Can the LACE index help identify uninsured patients at risk of loss to follow-up during a pharmacist-led transitions of care program?

BACKGROUND: Uninsured patients are susceptible to being lost to follow-up (LTFU). In addition to being uninsured, follow-up is especially critical among this population during transitions of care when patients are discharged from the hospital setting back to home because follow-up care after discharge has been proven to prevent readmissions. The LACE tool has historically been used to predict readmissions, but the LACE tool has not been used to evaluate patients' risk of LTFU. OBJECTIVE: To understand the potential translation of the LACE tool for use in uninsured patients' follow-up care, we assessed the association between LACE index scores and patients' risk of LTFU during a pharmacist-led transitions of care program for uninsured patients. METHODS: Data were extracted from a randomized controlled trial implementing a pharmacist-led transitions of care program at an indigent care clinic. The study population included uninsured adult patients (>18 years old) who spoke English and attended a clinical visit with a pharmacist within 16 days after discharge from a community hospital. Analyses sought to determine factors associated with the patients' LTFU status. RESULTS: Among 88 enrolled participants, 29 participants (32.95%) were LTFU. Thirty-two patients (36.4%) had a high LACE index score at baseline, indicating an increased risk of 30-day readmission. Of the remaining 56 patients (63.6%) with low-to-moderate LACE index scores, 54 (61.4%) had a moderate LACE index score, and only 2 (2.3%) had a low LACE index score. Uninsured patients with high LACE index scores had 70% lower odds of being LTFU than uninsured patients with low-to-moderate LACE index scores (exact odds ratio 0.297 [95% CI 0.081-0.947]). CONCLUSION: The LACE index score was inversely related to the risk of LTFU during a pharmacist-led transitions of care program. Pharmacists may use the LACE tool to identify patients at high risk of LTFU.

Implementation of a pharmacist-led transitions of care program in an indigent care clinic: A randomized controlled trial.

OBJECTIVES: Pharmacists' involvement in the transitions of care has shown the potential to decrease readmissions and increase access to care in many populations; however, the uninsured patient populations have not been studied. The evidence for the feasibility of implementing transitions of care services in indigent care clinics with limited resources also remains limited. The objectives were to implement a pharmacist-led transitions of care program in an indigent care clinic, to demonstrate the feasibility of its implementation, and to evaluate its impact on readmissions and emergency department (ED) visit rates among an uninsured population. METHODS: The study was a single-blind, parallel, randomized controlled trial implemented in an indigent care clinic in the Southeast region of the United States from October 2018 to July 2019. Eligible patients were those older than 18 years, uninsured, English-speaking, diagnosed with any condition, and recently discharged from a local community hospital within the past 16 days. The primary outcome was the hospital readmission rate at 30 days after discharge. The secondary outcomes included 60- and 90-day readmission rates in addition to 30-, 60-, and 90-day ED visit rates. RESULTS: A total of 88 participants were recruited. The intervention was successfully implemented in the clinic, but patient-level barriers to follow-ups included transportation, accessibility, financial burdens, inconsistent telephone communication, and a lack of knowledge about the importance of follow-ups. At 30 days postdischarge, 13.64% of the patients in the usual care group experienced readmissions compared with 9.30% of the patients in the intervention group. The relative change in the 30-day readmission rates between the usual care and the intervention groups was 1.7 (rate ratio [RR] 1.69 [95% CI 0.47-6.08]). The RRs were insignificant for the 30-, 60-, and 90-day readmission and ED visit rates. CONCLUSION: This study demonstrated the feasibility of implementing transitions of care services in a clinic with limited resources by pharmacists. The intervention showed promising results by reducing readmission rates.

An Examination of Prescribing Responsibilities between Psychiatrists and Primary Care Providers.

Patients with comorbid mental health and chronic conditions often receive care from both psychiatrists and primary care physicians (PCPs). The introduction of multiple providers into the care process introduces opportunities for disruptions in care continuity. The purpose of this study was to explore psychiatrists' and PCPs' comfort prescribing, along with their comfort having other physician specialties prescribe medications for cardiometabolic, psychiatric, and neurological/behavioral conditions. This cross-sectional study utilized an online, validated, pilot-tested, anonymous survey to examine prescribing practices of psychiatrists and PCPs. Eligible participants included physicians with medical degrees, U.S. prescribing authority, and active patient care for ≥2 days/week. Outcomes of interest were physicians' self-comfort and cross-specialty comfort (other specialists prescribing mutual patients' medications) prescribing cardiometabolic, psychiatric, and neurological/behavioral medications. Comfort prescribing was measured using 7-point Likert scales. Discrepancies in comfort were analyzed using student's, one-sample, and paired t-tests. Multiple linear regressions examined associations between physician practice characteristics and physicians' comfort-level prescribing cardiometabolic and psychiatric medication categories. Among 50 psychiatrists and 50 PCPs, psychiatrists reported significantly lower self-comfort prescribing cardiometabolic medications (mean ± SD = 2.99 ± 1.63 vs. 6.77 ± 0.39, p < 0.001), but significantly higher self-comfort prescribing psychiatric medications (mean ± SD = 6.79 ± 0.41 vs. 6.00 ± 0.88, p < 0.001) and neurological/behavioral medications (mean ± SD = 6.48 ± 0.74 vs. 5.56 ± 1.68, p < 0.001) than PCPs. After adjusting for covariates, physician specialty was strongly associated with self-comfort prescribing cardiometabolic and psychiatric medication categories (both p < 0.001). Differences between self-comfort and cross-specialty comfort were identified. Because comfort prescribing medications differed by physician type, incorporating psychiatrists through collaborative methods with PCPs could potentially ensure comfort among physicians when initiating medications.

Diabetes-related complications, glycemic levels, and healthcare utilization outcomes after therapeutic inertia in type 2 diabetes mellitus.

AIMS: To assess diabetes-related complications, glycemic levels, and healthcare utilization 12 months after exposure to therapeutic inertia among patients with type 2 diabetes mellitus (T2D). METHODS: This retrospective cohort study analyzed data from the OneFlorida Clinical Research Consortium (electronic health records from Florida practices/clinics). The cohort included adult patients (≥18 years old) with T2D who had an HbA1c≥7.0% (53 mmol/mol) recorded from January 1, 2014-September 30, 2019. Therapeutic inertia (exposed vs. not exposed) was evaluated during the six months following HbA1c≥7.0% (53 mmol/mol). The outcomes assessed during the 12-month follow-up period included diabetes-related complications (continuous Diabetes Complications and Severity Index (DCSI)), glycemic levels (continuous follow-up HbA1c lab), and healthcare utilization counts. We analyzed data using multivariable regression models, adjusting for covariates. RESULTS: The cohort included 26,881 patients with T2D (58.94% White race, 49.72% female, and mean age of 58.82 (SD=13.09)). After adjusting for covariates, therapeutic inertia exposure was associated with lower DCSI (estimate=-0.14 (SE=0.03), p < 0.001), higher follow-up HbA1c (estimate=0.14 (SE=0.04), p < 0.001), and lower rates of ambulatory visits (rate ratio=0.79, 95% CI=0.75-0.82). CONCLUSIONS: Findings communicate the clinical practice implications and public health implications for combating therapeutic inertia in diabetes care.

HIV testing and risk behaviors associated with depression in the United States.

Given the high correlation between depression and HIV infection rates, our objective was to assess national rates for HIV testing and HIV risk behaviors among U.S. adults stratified by self-reports of depression. We conducted a cross-sectional study using data from the 2018-2020 Behavioral Risk Factor Surveillance System (BRFSS). We included respondents aged 18 years old and above with self-reported depression status (Sample size = 1,228,405). The primary outcomes included HIV testing and HIV-related risk behaviors. For respondents with prior HIV testing experience, we estimated the duration since the last HIV test. We applied a multivariable logistic regression model to analyze the correlation between depression and HIV testing or risk behaviors. The results showed people with depression had 51% higher odds of receiving HIV testing [adjusted odds ratio (AOR) = 1.51, 95% CI = 1.48, 1.55] and 51% higher odds of involvement in HIV risk behaviors [AOR = 1.51, 95% CI = 1.44, 1.58] after adjusting for covariates. Various socio-demographics and healthcare access variables were significantly associated with HIV testing and HIV risk behaviors. When comparing the average time from the last HIV test, people with depression had a shorter period compared to those without depression [Median time in months: 27.1 ± 0.45 vs. 29.3 ± 0.34]. Even though people with depression had higher rates of HIV testing, they still experienced long time periods (median = 2 + years) between HIV testing, which exceeded the recommended annual HIV testing for people at high risk from the Centers for Disease Control and Prevention.

Associations Between Medicaid Expansion and Mental Health Among U.S. Racial and Ethnic Groups.

OBJECTIVE: The authors examined associations between Medicaid expansion and self-reported mental health by race-ethnicity, focusing on lagged associations. METHODS: This retrospective, cross-sectional study used 2011-2019 data from the Behavioral Risk Factor Surveillance System. The sample included low-income, childless adults ages 25-64 years. Difference-in-differences (DID) analysis was used to estimate associations between Medicaid expansion and self-reported mental health. Lagged associations were examined by separating the postexpansion period into proximal (2014-2016) and distal (2017-2019) periods. RESULTS: In the overall sample (N=327,248), Medicaid expansion was associated with a reduction in the mean number of self-reported past-month poor mental health days (DID=-0.12, 95% CI=-0.21 to -0.03), after adjustment for covariates. The expansion was associated with significant reductions in past-month poor mental health days for the following groups: non-Hispanic White (DID=-0.18, 95% CI=-0.29 to -0.07), non-Hispanic Asian (DID=-1.15, 95% CI=-1.37 to -0.93), non-Hispanic other (DID=-0.62, 95% CI=-1.03 to -0.21), and Hispanic (DID=-0.48, 95% CI=-0.73 to -0.23). The non-Hispanic Black group had a significant increase in past-month poor mental health days (DID=0.27, 95% CI=0.06 to 0.49), and no significant change was noted for the American Indian or Alaska Native (AIAN) group. Improvements in mental health observed at the beginning of the policy implementation (proximal period) were not sustained over time for some racial-ethnic minority groups. CONCLUSIONS: Although Medicaid expansion improved mental health for the overall sample, some racial-ethnic disparities were detected. The negative and insignificant associations for the non-Hispanic Black and AIAN groups, respectively, highlight the need to better understand why the Medicaid expansion affected racial-ethnic groups differently.

Reproducibility of the medical cost estimation from the Medicare Current Beneficiary Survey: Comparing claims and survey.

Background: The Medicare Current Beneficiary Survey (MCBS) limited-access data provides the unique opportunity to utilize administrative claims and adjusted survey data to investigate trends in utilization and medical expenditure across time. The adjusted survey data is a synthesized, matched version of the original survey data and claims. Researchers may choose adjusted survey data or original claims for cost evaluations according to their research purpose. However, limited research has examined methodological issues when estimating medical cost using different MCBS data sources. Objective: The study objective was to examine the reproducibility of individual-level medical cost using both MCBS data sources: adjusted survey and claims data. Methods: This serial cross-sectional study design analyzed 2006-2012 MCBS data. The sample included noninstitutionalized older Medicare beneficiaries (≥65 years old), with a cancer diagnosis and annually enrolled in Medicare Parts A, B, and D. The population was stratified by diabetes diagnosis. The primary outcome was annual medical cost. We investigated the discrepancies of medical cost estimated from the adjusted survey and original claims data. The agreement between cost estimates from the two sources in each year was determined using the Wilcoxon signed-rank test. Results: A total of 4918 eligible Medicare beneficiaries were included in this study, and 26% of beneficiaries also had diabetes (N = 1275). Significant disagreements in cost estimates between adjusted survey and claims data were present regardless of disease complexity (with or without diabetes). Significant disagreements in medical cost estimates were present in most years, except in 2010 (p = 0.467) and 2011 (p = 0.098), for beneficiaries with cancer and diabetes (p < 0.001 for all). Significant disagreements in medical cost estimates were present in all years for beneficiaries with cancer without diabetes (p < 0.001 for all). Conclusions: Based on discrepant cost estimates across data sources, researchers using MCBS to estimate costs should be cautious when using claims or adjusted survey data alone.

Medication use and contextual factors associated with meeting guideline-based glycemic levels in diabetes among a nationally representative sample.

Introduction: Based on the long-lasting diabetes management challenges in the United States, the objective was to examine glycemic levels among a nationally representative sample of people with diabetes stratified by prescribed antihyperglycemic treatment regimens and contextual factors. Methods: This serial cross-sectional study used United States population-based data from the 2015 to March 2020 National Health and Nutrition Examination Surveys (NHANES). The study included non-pregnant adults (≥20 years old) with non-missing A1C and self-reported diabetes diagnosis from NHANES. Using A1C lab values, we dichotomized the outcome of glycemic levels into <7% versus ≥7% (meeting vs. not meeting guideline-based glycemic levels, respectively). We stratified the outcome by antihyperglycemic medication use and contextual factors (e.g., race/ethnicity, gender, chronic conditions, diet, healthcare utilization, insurance, etc.) and performed multivariable logistic regression analyses. Results: The 2042 adults with diabetes had a mean age of 60.63 (SE = 0.50), 55.26% (95% CI = 51.39-59.09) were male, and 51.82% (95% CI = 47.11-56.51) met guideline-based glycemic levels. Contextual factors associated with meeting guideline-based glycemic levels included reporting an "excellent" versus "poor" diet (aOR = 4.21, 95% CI = 1.92-9.25) and having no family history of diabetes (aOR = 1.43, 95% CI = 1.03-1.98). Contextual factors associated with lower odds of meeting guideline-based glycemic levels included taking insulin (aOR = 0.16, 95% CI = 0.10-0.26), taking metformin (aOR = 0.66, 95% CI = 0.46-0.96), less frequent healthcare utilization [e.g., none vs. ≥4 times/year (aOR = 0.51, 95% CI = 0.27-0.96)], being uninsured (aOR = 0.51, 95% CI = 0.33-0.79), etc. Discussion: Meeting guideline-based glycemic levels was associated with medication use (taking vs. not taking respective antihyperglycemic medication classes) and contextual factors. The timely, population-based estimates can inform national efforts to optimize diabetes management.

Clinical risk factors and social needs of 30-day readmission among patients with diabetes: A retrospective study of the Deep South.

Introduction: Evidence is needed for 30-day readmission risk factors (clinical factors and social needs) among patients with diabetes in the Deep South. To address this need, our objectives were to identify risk factors associated with 30-day readmissions among this population and determine the added predictive value of considering social needs. Methods: This retrospective cohort study utilized electronic health records from an urban health system in the Southeastern U.S. The unit of analysis was index hospitalization with a 30-day washout period. The index hospitalizations were preceded by a 6-month pre-index period to capture risk factors (including social needs), and hospitalizations were followed 30 days post-discharge to evaluate all-cause readmissions (1=readmission; 0=no readmission). We performed unadjusted (chi-square and student's t-test, where applicable) and adjusted analyses (multiple logistic regression) to predict 30-day readmissions. Results: A total of 26,332 adults were retained in the study population. Eligible patients contributed a total of 42,126 index hospitalizations, and the readmission rate was 15.21%. Risk factors associated with 30-day readmissions included demographics (e.g., age, race/ethnicity, insurance), characteristics of hospitalizations (e.g., admission type, discharge status, length of stay), labs and vitals (e.g., highest and lowest blood glucose measurements, systolic and diastolic blood pressure), co-existing chronic conditions, and preadmission antihyperglycemic medication use. In univariate analyses of social needs, activities of daily living (p<0.001), alcohol use (p<0.001), substance use (p=0.002), smoking/tobacco use (p<0.001), employment status (p<0.001), housing stability (p<0.001), and social support (p=0.043) were significantly associated with readmission status. In the sensitivity analysis, former alcohol use was significantly associated with higher odds of readmission compared to no alcohol use [aOR (95% CI): 1.121 (1.008-1.247)]. Conclusions: Clinical assessment of readmission risk in the Deep South should consider patients' demographics, characteristics of hospitalizations, labs, vitals, co-existing chronic conditions, preadmission antihyperglycemic medication use, and social need (i.e., former alcohol use). Factors associated with readmission risk can help pharmacists and other healthcare providers identify high-risk patient groups for all-cause 30-day readmissions during transitions of care. Further research is needed about the influence of social needs on readmissions among populations with diabetes to understand the potential clinical utility of incorporating social needs into clinical services.

Telehealth delivery of motivational interviewing for diabetes management: A systematic review of randomized controlled trials.

OBJECTIVES: The objective of this systematic review was to explore and report the evidence and gaps in the literature for randomized controlled trials (RCTs) studying the effects of motivational interviewing (MI)-based telehealth interventions on outcomes among persons with diabetes (PWD) or prediabetes. METHODS: Following a modified Cochrane approach, we searched Pubmed, CENTRAL, CINAHL, PsycINFO, and Clinicaltrials.gov. Included studies were RCTs published in English before March 25, 2021 evaluating MI-based telehealth on outcomes for adults with diabetes or prediabetes. RESULTS: A total of 21 retained articles captured results for 6436 PWD. Among the most commonly investigated outcomes, 60% of articles documented A1C reductions (ranging from<1% to>3%), 56% documented systolic blood pressure reductions, 57% documented diabetes self-efficacy/empowerment improvements, and 40% documented physical activity improvements. Conversely, diastolic blood pressure, lipid panels, body mass index, depressive symptoms, and quality of life were frequently measured outcomes, where MI-based telehealth yielded minor effects (<30% of articles demonstrating improvements). CONCLUSIONS: MI-based telehealth seems most effective for improving A1C, systolic blood pressure, diabetes self-efficacy, and physical activity behaviors. Variability in outcome assessment and intervention heterogeneity were key challenges impeding comparisons across retained articles. PRACTICE IMPLICATIONS: MI-based telehealth interventions demonstrate promising results for improving outcomes in PWD.

Diabetes management behaviors associated with depression in the U.S.

BACKGROUND: There is a lack of nationally representative evidence from the U.S. investigating the relationships between depression and diabetes management behaviors. Our study aimed to assess the associations between diabetes management behaviors and depression status, and to compare U.S. population-level percentages of diabetes management behaviors among patients with and without depression. METHODS: A cross-sectional study was conducted using population-based survey data to assess patient-reported variables retrospectively. We used the Behavioral Risk Factor Surveillance System (BRFSS) data and included states in the U.S. that continuously adopted the diabetes optional modules in 2013, 2015, 2017, and 2019. We included U.S. adults (≥ 18 years old) with self-reported diabetes in our analysis. Main outcomes were diabetes management behaviors (i.e., self-check for blood glucose and feet sores/irritation, regular diabetes clinical visit, HbA1c check, professional feet check, and dilated eye examination) and lifestyle behaviors (i.e., exercise, smoking, and alcohol consumption). RESULTS: Among the 74,011 respondents with diabetes, patients with depression had a higher likelihood of performing routine HbA1c checks (adjusted odds ratio (AOR) = 1.12; 95% CI 1.01-1.23) but had a lower likelihood to perform regular self-check for blood glucose (AOR = 0.91; 95% CI 0.84-0.99), receive professional feet checks (AOR = 0.87; 95% CI 0.79-0.95), and receive a dilated eye examination (AOR = 0.89; 95% CI 0.82-0.98). For lifestyle behaviors, patients with depression were more likely to smoke (No smoking (AOR) = 0.65; 95% CI = 0.59-0.72) and less likely to engage in sufficient exercise time (AOR = 0.69; 95% CI 0.63-0.75). There were no significant associations between depression and other behaviors, including self-check for feet sores/irritation (AOR = 0.99; 95% CI 0.92-1.08), regular diabetes clinical visit (AOR = 1.03, 95% CI 0.94-1.13), and alcohol consumption (AOR = 1.01, 95% CI 0.92-1.10). CONCLUSIONS: The association between depression status and diabetes management behaviors varied. People with depression were positively associated with HbA1c checks. However, less uptake of other behaviors may indicate the needs for improvement in diabetes management.

Mental Health and Psychotropic Stigma Among Student Pharmacists.

Objective: To gain a better understanding of student pharmacists' stigma toward mental health and psychotropic medications. Methods: A cross-sectional study was conducted via paper and online surveys amongst all student pharmacists enrolled in a Doctor of Pharmacy program in the Southeastern United States (n = 501). The Perceived Devaluation and Discrimination (PDD) Scale was used to measure mental health stigma. The Beliefs about Medicines Questionnaire (BMQ) was modified to measure psychotropic stigma. MANOVAs were conducted to investigate relationships between student pharmacists' characteristics with mental health and psychotropic stigma. A paired t-test was used to determine if there was a difference between degree of mental health stigma and psychotropic stigma. Results: A total of 390 participants completed the survey (65%). The sample was mostly female (67%), white (79%), and non-Hispanic (96%). Ages were predominantly within the 19-24-year range (80%), and the majority of respondents reported previous interactions with patients who have mental health conditions (55%) or patients on psychotropic medications (65%). Student personal preferences for mental health treatment were primarily psychologic (42%) or both psychologic and psychotropic (40%). Degree of psychotropic stigma was significantly greater than that of mental health stigma. A statistically significant association was found between student personal preference for treatment and the psychotropic stigma. No difference was found in degree of either type of stigma across cohorts. Conclusions: Student pharmacists demonstrated both mental health and psychotropic stigmas. Future research should be performed to determine what effects these stigmas have on care of patients with mental health conditions.

Impact of Diabetes Self-Management Education/Support on Self-Reported Quality of Life in Youth With Type 1 or Type 2 Diabetes.

PURPOSE: The persistent requirement of self-management for diabetes impacts quality of life (QoL), yet the literature for impact of diabetes self-management education and support (DSMES) on QoL in youth has not been synthesized and reported. The purpose of this review was to systematically identify and describe the state of the science exploring the impact of DSMES on self-reported QoL in youth with type 1 diabetes (T1DM) or type 2 diabetes (T2DM). METHODS: A modified Cochrane review was conducted. Retained studies were published in the English language between January 1, 2007, and March 31, 2020. Included studies specified that the intervention had diabetes education addressing at least 1 or more of The Association of Diabetes Care & Education Specialists' ADCES7 Self-Care BehaviorsTM (ADCES7™) and used an established self-reported QoL measure. Retained studies were assessed for risk of bias. RESULTS: Eleven studies reported in 12 articles were retained. The interventions were primarily delivered to youth with T1DM or T2DM and included caregivers/families in some studies. The ADCES7™ were addressed across the retained studies. Five of the 11 studies assessed QoL as the primary outcome and 6 studies as a secondary outcome. CONCLUSION: To enhance the QoL outcomes and to provide insight into how to positively impact self-perceptions of QoL, ongoing generic and diabetes-specific QoL assessments are warranted for youth with T1DM or T2DM. Further research is needed in structured DSMES programs to help reduce variability in research designs, methods, measures, and outcomes to generate evidence for best practices that can be translated and disseminated into real-world settings.

Primary Care Physicians', Psychiatrists', and Oncologists' Coordination While Prescribing Medications for Patients With Multiple Chronic Conditions.

OBJECTIVES: Coordination of medication prescribing is important in the care of patients with multiple chronic conditions (MCC) given the involvement of multiple providers and multiple medications used to manage MCC. The objective of this study was to identify physician and practice factors associated with physicians' coordination of prescribing for complex patients with MCC. METHODS: Our cross-sectional study used a 33-item anonymous, online survey to assess physicians' coordination practices while prescribing for patients with MCC. We sampled primary care physicians (PCPs), psychiatrists, and oncologists across the United States. Coordination of medication prescribing was measured on a 7-point Likert-type scale. χ2, Fisher exact test, and binomial logistic regression, adjusted for factors and covariates, were used to determine differences in coordination of prescribing. Average marginal effects were calculated for factors. RESULTS: A total of 50 PCPs, 50 psychiatrists, and 50 oncologists participated. Most psychiatrists (56%) and oncologists (52%) reported frequently coordinating prescribing with other physicians, whereas less than half of the PCPs (42%) reported frequently coordinating prescribing. Female physicians were 25% points more likely to report coordinating prescribing than male physicians (P = 0.0186), and physicians not using electronic medical records were 30% points more likely to report coordinating prescribing than physicians using electronic medical records (P = 0.0230). Four additional factors were associated with lower likelihood of coordinating prescribing. CONCLUSIONS: Physician and practice factors may influence differences in coordination of medication prescribing, despite physician specialty. These factors can provide a foundation for developing interventions to improve coordination of prescribing practices for MCC.

The Effects of Diabetes Self-Management Education on Quality of Life for Persons With Type 1 Diabetes: A Systematic Review of Randomized Controlled Trials.

PURPOSE: It is well documented that chronic conditions, such as diabetes, impact quality of life (QoL). QoL assessment is essential when developing and evaluating diabetes self-management education support interventions. The aim of this systematic review was to evaluate the evidence and gaps in the research and the impact of diabetes self-management education (DSME) on QoL outcomes in persons with type 1 diabetes mellitus (T1DM). METHODS: A systematic review of English language studies published between January 1, 2007, and March 31, 2020, was conducted using a modified Cochrane review method. Studies were included if they were randomized controlled trials (RCTs), participants had T1DM with or without caregivers, a DSME intervention alone or a component(s) of the ADCES7™ Self-Care Behaviors was described, and QoL was a primary or secondary outcome. A 3-tiered review process was utilized for selecting articles. Retained articles were assessed for risk of bias. RESULTS: Nineteen articles, reporting on 17 RCTs, met inclusion criteria, of which 7 studies reported QoL as the primary outcome and 10 as a secondary outcome. Seven studies detected significant impact of DMSE on QoL outcomes in either the participants or family caregivers, which varied in participant populations, selection of QoL tools (generic vs diabetes-specific), intervention type, intervention length, and type of interventionist. CONCLUSION: DSME has the potential to influence QoL outcomes in people with T1DM. Research using more standardized methods are needed to delineate impact on a broader range of factors that influence QoL for those living with T1DM across the life span and their caregivers.

Persistent racial disparities in cervical cancer screening with Pap test.

Given the racial disparities in cervical cancer screening, incidence, and mortality, the purpose of this study was to estimate cervical cancer screening behaviors through self-reported Pap testing among racial groups in the U.S. This cross-sectional study utilized the Behavioral Risk Factor Surveillance System (BRFSS) data to compare Pap testing behaviors among women of different racial groups. The BRFSS data from 2014, 2016, and 2018 were chosen because these were the most recent years of data capturing cervical cancer screening information. The primary outcome was self-reported Pap testing behavior (yes/no). Racial groups were analyzed with the original categorical responses for the race/ethnicity variable to investigate Pap testing behaviors across all racial groups. Statistical analyses included descriptive statistics and a multivariable binomial logistic regression model to assess differences of Pap testing by race after adjusting for covariates. Among the 538,218 females included, 88.81% (95% CI: 88.60-89.03) reported receiving a Pap test. Pap testing behaviors differed significantly between racial groups in 2014, 2016, and 2018 (p < 0.001 for all years). Compared to White women, Asians (OR: 0.169, 95% CI: 0.149-0.191), Native Hawaiians/other Pacific Islanders (OR: 0.339, 95% CI: 0.249-0.462), American Indians or Alaskan Natives (OR: 0.664, 95% CI: 0.532-0.829), Hispanics (OR: 0.726, 95% CI: 0.670-0.786), and other non-Hispanic races (OR: 0.439, 95% CI: 0.323-0.598) were significantly less likely to receive Pap test. Racial disparities in cervical cancer screening with Pap tests exist for Asians, Native Hawaiians/other Pacific Islanders, American Indians or Alaskan Natives, Hispanics, and other non-Hispanics.

Disparities in Cervical Cancer Screening with HPV Test among Females with Diabetes in the Deep South.

BACKGROUND: Due to diabetes being linked with poorer cervical cancer prognosis, this study aimed to evaluate HPV testing behaviors among females with and without diabetes across the U.S. by geographic area in 2016, 2018, and 2020. METHODS: This cross-sectional study used the Behavioral Risk Factor Surveillance System (BRFSS) from 2016, 2018, and 2020. The study population included females aged 25-69 years old, stratified by self-reported diabetes status. The primary outcome measure was cervical cancer screening behavior, which was evaluated by self-reported HPV test uptake/receipt (yes/no). RESULTS: A total of 361,546 females from across the U.S. were sampled. Within the study population combined from all study years, the overall likelihood of receiving an HPV test was significantly lower among females with diabetes [37.95% (95% CI: 36.87-39.04)] compared to those without diabetes [46.21% (95% CI: 45.84-46.58)] (p < 0.001). Screening rates with HPV tests were lowest among females with diabetes in the South in 2016 (29.32% (95% CI: 26.82-31.83)), 2018 (39.63% (95% CI: 36.30-42.96)), and 2020 (41.02% (95% CI: 37.60-44.45)). CONCLUSIONS: Females with diabetes are screening with HPV tests less frequently than females without diabetes, and females living in the South, particularly states in the Deep South, report the lowest rates of HPV testing.

Economic burden of diabetes among medicare beneficiaries with cancer.

OBJECTIVES: Older adults are commonly affected by cancer and diabetes, and an investigation of the economic burden faced by these older adults remains a research gap. Therefore, the objective was to assess the economic burden of diabetes among Medicare beneficiaries with cancer by analyzing annual costs from administrative claims data. METHODS: We conducted a retrospective, serial cross-sectional study using the Medicare Current Beneficiary Survey (MCBS) from 2006 to 2012. Eligible beneficiaries must be currently or previously diagnosed with cancer (of any type), ≥65 years of age, non-institutionalized and continuously enrolled annually in Medicare Parts A, B and D. Diagnoses of cancer and diabetes were determined through self-report or claims. The primary outcome was the total economic burden of diabetes per capita annually, operationalized as the difference in total direct costs between cancer patients with and without diabetes. Simple linear regression was used to analyze trends of costs across the years. Multivariable regression estimated the effect of diabetes and covariates on total annual spending among beneficiaries with cancer from 2006-2012. KEY FINDINGS: From 2006 to 2012, 4918 beneficiaries included in MCBS had cancer, with over 25% (1275) also having diabetes. From 2006 to 2012, the mean economic burden of diabetes was $7815 per capita annually. After adjusting for covariates, beginning in 2006, diagnosis of diabetes significantly predicted higher total annual spending among cancer beneficiaries in 2007 [coefficient (SE) = 0.5768 (0.1918), P = 0.003], 2011 [coefficient (SE) = 0.4303 (0.1817), P = 0.018] and 2012 [coefficient (SE) = 0.3605 (0.1758), P = 0.040]. CONCLUSIONS: Medicare beneficiaries with cancer experienced a higher economic burden from concurrent diabetes.

Patient perspectives on primary care and oncology care coordination in the context of multiple chronic conditions: A systematic review.

BACKGROUND: Patients' views on the optimal model for care coordination between primary care providers (PCPs) and oncologists in the context of cancer and multiple chronic conditions (MCC) are unclear. Thus, the purpose of this systematic review is to evaluate the perceptions of patients with both cancer and MCC regarding their care coordination needs. METHODS: Following PRISMA guidelines, the literature was systematically searched through PubMed, CINAHL, and PsycINFO for articles pertaining to patients' perspectives, experiences, and needs regarding care coordination between PCPs and oncologists during the cancer care continuum, in the context of patients with cancer and MCC. English-language articles were included if they met the following criteria: 1) published between 2008 and 2018; 2) peer-reviewed study; 3) patients aged 18 years or older diagnosed with any type or stage of cancer; 4) patients have one or more chronic comorbid condition; 5) inclusion of patient perceptions, experiences, or needs related to care coordination between PCPs and oncologists; and 6) ability to extract results. Data extraction was performed with a standardized form, and themes were developed through qualitative synthesis. A grounded theory approach was used to qualitatively evaluate data extracted from articles and create a framework for providers to consider when developing patient-centered care coordination strategies for these complex patients. Risk of bias within each study was assessed independently by two authors using the Mixed Methods Appraisal Tool. RESULTS: A total of 22 articles were retained, representing the perspectives of 8,114 patients with cancer and MCC. Studies were heterogeneous in the patients' respective phases of cancer care and study design. From qualitative synthesis, four themes emerged regarding patients' needs for cancer care coordination and were included as constructs to develop the Patient-centered Care Coordination among Patients with Multiple Chronic Conditions and Cancer (PCP-MC) framework. Constructs included: 1) Communication; 2) Defining provider care roles; 3) Information access; and 4) Individualized patient care. Care navigators served as a communication bridge between providers and patients. CONCLUSIONS: Findings highlight the importance that patients with both cancer and MCC place on communication with and between providers, efficient access to understandable care information, defined provider care roles, and care tailored to their individual needs and circumstances. Providers and policymakers may consider the developed PCP-MC framework when designing, implementing, and evaluating patient-centered care coordination strategies for patients with both cancer and MCC.

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

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.