Association of co-pay elimination with medication adherence and total cost.

OBJECTIVES: To determine whether elimination of co-pays for prescription drugs affects medication adherence and total health care spending. STUDY DESIGN: Retrospective comparative study. METHODS: We conducted a difference-in-differences comparison in the year before and after expansion of a Zero Dollar Co-pay (ZDC) prescription drug benefit in commercially insured Louisiana residents. Blue Cross and Blue Shield of Louisiana members with continuous disease management program enrollment were analyzed, of whom 6463 were enrolled in the ZDC program and 1821 were controls who were ineligible because their employers did not opt in. RESULTS: After ZDC expansion, medication adherence fell in the control group and rose in the ZDC group, with a relative increase of 2.1 percentage points (P = .002). Medical spending fell by $71 per member per month (PMPM) (P = .027) in the ZDC group relative to controls. Overall, there was no significant increase in the cost of drugs between treatment and controls. However, when drugs were further categorized, there was a significant increase of $8 PMPM for generic drugs and no significant difference for brand name drugs. Comparisons of medication adherence rates by household income showed the largest relative increase post ZDC expansion among low-income members. CONCLUSIONS: Elimination of co-pays for drugs indicated to treat chronic illnesses was associated with increases in medication adherence and reductions in overall spending of $63. Benefit designs that eliminate co-pays for patients with chronic illnesses may improve adherence and reduce the total cost of care.

Delayed emergencies: The composition and magnitude of non-respiratory emergency department visits during the COVID-19 pandemic.

IMPORTANCE: COVID-19 has been associated with excess mortality among patients not diagnosed with COVID-19, suggesting disruption of acute health care provision may play a role. OBJECTIVE: To determine the degree of declines in emergency department (ED) visits attributable to COVID-19 and determine whether these declines were concentrated among patients with fewer comorbidities and lower severity visits. DESIGN: We conducted a differences-in-differences analysis of all commercial health insurance claims for ED visits in the first 20 weeks of 2018, 2019, and 2020. The intervention period began March 9 (week 11) of 2020, following state stay-at-home orders. SETTING: We analyzed claims from Blue Cross Blue Shield of Louisiana (BCBSLA), located in a state with an early US COVID-19 outbreak. Visit and patient risk was assessed through comorbidities previously described as increasing the risk of COVID-19 decompensation, the hospital location's COVID-19 outbreak status, and the Ambulatory Care Sensitive Condition algorithm. PARTICIPANTS: The study population comprised all ED visits from all BCBSLA members, whether admitted or discharged. There were 332,917 ED visits over the study period. The study population spanned member demographics including sex, age, and geography. Uninsured adults were not included due to data limitations. EXPOSURES: The COVID-19 outbreak beginning March 9, 2020 in Louisiana. MAIN OUTCOMES AND MEASURES: The main outcome of interest for this analysis is the difference (percent change) in all ED visits, categorized as either respiratory or non-respiratory, from week 1-20 in 2019 and week 1-10 in 2020, compared to week 11-20 in 2020. RESULTS: In this differences-in-differences study using data from a commercial health insurer, we found that non-respiratory ED visits declined by 39%, whereas respiratory visits did not experience a significant decline. Visits that were potentially deferrable or from lower risk patient populations showed greater declines, but even high-risk patients and non-avoidable visits experienced large declines in non-respiratory ED visits. Non-respiratory ED visits declined by only 18% in areas experiencing COVID outbreak. CONCLUSIONS AND RELEVANCE: COVID-19 has resulted in significant avoidance of ED care, comprising a mix of deferrable and high severity care. Hospital and public health pronouncements should emphasize appropriate care seeking.

Value-based insurance design in Louisiana: Blue Cross Blue Shield's Zero Dollar Co-pay program.

OBJECTIVES: To determine whether a program that eliminated pharmacy co-pays, the Blue Cross Blue Shield of Louisiana (BCBSLA) Zero Dollar Co-pay (ZDC) program, decreased health care spending. Previous studies have found that value-based insurance designs like the ZDC program have little or no impact on total health care spending. ZDC included an expansive set of medications related to 4 chronic diseases rather than a limited set of medications for 1 or 2 chronic diseases. Additionally, ZDC focused on the most at-risk patients. STUDY DESIGN: ZDC began in 2014 and enrolled patients over time based on (1) when a patient answered a call from a nurse care manager and (2) when a patient or their employer changed the benefit structure to meet the program criteria. During 2015 and 2016, 265 patients with at least 1 chronic condition (asthma, diabetes, hypertension, mental illness) enrolled in ZDC. METHODS: Observational study using within-patient variation and variation in patient enrollment month to identify the impact of the ZDC program on health spending measures. We used 100% BCBSLA claims data from January 2015 to June 2018. Monthly level event studies were used to test for differential spending patterns prior to ZDC enrollment. RESULTS: We found that total spending decreased by $205.9 (P = .049) per member per month, or approximately 18%. We saw a decrease in medical spending ($195.0; P = .023) but did not detect a change in pharmacy spending ($7.59; P = .752). We found no evidence of changes in spending patterns prior to ZDC enrollment. CONCLUSIONS: The ZDC program provides evidence that value-based insurance designs that incorporate a comprehensive set of medications and focus on populations with chronic disease can reduce spending.

Prevalence of obesity, type II diabetes mellitus, hyperlipidemia, and hypertension in the United States: findings from the GE Centricity Electronic Medical Record database.

This study analyzed GE Centricity Electronic Medical Record (EMR) data to examine the effects of body mass index (BMI) and obesity, key risk factor components of metabolic syndrome, on the prevalence of 3 chronic diseases: type II diabetes mellitus, hyperlipidemia, and hypertension. These chronic diseases occur with high prevalence and impose high disease burdens. The rationale for using Centricity EMR data is 2-fold. First, EMRs may be a good source of BMI/obesity data, which are often underreported in surveys and administrative databases. Second, EMRs provide an ideal means to track variables over time and, thus, allow longitudinal analyses of relationships between risk factors and disease prevalence and progression. Analysis of Centricity EMR data showed associations of age, sex, race/ethnicity, and BMI with diagnosed prevalence of the 3 conditions. Results include uniform direct correlations between age and BMI and prevalence of each disease; uniformly greater disease prevalence for males than females; varying differences by race/ethnicity (ie, African Americans have the highest prevalence of diagnosed type II diabetes and hypertension, while whites have the highest prevalence of diagnosed hypertension); and adverse effects of comorbidities. The direct associations between BMI and disease prevalence are consistent for males and females and across all racial/ethnic groups. The results reported herein contribute to the growing literature about the adverse effects of obesity on chronic disease prevalence and about the potential value of EMR data to elucidate trends in disease prevalence and facilitate longitudinal analyses.

Comparison of GE Centricity Electronic Medical Record database and National Ambulatory Medical Care Survey findings on the prevalence of major conditions in the United States.

The study objective was to facilitate investigations by assessing the external validity and generalizability of the Centricity Electronic Medical Record (EMR) database and analytical results to the US population using the National Ambulatory Medical Care Survey (NAMCS) data and results as an appropriate validation resource. Demographic and diagnostic data from the NAMCS were compared to similar data from the Centricity EMR database, and the impact of the different methods of data collection was analyzed. Compared to NAMCS survey data on visits, Centricity EMR data shows higher proportions of visits by younger patients and by females. Other comparisons suggest more acute visits in Centricity and more chronic visits in NAMCS. The key finding from the Centricity EMR is more visits for the 13 chronic conditions highlighted in the NAMCS survey, with virtually all comparisons showing higher proportions in Centricity. Although data and results from Centricity and NAMCS are not perfectly comparable, once techniques are employed to deal with limitations, Centricity data appear more sensitive in capturing diagnoses, especially chronic diagnoses. Likely explanations include differences in data collection using the EMR versus the survey, particularly more comprehensive medical documentation requirements for the Centricity EMR and its inclusion of laboratory results and medication data collected over time, compared to the survey, which focused on the primary reason for that visit. It is likely that Centricity data reflect medical problems more accurately and provide a more accurate estimate of the distribution of diagnoses in ambulatory visits in the United States. Further research should address potential methodological approaches to maximize the validity and utility of EMR databases.