Category: Nevin Manimala

Am J Manag Care. 2024 Aug;30(8):381-386. doi: 10.37765/ajmc.2024.89589.

ABSTRACT

OBJECTIVES: To examine characteristics of Medicare Advantage (MA) enrollees who use their plan’s customer service to help plans understand how to better meet members’ needs.

STUDY DESIGN: National sample of 259,533 respondents to MA Consumer Assessment of Healthcare Providers and Systems survey enrolled in any of the 559 MA contracts in 2022.

METHODS: We assessed the association between self-reported customer service use in the prior 6 months and enrollee demographic, coverage, health, and health care utilization characteristics. We used weighted linear regression models to test for bivariate and multivariate associations between customer service use and enrollee characteristics.

RESULTS: Forty-two percent of MA enrollees reported using customer service in the prior 6 months. Use was 20 percentage points (PP) higher for those in poor vs excellent/very good general health, 13 PP higher for those in poor vs excellent/very good mental health, and 14 PP higher for those reporting 3 or more vs no chronic conditions. Those using customer service more often had lower educational attainment, had limited income and assets, preferred another language to English, and had greater health care utilization.

CONCLUSIONS: MA customer service supports a less healthy, higher-need population with greater-than-average barriers to health care, and so should be designed and staffed to effectively serve medically complex, high-need patients. Commercial plan evidence suggests that continuity in customer service support for a member or a given issue may be helpful. Customer service is an important mechanism for improving quality and addressing health equity.

PMID:39146487 | DOI:10.37765/ajmc.2024.89589

Am J Manag Care. 2024 Aug;30(8):374-379. doi: 10.37765/ajmc.2024.89588.

ABSTRACT

OBJECTIVE: To determine the geographic variability of Medicaid acceptance among allergists in the US.

STUDY DESIGN: Geospatial analysis predicted Medicaid acceptance across space, and a multivariable regression identified area-level population demographic variables associated with acceptance.

METHODS: We used the National Plan & Provider Enumeration System database to identify allergists. Medicaid acceptance was determined from lists or search engines from state Medicaid offices and calls to provider offices. Spatial analysis was performed using the empirical Bayesian kriging tool. Multivariate logistic regression was used to identify county-level characteristics associated with provider Medicaid acceptance.

RESULTS: Of 5694 allergists, 55.5% accepted Medicaid. Acceptance in each state ranged from 13% to 90%. Washington, Arizona, and the Northeast had lowest predicted proportion of both Medicaid acceptance and Medicaid acceptance per 10,000 enrollees. Overall, county-level characteristics were not associated with the likelihood of accepting Medicaid in multivariate analyses. Only the percentage of individuals living in poverty was associated with a higher likelihood of providers accepting Medicaid (OR, 1.245; 95% CI, 1.156-1.340; P < .001).

CONCLUSIONS: A barrier to accessing allergy-related health care is finding a provider who accepts a patient’s insurance, which is largely variable by state. Lack of access to allergy care likely affects health outcomes for children with prevalent atopic conditions such as food allergy.

PMID:39146486 | DOI:10.37765/ajmc.2024.89588

Am J Manag Care. 2024 Aug;30(8):365-371. doi: 10.37765/ajmc.2024.89587.

ABSTRACT

OBJECTIVES: To discuss the social, psychological, and access barriers that inhibit weight loss, and to propose steps and initiatives for addressing the growing obesity epidemic.

STUDY DESIGN: Narrative review of the obesity epidemic in the US and associated racial/ethnic and socioeconomic disparities.

METHODS: An internet search of relevant studies and government reports was conducted.

RESULTS: Obesity is a significant health crisis affecting more than 123 million adults and children/adolescents in the US. An estimated 1 in 5 deaths in Black and White individuals aged 40 to 85 years in the US is attributable to obesity. Obesity puts individuals at elevated risk for type 2 diabetes, cardiovascular disease, chronic kidney disease, gastrointestinal disorders, nonalcoholic fatty liver disease, cancer, respiratory ailments, dementia/Alzheimer disease, and other disorders. In the US, significantly more Black (49.9%) and Hispanic (45.6%) individuals are affected by obesity than White (41.4%) and Asian (16.1%) individuals. Health care costs for obesity account for more than $260 billion of annual US health care spending-more than 50% greater in excess annual medical costs per person than individuals with normal weight.

CONCLUSIONS: Addressing the obesity epidemic will require a multifaceted approach that focuses on prevention, treatment, and reducing the impact of stigma. Continued advocacy and education efforts are necessary to make progress and improve the health and well-being of individuals affected by obesity.

PMID:39146485 | DOI:10.37765/ajmc.2024.89587

Am J Manag Care. 2024 Aug;30(8):353-358. doi: 10.37765/ajmc.2024.89559.

ABSTRACT

OBJECTIVES: To examine a 12-month dementia care management program’s effect on health care cost, utilization, and overall return on investment in a Medicare managed care population.

STUDY DESIGN: Pre-post analysis of participants (n = 121) enrolled in Ochsner’s Care Ecosystem program from 2019 through 2021 compared with propensity-matched controls (n = 121). The primary outcome comparison was total cost of care. Secondary outcomes included components of total cost of care (eg, inpatient, outpatient, emergency department [ED] costs), health care utilization (eg, number of ED visits), and differences in Hierarchical Condition Category (HCC) risk scores.

METHODS: Difference-in-differences analyses were conducted from baseline through 12 months comparing various financial metrics and utilization between groups.

RESULTS: Care Ecosystem participants had significantly lower total cost of care at 12 months, mean savings of $475.80 per member per month compared with controls. Care Ecosystem participants had fewer ED, outpatient, and professional visits. HCC risk scores were also better relative to matched controls.

CONCLUSIONS: A collaborative dementia care program demonstrated significant financial benefit in a managed Medicare population.

PMID:39146484 | DOI:10.37765/ajmc.2024.89559

Am J Manag Care. 2024 Aug 1;30(8):e247-e250. doi: 10.37765/ajmc.2024.89594.

ABSTRACT

Given recent congressional interest in codifying price transparency regulations, it is important to understand the extent to which newly available price transparency data capture true underlying procedure-level prices. To that end, we compared the prices for maternity services negotiated between a large payer and 26 hospitals in Mississippi across 2 separate price transparency data sources: payer and hospital. The degree of file overlap is low, with only 16.3% of hospital-billing code observations appearing in both data sources. However, for the observations that overlap, pricing concordance is high: Corresponding prices have a correlation coefficient of 0.975, 77.4% match to the penny, and 84.4% are within 10%. Exact price matching rates are greater than 90% for 3 of the 4 service lines included in this study. Taken together, these results suggest that although administrative misalignment exists between payers and hospitals, there is a measure of signal amid the price transparency noise.

PMID:39146482 | DOI:10.37765/ajmc.2024.89594

Am J Manag Care. 2024 Aug 1;30(8):e240-e246. doi: 10.37765/ajmc.2024.89593.

ABSTRACT

OBJECTIVES: Hospitals in the US operate under various value-based payment programs, but little is known regarding the strategies they use in this context to improve quality and reduce costs, overall or in voluntary programs including Bundled Payments for Care Improvement Advanced (BPCI-A).

STUDY DESIGN: A survey was administered to hospital leaders at 588 randomly selected acute care hospitals, with oversampling of BPCI-A participants, from November 2020 to June 2021. Twenty strategies and 20 barriers were queried in 4 domains: inpatient, postacute, outpatient, and community resources for vulnerable patients.

METHODS: Summary statistics were tabulated, and responses were adjusted for sampling strategy and nonresponse.

RESULTS: There were 203 respondents (35%), of which 159 (78%) were BPCI-A participants and 44 (22%) were nonparticipants. On average, respondents reported implementing 89% of queried strategies in the inpatient domain, such as care pathways or predictive analytics; 65% of postacute strategies, such as forming partnerships with skilled nursing facilities; 84% of outpatient strategies, such as scheduling close follow-up to prevent emergency department visits/hospitalizations; and 82% of strategies aimed at high-risk populations, such as building connections with community resources. There were no differences between BPCI-A and non-BPCI-A hospitals in 19 of 20 care redesign strategies queried. However, 78.3% of BPCI-A-participating hospitals reported programs aimed at reducing utilization of skilled nursing and inpatient rehabilitation facilities compared with 37.6% of non-BPCI-A hospitals (P < .0001).

CONCLUSIONS: Hospitals pursue a broad range of efforts to improve quality. BPCI-A hospitals have attempted to reduce use of postacute care, but otherwise the strategies they pursue are similar to other hospitals.

PMID:39146481 | DOI:10.37765/ajmc.2024.89593

Am J Manag Care. 2024 Aug 1;30(8):e233-e239. doi: 10.37765/ajmc.2024.89592.

ABSTRACT

OBJECTIVES: To evaluate the FeelBetter machine learning system’s ability to accurately identify older patients with multimorbidity at Brigham and Women’s Hospital at highest risk of medication-associated emergency department (ED) visits and hospitalizations, and to assess the system’s ability to provide accurate medication recommendations for these patients.

STUDY DESIGN: Retrospective cohort study.

METHODS: The system uses medications, demographics, diagnoses, laboratory results, health care utilization patterns, and costs to stratify patients’ risk of ED visits and hospitalizations. Patients were assigned 1 of 22 risk levels based on their system-generated risk percentile of either ED visits or hospitalizations. Logistic regression models were used to estimate the odds of ED visits and hospitalizations associated with each successive risk level compared with the 45th to 50th percentiles. After stratification, 100 high-risk (95th-100th percentiles) and 100 medium-risk (45th-55th percentiles) patients were randomly selected for generation of medication recommendations. Two clinical pharmacists reviewed the system-generated medication recommendations for these patients.

RESULTS: Logistic regression models predicting 3-month utilization showed that compared with the 45th to 50th percentiles, patients in the top 1% risk percentile had ORs of 7.9 and 17.3 for ED visits and hospitalizations, respectively. The first 5 high-priority medications on each patient’s medication list were associated with a mean (SD) of 6.65 (4.09) warnings. Of 1290 warnings reviewed, 1151 (89.2%) were assessed as correct.

CONCLUSIONS: The FeelBetter system effectively stratifies older patients with multimorbidity at risk of ED use and hospitalizations. Medication recommendations provided by the system are largely accurate and can potentially be beneficial for patient care.

PMID:39146480 | DOI:10.37765/ajmc.2024.89592

Am J Manag Care. 2024 Aug 1;30(8):e226-e232. doi: 10.37765/ajmc.2024.89591.

ABSTRACT

OBJECTIVES: Adherence to medications is important for the management of chronic diseases. Although the proportion of days covered (PDC) is a common metric for measuring adherence, it may be insufficient to distinguish relevant differences in medication-taking behavior. Group-based trajectory models (GBTMs) have been used to better represent adherence over time. This study aims to examine adherence patterns 1 year after initiation among users of sodium-glucose cotransporter 2 (SGLT2) inhibitors using GBTMs and evaluate the ability of baseline characteristics to predict adherence trajectory.

STUDY DESIGN: SGLT2 inhibitor new-user cohort study from 2014 to 2018.

METHODS: We calculated 12-month PDC and categorized patients with PDC of 80% or greater as adherent. We performed multivariable logistic regression on adherence status controlling for baseline covariates. GBTMs were fit to identify adherence patterns 12 months following SGLT2 inhibitor initiation. Five multinomial logistic regression models including different subsets of predictors were used to predict adherence trajectory group assignment.

RESULTS: In a cohort of 228,363 SGLT2 inhibitor users, the mean PDC was 57%, with 36% of the cohort being adherent. Overall, women and patients with anxiety or depression were less likely to be adherent. Six patterns of SGLT2 inhibitor adherence were identified with GBTMs: 1 fill (PDC = 0.08), early discontinuation (PDC = 0.22), consistently low adherence (PDC = 0.35), moderate adherence (PDC = 0.48), high adherence (PDC = 0.79), and near-perfect adherence (PDC = 0.95). All prediction models showed poor predictive accuracy (0.35).

CONCLUSIONS: We found wide variation in adherence patterns among SGLT2 inhibitor users in a national cohort. Predictors from a health care claims database were unable to accurately predict adherence trajectory.

PMID:39146479 | DOI:10.37765/ajmc.2024.89591

Chem Biodivers. 2024 Aug 15:e202401383. doi: 10.1002/cbdv.202401383. Online ahead of print.

ABSTRACT

Chuju, a cultivar of Chrysanthemum morifolium, has been traditionally cultivated for over 2000 years in China for both ornamental and medicinal purposes. To date, investigations into the chemical composition of this plant have indicated that it contains compounds with extensive biological activities, although detailed information on the chemical composition of Chuju remains scarce. In the present study, the chemical compositions of Chuju flowers were investigated across five sites in the core Chuju planting area in Anhui province, China. Analytical pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) was used to explore variations in flower chemical fingerprints from different Chuju planting sites. The study identified approximately 200 components in Chuju flowers and stems, including high levels of fatty acids, lipids, polysaccharides and terpenoids. Multivariate statistical analysis indicated that 16 chemical compounds were influential determinants of the chemical fingerprint and could be used to distinguish two clusters in the five core planting areas. The established Py-GC/MS analytical workflow could provide a basis for determining the chemical fingerprints of Chuju and help elucidate that products contain a reproducible content of bioactive compounds and overall quality for potential development of health and medicinal purposes.

PMID:39146472 | DOI:10.1002/cbdv.202401383

Ophthalmic Epidemiol. 2024 Aug 15:1-9. doi: 10.1080/09286586.2024.2371467. Online ahead of print.

ABSTRACT

PURPOSES: To determine the relationship between carotid artery stenosis (CAS) and the development of open-angle glaucoma (OAG) in the Taiwanese population.

METHODS: This retrospective cohort study was conducted using Chang Gung Research Database. Cox-proportional hazards model was applied to calculate the hazard ratio for OAG between CAS and the control cohort.

RESULTS: Among 19,590 CAS patients, 17,238 had mild CAS (<50%), 1,895 had moderate CAS (50-69%), and 457 had severe CAS (≥70%). The CAS cohort had a higher proportion of several comorbidities. After adjusting for comorbidities, no significant difference in OAG development was found between CAS and control cohorts. Matching for key comorbidities, no significant differences in OAG incidence were found between matched cohorts (P = .869). Subdividing the matched CAS cohort by stenosis severity: mild (<50%), moderate (50-69%), and severe (≥70%), a statistically significantly lower OAG risk was observed in patients with mild CAS stenosis (HR: 1.12, 95% CI = 1.03-1.21, P = .006). Kaplan-Meier analysis revealed reduced OAG incidence in CAS patients who underwent surgical intervention, compared to the control cohort (P <.001). Subgroup analysis revealed that patients in the mild CAS stenosis group, those who underwent surgical intervention exhibited a reduced OAG risk (HR: 0.29, 95% CI = 0.15-0.58, P = .001).

CONCLUSIONS: No statistically significant differences in OAG risk were observed between patients with CAS and the control cohort. The severity of CAS appears to influence OAG risk, with surgical intervention potentially offering protective effects, particularly in patients with mild CAS stenosis (<50%), suggesting that enhanced ocular perfusion post-surgery may act as a protective factor against OAG development.

PMID:39146467 | DOI:10.1080/09286586.2024.2371467