Evaluation of claims data from a commercial value-based insurance product shows pediatric imaging is not a major driver of overall or pediatric healthcare expenditures.

BACKGROUND: Initiatives to reduce healthcare expenditures often focus on imaging, suggesting that imaging is a major driver of cost. OBJECTIVE: To evaluate medical expenditures and determine if imaging was a major driver in pediatric as compared to adult populations. METHODS: We reviewed all claims data for members in a value-based contract between a commercial insurer and a healthcare system for calendar years 2021 and 2022. For both pediatric (<18 years of age) and adult populations, we analyzed average per member per year (PMPY) medical expenditures related to imaging as well as other categories of large medical expenses. Average PMPY expenditures were compared between adult and pediatric patients. RESULTS: Children made up approximately 20% of members and 21% of member months but only 8-9% of expenditures. Imaging expenditures in pediatric members were 0.2% of the total healthcare spend and 2.9% of total pediatric expenditures. Imaging expenditures per member were seven times greater in adults than children. The rank order of imaging expenditures and imaging modalities was also different in pediatric as compared to adult members. CONCLUSION: Evaluation of claims data from a commercial value-based insurance product shows that pediatric imaging is not a major driver of overall, nor pediatric only, healthcare expenditures.

Screening for Melanoma in Men: a Cost-Effectiveness Analysis.

BACKGROUND: Systematic screening skin examination has been proposed to reduce melanoma-related mortality. OBJECTIVE: To assess the potential effectiveness of screening, in a demographic at high risk of melanoma mortality. DESIGN: A cohort Markov state-transition model was developed comparing systematic screening versus usual care (no systematic screening). In the base case, we evaluated a sensitivity and specificity of 20% and 85%, respectively, for usual care (incidental detection) and 50% sensitivity and 85% specificity from systematic screening. We examined a wide range of values in sensitivity analyses. PARTICIPANTS: Potential screening strategies applied to a hypothetical population of 10,000 white men from ages 50-75. MAIN MEASURES: Incremental cost-effectiveness ratio, measured in cost per quality adjusted life year (QALY). KEY RESULTS: Using base case assumptions, screening every 2 years beginning at age 60 reduced melanoma mortality by 20% with a cost-utility of $26,503 per QALY gained. Screening every 2 years beginning at age 50 reduced mortality by 30% with an incremental cost-utility of $67,970 per QALY. Results were sensitive to differences in accuracy of systematic screening versus usual care, and costs of screening, but were generally insensitive to costs of biopsy or treatment. CONCLUSIONS: Assuming moderate differences in accuracy with systematic screening versus usual care, screening for melanoma every 2 years starting at age 50 or 60 may be cost-effective in white men. Results are sensitive to degree of difference in sensitivity with screening compared to usual care. Better studies of the accuracy of systematic screening exams compared with usual care are required to determine whether a trial of screening should be undertaken.

Continuous Care Provided Through Comprehensive Medication Management in an Acute Care Practice Model.

BACKGROUND: Pharmacy practice models that foster pharmacists' accountability for medication-related outcomes are imperative for the profession. Comprehensive medication management (CMM) is an opportunity to advance patient care. OBJECTIVE: The objective of this study was to evaluate the impact of a CMM practice model in the acute care setting on organizational, patient, and financial outcomes. METHODS: Three adult service lines focused on at-risk patients identified using internal risk stratification methodology were implemented. Core CMM elements included medication reconciliation, differentiated clinical pharmacy services, inpatient MTM consultations, discharge services, and documentation. Mixed methods compared the effect of the CMM model before and after implementation. Historical patients served as comparative controls in an observational design. Pharmacists completed a 60-minute interview regarding their experiences. Qualitative data were analyzed using thematic coding to characterize perception of the model. RESULTS: Three pharmacists implemented the model on cardiology, hematology/oncology, and surgery transplant services and provided services to 75 patients during the study. A total of 145 medication-related problems were identified and resolved. CMM was associated with a nonsignificant reduction of 8.8% in 30-day hospital readmission rates ( P = 0.64) and a 24.9% reduction in 30-day hospital utilization ( P = 0.41) as well as a significant reduction of 86.5% in emergency department visits ( P = 0.02). Patients receiving discharge prescriptions from our outpatient pharmacies increased by 21.4%, resulting in an 11.3% increase in discharge prescription capture and additional revenue of $5780. Themes identified from qualitative interviews included CMM structure, challenges, value, and resources. CONCLUSION: This study demonstrated successful implementation of a CMM model that positively affected organizational, patient, and financial outcomes.

Expenditure mapping of pediatric imaging costs using a resource utilization band analysis of claims data.

OBJECTIVE: To segregate imaging expenditures from claims data by resource utilization bands (RUBs) and underlying conditions to create an "expenditure map" of pediatric imaging costs. METHODS: A Claims data for children enrolled in a commercial value-based plan were categorized by RUB 0 non-user, 1 healthy user, 2 low morbidity, 3 moderate morbidity, 4 high morbidity, & 5 very high morbidity. The per member per year (PMPY) expense, total imaging spend, and imaging modality with the highest spend were assessed for each RUB. Diagnosis categories associated with high imaging costs were also evaluated. RESULTS: There were 40,022 pediatric plan members. 14% had imaging-related claims accounting for approximately $2.8 million in expenditures. Member distribution and mean PMPY expenditure RUB was respectively: RUB 0 (3,037, $0), RUB 1 (6,604, $7), RUB 2 - 13,698, $27), RUB 3 - 13,341, $87), RUB 4 (2,810, $268), RUB 5 (532, $841). RUB 3 had the largest total imaging costs at $1,159,523. The imaging modality with the greatest mean PMPY expense varied by RUB with radiography highest in lower RUBs and MRI highest in higher RUBs. The top 3 diagnoses associated with the highest total imaging costs were developmental disorders ($443,980), asthma ($388,797), and congenital heart disease ($294,977) and greatest mean PMPY imaging expenditures malignancy/leukemia ($3,100), transplant ($2,639), and tracheostomy ($1,661). DISCUSSION: Expense mapping using claims data allows for a better understanding of the distribution of imaging costs across a covered pediatric population. This tool may assist organizations in planning effective cost-reduction initiatives and learning how imaging utilization varies by patient complexity in their system.

Coronary heart disease and ischemic stroke polygenic risk scores and atherosclerotic cardiovascular disease in a diverse, population-based cohort study.

The predictive ability of coronary heart disease (CHD) and ischemic stroke (IS) polygenic risk scores (PRS) have been evaluated individually, but whether they predict the combined outcome of atherosclerotic cardiovascular disease (ASCVD) remains insufficiently researched. It is also unclear whether associations of the CHD and IS PRS with ASCVD are independent of subclinical atherosclerosis measures. 7,286 White and 2,016 Black participants from the population-based Atherosclerosis Risk in Communities study who were free of cardiovascular disease and type 2 diabetes at baseline were included. We computed previously validated CHD and IS PRS consisting of 1,745,179 and 3,225,583 genetic variants, respectively. Cox proportional hazards models were used to test the association between each PRS and ASCVD, adjusting for traditional risk factors, ankle-brachial index, carotid intima media thickness, and carotid plaque. The hazard ratios (HR) for the CHD and IS PRS were significant with HR of 1.50 (95% CI: 1.36-1.66) and 1.31 (95% CI: 1.18-1.45) respectively for the risk of incident ASCVD per standard deviation increase in CHD and IS PRS among White participants after adjusting for traditional risk factors. The HR for the CHD PRS was not significant with an HR of 0.95 (95% CI: 0.79-1.13) for the risk of incident ASCVD in Black participants. The HR for the IS PRS was significant with an HR of 1.26 (95%CI: 1.05-1.51) for the risk of incident ASCVD in Black participants. The association of the CHD and IS PRS with ASCVD was not attenuated in White participants after adjustment for ankle-brachial index, carotid intima media thickness, and carotid plaque. The CHD and IS PRS do not cross-predict well, and predict better the outcome for which they were created than the composite ASCVD outcome. Thus, the use of the composite outcome of ASCVD may not be ideal for genetic risk prediction.

Vascular thromboembolic events following COVID-19 hospital discharge: Incidence and risk factors.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with high rates of thromboembolic events in hospitalized patients. It remains to be determined if this risk persists following hospital discharge. METHODS: We conducted a retrospective cohort study of outpatients recently hospitalized for COVID-19 to determine the incidence of vascular thromboembolic events within 30 days of discharge. We investigated the risk factors associated with these events, including intensive care admission, age, and anticoagulation. RESULTS: Among 447 patients hospitalized for COVID-19, 2.0% experienced a vascular thromboembolic event within 30 days of discharge. No risk factor variable was significantly associated with an increased risk for these events. CONCLUSIONS: The incidence of vascular thromboembolic events following hospital discharge for COVID-19 is low. These findings suggest against the routine use of postdischarge thromboprophylaxis in patients with COVID-19.

Population Impact & Efficiency of Benefit-Targeted Versus Risk-Targeted Statin Prescribing for Primary Prevention of Cardiovascular Disease.

BACKGROUND: Benefit-targeted statin prescribing may be superior to risk-targeted statin prescribing (the current standard), but the impact and efficiency of this approach are unclear. METHODS AND RESULTS: We analyzed the National Health and Nutrition Examination Survey (NHANES) using an open-source model (the Prevention Impact and Efficiency Model) to compare targeting of statin therapy according to expected benefit (benefit-targeted) versus baseline risk (risk-targeted) in terms of projected population-level impact and efficiency. Impact was defined as relative % reduction in atherosclerotic cardiovascular disease in the US population for the given strategy compared to current statin treatment patterns; and efficiency as the number needed to treat over 10 years (NNT10, average and maximum) to prevent each atherosclerotic cardiovascular disease event. Benefit-targeted moderate-intensity statin therapy at a treatment threshold of 2.3% expected 10-year absolute risk reduction could produce a 5.7% impact (95% confidence interval, 4.8-6.7). This is approximately equivalent to the potential impact of risk-targeted therapy at a treatment threshold of 5% 10-year atherosclerotic cardiovascular disease risk (5.6% impact [4.7-6.6]). Whereas the estimated maximum NNT10 is much improved for benefit-targeted versus risk-targeted therapy at these equivalent-impact thresholds (43.5 vs 180), the average NNT10 is nearly equivalent (24.2 vs 24.6). Reaching 10% impact (half the Healthy People 2020 impact objective, loosely defined) is theoretically possible with benefit-targeted moderate-intensity statins of persons with expected absolute risk reduction >2.3% if we expand age eligibility and account for treatment of all persons with diabetes mellitus or with low-density lipoprotein >190 mg/dL (impact=12.4%; average NNT10=23.0). CONCLUSIONS: Benefit-based targeting of statin therapy provides modest gains in efficiency over risk-based prescribing and could theoretically help attain approximately half of the Healthy People 2020 impact goal with reasonable efficiency.

Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.

BACKGROUND: Hemoglobin A1C (HbA1C) is associated with increased risk of cardiovascular events, but its use for prediction of cardiovascular disease (CVD) events in combination with conventional risk factors has not been well defined. METHODS AND RESULTS: To understand the effect of HbA1C on CVD risk in the context of other CVD risk factors, we analyzed HbA1C and other CVD risk factor measurements in 2000 individuals aged 40 to 79 years without pre-existing diabetes mellitus or CVD from the 2011 to 2012 National Health and Nutrition Examination Surveys survey. The resulting regression model was used to predict the HbA1C distribution based on individual patient characteristics. We then calculated post-test 10-year atherosclerotic CVD risk incorporating the actual versus predicted HbA1C, according to established methods, for a set of example scenarios. Age, sex, race/ethnicity, and traditional cardiovascular risk factors were significant predictors of HbA1C in our model, with the expected HbA1C distribution being significantly higher in non-Hispanic black, non-Hispanic Asian, and Hispanic individuals than that in non-Hispanic white/other individuals. Incorporating the expected HbA1C distribution into pretest atherosclerotic CVD risk has a modest effect on post-test atherosclerotic CVD risk. In the patient examples, we assessed that having an HbA1C of <5.7% reduced post-test risk by 0.4% to 2.0% points, whereas having an HbA1C of ≥6.5% increased post-test risk by 1.0% to 2.5% points, depending on the scenario. The post-test risk increase from having an HbA1C of ≥6.5% tends to approximate the risk increase from being 5 years older. CONCLUSIONS: HbA1C has modest effects on predicted atherosclerotic CVD risk when considered in the context of conventional risk factors.