80; 95% CI, 0.78-0.82; post 6: OR=0.66; 95% CI, 0.57-0.76). CONCLUSIONS: : In the 6 years after surgery, individuals with type 2 diabetes did not have lower health care costs than before surgery.

Surgical site infections and cost in obese patients undergoing colorectal surgery.

OBJECTIVES: To measure the effect of obesity on surgical site infection (SSI) rates and to define the cost of SSIs in patients undergoing colorectal surgery. DESIGN, SETTING, AND PATIENTS: This is a retrospective cohort study of 7020 colectomy patients using administrative claims data from 8 Blue Cross and Blue Shield insurance plans. Patients who had a total or segmental colectomy for colon cancer, diverticulitis, or inflammatory bowel disease between January 1, 2002, and December 31, 2008, were included. MAIN OUTCOME MEASURES: We compared 30-day SSI rates among obese and nonobese patients and calculated total costs from all health care claims for 90 days following surgery. Multivariate logistic regression was performed to identify risk factors for SSIs. RESULTS: Obese patients had an increased rate of SSI compared with nonobese patients (14.5% vs 9.5%, respectively; P < .001). Independent risk factors for these infections were obesity (odds ratio = 1.59; 95% confidence interval, 1.32-1.91) and open operation as compared with a laparoscopic procedure (odds ratio = 1.57; 95% confidence interval, 1.25-1.97). The mean total cost was $31,933 in patients with infection vs $14,608 in patients without infection (P < .001). Total length of stay was longer in patients with infection than in those without infection (mean, 9.5 vs 8.1 days, respectively; P < .001), as was the probability of hospital readmission (27.8% vs 6.8%, respectively; P < .001). CONCLUSIONS: Obesity increases the risk of an SSI after colectomy by 60%, and the presence of infection increases the colectomy cost by a mean of $17,324. Pay-for-performance policies that do not account for this increased rate of SSI and cost of caring for obese patients may lead to perverse incentives that could penalize surgeons who care for this population.

Morbidity trajectories as predictors of utilization: multi-year disease patterns in Taiwan's national health insurance program.

BACKGROUND: Little is known about how morbidity levels progress over time and the implications of these morbidity trajectories for healthcare utilization. OBJECTIVES: To identify and compare characteristics of people in different morbidity trajectories and to evaluate how morbidity trajectories impact the performance of diagnostic risk-adjustment models. RESEARCH DESIGN: Morbidity trajectories were derived from 3-year (2002 to 2004) of claims from a national insurance system. These trajectories, with or without 2004 claims-based risk adjusters developed from the Adjusted Clinical Group case-mix system, were used to explain medical utilization in 2005. SUBJECTS: A random sample of Taiwanese National Health Insurance beneficiaries continuously enrolled from 2002 to 2005 (n=147,892). MEASURES: Adjusted R of 5 types of healthcare expenditures. RESULTS: On the basis of naturally occurring patterns, we identified 6 morbidity trajectory groups. People assigned to different trajectory groups have distinct demographics and medical utilization. The effect of adding morbidity trajectory indicators differed substantially by the comprehensiveness of baseline risk-adjustment models: the increase in adjusted R ranged from 0.3% in the most comprehensive model to 5.7% in the demographics model. CONCLUSIONS: A simple morbidity trajectory classification over a 3-year period is almost as powerful a predictor of prospective medical utilization as more comprehensive baseline risk adjusters. It may be unnecessary to construct longitudinal morbidity trajectories if a comprehensive baseline model was adopted, especially for healthcare systems without the stability of continuous enrollment.

Medication utilization and annual health care costs in patients with type 2 diabetes mellitus before and after bariatric surgery.

OBJECTIVE: To examine the relationship of bariatric surgery with the use of diabetes medications and with total health care costs in patients with type 2 diabetes mellitus. DESIGN: We studied 2235 adults with type 2 diabetes and commercial health insurance who underwent bariatric surgery in the United States during a 4-year period from January 1, 2002, through December 31, 2005. We used administrative claims data to measure the use of diabetes medications at specified time intervals before and after surgery and total median health care costs per year. SETTING: Seven states in the Blue Cross/Blue Shield Obesity Care Collaborative. PATIENTS: Two thousand two hundred thirty-five patients with type 2 diabetes mellitus who underwent bariatric surgery. RESULTS: Surgery was associated with elimination of diabetes medication therapy in 1669 of 2235 patients (74.7%) at 6 months, 1489 of 1847 (80.6%) at 1 year, and 906 of 1072 (84.5%) at 2 years after surgery. Reduction of use was observed in all classes of diabetes medications. The median cost of the surgical procedure and hospitalization was $29,959. In the 3 years following surgery, total annual health care costs per person increased by 9.7% ($616) in year 1 but then decreased by 34.2% ($2179) in year 2 and by 70.5% ($4498) in year 3 compared with a preoperative annual cost of $6376 observed from 1 to 2 years before surgery. CONCLUSIONS: Bariatric surgery is associated with reductions in the use of medication and in overall health care costs in patients with type 2 diabetes. Health insurance should cover bariatric surgery because of its health and cost benefits.

Development of a claims-based risk score to identify obese individuals.

Obesity is underdiagnosed, hampering system-based health promotion and research. Our objective was to develop and validate a claims-based risk model to identify obese persons using medical diagnosis and prescription records. We conducted a cross-sectional analysis of de-identified claims data from enrollees of 3 Blue Cross Blue Shield plans who completed a health risk assessment capturing height and weight. The final sample of 71,057 enrollees was randomly split into 2 subsamples for development and validation of the obesity risk model. Using the Johns Hopkins Adjusted Clinical Groups case-mix/predictive risk methodology, we categorized study members' diagnosis (ICD) codes. Logistic regression was used to determine which claims-based risk markers were associated with a body mass index (BMI) > or = 35 kg/m(2). The sensitivities of the scores > or =90(th) percentile to detect obesity were 26% to 33%, while the specificities were >90%. The areas under the receiver operator curve ranged from 0.67 to 0.73. In contrast, a diagnosis of obesity or an obesity medication alone had very poor sensitivity (10% and 1%, respectively); the obesity risk model identified an additional 22% of obese members. Varying the percentile cut-point from the 70(th) to the 99(th) percentile resulted in positive predictive values ranging from 15.5 to 59.2. An obesity risk score was highly specific for detecting a BMI > or = 35 kg/m(2) and substantially increased the detection of obese members beyond a provider-coded obesity diagnosis or medication claim. This model could be used for obesity care management and health promotion or for obesity-related research.