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OBJECTIVES To determine whether elimination of co-pays for prescription drugs affects medication adherence and total health care spending. STUDY DESIGN Retrospective comparative study. METHODS We conducted a difference-in-differences comparison in the year before and after expansion of a Zero Dollar Co-pay (ZDC) prescription drug benefit in commercially insured Louisiana residents. Blue Cross and Blue Shield of Louisiana members with continuous disease management program enrollment were analyzed, of whom 6463 were enrolled in the ZDC program and 1821 were controls who were ineligible because their employers did not opt in. RESULTS After ZDC expansion, medication adherence fell in the control group and rose in the ZDC group, with a relative increase of 2.1 percentage points (P = .002). Medical spending fell by $71 per member per month (PMPM) (P = .027) in the ZDC group relative to controls. Overall, there was no significant increase in the cost of drugs between treatment and controls. However, when drugs were further categorized, there was a significant increase of $8 PMPM for generic drugs and no significant difference for brand name drugs. Comparisons of medication adherence rates by household income showed the largest relative increase post ZDC expansion among low-income members. CONCLUSIONS Elimination of co-pays for drugs indicated to treat chronic illnesses was associated with increases in medication adherence and reductions in overall spending of $63. Benefit designs that eliminate co-pays for patients with chronic illnesses may improve adherence and reduce the total cost of care.

AIM To compare the cardiovascular risks between users and non-users of sodium-glucose co-transporter-2 (SGLT2) inhibitors based on electronic medical record data from a large integrated healthcare system in South Louisiana. MATERIALS AND METHODS Demographic, anthropometric, laboratory and medication prescription information for patients with type 2 diabetes who were new users of SGLT2 inhibitors, either as initial treatments or as add-on treatments, were obtained from electronic health records. Mediation analysis was performed to evaluate the association of use of SGLT2 inhibitors and changes of metabolic risk factors with the risk of incident ischaemic heart disease. RESULTS A total of 5338 new users of SGLT2 inhibitors were matched with 13 821 non-users. During a mean follow-up of 3.26 years, 2302 incident cases of ischaemic heart disease were defined. After adjusting for multiple confounding factors, patients using SGLT2 inhibitors had a lower risk of incident ischaemic heart disease compared to patients not using SGLT2 inhibitors (hazard ratio [HR] 0.63, 95% confidence interval [CI] 0.54-0.73). Patients using SGLT2 inhibitors also had a lower risk of incident ischaemic heart disease within 6 months (HR 0.36, 95% CI 0.25-0.44), 12 months (HR 0.40, 95% CI 0.32-0.49), 24 months (HR 0.53, 95% CI 0.43-0.60) and 36 months (HR 0.65, 95% CI 0.54-0.73), respectively. Reductions in systolic blood pressure partly mediated lowering risk of ischaemic heart disease among patients using SGLT2 inhibitors. CONCLUSIONS The real-world data in the present study show the contribution of SGLT2 inhibitors to reducing risk of ischaemic heart disease, and their benefits beyond glucose-lowering.

OBJECTIVES Although pharmacy benefit carve-outs are promoted as a cost-containment tool, their impact on medical spending is not well understood. We compare the health care spending of Blue Cross and Blue Shield of Louisiana (BCBSLA) members covered by an integrated ("carved-in") pharmacy benefit with that of members covered under a pharmacy benefit carve-out. STUDY DESIGN Matched, longitudinal cohort study. METHODS We identified members with coverage through an employer contracting for administrative services only (ie, self-insured) and determined whether they received a pharmacy benefit through BCBSLA. We matched members with and without integrated benefits using a baseline year and compared their medical spending trajectories in 3 subsequent years. These comparisons were repeated in the subset of patients with chronic comorbidities. RESULTS Among patients with chronic illnesses, relative growth in per-member per-month (PMPM) medical spending was significantly lower in the integrated benefit group by the second and third follow-up years. Neither the level nor the growth of PMPM medical spending significantly differed in the full population sample, although point estimates suggest that the integrated benefit members may be on a lower cost growth trajectory over time. CONCLUSIONS Members with chronic illnesses receiving an integrated pharmacy benefit experienced slower medical cost growth compared with members covered by a pharmacy carve-out. Group leaders and brokers should consider the additional cost savings achieved by integrated pharmacy benefits when comparing the total costs of carve-in vs carve-out prescription drug programs.

Importance COVID-19 has been associated with excess mortality among patients not diagnosed with COVID-19, suggesting disruption of acute health care provision may play a role. Objective To determine the degree of declines in emergency department (ED) visits attributable to COVID-19 and determine whether these declines were concentrated among patients with fewer comorbidities and lower severity visits. Design We conducted a differences-in-differences analysis of all commercial health insurance claims for ED visits in the first 20 weeks of 2018, 2019, and 2020. The intervention period began March 9 (week 11) of 2020, following state stay-at-home orders. Setting We analyzed claims from Blue Cross Blue Shield of Louisiana (BCBSLA), located in a state with an early US COVID-19 outbreak. Visit and patient risk was assessed through comorbidities previously described as increasing the risk of COVID-19 decompensation, the hospital location's COVID-19 outbreak status, and the Ambulatory Care Sensitive Condition algorithm. Participants The study population comprised all ED visits from all BCBSLA members, whether admitted or discharged. There were 332,917 ED visits over the study period. The study population spanned member demographics including sex, age, and geography. Uninsured adults were not included due to data limitations. Exposures The COVID-19 outbreak beginning March 9, 2020 in Louisiana. Main outcomes and measures The main outcome of interest for this analysis is the difference (percent change) in all ED visits, categorized as either respiratory or non-respiratory, from week 1-20 in 2019 and week 1-10 in 2020, compared to week 11-20 in 2020. Results In this differences-in-differences study using data from a commercial health insurer, we found that non-respiratory ED visits declined by 39%, whereas respiratory visits did not experience a significant decline. Visits that were potentially deferrable or from lower risk patient populations showed greater declines, but even high-risk patients and non-avoidable visits experienced large declines in non-respiratory ED visits. Non-respiratory ED visits declined by only 18% in areas experiencing COVID outbreak. Conclusions and relevance COVID-19 has resulted in significant avoidance of ED care, comprising a mix of deferrable and high severity care. Hospital and public health pronouncements should emphasize appropriate care seeking.

AIM: To investigate the association between visit-to-visit HbA1c variability and the risk of cardiovascular disease in patients with type 2 diabetes. MATERIALS AND METHODS: We performed a retrospective cohort study of 29 260 patients with at least four HbA1c measurements obtained within 2 years of their first diagnosis of type 2 diabetes. Different HbA1c variability markers were calculated, including the standard deviation (SD), coefficient of variation (CV) and adjusted SD. Cox proportional hazards regression models were used to estimate the association of these HbA1c variability markers with incident cardiovascular disease. RESULTS: During a mean follow-up of 4.18 years, a total of 3746 incident cardiovascular disease cases were diagnosed. Multivariate-adjusted hazard ratios for cardiovascular disease across the first, second, third and fourth quartiles of HbA1c SD values were 1.00, 1.30 (95% confidence interval [CI] 1.18–1.42), 1.40 (95% CI 1.26–1.55) and 1.59 (95% CI 1.41–1.77) (P for trend

Aims: This study compares the cardiovascular benefits between SGLT2 inhibitors and other glucose-lowering drugs (oGLDs) based on electronic medical record data from a large integrated delivery health system in South Louisiana. Materials and Methods: Demographic, anthropometric, laboratory and medication prescription information for patients with type 2 diabetes who were new users of SGLT2 inhibitors either as initial treatments or as add-on treatments were obtained from electronic health records. Mediation analysis was performed in demonstrating the association of use of SGLT2 inhibitors and changes of metabolic risk factors with the risk of incident coronary heart disease. Results: A total of 5,338 new users of SGLT2 inhibitors were matched with 13,821 patients using oGLDs. During a mean follow up of 3.26 years, 2,303 incident cases of coronary heart disease were defined. After adjusting for multiple confounding factors, patients using SGLT2 inhibitors had a lower risk of incident coronary heart disease compared to patients using oGLDs (hazard ratio [HR] 0.63; 95% confidence interval [CI] 0.55-0.72). Patients using SGLT2 inhibitors also had a lower risk of incident coronary heart disease within 6 months (HR 0.32; 95% CI 0.23-0.43), 12 months (HR 0.38; 95% CI0.31-0.48), 24 months (HR 0.49; 95% CI 0.41-0.59) and 36 months (HR 0.59; 95% CI 0.51-0.69), respectively. Reductions in systolic blood pressure attributed the lower risk of coronary heart disease among patients using SGLT2 inhibitors. Conclusions: Evidence from real world data indicated the contribution of SGLT2 inhibitors to reducing risk of coronary heart disease, as well as the benefits beyond glucose-lowering. Disclosure Y. Shen: None. J. Zhou: None. L. Shi: None. E. Nauman: None. P.T. Katzmarzyk: None. E.G. Price-Haywood: None. S. Chu: None. S. Yang: None. A.N. Bazzano: None. S. Nigam: None. G. Hu: None.

Background and Purpose— Few studies have assessed the association of HDL (high-density lipoprotein) cholesterol with stroke risk among patients with type 2 diabetes mellitus. We aimed to investigate the association of HDL cholesterol with total and type-specific stroke risk in patients with type 2 diabetes mellitus. Methods— We performed a retrospective cohort study of 27 113 blacks and 40 431 whites with type 2 diabetes mellitus. Cox proportional hazards regression models were used to estimate the association of different levels of HDL cholesterol with stroke risk. Results— During a mean follow-up period of 3.0 years, 8496 patients developed stroke (8048 ischemic and 448 hemorrhagic). Multivariable-adjusted hazard ratios across levels of HDL at baseline (P trend P trend P trend =0.021) for hemorrhagic stroke, respectively. When we used an updated mean value of HDL cholesterol, the inverse association of HDL cholesterol with stroke risk did not change. This inverse association was consistent among patients of different ages, races, sexes, body mass index, hemoglobin A1c levels, never and past or current smokers, and patients with and without using glucose-lowering, cholesterol-lowering, or antihypertensive agents. Conclusions— The present study found consistent inverse associations between HDL cholesterol and the risk of total, ischemic and hemorrhagic stroke among patients with type 2 diabetes mellitus.

Context Very few studies focused on the association between body mass index (BMI) and stroke risk among patients with diabetes. Objective We aimed to investigate the association between BMI and stroke risk in patients with type 2 diabetes. Design Demographic, anthropometric, laboratory, and medication information were extracted from the National Patient-Centered Clinical Research Network common data model. Participants We performed a retrospective cohort study of 67 086 patients with type 2 diabetes. Main Outcome Measures Incident stroke including both ischemic and hemorrhagic stroke were defined. Results During a mean follow up of 3.74 years. 8918 incident stroke events occurred. Multivariable-adjusted hazard ratios across different categories of BMI at baseline (18.5–24.9 [reference group], 25.0–29.9, 30.0–34.9, 35.0–39.9, and ≥40 kg/m2) were 1.00, 0.92, 0.85, 0.74, and 0.63 (Ptrend Conclusion The present study found an inverse association between BMI and the risk of total, ischemic, and hemorrhagic stroke among patients with type 2 diabetes. More clinical and molecular insights are still needed in explaining these findings.

Background and Purpose The association between hemoglobin A1c (HbA1c) and stroke risk along with its subtypes is rarely reported. We aimed to investigate the association between HbA1c and the risk of incident stroke in patients with type 2 diabetes based on real world data from three healthcare systems.Methods We performed a retrospective cohort study of 27,113 African Americans and 40,431 whites with type 2 diabetes. Demographic, anthropometric, laboratory, and medication information were abstracted from the National Patient-Centered Clinical Research Network common data model. Incident stroke events including both ischemic and hemorrhagic stroke were defined.Results During a mean follow-up period of 3.79±1.68 years, 7,735 patients developed stroke (6,862 ischemic and 873 hemorrhagic). Multivariable-adjusted hazard ratios across levels of HbA1c at baseline (Ptrend Ptrend Ptrend=0.002) for hemorrhagic stroke. When we used an updated mean value of HbA1c, the U-shaped association of HbA1c with stroke risk did not change. This U-shaped association was consistent among patients of different subgroups. The U-shaped association was more pronounced among patients taking antidiabetic, lipid-lowering, and antihypertensive medications compared with those without these medications.Conclusions These data suggest that diabetes management may have to be individualized according to the guideline recommendations rather than intensively attempting to lower HbA1c.

Clinical findings regarding the association between hemoglobin A1c (HbA1c) and stroke risk remain inconclusive, especially among patients with diabetes. We aimed to investigate the association between HbA1c and the risk of incident stroke in patients with type 2 diabetes using electronic medical record data from three large healthcare systems in Louisiana. We performed a retrospective cohort study of 27,113 African Americans and 40,431 whites with type 2 diabetes. Cox proportional hazards regression models were used to estimate the association of different levels of HbA1c with stroke risk. During a mean follow-up period of 3.74 years, 8986 patients developed stroke (8438 ischemic and 548 hemorrhagic). Multivariable-adjusted hazard ratios across levels of HbA1c at baseline ( Disclosure Y. Shen: None. L. Shi: None. E. Nauman: None. P. Katzmarzyk: None. E.G. Price-Haywood: None. A.N. Bazzano: None. S. Nigam: None. G. Hu: None. Funding Patient-Centered Outcomes Research Institute (NEN-1508-32257); National Institute of General Medical Sciences (U54GM104940 to G.H., P.K.)

Studies on racial differences in diabetic complications are very limited. The aim of this study was to investigate the race and sex differences in diabetic complications between African Americans and Whites with type 2 diabetes (T2D) in Louisiana.A prospective cohort study was performed of 27 113 African Americans and 40 431 Whites with T2D who were 35 to 95 years of age from three healthcare systems located in south Louisiana. Four major diabetic complications were assessed: coronary heart disease (CHD), heart failure, stroke, and end-stage renal disease (ESRD).The age- and sex-adjusted incident rates per 1000 person-years and 95% confidence intervals (CI) for CHD, heart failure, stroke, and ESRD for African Americans with diabetes were 43.1 (95% CI 41.6-44.6), 36.6 (95% CI 35.2-37.9), 29.6 (95% CI 28.4-30.8), and 38.3 (95% CI 36.9-39.7), respectively. Cox regression models showed that African American women had a higher risk than White women for heart failure (hazard ratio (HR) 1.26; 95% CI 1.18-1.34), stroke (HR 1.15; 95% CI 1.08-1.22), and ESRD (HR 1.32; 95% CI 1.24-1.40), whereas African American men had higher risks than White men for heart failure (HR 1.33; 95% CI 1.25-1.43) and ESRD (HR 1.47; 95% CI 1.37-1.57) but a lower risk of CHD (HR 0.88; 95% CI 0.83-0.94).The incidence of major diabetic complications varied among difference race and sex groups. More race- or sex-specific studies on complications in patients with diabetes are needed to see whether incident rates are changing over time.摘要: 背景 目前有关糖尿病并发症种族差异的研究非常有限。本研究旨在路易斯安那州患有2型糖尿病的非裔美国人与白种人中，调查糖尿病并发症的种族与性别差异。 方法 这是一项前瞻性的队列研究，纳入了患有2型糖尿病的27113名非裔美国人与40431名白种人，他们的年龄为35至95岁，来自路易斯安那州南部的3个医疗机构。评估了4种主要的糖尿病并发症:冠心病(coronary heart disease，CHD)、心力衰竭、中风以及终末期肾病(end-stage renal disease，ESRD)。 结果 在患有糖尿病的非裔美国人中，校正年龄与性别后，每1000人-年的CHD、心力衰竭、中风以及ESRD的发生率与95%置信区间(CI)分别为43.1(95% CI为41.6-44.6)、36.6(95% CI为35.2-37.9)、29.6(95% CI为28.4-30.8)与38.3(95% CI为36.9-39.7)。使用Cox回归模型分析后发现，非裔美国妇女与白种妇女相比，前者出现心力衰竭(风险比[HR]为1.26；95% CI为1.18-1.34)、中风(HR为1.15；95% CI为1.08-1.22)以及ESRD(HR为1.32；95% CI为1.24-1.40)的风险都更高，而非裔美国男性与白种男性相比，前者出现心力衰竭(HR为1.33；95% CI为1.25-1.43)与ESRD(HR为1.47；95% CI为1.37-1.57)的风险都更高，但是出现CHD(HR为0.88；95% CI为0.83-0.94)的风险却较低。 结论 在不同的种族与性别组中主要糖尿病并发症的发病率都各不相同。为了观察发病率是否会随着时间而变化，需要在糖尿病患者中进行更多的种族或者性别特异性的并发症研究。.

No abstract available. Editor’s Note: This is the second in a series of articles by Dr. Nigam on the use of digital information and communication technologies, commonly referred to as telehealth and telemedicine. In this article the author discusses clinical practice issues and the challenges of regulation and security of digital health information facing society today.

No abstract available. Editor’s Note: This is the first in a series of articles by Dr. Nigam on the use of digital information and communication technologies, commonly referred to as telehealth and telemedicine. In this article the author distinguished between these terms and identifies the potential contributions of digital information and communication in meeting healthcare challenges facing society today. In future articles, Dr. Nigam will address regulatory issues and the future of telemedicine. The series concludes with a comparison of the use of telemedicine in North America and the international community.

Objective To compare costs and utilization for patients with diabetes enrolled in patient-centered medical home (PCMH) practices and non-PCMH practices. Design Commercial Health Maintenance Organization members with diabetes who enrolled between 2008 and 2011 in 26 Pennsylvania-based PCMH practices that were recognized by the National Committee for Quality Assurance in 2009 were compared with similar patients in 97 non-PCMH primary care practices. A difference-in-differences longitudinal research design was used to analyze differences between both groups on per-member, per-month costs and utilization. The statistical models controlled for baseline practice and patient-level characteristics through 2-step propensity score matching. The regression analysis on program effect further controlled for within-practice variation. Sensitivity analyses were also conducted on patients with type 1 and type 2 diabetes separately, and a third analysis was limited to diabetic patients enrolled in practices within Philadelphia. Results Adoption of the PCMH reduced overall medical costs for diabetic patients by 21% in year 1. This reduction was driven largely by inpatient costs, which fell by 44%. Reductions in emergency department visits, outpatient costs, and specialist visits were also seen in subsequent years among patients enrolled in PCMH practices. Additional sensitivity analyses indicated that adoption of the PCMH model yielded similar results when analyzing patients with type 2 diabetes as well as for diabetic patients enrolled in PCMH practices located within the city of Philadelphia. Conclusions The cost of care for patients with diabetes can be reduced by securing care at a PCMH practice. Immediate results were seen in reduction of inpatient costs, which indicate that these patients enrolled in PCMH practices were using less costly inpatient services.

Owing to a lack of current understanding of outcomes and costs by type of hysterectomy procedure, we attempt to quantify the incidence and impact of surgical site infection (SSI) in laparoscopic and non-laparoscopic approaches to abdominal and vaginal hysterectomy.Patients whose data were contained in the Premier Perspectives Database of 600 hospitals in the United States were selected on the basis of a post-operative diagnosis of SSI and treatment with antibiotics. The incidence of SSI and associated hospital length of stay (LOS) and costs were estimated. The effect of SSI on readmission was also analyzed.Of 210,916 hysterectomies included in the study, 55% were open abdominal procedures. Although the overall incidence of SSI in hysterectomy was low, its incidence was greater in open abdominal hysterectomy than in other approaches to hysterectomy. Patients with an SSI experienced a three- to five-fold greater LOS, two-fold greater cost, and three-fold greater risk of hospital readmission than those without an SSI.This study provides clinical evidence in support of less invasive approaches to hysterectomy. In addition to other documented benefits of such less invasive procedures, the lower incidence of SSIs and lower rates of associated complications and costs with these procedures than with open abdominal hysterectomy should be taken into account when weighing the risks and benefits of a surgical approach for patients whose condition warrants hysterectomy.

We present a new approach to population health, in which data-driven predictive models are learned for outcomes such as type 2 diabetes. Our approach enables risk assessment from readily available electronic claims data on large populations, without additional screening cost. Proposed model uncovers early and late-stage risk factors. Using administrative claims, pharmacy records, healthcare utilization, and laboratory results of 4.1 million individuals between 2005 and 2009, an initial set of 42,000 variables were derived that together describe the full health status and history of every individual. Machine learning was then used to methodically enhance predictive variable set and fit models predicting onset of type 2 diabetes in 2009-2011, 2010-2012, and 2011-2013. We compared the enhanced model with a parsimonious model consisting of known diabetes risk factors in a real-world environment, where missing values are common and prevalent. Furthermore, we analyzed novel and known risk factors emerging from the model at different age groups at different stages before the onset. Parsimonious model using 21 classic diabetes risk factors resulted in area under ROC curve (AUC) of 0.75 for diabetes prediction within a 2-year window following the baseline. The enhanced model increased the AUC to 0.80, with about 900 variables selected as predictive (p 0.0001 for differences between AUCs). Similar improvements were observed for models predicting diabetes onset 1-3 years and 2-4 years after baseline. The enhanced model improved positive predictive value by at least 50% and identified novel surrogate risk factors for type 2 diabetes, such as chronic liver disease (odds ratio [OR] 3.71), high alanine aminotransferase (OR 2.26), esophageal reflux (OR 1.85), and history of acute bronchitis (OR 1.45). Liver risk factors emerge later in the process of diabetes development compared with obesity-related factors such as hypertension and high hemoglobin A1c. In conclusion, population-level risk prediction for type 2 diabetes using readily available administrative data is feasible and has better prediction performance than classical diabetes risk prediction algorithms on very large populations with missing data. The new model enables intervention allocation at national scale quickly and accurately and recovers potentially novel risk factors at different stages before the disease onset.

Previous studies have reported VTE rates during surgical stays in hospitals or by diagnoses over extended periods without being linked to specific surgical events. The purpose of this project was to assess the potential rate of venous thromboembolism in patients with cancer after a surgical procedure within the immediate posthospital admission period of 30 days, with special emphasis in increased sensitivity of detection. Patients with cancer who had a major surgery were identified in a large commercial (non-Medicare) database containing data from more than 22 million patients in the United States. Those with a new diagnosis of VTE within 30 days postadmission for surgery were identified. Additional drug-based criteria were used to vary the VTE definition in a sensitivity analysis. VTE rates are reported for each of the surgical procedure group and overall. The overall 30-day VTE rate was 3.5% with a diagnosis based definition, with rates ranging by procedure from 1.8 to 13.2%. Esophageal resection patients have a VTE rate of 13.2% (95% confidence interval (CI), 8.8–18.9%), whereas prostatectomy patients have a VTE rate of 1.8% (95% CI, 1.5–2.1%). Of the 3.5% of patients with a VTE diagnosis on or before postoperative day 30, 73% of those have the VTE diagnosis by day 14. Another 1.15% is added to the overall VTE rate as the definition sensitivity is increased with outpatient pharmacy claims data. Using administrative data from large populations provides valuable insight into the potential VTE rates that occur within the 30-day post period after various cancer-related surgeries. The information can be used by surgeons as one component of the benefit-risk decision regarding postoperative VTE prophylaxis in surgical patients.

This study analyzed GE Centricity Electronic Medical Record (EMR) data to examine the effects of body mass index (BMI) and obesity, key risk factor components of metabolic syndrome, on the prevalence of 3 chronic diseases: type II diabetes mellitus, hyperlipidemia, and hypertension. These chronic diseases occur with high prevalence and impose high disease burdens. The rationale for using Centricity EMR data is 2-fold. First, EMRs may be a good source of BMI/obesity data, which are often underreported in surveys and administrative databases. Second, EMRs provide an ideal means to track variables over time and, thus, allow longitudinal analyses of relationships between risk factors and disease prevalence and progression. Analysis of Centricity EMR data showed associations of age, sex, race/ethnicity, and BMI with diagnosed prevalence of the 3 conditions. Results include uniform direct correlations between age and BMI and prevalence of each disease; uniformly greater disease prevalence for males than females; varying differences by race/ethnicity (ie, African Americans have the highest prevalence of diagnosed type II diabetes and hypertension, while whites have the highest prevalence of diagnosed hypertension); and adverse effects of comorbidities. The direct associations between BMI and disease prevalence are consistent for males and females and across all racial/ethnic groups. The results reported herein contribute to the growing literature about the adverse effects of obesity on chronic disease prevalence and about the potential value of EMR data to elucidate trends in disease prevalence and facilitate longitudinal analyses.

The impact of primary care practices adopting the patient-centered medical home (PCMH) model is analyzed by comparing per member per month (PMPM) costs and utilization among commercial HMO members with chronic illnesses in PCMH and non-PCHM practices in the Philadelphia area. Transforming primary care practices to conform to the PCMH model has shown early promise in reducing costs and improving outcomes, and chronically ill patients' frequent contact with the healthcare system and costly care make them ideal targets for such health system reforms.The impact of the PCMH model on PMPM costs was analyzed using a generalized linear regression model to adjust for age, gender, and baseline cost. The impact of the PCMH model on utilization per 1000 rates was analyzed with the Poisson regression model, adjusting for baseline differences in age, gender, and risk score.After accounting for differences at baseline, PCMH practices achieved lower total, inpatient, and specialist PMPM costs, as well as lower relative utilization of hospital admissions and specialist visits.These findings suggest that policy makers should maintain or expand incentives to adopt PCMH reforms and that targeting chronically ill patients may be the most effective way to leverage the benefits of PCMH adoption.

The patient-centered medical home (PCMH) model has shown early promise as a vehicle for reorganizing health care systems and improving the management of chronic illness. Studies of the medical home and related interventions have shown improvements in provider experience (Reid et al. 2010), patient experience (Reid et al. 2009, 2010; Solberg et al. 2011), processes of care (Zuckerman et al. 2004; Wise et al. 2006; Domino et al. 2009), practice-level measures of quality and preventive care utilization (Paustian et al. 2013), and economic outcomes such as reductions in total costs (Devries et al. 2012; Paustian et al. 2013) and use of high-intensity domains of care, such as hospital admissions or emergency department (ED) visits (Reid et al. 2010). However, systematic reviews of evaluations of the PCMH demonstrate that the work to date is inconclusive and often yields conflicting results (Peikes et al. 2012; Jackson et al. 2013). For example, the transition to a PCMH model has been shown, variously, to reduce total costs (Devries et al. 2012) or increase costs (Domino et al. 2009), while others found spending rose in some areas and fell in others (Reid et al. 2010) or found no significant effects (Leff et al. 2009; Werner et al. 2013). In addition, several reviews of the PCMH literature point out methodological concerns regarding the existing work: studies examine too few practices, include inadequate follow-up, and have failed to account for the clustering of results by practice (Peikes et al. 2011). This article intends to contribute to the growing literature evaluating the impact of adoption of the PCMH model by primary care practices. By using a novel identification strategy and a rigorous difference-in-differences approach to study a large administrative dataset—over 1 million patient-years across 280 PCMH-certified primary care practices—we aim to address the methodological concerns raised elsewhere to sort through the uncertainty and point toward a research agenda for future evaluations of the PCMH model. In particular, we are interested in the mechanisms through which the PCMH affects ED utilization. One possibility is that expanding access would allow some patients, who might otherwise present to the ED, to receive medical attention in a primary care setting. Other ED patients require urgent care to treat acute episodes of chronic illness, but many of these encounters could have been prevented if patients’ conditions were appropriately managed by primary care. We shed some light on these issues by analyzing a subset of weekend ED visits and avoidable ED visits. The Patient-Centered Medical Home Recent literature on primary care emphasizes significant challenges, such as perverse incentives related to fee-for-service reimbursement (American College of Physicians 2006), the supply of primary care physicians relative to specialists (Moore and Showstack 2003; Bodenheimer, Grumbach, and Berenson 2009), and an orientation poorly suited to effectively managing chronic illness (Wagner, Austin, and Von Korff 1996; Bodenheimer, Wagner, and Grumbach 2002). In light of these challenges, as well as the optimism surrounding initiatives to improve primary care, the PCMH model has garnered considerable interest. Comprehensive discussion of the PCMH and its history can be found elsewhere (American Academy of Family Physicians 2007; Friedberg et al. 2009; Kilo and Wasson 2010). Generally speaking, the medical home model calls for the following: improved coordination of services, orchestrated by a personal physician; a “whole person” orientation to care; expanded patient access to primary care practices; increased usage of health information technology; and aligning reimbursement incentives to better compensate this expanded role for primary care (American Academy of Family Physicians 2007). The National Committee for Quality Assurance (NCQA) publishes guidelines for primary care practices looking to adopt the PCMH model, and it accredits practices as having adopted these improvements using a three-level typology reflecting the number of reforms in place. To gain recognition at each level, practices must demonstrate successful adoption of a group of “must pass” elements, and they are graded using a point-based system for additional improvements (National Committee for Quality Assurance 2008). Though competing standards exist, the NCQA guidelines are the most widely used in the PCMH literature (Friedberg et al. 2009; Cassidy 2010). The 2011 NCQA guidelines include 28 specific practice improvements across six categories, including enhanced access and continuity, identifying and managing patient populations, planning and managing care, providing self-care support and community resources, tracking and coordinating care, and measuring and improving performance (National Committee for Quality Assurance 2011). In terms of their impact on ED utilization, these categories can be grouped under two headings, divided by their hypothesized effect. Some improvements expand access to clinics (such as extended operating hours, electronic access, etc.), potentially leading to substitution of primary care for expensive and intensive ED services; others are aimed at improving population health (like use of data for population management, identifying high-risk patients, care coordination, use of electronic prescribing, and implementation of evidence-based guidelines). Disentangling the effects of these two categories of the PCMH has important implications for medical care and future policy. PCMH and Emergency Departments Utilization A number of drivers of high ED volume are offered in the literature (Billings, Parikh, and Mijanovich 2000). Some visits are for nonurgent health issues; some are urgent but could be safely and effectively addressed in the realm of primary care; and still others are appropriate for the ED at the time of visit but could have been avoided with better disease management. These visits not only increase health system spending but also may lead to excessive or unnecessary treatment and testing. Though estimates vary, a substantial fraction of visits to EDs are avoidable. One study calculated that between 13.7 and 27.1 percent of all ED encounters were for conditions that could have been addressed in retail or urgent care clinics, saving roughly $4.4 billion each year (Weinick, Burns, and Mehrotra 2010). Expanding access to primary care clinics may help address these problems, as patients reporting fewer barriers to after-hours contact with their physicians reported fewer ED visits (O'Malley 2013). Conceptual models of the PCMH suggest that adoption of such reforms may lead to fewer ED visits by patients, both by improving the coordination of care and by reducing delays in treatment, thereby reducing the likelihood of complications (Hearld and Alexander 2012).

Evaluate the effects of the patient-centered medical home (PCMH) model on medical costs and utilization in the nonpediatric population, particularly among high-risk patients.Longitudinal case-control design, comparing per member per month (PMPM) cost and utilization per 1000 patients for members enrolled in PCMH and non-PCMH practices from 2009 to 2011.Commercial health maintenance organization members in nonpediatric practices that adopted the PCMH model in 2009 were matched to patients in nonpediatric practices that did not adopt the model until 2011 or later. Propensity score matching was used to identify a pool of similar controls, and difference-in-differences regression analysis was used to compare PCMH and non-PCMH patients relative to baseline. Analysis was conducted using the complete pool of matched patients (N = 6940 cases and 6940 controls), then using the 10% of patients with the highest DxCG risk scores (N = 654 cases and 734 controls).There were no significant cost or utilization differences for the overall population. Total cost decreased significantly more for the PCMH group than for controls in the high-risk group in years 1 and 2 (reductions of $107 and $75 PMPM), driven by lower inpatient costs. The PCMH group experienced a significantly greater reduction in inpatient admissions in all 3 years (61, 48, and 94 hospitalizations per 1000).PCMH practices had significantly reduced costs and utilization for the highest risk patients, particularly with respect to inpatient care. As high-risk members represent a high-cost group, the most benefit can be gained by targeting these members.

Validation of direct surface swabbing procedure in conjuction with total organic carbon (TOC) analysis is described for a biopharmaceutical product manufacturing operation. The swabbing technique was found to be very effective in reliably detecting very low levels of residuals for diverse process streams (limit of detection of approximately 0.5microg/cm(2)). However, contaminant recovery was significantly dependent on both the type of contaminant and the processing surface. This study serves as a guide for designing effective cleaning validation protocols based on direct surface swabbing techniques. (c) 1995 John Wiley & Sons, Inc.

The value of self-monitoring of blood glucose (SMBG) for persons with type 2 diabetes who do not use insulin remains controversial. This observational study compares the likelihood of medication adherence and change in glycated hemoglobin (A1C) for non-insulin-using patients using SMBG versus those not using SMBG. The study also assessed the association between diabetes medication adherence and SMBG use.Data were extracted on 5,172 patients who began non-insulin diabetes medication between October 1, 2006, and March 31, 2009. The study assessed change in A1C associated with SMBG use and testing frequency at different categorical levels of baseline A1C. The likelihood of medication adherence for SMBG users was compared with that for non-SMBG users at different categorical levels of baseline A1C. The study further explored the interactions between SMBG use and medication adherence on change in A1C.SMBG users had greater reductions in A1C compared with nonusers when the baseline A1C was ≥ 7%. Increasing SMBG frequency was associated with greater reductions in A1C. The study also examined the associations among SMBG use, medication adherence, and change in A1C. SMBG users had greater decreases in A1C for both medication-adherent and -nonadherent patients. As expected, medication adherence was associated with greater reductions in A1C for both SMBG nonusers and users. It is interesting that medication-nonadherent SMBG users had similar reductions in A1C compared with medication-adherent non-SMBG users.Both SMBG use and medication adherence were associated with similar degrees of A1C reduction after controlling for baseline A1C, suggesting that both factors may be important for attaining glycemic control.

Background: We evaluated the association between self-monitoring of blood glucose (SMBG) use and sitagliptin or sitagliptin/ metformin (SSMT) adherence. SSMT was chosen as these medications have little risk of hypoglycemia and are believed to not require SMBG data for titration. Methods: This was an observational study using data extracted from a large United States insurance claims database (i3 InVision™ Data Mart, Ingenix, Inc.). Data were extracted on noninsulin-using patients initiating SSMT for each 12-month period pre- and post-SSMT initiation. Logistic regression was used to assess the relationship between SMBG use and the likelihood of being medication adherent (defined as a medication possession ratio of ≥75%) while controlling for covariates. Results: This analysis included 7,306 patients (57.6% male; mean age 54.2 years). Mean pre-SSMT hemoglobin A1c (HbA1c) was 8.0%. In the post-SSMT initiation period, 58% of patients were adherent with SSMT. Older age, male gender, prior use of oral diabetes medication, and lower HbA1c were associated with improved SSMT adherence. SMBG use was associated with improved adherence [odds ratio (OR) ranged from 1.198 to 1.338; p < .05] compared with patients with no SMBG use pre- or post-SSMT initiation. For patients who began SMBG after starting SSMT, greater SMBG use was associated with better adherence (OR 1.449 for higher vs 1.246 for lower strip use; p < .05). Conclusions: This study demonstrated that SMBG is associated with improved SSMT adherence. This relationship is strengthened with greater SMBG use.

Neurotrophin-4 (NT-4) is the most recently discovered member of the neurotrophin family. We have expressed, refolded, and purified recombinant human NT-4 from Escherichia coli and compared it with recombinant human NT-4 secreted into the culture medium of baculovirus-infected insect cells. Both preparations were characterized and determined to be indistinguishable according to several biochemical criteria. Recombinant NT-4 from E. coli was crystallized in a form suitable for x-ray analysis, and characterization of these crystals indicated that NT-4 was present as a dimer within the asymmetric unit. NT-4 was active in promoting the survival of rat TrkB receptor-expressing fibroblasts, but was inactive on embryonic chicken sensory neurons, unlike the other members of the neurotrophin family and in contrast to the reported activities of partially purified NT-4.

The study objective was to facilitate investigations by assessing the external validity and generalizability of the Centricity Electronic Medical Record (EMR) database and analytical results to the US population using the National Ambulatory Medical Care Survey (NAMCS) data and results as an appropriate validation resource. Demographic and diagnostic data from the NAMCS were compared to similar data from the Centricity EMR database, and the impact of the different methods of data collection was analyzed. Compared to NAMCS survey data on visits, Centricity EMR data shows higher proportions of visits by younger patients and by females. Other comparisons suggest more acute visits in Centricity and more chronic visits in NAMCS. The key finding from the Centricity EMR is more visits for the 13 chronic conditions highlighted in the NAMCS survey, with virtually all comparisons showing higher proportions in Centricity. Although data and results from Centricity and NAMCS are not perfectly comparable, once techniques are employed to deal with limitations, Centricity data appear more sensitive in capturing diagnoses, especially chronic diagnoses. Likely explanations include differences in data collection using the EMR versus the survey, particularly more comprehensive medical documentation requirements for the Centricity EMR and its inclusion of laboratory results and medication data collected over time, compared to the survey, which focused on the primary reason for that visit. It is likely that Centricity data reflect medical problems more accurately and provide a more accurate estimate of the distribution of diagnoses in ambulatory visits in the United States. Further research should address potential methodological approaches to maximize the validity and utility of EMR databases.