Precision of provider licensure data for mapping member accessibility to Medicaid managed care provider networks

Bell, Nathaniel; Lòpez-DeFede, Ana; Wilkerson, Rebecca; Mayfield-Smith, Kathy

doi:10.1186/s12913-018-3776-4

Cited by 8 publications

(6 citation statements)

References 29 publications

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“…The researchers do not explicitly test, however, whether narrow network plans are linked to reduced access to care. Others have criticized the quality of network data used by states to evaluate access to care (3).…”

Section: Accessmentioning

confidence: 99%

Medicaid Managed Care's Effects on Costs, Access, and Quality: An Update

Montoya

Chehal

Adams

2020

Annu. Rev. Public Health

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Medicaid is integral to public health because it insures one in five Americans and half of the nation's births. Nearly two-thirds of all Medicaid recipients are currently enrolled in a health maintenance organization (HMO). Proponents of HMOs argue that they can lower costs while maintaining access and quality. We critically reviewed 32 studies on Medicaid managed care (2011–2019). Authors reported state-specific cost savings and instances of increased access or quality with implementation or redesign of Medicaid managed-care programs. Studies on high-risk populations (e.g., disabled) found improvements in quality specific to a state or a high-risk population. A unique model of managed care (i.e., the Oregon Health Plan) was associated with reduced costs and improved access and quality, but results varied by comparison state. New trends in the literature focused on analysis of auto-assignment algorithms, provider networks, and plan quality. More analysis of costs jointly with access/quality is needed, as is research on managing long-term care among elderly and disabled Medicaid recipients.

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Section: Accessmentioning

confidence: 99%

Medicaid Managed Care's Effects on Costs, Access, and Quality: An Update

Montoya

Chehal

Adams

2020

Annu. Rev. Public Health

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“…Perhaps most important, as noted elsewhere (Bindman, 2013), a lack of accurate data could prohibit the evaluation of policies intended to improve access to services. Although CMS developed the NPI data set for administrative purposes, the utilization of NPI data for research on the workforce capacity of health care providers is becoming more frequent (Andrilla, Patterson, Barberson, Coulthard, & Larson, 2018;Miller, Petterson, Burke, Phillips, & Green, 2014;Miller, Petterson, Levey, et al, 2014b;Richman, Lombardi, & Zerden, 2018), and although improvements are needed, evidence indicates that the NPI data set is superior to other data sources in the accuracy of provider locations (e.g., Bell, Lòpez-DeFede, Wilkerson, & Mayfield-Smith, 2018). NPI data have other advantages as well.…”

Section: How These Results Affect Practicementioning

confidence: 99%

The Misclassification of Behavior Analysts: How National Provider Identifiers (NPIs) Fail to Adequately Capture the Scope of the Field

Dubuque

Yingling

Allday

2020

Behav Analysis Practice

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To remain in compliance with the Health Insurance Portability and Accountability Act of 1996, U.S. health care providers are required to register for a National Provider Identifier (NPI). When applying for an NPI, providers must select the Healthcare Provider Taxonomy Code(s) that most closely describes the services they offer. Three distinct taxonomies describe the services offered by behavior analysts. Two of these codes, the Behavior Analyst (103K00000X) and the Assistant Behavior Analyst (106E00000X) taxonomies, specify that the health care provider must hold either a certification from the Behavior Analyst Certification Board or a state-issued credential to practice behavior analysis. The purpose of this study was to investigate the concordance between health care providers who utilize these behavior-analytic NPI taxonomy classifications and health care providers who meet the credential qualifications specified in the code descriptions. Results indicated that there are potentially more than 20,000 U.S. health care providers who do not hold the behavior analyst credentials specified in the taxonomy descriptions linked to their accounts. The implications of providers being mistakenly classified as credentialed behavior analysts and credentialed assistant behavior analysts in federal data and how the field should respond are discussed.

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“…All distance estimates were derived using ESRI's Street Map Premium Address File, which is an enhanced version of commercial street reference data from HERE, TomTom, and INCREMENT P. The network analysis process was built using a composite geocoding algorithm using a validated approach. [52] The geocoded data les were then linked to its corresponding patient-, provider-, and area-level data in SAS statistical software for Windows using SQL scripting language.…”

Section: Geocoding and Data Linkagesmentioning

confidence: 99%

Centering Racial and Ethnic Equity in Health Care Throughout Spatial Data Analysis

Bell

Cai

Brooks

et al. 2021

Preprint

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BackgroundThe ongoing COVID-19 pandemic as well as a host of social movements have put a nation-sized spotlight on structural inequality and racial disparities in health throughout America. As health care systems begin to advance health equity by holding plans and payers accounting for racial and socioeconomic disparities in care, quantitative methods are needed that emphasize the distinct linkages between physical locations and racially disparate outcomes.MethodsWe apply a counterfactual model to compare differences in avoidable and potentially avoidable emergency department (ED) admissions among a panel of 8,924 non-Hispanic White, Black, and Hispanic Medicaid participants between 2016 - 2018. The magnitude of disparity estimates is examined in relation to geographic proximity to health care providers, neighborhood socioeconomic contexts, as well as the type of primary care delivery model individuals received. The adjusted rates were assessed by generalized estimating equations (GEE) and average marginal effects models to contrast differences in probability of events in association with race/ethnicity, proximity to care, and treatment through patient-centered medical homes (PCMH). ResultsAttending a patient-centered medical home was associated with a 3.4 percentage point (p <0.001) decrease in Black-White racial disparity and a 1.8 percentage point (p < 0.10) reduction in the overall Black-White disparity for potentially avoidable ED admissions. PCMH attendance was attributed to a 2.6 percentage point (p < 0.10) reduction in Hispanic-White disparities in potentially avoidable admissions, but this difference was not substantial enough to curb the overall Hispanic-White racial disparity in ED admissions. No statistically significant reductions in Black-White or Hispanic-White disparities in avoidable ED admissions were observed. ConclusionMedical homes may be able to curb, but not necessarily eliminate, racial disparities in ED admissions. Counterfactual models of health disparities are in line with recent transitions toward evaluating patient- and value-centered health care reform changes as they are designed to measure health and racial equity. This strategy, or variations of it, are adaptable to other investigations where emphasis on physical locations is considered essential to understanding racial disparities in health outcomes.

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Precision of provider licensure data for mapping member accessibility to Medicaid managed care provider networks

Cited by 8 publications

References 29 publications

Medicaid Managed Care's Effects on Costs, Access, and Quality: An Update

Medicaid Managed Care's Effects on Costs, Access, and Quality: An Update

The Misclassification of Behavior Analysts: How National Provider Identifiers (NPIs) Fail to Adequately Capture the Scope of the Field

Centering Racial and Ethnic Equity in Health Care Throughout Spatial Data Analysis

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