Publications by authors named "Matthew L Maciejewski"

230 Publications

Unintended consequences of COVID-19 social distancing among older adults with kidney disease.

J Gerontol A Biol Sci Med Sci 2021 Jul 21. Epub 2021 Jul 21.

Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, NC.

Background: While social distancing policies protect older adults with advanced chronic kidney disease (CKD) from exposure to COVID-19, reduced social interaction may also have unintended consequences.

Methods: To identify subgroups of patients at risk for unintended health consequences of social distancing, we conducted a cross-sectional analysis of data from a national cohort study of older Veterans with advanced CKD (n=223). Characteristics included activities of daily living (ADLs), instrumental ADLs (IADLs), cognition score, depression score, social support, financial stress, symptom burden, and number of chronic conditions. Unintended consequences of social distancing included restricted Life Space mobility, low willingness for video telehealth, reduced in-person contact with caregivers, and food insecurity. We identified subgroups of patients at risk of unintended consequences using model-based recursive partitioning (MoB).

Results: Participants had a mean age of 77.9 years, 64.6% were white, and 96.9% were male. Overall, 22.4% of participants had restricted Life Space, 33.9% reported low willingness for video telehealth, 19.0% reported reduced caregiver contact, and 3.2% reported food insecurity. For Life Space restriction, four subgroups partitioned (i.e., split) by IADL difficulty, cognition score, and ADL difficulty were identified. The highest rate of restricted Life Space was 54.7% in the subgroup of participants with >3 IADL difficulties For low willingness for telehealth and reduced caregiver contact, separate models identified two subgroups split by cognition score and depression score, respectively.

Conclusions: Measures of function, cognition, and depressive symptoms may identify older adults with advanced CKD who are at higher risk for unintended health consequences of social distancing.
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http://dx.doi.org/10.1093/gerona/glab211DOI Listing
July 2021

Annual wellness visits and care management before and after dialysis initiation.

BMC Nephrol 2021 May 5;22(1):164. Epub 2021 May 5.

Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, NC, USA.

Introduction: Demands of dialysis regimens may pose challenges for primary care provider (PCP) engagement and timely preventive care. This is especially the case for patients initiating dialysis adjusting to new logistical challenges and management of symptoms and existing comorbid conditions. Since 2011, Medicare has provided coverage for annual wellness visits (AWV), which are primarily conducted by PCPs and may be useful for older adults undergoing dialysis.

Methods: We used the OptumLabs® Data Warehouse to identify a cohort of 1,794 Medicare Advantage (MA) enrollees initiating dialysis in 2014-2017 and examined whether MA enrollees (1) were seen by a PCP during an outpatient visit and (2) received an AWV in the year following dialysis initiation.

Results: In the year after initiating dialysis, 93 % of MA enrollees had an outpatient PCP visit but only 24 % received an annual wellness visit. MA enrollees were less likely to see a PCP if they had Charlson comorbidity scores between 0 and 5 than those with scores 6-9 (odds ratio (OR) = 0.59, 95 % CI: 0.37-0.95), but more likely if seen by a nephrologist (OR = 1.60, 95 % CI: 1.01-2.52) or a PCP (OR = 15.65, 95 % CI: 9.26-26.46) prior to initiation. Following dialysis initiation, 24 % of MA enrollees had an AWV. Hispanic MA enrollees were less likely (OR = 0.57, 95 % CI: 0.39-0.84) to have an AWV than White MA enrollees, but enrollees were more likely if they initiated peritoneal dialysis (OR = 1.54, 95 % CI: 1.07-2.23) or had an AWV in the year before dialysis initiation (OR = 4.96, 95 % CI: 3.88-6.34).

Conclusions: AWVs are provided at low rates to MA enrollees initiating dialysis, particularly Hispanic enrollees, and represent a missed opportunity for better care management for patients with ESKD. Increasing patient awareness and provider provision of AWV use among dialysis patients may be needed, to realize better preventive care for dialysis patients.
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http://dx.doi.org/10.1186/s12882-021-02368-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097997PMC
May 2021

The association of alcohol use with all-cause and cardiovascular disease-related hospitalizations or death in older, high-risk Veterans.

Alcohol Clin Exp Res 2021 06 4;45(6):1215-1224. Epub 2021 May 4.

Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT, Durham Veterans Affairs Health Care System, Durham, NC, USA.

Background: The prevalence of alcohol misuse among older adults has grown dramatically in the past decade, yet little is known about the association of alcohol misuse with hospitalization and death in this patient population.

Methods: We examined the association between alcohol use (measured by a screening instrument in primary care) and rates of all-cause and cardiovascular disease (CVD)-related 6-month hospitalization or death via electronic health records (EHRs) in a nationally representative sample of older, high-risk Veterans. Models were adjusted for sociodemographic and clinical characteristics, including frailty and comorbid conditions.

Results: The all-cause hospitalization or death rate at 6 months was 14.9%, and the CVD-related hospitalization or death rate was 1.8%. In adjusted analyses, all-cause hospitalization or death was higher in older Veterans who were nondrinkers or harmful use drinkers compared to moderate use drinkers, but CVD-related hospitalization or death was similar in all categories of drinking.

Conclusions: These findings suggest that the complex association between alcohol and all-cause acute healthcare utilization found in the broader population is similar in older, high-risk Veteran patients. These findings do not support an association between alcohol consumption and CVD-specific hospitalizations.
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http://dx.doi.org/10.1111/acer.14610DOI Listing
June 2021

Subgroups of High-Risk Veterans Affairs Patients Based on Social Determinants of Health Predict Risk of Future Hospitalization.

Med Care 2021 May;59(5):410-417

Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System.

Objective: Population segmentation has been recognized as a foundational step to help tailor interventions. Prior studies have predominantly identified subgroups based on diagnoses. In this study, we identify clinically coherent subgroups using social determinants of health (SDH) measures collected from Veterans at high risk of hospitalization or death.

Study Design And Setting: SDH measures were obtained for 4684 Veterans at high risk of hospitalization through mail survey. Eleven self-report measures known to impact hospitalization and amenable to intervention were chosen a priori by the study team to identify subgroups through latent class analysis. Associations between subgroups and demographic and comorbidity characteristics were calculated through multinomial logistic regression. Odds of 180-day hospitalization were compared across subgroups through logistic regression.

Results: Five subgroups of high-risk patients emerged-those with: minimal SDH vulnerabilities (8% hospitalized), poor/fair health with few SDH vulnerabilities (12% hospitalized), social isolation (10% hospitalized), multiple SDH vulnerabilities (12% hospitalized), and multiple SDH vulnerabilities without food or medication insecurity (10% hospitalized). In logistic regression, the "multiple SDH vulnerabilities" subgroup had greater odds of 180-day hospitalization than did the "minimal SDH vulnerabilities" reference subgroup (odds ratio: 1.53, 95% confidence interval: 1.09-2.14).

Conclusion: Self-reported SDH measures can identify meaningful subgroups that may be used to offer tailored interventions to reduce their risk of hospitalization and other adverse events.
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http://dx.doi.org/10.1097/MLR.0000000000001526DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034377PMC
May 2021

A machine learning approach to identify distinct subgroups of veterans at risk for hospitalization or death using administrative and electronic health record data.

PLoS One 2021 19;16(2):e0247203. Epub 2021 Feb 19.

Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, United States of America.

Background: Identifying individuals at risk for future hospitalization or death has been a major priority of population health management strategies. High-risk individuals are a heterogeneous group, and existing studies describing heterogeneity in high-risk individuals have been limited by data focused on clinical comorbidities and not socioeconomic or behavioral factors. We used machine learning clustering methods and linked comorbidity-based, sociodemographic, and psychobehavioral data to identify subgroups of high-risk Veterans and study long-term outcomes, hypothesizing that factors other than comorbidities would characterize several subgroups.

Methods And Findings: In this cross-sectional study, we used data from the VA Corporate Data Warehouse, a national repository of VA administrative claims and electronic health data. To identify high-risk Veterans, we used the Care Assessment Needs (CAN) score, a routinely-used VA model that predicts a patient's percentile risk of hospitalization or death at one year. Our study population consisted of 110,000 Veterans who were randomly sampled from 1,920,436 Veterans with a CAN score≥75th percentile in 2014. We categorized patient-level data into 119 independent variables based on demographics, comorbidities, pharmacy, vital signs, laboratories, and prior utilization. We used a previously validated density-based clustering algorithm to identify 30 subgroups of high-risk Veterans ranging in size from 50 to 2,446 patients. Mean CAN score ranged from 72.4 to 90.3 among subgroups. Two-year mortality ranged from 0.9% to 45.6% and was highest in the home-based care and metastatic cancer subgroups. Mean inpatient days ranged from 1.4 to 30.5 and were highest in the post-surgery and blood loss anemia subgroups. Mean emergency room visits ranged from 1.0 to 4.3 and were highest in the chronic sedative use and polysubstance use with amphetamine predominance subgroups. Five subgroups were distinguished by psychobehavioral factors and four subgroups were distinguished by sociodemographic factors.

Conclusions: High-risk Veterans are a heterogeneous population consisting of multiple distinct subgroups-many of which are not defined by clinical comorbidities-with distinct utilization and outcome patterns. To our knowledge, this represents the largest application of ML clustering methods to subgroup a high-risk population. Further study is needed to determine whether distinct subgroups may benefit from individualized interventions.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0247203PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7894856PMC
February 2021

A Method to Quantify Mean Hypertension Treatment Daily Dose Intensity Using Health Care System Data.

JAMA Netw Open 2021 01 4;4(1):e2034059. Epub 2021 Jan 4.

Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis.

Importance: Simple measures of hypertension treatment, such as achievement of blood pressure (BP) targets, ignore the intensity of treatment once the BP target is met. High-intensity treatment involves increased treatment burden and can be associated with potential adverse effects in older adults. A method was previously developed to identify older patients receiving intense hypertension treatment by low BP and number of BP medications using national Veterans Health Administration and Medicare Part D administrative pharmacy data to evaluate which BP medications a patient is likely taking on any given day.

Objective: To further develop and validate a method to more precisely quantify dose intensity of hypertension treatment using only health system administrative pharmacy fill data.

Design, Setting, And Participants: Observational, cross-sectional study of 319 randomly selected older veterans in the national Veterans Health Administration health care system who were taking multiple BP-lowering medications and had a total of 3625 ambulatory care visits from July 1, 2011, to June 30, 2013. Measure development and medical record review occurred January 1, 2017, through November 30, 2018, and data analysis was conducted from December 1, 2019, to August 31, 2020.

Main Outcomes And Measures: For each BP-lowering medication, a moderate hypertension daily dose (HDD) was defined as half the maximum dose above which no further clinical benefit has been demonstrated by that medication in hypertension trials. Patients' total HDD was calculated using pharmacy data (pharmacy HDDs), accounting for substantial delays in refills (>30 days) when a patient's pill supply was stretched (eg, cutting existing pills in half). As an external comparison, the pharmacy HDDs were correlated with doses manually extracted from clinicians' visit notes (clinically noted HDDs). How well the pharmacy HDDs correlated with clinically noted HDDs was calculated (using C statistics). To facilitate interpretation, HDDs were described in association with the number of medications.

Results: A total of 316 patients (99.1%) were male; the mean (SD) age was 75.6 (7.2) years. Pharmacy HDDs were highly correlated (r = 0.92) with clinically noted HDDs, with a mean (SD) of 2.7 (1.8) for pharmacy HDDs and 2.8 (1.8) for clinically noted HDDs. Pharmacy HDDs correlated with high-intensity, clinically noted HDDs ranging from a C statistic of 92.8% (95% CI, 92.0%-93.7%) for 2 or more clinically noted HDDs to 88.1% (95% CI, 85.5%-90.6%) for 6 or more clinically noted HDDs.

Conclusions And Relevance: This study suggests that health system pharmacy data may be used to accurately quantify hypertension regimen dose intensity. Together with clinic-measured BP, this tool can be used in future health system-based research or quality improvement efforts to fine-tune, manage, and optimize hypertension treatment in older adults.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.34059DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7811181PMC
January 2021

Association of Bariatric Surgical Procedures With Changes in Unhealthy Alcohol Use Among US Veterans.

JAMA Netw Open 2020 12 1;3(12):e2028117. Epub 2020 Dec 1.

Kaiser Permanente Washington Health Research Institute, Seattle, Washington.

Importance: Bariatric surgical procedures have been associated with increased risk of unhealthy alcohol use, but no previous research has evaluated the long-term alcohol-related risks after laparoscopic sleeve gastrectomy (LSG), currently the most used bariatric procedure. No US-based study has compared long-term alcohol-related outcomes between patients who have undergone Roux-en-Y gastric bypass (RYGB) and those who have not.

Objective: To evaluate the changes over time in alcohol use and unhealthy alcohol use from 2 years before to 8 years after a bariatric surgical procedure among individuals with or without preoperative unhealthy alcohol use.

Design, Setting, And Participants: This retrospective cohort study analyzed electronic health record (EHR) data on military veterans who underwent a bariatric surgical procedure at any of the bariatric centers in the US Department of Veterans Affairs (VA) health system between October 1, 2008, and September 30, 2016. Surgical patients without unhealthy alcohol use at baseline were matched using sequential stratification to nonsurgical control patients without unhealthy alcohol use at baseline, and surgical patients with unhealthy alcohol use at baseline were matched to nonsurgical patients with unhealthy alcohol use at baseline. Data were analyzed in February 2020.

Interventions: LSG (n = 1684) and RYGB (n = 924).

Main Outcomes And Measures: Mean alcohol use, unhealthy alcohol use, and no alcohol use were estimated using scores from the validated 3-item Alcohol Use Disorders Identification Test-Consumption (AUDIT-C), which had been documented in the VA EHR. Alcohol outcomes were estimated with mixed-effects models.

Results: A total of 2608 surgical patients were included in the final cohort (1964 male [75.3%] and 644 female [24.7%] veterans. Mean (SD) age of surgical patients was 53.0 (9.9) years and 53.6 (9.9) years for the matched nonsurgical patients. Among patients without baseline unhealthy alcohol use, 1539 patients who underwent an LSG were matched to 14 555 nonsurgical control patients and 854 patients who underwent an RYGB were matched to 8038 nonsurgical control patients. In patients without baseline unhealthy alcohol use, the mean AUDIT-C scores and the probability of unhealthy alcohol use both increased significantly 3 to 8 years after an LSG or an RYGB, compared with control patients. Eight years after an LSG, the probability of unhealthy alcohol use was higher in surgical vs control patients (7.9% [95% CI, 6.4-9.5] vs 4.5% [95% CI, 4.1-4.9]; difference, 3.4% [95% CI, 1.8-5.0])). Similarly, 8 years after an RYGB, the probability of unhealthy alcohol use was higher in surgical vs control patients (9.2% [95% CI, 8.0-10.3] vs 4.4% [95% CI, 4.1-4.6]; difference, 4.8% [95% CI, 3.6-5.9]). The probability of no alcohol use also decreased significantly 5 to 8 years after both procedures for surgical vs control patients. Among patients with unhealthy alcohol use at baseline, prevalence of unhealthy alcohol use was higher for patients who underwent an RYGB than matched controls.

Conclusions And Relevance: In this multi-site cohort study of predominantly male patients, among those who did not have unhealthy alcohol use in the 2 years before bariatric surgery, the probability of developing unhealthy alcohol use increased significantly 3-8 years after bariatric procedures compared with matched controls during follow-up.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.28117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7753905PMC
December 2020

Comparing Mortality of Peritoneal and Hemodialysis Patients in an Era of Medicare Payment Reform.

Med Care 2021 02;59(2):155-162

Departments of Population Health Sciences.

Background: Prior studies have shown peritoneal dialysis (PD) patients to have lower or equivalent mortality to patients who receive in-center hemodialysis (HD). Medicare's 2011 bundled dialysis prospective payment system encouraged expansion of home-based PD with unclear impacts on patient outcomes. This paper revisits the comparative risk of mortality between HD and PD among patients with incident end-stage kidney disease initiating dialysis in 2006-2013.

Research Design: We conducted a retrospective cohort study comparing 2-year all-cause mortality among patients with incident end-stage kidney disease initiating dialysis via HD and PD in 2006-2013, using data from the US Renal Data System and Medicare. Analysis was conducted using Cox proportional hazards models fit with inverse probability of treatment weighting that adjusted for measured patient demographic and clinical characteristics and dialysis market characteristics.

Results: Of the 449,652 patients starting dialysis between 2006 and 2013, the rate of PD use in the first 90 days increased from 9.3% of incident patients in 2006 to 14.2% in 2013. Crude 2-year mortality was 27.6% for patients dialyzing via HD and 16.7% for patients on PD. In adjusted models, there was no evidence of mortality differences between PD and HD before and after bundled payment (hazard ratio, 0.96; 95% confidence interval, 0.89-1.04; P=0.33).

Conclusions: Overall mortality for HD and PD use was similar and mortality differences between modalities did not change before versus after the 2011 Medicare dialysis bundled payment, suggesting that increased use of home-based PD did not adversely impact patient outcomes.
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http://dx.doi.org/10.1097/MLR.0000000000001457DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855236PMC
February 2021

Opioid Prescribing in the 2016 Medicare Fee-for-Service Population.

J Am Geriatr Soc 2021 Feb 20;69(2):485-493. Epub 2020 Nov 20.

Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA.

Background And Objectives: Opioid use and misuse are prevalent and remain a national crisis. This study identified beneficiary characteristics associated with filling opioid prescriptions, variation in opioid dosing, and opioid use with average daily doses (ADDs) equal to 120 morphine milligram equivalents (MMEs) or more in the 100% Medicare fee-for-service (FFS) population.

Design, Setting, Participants, And Measurements: In a cohort of FFS beneficiaries with 12 months of Medicare Part D coverage in 2016, we examined patient factors associated with filling an opioid prescription (n = 20,880,490) and variation in ADDs (n = 7,325,031) in a two-part model. Among those filling opioids, we also examined the probability of ADD equal to 120 MMEs or more via logistic regression.

Results: About 35% of FFS beneficiaries had one or more opioid prescription fills in 2016 and 1.5% had ADDs equal to 120 MMEs or more. Disability-eligible beneficiaries and beneficiaries with multiple chronic conditions were more likely to fill opioids, to have higher ADDs or were more likely to have ADD equal to 120 MMEs or more. Beneficiaries with chronic obstructive pulmonary disease (COPD) were more likely to fill opioids (odds ratio (OR) = 1.47, 95% confidence interval (CI) = 1.46-1.47), have higher ADDs (rate ratio = 1.06, 95% CI = 1.06-1.06) when filled and were more likely to have ADD equal to 120 MMEs or more (OR = 1.23, 95% CI = 1.21-1.24). Finally, black and Hispanic beneficiaries were less likely to fill opioids, had lower overall doses and were less likely to have ADDs equal to 120 MMEs or more compared to white beneficiaries.

Conclusion: Several beneficiary subgroups have underappreciated risk of adverse events associated with ADD equal to 120 MMEs or more that may benefit from opioid optimization interventions that balance pain management and adverse event risk, especially beneficiaries with COPD who are at risk for respiratory depression.
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http://dx.doi.org/10.1111/jgs.16911DOI Listing
February 2021

Factors associated with non-adherence to insulin and non-insulin medications in patients with poorly controlled diabetes.

Chronic Illn 2020 Oct 25:1742395320968627. Epub 2020 Oct 25.

Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham VA Medical Center, Durham, USA.

Objectives: To evaluate differences in factors associated with self-reported medication non-adherence to insulin and non-insulin medications in patients with uncontrolled type 2 diabetes.

Methods: In this secondary analysis of a randomized trial in patients with obesity and uncontrolled type 2 diabetes, multivariable logistic regression was used to evaluate associations between several clinical factors (measured with survey questionnaires at study baseline) and self-reported non-adherence to insulin and non-insulin medications.

Results: Among 263 patients, reported non-adherence was 62% (52% for insulin, 55% for non-insulin medications). Reported non-adherence to non-insulin medications was less likely in white versus non-white patients (odds ratio (OR) = 0.42; 95%CI: 0.22,0.80) and with each additional medication taken (OR = 0.75; 95%CI: 0.61,0.93). Non-adherence to non-insulin medications was more likely with each point increase in a measure of diabetes medication intensity (OR = 1.43; 95%CI: 1.01,2.03), the Problem Areas in Diabetes (PAID) score (OR = 1.06; 95%CI: 1.02,1.12), and in men versus women (OR = 3.03; 95%CI: 1.06,8.65). For insulin, reporting non-adherence was more likely (OR = 1.02; 95%CI: 1.00,1.04) with each point increase in the PAID.

Discussion: Despite similar overall rates of reported non-adherence to insulin and non-insulin medications, factors associated with reported non-adherence to each medication type differed. These findings may help tailor approaches to supporting adherence in patients using different types of diabetes medications.
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http://dx.doi.org/10.1177/1742395320968627DOI Listing
October 2020

Patient-Reported Social and Behavioral Determinants of Health and Estimated Risk of Hospitalization in High-Risk Veterans Affairs Patients.

JAMA Netw Open 2020 10 1;3(10):e2021457. Epub 2020 Oct 1.

Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina.

Importance: Despite recognition of the association between individual social and behavioral determinants of health (SDH) and patient outcomes, little is known regarding the value of SDH in explaining variation in outcomes for high-risk patients.

Objective: To describe SDH factors among veterans who are at high risk for hospitalization, and to determine whether adding patient-reported SDH measures to electronic health record (EHR) measures improves estimation of 90-day and 180-day all-cause hospital admission.

Design, Setting, And Participants: A survey was mailed between April 16 and June 29, 2018, to a nationally representative sample of 10 000 Veterans Affairs (VA) patients whose 1-year risk of hospitalization or death was in the 75th percentile or higher based on a VA EHR-derived risk score. The survey included multiple SDH measures, such as resilience, social support, health literacy, smoking status, transportation barriers, and recent life stressors.

Main Outcomes And Measures: The EHR-based characteristics of survey respondents and nonrespondents were compared using standardized differences. Estimation of 90-day and 180-day hospital admission risk was assessed for 3 logistic regression models: (1) a base model of all prespecified EHR-based covariates, (2) a restricted model of EHR-based covariates chosen via forward selection based on minimizing Akaike information criterion (AIC), and (3) a model of EHR- and survey-based covariates chosen via forward selection based on AIC minimization.

Results: In total, 4685 individuals (response rate 46.9%) responded to the survey. Respondents were comparable to nonrespondents in most characteristics, but survey respondents were older (eg, >80 years old, 881 [18.8%] vs 800 [15.1%]), comprised a higher percentage of men (4391 [93.7%] vs 4794 [90.2%]), and were composed of more White non-Hispanic individuals (3366 [71.8%] vs 3259 [61.3%]). Based on AIC, the regression model with survey-based covariates and EHR-based covariates better estimated hospital admission at 90 days (AIC, 1947.7) and 180 days (AIC, 2951.9) than restricted models with only EHR-based covariates (AIC, 1980.2 at 90 days; AIC, 2981.9 at 180 days). This result was due to inclusion of self-reported measures such as marital or partner status, health-related locus of control, resilience, smoking status, health literacy, and medication insecurity.

Conclusions And Relevance: Augmenting EHR data with patient-reported social information improved estimation of 90-day and 180-day hospitalization risk, highlighting specific SDH factors that might identify individuals who are at high risk for hospitalization.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.21457DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576406PMC
October 2020

Practical telehealth to improve control and engagement for patients with clinic-refractory diabetes mellitus (PRACTICE-DM): Protocol and baseline data for a randomized trial.

Contemp Clin Trials 2020 11 21;98:106157. Epub 2020 Sep 21.

Durham Veterans Affairs Center of Innovation to Accelerate Discovery and Practice Change (ADAPT), Durham, NC, United States of America; Division of Endocrinology, Department of Medicine, Duke University School of Medicine, Durham, NC, United States of America. Electronic address:

Background: Persistent poorly-controlled type 2 diabetes mellitus (PPDM), or maintenance of a hemoglobin A1c (HbA1c) ≥8.5% despite receiving clinic-based diabetes care, contributes disproportionately to the national diabetes burden. Comprehensive telehealth interventions may help ameliorate PPDM, but existing approaches have rarely been designed with clinical implementation in mind, limiting use in routine practice. We describe a study testing a novel telehealth intervention that comprehensively targets clinic-refractory PPDM, and was explicitly developed for practical delivery using existing Veterans Health Administration (VHA) clinical infrastructure.

Methods: Practical Telehealth to Improve Control and Engagement for Patients with Clinic-Refractory Diabetes Mellitus (PRACTICE-DM) is an ongoing randomized controlled trial comparing two 12-month interventions: 1) standard VHA Home Telehealth (HT) telemonitoring/care coordination; or 2) the PRACTICE-DM intervention, a comprehensive HT-delivered intervention combining telemonitoring, self-management support, diet/activity support, medication management, and depression management. The primary outcome is HbA1c. Secondary outcomes include diabetes distress, self-care, self-efficacy, weight, depressive symptoms, implementation barriers/facilitators, and costs. We hypothesize that the PRACTICE-DM intervention will reduce HbA1c by >0.6% versus standard HT over 12 months.

Results: Enrollment for this ongoing trial concluded in January 2020; 200 patients were randomized (99 to standard HT and 101 to the PRACTICE-DM intervention). The cohort has a mean age of 58 and is 23% female and 72% African American. Mean baseline HbA1c and BMI were 10.2% and 34.8 kg/m.

Conclusions: Because it comprehensively targets factors underlying PPDM using existing clinical infrastructure, the PRACTICE-DM intervention may be well suited to lower the complications and costs of PPDM in routine practice.
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http://dx.doi.org/10.1016/j.cct.2020.106157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505207PMC
November 2020

Association of VA Payment Reform for Dialysis with Spending, Access to Care, and Outcomes for Veterans with ESKD.

Clin J Am Soc Nephrol 2020 11 22;15(11):1631-1639. Epub 2020 Sep 22.

Center of Innovation for Long Term Services and Supports, Providence Veterans Affairs Health Care System, Providence, Rhode Island.

Background And Objectives: Because of the limited capacity of its own dialysis facilities, the Department of Veterans Affairs (VA) Veterans Health Administration routinely outsources dialysis care to community providers. Prior to 2011-when the VA implemented a process of standardizing payments and establishing national contracts for community-based dialysis care-payments to community providers were largely unregulated. This study examined the association of changes in the Department of Veterans Affairs payment policy for community dialysis with temporal trends in VA spending and veterans' access to dialysis care and mortality.

Design, Setting, Participants, & Measurements: An interrupted time series design and VA, Medicare, and US Renal Data System data were used to identify veterans who received VA-financed dialysis in community-based dialysis facilities before (2006-2008), during (2009-2010), and after the enactment of VA policies to standardize dialysis payments (2011-2016). We used multivariable, differential trend/intercept shift regression models to examine trends in average reimbursement for community-based dialysis, access to quality care (veterans' distance to community dialysis, number of community dialysis providers, and dialysis facility quality indicators), and 1-year mortality over this time period.

Results: Before payment reform, the unadjusted average per-treatment reimbursement for non-VA dialysis care varied widely ($47-$1575). After payment reform, there was a 44% reduction ($44-$250) in the adjusted price per dialysis session (<0.001) and less variation in payments for dialysis ($73-$663). Over the same time period, there was an increase in the number of community dialysis facilities contracting with VA to deliver care to veterans with ESKD from 19 to 37 facilities (per VA hospital), and there were no changes in either the quality of community dialysis facilities or crude 1-year mortality rate of veterans (12% versus 11%).

Conclusions: VA policies to standardize payment and establish national dialysis contracts increased the value of VA-financed community dialysis care by reducing reimbursement without compromising access to care or survival.
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http://dx.doi.org/10.2215/CJN.02100220DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646236PMC
November 2020

A data-driven examination of which patients follow trial protocol.

Contemp Clin Trials Commun 2020 Sep 13;19:100631. Epub 2020 Aug 13.

Durham Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, NC, USA.

Protocol adherence in behavioral intervention clinical trials is critical to trial success. There is increasing interest in understanding which patients are more likely to adhere to trial protocols. The objective of this study was to demonstrate the use of a data-driven approach to explore patient characteristics associated with the lowest and highest rates of adherence in three trials assessing interventions targeting behaviors related to lifestyle and risk for cardiovascular disease. Each trial included a common set of baseline variables. Model-based recursive partitioning (MoB) was applied in each trial to identify participant characteristics of subgroups characterized by these baseline variables with differences in protocol adherence. Bootstrap resampling was conducted to provide optimism-corrected c-statistics of the final solutions. In the three trials, rates of protocol adherence varied from 56.9% to 87.5%. Evaluation of heterogeneity of protocol adherence via MoB in each trial resulted in trees with 2-4 subgroups based on splits of 1-3 variables. In two of the three trials, the first split was based on pain in the past week, and those reporting lower pain were less likely to be adherent. In one of these trials, the second and third splits were based on education and employment, where those with lower education levels and who were employed were less likely to be adherent. In the third trial, the two splits were based on smoking status and then marriage status, where smokers who were married were least likely to be adherent. Optimism-corrected c-statistics ranged from 0.54 to 0.63. Model-based recursive partitioning can be a useful approach to explore heterogeneity in protocol adherence in behavioral intervention trials. An important next step would be to assess whether patterns hold in other similar studies and samples. Identifying subgroups who are less likely to be adherent to an intervention can help inform modifications to the intervention to help tailor the intervention to these subgroups and increase future uptake and impact.

Trial Registration: ClinicalTrials.gov identifiers: NCT01828567, NCT02360293, and NCT01838226.
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http://dx.doi.org/10.1016/j.conctc.2020.100631DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471618PMC
September 2020

Payer Mix Among Patients Receiving Dialysis-Reply.

JAMA 2020 09;324(9):901

Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.

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http://dx.doi.org/10.1001/jama.2020.10774DOI Listing
September 2020

Validation of a Health System Measure to Capture Intensive Medication Treatment of Hypertension in the Veterans Health Administration.

JAMA Netw Open 2020 07 1;3(7):e205417. Epub 2020 Jul 1.

VA Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan.

Importance: Blood pressure (BP) targets are the main measure of high-quality hypertension care in health systems. However, BP alone does not reflect intensity of pharmacological treatment, which should be carefully managed in older patients.

Objectives: To develop and validate an electronic health record (EHR) data-only algorithm using pharmacy and BP data to capture intensive hypertension care (IHC), defined as 3 or more BP medications and BP less than 120 mm Hg, and to identify conditions associated with greater IHC, either through greater algorithm false-positive IHC, or by contributing clinically to delivering more IHC.

Design, Setting, And Participants: This cross-sectional study was conducted among 319 randomly selected patients aged 65 years or older receiving IHC from the Veterans Health Administration (VHA) from July 1, 2011, to June 30, 2013. Data were collected from a total of 3625 primary care visits. Data were analyzed from January 2017 to March 2020.

Exposures: Calibration and measurement of the algorithm for IHC (algorithm IHC).

Main Outcomes And Measures: For each primary care visit, the reference standard, clinical IHC, was determined by detailed review of free-text clinical notes. The correlation in BP medication count between the EHR-only algorithm vs the reference standard and the sensitivity and specificity of the algorithm IHC were calculated. In addition, presence vs absence of contributing conditions acting in combination with hypertension management were measured to examine incidence of IHC associated with contributing conditions, including an acute condition that lowered BP (eg, dehydration), another condition requiring a BP target lower than the standard 140 mm Hg (eg, diabetes), or the patient needing a BP-lowering medication for a nonhypertension condition (eg, β-blocker for atrial fibrillation) resulting in low BP.

Results: Among 319 patients with 3625 visits (mean [SD] age, 75.6 [7.2] years; 3592 [99.1%] men), 911 visits (25.1%) had clinical IHC by the reference standard. The algorithm for determining medication count was highly correlated with the reference standard (r = 0.84). Sensitivity of detecting clinical IHC was 92.2% (95% CI, 89.3%-95.1%), and specificity was 97.2% (95% CI, 96.1%-98.3%), suggesting that clinical IHC can be identified from routinely collected data. Only 75 visits (2.1%) were algorithm IHC false positives, 55 visits (1.5%) involved IHC with contributing conditions, and 125 visits (3.5%) involved either false-positive or IHC with contributing conditions. Among select contributing conditions, congestive heart failure (37 patients [5.2%]) was most associated with a prespecified combined false-positive or IHC with contributing conditions rate higher than 5%.

Conclusions And Relevance: These findings suggest that health system data can be used reliably to estimate IHC.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.5417DOI Listing
July 2020

Designing a Primary Care-Based Deprescribing Intervention for Patients with Dementia and Multiple Chronic Conditions: a Qualitative Study.

J Gen Intern Med 2020 12 29;35(12):3556-3563. Epub 2020 Jul 29.

Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA.

Background: Patients with dementia and multiple chronic conditions (MCC) frequently experience polypharmacy, increasing their risk of adverse drug events.

Objectives: To elucidate patient, family, and physician perspectives on medication discontinuation and recommended language for deprescribing discussions in order to inform an intervention to increase awareness of deprescribing among individuals with dementia and MCC, family caregivers and primary care physicians. We also explored participant views on culturally competent approaches to deprescribing.

Design: Qualitative approach based on semi-structured interviews with patients, caregivers, and physicians.

Participants: Patients aged ≥ 65 years with claims-based diagnosis of dementia, ≥ 1 additional chronic condition, and ≥ 5 chronic medications were recruited from an integrated delivery system in Colorado and an academic medical center in Maryland. We included caregivers when present or if patients were unable to participate due to severe cognitive impairment. Physicians were recruited within the same systems and through snowball sampling, targeting areas with large African American and Hispanic populations.

Approach: We used constant comparison to identify and compare themes between patients, caregivers, and physicians.

Key Results: We conducted interviews with 17 patients, 16 caregivers, and 16 physicians. All groups said it was important to earn trust before deprescribing, frame deprescribing as routine and positive, align deprescribing with goals of dementia care, and respect caregivers' expertise. As in other areas of medicine, racial, ethnic, and language concordance was important to patients and caregivers from minority cultural backgrounds. Participants favored direct-to-patient educational materials, support from pharmacists and other team members, and close follow-up during deprescribing. Patients and caregivers favored language that explained deprescribing in terms of altered physiology with aging. Physicians desired communication tips addressing specific clinical situations.

Conclusions: Culturally sensitive communication within a trusted patient-physician relationship supplemented by pharmacists, and language tailored to specific clinical situations may support deprescribing in primary care for patients with dementia and MCC.
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http://dx.doi.org/10.1007/s11606-020-06063-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728901PMC
December 2020

High-Deductible Health Plans and Health Savings Accounts: A Match Made in Heaven but Not for This Irrational World.

JAMA Netw Open 2020 07 1;3(7):e2011000. Epub 2020 Jul 1.

Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina.

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http://dx.doi.org/10.1001/jamanetworkopen.2020.11000DOI Listing
July 2020

Regression Discontinuity Design.

JAMA 2020 07;324(4):381-382

The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, Departments of Pharmacy, Health Services, and Economics, University of Washington, Seattle.

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http://dx.doi.org/10.1001/jama.2020.3822DOI Listing
July 2020

Long-term opioid use after bariatric surgery.

Surg Obes Relat Dis 2020 Aug 7;16(8):1100-1110. Epub 2020 May 7.

University of North Dakota School of Medicine and Health Sciences, Fargo, North Dakota.

Background: Opioid analgesics are often prescribed to manage pain after bariatric surgery, which may develop into chronic prescription opioid use (CPOU) in opioid-naïve patients. Bariatric surgery may affect opioid use in those with or without presurgical CPOU.

Objective: To compare CPOU persistence and incidence in a large multisite cohort of veterans undergoing bariatric surgery (open Roux-en-Y gastric bypass, laparoscopic RYGB, or laparoscopic sleeve gastrectomy) and matched nonsurgical controls.

Setting: Veterans Administration hospitals.

Methods: In a retrospective cohort study, we matched 1117 surgical patients with baseline CPOU to 9531 nonsurgical controls, and 2822 surgical patients without CPOU at baseline to 26,392 nonsurgical controls using sequential stratification. CPOU persistence in veterans with baseline CPOU was estimated using generalized estimating equations by procedure type. CPOU incidence in veterans without baseline CPOU was estimated in Cox regression models by procedure type because postoperative pain, complications, and absorption may differ by procedure.

Results: In veterans with baseline CPOU, postsurgical CPOU declined over time for each surgical procedure; these trends did not differ between surgical patients and nonsurgical controls. In veterans without baseline CPOU, compared with nonsurgical controls, bariatric patients had higher CPOU incidence within 5 years after open Roux-en-Y gastric bypass (hazard ratio = 1.19; 95% confidence interval: 1.06-1.34) or laparoscopic open Roux-en-Y gastric bypass (hazard ratio = 1.22, 95% confidence interval: 1.06-1.41). Veterans undergoing laparoscopic sleeve gastrectomy had higher CPOU incidence 1 to 5 years after surgery (hazard ratio = 1.28; 95% confidence interval: 1.05-1.56) than nonsurgical controls.

Conclusions: Bariatric surgery was associated with greater risk of CPOU incidence in patients without baseline CPOU but was not associated with greater CPOU persistence.
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http://dx.doi.org/10.1016/j.soard.2020.04.037DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7423624PMC
August 2020

Trends in Regional Supply of Peritoneal Dialysis in an Era of Health Reform, 2006 to 2013.

Med Care Res Rev 2021 Jun 6;78(3):281-290. Epub 2020 Mar 6.

Duke University, Durham, NC, USA.

Peritoneal dialysis (PD), a home-based treatment for kidney failure, is associated with similar mortality, higher quality of life, and lower costs compared with hemodialysis. Yet <10% of patients receive PD. Access to this alternative treatment, vis-à-vis providers' supply of PD services, may be an important factor but has been sparsely studied in the current era of national payment reform for dialysis care. We describe temporal and regional variation in PD supply among Medicare-certified dialysis facilities from 2006 to 2013. The average proportion of facilities offering PD per hospital referral region increased from 40% (2006) to 43% (2013). PD supply was highest in hospital referral regions with higher percentage of facilities in urban areas ( = .004), prevalence of PD use ( < .0001), percentage of White end-stage renal disease patients ( = .02), and per capita income ( = .02). Disparities in PD access persist in rural, non-White, and low-income regions. Policy efforts to further increase regional PD supply should focus on these underserved communities.
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http://dx.doi.org/10.1177/1077558720910633DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483785PMC
June 2021

Risk Factors and Outcomes of Opioid Users with and Without Concurrent Benzodiazepine Use in the North Carolina Medicaid Population.

J Manag Care Spec Pharm 2020 Feb;26(2):169-175

Department of Population Health Sciences, Duke University, Durham, North Carolina.

Background: Concurrent use of opioids and benzodiazepines is associated with increased risk of opioid overdose and death. Clinical guidelines recommend against this practice and quality measures incentivize plans to minimize concurrent use.

Objective: To compare comorbidities, risky opioid-related behaviors such as high daily doses or multiple prescribers or pharmacies, and outcomes of users of opioids with and without benzodiazepine in the 2017-2018 North Carolina Medicaid population.

Methods: This was a retrospective claims analysis that used 2017-2018 North Carolina Medicaid enrollment and administrative claims data to describe 3 populations: (1) opioid users who concurrently used benzodiazepine for at least 30 days, (2) opioid users who used some benzodiazepine for 0 to less than 30 overlapping days, and (3) opioid users who did not use benzodiazepines.

Results: From 2017 to 2018, 6% of opioid users concurrently used opioids and benzodiazepines for at least 30 days, and 14% used some benzodiazepine for less than 30 overlapping days. Persons filling prescriptions for opioids and benzodiazepines were more likely to have mood disorders and more likely to have depression than opioid users who did not use benzodiazepines. Compared with those not using benzodiazepines, opioid users using benzodiazepine were also more likely to have higher daily opioid doses (at least 90 morphine milligram equivalents), at least 3 prescribers, and at least 3 pharmacies for opioid prescriptions. Although enrollees with at least 30 days of overlapping benzodiazepines and opioids had a higher percentage diagnosed with opioid use disorder compared with those with less than 30 days (30% vs. 13%), a similar percentage received medication-assisted treatment continuously for 90 days (2.6% vs. 2.7%) during 2017-2018. Users of opioids and benzodiazepines, whether for at least 30 overlapping days or less, had higher 1-year cumulative incidences of all-cause outpatient emergency department visits (64% and 65% vs. 52%) and all-cause hospitalizations (25% and 21% vs. 14%) compared with opioid users without benzodiazepine use.

Conclusions: Despite guidelines and quality measures, patients continue to use opioids and benzodiazepines concurrently. Addressing underlying mood disorders and depression, curbing risky opioid-related behaviors, and increasing access to medication-assisted treatment may benefit this population.

Disclosures: This project was supported by Arnold Ventures (formerly Arnold Foundation). Hung reports personal fees from CVS Health and Blue Cross Blue Shield Association, unrelated to this work. Maciejewski reports Amgen stock ownership due to spouse employment, unrelated to this work. McKethan reports personal fees from North Carolina Department of Health and Human Services. All other authors have nothing to disclose. Part of this content was presented as a poster at AMCP Nexus 2019; October 29-November 1, 2019; National Harbor, MD.
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http://dx.doi.org/10.18553/jmcp.2020.26.2.169DOI Listing
February 2020

Short-Term VA Health Care Expenditures Following a Health Risk Assessment and Coaching Trial.

J Gen Intern Med 2020 05 2;35(5):1452-1457. Epub 2020 Jan 2.

Durham Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), , Durham Veterans Affairs Health Care System, Durham, NC, USA.

Background: Short-term health care costs following completion of health risk assessments and coaching programs in the VA have not been assessed.

Objective: To compare VA health care expenditures among veterans who participated in a behavioral intervention trial that randomized patients to complete a HRA followed by health coaching (HRA + coaching) or to complete the HRA without coaching (HRA-alone).

Design: Four-hundred seventeen veterans at three Veterans Affairs (VA) Medical Centers or Clinics were randomized to HRA + coaching or HRA-alone. Veterans randomized to HRA-alone (n = 209) were encouraged to discuss HRA results with their primary care team, while veterans randomized to HRA + coaching (n = 208) received two brief telephone-delivered health coaching calls.

Participants: We included 411 veterans with available cost data.

Main Measures: Total VA health expenditures 6 months following trial enrollment were estimated using a generalized linear model with a gamma distribution and log link function. In exploratory analysis, model-based recursive partitioning was used to determine whether the intervention effect on short-term costs differed among any patient subgroups.

Key Results: Most participants were male (85%); mean age was 56, and mean body mass index was 34. From the generalized linear model, 6-month estimated mean total VA expenditures were similar ($8665 for HRA + coaching vs $9900 for HRA-alone, p = 0.25). In exploratory subgroup analysis, among unemployed veterans with good sleep and fair or poor perceived health, mean observed expenditures in the HRA + coaching group were higher than in the HRA-alone group ($12,814 vs $7971). Among unemployed veterans with good sleep and good general health, mean observed expenditures in the HRA + coaching group were lower than in the HRA-alone group ($5082 vs $11,612).

Conclusions: Compared to completing and receiving HRA results, working with health coaches to set actionable health behavior change goals following HRA completion did not reduce short-term health expenditures.

Trial Registration: Clinicaltrials.gov identifier: NCT01828567.
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http://dx.doi.org/10.1007/s11606-019-05455-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7210324PMC
May 2020

Trends in Peritoneal Dialysis Use in the United States after Medicare Payment Reform.

Clin J Am Soc Nephrol 2019 12 21;14(12):1763-1772. Epub 2019 Nov 21.

Departments of Medicine,

Background And Objectives: Peritoneal dialysis (PD) for ESKD is associated with similar mortality, higher quality of life, and lower costs compared with hemodialysis (HD), but has historically been underused. We assessed the effect of the 2011 Medicare prospective payment system (PPS) for dialysis on PD initiation, modality switches, and stable PD use.

Design, Setting, Participants, & Measurements: Using US Renal Data System and Medicare data, we identified all United States patients with ESKD initiating dialysis before (2006-2010) and after (2011-2013) PPS implementation, and observed their modality for up to 2 years after dialysis initiation. Using logistic regression models, we examined the associations between PPS and early PD experience (any PD 1-90 days after initiation), late PD use (any PD 91-730 days after initiation), and modality switches (PD-to-HD or HD-to-PD 91-730 days after initiation). We adjusted for patient, dialysis facility, and regional characteristics.

Results: Overall, 619,126 patients with incident ESKD received dialysis at Medicare-certified facilities, 2006-2013. Observed early PD experience increased from 9.4% before PPS to 12.6% after PPS. Observed late PD use increased from 12.1% to 16.1%. In adjusted analyses, PPS was associated with increased early PD experience (odds ratio [OR], 1.51; 95% confidence interval [95% CI], 1.47 to 1.55; <0.001) and late PD use (OR, 1.47; 95% CI, 1.45 to 1.50; <0.001). In subgroup analyses, late PD use increased in part due to an increase in HD-to-PD switches among those without early PD experience (OR, 1.59; 95% CI, 1.52 to 1.66; <0.001) and a decrease in PD-to-HD switches among those with early PD experience (OR, 0.92; 95% CI, 0.87 to 0.98; =0.004).

Conclusions: More patients started, stayed on, and switched to PD after dialysis payment reform. This occurred without a substantial increase in transfers to HD.
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http://dx.doi.org/10.2215/CJN.05910519DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895485PMC
December 2019

How comfortable are primary care physicians and oncologists prescribing medications for comorbidities in patients with cancer?

Res Social Adm Pharm 2020 08 9;16(8):1087-1094. Epub 2019 Nov 9.

Auburn University Harrison School of Pharmacy, Department of Health Outcomes Research and Policy, 4306 Walker Building, Auburn University, AL, 36849, USA.

Background: Treating cancer and existing chronic comorbidities requires a dynamic mix of primary care and specialist providers. However, little is known regarding primary care physicians' (PCPs) and oncologists' comfort level prescribing for comorbid conditions.

Objectives: The objectives of this study were to describe oncologists' and PCPs': 1) comfort-level prescribing, 2) perceptions of providers' role in prescribing cardiometabolic and psychiatric medications in persons with cancer and comorbidity, and 3) provider factors associated with comfort-levels.

Methods: This cross-sectional online survey examined responses from practicing U.S. PCPs and oncologists. A 33-question survey was used to assess PCPs' and oncologists' comfort-levels for prescribing 6 classes of medications used to treat common comorbid cardiometabolic or psychiatric conditions. Using t-tests, chi-square tests, or Fisher's Exact tests, physicians' own comfort and comfort with other physicians prescribing medications for shared patients were compared between PCPs and oncologists. Linear regression models were used to analyze predictors of comfort-level scale score for prescribing medications.

Results: Oncologists were more comfortable with PCPs initiating or refilling antidiabetics, antihyperlipidemics, antidepressants, and antipsychotics, and PCPs were more comfortable initiating antihypertensives, antidiabetics, antihyperlipidemics, antidepressants, and antipsychotics themselves as opposed to having an oncologist initiate or refill these medications. Compared to oncologists, PCPs reported a 32.3% higher comfort-level for initiating cardiometabolic medications (Adjusted Coefficient (standard error) = 0.323 (0.033), p < 0.001), and a 25.0% higher comfort-level for initiating psychiatric medications in cancer patients (Adjusted Coefficient (standard error) = 0.250 (0.030), p < 0.001), after controlling for prescriber demographics and practice site characteristics.

Conclusions: Findings suggest that when a cancer diagnosis is made for patients with pre-existing cardiometabolic or psychiatric conditions, oncologists prefer PCPs to manage these medications. This enhanced understanding of PCPs' and oncologists' comfort managing these medications may help develop a standard for defining physician roles in medication therapy as part of a shared care plan for patients with cancer and comorbidities.
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http://dx.doi.org/10.1016/j.sapharm.2019.11.006DOI Listing
August 2020

Comparison of Group Medical Visits Combined With Intensive Weight Management vs Group Medical Visits Alone for Glycemia in Patients With Type 2 Diabetes: A Noninferiority Randomized Clinical Trial.

JAMA Intern Med 2020 Jan;180(1):70-79

Center of Innovation to Accelerate Discovery and Practice Transformation, Department of Veterans Affairs, Durham, North Carolina.

Importance: Traditionally, group medical visits (GMVs) for persons with diabetes improved glycemia by intensifying medications, which infrequently led to weight loss. Incorporating GMVs with intensive dietary change could enable weight loss and improve glycemia while decreasing medication intensity.

Objective: To examine whether a program of GMVs combined with intensive weight management (WM) is noninferior to GMVs alone for change in glycated hemoglobin (HbA1c) level at 48 weeks (prespecified margin of 0.5%) and superior to GMVs alone for hypoglycemic events, diabetes medication intensity, and weight loss.

Design, Setting, And Participants: This randomized clinical trial identified via the electronic medical record 2814 outpatients with type 2 diabetes, uncontrolled HbA1c, and body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 27 or higher from Veterans Affairs Medical Center clinics in Durham and Greenville, North Carolina. Between January 12, 2015, and May 30, 2017, 263 outpatients started the intervention.

Interventions: Participants randomized to the GMV group (n = 136) received counseling about diabetes-related topics with medication optimization every 4 weeks for 16 weeks, then every 8 weeks (9 visits). Participants randomized to the WM/GMV group (n = 127) received low-carbohydrate diet counseling with baseline medication reduction and subsequent medication optimization every 2 weeks for 16 weeks followed by an abbreviated GMV intervention every 8 weeks (13 visits).

Main Outcomes And Measures: Outcomes included HbA1c level, hypoglycemic events, diabetes medication effect score, and weight at 48 weeks analyzed using hierarchical generalized mixed models to account for clustering within group sessions.

Results: Among 263 participants (mean [SD] age, 60.7 [8.2] years; 235 [89.4%] men; 143 [54.4%] black), baseline HbA1c level was 9.1% (1.3%) and BMI was 35.3 (5.1). At 48 weeks, HbA1c level was improved in both study arms (8.2% in the WM/GMV arm and 8.3% in the GMV arm; mean difference, -0.1%; 95% CI, -0.5% to 0.2%; upper 95% CI, <0.5% threshold; P = .44). The WM/GMV arm had lower diabetes medication use (mean difference in medication effect score, -0.5; 95% CI, -0.6 to -0.3; P < .001) and greater weight loss (mean difference, -3.7 kg; 95% CI, -5.5 to -1.9 kg; P < .001) than did the GMV arm at 48 weeks and approximately 50% fewer hypoglycemic events (incidence rate ratio, 0.49; 95% CI, 0.27 to 0.71; P < .001) during the 48-week period.

Conclusions And Relevance: In GMVs for diabetes, addition of WM using a low-carbohydrate diet was noninferior for lowering HbA1c levels compared with conventional medication management and showed advantages in other clinically important outcomes.

Trial Registration: ClinicalTrials.gov identifier: NCT01973972.
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http://dx.doi.org/10.1001/jamainternmed.2019.4802DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6830502PMC
January 2020

Association Between Bariatric Surgery and Long-term Health Care Expenditures Among Veterans With Severe Obesity.

JAMA Surg 2019 12 18;154(12):e193732. Epub 2019 Dec 18.

Center of Innovation to Accelerate Discovery and Practice Transformation, Durham VA Medical Center, Durham, North Carolina.

Importance: Bariatric surgery has been associated with improvements in health in patients with severe obesity; however, it is unclear whether these health benefits translate into lower health care expenditures.

Objective: To examine 10-year health care expenditures in a large, multisite retrospective cohort study of veterans with severe obesity who did and did not undergo bariatric surgery.

Design, Setting, And Participants: A total of 9954 veterans with severe obesity between January 1, 2000, and September 30, 2011, were identified from veterans affairs (VA) electronic health records. Of those, 2498 veterans who underwent bariatric surgery were allocated to the surgery cohort. Sequential stratification was used to match each patient in the surgery cohort with up to 3 patients who had not undergone bariatric surgery but were of the same sex, race/ethnicity, diabetes status, and VA regional network and were closest in age, body mass index (calculated as weight in kilograms divided by height in meters squared), and comorbidities. A total of 7456 patients were identified and allocated to the nonsurgery (control) cohort. The VA health care expenditures among the surgery and nonsurgery cohorts were estimated using regression models. Data were analyzed from July to August 2018 and in April 2019.

Interventions: The bariatric surgical procedures (n = 2498) included in this study were Roux-en-Y gastric bypass (1842 [73.7%]), sleeve gastrectomy (381 [15.3%]), adjustable gastric banding (249 [10.0%]), and other procedures (26 [1.0%]).

Main Outcomes And Measures: The study measured total, outpatient, inpatient, and outpatient pharmacy expenditures from 3 years before surgery to 10 years after surgery, excluding expenditures associated with the initial bariatric surgical procedure.

Results: Among 9954 veterans with severe obesity, 7387 (74.2%) were men; the mean (SD) age was 52.3 (8.8) years for the surgery cohort and 52.5 (8.7) years for the nonsurgery cohort. Mean total expenditures for the surgery cohort were $5093 (95% CI, $4811-$5391) at 7 to 12 months before surgery, which increased to $7448 (95% CI, $6989-$7936) at 6 months after surgery. Postsurgical expenditures decreased to $6692 (95% CI, $6197-$7226) at 5 years after surgery, followed by a gradual increase to $8495 (95% CI, $7609-$9484) at 10 years after surgery. Total expenditures were higher in the surgery cohort than in the nonsurgery cohort during the 3 years before surgery and in the first 2 years after surgery. The expenditures of the 2 cohorts converged 5 to 10 years after surgery. Outpatient pharmacy expenditures were significantly lower among the surgery cohort in all years of follow-up ($509 lower at 3 years before surgery and $461 lower at 7 to 12 months before surgery), but these cost reductions were offset by higher inpatient and outpatient (nonpharmacy) expenditures.

Conclusions And Relevance: In this cohort study of 9954 predominantly older male veterans with severe obesity, total health care expenditures increased immediately after patients underwent bariatric surgery but converged with those of patients who had not undergone surgery at 10 years after surgery. This finding suggests that the value of bariatric surgery lies primarily in its associations with improvements in health and not in its potential to decrease health care costs.
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http://dx.doi.org/10.1001/jamasurg.2019.3732DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822094PMC
December 2019

Clinical associations of an updated medication effect score for measuring diabetes treatment intensity.

Chronic Illn 2019 Oct 25:1742395319884096. Epub 2019 Oct 25.

Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham VA Medical Center, Durham, NC, USA.

Objectives: The medication effect score reflects overall intensity of a diabetes regimen by consolidating dosage and potency of agents used. Little is understood regarding how medication intensity relates to clinical factors. We updated the medication effect score to account for newer agents and explored associations between medication effect score and patient-level clinical factors.

Methods: Cross-sectional analysis of baseline data from a randomized controlled trial involving 263 Veterans with type 2 diabetes and hemoglobin A1c levels ≥8.0% (≥7.5% if under age 50). Medication effect score was calculated for all patients at baseline, alongside additional measures including demographics, comorbid illnesses, hemoglobin A1c, and self-reported psychosocial factors. We used multivariable regression to explore associations between baseline medication effect score and patient-level clinical factors.

Results: Our sample had a mean age of 60.7 ( = 8.2) years, was 89.4% male, and 57.4% non-White. Older age and younger onset of diabetes were associated with a higher medication effect score, as was higher body mass index. Higher medication effect score was significantly associated with medication nonadherence, although not with hemoglobin A1c, self-reported hypoglycemia, diabetes-related distress, or depression.

Discussion: We observed several expected associations between an updated medication effect score and patient-level clinical factors. These associations support the medication effect score as an appropriate measure of diabetes regimen intensity in clinical and research contexts.
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http://dx.doi.org/10.1177/1742395319884096DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7182482PMC
October 2019
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