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Background: Multimorbidity (MM) and functional limitation (FL) are associated with poor outcomes in heart failure (HF). However, the individual and combined effect of these on mental health and quality of life in patients with HF is not well understood. Methods: Patients aged ≥ 30 years with 2 or more HF diagnostic codes and 1 or more HF-related prescription drugs from four US institutions were mailed a survey to measure functional status (activities of daily living [ADLs]), quality of life and mental health (PROMIS-29 Health Profile) and social support (PROMIS Informational Support, Instrumental Support, and Social Isolation Short Forms). The sampling frame was restricted to patients with a first ever-diagnosis of HF on or after 1/1/2013 at 1 of the participating sites and on or after 1/1/2015 for the other 3 participating sites. A total of 3330 patients returned the survey (response rate 35%); among these, 3020 completed the questions of interest for this analysis and were retained. MM was defined as the presence of ≥ 2 non-cardiovascular comorbidities, and FL was defined as reporting any limitation in at least 1 of 8 ADLs. Patients were categorized into 4 groups by MM (Yes/No) and FL (Yes/No). We dichotomized the subscale scores of the PROMIS-29 at the median and calculated odd ratios for the 4 MM/FL groups. Results: Among 3020 patients with HF (45% female; mean age 73±12 years), 29% had neither MM or FL, 24% had MM only, 22% had FL only, and 25% had both. After adjustment, having both MM and FL or only FL was associated with increased odds of higher anxiety, depression, fatigue, sleep, and pain scores compared to having neither (Figure); having MM only was associated with a higher pain score. Conclusions: Patients with both FL and MM and only FL have similar odds of poor mental health and quality of life scores, underscoring the importance of the role that FL plays in outcomes in patients with HF.

Background: Most patients with heart failure (HF) have multimorbidity which may cause difficulties with self-management. Understanding the determinants of successful self-management and the resources patients draw upon to effectively manage their health is fundamental to designing new practice models to improve outcomes in HF. Methods: We developed a survey guided by the Chronic Care Model to understand the distribution of patient-centric factors, including health literacy, social support, self-management, and functional and mental status in patients with HF. The survey was administered to HF patients from 4 health care systems participating in PCORnet® (the National Patient-Centered Clinical Research Network). Patients were identified utilizing data available in the PCORnet common data model on or after 1/1/2013 at 1 health system and on or after 1/1/2015 at 3 health systems: age ≥30 years, ≥2 HF diagnostic codes, and ≥1 HF-related prescription (positive predictive value of algorithm: 81%). Results: A total of 10,662 patients with HF were identified, 9684 were mailed a survey, and 3330 completed a survey (response rate: 35%). Responders were older than non-responders (74 vs. 71 years), less racially diverse (3% vs. 12% non-White), less likely to have reduced ejection fraction (EF; 22% vs. 27% with EF Conclusion: More than half of patients with HF manage their health by themselves even though most bring someone along to their health care appointments. Increased understanding of self-management resources may guide the development of interventions to improve HF outcomes.

Ursodeoxycholic acid (UDCA) remains the first-line therapy for primary biliary cholangitis (PBC); however, inadequate treatment response (ITR) is common. The UK-PBC Consortium developed the modified UDCA Response Score (m-URS) to predict ITR (using alkaline phosphatase [ALP] > 1.67 times the upper limit of normal [*ULN]) at 12 months post-UDCA initiation). Using data from the US-based Fibrotic Liver Disease Consortium, we assessed the m-URS in our multi-racial cohort. We then used a dynamic modeling approach to improve prediction accuracy. Using data collected at the time of UDCA initiation, we assessed the m-URS using the original formula; then, by calibrating coefficients to our data, we also assessed whether it remained accurate when using Paris II criteria for ITR. Next, we developed and validated a dynamic risk prediction model that included post-UDCA initiation laboratory data. Among 1578 patients (13% men; 8% African American, 9% Asian American/American Indian/Pacific Islander; 25% Hispanic), the rate of ITR was 27% using ALP > 1.67*ULN and 45% using Paris II criteria. M-URS accuracy was “very good” (AUROC = 0.87, sensitivity = 0.62, and specificity = 0.82) for ALP > 1.67*ULN and “moderate” (AUROC = 0.74, sensitivity = 0.57, and specificity = 0.70) for Paris II. Our dynamic model significantly improved accuracy for both definitions of ITR (ALP > 1.67*ULN: AUROC = 0.91; Paris II: AUROC = 0.81); specificity approached 100%. Roughly 9% of patients in our cohort were at the highest risk of ITR. Early identification of patients who will not respond to UDCA treatment using a dynamic prediction model based on longitudinal, repeated risk factor measurements may facilitate earlier introduction of adjuvant treatment.

Objective To determine the effects of missing and inconsistent data on a weight management mail survey results. Patients and Methods Weight management surveys were sent to 5000 overweight and obese individuals in the Learning Health System Network. Survey information was collected between October 27, 2017, and March 1, 2018. Some participants reported body mass index (BMI) values inconsistent with the intended overweight and obese sampling cohort. Analyses were performed after excluding these surveys and also performed again after setting these low BMI values to missing. Models were run after imputing missing values using expectation-maximization, Markov chain Monte Carlo, random forest imputation, multivariate imputation by chained equations, and multiple imputation and replacing missing BMI values with the minimum, maximum, mean, or median of the known BMI values. Results Of 2799 surveys, 222 (8%) had missing BMI values and 155 (6%) reported invalid BMI values. Overall, 725 of these 2799 surveys (26%) were missing at least 1 variable that was essential to the main analyses. Different imputation methods consistently found that BMI was related to age, sex, race, marital status, and education. Patients with a BMI of 35.0 kg/m2 or greater were more likely to feel judged because of their weight, and patients with a BMI of 40.0 kg/m2 or greater were more likely to feel they were not always treated with respect and treated as an equal. Conclusion Analyses using different imputation methods were consistent with the original published results. Missing data likely did not affect the study results.

Author(s): Lu, Mei; Bowlus, Christopher L; Lindor, Keith; Rodriguez-Watson, Carla V; Romanelli, Robert J; Haller, Irina V; Anderson, Heather; VanWormer, Jeffrey J; Boscarino, Joseph A; Schmidt, Mark A; Daida, Yihe G; Sahota, Amandeep; Vincent, Jennifer; Li, Jia; Trudeau, Sheri; Rupp, Loralee B; Gordon, Stuart C; FOLD Investigators | Abstract: BackgroundBiopsy remains the gold standard for determining fibrosis stage in patients with primary biliary cholangitis (PBC), but it is unavailable for most patients. We used data from the 11 US health systems in the FibrOtic Liver Disease Consortium to explore a combination of biochemical markers and electronic health record (EHR)-based diagnosis/procedure codes (DPCs) to identify the presence of cirrhosis in PBC patients.MethodsHistological fibrosis staging data were obtained from liver biopsies. Variables considered for the model included demographics (age, gender, race, ethnicity), total bilirubin, alkaline phosphatase, albumin, aspartate aminotransferase (AST) to platelet ratio index (APRI), Fibrosis 4 (FIB4) index, AST to alanine aminotransferase (ALT) ratio, and g100 DPCs associated with cirrhosis/decompensated cirrhosis, categorized into ten clusters. Using least absolute shrinkage and selection operator regression (LASSO), we derived and validated cutoffs for identifying cirrhosis.ResultsAmong 4328 PBC patients, 1350 (32%) had biopsy data; 121 (9%) were staged F4 (cirrhosis). DPC clusters (including codes related to cirrhosis and hepatocellular carcinoma diagnoses/procedures), Hispanic ethnicity, ALP, AST/ALT ratio, and total bilirubin were retained in the final model (AUROC=0.86 and 0.83 on learning and testing data, respectively); this model with two cutoffs divided patients into three categories (no cirrhosis, indeterminate, and cirrhosis) with specificities of 81.8% (for no cirrhosis) and 80.3% (for cirrhosis). A model excluding DPCs retained ALP, AST/ALT ratio, total bilirubin, Hispanic ethnicity, and gender (AUROC=0.81 and 0.78 on learning and testing data, respectively).ConclusionAn algorithm using laboratory results and DPCs can categorize a majority of PBC patients as cirrhotic or noncirrhotic with high accuracy (with a small remaining group of patients' cirrhosis status indeterminate). In the absence of biopsy data, this EHR-based model can be used to identify cirrhosis in cohorts of PBC patients for research and/or clinical follow-up.

Objective Develop and implement a prescription opioid registry in 10 diverse health systems across the US and describe trends in prescribed opioids between 2012 and 2018. Materials and Methods Using electronic health record and claims data, we identified patients who had an outpatient fill for any prescription opioid, and/or an opioid use disorder diagnosis, between January 1, 2012 and December 31, 2018. The registry contains distributed files of prescription opioids, benzodiazepines and other select medications, opioid antagonists, clinical diagnoses, procedures, health services utilization, and health plan membership. Rates of outpatient opioid fills over the study period, standardized to health system demographic distributions, are described by age, gender, and race/ethnicity among members without cancer. Results The registry includes 6 249 710 patients and over 40 million outpatient opioid fills. For the combined registry population, opioid fills declined from a high of 0.718 per member-year in 2013 to 0.478 in 2018, and morphine milligram equivalents (MMEs) per fill declined from 985 MMEs per fill in 2012 to 758 MMEs in 2018. MMEs per member declined from 692 MMEs per member in 2012 to 362 MMEs per member in 2018. Conclusion This study established a population-based opioid registry across 10 diverse health systems that can be used to address questions related to opioid use. Initial analyses showed large reductions in overall opioid use per member among the combined health systems. The registry will be used in future studies to answer a broad range of other critical public health issues relating to prescription opioid use.

Opioid-related deaths continue to rise in the U.S. A shared decision-making (SDM) system to help primary care clinicians (PCCs) identify and treat patients with opioid use disorder (OUD) could help address this crisis.In this cluster-randomized trial, primary care clinics in three healthcare systems were randomized to receive or not receive access to an OUD-SDM system. The OUD-SDM system alerts PCCs and patients to elevated risk of OUD and supports OUD screening and treatment. It includes guidance on OUD screening and diagnosis, treatment selection, starting and maintaining patients on buprenorphine for waivered clinicians, and screening for common comorbid conditions. The primary study outcome is, of patients at high risk for OUD, the percentage receiving an OUD diagnosis within 30 days of index visit. Additional outcomes are, of patients at high risk for or with a diagnosis of OUD, (a) the percentage receiving a naloxone prescription, or (b) the percentage receiving a medication for OUD (MOUD) prescription or referral to specialty care within 30 days of an index visit, and (c) total days covered by a MOUD prescription within 90 days of an index visit.The intervention started in April 2021 and continues through December 2023. PCCs and patients in 90 clinics are included; study results are expected in 2024.This protocol paper describes the design of a multi-site trial to help PCCs recognize and treat OUD. If effective, this OUD-SDM intervention could improve screening of at-risk patients and rates of OUD treatment for people with OUD.

Background The prevalence of opioid use disorder (OUD) has increased rapidly in the United States and improving treatment access is critical. Among patients with OUD, we examined factors associated with the Healthcare Effectiveness Data and Information Set (HEDIS) performance measures of alcohol and other drug (AOD) treatment initiation and engagement. Methods Electronic health record and claims data between October 1, 2014, and August 15, 2015, from 7 health systems were used to identify patients ( n = 11,490) with a new index OUD diagnosis (no AOD diagnosis prior Results The prevalence of OUD among all AOD diagnoses varied across health systems, as did rates of AOD initiation (5.7%–21.6%) and engagement (7.6%–24.6%). Those diagnosed in the emergency department (adjusted odds ratio [aOR] = 1.58, 95% confidence interval [CI] = 1.27,1.97) or psychiatry/AOD treatment (aOR = 2.92, 95% CI = 2.47,3.46) were more likely to initiate treatment compared with primary care. Older patients were less likely to initiate (age 50–64 vs. age 18–29: aOR = 0.42, 95% CI = 0.35, 0.51; age 65+ vs. age 18–29: aOR = 0.34, 95% CI = 0.26, 0.43), as were women (aOR = 0.72, 95% CI = 0.62, 0.85). Patients diagnosed in psychiatry/AOD treatment (aOR = 2.67, 95% CI = 1.98, 3.60) compared with primary care were more likely to engage in treatment. Those identified in an inpatient setting (aOR = 0.19, 95% CI = 0.14, 0.27 vs. primary care), those with medical comorbidity (aOR = 0.70, 95% CI = 0.52, 0.95), and older patients (age 50–64 vs. 18–29: aOR = 0.64, 95% CI = 0.46, 0.88; age 65+ vs. 18–29: aOR = 0.36, 95% CI = 0.22, 0.57) were less likely to engage in treatment. Conclusions Rates of initiation and engagement for OUD patients vary widely with noticeable room for improvement, particularly in this critical time of the opioid crisis. Targeting patient and system factors may improve health system performance, which is key to improving patient outcomes.

Background Only 10% of patients with alcohol and other drug (AOD) disorders receive treatment. The AOD Initiation and Engagement in Treatment (AOD-IET) measure was added to the national Healthcare Effectiveness Data and Information Set (HEDIS) to improve access to care. This study identifies factors related to improving AOD-IET rates. Methods We include data from 7 health systems with differing geographic, patient demographic, and organizational characteristics; all used a common Virtual Data Warehouse containing electronic health records and insurance claims data. Multilevel logistic regression models examined AOD-IET among adults (18+). Results A total of 86,565 patients had an AOD diagnosis qualifying for the HEDIS denominator. The overall initiation rate was 27.9% with wide variation; the overall engagement rate was 11.5% and varied from 4.5% to 17.9%. Women versus men (odds ratio [OR] = 0.81, 95% confidence interval [CI] = 0.76–0.86); Hispanics (OR = 0.85, 95% CI = 0.79–0.91), black/African Americans (OR = 0.82, 95% CI = 0.75–0.90), and Asian Americans (OR = 0.83, 95% CI = 0.72–0.95) versus whites; and patients aged 65+ versus 18–29 (OR = 0.82, 95% CI = 0.74–0.90) had lower odds of initiation. Patients aged 30–49 versus 18–29 (OR = 1.11, 95% CI = 1.04–1.19) and those with prior psychiatric (OR = 1.26, 95% CI = 1.18–1.35) and medical conditions (OR = 1.18, 95% CI = 1.10–1.26) had higher odds of initiation. Identification in primary care versus other departments was related to lower odds of initiation (emergency department [ED]: OR = 1.55, 95% CI = 1.45–1.66; psychiatry/AOD treatment: OR = 3.58, 95% CI = 3.33–3.84; other outpatient: OR = 1.19, 95% CI = 1.06–1.32). Patients aged 30–49 versus 18–29 had higher odds of engagement (OR = 1.26, 95% CI = 1.10–1.43). Patients aged 65+ versus 18–29 (OR = 0.51, 95% CI = 0.43–0.62) and black/African Americans versus whites (OR = 0.64, 95% CI = 0.53–0.77) had lower odds. Those initiating treatment in psychiatry/AOD treatment versus primary care (OR = 7.02, 95% CI = 5.93–8.31) had higher odds of engagement; those in inpatient (OR = 0.40, 95% CI = 0.32–0.50) or other outpatient (OR = 0.73, 95% CI = 0.59–0.91) settings had lower odds. Discussion Rates of initiation and engagement varied but were low. Findings identified age, race/ethnicity, co-occurring conditions, and department of identification as key factors associated with AOD-IET. Focusing on these could help programs develop interventions that facilitate AOD-IET for those less likely to receive care.

Background Problematic use of alcohol and other drugs (AOD) is highly prevalent among people living with the human immunodeficiency virus (PLWH), and untreated AOD use disorders have particularly detrimental effects on human immunodeficiency virus (HIV) outcomes. The Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement are important benchmarks for access to AOD use disorder treatment. To inform improved patient care, we compared HEDIS measures of AOD use disorder treatment initiation and engagement and health care utilization among PLWH and patients without an HIV diagnosis. Methods Patients with a new AOD use disorder diagnosis documented between October 1, 2014, and August 15, 2015, were identified using electronic health records (EHR) and insurance claims data from 7 health care systems in the United States. Demographic characteristics, clinical diagnoses, and health care utilization data were also obtained. AOD use disorder treatment initiation and engagement rates were calculated using HEDIS measure criteria. Factors associated with treatment initiation and engagement were examined using multivariable logistic regression models. Results There were 469 PLWH (93% male) and 86,096 patients without an HIV diagnosis (60% male) in the study cohort. AOD use disorder treatment initiation was similar in PLWH and patients without an HIV diagnosis (10% vs. 11%, respectively). Among those who initiated treatment, few engaged in treatment in both groups (9% PLWH vs. 12% patients without an HIV diagnosis). In multivariable analysis, HIV status was not significantly associated with either AOD use disorder treatment initiation or engagement. Conclusions AOD use disorder treatment initiation and engagement rates were low in both PLWH and patients without an HIV diagnosis. Future studies need to focus on developing strategies to efficiently integrate AOD use disorder treatment with medical care for HIV.

Background Treatment initiation and engagement rates for alcohol and other drug (AOD) use disorders differ depending on where the AOD use disorder was identified. Emergency department (ED) and primary care (PC) are 2 common settings where patients are identified; however, it is unknown whether characteristics of patients who initiate and engage in treatment differ between these settings. Methods Patients identified with an AOD disorder in ED or PC settings were drawn from a larger study that examined Healthcare Effectiveness Data and Information Set (HEDIS) AOD treatment initiation and engagement measures across 7 health systems using electronic health record data ( n = 54,321). Multivariable generalized linear models, with a logit link, clustered on health system, were used to model patient factors associated with initiation and engagement in treatment, between and within each setting. Results Patients identified in the ED had higher odds of initiating treatment than those identified in PC (adjusted odds ratio [aOR] = 1.89, 95% confidence interval [CI] = 1.73–2.07), with no difference in engagement between the settings. Among those identified in the ED, compared with patients aged 18–29, older patients had higher odds of treatment initiation (age 30–49: aOR = 1.25, 95% CI = 1.12–1.40; age 50–64: aOR = 1.42, 95% CI = 1.26–1.60; age 65+: aOR = 1.27, 95% CI = 1.08–1.49). However, among those identified in PC, compared with patients aged 18–29, older patients were less likely to initiate (age 30–49: aOR = 0.81, 95% CI = 0.71–0.94; age 50–64: aOR = 0.68, 95% CI = 0.58–0.78; age 65+: aOR = 0.47, 95% CI = 0.40–0.56). Women identified in ED had lower odds of initiating treatment (aOR = 0.80, 95% CI = 0.72–0.88), whereas sex was not associated with treatment initiation in PC. In both settings, patients aged 65+ had lower odds of engaging compared with patients aged 18–29 (ED: aOR = 0.61, 95% CI = 0.38–0.98; PC: aOR = 0.42, 95% CI = 0.26–0.68). Conclusion Initiation and engagement in treatment differed by sex and age depending on identification setting. This information could inform tailoring of future AOD interventions.

Objective Investigate sociodemographic differences in the use of a patient-facing family health history (FHH)-based risk assessment platform. Methods In this large multisite trial with a diverse patient population, we evaluated the relationship between sociodemographic factors and FHH health risk assessment uptake using an information technology (IT) platform. The entire study was administered online, including consent, baseline survey, and risk assessment completion. We used multivariate logistic regression to model effect of sociodemographic factors on study progression. Quality of FHH data entered as defined as relatives: (1) with age of onset reported on relevant conditions; (2) if deceased, with cause of death and (3) age of death reported; and (4) percentage of relatives with medical history marked as unknown was analyzed using grouped logistic fixed effect regression. Results A total of 2,514 participants consented with a mean age of 57 and 10.4% minority. Multivariate modeling showed that progression through study stages was more likely for younger (p-value = 0.005), more educated (p-value = 0.004), non-Asian (p-value = 0.009), and female (p-value = 0.005) participants. Those with lower health literacy or information-seeking confidence were also less likely to complete the study. Most significant drop-out occurred during the risk assessment completion phase. Overall, quality of FHH data entered was high with condition's age of onset reported 87.85%, relative's cause of death 85.55% and age of death 93.76%, and relative's medical history marked as unknown 19.75% of the time. Conclusion A demographically diverse population was able to complete an IT-based risk assessment but there were differences in attrition by sociodemographic factors. More attention should be given to ensure end-user functionality of health IT and leverage electronic medical records to lessen patient burden.

This paper describes the implementation outcomes associated with integrating a family health history–based risk assessment and clinical decision support platform within primary care clinics at four diverse healthcare systems. A type III hybrid implementation-effectiveness trial. Uptake and implementation processes were evaluated using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. One hundred (58%) primary care providers and 2514 (7.8%) adult patients enrolled. Enrolled patients were 69% female, 22% minority, and 32% Medicare/Medicaid. Compared with their respective clinic’s population, patient-participants were more likely to be female (69 vs. 59%), older (mean age 57 vs. 49), and Caucasian (88 vs. 69%) (all p values

Obesity is stigmatized and people with obesity report experiencing stigmatizing situations when seeking health care. The implications of these experiences are not well understood. This study tests an indirect effects model of negative care experiences as an intermediate variable between obesity and care avoidance/utilization and switching primary care doctors.A survey was completed by 2380 primary care patients in the Learning Health Systems Network (LHSNet) Clinical Data Research Network with a BMI 25 kg/mThe hypothesized model was supported by findings. The associations between BMI and delaying needed care (OR = 1.06,People with higher BMIs may avoid care or switch doctors as a result of stigmatizing experiences and poor communication with doctors. These outcomes may contribute to morbidity in people with obesity if they delay or avoid care for health concerns when symptoms first present.

Background Risk assessment is a precision medicine technique that can be used to enhance population health when applied to prevention. Several barriers limit the uptake of risk assessment in health care systems; and little is known about the potential impact that adoption of systematic risk assessment for screening and prevention in the primary care population might have. Here we present results of a first of its kind multi-institutional study of a precision medicine tool for systematic risk assessment. Methods We undertook an implementation-effectiveness trial of systematic risk assessment of primary care patients in 19 primary care clinics at four geographically and culturally diverse healthcare systems. All adult English or Spanish speaking patients were invited to enter personal and family health history data into MeTree, a patient-facing family health history driven risk assessment program, for 27 medical conditions. Risk assessment recommendations followed evidence-based guidelines for identifying and managing those at increased disease risk. Results One thousand eight hundred eighty-nine participants completed MeTree, entering information on N = 25,967 individuals. Mean relatives entered = 13.7 (SD 7.9), range 7–74. N = 1443 (76.4%) participants received increased risk recommendations: 597 (31.6%) for monogenic hereditary conditions, 508 (26.9%) for familial-level risk, and 1056 (56.1%) for risk of a common chronic disease. There were 6617 recommendations given across the 1443 participants. In multivariate analysis, only the total number of relatives entered was significantly associated with receiving a recommendation. Conclusions A significant percentage of the general primary care population meet criteria for more intensive risk management. In particular 46% for monogenic hereditary and familial level disease risk. Adopting strategies to facilitate systematic risk assessment in primary care could have a significant impact on populations within the U.S. and even beyond. Trial registration Clinicaltrials.gov number NCT01956773, registered 10/8/2013.

Background We used data from the Fibrotic Liver Disease Consortium to evaluate the impact of ursodeoxycholic acid (UDCA) treatment across race/ethnicity, gender, and clinical status among patients with primary biliary cholangitis. Methods Data were collected from "index date" (baseline) through December 31, 2016. Inverse Probability of Treatment Weighting was used to adjust for UDCA treatment selection bias. Cox regression, focusing on UDCA-by-risk factor interactions, was used to assess the association between treatment and mortality and liver transplant/death. Results Among 4,238 patients with primary biliary cholangitis (13% men; 8% African American, 7% Asian American/American Indian/Pacific Island [ASINPI]; 21% Hispanic), 78% had ever received UDCA. The final multivariable model for mortality retained age, household income, comorbidity score, total bilirubin, albumin, alkaline phosphatase, and interactions of UDCA with race, gender, and aspartate aminotransferase/alanine aminotransferase ≥1.1. Among untreated patients, African Americans and ASINPIs had higher mortality than whites (adjusted hazard ratio [aHR] = 1.34, 95% confidence interval [CI] 1.08-1.67 and aHR = 1.40, 95% CI 1.11-1.76, respectively). Among treated patients, this relationship was reversed (aHR = 0.67, 95% CI 0.51-0.86 and aHR = 0.88, 95% CI 0.67-1.16). Patterns were similar for liver transplant/death. UDCA reduced the risk of liver transplant/death in all patient groups and mortality across all groups except white women with aspartate aminotransferase/alanine aminotransferase ≥1.1. As compared to patients with low-normal bilirubin at baseline (≤0.4 mg/dL), those with high-normal (1.0 > 0.7) and mid-normal bilirubin (0.7 > 0.4) had significantly higher liver transplant/death and all-cause mortality. Discussion African American and ASINPI patients who did not receive UDCA had significantly higher mortality than white patients. Among African Americans, treatment was associated with significantly lower mortality. Regardless of UDCA treatment, higher baseline bilirubin, even within the normal range, was associated with increased mortality and liver transplant/death compared with low-normal levels.

To evaluate the association between obesity and history of childhood trauma in an effort to define implications for the provider-patient relationship and possible causes of failure of obesity treatment.Multisite survey developed by the Patient-Centered Outcomes Research Institute Learning Health Systems Obesity Cohort Workgroup consisting of 49 questions with 2 questions focusing on history of being a victim of childhood physical and/or sexual abuse was mailed to 19,964 overweight or obese patients. Data collection for this survey occurred from October 27, 2017, through March 1, 2018.Among the 2211 surveys included in analysis, respondents reporting being a victim of childhood abuse increased significantly with obesity (23.6%, 26.0%, 29.1%, and 36.8% for overweight, class I, class II, and class III obesity, respectively; P.001). A higher percentage of those who reported being a victim of childhood abuse noted that their weight issues began at an earlier age (P=.002) and were more likely to have weight-related comorbidities (P.001), even after controlling for body mass index. Impacting physician counseling on weight loss, patients who were childhood victims of abuse reported lower self-esteem (P.001), were more likely to feel judged by their health care providers (P=.009), and less likely to feel being treated with respect (P=.045).Overall, being a victim of childhood abuse was significantly associated with obesity, lower self-esteem and negative experiences interacting with health care providers. Health care providers should receive training to ensure open and nonjudgmental visits with obese patients and consider the role of trauma survivorship issues in patients' development of obesity and health care experiences.

IntroductionThe Learning Health System Network clinical data research network includes academic medical centers, health-care systems, public health departments, and health plans, and is designed to facilitate outcomes research, pragmatic trials, comparative effectiveness research, and evaluation of population health interventions.MethodsThe Learning Health System Network is 1 of 13 clinical data research networks assembled to create, in partnership with 20 patient-powered research networks, a National Patient-Centered Clinical Research Network.Results and ConclusionsHerein, we describe the Learning Health System Network as an emerging resource for translational research, providing details on the governance and organizational structure of the network, the key milestones of the current funding period, and challenges and opportunities for collaborative science leveraging the network.

BackgroundIndividuals with major depressive disorder (MDD) and bipolar disorder (BD) have particularly high rates of chronic non-cancer pain (CNCP) and are also more likely to receive prescription opioids for their pain. However, there have been no known studies published to date that have examined opioid treatment patterns among individuals with schizophrenia.MethodsUsing electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of MDD (N = 65,750), BD (N = 38,117) or schizophrenia or schizoaffective disorder (N = 12,916) were identified and matched on age, sex and Medicare status to controls with no documented mental illness. CNCP diagnoses and prescription opioid medication dispensings were extracted for the matched samples. Multivariate analyses were conducted to evaluate (1) the odds of receiving a pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses.ResultsMultivariable models indicated that having a MDD (OR = 1.90; 95% CI = 1.85–1.95) or BD (OR = 1.71; 95% CI = 1.66–1.77) diagnosis was associated with increased odds of a CNCP diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis was associated with decreased odds of receiving a chronic pain diagnosis (OR = 0.86; 95% CI = 0.82–0.90). Having a MDD (OR = 2.59; 95% CI = 2.44–2.75) or BD (OR = 2.12; 95% CI = 1.97–2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications.ConclusionsIndividuals with serious mental illness, who are most at risk for developing opioid-related problems, continue to be prescribed opioids more often than their peers without mental illness. Mental health clinicians may be particularly well-suited to lead pain assessment and management efforts for these patients. Future research is needed to evaluate the effectiveness of involving mental health clinicians in these efforts.

Background Individuals with major depressive disorder (MDD) and bipolar disorder (BD) have particularly high rates of chronic non-cancer pain (CNCP) and are also more likely to receive prescription opioids for their pain. However, there have been no known studies published to date that have examined opioid treatment patterns among individuals with schizophrenia. Methods Using electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of MDD (N=65,750), BD (N=38,117) or schizophrenia or schizoaffective disorder (N=12,916) were identified and matched on age, sex and Medicare status to controls with no documented mental illness. CNCP diagnoses and prescription opioid medication dispensings were extracted for the matched samples. Multivariate analyses were conducted to evaluate (1) the odds of receiving a pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses. Results Multivariable models indicated that having a MDD (OR=1.90; 95% CI=1.85–1.95) or BD (OR=1.71; 95% CI=1.66–1.77) diagnosis was associated with increased odds of a CNCP diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis was associated with decreased odds of receiving a chronic pain diagnosis (OR=0.86; 95% CI=0.82– 0.90). Having a MDD (OR=2.59; 95% CI=2.44–2.75) or BD (OR=2.12; 95% CI=1.97–2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications. Conclusions Individuals with serious mental illness, who are most at risk for developing opioid-related problems, continue to be prescribed opioids more often than their peers without mental illness. Healthcare providers need to be especially conservative in prescribing opioids – or avoid opioid therapy altogether – for this population. Mental health clinicians may be particularly well-suited to lead pain assessment and management efforts for these patients.

Background Psychiatric comorbidity is common among patients with alcohol and other drug (AOD) use disorders. To better understand how psychiatric comorbidity influences AOD treatment access in health care systems, the present study examined treatment initiation and engagement among a large, diverse sample of patients with comorbid psychiatric and AOD use disorders. Methods This study utilized data from a multisite observational study examining Healthcare Effectiveness Data and Information Set (HEDIS) measures of initiation and engagement in treatment (IET) among patients with AOD use disorders from 7 health care systems. Participants were aged 18 or older with at least 1 AOD index diagnosis between October 1, 2014, and August 15, 2015. Data elements extracted from electronic health records and insurance claims data included patient demographic characteristics, ICD-9 (International Classification of Diseases, Ninth Revision) diagnostic codes, and procedure codes. Descriptive analyses and multivariate logistic regression models were used to examine the relationship between patient-level factors and IET measures. Results Across health care systems, out of a total of 86,565 patients who had at least 1 AOD index diagnosis during the study period, 66.2% ( n = 57,335) patients also had a comorbid psychiatric disorder. Among patients with a comorbid psychiatric disorder, 34.9% ( n = 19,998) initiated AOD treatment, and of those, 10.3% ( n = 2,060) engaged in treatment. After adjusting for age, sex, and race/ethnicity, patients with comorbid psychiatric disorders were more likely to initiate (odds ratio [OR] = 3.20, 95% confidence interval [CI] = 3.08, 3.32) but no more likely to engage (OR = 0.56, 95% CI = 0.51, 0.61) in AOD treatment, compared with those without a comorbid psychiatric disorder. Conclusions Findings suggest that identification of comorbid psychiatric disorders may increase initiation in AOD treatment. However, innovative efforts are needed to enhance treatment engagement both generally and especially for individuals without diagnosed psychiatric conditions.

Background Medical comorbidity may influence treatment initiation and engagement for alcohol and other drug (AOD) use disorders. We examined the association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures. Methods We used electronic health record and insurance claims data from 7 US health care systems to identify patients with AOD use disorders between October 1, 2014, and August 15, 2015 ( N = 86,565). Among patients identified with AOD use disorders in outpatient and emergency department (ED) settings, we examined how Charlson/Deyo comorbidity index scores and medical complications of AOD use were associated with treatment initiation. Among those who initiated treatment in inpatient and outpatient/ED settings, we also examined how comorbidity and AOD use–related medical complications were associated with treatment engagement. Analyses were conducted using generalized estimating equation logistic regression modeling. Results Among patients identified as having an AOD diagnosis in outpatient and ED settings ( n = 69,965), Charlson/Deyo comorbidity index scores of 2 or more were independently associated with reduced likelihood of initiation (risk ratio [RR] = 0.80, 95% confidence interval [CI] = 0.74, 0.86; reference score = 0), whereas prior-year diagnoses of cirrhosis (RR = 1.25, 95% CI = 1.12, 1.35) and pancreatic disease (RR = 1.34, 95% CI = 1.15, 1.56) were associated with greater likelihood of initiation. Among those who were identified in outpatient/ED settings and initiated, higher comorbidity scores were associated with lower likelihood of engagement (score 1: RR = 0.85, 95% CI = 0.76, 0.94; score 2+: RR = 0.61, 95% CI = 0.53, 0.71). Conclusion Medical comorbidity was associated with lower likelihood of initiating or engaging in AOD treatment, but cirrhosis and pancreatic disease were associated with greater likelihood of initiation. Interventions to improve AOD treatment initiation and engagement for patients with comorbidities are needed, such as integrating medical and AOD treatment.

Background Cannabis use disorders (CUDs) have increased with more individuals using cannabis, yet few receive treatment. Health systems have adopted the Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of initiation and engagement in alcohol and other drug (AOD) dependence treatment, but little is known about the performance of these among patients with CUDs. Methods This cohort study utilized electronic health records and claims data from 7 health care systems to identify patients with documentation of a new index CUD diagnosis (no AOD diagnosis ≤60 days prior) from International Classification of Diseases, Ninth revision, codes (October 1, 2014, to August 31, 2015). The adjusted prevalence of each outcome (initiation, engagement, and a composite of both) was estimated from generalized linear regression models, across index identification settings (inpatient, emergency department, primary care, addiction treatment, and mental health/psychiatry), AOD comorbidity (patients with CUD only and CUD plus other AOD diagnoses), and patient characteristics. Results Among 15,202 patients with an index CUD diagnosis, 30.0% (95% confidence interval [CI]: 29.2–30.7%) initiated, 6.9% (95% CI: 6.2–7.7%) engaged among initiated, and 2.1% (95% CI: 1.9–2.3%) overall both initiated and engaged in treatment. The adjusted prevalence of outcomes varied across index identification settings and was highest among patients diagnosed in addiction treatment, with 25.0% (95% CI: 22.5–27.6%) initiated, 40.9% (95% CI: 34.8–47.0%) engaged, and 12.5% (95% CI: 10.0–15.1%) initiated and engaged. The adjusted prevalence of each outcome was generally highest among patients with CUD plus other AOD diagnosis at index diagnosis compared with those with CUD only, overall and across index identification settings, and was lowest among uninsured and older patients. Conclusion Among patients with a new CUD diagnosis, the proportion meeting HEDIS criteria for initiation and/or engagement in AOD treatment was low and demonstrated variation across index diagnosis settings, AOD comorbidity, and patient characteristics, pointing to opportunities for improvement.

Background & Aims Reported prevalence of primary biliary cholangitis (PBC) varies widely. Demographic features and treatment patterns are not well characterized in the United States (US). We analyzed data from the Fibrotic Liver Disease (FOLD) Consortium, drawn from 11 geographically diverse health systems, to investigate epidemiologic factors and treatment of PBC in the US. Methods We developed a validated electronic health record-based classification model to identify patients with PBC in the FOLD database from 2003 through 2014. We used multivariable modeling to assess the effects of factors associated with PBC prevalence and treatment with ursodeoxycholic acid (UDCA). Results We identified 4241 PBC cases among over 14.5 million patients in FOLD health systems; median follow-up was 5 years. Accuracy of the classification model was excellent, with an area under the receiver operating characteristic curve value of 93%, 94% sensitivity, and 87% specificity. The average patient age at diagnosis was 60 years; 21% were Hispanic, 8% were African American, and 7% were Asian American/American Indian/Pacific Islander. Half of the cohort (49%) had elevated levels of alkaline phosphatase, and overall, 70% were treated with UDCA. The estimated 12-year prevalence of PBC was 29.3 per 100,000 persons. Adjusted prevalence values were highest among women (42.8 per 100,000), White patients (29.6 per 100,000), and patients 60–70 years old (44.7 per 100,000). Prevalence was significantly lower among men and African Americans (10.7 and 19.7 per 100,000, respectively) than women and whites; men and African Americans were also less likely to receive UDCA treatment (odds ratios, 0.6 and 0.5, respectively; P Conclusions In an analysis of a large cohort of patients with PBC receiving routine clinical care, we observed significant differences in PBC prevalence and treatment by gender, race, and age.

A 2006 article published in the International Journal of Dermatology reported that oral zinc sulfate 100 mg three times daily was associated with improvement in the severity of facial rosacea (Sharquie et al. 2006; 45: 857-861). The current study was undertaken to further assess the role of zinc in the management of rosacea. This was a randomized, double-blind trial of 220 mg of zinc sulfate twice daily for 90 days in patients with moderately severe facial rosacea at baseline. Subjects were recruited in the Upper Midwest USA between August 2006 and April 2008, and followed until July 2008. Forty-four subjects completed the trial (22 in each arm). Rosacea improved in both groups. There were no differences in magnitude of improvement based on rosacea severity scores between subjects receiving zinc sulfate and subjects receiving placebo (P=0.284). Serum zinc levels were higher in subjects receiving zinc (P

There are few data from longitudinal studies of trends in primary biliary cholangitis (PBC) among patients under routine clinical care in the United States. We collected data from the Fibrotic Liver Disease consortium to investigate changes in the incidence and prevalence of PBC and the effects of patient demographics, clinical features, and treatment on mortality.We collected demographic and clinical data for the general patient population as well as PBC patients receiving care from 11 health systems in different regions of the United States (Northeast, Midwest, Northwest, and South) from January 1, 2003, through December 31, 2014. Annual percentage changes in PBC prevalence and incidence were estimated using join-point Poisson regression. Differences based on race, age, and gender were calculated with rate ratios. All-cause mortality was estimated using Cox regression with adjustment for patient characteristics and treatment with ursodeoxycholic acid (UDCA). Propensity scores were used to adjust for treatment selection bias. Analyses were adjusted by geographic regions.In our racially diverse cohort of 3488 patients with PBC (21% Hispanic, 8% African American, 7% Asian American), 70% had ever received UDCA. From 2006 through 2014, the prevalence of PBC increased from 21.7 to 39.2 per 100,000 persons. Adjusted annual percentage changes in prevalence differed among age groups (≤40 y, 41-50 y, 51-60 y, 61-70 y, and70 y), ranging from 3.0% to 7.5% (P.05). Incidence did not change significantly during the study period (4.2 vs 4.3 per 100,000 person-years in 2006 and 2014, respectively; P = .98). Ratios of prevalence for women vs men (3.9:1) and incidence for women vs men (3.2:1) were consistent over the study period. Among African Americans, the prevalence of PBC increased from 16.9 to 30.8 per 100,000 during the study period, and annual incidence ranged from 2.6 to 6.6 per 100,000 person-years. In adjusted analyses, an increased level of alkaline phosphatase at baseline was associated with significantly higher mortality (adjusted hazard ratios [aHR], 1.24; 95% CI, 1.04-1.48 for patients with levels 1-2 times the upper limit of normal and aHR, 2.27; 95% CI, 1.88-2.73 for patients with levels more than 3 times the upper limit of normal). UDCA treatment was associated with significantly reduced mortality (aHR, 0.57; 95% CI, 0.52-0.64).In an analysis of data from patients receiving routine clinical care in Fibrotic Liver Disease Consortium health systems, we found that the prevalence of PBC increased from 2004 through 2014, despite steady incidence. Patient demographic and clinical characteristics, as well as UDCA treatment, affected mortality.

Background:Medicare beneficiaries incur 27%-30% of lifetime charges in the last year of life; most charges occur in the last quarter. Factors associated with high end-of-life Medicare charges include less advanced age, non-white race, absence of advance directive, and urban residence. Methods: We analyzed Medicare hospital charges in the last year of life for nursing home residents with severe cognitive impairment, focusing on rural–urban differences. The study population consisted of 3,703 nursing home residents (1,882 rural, 1,821 urban) in Minnesota and Texas who died in 2000-2001. Data on Medicare hospital charges were obtained from 1998-2001 Centers for Medicare and Medicaid Services MedPAR files. Results: During the last year of life, unadjusted charges averaged $12,448 for rural subjects; $31,780 for urban. The charges were distributed across the last 4 quarters similarly for the 2 populations, with 15%-20% of charges incurred in each of the first 3 quarters, and 47% (rural) and 52% (urban) in the last quarter. At the individual level, a higher percentage of hospital charges were incurred in the last 90 days by urban than by rural residents (P < .001). A larger proportion of urban (43%) than rural (37%) residents were hospitalized in the final quarter. The charges for hospitalized residents (N = 1,994) were distributed similarly to those of the entire study population. Discussion: Medicare hospital charges during the last year of life were lower for rural nursing home residents with cognitive impairment than for their urban counterparts. Charges tend to be more concentrated in the last 90 days of life for urban residents.

It is unclear if vitamin D supplementation improves central blood pressure or arterial stiffness in Native American (NA) women.Healthy postmenopausal NA women were randomized to receive 400 IU or 2500 IU of vitamin D for 6 months. Central systolic blood pressure (cSBP), central pulse pressure (cPP) and aortic augmentation index (AIx) were estimated by tonometry at baseline and after 6 months.Study volunteers (n = 98) were 61 (7.3) years old. 25(OH)D was 26.4 (11.0) ng/mL. 25(OH)D was similar between the two treatment groups (p = 0.291), as were baseline cSBP, cPP, and CVD risk factors (all p 0.1). Treatment with 2500 IU of daily vitamin D3 did not affect cSBP, cPP, or AIx (all p 0.1) compared to 400 IU daily.Despite low serum 25(OH)D at baseline, 6 months of vitamin D supplementation did not improve central blood pressure parameters or arterial stiffness in NA women. CLINICAL TRIALS.NCT01490333.

OBJECTIVES: To identify factors associated with the use of selected medical services near the end of life in cognitively impaired residents of rural and urban nursing homes. DESIGN: Retrospective cohort study using Centers for Medicare and Medicaid Services administrative data for 1998 through 2002. SETTING: Minnesota and Texas nursing homes. PARTICIPANTS: Nursing home residents aged 65 and older with severe cognitive impairment who subsequently died during 2000/01. MEASUREMENTS: Minimum Data Set and Medicare Provider Analysis and Review, Hospice, and Denominator files were used to identify subjects and to assess medical service use. U.S. Department of Agriculture metro–nonmetro continuum county codes defined rural (codes 6–9) and urban (codes 0–2) nursing homes. Nursing home residents with hospice or health maintenance organization benefits were excluded. Use of hospital services at the end of life was adjusted for use of corresponding services before the last year of life. Outcome variables were feeding tube use, any hospitalization, more than 10 days of hospitalization, and intensive care unit (ICU) admission. RESULTS: The population included 3,710 subjects (1,886 rural, 1,824 urban). In multivariable logistic regression analyses (all P

This study analyzed the impact of eight common chronic medical conditions on cancer patients' health-related quality of life (HRQoL) as measured by the functional living index-cancer (FLIC). The FLIC was administered to a population of 405 people in 14 communities in the North Central US within 4–8 weeks of diagnosis with breast or colorectal cancer. At that time, patients also self-reported any other health conditions for which they had been receiving medical treatment. The impact of the selected chronic conditions on the FLIC scores was analyzed using Student's t-tests and linear multiple regression. In the bivariate analysis, patients with heart/circulation problems had lower FLIC total scores (p < 0.05), physical well-being subscale scores (p < 0.05), and nausea subscale scores (p < 0.01). Patients with diabetes had lower nausea subscale scores (p < 0.05). The social well-being subscale score was higher with the report of arthritis/joint problems (p = 0.001). In multivariate analysis adjusted for age, arthritis/joint problems were predictive of the social well-being (p < 0.01) and hardship due to cancer (p < 0.05) subscale scores; heart/circulation problems (p < 0.001) and diabetes were predictive of the nausea subscale scores. ECOG performance status was significant predictor for the FLIC total and all of the subscale scores. HRQoL as measured with the FLIC scores in patients with cancer is impacted by the presence of other concurrent health conditions; this finding has implications for HRQoL theory and application.

Context Significant barriers exist in the delivery of state-of-the-art cancer care to rural populations. Rural providers' knowledge and practices, their rural health care delivery systems, and linkages to cancer specialists are not optimal; therefore, rural cancer patient outcomes are less than achievable. Purpose To test the effects of a strategy targeting rural providers and their practice environment on patient travel for care, satisfaction, economic barriers, and health-related quality of life. Methods A group-randomized trial was conducted with 18 rural communities in the north-central United States. Twelve of these communities were included and defined as the unit of analysis for the patient outcomes portion of the study. The intervention targeted rural providers and their practice environment. The subjects were patients with breast, colorectal, lung, and prostate cancers from the rural communities. The main outcomes were patients' travel to obtain health care, satisfaction with care, perceptions of economic barriers to care, and health-related quality of life. In total, 881 patients were included. Results Group randomization was balanced. Travel for health care was significantly reduced in the community group exposed to the intervention during months 13 to 24 following cancer diagnosis. The mean miles traveled per patient were 1,326 (SE = 306) for the experimental group and 2,186 (SE = 347) for the control group (P = 0.03). No significant differences in satisfaction with care, economic barriers to care, or health-related quality of life were found. Conclusions The intervention significantly reduced cancer patient travel for health care, which suggests that access to care improved in the experimental group. The results of this study do not allow conclusion that there was no effect on other patient outcomes. The results supported the study's conceptual framework and many of its hypotheses.

Background/Aims Most HMORN members offer both insurance coverage and health care. Health plan enrollment provides a well-defined population denominator for HMORN-based research. The HMORN common data model combines electronic data, routinely collected in health care delivery or claims processing, into the Virtual Data Warehouse (VDW). Sites with health plans capture insurance enrollment in the VDW enrollment file. Recently HMORN included sites that deliver health care without offering insurance. Since health plan membership is unknown, population denominators must be determined using alternate methods. This study validated a utilization-based proxy enrollment (PE) using standard VDW enrollment (SE) in 5 HMORN sites with Epic EHR and SE files.

Some individuals of the mixed group of “lean” littermates (+/ ob and +/+) of (C57BL/6J ob/ob) often suggest phenotypic characteristics of ob/ob animals. Therefore, it was of interest to determine whether expression of the ob gene had physiological significance in +/ ob animals. Body weight (BW), fasting blood glucose (FBG), and body core temperature (Tr) were monitored between 62 and 364 days of age in +/+ and +/ obmice. Among females but not males, +/ ob mice were heavier ( P = 0.003) and FBG levels were greater ( P = 0.04) than in +/+ animals. Comparison of Trindicated differences suggesting falling Tr in +/ ob but rising Tr in +/+ mice with age in males but not females. Multivariate analysis of variance yielded genotype effects for both males ( P = 0.002) and females ( P = 0.02). BW, FBG, and Tr alone were sufficient at the 75% level for genotypic characterization and separation of +/? animals as +/ ob or +/+; clearly, expression of the ob gene in heterozygotes of the +/ ob animal may make the mixed +/? group inappropriate as lean controls.

Background/Aims Rural health describes a set of health issues, health care challenges and research priorities driven by a single geo-demographic factor: low population density. Rural areas compared to urbanized areas have fewer providers per capita, longer distance to care, lower socioeconomic status, higher rates of untreated illness, greater exposure to agricultural chemicals, and higher rates of alcohol use, fatal motor vehicle crashes, and suicide. Accessing clinical data for large numbers of rural residents can be challenging. To meet this challenge, seven sites formed the HMORN Rural Health Scientific Interest Group (SIG).

Background/Aims The Virtual Data Warehouse (VDW) was created as a mechanism to produce comparable data across sites for purposes of proposing and conducting research. The VDW is not a multi-site physical database at a centralized location, but a distributed ‘virtual’ database with the data remaining at the local sites. At the core of the VDW are a series of standardized file definitions. Content areas and data elements that are commonly required for research studies are identified, and data dictionaries are created for each of the content areas, specifying a common format for each of the elements - variable name, extended definition, code values. Local site programmers have mapped the data elements from their legacy data systems into this standardized set of variable definitions, names, and codes, as well as onto standardized SAS file formats. This common structure of the VDW files enables a SAS analyst at one site to write one program to extract and/or analyze data at all participating sites.

Background Regional variation in the intensity of end-of-life care contributes significantly to the overall cost of health care. The interpretation of patterns of regional variation hinges, in part, on appropriate adjustment for regional variation in demographic variables such as age, race, sex, and rural vs. urban residence. This study examined regional variation in discontinuation of dialysis prior to death in the US, after adjustment for key demographic variables. Methods In this retrospective cohort study of the 2009 United States Renal Data System (USRDS) database we examined discontinuation of dialysis prior to death among deceased adult patients with end-stage renal disease (ESRD) from the 50 states and the District of Columbia. The discontinuation of dialysis prior to death was ascertained from the Centers for Medicare & Medicaid Services form 2746 (ESRD Death Notification form). We used logistic regression to estimate the log-odds of discontinuation of dialysis with ESRD network as independent variable adjusted for urban–rural status, demographic and treatment variables. Results The study cohort included 715,605 deceased ESRD patients; for 176,021 of whom (24.6%) dialysis was discontinued prior to death. Dialysis was discontinued at higher rates for women than for men (26.3% vs. 23.0%, p < 0.001) and for whites than for blacks (29.5% vs. 14.7%, p < 0.001). Significant regional variation in dialysis discontinuation prior to death was noted after adjustment for age, race and rural–urban status: rates of discontinuation in the Upper Midwest and Mountain regions were more than double the rates in Southern and Coastal regions. This pattern parallels the regional pattern of end-of-life health service utilization documented in the Dartmouth Atlas and other studies. Conclusions Discontinuation of dialysis prior to death was common in the US between 1995 and 2009. The deaths of nearly one quarter of chronic dialysis patients followed a decision to discontinue dialysis. Significant regional variation in discontinuation rates exists after adjusting for age, race, sex, and rural–urban status. Further research and analysis is needed on the cultural and economic factors that affect regional variation in health services utilization, especially in regard to the use of expensive medical services near the end of life.

Introduction: More than 21% of adults in the United States (U.S.) have self-reported physician diagnosed arthritis with the prevalence increasing to 70% for adults aged 75 years and older. Despite significant disease burden of arthritis, little research has been conducted to examine health service deficits experienced by U.S. adults with this disease. Since U.S. rural residents experience more disease and greater health and health care disparities than urban residents, this study sought to ascertain the prevalence of health service deficits in U.S. adults with arthritis and to explore whether rural residents experienced greater deficits than urban residents. Methods: Multivariate techniques were performed on 2011 Behavioral Risk Factor Surveillance System data to determine if there were differences in the prevalence of health service deficits in rural versus urban adults with arthritis and if rural residency was an independent risk factor for health service deficits after controlling for socioeconomic status and race/ ethnicity. The population of interest was U.S. adults who self-reported having arthritis diagnosed by a health care provider. Results: Bivariate analysis revealed and logistic regression confirmed that among U.S. adults > 45 years of age, rural residency was a predictor for a higher prevalence of arthritis as well as for health service deficits among those with arthritis. Overall about 1 in 3 individuals > 45 years of age suffering from arthritis experienced a health deficit. The two most common health service deficits were not having a routine medical checkup within the last 12 months and deferring health care because of cost. Rural residency emerged as an independent risk factor for health service deficits after controlling for socioeconomic status and race/ethnicity. Conclusions: Many individuals with arthritis experience a health service deficit and rural residents are at greater risk when compared to their urban counterparts. Given the burden of disease from arthritis the results suggest that there is considerable potential for improving services and perhaps improving outcomes for individuals with arthritis. The finding that the most common health service deficits were delaying care because of cost and not having seen a provider within the last 12 months suggests that finances rather than simply the availability of services is a key factor.

Dual-energy X-ray absorptiometry (DXA) is widely used to evaluate body composition in athletes. Knowledge of measurement precision is essential for monitoring body composition changes over time. This study begins characterizing DXA body composition precision in 60 (30 males and 30 females) Division 1 athletes focusing on gender, regional, and tissue type differences. Two total body scans with repositioning between were performed on the same day. Least significant change (LSC) for the root-mean-square deviation (LSCRMSD) and the percent coefficient of variation (LSC%CV) for total, lean, and fat mass was calculated for 6 regions of interest. The effect of gender, region, tissue type, and mass on the standard deviation (SD) and percent coefficient of variation (%CV) between the 2 scans was evaluated using repeated measures regression analysis. Statistically significant effects of gender, region, tissue type, and mass on SD and %CV were noted. To generalize, a nonlinear positive relationship between LSCRMSD and mass and a nonlinear negative relationship between LSC%CV and mass were observed. In conclusion, DXA body composition LSC varies among genders, regions, tissues, and mass. As such, when evaluating serial body composition in athletes, especially if assessing regional change, knowledge of precision in individuals of similar body size and gender to the population of interest is needed.

Objectives Clinical guidelines for the use of opioids in chronic noncancer pain recommend assessing risk for aberrant drug-related behaviors prior to initiating opioid therapy. Despite recent dramatic increases in prescription opioid misuse and abuse, use of screening tools by clinicians continues to be underutilized. This research evaluated natural language processing (NLP) together with other data extraction techniques for risk assessment of patients considered for opioid therapy as a means of predicting opioid abuse. Design Using a retrospective cohort of 3,668 chronic noncancer pain patients with at least one opioid agreement between January 1, 2007, and December 31, 2012, we examined the availability of electronic health record structured and unstructured data to populate the Opioid Risk Tool (ORT) and other selected outcomes. Clinician-documented opioid agreement violations in the clinical notes were determined using NLP techniques followed by manual review of the notes. Results Confirmed through manual review, the NLP algorithm had 96.1% sensitivity, 92.8% specificity, and 92.6% positive predictive value in identifying opioid agreement violation. At the time of most recent opioid agreement, automated ORT identified 42.8% of patients as at low risk, 28.2% as at moderate risk, and 29.0% as at high risk for opioid abuse. During a year following the agreement, 22.5% of patients had opioid agreement violations. Patients classified as high risk were three times more likely to violate opioid agreements compared with those with low/moderate risk. Conclusion Our findings suggest that NLP techniques have potential utility to support clinicians in screening chronic noncancer pain patients considered for long-term opioid therapy.