Variation in incidence rates of outcomes relevant to vaccine safety monitoring in a US commercially insured population by case identification algorithm.

BACKGROUND: Large health insurance claims databases can be used to estimate rates of rare safety outcomes. We measured incidence rates of rare outcomes that could be used to contextualize adverse events among people receiving pneumococcal vaccines in clinical trials or clinical practice. However, algorithms used to identify outcomes in administrative databases are subject to error. Using two algorithms for each outcome, we assessed the influence of algorithm choice on the rates of the outcomes. METHODS: We used closed administrative medical and pharmacy claims in the Healthcare Integrated Research DatabaseSM (HIRD) to construct a broad cohort of individuals less than 100 years old (i.e., the target cohort) and a trial-similar cohort of individuals resembling those potentially eligible for a vaccine clinical trial (e.g., for a pneumococcal vaccine). We stratified by age and sex and used specific and sensitive algorithms to estimate rates of 39 outcomes including cardiac/cerebrovascular, metabolic, allergic/autoimmune, neurological, and hematologic outcomes. Specific algorithms intended to reduce false positive errors, while sensitive algorithms intended to reduce false negative errors, thereby providing lower and upper bounds for the "true" rates. RESULTS: We followed approximately 40 million individuals in the target cohort for an average of 3 years. Of 39 outcomes, 14 (36 %) had a rate from the specific algorithm that was less than half the rate from the sensitive algorithm. Rates of cardiac/cerebrovascular outcomes were most consistent (mean ratio of rates from specific algorithms compared to rates from sensitive algorithms = 0.76), while the rates of neurological and hematologic outcomes were the least consistent (mean ratio of rates = 0.33 and 0.36, respectively). CONCLUSIONS: For many cardiac/cerebrovascular outcomes, rates were similar regardless of the algorithm. For other outcomes, rates varied substantially by algorithm. Using multiple algorithms to ascertain outcomes in claims data can be informative about the extent of uncertainty due to outcome misclassification.

Descriptive study of the economic burden among patients with type 2 diabetes mellitus, chronic kidney disease, and chronic kidney disease and type 2 diabetes mellitus in a large US commercially insured population.

BACKGROUND: Chronic kidney disease (CKD) is a major public health concern that affects 37 million adults in the United States. It is well known that CKD presents a large economic burden, especially in the Medicare population. However, studies of the economic burden of CKD in younger populations are scarce. In particular, there is a gap in understanding how the presence of type 2 diabetes mellitus (T2DM) affects the burden of CKD in commercially insured populations. OBJECTIVE: To describe the economic and health care resource utilization (HCRU) burden of CKD within 3 patient groups (T2DM only, CKD only, and CKD and T2DM) aged 45-64 years overall and by Kidney Disease Improving Global Outcomes (KDIGO) CKD estimated glomerular filtration rate-based stage categories. METHODS: A descriptive, observational retrospective cohort study was conducted using administrative medical and pharmacy claims integrated with laboratory results data available in the HealthCore Integrated Research Database from January 1, 2017, to December 31, 2019. Three mutually exclusive groups of commercially insured patients aged 45-64 years were identified: T2DM only, CKD only, and CKD and T2DM. All-cause and disease-specific HCRU and costs in total, by medical and pharmacy benefits and across all places of service, were described for each of these groups 12 months after index date. For the CKD only and CKD and T2DM groups, costs were also described by KDIGO CKD stage. RESULTS: The CKD and T2DM group (n = 13,052) had numerically higher 12-month post-index all-cause and CKD/T2DM-related HCRU across all places of service. Mean 12-month all-cause costs for this group were $35,649, whereas costs for the CKD only group (n = 7,876) were $25,010 and costs for the T2DM only group (n = 120,364) were $16,121. Costs also tended to increase as CKD stage increased, with the greatest increases beginning at KDIGO stage 3b and higher. Mean 12-month all-cause costs for the CKD and T2DM group ranged from $29,993 to $41,222 for stages 1 to 3a and from $46,796 to $119,944 for stages 3b to 5. CONCLUSIONS: Commercially insured patients aged 45-64 years with CKD, especially those who also have T2DM, present a substantial burden in terms of elevated HCRU and costs. Costs tend to increase across KDIGO CKD stages and increase most rapidly at stage 3b and later. Therefore, there is an opportunity to reduce the burden of CKD in this population by investing in interventions to prevent or delay CKD disease progression. DISCLOSURES: HealthCore, Inc, received funding to perform this research, as well as funding from multiple pharmaceutical companies to perform various research studies outside of the submitted work. Mr Crowe and Dr Willey are employees of HealthCore, Inc., a wholly owned subsidiary of Elevance Health, Inc. Ms Chung was an employee of HealthCore, Inc., a wholly owned subsidiary of Elevance Health, Inc, at the time of study performance. Ms Chung and Dr Willey are shareholders of Elevance Health, Inc. Dr Kong, Dr Singh, Mr Farej, Dr Elliot, and Dr Williamson are employees of Bayer US, LLC. Dr Singh is a shareholder of Bayer US, LLC.

Cost-Effectiveness of a Proteomic Test for Preterm Birth Prediction.

BACKGROUND: Preterm birth (PTB) carries increased risk of short- and long-term health problems as well as higher healthcare costs. Current strategies using clinically accepted maternal risk factors (prior PTB, short cervix) can only identify a minority of singleton PTBs. OBJECTIVE: We modeled the cost-effectiveness of a risk-screening-and-treat strategy versus usual care for commercially insured pregnant US women without clinically accepted PTB risk factors. The risk-screening-and-treat strategy included use of a novel PTB prognostic blood test (PreTRM®) in the 19th-20th week of pregnancy, followed by treatment with a combined regimen of multi-component high-intensity-case-management and pharmacologic interventions for the remainder of the pregnancy for women assessed as higher-risk by the test, and usual care in women without higher risk. METHODS: We built a cost-effectiveness model using a combined decision-tree/Markov approach and a US payer perspective. We modeled 1-week cycles of pregnancy from week 19 to birth (preterm or term) and assessed costs throughout the pregnancy, and further to 12-months post-delivery in mothers and 30-months in infants. PTB rates and costs were based on >40,000 mothers and infants from the HealthCore Integrated Research Database® with birth events in 2016. Estimates of test performance, treatment effectiveness, and other model inputs were derived from published literature. RESULTS: In the base case, the risk-screening-and-treat strategy dominated usual care with an estimated 870 fewer PTBs (20% reduction) and $54 million less in total cost ($863 net savings per pregnant woman). Reductions were projected for neonatal intensive care admissions (10%), overall length-of-stay (7%), and births <32 weeks (33%). Treatment effectiveness had the strongest influence on cost-effectiveness estimates. The risk-screening-and-treat strategy remained dominant in the majority of probabilistic sensitivity analysis simulations and model scenarios. CONCLUSION: Use of a novel prognostic test during pregnancy to identify women at risk of PTB combined with evidence-based treatment is estimated to reduce total costs while preventing PTBs and their consequences.

Rate of preventative vaccine use and vaccine beliefs among a commercially insured population.

Immunization is an important component of preventive healthcare services. By recognizing and understanding factors associated with suboptimal vaccination compliance, healthcare providers can better approach at-risk populations and target efforts at reinforcing the vital importance of immunizations. The objective of this study was to understand the factors associated with adherence, beliefs and behaviors of influenza, pneumococcal, and herpes zoster vaccines receipt among commercially insured adults. A cross-sectional survey of patients with medical and pharmacy benefits for a 24-month period between August 1, 2014 and July 31, 2016 who were eligible to receive at least one of three adult vaccines (influenza, pneumococcal, and herpes zoster) was completed. Patients were identified as eligible to receive a vaccine based on current guidelines from the CDC ACIP. Health plan members were identified from administrative claims data in the HealthCore Integrated Research DatabaseSM (HIRD). Among the participants, 11% were eligible and up-to-date on all three vaccines; 52% on some and 37% were not up-to-date on any of the three vaccines. Participants with a healthcare provider were more likely to be up-to-date on eligible vaccines: 79.9% for none, 91.3% for some, and 97.8% for all eligible vaccines. The composite Vaccine Myth Belief score was significantly associated with being up to date on eligible vaccines: 45.0%/12.8% for none, 12/5%/30.8% for some, and 8.9%/33.3% for those up-to-date on all eligible vaccines. Despite numerous interventions designed to increase vaccination rates among adults, compliance remains suboptimal. It is evident that patient and provider education is necessary to fill knowledge gaps and misunderstandings; however knowledge by itself is not sufficient to improve immunization practices. Our results highlight a population that could benefit from a multidisciplinary approach, including interventions at the individual and health system levels.

Health Plan Enrollment and Disenrollment of Individuals With and Without Established Chronic Disease in a U.S. Commercially Insured and Medicare Advantage Population.

BACKGROUND: Chronic disease is associated with increased health care resource utilization and costs. Effective development and implementation of health care management and clinical intervention programs require an understanding of health plan member enrollment and disenrollment behavior. OBJECTIVE: To examine the health plan enrollment and disenrollment behavior of commercially insured and Medicare Advantage members with established chronic disease compared with matched members without the disease of interest, using data from a large national health insurer in the United States. METHODS: This retrospective matched cohort study used administrative claims data from the HealthCore Integrated Research Database from January 1, 2006, to November 30, 2015, to identify adults with chronic disease (type 2 diabetes mellitus [T2DM], cardiovascular disease [CVD], chronic obstructive pulmonary disease [COPD], rheumatoid arthritis [RA], and breast cancer [BC]). Members with no established chronic disease (controls) were directly matched to members with established chronic disease (cases) on demographic characteristics. The earliest date on which members met the criteria for a given disease was defined as the index date. Controls had the same index date as the matched cases. All members had ≥ 12 months of continuous health plan enrollment before the index date. Outcomes included health plan member disenrollment and enrollment duration. Incidence rates per 1,000 member-years for member disenrollment were evaluated along with incidence rate ratios (relative risk) using a Poisson model. Time to disenrollment was analyzed by Cox proportional hazard models and Kaplan-Meier survival curves. Sensitivity analyses were conducted where death was included as a disenrollment event. RESULTS: 70,907 health plan members with BC (99.7% female, mean age 60.5 years); 28,883 members with COPD (52.3% female, mean age 66.7); 835,358 members with CVD (50.5% female, mean age 62.7 years); 210,936 members with T2DM (45.2% female, mean age 53.6 years); and 31,954 members with RA (72.0% female, mean age 55.5 years) were matched to controls and met the study criteria. The incidence rates of health plan disenrollment ranged from 155 to 192 members per 1,000 members per year. Compared with controls, members with chronic disease were 30%-40% less likely to disenroll from a health plan (P < 0.001 for all comparisons). Among those who disenrolled, enrollment duration ranged from 2.3 to 2.7 years among cases and 1.5 to 1.8 years among matched controls (P ≤ 0.001 for all comparisons). CONCLUSIONS: This real-world study demonstrated that members with chronic disease had a significantly lower rate of disenrollment and a longer duration of enrollment compared with matched controls and were continuously enrolled for almost a year longer than members without a diagnosed chronic disease. Understanding health plan enrollment and disenrollment behavior may provide a valuable context for determining the time frame for the effect of health care programs and initiatives. DISCLOSURES: Funding for this study was provided by HealthCore, a wholly owned subsidiary of Anthem. Chung, Deshpande, Zolotarjova, Quimbo, and Willey are employees of HealthCore. Kern and Cochetti are former employees of HealthCore. Quimbo, Cochetti, and Willey are shareholders of Anthem. HealthCore receives funding from multiple pharmaceutical companies to perform various research studies outside of the submitted work. The preliminary results of this study were presented at AMCP Nexus 2015; March 26-29, 2015; Orlando, FL, and the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 2017 Conference; May 20-24, 2017; Boston, MA.

Administrative claims data to support pragmatic clinical trial outcome ascertainment on cardiovascular health.

BACKGROUND/AIMS: Health plan administrative claims data present a cost-effective complement to traditional trial-specific ascertainment of clinical events typically conducted through patient report or a single health system electronic health record. We aim to demonstrate the value of health plan claims data in improving the capture of endpoints in longitudinal pragmatic clinical trials. METHODS: This retrospective cohort study paralleled the design of the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) trial designed to compare the effectiveness of two doses of aspirin. We applied the ADAPTABLE identification query in claims data from Anthem, an American health insurance company, and identified health plan members who met the ADAPTABLE trial criteria. Among the ADAPTABLE eligible members, we selected overlapping members with PCORnet Clinical Data Research Networks in the 2 years prior to the index date (1 April 2014). PCORnet Clinical Data Research Networks consist of network partners (or healthcare systems) that store their electronic health record data in the same format to support multi-institutional research. ADAPTABLE outcome events-cardiovascular hospitalizations including admissions for myocardial infarction, stroke, or cardiac procedures; hospitalizations for major bleeding; and in-hospital deaths-were evaluated for a 2-year follow-up period. Events were classified as within or outside PCORnet Clinical Data Research Networks using facility identifiers affiliated with each hospital stay. Patient characteristics were examined with descriptive statistics, and incidence rates were reported for available Clinical Data Research Networks and claims data. RESULTS: Among 884,311 ADAPTABLE eligible health plan members, 11,101 patients overlapped with PCORnet Clinical Data Research Networks. Average age was 70 years, 71% were male, and average follow-up was 20.7 months. Patients had 1521 cardiovascular hospitalizations (571 (37.5%) occurred outside PCORnet Clinical Data Research Networks), 710 for major bleeding (296 (41.7%) outside PCORnet Clinical Data Research Networks), and 196 in-hospital deaths (67 (34.2%) outside PCORnet Clinical Data Research Networks). Incidence rates (events per1000 patient-months) differed between available network partners and claims data: cardiovascular hospitalizations, 4.1 (95% confidence interval: 3.9, 4.4) versus 6.6 (95% confidence interval: 6.3, 7.0), major bleeding, 1.8 (95% confidence interval: 1.6, 2.0) versus 3.1 (95% confidence interval: 2.9, 3.3), and in-hospital death, 0.56 (95% confidence interval: 0.47, 0.67) versus 0.85 (95% confidence interval: 0.74, 0.98), respectively. CONCLUSION: This study demonstrated the value of supplementing longitudinal site-based clinical studies with administrative claims data. Our results suggest that claims data together with network partner electronic health record data constitute an effective vehicle to capture patient outcomes since >30% of patients have non-fatal and fatal events outside of enrolling sites.

The role of pharmacoeconomics in current Indian healthcare system.

Phamacoeconomics can aid the policy makers and the healthcare providers in decision making in evaluating the affordability of and access to rational drug use. Efficiency is a key concept of pharmacoeconomics, and various strategies are suggested for buying the greatest amount of benefits for a given resource use. Phamacoeconomic evaluation techniques such as cost minimization analysis, cost effectiveness analysis, cost benefit analysis, and cost utilization analysis, which support identification and quantification of cost of drugs, are conducted in a similar way, but vary in measurement of value of health benefits and outcomes. This article provides a brief overview about pharmacoeconomics, its utility with respect to the Indian pharmaceutical industry, and the expanding insurance system in India. Pharmacoeconomic evidences can be utilized to support decisions on licensing, pricing, reimbursement, and maintenance of formulary procedure of pharmaceuticals. For the insurance companies to give better facility at minimum cost, India must develop the platform for pharmacoeconomics with a validating methodology and appropriate training. The role of clinical pharmacists including PharmD graduates are expected to be more beneficial than the conventional pharmacists, as they will be able to apply the principles of economics in daily basis practice in community and hospital pharmacy.