Mapping disparities in diabetic eye exam adherence using geographic information systems

Improving Medication Management of Depression in Health Plans

Few quality of care evaluations examine the relationship between clinical processes and patient outcomes. To determine the association between health plan performance on Healthcare Effectiveness Data and Information Set (HEDIS) clinical processes and intermediate outcome measures and Health Outcomes Survey (HOS) self-reported physical and mental health scores among Medicare plan enrollees with diabetes. Secondary data analysis of 2002 HEDIS and 2001-2003 HOS data. This study focused on Medicare plan enrollees with self-reported diabetes (N = 8184). Plan-level HEDIS diabetes care measures for 2002 and longitudinal, patient-level 2001-2003 HOS physical and mental health outcomes scores. Hierarchical linear models estimated the relationship between plan HEDIS performance on diabetes process of care and intermediate outcome measures and 2-year changes in enrollee HOS physical and mental health scores. Each 10% point improvement in plan performance on HEDIS intermediate outcomes (ie, the proportion of well-controlled diabetes) was related to significant positive increase in the probability of being healthy as measured by both enrollee physical health scores (7 percentage point increase, P < 0.05) and mental health scores (11 percentage point increase, P < 0.01). Similar increases in plan process of care measures were associated with increases in the probability of being healthy as measured by enrollee mental health scores (11 percentage point increase, P < 0.001). This study represents one of the first attempts to link plan HEDIS performance to changes in enrollee health. The results suggest that improved quality of care, as measured by process and intermediate outcomes measures for diabetes, can result in better health among patients with diabetes. Further research should address whether this relationship exists in other quality measures, clinical conditions, and populations.

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

There are a limited number of studies investigating the relationship between primary care physician (PCP) characteristics and the quality of care they deliver. To examine the association between PCP performance and physician age, solo versus group affiliation, training, and participation in California's Affordable Care Act (ACA) exchange. Observational study of 2013-2014 data from Healthcare Effectiveness Data and Information Set (HEDIS) measures and select physician characteristics. PCPs in California HMO and PPO practices (n = 5053) with part of their patient panel covered by a large commercial health insurance company. Hemoglobin A1c testing; medical attention nephropathy; appropriate treatment hypertension (ACE/ARB); breast cancer screening; proportion days covered by statins; monitoring ACE/ARBs; monitoring diuretics. A composite performance measure also was constructed. For the average 35- versus 75-year-old PCP, regression-adjusted mean composite relative performance scores were at the 60th versus 47th percentile (89% vs. 86% composite absolute HEDIS scores; p < .001). For group versus solo PCPs, scores were at the 55th versus 50th percentiles (88% vs. 87% composite absolute HEDIS scores; p < .001). The effect of age on performance was greater for group versus solo PCPs. There was no association between scores and participation in ACA exchanges. The associations between population-based care performance measures and PCP age, solo versus group affiliation, training, and participation in ACA exchanges, while statistically significant in some cases, were small. Understanding how to help older PCPs excel equally well in group practice compared with younger PCPs may be a fruitful avenue of future research.

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 <65 years old with no comorbidities derived from HEDIS (HbA1c target <7.0% [53 mmol/mol]), or as high risk (HR) if patients were either ≥65 years old or had one or more HEDIS-defined comorbidities (HbA1c target <8.0% [64 mmol/mol]). Primary endpoint was a composite of patients achieving HbA1c target without confirmed or severe hypoglycemia over 6 months in the different treatment groups in each of the EDITION trials.Results: There was a statistically nonsignificant trend of more patients treated with Gla-300 achieving the composite endpoint compared with Gla-100 in both the LR and HR patient cohorts, regardless of prior insulin experience. A similar trend was observed for the composite endpoint of HbA1c target without nocturnal hypoglycemia.Conclusions: There is a consistent, nonsignificant trend suggesting that Gla-300 might reduce the burden of hypoglycemia compared with Gla-100 in patients with T2D irrespective of whether they are classed as LR or HR based on age- and National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set-derived comorbidities.

In 2010, private and public sector health plans will be asked to add influenza immunization as a first-year measure for children in the Healthcare Effectiveness Data and Information Set (HEDIS) quality measure set for pediatric immunization practices, the National Committee for Quality Assurance (

BackgroundIn the USA, chlamydia screening of all sexually active women aged ≤25 years is recommended, but screening rates are low. The Healthcare Effectiveness Data and Information Set (HEDIS) performance measure...

The nationally reported Healthcare Effectiveness Data and Information Set (HEDIS) antidepressant medication management measure assesses whether patients with new episodes of depression receive antidepressant coverage for 84 of the first 114 days of treatment. Although initial prescriptions for a 90-day supply satisfy measure requirements, they may circumvent its purpose of ensuring adequate medication management. To assess the extent to which 90-day initial prescriptions have contributed to health system performance on the HEDIS antidepressant measure from fiscal years 2001 to 2008. Retrospective cohort analysis of Veterans Health Administration administrative data. Patients with a new diagnosis of depression and a new antidepressant prescription (N=383,634). HEDIS antidepressant measures, days supply of initial antidepressant prescriptions, antidepressant refills, and clinical encounters. Health system performance on the HEDIS acute phase antidepressant measure increased from 63.1% in 2001 to 71.0% in 2008. Receipt of an initial 90-day antidepressant supply increased from 10.5% to 29.1% during this same period; when these are excluded, HEDIS performance was 58.8% in 2001 and 59.4% in 2008. Receiving an initial 90-day prescription was associated with prior antidepressant treatment, fewer clinical encounters, and similar rates of antidepressant refills compared with patients prescribed less than 90-day supplies. Although increases in initial 90-day supplies contribute to improved performance on the HEDIS measure, actual adherence during the acute treatment phase may not be changed by this practice. Quality measures based on pharmacy fills may need modification in the setting of large initial prescriptions.

This paper explores the integration of healthcare data into commercial Healthcare Effectiveness Data and Information Set (HEDIS) systems, emphasizing its critical role in improving healthcare quality, transparency, and accountability. HEDIS, maintained by National Committee for Quality Assurance (NCQA), offers a standardized framework to measure health plan performance across various domains such as preventive care, chronic disease management, and mental health. The paper reviews the structure and importance of HEDIS, evaluates commercial systems like Cozeva, Epic, TriZetto, and Waystar, and compares their capabilities in quality reporting, analytics, and interoperability. It delves into data integration challenges—including standardization, interoperability, data quality, and security—and presents technical solutions such as data warehousing, API use, ETL pipelines, and master data management. The study highlights the necessity of strong data governance, secure data exchange, and adherence to regulatory compliance like HIPAA. Additionally, it explores the transformative potential of emerging technologies like AI, machine learning, and predictive analytics in enhancing HEDIS reporting accuracy and efficiency. The paper concludes by presenting a practical roadmap for successful data integration into HEDIS systems, advocating for strategic planning, robust infrastructure, and innovative tools to enable data-driven decision-making and improved healthcare outcomes.

PND3 HEALTH OUTCOMES ASSOCIATED WITH ADHERENCE TO HEALTHCARE EFFECTIVENESS DATA AND INFORMATION SET (HEDIS) ANTIDEPRESSANT MEDICATION MANAGEMENT MEASURES DURING ACUTE AND CONTINUATION PHASES OF DEPRESSION TREATMENT AMONG OLDER ADULTS WITH DEMENTIA AND MAJOR DEPRESSIVE DISORDER

BackgroundThere 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).MethodsWe 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.ResultsData 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).ConclusionsThe 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.

Medicare Advantage special needs plans (SNPs) have grown significantly over the past 7 years, but patient outcomes have only recently been publicly reported. Reporting rates and scores on 4 publicly reported Healthcare Effectiveness Data and Information Set (HEDIS) measures of 697 SNPs in 2008 are examined, as are SNP characteristics associated with reporting HEDIS scores. SNP participation increased from 11 plans serving 12,774 beneficiaries in 2004 to 762 plans serving 1,323,132 beneficiaries in December 2008, and then dropped to 455 plans serving 1,293,579 beneficiaries in February 2011. Fifty-eight percent of the 697 SNPs were dual-eligible SNPs, 30% were chronic SNPs, and 12% were institutional SNPs. The total number of SNPs and total SNP enrollment was concentrated in 9 states and Puerto Rico, representing 59.4% of all SNPs and 75% of all SNP enrollments. Seventeen percent of SNPs reported all 4 HEDIS measures in 2008, but 60% were not required to report HEDIS measures. Among SNPs reporting scores, 42% of enrollees received colorectal cancer screening, 86% received appropriate monitoring of long-term medications, 55% had blood pressure control, and 56% of physicians were board certified. These early HEDIS reporting and performance results raise questions about whether SNPs add value above traditional Medicare Advantage plans. New HEDIS measures and new regulatory requirements have the potential to improve SNP care practices, and are likely to improve our understanding of SNP outcomes most relevant to enrollees.

Civilian injuries caused during contact with law enforcement personnel erode community trust in policing, impact individual well-being, and exacerbate existing health inequities. We assessed the relationship between ZIP code-level rates of civilian injuries caused during legal interventions and community-level sociodemographic characteristics using Illinois hospital data from 2016 to 2022. We developed multivariable Poisson regression models to examine whether legal intervention injury rates differed by race-ethnicity and community economic disadvantage across three geographic regions of Illinois representing different levels of urbanization. Over the study period, 4976 civilian injuries were treated in Illinois hospitals (rate of 5.6 per 100,000 residents). Compared to non-Hispanic white residents, non-Hispanic Black residents demonstrated 5.5-10.5 times higher injury rates across the three geographic regions, and Hispanic-Latino residents demonstrated higher rates in Chicago and suburban Cook County, but lower rates in the rest of the state. In most regions, models showed that as the percent of minority residents in a ZIP code increased, injury rates among non-Hispanic Black and Hispanic-Latino residents decreased. As community economic disadvantage increased at the ZIP code level, civilian injury rates increased. Communities with the highest injury rates involving non-Hispanic white residents were significantly more economically unequal and disadvantaged. While the injury rates were consistently and substantially higher among non-Hispanic Black residents throughout the state, the findings illustrate that the association between overall civilian injuries caused during contact with law enforcement and community sociodemographic characteristics varied across regions. Data on local law enforcement agency policies and procedures are needed to better identify appropriate interventions.

Background: The Stroke Encounter Quality Improvement Project (SEQIP) is a collaboration between certified stroke centers, the AHA/ASA and the Kentucky Department for Public Health (KDPH) to implement statewide QI initiatives to improve the care of stroke patients. From 2009 to 2018, 23 hospital in Kentucky participating in SEQIP have entered 76,222 stroke patient records into Get With The Guidelines® (GWTG) / Patient Management Tool™ (PMT). Purpose: Geographic information systems (GIS) tools can expand our understanding of care and outcomes based on patient location. The purpose of this project was to demonstrate the methods of linking a disease management registry with GIS mapping and analysis program,) to understand challenges when performing this link, and to derive meaningful insight on stroke care and outcomes by zip code. Methods: Stroke data from GWTG and PMT was compiled and downloaded by KDPH. The information was converted to a database file for use in ArcGIS. After excluding those who had missing or incomplete zip codes, records were Geocoded annually from 2009 to 2018. The data were then matched to one of 945 zip codes in Kentucky. Data were summarized by zip code, calendar year by the number of ischemic strokes; number IV alteplase administration; rate ischemic stroke receiving IV alteplase; number and rate of ischemic stroke patients arriving to hospital by EMS, privately owned vehicle or transfer; and median time from last known well to hospital arrival; and medical history of hypertension. Additional data including hospitals, certified stroke centers, drive time analysis, etc. were added to maps. Results: Mapping GWTG and PMT stroke data is feasible and may allow for additional analysis by location. Conclusion: Using GIS mapping and methodology can assist hospital stroke coordinators and public health officials in developing and implementing interventions to improvement stroke care and outcomes. Further analysis including socioeconomic, demographic and marketing/consumer preference data is planned to better understand variations by zip codes. This feasibility project provides an example of a useful application of GIS analyses applied to data registry including GWTG and PMT.

Background: Adolescents with substance use disorders (SUD) should receive timely access to treatment to improve lifelong outcomes. The Healthcare Effectiveness Data and Information Set (HEDIS) initiation and engagement in treatment (IET) performance measure was intended to promote quality improvement for patients with SUD. Yet, few studies have assessed predictors of measure performance among adolescents or other engagement in mental health services, which is critical to understanding disparities in treatment quality or opportunities for targeted improvement strategies. The present study reports the rates and predictors of IET among adolescents with SUD, as well as receipt of any mental health services. Methods: The sample included adolescents enrolled in Medicaid in 14 states who had a qualifying diagnosis for SUD (2009–2013) and met HEDIS IET performance measure eligibility criteria. Three outcomes were assessed, including initiation of SUD treatment within 14 days of qualifying diagnosis, engagement in SUD treatment (2 or more encounters) within 30 days of initiation, and receipt of any mental health services (1 or more encounters) within 30 days of initiation. Logistic regression was used to identify demographic and clinical characteristics associated with outcomes. Results: Among 20,602 adolescents who met eligibility criteria, 49.5% initiated SUD treatment, 48.5% engaged in SUD treatment, and 70% received any mental health service. Adolescents with higher levels of clinical need (e.g., medical complexity, mental health comorbidity, and multiple SUD diagnoses) had significantly higher odds of initiating, but lower odds of engaging in treatment or receiving any mental health service. Conclusions: To increase the delivery of SUD treatment, efforts should target adolescents with co-occurring mental health needs, many of whom are receiving mental health services after SUD diagnosis. Integrating addiction and mental health services could address these missed opportunities.