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Background Diabetes mellitus is associated with increased rates of mortality in patients with less severe (stage C) heart failure (HF). The prevalence of diabetes and its complications in advanced (stage D) HF and their contributions to mortality risk are unknown. Methods and Results We conducted a retrospective population-based cohort study of all adult residents of Olmsted County, Minnesota, who had advanced HF between 2007 and 2017. Patients with diabetes were identified by using the criteria of the Healthcare Effectiveness Data and Information Set. Diabetes complications were captured by using the Diabetes Complications Severity Index. Of 936 patients with advanced HF, 338 (36.1%) had diabetes. Overall, median survival time after development of advanced HF was 13.1 (3.9–33.1) months; mortality did not vary by diabetes status (aHR 1.06, 95% CI 0.90–1.25; P = 0.45) or by glycated hemoglobin levels in those with diabetes (aHR 1.01 per 1% increase, 95% CI 0.93–1.10; P = 0.82). However, patients with diabetes and 4 (aHR 1.24, 95% CI 0.92–1.67) or 5–7 (aHR 1.49, 95% CI 1.09–2.03) diabetes complications were at increased risk of mortality compared to those with ≤ 3 complications. Conclusions More than one-third of patients with advanced HF have diabetes. In advanced HF, overall prognosis is poor, but we found no evidence that diabetes is associated with a significantly higher mortality risk.

A multidisciplinary approach, including pharmacist interventions, has improved clinical outcomes and reduced economic costs in chronic disease management. To our knowledge, this is the first study to describe the incorporation of pharmacist‐driven medication management with partnering nephrologists while capitalizing on technology to improve outcomes in a Chronic kidney disease (CKD) population. The authors created a collaborative drug therapy management agreement to enhance medication management for hypertension and diabetes mellitus. Our metrics aligned with the Healthcare Effectiveness Data and Information Set (HEDIS) measures. Most referrals to the program met the HEDIS definition of suboptimal disease control (Diabetes: 19/25 and Hypertension: 45/70). In patients with multiple pharmacy visits, achievement of diabetes targets increased from 23% to 67% and hypertension from 29% to 58%. Those who used technology tools were more likely to reach goals. The positive impact of a pharmacist‐physician collaboration and utilization of technology tools present an opportunity to improve care for CKD patients.

ObjectiveTo explore the use of health plan quality measures specified for electronic clinical data to monitor immunizations.Materials and MethodsWe analyzed 2018 data submitted by health plans reporting 2 new Healthcare Effectiveness Data and Information Set measures assessing receipt of clinically recommended vaccines among pregnant women and adults. We analyzed the number of plans reporting a valid performance rate and electronic data source used. We consulted expert panels and reviewed coverage rates from other sources to understand the results.ResultsWe received 136 data submissions across commercial, Medicaid and Medicare plans and 87 submissions across commercial and Medicaid plans for the adult and prenatal immunization measures, respectively. These submissions represent approximately 15% of possible submissions. Plans used claims, registries and electronic health records. Mean performance rates for adult immunizations were 21.2 (commercial), 14.0 (Medicaid) and 19.5% (Medicare). Mean rates for prenatal immunizations were 33.1 (commercial) and 16.7% (Medicaid).DiscussionResults from the first year of reporting 2 electronic clinical data measures suggest health plans can feasibly report these measures and are seeking electronic data to supplement claims. Comparison of rates to other national results showed lower than expected rates for the adult immunization measure. However, prenatal immunization rates were on par with those from a national survey, suggesting this measure is closer to use for quality improvement.ConclusionQuality measure reporting that encourages connection to electronic data sources is a step forward in performance monitoring and improvement. The use of electronic sources may advance health information exchange for patient care.

PURPOSE: This study aimed to evaluate the receipt of chlamydia and gonorrhea screening among women aged 15–24 years undergoing long-acting reversible contraception (LARC) insertion. METHODS: We used the 2016–2017 MarketScan commercial claims data set to identify sexually active women aged 15–24 years with LARC insertion in 2017 and had ≥12 months of insurance coverage before the date of LARC insertion. Sexual activity (defined by Healthcare Effectiveness Data and Information Set chlamydia testing measure) and LARC insertion, including intrauterine device (IUD) and implant insertion, were identified by applicable International Classification of Disease, Tenth Revision, Healthcare Common Procedure Coding System, and Current Procedural Terminology codes. We evaluated chlamydia and gonorrhea testing performed in the preceding 12 months or at the time of LARC insertion among sexually active women aged 15–24 years. RESULTS: We identified 37,331sexually active women aged 15–24 years with LARC insertion. Among these women, overall chlamydia testing was more frequent among women initiating an IUD (77.8%) than implant initiators (67.8%), p < .001. A similar pattern was seen for gonorrhea testing (80.0% for IUD users, 71.1% for implant users), p < .001. Among sexually active women without chlamydia and gonorrhea testing within the 12 months before the date of insertion, IUD users were more frequently tested for chlamydia (1,410 [20.9%] vs. 433 [9.2%]; p < .001) and for gonorrhea (1,206 [20.0%] vs. 374 [8.9%]; p < .001) than implant users on the day of LARC insertion. CONCLUSIONS: Our results showed that approximately one in four sexually active women undergoing LARC insertion had not received recommended chlamydia and gonorrhea screening past year. Health care providers may use LARC-related visits as an opportunity to educate patients about, and to offer, chlamydia and gonorrhea screening if they had not been screened in the past 12 months.

Introduction Emergency department (ED) initiated opioid use disorder (OUD) care is effective; however, real-world predictors of patient engagement are lacking. Objective This program evaluation examined predictors of ED-based OUD treatment and subsequent engagement. Method Program evaluation in Boston, MA. Adult patients who met criteria for OUD during an ED visit in 2019 were included. Patients were included if a diagnosis of OUD or opioid-related overdose was associated with the ED visit or if they met previously validated criteria for OUD within the previous 12 months. We assessed predictors of ED-OUD treatment receipt and subsequent engagement, using Healthcare Effectiveness Data and Information Set definition of initial encounter within 14 days of discharge and either 2 subsequent encounters or a subsequent buprenorphine prescription within 34 days of the initial encounter. We used generalized estimating equations for panel data. Results During 2019, 1946 patients met criteria for OUD. Referrals to Bridge Clinic were made for 207 (11%), buprenorphine initiated for 106 (5%), and home induction buprenorphine kits given to 56 (3%). Following ED discharge, 237 patients (12%) had a visit within 14 days, 122 (6%) had ≥2 additional visits, and 207 (11%) received a subsequent buprenorphine prescription. Young, White, male patients were most likely to receive ED-OUD care. Patients who received ED-OUD care were more likely to have subsequent treatment engagement (adjusted rate ratio: 2.30, 95% confidence intervals: 1.62-3.27). Referrals were made less often than predicted for Black (-49%) or Hispanic/Latinx (-25%) patients. Conclusions Initiating treatment for OUD in the ED was associated with increased engagement in outpatient addiction care.

Recommended A1C targets for people with type 2 diabetes are between 6.5 and 8%; however, real-world data suggest that an increasing proportion of people with diabetes have suboptimal control, and ∼15% have an A1C level >9%. People with A1C >9% are at increased risk for micro- and macrovascular complications and require treatment intensification to improve glycemic control as early as possible. In a series of short videos now available on the Clinical Diabetes website, the authors discuss the pathophysiological changes that occur during the progression of type 2 diabetes, with particular focus on the key role of declining β-cell function. The authors review clinical characteristics—long diabetes duration and A1C ≥9%—that are indicative of diminishing β-cell function, and they discuss the clinical data that support the use of available treatment options for these individuals, consistent with current diabetes treatment guidelines. This article is intended to briefly summarize those discussions. The videos described below are available in their entirety, along with short biographies of the authors, at https://clinical.diabetesjournals.org/content/combination-injectable-therapy. ### Need for Glycemic Control in Individuals With A1C ≥9% (Video 1) Video 1. Need for Glycemic Control in Individuals With A1C ≥9%. Available from https://bcove.video/3bda5FB. Current treatment guidelines for people with type 2 diabetes from the American Diabetes Association, the American Association of Clinical Endocrinologists, the American College of Endocrinology, and the American College of Physicians recommend A1C targets within the range of 6.5–8% (1–3). However, public health reports suggest that a significant proportion of U.S. adults with diabetes have an A1C >9% (4), which is defined as “poor glycemic control” by the Healthcare Effectiveness Data and Information Set (5). Furthermore, A1C levels >9% can negatively affect reimbursement (e.g., through a decrease in the star ratings used to assess quality and performance) (6). In this video, the authors discuss the deleterious health consequences for patients with high A1C levels, including …

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians, Inc., and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes. The following article describes a resident-led initiative that improved diabetic nephropathy screening in a primary care clinic. It also highlights the challenges of complex metrics, as well as the potential unintended consequences of emphasizing one dimension of a care process over another.

BACKGROUND: Medicaid managed care plans change provider networks frequently, yet there is no evidence about the performance of exiting providers relative to those that remain. OBJECTIVES: To investigate the association between provider cost and quality and network exit. DESIGN: Observational study with provider network directory data linked to administrative claims from managed care plans in Tennessee’s Medicaid program during the period 2010–2016. PARTICIPANTS: 1,966,022 recipients assigned to 9593 unique providers. MAIN MEASURES: Exposures were risk-adjusted total costs of care and nine measures from the Healthcare Effectiveness Data and Information Set (HEDIS) were used to construct a composite annual indicators of provider performance on quality. Outcome was provider exit from a Medicaid managed care plan. Differences in quality and cost between providers that exited and remained in managed care networks were estimated using a propensity score model to match exiting to nonexiting providers. KEY RESULTS: Over our study period, we found that 21% of participating providers exited at least one of the Medicaid managed care plans in Tennessee. As compared with providers that remained in networks, those that exited performed 3.8 percentage points [95% CI, 2.3, 5.3] worse on quality as measured by a composite of the nine HEDIS quality metrics. However, 22% of exiting providers performed above average in quality and cost and only 29% of exiting providers had lower than average quality scores and higher than average costs. Overall, exiting providers had lower aggregate costs in terms of the annual unadjusted cost of care per-member-month − $21.57 [95% CI, − $41.02, − $2.13], though difference in annual risk-adjusted cost per-member-month was nonsignificant. CONCLUSIONS: Providers exiting Medicaid managed care plans appear to have lower quality scores in the year prior to their exit than the providers who remain in network. Our study did not show that managed care plans disproportionately drop high-cost providers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-020-05784-4) contains supplementary material, which is available to authorized users.

Nineteen US states and D.C. have used the Affordable Care Act Medicaid health home waiver to create behavioral health home (BHH) programs for Medicaid beneficiaries with serious mental illness (SMI). BHH programs integrate physical healthcare management and coordination into specialty mental health programs. No studies have evaluated the effects of a BHH program created through the Affordable Care Act waiver on cardiovascular care quality among people with SMI. To study the effects of Maryland’s Medicaid health home waiver BHH program, implemented October 1, 2013, on quality of cardiovascular care among individuals with SMI. Retrospective cohort analysis using Maryland Medicaid administrative claims data from July 1, 2010, to September 30, 2016. We used marginal structural modeling with inverse probability of treatment weighting to account for censoring and potential time-dependent confounding. Maryland Medicaid beneficiaries with diabetes or cardiovascular disease (CVD) participating in psychiatric rehabilitation programs, the setting in which BHHs were implemented. To qualify for psychiatric rehabilitation programs, individuals must have SMI. The analytic sample included BHH and non-BHH participants, N = 2605 with diabetes and N = 1899 with CVD. Healthcare Effectiveness Data and Information Set (HEDIS) measures of cardiovascular care quality including annual receipt of diabetic eye and foot exams; HbA1c, diabetic nephropathy, and cholesterol testing; and statin therapy receipt and adherence among individuals with diabetes, as well as HEDIS measures of annual receipt of cholesterol testing and statin therapy and adherence among individuals with CVD. Relative to non-enrollment, enrollment in Maryland’s BHH program was associated with increased likelihood of eye exam receipt among individuals with SMI and co-morbid diabetes, but no changes in other care quality measures. Additional financing, infrastructure, and implementation supports may be needed to realize the full potential of Maryland’s BHH to improve cardiovascular care for people with SMI.

Introduction Primary care provider encounters are associated with health and well-being; however, limited evidence guides optimal primary care provider rate of visit, referred to as encounter cadence. This study measures associations between primary care provider encounter cadence and diabetes outcomes among individuals newly diagnosed with type 2 diabetes mellitus. Methods In this retrospective cohort study, 7,106 people enrolled in Medicare Advantage and newly diagnosed with type 2 diabetes mellitus between July 1, 2012 and June 30, 2013 were identified and followed for 36 months. Two methods measured primary care provider encounter cadence: total primary care provider encounters (frequency) and quarters with primary care provider encounter (regularity). Logistic regression measured relationships between primary care provider encounter cadence and non-insulin diabetes medication adherence, HbA1c control, emergency department visits, and inpatient admissions. Non-insulin diabetes medication adherence was defined according to the National Committee for Quality Assurance, Healthcare Effectiveness Data and Information Set specifications and measured using healthcare claims data. Post-hoc models examined adherence and diabetes control among those nonadherent (n=5,212) and with noncontrolled HbA1c (n=326) during the encounter/cadence period. Data were extracted and analyzed in 2017. Results Adjusted models indicated that both frequency (AOR=1.08, 95% CI=1.06, 1.10) and regularity (AOR=1.18, 95% CI=1.13, 1.22) of primary care provider encounters were associated with increased odds of adherence. Post-hoc analyses indicated that more frequent (AOR=1.12, 95% CI=1.10, 1.15) and regular (AOR=1.27, 95% CI=1.22, 1.33) primary care provider encounters were associated significantly with adherence and were associated directionally with HbA1c control. Conclusions More frequent and regular primary care provider encounters are associated with an increased likelihood of non-insulin diabetes medication adherence. These findings contribute to data needed to establish evidence-based guidelines for primary care provider encounter cadence for those newly diagnosed with type 2 diabetes mellitus.

Background As treatments for cancer have improved, more people are surviving cancer. However, compared to people without a history of cancer, cancer survivors are more likely to die of cardiovascular disease (CVD). Increased risk for CVD-related mortality among cancer survivors is partially due to lack of medication adherence and problems that exist in care coordination between cancer specialists, primary care physicians, and cardiologists. Methods/Design The Onco-primary care networking to support TEAM-based care (ONE TEAM) study is an 18-month cluster-randomized controlled trial with clustering at the primary care clinic level. ONE TEAM compares the provision of the iGuide intervention to patients and primary care providers versus an education-only control. For phase 1, at the patient level, the intervention includes video vignettes and a live webinar; provider-level interventions include electronic health records-based communication and case-based webinars. Participants will be enrolled from across North Carolina one of their first visits with a cancer specialist (e.g., surgeon, radiation or medical oncologist). We use a sequential multiple assignment randomized trial (SMART) design. Outcomes (measured at the patient level) will include Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of management of three CVD comorbidities using laboratory testing (glycated hemoglobin [A1c], lipid profile) and blood pressure measurements; (2) medication adherence assessed pharmacy refill data using Proportion of Days Covered (PDC); and (3) patient-provider communication (Patient-Centered Communication in Cancer Care, PCC-Ca-36). Primary care clinics in the intervention arm will be considered non-responders if 90% or more of their participating patients do not meet the modified HEDIS quality metrics at the 6-month measurement, assessed once the first enrollee from each practice reaches the 12-month mark. Non-responders will be re-randomized to either continue to receive the iGuide 1 intervention, or to receive the iGuide 2 intervention, which includes tailored videos for participants and specialist consults with primary care providers. Discussion As the population of cancer survivors grows, ONE TEAM will contribute to closing the CVD outcomes gap among cancer survivors by optimizing and integrating cancer care and primary care teams. ONE TEAM is designed so that it will be possible for others to emulate and implement at scale. Trial registration This study (NCT04258813) was registered in clinicaltrals.gov on February 6, 2020.

Background Pharmacists can optimize outcomes related to type-2 diabetes (T2D) by taking advantage of telehealth opportunities despite the coronavirus 2019 (COVID-19) Public Health Emergency (PHE). Objective Identify and compare changes in T2D outcomes before (August 2019 through February 2020) and during (March 2020 through October 2020) the COVID-19 PHE. Secondary objectives were to identify and compare pay-for-performance metrics and additional fee-for-service submitted in these patients. Methods This study examined changes in T2D outcomes at one primary care office within a community health system. Pharmacists started regularly using Remote Patient Monitoring (RPM) services during the COVID-19 PHE to reduce in-person visits. Patients with an initial glycosylated hemoglobin (A1C) greater than or equal to 8% were included. Data collected included comorbidities, change in A1C, and diabetes and statin medication therapy adherence. Percentage of Healthcare Effectiveness Data and Information Set (HEDIS) and Merit-Based Incentive Payment System (MIPS) measures were met, and billing code frequencies were also assessed. Results In the pre–COVID-19 PHE group (N = 30), the average 3- and 6-month A1C reductions were 1.3% and 1.2%, respectively, and the reductions were 2.0% and 2.2% in the during-COVID-19 PHE group (N = 61). The percentage of patients appropriately initiated or maintained on statins was 96.2% in the pre–COVID-19 PHE group versus 82.6% in the during-COVID-19 PHE group. Related to HEDIS, statin adherence was 95.2% in the pre–COVID-19 PHE group and 84.2% in the during-COVID-19 PHE group, and A1C control was 41.7% versus 54%, respectively. A1C control related to MIPS was 60% before COVID-19 PHE versus 73.8% during the COVID-19 PHE. Diabetes medication adherence related to HEDIS and medication reconciliation related to MIPS was 100% for both groups. Conclusion Data demonstrate the opportunity for pharmacists to maintain and improve clinical outcomes related to T2D despite the ongoing COVID-19 PHE through implementation of telephonic monitoring.

Objective The tAccess Patient Support Program (PSP) is a personalized support program for patients prescribed vortioxetine therapy. We assessed the impact of the tAccess PSP on adherence to and persistence with vortioxetine among adult patients with major depressive disorder (MDD). Methods A retrospective observational cohort study was conducted in patients with MDD receiving vortioxetine who were enrolled in the tAccess PSP. Eligible patients were 18 to 64 years of age and had ≥1 vortioxetine claim and ≥1 inpatient/outpatient medical MDD claim during the 12 months preceding or on the index date, defined as the date of the earliest vortioxetine claim. Study outcomes included medication adherence (proportion of days covered [PDC], adherent ≥80%) and persistence (the total number of days on therapy without a ≥30-day gap) at 90, 180, and 365 days. Additionally, persistence was reported for a subset of patients meeting the standardized Healthcare Effectiveness Data and Information Set (HEDIS®) Antidepressant Medication Management (AMM) criteria (the percentage of adults aged 18 to 64 years who remained on an antidepressant for ≥84 days or ≥180 days), as defined by the National Committee for Quality Assurance. These data were reviewed alongside current HEDIS AMM data for commercially insured patients meeting the standardized metric. Results The study identified a total of 2635 patients with an MDD diagnosis and ≥90 days of follow-up time and a subset of 2238 patients meeting HEDIS AMM criteria. Mean PDC among all patients with MDD was 0.78, with 58.3% of patients achieving PDC ≥80%. During the 90-day follow-up, 62.1% of patients with MDD were persistent on vortioxetine. Among the subset of patients who met HEDIS AMM criteria, persistence was 83.4% and 69.9% at 84 and 180 days, respectively. In comparison, in 2017, HEDIS AMM criteria for antidepressant persistence were met by 67.8% of commercially insured patients at 84 days and 51.8% at 180 days. Conclusions These initial results, reviewed alongside recent available HEDIS AMM data, suggest that the tAccess PSP may be beneficial in addressing treatment adherence and persistence in patients with MDD.

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

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

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

Introduction A composite adult immunization status measure is currently under consideration for adoption into the Healthcare Effectiveness Data and Information Set. This paper complements the Healthcare Effectiveness Data and Information Set health plan–level measure testing efforts by examining use of survey-based self-reported vaccination data to assess composite adult immunization coverage and identify limitations to using survey data to measure progress. Methods The 2015 National Health Interview Survey data were used in 2017 to calculate estimates for a composite of selected vaccines routinely recommended for adults aged ≥19 years, overall and in three age groups: 19–59, 60–64, and ≥65 years for tetanus and diphtheria toxoids (Td); tetanus toxoid; reduced diphtheria toxoid; and tetanus, diphtheria, acellular pertussis vaccine (Tdap); and herpes zoster, pneumococcal, and influenza vaccines. Results Composite coverage for adults aged ≥19 years including receipt of Tdap in the past 10 years and influenza vaccination was 11.9%, ranging from 6.3% in adults aged 60–64 years to 13.7% in adults aged 19–59 years. Excluding influenza, composite coverage was 20.7%, ranging from 8.1% (adults aged 60–64 years) to 25.2% (adults aged 19–59 years). In a composite including any Td-containing vaccine in the past 10 years, coverage including influenza vaccination for adults aged ≥19 years was 23.4%, ranging from 12.6% (adults aged 60–64 years) to 25.7% (adults aged 19–59 years). Excluding influenza, composite coverage was 51.4%, ranging from 15.8% (adults aged 60–64 years) to 63.0% (adults aged 19–59 years). Conclusions Survey-based vaccination data may under- or over-estimate coverage, but most adults require at least one additional vaccination by any metric. A composite measure provides a single focal point to promote adherence to standards of care.

As the Medicare population becomes more diverse and its demand for behavioral health care grows, a better understanding of racial/ethnic disparities in the quality of behavioral health care is crucial. Medicare Advantage (MA) plans are accountable through the public reporting of quality performance on measures, including the Healthcare Effectiveness Data and Information Set (HEDIS). We examined HEDIS data on eight MA behavioral health care quality measures, using mixed-effects logistic regressions to distinguish racial/ethnic differences within and between MA health plans. We found that performance differed across racial/ethnic groups by more than 10 percentage points on most quality measures. Significant within-plan disparities were found in twenty of twenty-four comparisons of racial/ethnic minority groups with whites. Within-plan disparities varied widely across plans, with performance being equivalent across racial/ethnic groups in some plans and widely divergent in others. Unlike other types of medical care, in behavioral health within-plan quality disparities are prominent in MA plans, which suggests a role for stratified reporting by racial/ethnic group.

Introduction For the past 16 years, Military Health System primary care providers have been incentivized to pursue work in a fee-for-service (FFS) model. The system values documentation of productivity to earn as many relative value units as possible. The result is densely packed clinic schedules that often lack the space or flexibility to accommodate patients when sick. Leakage ensues. Furthermore, prevention and patient experience are not directly incentivized. Methods The Central Texas Market’s Accountable Care Organization reformed incentives in its #5 FFS-designed community-based medical homes to value outcomes over productivity. The resulting quality, urgent, internet, and phone care (QUiC) clinics are value-based and, therefore, better structured to achieve the Quad aim (better care, better health/readiness, and low cost). Forsaking deeply ingrained FFS practices, QUiC clinics funnel all routine (information-sharing) appointments into efficient internet or phone appointments. With the time freed by managing common needs in short bursts, QUiC clinics see sick patients with no notice (urgent care). They also focus on prevention and patient experience. We measured the effectiveness of the QUiC clinics in the value-based metrics of (1) patient experience, (2) Healthcare Effectiveness Data and Information Set measures of quality and prevention. (3) access-to-care, (4) leakage, and (5) enrollment. Results Over a 19 month period, the five community-based medical homes improved significantly in all areas. Specifically, measures of patient satisfaction improved from the mid-80s percent satisfied to the mid-90s percent satisfied. Healthcare Effectiveness Data and Information Set measures increased from average compared to national benchmarks ( Conclusions This performance improvement project proved the concept that a military market can vastly improve value-based primary care outcomes at no cost and within multiple community-based clinics.

Background The American Community Survey (ACS) is the largest household survey conducted by the US Census Bureau. We sought to describe the community-level characteristics derived from the ACS among enrollees of Kaiser Permanente Southern California (KPSC), evaluate the associations between ACS estimates and selective individual-level health outcomes, and explore how using different scales of the census geography and the linearity assumption affect the associations. Methods We examined the associations between track-level and block group-level ACS 5-year estimates and 4 individual-level Healthcare Effectiveness Data and Information Set (HEDIS) outcome measures (comprehensive diabetes care, postpartum care, antidepressant medication management, and childhood immunization status) using multilevel generalized linear models. Odds ratios and their 95% confidence intervals were estimated for every 10% increase in ACS measures. Results 6,357,841 addresses were successfully geocoded to at least the tract level. The community-level demographic, socioeconomic, residential, and other ACS measures varied among KPSC health plan enrollees. A majority of these ACS measures were associated with the selected HEDIS health outcomes. The directions of the effects were consistent across health outcomes; however, the magnitudes of the effect sizes varied. Within each HEDIS health outcome, the relative size of the effects appeared to remain similar. Differences between the census tract- and block group-level estimates were minor, especially for measures related to race/ethnicity, education, income, and occupation. Conclusion These findings support the use of many ACS measures at neighborhood levels to predict health outcomes. The geographic units might have little effect on the results. The linearity assumption should be made with caution.

Objective Pediatric asthma is a costly and complex disease with proven interventions to prevent exacerbations. Finding the patients at highest risk of exacerbations is paramount given limited resources. Insurance claims identify all outpatient, inpatient, emergency, pharmacy, and diagnostic services. The objective was to develop a risk score indicating the likelihood of asthma exacerbation within the next year based on prior utilization. Methods A retrospective analysis of insurance claims for patients 2 to 18 years in a network in Massachusetts with 3 years of continuous enrollment in a commercial plan. Thirty-six potential predictors of exacerbation in the third year were assessed with a stepwise regression. Retained predictors were weighted relative to their contribution to asthma exacerbation risk and summed to create the Asthma Exacerbation Risk (AER) score. Results In a cohort of 28,196 patients, there were 10 predictors associated with the outcome of having an asthma exacerbation in the next year that depend on age, meeting the Healthcare Effectiveness Data and Information Set persistent asthma criteria, fill patterns of asthma medications and oral steroids, counts of nonexacerbation outpatient visits, an exacerbation in the last 6 months, and whether spirometry was performed. The AER score is calculated monthly from a claims database to identify potential patients for an asthma home-visiting program. Conclusions The AER score assigns a risk of exacerbation within the next 12 months using claims data to identify patients in need of preventive services.

Objectives: To assess the association of HEDIS C&M phase follow-up measure with ADHD medication adherence. Methods: A retrospective study was conducted using Medicaid data (2014–2016) of children initiated with ADHD medication. Patients were categorized as meeting the C&M follow-up measure or not according to the HEDIS specifications. Medication adherence was measured using both Proportion of Days Covered (PDC) & Group-Based Trajectory Modeling (GBTM). The association of medication adherence with HEDIS measure was assessed using Chi-square test. Results: Nearly all (97%) children with PDC≥0.7 and 72% of patients following the late decliner adherence trajectory met the HEDIS C&M follow-up criteria. In contrast, none of the children with PDCConclusion: ADHD medication adherence, regardless of how it was measured, clearly differentiated children with and without C&M phase follow-up, which essentially questions the implication of HEDIS C&M phase follow-up care measure.

Background There is excess amenable mortality risk and evidence of healthcare quality deficits for persons with serious mental illness (SMI). We sought to identify sociodemographic and clinical characteristics associated with variations in two 2015 Healthcare Effectiveness Data and Information Set (HEDIS) measures, antipsychotic medication adherence and preventive diabetes screening, among Medicaid enrollees with serious mental illness (SMI). Methods We retrospectively analyzed claims data from September 2014 to December 2015 from enrollees in a Medicaid specialty health plan in Florida. All plan enrollees had SMI; analyses included continuously enrolled adults with antipsychotic medication prescriptions and schizophrenia or bipolar disorder. Associations were identified using mixed effects logistic regression models. Results Data for 5502 enrollees were analyzed. Substance use disorders, depression, and having both schizophrenia and bipolar disorder diagnoses were associated with both HEDIS measures but the direction of the associations differed; each was significantly associated with antipsychotic medication non-adherence (a marker of suboptimal care quality) but an increased likelihood of diabetes screening (a marker of quality care). Compared to whites, blacks and Hispanics had a significantly greater risk of medication non-adherence. Increasing age was significantly associated with increasing medication adherence, but the association between age and diabetes screening varied by sex. Other characteristics significantly associated with quality variations according to one or both measures were education (associated with antipsychotic medication adherence), urbanization (relative to urban locales, residing in suburban areas was associated with both adherence and diabetes screening), obesity (associated with both adherence and diabetes screening), language (non-English speakers had a greater likelihood of diabetes screening), and anxiety, asthma, and hypertension (each positively associated with diabetes screening). Conclusions The characteristics associated with variations in the quality of care provided to Medicaid enrollees with SMI as gauged by two HEDIS measures often differed, and at times associations were directionally opposite. The variations in the quality of healthcare received by persons with SMI that were identified in this study can guide quality improvement and delivery system reform efforts; however, given the sociodemographic and clinical characteristics’ differing associations with different measures of care quality, multidimensional approaches are warranted.

Introduction Improving the utilization of preventive care among adolescents is important for achieving individual-level and population-level health goals. The Healthcare Effectiveness Data and Information Set reports data submitted by managed care health plans, capturing a large number of individuals in the U.S. Methods Using Healthcare Effectiveness Data and Information Set from 2018, mean performance levels were calculated for 5 preventive care measures among adolescents. Differences in performance between states that use Healthcare Effectiveness Data and Information Set or Health Plan Accreditation and those that use neither were estimated. Analysis was conducted in January–July 2020. Results The sample included data from 39 states, with 32 that use Healthcare Effectiveness Data and Information Set or Health Plan Accreditation and 7 that do not. Adolescent vaccination coverage was 28% for the complete human papillomavirus series, 81% for meningococcal, and 88% for tetanus, diphtheria, and acellular pertussis. Access to a primary care practitioner (a 2-year measure) was 91%, and well-care visits (a 1-year measure) were 50%. When compared with states that do not use Healthcare Effectiveness Data and Information Set or Health Plan Accreditation, the mean performance of states that used either Healthcare Effectiveness Data and Information Set or Health Plan Accreditation was statistically significantly higher for 4 of the 5 assessed measures. Conclusions Healthcare Effectiveness Data and Information Set measures can help public health officials to monitor progress toward health goals, such as Healthy People 2020, and identify poorly performing health plans and types of preventive services in greatest need of improvement. States using Healthcare Effectiveness Data and Information Set or Health Plan Accreditation were associated with better performance in some adolescent measures, which suggests that health plan accountability may have a role in achieving health outcomes and could be an important area for future research.

Patient-reported outcomes are a useful tool to understand the impact of treatments in clinical application on a large scale. This retrospective study characterized patient-reported outcomes of a large cohort of adults in the United States with type 2 diabetes using a tubeless insulin pump (Omnipod® or Omnipod DASH™ Insulin Management System, Acton, MA). From Jan. 2015-Jan. 2020, patient-reported outcomes were recorded before and ≥90 days after initiating system use. Primary outcomes were change in self-reported A1C and total daily dose of insulin. Patients (N=2,335) were aged (mean±SD) 58±11y and 53% female. The percentage of users with a self-reported A1C ≤8% increased from 33% pre-tubeless pump to 64% post-tubeless pump, and the percentage with a self-reported A1C >9% decreased from 44% to 15% (p These patient-reported outcomes provide positive evidence that use of a tubeless insulin pump was associated with glycemic outcomes that exceed U.S. National Healthcare Effectiveness Data and Information Set (HEDIS) standards for adequate diabetes management. Disclosure A.L. Carlson: Consultant; Self; Medtronic. Research Support; Self; Abbott, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S, Sanofi, UnitedHealth Group. L.M. Huyett: Employee; Self; Insulet Corporation. J. Jantz: Employee; Self; Insulet Corporation. A. Chang: Employee; Self; Insulet Corporation. Stock/Shareholder; Self; Insulet Corporation. T. Vienneau: Employee; Self; Insulet Corporation. Stock/Shareholder; Self; Insulet Corporation. T.T. Ly: Employee; Self; Insulet Corporation. Funding Insulet Corporation

BackgroundThe National Committee on Quality Assurance’s Healthcare Effectiveness Data and Information Set on Comprehensive Diabetes Care requires patients with diabetes obtain a hemoglobin A1c (Hb A1c) and urine albumin-to-creatinine ratio (ACR) test every year. To improve these measures, managed care organizations (MCOs) rely on claim and prescription data to identify members for care management. TriCore Reference Laboratories collaborated with Blue Cross Blue Shield of New Mexico (BCBSNM) to determine if laboratory information would augment BCBSNM’s diabetes care management services.MethodIn January 2018, BCBSNM provided its Medicaid enrollment file to TriCore for identifying members and determining their diabetes status by evaluating their recent Hb A1c results. Of the 6,138 members with diabetes, a random sample of 600 was extracted, and half were provided to BCBSNM to perform care management from January 18 to May 1, 2018. Completion of Hb A1c and ACR were measured.ResultsSignificantly more (P = 0.03) study group members (25%) than control group members (18%) received an Hb A1c test. The study group (14%) also received more ACR tests than the control group (9%; P = 0.07). We then calculated the monetary penalty to which New Mexico Medicaid MCOs are subject, leading to the identification of additional value ($3,693,000) that clinical laboratories provide beyond the cost per test.ConclusionClinical laboratories play a critical role in healthcare, and this article demonstrates an approach for laboratories to collaborate with MCOs in their care management efforts. In addition, we calculate the value of this novel collaboration, which may play an integral role in laboratories’ pursuit of value-based care.

This cross-sectional study evaluates the agreement between readmission rates reported by Medicare Advantage contracts and readmission rates calculated from their encounter data in the Healthcare Effectiveness Data and Information Set (HEDIS).

Inpatient hospitalizations for ambulatory care sensitive conditions (ACSC) among beneficiaries with and without intellectual and developmental disabilities (IDD) were examined using Medicaid and commercial claims from 2010–2014 in New Hampshire. IDD was defined with International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes using algorithms from the Centers for Medicare and Medicaid Services, and inpatient encounters were identified using the Healthcare Effectiveness Data and Information Set. In adjusted analyses, beneficiaries with IDD had more hospitalizations for ACSC than those without IDD in both insurance groups. Differences in patterns of ACSC prevalence, comorbidities, and hospital admissions between the commercially and Medicaid-insured groups show the value of using all-payer claims data, when possible, to understand health needs and health care utilization of insurance beneficiaries with IDD.

Background Reducing caries and improving access to dental care is a public health challenge. Understanding low use of dental care is of critical importance. This study estimated parent- or caregiver-reported prevalence and identified factors associated with children’s dental care use, including the association with children’s oral health. Methods A cross-sectional analysis of children enrolled in Medicaid in Alabama, using data from the 2017 statewide Consumer Assessment of Healthcare Providers and Systems Health Plan Survey, was conducted. Associations were measured using adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs) from logit regression and generalized linear model postestimation of least-squares means. Results The 6-month prevalence of children receiving dental care was 70.4%. Children aged 0 through 3 years (aPR, 0.72; 95% CI, 0.53 to 0.91) had lower prevalence of care than other age groups. The prevalence of low-rated oral health was 9.2%. Low-rated oral health was associated with not receiving dental care (aPR, 1.50; 95% CI, 1.12 to 1.87) and parental education of 8th grade or less (aPR, 2.59; 95% CI, 1.20 to 3.98). Falsification tests determined that dental care use was not associated with ratings for overall health (aPR, 1.18; 95% CI, 0.83 to 1.52) or emotional health (aPR, 1.06; 95% CI, 0.79 to 1.33). Conclusions It was observed that children not receiving dental care had low-rated oral health; however, as a cross-sectional study, it was not possible to assess the temporality of this relationship. Practical Implications Oral health care providers should continue to recognize their role in educating parents and providing anticipatory guidance on children’s oral health.

Understanding the nature of variations in the quality of substance use treatment is critical to ensuring equity in service delivery and maximizing treatment effectiveness. We used adapted versions of the US Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures to assess care quality in specialized outpatient services for substance use in Ontario, Canada. Using administrative data, we calculated rates of outpatient treatment initiation and engagement (N = 120,394 episodes) and investigated variation by client characteristics and treatment mandates. About half of clients who entered outpatient treatment met the criteria for initiation (i.e., had a second visit within 14 days) and 30% met the criteria for engagement (i.e., had another two visits within 30 days of initiation). The likelihood of treatment initiation and engagement was greater among older people, those with more education, those who were not mandated to enter treatment, and those with greater substance use at admission. People who entered treatment for cannabis were less likely to engage. Engagement was less likely among men than women, but gender differences were slight overall. This study demonstrates the feasibility of using adapted versions of two common measures to characterise care quality in substance use treatment services in the Canadian context. Overall, the magnitude of associations with client characteristics were quite small, suggesting that initiation and engagement were not overly localized to specific client subgroups. Findings suggest that the Ontario system has difficulty retaining clients who enter treatment and that most outpatient treatment involves care episodes of limited duration.

Attainment of asthma-specific US Healthcare Effectiveness Data and Information Set (HEDIS) quality measures may be associated with improved clinical outcomes and reduced economic burden.We examined the relationship between the attainment of HEDIS measures asthma medication ratio (AMR) and medication management for people with asthma (MMA) on clinical and economic outcomes.This retrospective claims database analysis linked to ambulatory electronic medical records enrolled US patients aged ≥5 years with persistent asthma between May 2015 and April 2017. The attainment of AMR ≥0.5 and MMA ≥75% was determined over a 1-year premeasurement period. Asthma exacerbations and asthma-related health care costs were evaluated during the subsequent 12-month measurement period, comparing patients attaining 1 or both measures with those not attaining either.In total, 32,748 patients were included, 75.2% of whom attained AMR (n = 24,388) and/or MMA (n = 12,042) during the premeasurement period. Fewer attainers of 1 or more HEDIS measures had ≥1 asthma-related hospitalizations, emergency department visit, corticosteroid burst, or exacerbation (4.9% vs 7.3%; 9.6% vs 18.2%; 43.8% vs 51.6%; 14.3% vs 23.3%, respectively; all P.001) compared with nonattainers. In adjusted analyses, HEDIS attainment was associated with a lower likelihood of exacerbations (odds ratio: 0.63, [95% confidence interval: 0.60-0.67]; P.001). The attainment of ≥1 HEDIS measures lowered total and asthma-related costs, and asthma exacerbation-related health care costs per patient relative to nonattainers (cost ratio: 0.87, P.001; 0.96, P = .02; and 0.59, P.001, respectively). Overall and asthma-specific costs were lower for patients attaining AMR, but not MMA.HEDIS attainment was associated with significantly improved asthma outcomes and lower asthma-specific costs.

Background Health plans are increasingly implementing quality improvement strategies aimed at meeting adolescent clinical quality measures, yet clinics often struggle to meet these measures. This qualitative study was conducted to explore how efforts to meet the National Committee for Quality Assurance (NCQA) Healthcare Effectiveness Data and Information Set (HEDIS) performance measure for adolescent well-care visits were perceived by a multidisciplinary group of stakeholders. Methods The research team conducted 26 in-depth, semistructured interviews with participants from three stakeholder groups: clinic staff with direct patient contact, health care institutional leaders, and representatives of a payer organization. Interviews were about 45 minutes in duration, audio-recorded, and professionally transcribed. Framework analysis was used to identify and organize emergent themes, and Atlas.ti was used to facilitate data management and analysis. Results Stakeholder groups diverged in their opinions regarding strategies for achieving adolescent quality measures. Stakeholders with no direct patient interaction touted transactional quality improvement strategies that directly incentivized patients and families. In contrast, clinic staff with direct patient contact believed that incentive-based efforts undermined patient-provider relationships and the clinics' focus on wellness. Conclusion A considerable disconnect exists between stakeholders with and without patient contact with regard to approaches to the delivery of well care and quality improvement strategies for meeting the adolescent well-care visit performance measure. Efforts to reconcile discordant perspectives and promote a mutual understanding between payers, institutional leaders, and clinic staff could inform the development of creative initiatives that are sustainable and effective at achieving adolescent and family engagement, as well as clinical performance benchmarks.

Persistent asthma requires a daily controller medication. National Heart, Lung, and Blood Institute (NHLBI) guidelines and Healthcare Effectiveness Data and Information Set (HEDIS) quality measures are used to identify persistent asthma, the former method used by clinicians, and the latter by managed care organizations (MCOs). This study aims to determine the degree of agreement between these criteria in classifying pediatric persistent asthma. Asthmatic patients aged 5-18 years old in a university pediatric practice who were continuously enrolled with one MCO from January 1, 2012 to December 31, 2013 (Cohort 1: 329 patients) and January 1, 2013 to December 31, 2014 (Cohort 2: 212 patients) were identified. Subjects with at least one asthma visit were included. Independence of NHLBI and HEDIS criteria was determined by the McNemar test. Agreement was determined by confusion matrix analysis and Cohen kappa statistic with continuity correction. Agreement in controller assignment was 82% in Cohort 1 and 88% in Cohort 2. Agreement was fair in Cohort 1 (Cohen kappa = 0.364; 95% confidence interval [CI] = 0.217-0.511) and moderate in Cohort 2 (Cohen kappa = 0.447; 95% CI = 0.247-0.646). The HEDIS misclassified persistent asthma by 16.4% (95% CI: 11.5-21.2%) and 11.8% (95% CI: 6.8-16.7%) in Cohorts 1 and 2, respectively. NHLBI and HEDIS criteria show fair to moderate agreement; however, the HEDIS consistently misclassified persistent asthma, suggesting that it is a poor measure of practice performance.

U.S. guidelines recommend that patients with severe asthma be referred to specialists (allergists/immunologists or pulmonologists) for systematic assessment or comanagement; however, contemporary, real-world data on the frequency and impact of specialist care among U.S. severe asthma patients are lacking.To quantify the frequency of asthma specialist visits among U.S. patients with severe asthma, identify patient demographic and clinical characteristics associated with specialist visits and describe health outcomes following specialist care.Severe asthma patients aged 6 years or older were identified between January 1, 2015, and December 31, 2017, in the IQVIA PharMetrics® Plus database of commercially insured individuals, based on Healthcare Effectiveness Data and Information Set (HEDIS) criteria and Global Initiative for Asthma (GINA) step 4 or 5 treatment regimens. The frequency of asthma specialist (allergist/immunologist or pulmonologist) visits was described over 2 years. Patient characteristics associated with having 1 or more specialist visits were analyzed using multivariate regressions. Asthma exacerbations and health care resource utilization before and after specialist visit were compared.Of 54,332 patients identified, 38.2% had 1 or more specialist visits over 2 years. Patient characteristics predictive of specialist visits were asthma exacerbation frequency, younger age, and allergy/respiratory comorbidity burden (all P.001). Among patients with 1 or more specialist visits, a lower prevalence of asthma exacerbations and rescue inhaler use was observed following the first observed specialist visit.Specialist care was observed in fewer than half of U.S. patients with severe asthma and was least frequent among older adult patients and those with more nonrespiratory comorbidities. Increased specialist involvement in managing severe asthma may help improve care and patient outcomes.

The gold-standard goal of diabetes management has been to achieve meaningful and sustained glycemic control to reduce the risk of long-term complications. Unfortunately, results from the National Health and Nutrition Examination Survey indicate that only ∼50% of adults with diabetes in the United States, mostly with type 2 diabetes, are achieving an A1C 9%, has actually increased (2,3). The Healthcare Effectiveness Data and Information Set results, with data from >1,000 health plans covering >171 million lives, are even more striking, demonstrating that, in 2014, ∼40% of commercially insured health maintenance organization patients and 30% of government insured patients achieved an A1C 40 new treatment options for people with type 2 diabetes. This fact is quite shocking and difficult to understand, especially given that our armamentarium of effective and safe type 2 medications has expanded over the same time period to include dipeptidyl peptidase 4 (DPP-4) inhibitors, sodium glucose cotransporter 2 inhibitors, designer insulins, inhaled insulin, and glucagon-like peptide 1 (GLP-1) receptor agonists. Although there may be many reasons why these new treatment options haven’t made a dent in the glycemic control of our patients with type 2 diabetes during these past 10 years, I feel strongly that the basic and primary issue is a lack of patient education, motivation, and activation. Type 2 diabetes is a silent condition with few or no symptoms caused by poor …

Background Alcohol use disorder (AUD) reduces the health of soldiers and the readiness of the Armed Forces. It remains unknown if engagement in substance use treatment in the Military Health System improves retention in the military. Methods The sample consisted of active duty soldiers returning from an Afghanistan/Iraq deployment in fiscal years 2008-2010 who received an AUD diagnosis within 150 days of completing a post-deployment health re-assessment survey (n = 4,726). A Heckman probit procedure was used to examine predictors of substance use treatment initiation and engagement in accordance with Healthcare Effectiveness Data and Information Set (HEDIS) criteria. Cox proportional hazard modeling was used to examine the association between treatment engagement and retention, defined as a negative separation for a non-routine cause (e.g., separation due to misconduct, poor performance, disability) from the military in the two years following the index AUD diagnosis. Results 40 % of soldiers meeting HEDIS AUD criteria initiated and 24 % engaged in substance use treatment. Among soldiers diagnosed with AUD, meeting criteria for treatment engagement was associated with a significantly higher hazard of having a negative separation compared to soldiers who did not engage in treatment. Conclusions Rates of initiation and engagement in substance use treatment for post-deployment AUD were relatively low. Soldiers with AUD who engaged in substance use treatment were more likely to have a negative separation from the military than soldiers with AUD who did not engage. Our findings imply that in the study cohort, treatment did not mitigate negative career consequences of AUD.

Despite U.S. Food and Drug Administration (FDA) approval of over 40 new treatment options for type 2 diabetes since 2005, the latest data from the National Health and Nutrition Examination Survey show that the proportion of patients achieving glycated hemoglobin (HbA1c)

Prior studies have shown higher screening mammography rates for beneficiaries in capitated managed care Medicare Advantage (MA) plans compared with traditional fee-for-service Medicare. The aim of this study was to explore variation in screening mammography rates at the level of MA managed care plans.Using the 2016 MA Healthcare Effectiveness Data and Information Set Public Use File, screening mammography rates were identified for all 385 reporting MA plans. Associations were explored with a range of plan characteristics from this file, as well as from the CMS Part C and Part D Medicare Star Ratings Data File, Medicare Advantage Plan Directory, and Medicare Monthly Enrollment by Plan File.Overall MA plan screening rates were high (mean, 72.6 ± 9.4%) but varied substantially among plans (range, 14.3%-91.8%). Screening rates were higher in nonprofit versus for-profit plans (77.3% versus 71.8%, P.001), as well as in health maintenance organization or local preferred provider organization plans versus private fee-for-service or regional preferred provider organization plans (71.9%-73.2% versus 65.5%-66.8%, P = .001). Among parent organizations with five or more plans, screening rates were highest for Kaiser Foundation (median, 88.4%) and lowest for Molina Healthcare (median, 65.3%). Screening rates showed small but significant associations with plans' contract lengths, enrolled populations, and counties served. Screening rates showed strong associations (r = 0.796-0.798) with colorectal cancer screening and annual flu vaccine rates and showed moderate associations (r = 0.283-0.365) with ambulatory and preventive care visits, osteoporosis screenings, body mass index assessments, and nonrecommended prostate-specific antigen screenings after age 70.Screening mammography rates vary considerably among MA plans. With increased federal interest in promoting the MA program, enhanced transparency will be necessary to ensure appropriate Medicare beneficiary participation decision making.

Purpose To increase the proportion of adolescents with Medicaid who receive preventive care services in an urban pediatric clinic. Methods A quality improvement intervention was implemented at an urban pediatric primary care clinic between November 2013 and October 2014. The intervention systematically "flipped" acute visits into well-care visits for patients ages 12–21 years, when overdue. The primary process measure was the percentage of acute visits expanded to include well-care components out of total eligible opportunities. The primary outcome measure was adolescent well-care (AWC) completion in 2014 versus 2013 and 2012. Results Among 857 adolescents with Medicaid, 124 additional AWC visits were completed by October 2014 compared to 2013 and 71 additional visits compared to 2012. The gap to achieving Healthcare Effectiveness Data and Information Set neutral zone targets for AWC was reduced by 59% compared to 2013 and by 54% compared to 2012. The mean proportion of eligible acute opportunities "flipped" monthly increased from 17% (range: 10%–21%) during the initial 3 months of implementation to 30% (range: 5%–50%) in the last 3 months. Conclusions Systematically flipping acute visits into well visits resulted in reaching Healthcare Effectiveness Data and Information Set quality targets for AWC, which had not previously been accomplished by this clinic. Incorporating staff and provider feedback strengthened intervention fidelity and buy-in despite time constraints in a busy, urban setting.

Background: To determine whether previously reported reductions in hypoglycemia associated with insulin glargine 300 U/mL (Gla-300) compared with insulin glargine 100 U/mL (Gla-100) are impacted by patient risk category in type 2 diabetes (T2D), clinical performance measures based on the Healthcare Effectiveness Data and Information Set (HEDIS) were applied to patient-level data from the EDITION 2 and EDITION 3 clinical trials that compared Gla-300 and Gla-100. Methods: In this post hoc analysis, patients were stratified as low risk (LR) if patients were

Evaluation and payment for health plans and providers have been increasingly tied to their performance on quality metrics, which can be influenced by patient- and community-level sociodemographic factors. The aim of this study was to examine whether performance on Healthcare Effectiveness Data and Information Set (HEDIS) measures varied as a function of community sociodemographic characteristics at the primary care clinic level. Twenty-two primary care sites of a large multispecialty group practice were studied during the period of April 2013 to June 2016. Significant associations were found between sites' performance on selected HEDIS measures and their neighborhood sociodemographic characteristics. Outcome measures had stronger associations with sociodemographic factors than did process measures, with a range of significant correlation coefficients (absolute value, regardless of sign) from 0.44 to 0.72. Sociodemographic factors accounted for as much as 25% to 50% of the observed variance in measures such as HbA1c or blood pressure control.

The Affordable Care Act requires the federal government to collect and report population data on race, ethnicity, and language needs to help reduce health and health care disparities. We assessed data availability in commercial, Medicaid, and Medicare managed care plans using the Healthcare Effectiveness Data and Information Set. Data availability varied but remained largely incomplete.

Objective Specialty addictions treatment can improve outcomes for patients with alcohol use disorders (AUD). Thus, initiation of and engagement with specialty addictions treatment are considered quality care for patients with AUD. Previous studies have demonstrated racial/ethnic differences in alcohol-related care but whether differences exist in initiation of and engagement with specialty addictions treatment among patients with clinically recognized alcohol use disorders is unknown. We investigated racial/ethnic variation in initiation of and engagement with specialty addictions treatment in a national sample of Black, Hispanic, and White patients with clinically recognized alcohol use disorders (AUD) from the US Veterans Health Administration (VA). Methods National VA data were extracted for all Black, Hispanic, and White patients with a diagnosed AUD during fiscal year 2012. Mixed effects regression models estimated the odds of two measures of initiation (an initial visit within 180 days of diagnosis; and initiation defined consistent with Healthcare Effectiveness Data and Information Set (HEDIS) as a documented visit ≤14 days after index visit or inpatient admission), and three established measures of treatment engagement (≥3 visits within first month after initiation; ≥2 visits in each of the first 3 months after initiation; and ≥2 visits within 30 days of HEDIS initiation) for Black and Hispanic relative to White patients after adjustment for facility- and patient-level characteristics. Results Among 302,406 patients with AUD, 30% (90,879) initiated treatment within 180 days of diagnosis (38% Black, 32% Hispanic, and 27% White). Black patients were more likely to initiate treatment than Whites for both measures of initiation [odds ratio (OR) for initiation: 1.4, 95% confidence interval (CI) 1.4–1.4; OR for HEDIS initiation: 1.1, 95% CI: 1.1–1.1]. Hispanic patients were more likely than White patients to initiate treatment within 180 days (OR: 1.2, 95% CI 1.2–1.3) but HEDIS initiation did not differ between Hispanic and White patients. Engagement results varied depending on the measure but was more likely for Black patients relative to White for all measures (OR for engagement in first month: 1.1, 95% CI: 1.0–1.1; OR for engagement in first three months: 1.2, 95% CI: 1.1–1.2; OR for HEDIS measure: 1.1, 95% CI: 1.0–1.1), and did not differ between Hispanic and White patients. Conclusions After accounting for facility- and patient-level characteristics, Black and Hispanic patients with AUD were more likely than Whites to initiate specialty addictions treatment, and Black patients were more likely than Whites to engage. Research is needed to understand underlying mechanisms and whether differences in initiation of and engagement with care influence health outcomes.

Purpose This paper describes the implementation of an innovative program that aims to improve postpartum care through a set of coordinated delivery and payment system changes designed to use postpartum care as an opportunity to impact the current and future health of vulnerable women and reduce disparities in health outcomes among minority women. Description A large health care system, a Medicaid managed care organization, and a multidisciplinary team of experts in obstetrics, health economics, and health disparities designed an intervention to improve postpartum care for women identified as high-risk. The program includes a social work/care management component and a payment system redesign with a cost-sharing arrangement between the health system and the Medicaid managed care plan to cover the cost of staff, clinician education, performance feedback, and clinic/clinician financial incentives. The goal is to enroll 510 high-risk postpartum mothers. Assessment The primary outcome of interest is a timely postpartum visit in accordance with NCQA healthcare effectiveness data and information set guidelines. Secondary outcomes include care process measures for women with specific high-risk conditions, emergency room visits, postpartum readmissions, depression screens, and health care costs. Conclusion Our evidence-based program focuses on an important area of maternal health, targets racial/ethnic disparities in postpartum care, utilizes an innovative payment reform strategy, and brings together insurers, researchers, clinicians, and policy experts to work together to foster health and wellness for postpartum women and reduce disparities.

Purpose The purpose of this paper is to assess the relationship between patient satisfaction and a variety of clinical quality measures in an ambulatory setting to determine if there is significant overlap between patient satisfaction and clinical quality or if they are separate domains of overall physician quality. Assessing this relationship will help to determine whether there is congruence between different types of clinical quality performance and patient satisfaction and therefore provide insight to appropriate financial structures for physicians. Design/methodology/approach Ordered probit regression analysis is conducted with overall rating of physician from patient satisfaction responses to the Clinician and Groups Consumer Assessment of Healthcare Providers and Systems survey as the dependent variable. Physician clinical quality is measured across five composite groups based on 26 Healthcare Effectiveness Data and Information Set (HEDIS) measures aggregated from patient electronic health records. Physician and patient demographic variables are also included in the model. Findings Better physician performance on HEDIS measures are correlated with increases in patient satisfaction for three composite measures: antibiotics, generics, and vaccination; it has no relationship for chronic conditions and is correlated with decrease in patient satisfaction for preventative measures, although the negative relationship for preventative measures is not robust in sensitivity analysis. In addition, younger physicians and male physicians have higher satisfaction scores even with the HEDIS quality measures in the regression. Research limitations/implications There are four primary limitations to this study. First, the data for the study come from a single hospital provider organization. Second, the survey response rate for the satisfaction measure is low. Third, the physician clinical quality measure is the percent of the physician’s relevant patient population that met the HEDIS measure rather than if the measure was met for the individual patient. Finally, it is not possible to distinguish if the significant coefficient estimates on the physician age and gender variables are capturing systematic differences in physician behavior or capturing patient bias. Practical implications The results suggest patient satisfaction and physician clinical quality may be complementary, capturing similar aspects of overall physician quality, across some clinical quality measures but for other measures satisfaction and clinical quality are unrelated or negatively related. Therefore, for some clinical quality metrics, it will be important to separately compensate clinical quality and satisfaction and understand the relationship between metrics. Finally, the strong relationship between the level of patient satisfaction and physician age, physician gender, and patient age are important to consider when designing a physician compensation package based on patient satisfaction; if these differences reflect patient bias they could increase inequality among medical staff if compensation is based on patient satisfaction. Originality/value This study is the first to use physician organization data to examine patient satisfaction and physician performance on a variety of HEDIS quality metrics.

Suboptimal treatment of exacerbations is a major concern in management of chronic obstructive pulmonary disease (COPD). The Pharmacotherapy Management of COPD Exacerbation (PCE) Healthcare Effectiveness Data and Information Set (HEDIS) measure is a quality measure included by the National Committee for Quality Assurance that focuses on appropriate use of steroids and bronchodilators during an acute COPD exacerbation. There is limited evidence evaluating predictors of this quality measure, as well as its association with hospital readmission and cost outcomes.To (a) describe characteristics of patients hospitalized for COPD, (b) evaluate factors associated with appropriate receipt of pharmacotherapy upon discharge, and (c) evaluate factors associated with the rate of readmission.In this retrospective, observational, event-based study of COPD-related hospital and ED visits, events were identified between 2007 and 2013 from a Central Texas health plan using administrative claims data. The index date was defined as the date of admission. Subjects were included if they were aged ≥ 40 years and had a medical claim with a primary diagnosis for COPD or a pharmacy claim for a COPD maintenance medication during the 1-year pre-index period. Study groups were identified based on the receipt of PCE within the time frame specified by HEDIS: (a) a systemic corticosteroid within 14 days of discharge (PCE-C) or (b) a bronchodilator within 30 days of discharge (PCE-D). Bivariate analyses of potential factors associated with the receipt of PCE were performed using t-tests for continuous data and chi-square tests for categorical data. Generalized estimating equations, including significant predictors from the bivariate analyses, were used to determine factors associated with receipt of PCE-C and/or PCE-D, as well association with COPD-related and all-cause readmission within 6 months of discharge.Of 375 identified index admissions, 254 (68%) patients received PCE-C; 299 (80%) received PCE-D; and 229 (61%) received both. Patients were more likely to receive PCE with an index inpatient visit as compared with an ED visit (PCE-C: RR = 2.25, 95% CI = 1.21-4.17, P = 0.010; PCE-D: RR = 1.90, 95% CI = 1.01-3.58, P = 0.048). Those with previous use of rescue medication were also more likely to receive PCE (PCE-C: RR = 1.88, 95% CI = 1.12-3.17, P = 0.018; PCE-D: RR = 2.11, 95% CI = 1.16-3.83, P = 0.014). Patients with greater adherence (proportion of days covered [PDC] ≥ 75%) to COPD maintenance medication before admission (RR = 8.67, 95% CI = 1.60-46.78, P = 0.012) were also more likely to receive PCE-D. Older patients were more likely to have a COPD-related readmission (RR = 1.07, 95% CI = 1.01-1.13, P = 0.028), while use of maintenance medication before admission was associated with lower risk of an all-cause readmission (RR = 0.49, 95% CI = 0.30-0.79, P = 0.004). In addition, patients with higher medical and pharmacy costs before the index event were more likely to have all-cause readmission (RR = 1.01, 95% CI = 1.00-1.02, P = 0.013). Receipt of PCE was not shown to be a significant predictor of all-cause or COPD-related readmission.The use of bronchodilators and systemic corticosteroids after a COPD-related inpatient or ED visit may be related to the severity of the index COPD exacerbation or patients' previous pattern of bronchodilator use. However, the use of maintenance medication before the index event was associated with a significant reduction in all-cause readmission, so proper treatment of the underlying disease may be an effective strategy in reducing readmission.Funding for this study was provided by GlaxoSmithKline (HO-14-15081). Tran was a Fellow at ScottWhite Health Plan (SWHP) during year 1 of this study and a Fellow at Novartis during year 2 of this study. Novartis did not have any input in this study nor did it contribute any funding or support for this research. Tran, Xiang, Godley, and Stock were employed by SWHP at the time of this study. Rascati is employed by the University of Texas at Austin and also by the Journal of Managed CareSpecialty Pharmacy and has received consulting fees from GlaxoSmithKline. Coleman, Bogart, and Stanford are GlaxoSmithKline employees and shareholders. Study design was created by Rascati, Tran, and Godley, with assistance from Stock, Coleman, Bogart, and Stanford. Tran and Xiang collected the data, with data analysis and interpretation performed by Stock and Rascati. The manuscript was written by Tran, Rascati, and Xiang and revised by Godley, Stock, Coleman, Bogart, and Stanford.

Incentive programmes are used in health systems worldwide to spur improvement in quality of care; these include both financial incentives (eg, pay for performance) and non-financial incentives (eg, public reporting). In the USA, the Centers for Medicare & Medicaid Services’ (CMS) Star Ratings quality incentive programme for private Medicare insurance plans, or Medicare Advantage plans, incorporates both non-financial and financial incentives. Star Ratings on a 1–5 scale are publicly reported on the Medicare Plan Finder website. Owing to provisions in the March 2010 Affordable Care Act and a demonstration programme, since 2012 Quality Bonus Payments of more than $3 billion annually have been paid directly to plans on the basis of the Star Ratings achieved the year before, which reflects care delivered to the plan’s enrollees 1–2 years prior.1 The Star Ratings incorporate measures from various sources (eg, Healthcare Effectiveness Data and Information Set (HEDIS), Consumer Assessment of Healthcare Providers and Systems (CAHPS), Health Outcomes Survey (HOS)). CMS has added and removed Star Ratings measures over time; removed measures are still monitored and published on cms.gov, but no longer contribute to bonus payments to plans and are not publicly reported to consumers on the Medicare Plan Finder website. Thus, both financial and non-financial incentives are removed when measures are removed from the Star Ratings methodology. Studies of pay-for-performance programmes in the UK and the USA in which incentives paid directly to healthcare providers or facilities were removed have shown mixed results as to whether performance was sustained or declined after removal of incentives.2–6 No prior study has assessed performance on measures removed from CMS’s Medicare Advantage Star Ratings incentive programme for insurance plans. As policymakers face pressure to reduce measurement burdens on providers, it is important to understand what happens to performance after measures are deincentivised. We performed an observational …