Bone Marrow Harvest: A White Paper of Best Practices by the NMDP Marrow Alliance.

Data on recent bone marrow harvest (BMH) collections from the NMDP has shown that bone marrow (BM) quality has decreased based on total nucleated cell count in the product. To ensure that quality BM products are available to all recipients, the NMDP Marrow Alliance was formed in April 2021 to increase the capability of BM collection centers to safely deliver high-quality products consistently and to identify and disseminate guidelines for performing BMH. This white paper describes the best practices for BMH as defined by the NMDP Marrow Alliance.

Five-Year Trends in Payments for Neurologist-Prescribed Drugs in Medicare Part D.

OBJECTIVE: To determine whether there was an increase in payments for neurologist-prescribed drugs, we performed a retrospective analysis of prescription claims in the Medicare Part D Prescriber Public Use Files from 2013 to 2017. METHODS: We included claims prescribed by providers with the taxonomy "neurology" and included drugs present in all 5 years. Drugs were designated in 2013 as generic (GEN), brand name only (BNO), and brand name prescribed even though a generic equivalent is available (BNGE). To observe payment trends, the percentage change in the per claim payment was compared between drug classes. RESULTS: We included 520 drugs, of which 322 were GEN, 61 were BNO, and 137 were BNGE, representing 90,716,536 claims and generating payments of $26,654,750,720. While the number of claims from 2013 to 2017 increased only 7.6%, the total payment increased 50.4%. Adjusted for inflation, claim payments for GEN drug increased 0.6%, compared to significant increases in BNO and BNGE drugs of 42.4% and 45.0% (p trend < 0.001). The percentage of overall GEN claims increased from 81.9% to 88.0%, BNO increased from 4.9% to 6.2%, and BNGE decreased from 13.3% to 5.8%. Neuroimmunology/multiple sclerosis drugs represented >50% of the total payments despite being only 4.3% of claims. CONCLUSIONS: Payments for neurologist-prescribed brand name, but not generic, drugs in Medicare Part D increased consistently and well above inflation from 2013 to 2017. Unless the overall trend stabilizes or is reversed or high cost-to-claim drugs are addressed, this trend will place an increasing burden on the neurologic Medicare budget.

Geographic Variation in Neurologist Density and Neurologic Care in the United States.

OBJECTIVE: To describe geographic variation in neurologist density, neurologic conditions, and neurologist involvement in neurologic care. METHODS: We used 20% 2015 Medicare data to summarize variation by Hospital Referral Region (HRR). Neurologic care was defined as office-based evaluation/management visits with a primary diagnosis of a neurologic condition. RESULTS: Mean density of neurologists varied nearly 4-fold from the lowest to the highest density quintile (9.7 [95% confidence interval (CI) 9.2-10.2] vs 43.1 [95% CI 37.6-48.5] per 100,000 Medicare beneficiaries). The mean prevalence of patients with neurologic conditions did not substantially differ across neurologist density quintile regions (293 vs 311 per 1,000 beneficiaries in the lowest vs highest quintiles, respectively). Of patients with a neurologic condition, 23.5% were seen by a neurologist, ranging from 20.6% in the lowest quintile regions to 27.0% in the highest quintile regions (6.4% absolute difference). Most of the difference comprised dementia, pain, and stroke conditions seen by neurologists. In contrast, very little of the difference comprised Parkinson disease and multiple sclerosis, both of which had a very high proportion (>80%) of neurologist involvement even in the lowest quintile regions. CONCLUSIONS: The supply of neurologists varies substantially by region, but the prevalence of neurologic conditions does not. As neurologist supply increases, access to neurologist care for certain neurologic conditions (dementia, pain, and stroke) increases much more than for others (Parkinson disease and multiple sclerosis). These data provide insight for policy makers when considering strategies in matching the demand for neurologic care with the appropriate supply of neurologists.

Increasing Out-of-Pocket Costs for Neurologic Care for Privately Insured Patients.

OBJECTIVE: To measure the out-of-pocket (OOP) costs of evaluation and management (E/M) services and common diagnostic testing for neurology patients. METHODS: Using a large, privately insured health care claims database, we identified patients with a neurologic visit or diagnostic test from 2001 to 2016 and assessed inflation-adjusted OOP costs for E/M visits, neuroimaging, and neurophysiologic testing. For each diagnostic service each year, we estimated the proportion of patients with OOP costs, the mean OOP cost, and the proportion of the total service cost paid OOP. We modeled OOP cost as a function of patient and insurance factors. RESULTS: We identified 3,724,342 patients. The most frequent neurologic services were E/M visits (78.5%), EMG/nerve conduction studies (NCS) (7.7%), MRIs (5.3%), and EEGs (4.5%). Annually, 86.5%-95.2% of patients paid OOP costs for E/M visits and 23.1%-69.5% for diagnostic tests. For patients paying any OOP cost, the mean OOP cost increased over time, most substantially for EEG, MRI, and E/M. OOP costs varied considerably; for an MRI in 2016, the 50th percentile paid $103.10 and the 95th percentile paid $875.40. The proportion of total service cost paid OOP increased. High deductible health plan (HDHP) enrollment was associated with higher OOP costs for MRI, EMG/NCS, and EEG. CONCLUSION: An increasing number of patients pay OOP for neurologic diagnostic services. These costs are rising and vary greatly across patients and tests. The cost sharing burden is particularly high for the growing population with HDHPs. In this setting, neurologic evaluation might result in financial hardship for patients.

The effects of the Medicare NCS reimbursement policy: Utilization, payments, and patient access.

OBJECTIVE: To determine whether the 2013 nerve conduction study (NCS) reimbursement reduction changed Medicare use, payments, and patient access to Medicare physicians by performing a retrospective analysis of Medicare data (2012-2016 fee-for-service data from the CMS Physician and Other Supplier Public Use File). METHODS: Individual billable services were identified by Healthcare Common Procedure Coding System Current Procedural Terminology and G codes. Medicare use and payments were stratified by specialty and type of service (electrodiagnostic tests, including NCS and EMG, and other neurologic procedures). We also assessed access to Medicare physicians using the annual number of unique beneficiaries receiving initial Evaluation and Management (E/M) services. RESULTS: We identified 676,113 Medicare providers included in all analysis years from 2012 to 2016 (10,599 neurologists, 5,881 physiatrists, and 659,633 other specialties). Comparing 2016 to 2012 showed that 21.1% fewer neurologists, 28.6% fewer physiatrists, and 69.3% fewer other specialists performed NCS and 3.8% fewer neurologists, 21.7% fewer physiatrists, and 5.6% fewer other specialists performed EMG. For NCS providers in 2012, the mean number of unique Medicare beneficiaries increased for neurologists (1.2%) and physiatrists (4.8%) but decreased for other specialists (-6.5%) by 2016. After the NCS cut, the number of providers performing autonomic and evoked potential testing increased substantially. CONCLUSIONS: The Medicare NCS reimbursement policy resulted in a larger decrease in NCS providers than in EMG providers. Despite fewer neurologists and physiatrists performing NCS, Medicare access to these physicians for E/M services was not affected. Increased autonomic and evoked potential testing may be an unintended consequence of NCS reimbursement change.

Implementation of a data accuracy plan to improve data extraction yield in the Axon Registry®.

OBJECTIVE: To conduct a data quality improvement project to improve the quality measure data mapping and to measure key phrase logic in the Axon Registry.® METHODS: Prior validation analysis of the Axon Registry identified 2 main areas for remediation: methodology for mapping data from electronic health record (EHR) into the registry clinical data record (CDR) and key phrase logic for each measure. Practice groups participating in Axon Registry and 6 Axon Registry quality measures were selected for intervention. Mapping of measure elements and measure performances for each of the selected measures and practices were reviewed before intervention. The Data Accuracy Plan (DAP) was performed, and documentation data and visit data counts and data yield after intervention were calculated and analyzed. RESULTS: Documentation data and visit data counts and data yield increased for all 6 quality measures and all practices in the DAP. Increase in documentation data count ranged from 815 to 15,782 occurrences, while visit data count increase ranged from 519 to 16,383 visits. Average data yield range was 7.22% to 33.46% before intervention and increased to a range from 15.34% to 74.40% after intervention. CONCLUSION: There was substantial improvement in the accuracy of data extraction for quality measure elements after intervention to improve methodology for mapping EHR data into CDR and key phrase logic. Implementation of changes and continued review of data mapping and data dictionary are important to ensure accurate measure performance and to improve reliability and validity of Axon Registry data.

Association of out-of-pocket costs on adherence to common neurologic medications.

OBJECTIVE: To determine the association between out-of-pocket costs and medication adherence in 3 common neurologic diseases. METHODS: Utilizing privately insured claims from 2001 to 2016, we identified patients with incident neuropathy, dementia, or Parkinson disease (PD). We selected patients who were prescribed medications with similar efficacy and tolerability, but differential out-of-pocket costs (neuropathy with gabapentinoids or mixed serotonin/norepinephrine reuptake inhibitors [SNRIs], dementia with cholinesterase inhibitors, PD with dopamine agonists). Medication adherence was defined as the number of days supplied in the first 6 months. Instrumental variable analysis was used to estimate the association of out-of-pocket costs and other patient factors on medication adherence. RESULTS: We identified 52,249 patients with neuropathy on gabapentinoids, 5,246 patients with neuropathy on SNRIs, 19,820 patients with dementia on cholinesterase inhibitors, and 3,130 patients with PD on dopamine agonists. Increasing out-of-pocket costs by $50 was associated with significantly lower medication adherence for patients with neuropathy on gabapentinoids (adjusted incidence rate ratio [IRR] 0.91, 0.89-0.93) and dementia (adjusted IRR 0.88, 0.86-0.91). Increased out-of-pocket costs for patients with neuropathy on SNRIs (adjusted IRR 0.97, 0.88-1.08) and patients with PD (adjusted IRR 0.90, 0.81-1.00) were not significantly associated with medication adherence. Minority populations had lower adherence with gabapentinoids and cholinesterase inhibitors compared to white patients. CONCLUSIONS: Higher out-of-pocket costs were associated with lower medication adherence in 3 common neurologic conditions. When prescribing medications, physicians should consider these costs in order to increase adherence, especially as out-of-pocket costs continue to rise. Racial/ethnic disparities were also observed; therefore, minority populations should receive additional focus in future intervention efforts to improve adherence.

Implementation of quality measures and patient-reported outcomes in an epilepsy clinic.

OBJECTIVE: To see if systematic collection of patient-reported epilepsy quality measures can identify opportunities to improve care, and to examine the associations between these measures and physical and mental health. METHODS: We developed a patient-reported questionnaire for medication adherence, seizure frequency, medication side effects, and driving that included the Patient-Reported Outcome Measurement Information System-10 (PROMIS-10) (physical and mental health). We offered it to all adult patients seen twice in an epilepsy clinic (January 2017-January 2018). The questionnaire was available on the web as well as a tablet provided at appointment check-in. We used the first completed questionnaire to explore the relationship between patient-reported care quality and measures of physical and mental health. RESULTS: A total of 610 unique patients (15% of the total encounters) completed a survey. Respondents were comparable to nonrespondents. Respondents reported gaps in care or opportunities for quality improvement in 48.4% (n = 295) of the encounters. Of patients who reported at least 1 seizure per month over the previous 3 months, 55.2% (n = 100) reported problems with adherence, 30.0% (n = 131) reported having problems believed to be adverse reactions to anticonvulsants, and 15.2% (n = 41) reported driving. In addition, respondents who reported either seizures over the recent 3 months, nonadherence to treatment due to cost, or anticonvulsant-associated adverse effects had consistently worse physical and mental health (all p < 0.05). CONCLUSIONS: Systematic collection of epilepsy quality measures endorsed by the American Academy of Neurology can identify opportunities for quality improvement. Measures of epilepsy care quality predict outcomes that matter to patients.

Out-of-pocket costs are on the rise for commonly prescribed neurologic medications.

OBJECTIVE: To determine out-of-pocket costs for neurologic medications in 5 common neurologic diseases. METHODS: Utilizing a large, privately insured, health care claims database from 2004 to 2016, we captured out-of-pocket medication costs for patients seen by outpatient neurologists with multiple sclerosis (MS), peripheral neuropathy, epilepsy, dementia, and Parkinson disease (PD). We compared out-of-pocket costs for those in high-deductible health plans compared to traditional plans and explored cumulative out-of-pocket costs over the first 2 years after diagnosis across conditions with high- (MS) and low/medium-cost (epilepsy) medications. RESULTS: The population consisted of 105,355 patients with MS, 314,530 with peripheral neuropathy, 281,073 with epilepsy, 120,720 with dementia, and 90,801 with PD. MS medications had the fastest rise in monthly out-of-pocket expenses (mean [SD] $15 [$23] in 2004, $309 [$593] in 2016) with minimal differences between medications. Out-of-pocket costs for brand name medications in the other conditions also rose considerably. Patients in high-deductible health plans incurred approximately twice the monthly out-of-pocket expense as compared to those not in these plans ($661 [$964] vs $246 [$472] in MS, $40 [$94] vs $18 [$46] in epilepsy in 2016). Cumulative 2-year out-of-pocket costs rose almost linearly over time in MS ($2,238 [$3,342]) and epilepsy ($230 [$443]). CONCLUSIONS: Out-of-pocket costs for neurologic medications have increased considerably over the last 12 years, particularly for those in high-deductible health plans. Out-of-pocket costs vary widely both across and within conditions. To minimize patient financial burden, neurologists require access to precise cost information when making treatment decisions.

Axon Registry® data validation: Accuracy assessment of data extraction and measure specification.

OBJECTIVE: To conduct a data validation study encompassing an accuracy assessment of the data extraction process for the Axon Registry®. METHODS: Data elements were abstracted from electronic health records (EHRs) by an external auditor (IQVIA) using virtual site visits at participating sites. IQVIA independently calculated Axon Registry quality measure performance rates based on American Academy of Neurology measure specifications and logic using Axon Registry data. Agreement between Axon Registry and IQVIA data elements and measure performance rates was calculated. Discordance was investigated to elucidate underlying systemic or idiosyncratic reasons for disagreement. RESULTS: Nine sites (n = 720 patients; n = 80 patients per site) with diversity among EHR vendor, practice settings, size, locations, and data transfer method were included. There was variable concordance between the data elements in the Axon Registry and those abstracted independently by IQVIA; high match rates (≥92%) were observed for discrete elements (e.g., demographics); lower match rates (<44%) were observed for elements with free text (e.g., plan of care). Across all measures, there was a 76% patient-level measure performance agreement between Axon Registry and IQVIA (κ = 0.53, p < 0.001). CONCLUSION: There was a range of concordance between data elements and quality measures in the Axon Registry and those independently abstracted and calculated by an independent vendor. Validation of data and processes is important for the Axon Registry as a clinical quality data registry that utilizes automated data extraction methods from the EHR. Implementation of remediation strategies to improve data accuracy will support the ability of the Axon Registry to perform accurate quality reporting.

An Economic Analysis of Updating and Expanding School Breakfast Program Offerings in High Schools.

BACKGROUND: School breakfast is an important nutritional component of a student's day. Many schools operate a school breakfast program, but high schools have low rates of participation. This study aimed to investigate the economic impact on school food service, of expanding the school breakfast program to increase participation in high schools. METHODS: Ten rural high schools participated in the economic analysis of expanding their school breakfast program. Schools provided data on costs of daily operation and start-up costs. Analyses calculated the daily breakeven point, revenue, cost, and days needed to recoup costs. RESULTS: Schools sold enough breakfast meals to break even on daily costs of operating an expanded program. Schools saw daily profits ranging from $196-$432 and recouped costs associated with expanding the breakfast program within 15-46 days. CONCLUSIONS: Expanding the school breakfast program can be economical for schools, while increasing student exposure to the health and academic benefits of school breakfast.

Claims data analyses unable to properly characterize the value of neurologists in epilepsy care.

OBJECTIVE: To determine the association of a neurologist visit with health care use and cost outcomes for patients with incident epilepsy. METHODS: Using health care claims data for individuals insured by United Healthcare from 2001 to 2016, we identified patients with incident epilepsy. The population was defined by an epilepsy/convulsion diagnosis code (ICD codes 345.xx/780.3x, G40.xx/R56.xx), an antiepileptic prescription filled within the succeeding 2 years, and neither criterion met in the 2 preceding years. Cases were defined as patients who had a neurologist encounter for epilepsy within 1 year after an incident diagnosis; a control cohort was constructed with propensity score matching. Primary outcomes were emergency room (ER) visits and hospitalizations for epilepsy. Secondary outcomes included measures of cost (epilepsy related, not epilepsy related, and antiepileptic drugs) and care escalation (including EEG evaluation and epilepsy surgery). RESULTS: After participant identification and propensity score matching, there were 3,400 cases and 3,400 controls. Epilepsy-related ER visits were more likely for cases than controls (year 1: 5.9% vs 2.3%, p < 0.001), as were hospitalizations (year 1: 2.1% vs 0.7%, p < 0.001). Total medical costs for epilepsy care, nonepilepsy care, and antiepileptic drugs were greater for cases (p ≤ 0.001). EEG evaluation and epilepsy surgery occurred more commonly for cases (p ≤ 0.001). CONCLUSIONS: Patients with epilepsy who visited a neurologist had greater subsequent health care use, medical costs, and care escalation than controls. This comparison using administrative claims is plausibly confounded by case disease severity, as suggested by higher nonepilepsy care costs. Linking patient-centered outcomes to claims data may provide the clinical resolution to assess care value within a heterogeneous population.

Association of neurologist care with headache expenditures: A population-based, longitudinal analysis.

Objective To assess the association of neurologist ambulatory care with healthcare utilization and expenditure in headache. Methods This was a longitudinal cohort study from two-year duration panel data, pooled from 2002-2013, of adult respondents identified with diagnostic codes for headache in the Medical Expenditure Panel Survey. Those with a neurologist ambulatory care visit in year one of panel participation were compared with those who did not for the change in annual aggregate direct headache-related health care costs from year one to year two of panel participation, inflated to 2015 US dollars. Results were adjusted via multiple linear regression for demographic and clinical variables, utilizing survey variables for accurate estimates and standard errors. Results Eight hundred and eighty-seven respondents were included, with 23.3% (207/887) seeing a neurologist in year one. The neurologist group had higher year-one mean headache-related expenditures ($3032 vs. $1636), but nearly equal mean year-two expenditures compared to controls ($1900 vs. $1929). Adjusted association between neurologist care and difference in mean annual expenditures from year two to year one was -$1579 (95% CI -$2468, -$690, p < 0.001). Conclusion Among headache sufferers, particularly those with higher headache-related healthcare expenditures, neurologist care is associated with a significant reduction in costs over two years.

The association of neurologists with headache health care utilization and costs.

OBJECTIVE: To determine the association of a neurologist visit with headache health care utilization and costs. METHODS: Utilizing a large privately insured health care claims database, we identified patients with an incident headache diagnosis (ICD-9 codes 339.xx, 784.0x, 306.81) with at least 5 years follow-up. Patients with a subsequent neurologist visit were matched to controls without a neurologist visit using propensity score matching, accounting for 54 potential confounders and regional variation in neurologist density. Co-primary outcomes were emergency department (ED) visits and hospitalizations for headache. Secondary outcomes were quality measures (abortive, prophylactic, and opioid prescriptions) and costs (total, headache-related, and non-headache-related). Generalized estimating equations assessed differences in longitudinal outcomes between cases and controls. RESULTS: We identified 28,585 cases and 57,170 controls. ED visits did not differ between cases and controls (p = 0.05). Hospitalizations were more common in cases in year 0-1 (0.2%, 95% confidence interval [CI] 0.2%-0.3% vs 0.01%, 95% CI 0.01%-0.02%; p < 0.01), with minimal differences in subsequent years. Costs (including non-headache-related costs) and high-quality and low-quality medication utilization were higher in cases in the first year and decreased toward control costs in subsequent years with small differences persisting over 5 years. Opioid prescriptions increased over time in both cases and controls. CONCLUSION: Compared with those without a neurologist, headache patients who visit neurologists had a transient increase in hospitalizations, but the same ED utilization. Confounding by severity is the most likely explanation given the non-headache-related cost trajectory. Claims-based risk adjustment will likely underestimate disease severity of headache patients seen by neurologists.