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The American Journal of Managed Care Jun 2024Most Medicare beneficiaries obtain supplemental insurance or enroll in Medicare Advantage (MA) to protect against potentially high cost sharing in traditional Medicare...
OBJECTIVES
Most Medicare beneficiaries obtain supplemental insurance or enroll in Medicare Advantage (MA) to protect against potentially high cost sharing in traditional Medicare (TM). We examined changes in Medicare supplemental insurance coverage in the context of MA growth.
STUDY DESIGN
Repeated cross-sectional analysis of the Medicare Current Beneficiary Survey from 2005 to 2019.
METHODS
We determined whether Medicare beneficiaries 65 years and older were enrolled in MA (without Medicaid), TM without supplemental coverage, TM with employer-sponsored supplemental coverage, TM with Medigap, or Medicaid (in TM or MA).
RESULTS
From 2005 to 2019, beneficiaries with TM and supplemental insurance provided by their former (or current) employer declined by approximately half (31.8% to 15.5%) while the share in MA (without Medicaid) more than doubled (13.4% to 35.1%). The decline in supplemental employer-sponsored insurance use was greater for White and for higher-income beneficiaries. Over the same period, beneficiaries in TM without supplemental coverage declined by more than a quarter (13.9% to 10.1%). This decline was largest for Black, Hispanic, and lower-income beneficiaries.
CONCLUSIONS
The rapid rise in MA enrollment from 2005 to 2019 was accompanied by substantial changes in supplemental insurance with TM. Our results emphasize the interconnectedness of different insurance choices made by Medicare beneficiaries.
Topics: Humans; United States; Aged; Male; Female; Cross-Sectional Studies; Primary Health Care; Medicare; Medicare Part C; Aged, 80 and over; Hospitalization; Insurance Coverage; Medicaid; Cost Sharing
PubMed: 38912952
DOI: 10.37765/ajmc.2024.89509 -
The American Journal of Managed Care Jun 2024To assess whether hospitals participating in Medicare's Bundled Payments for Care Improvement (BPCI) program for joint replacement changed their referral patterns to... (Observational Study)
Observational Study
OBJECTIVES
To assess whether hospitals participating in Medicare's Bundled Payments for Care Improvement (BPCI) program for joint replacement changed their referral patterns to favor higher-quality skilled nursing facilities (SNFs).
STUDY DESIGN
Retrospective observational study using 2009-2015 inpatient and outpatient claims from a 20% sample of Medicare beneficiaries undergoing joint replacement in US hospitals (N = 146,074) linked with data from Medicare's BPCI program and Nursing Home Compare.
METHODS
We ran fixed effect regression models regressing BPCI participation on hospital-SNF referral patterns (number of SNF discharges, number of SNF partners, and SNF referral concentration) and SNF quality (facility inspection survey rating, patient outcome rating, staffing rating, and registered nurse staffing rating).
RESULTS
We found that BPCI participation was associated with a decrease in the number of SNF referrals and no significant change in the number of SNF partners or concentration of SNF partners. BPCI participation was associated with discharge to SNFs with a higher patient outcome rating by 0.04 stars (95% CI, 0.04-0.26). BPCI participation was not associated with improvements in discharge to SNFs with a higher facility survey rating (95% CI, -0.03 to 0.11), staffing rating (95% CI, -0.07 to 0.04), or registered nurse staffing rating (95% CI, -0.09 to 0.02).
CONCLUSIONS
BPCI participation was associated with lower volume of SNF referrals and small increases in the quality of SNFs to which patients were discharged, without narrowing hospital-SNF referral networks.
Topics: Skilled Nursing Facilities; Humans; United States; Retrospective Studies; Medicare; Referral and Consultation; Quality Improvement; Female; Patient Care Bundles; Male; Arthroplasty, Replacement; Aged
PubMed: 38912933
DOI: 10.37765/ajmc.2024.89566 -
The American Journal of Managed Care Jun 2024Chronic kidney disease (CKD) is a widely prevalent disease with heterogeneous disease progression. Prior study findings suggest that early referral to nephrologists can...
OBJECTIVES
Chronic kidney disease (CKD) is a widely prevalent disease with heterogeneous disease progression. Prior study findings suggest that early referral to nephrologists can improve health outcomes for patients with CKD. Current practice guidelines recommend nephrology referral when patients are diagnosed with CKD stage 4. We tested whether a subset of patients with CKD stage 3 and common medical comorbidities demonstrates disease progression, cost, and utilization patterns that would merit earlier referral.
STUDY DESIGN
Retrospective study of Medicare fee-for-service beneficiaries with CKD stages 3 through 5 and end-stage kidney disease.
METHODS
We identified 7 comorbidities with high prevalence in patients with progressive CKD and segmented beneficiaries with CKD stage 3 based on the presence of these comorbidities. Outcomes including costs, utilization, and disease progression were then compared across beneficiaries with different stages of CKD.
RESULTS
We identified that beneficiaries with CKD stage 3 and at least 1 of the selected comorbidities (CKD stage 3-plus) represented 35.4% of all beneficiaries with CKD stage 3. The CKD stage 3-plus cohort had cost and utilization patterns that were more similar to beneficiaries with CKD stages 4 and 5 than to beneficiaries with CKD stage 3 without the selected comorbidities.
CONCLUSIONS
Our findings demonstrate the use of a claims-based algorithm to identify patients with CKD stage 3 who have high costs and are at risk of disease progression, highlighting a potential subset of patients who might benefit from earlier nephrology intervention.
Topics: Humans; Retrospective Studies; Male; United States; Female; Renal Insufficiency, Chronic; Medicare; Aged; Disease Progression; Comorbidity; Cost of Illness; Fee-for-Service Plans; Aged, 80 and over; Severity of Illness Index; Kidney Failure, Chronic; Referral and Consultation
PubMed: 38912931
DOI: 10.37765/ajmc.2024.89564 -
The American Journal of Managed Care Jun 2024This analysis examines the implications of new Alzheimer disease drugs in the era of the Inflation Reduction Act (IRA). It focuses on balancing innovation in Alzheimer... (Review)
Review
OBJECTIVES
This analysis examines the implications of new Alzheimer disease drugs in the era of the Inflation Reduction Act (IRA). It focuses on balancing innovation in Alzheimer disease treatment with affordability and access, assessing the impact on Medicare's budget, patient cost, and health care system readiness.
STUDY DESIGN
A comprehensive review was conducted, synthesizing information from recent FDA drug approvals, drug pricing models, Medicare coverage policies, and the updated regulations under the IRA. This analysis reflects on the broader clinical and economic consequences of introducing new Alzheimer disease treatments.
METHODS
The study employs a qualitative review of existing literature, policy documents, and economic data. It explores the implications of Alzheimer disease drugs on health care policy, analyzing the economic and clinical impacts within the current health care landscape in the US.
RESULTS
The study highlights the economic challenges posed by the high costs of new Alzheimer disease drugs, contrasting with their moderate clinical benefits and potential risks. It discusses the limitations of the IRA in regulating drug prices and the resulting implications for Medicare's budget. Additionally, it examines disparities in health care access and system preparedness for these new treatments.
CONCLUSIONS
The study findings underscore the need for a comprehensive approach to ensure fair pricing and equitable access to Alzheimer disease treatments. It suggests the application of frameworks such as the ISPOR Value Flower, focusing on diversity, equity, and comprehensive economic evaluations, to navigate the evolving landscape of Alzheimer disease treatment in the context of the IRA.
Topics: Alzheimer Disease; Humans; United States; Medicare; Health Services Accessibility; Drug Costs; Drug Approval
PubMed: 38912930
DOI: 10.37765/ajmc.2024.89563 -
National Health Statistics Reports Jun 2024Objectives-This report examines changes in telemedicine use among U.S. adults between 2021 and 2022 by selected sociodemographic and geographic characteristics....
Objectives-This report examines changes in telemedicine use among U.S. adults between 2021 and 2022 by selected sociodemographic and geographic characteristics. Methods-Data from the 2021 and 2022 National Health Interview Survey were used to assess changes between these 2 years in the percentage of adults who used telemedicine in the previous 12 months, by sex, age, race and Hispanic origin, family income, education, region of residence, urbanization level, and health insurance coverage. Results-Overall, the percentage of adults who used telemedicine in the past 12 months decreased from 37.0% in 2021 to 30.1% in 2022. This pattern was observed across several sociodemographic and geographic characteristics, such as sex, family income, education, region, and urbanization level. Women, adults with a college degree or higher, and adults living in more urban areas were all more likely to use telemedicine in 2022. In 2021 and 2022, uninsured adults ages 18-64 were less likely to use telemedicine compared with those who had private or public insurance, while adults age 65 and older who had Medicare only were less likely to use telemedicine compared with those with other types of insurance. However, for both age groups, telemedicine use decreased from 2021 to 2022 for all insurance types except public coverage for adults ages 18-64. Summary-National Health Interview Survey data may be used to monitor national trends and understand patterns of telemedicine use by sociodemographic and geographic characteristics as the transition forward from the global COVID-19 pandemic continues.
Topics: Humans; Telemedicine; United States; Adult; Middle Aged; Female; Male; Young Adult; Adolescent; Aged; Insurance Coverage; COVID-19; Insurance, Health; Socioeconomic Factors; Health Surveys; Sociodemographic Factors
PubMed: 38912919
DOI: No ID Found -
Access to insurance navigation support through the State Health Insurance Assistance Program (SHIP).Health Affairs Scholar Jun 2024Medicare enrollment is complex, particularly for low-income individuals who are dually eligible for Medicare and Medicaid, and the wrong plan choice can adversely impact...
Medicare enrollment is complex, particularly for low-income individuals who are dually eligible for Medicare and Medicaid, and the wrong plan choice can adversely impact beneficiaries' out-of-pocket costs and access to providers and medications. The State Health Insurance Assistance Program (SHIP) is a federal program that provides counseling on Medicare coverage, but the degree to which SHIP services are accessible to low-income beneficiaries is unknown. We interviewed SHIP counselors and coordinators to characterize factors affecting access to and quality of SHIP services for low-income beneficiaries. Availability of volunteers was cited as the primary barrier to SHIP services. Topics related to dual eligibility for Medicare and Medicaid were frequently covered in counseling sessions, and staff expressed a desire for more training related to Medicaid and integrated-care programs. Our results suggest that additional counselors and increased training on topics relevant to dually eligible individuals may improve SHIP's ability to provide health insurance-related information to low-income Medicare beneficiaries.
PubMed: 38911681
DOI: 10.1093/haschl/qxae072 -
JAMIA Open Jul 2024Anaphylaxis is a severe life-threatening allergic reaction, and its accurate identification in healthcare databases can harness the potential of "Big Data" for...
OBJECTIVES
Anaphylaxis is a severe life-threatening allergic reaction, and its accurate identification in healthcare databases can harness the potential of "Big Data" for healthcare or public health purposes.
MATERIALS AND METHODS
This study used claims data obtained between October 1, 2015 and February 28, 2019 from the CMS database to examine the utility of machine learning in identifying incident anaphylaxis cases. We created a feature selection pipeline to identify critical features between different datasets. Then a variety of unsupervised and supervised methods were used (eg, Sammon mapping and eXtreme Gradient Boosting) to train models on datasets of differing data quality, which reflects the varying availability and potential rarity of ground truth data in medical databases.
RESULTS
Resulting machine learning model accuracies ranged from 47.7% to 94.4% when tested on ground truth data. Finally, we found new features to help experts enhance existing case-finding algorithms.
DISCUSSION
Developing precise algorithms to detect medical outcomes in claims can be a laborious and expensive process, particularly for conditions presented and coded diversely. We found it beneficial to filter out highly potent codes used for data curation to identify underlying patterns and features. To improve rule-based algorithms where necessary, researchers could use model explainers to determine noteworthy features, which could then be shared with experts and included in the algorithm.
CONCLUSION
Our work suggests machine learning models can perform at similar levels as a previously published expert case-finding algorithm, while also having the potential to improve performance or streamline algorithm construction processes by identifying new relevant features for algorithm construction.
PubMed: 38911332
DOI: 10.1093/jamiaopen/ooae037 -
Cureus May 2024Amidst the coronavirus disease 2019 (COVID-19) pandemic, the sudden demand for virtual medical visits drove the expansion of telemedicine across all medical...
BACKGROUND
Amidst the coronavirus disease 2019 (COVID-19) pandemic, the sudden demand for virtual medical visits drove the expansion of telemedicine across all medical specialties. Current literature demonstrates limited knowledge of the impact of telehealth on appointment adherence, particularly in preoperative anesthesia evaluations. This study aims to describe the impact of telemedicine-based anesthesia evaluation and its effects on appointment completion. Methods: This was a retrospective, non-randomized, cohort study of adult patients at the University of California, Los Angeles, United States, who received preoperative anesthesia evaluations by telemedicine or in-person in an academic medical center. From January to September 2021, we evaluated telemedicine and in-person appointment completion in patients scheduled for surgery. The primary outcome was the incidence of appointment completion. The secondary outcomes included appointment no-shows and cancellations. Results: Of 1332 patients included in this study, 956 patients received telehealth visits while 376 patients received in-person preoperative anesthesia evaluations. Compared to the in-person group, the telemedicine group had more appointment completions (81.38% vs 76.60%), fewer cancellations (12.55% vs 19.41%), and no statistical difference in appointment no-shows (6.07% vs 3.99%). Compared to the in-person group, patients who received telemedicine evaluations were younger (55.81 ± 18.38 vs 65.97 ± 15.19), less likely Native American and Alaska Native (0.31% vs 1.60%), more likely of Hispanic or Latino ethnicity (16.63% vs 12.23%), required less interpreter services (4.18% vs 9.31%), had more private insurance coverage (53.45% vs 37.50%) and less Medicare coverage (37.03% vs 50.53%).
CONCLUSIONS
This study demonstrates that telemedicine can improve preoperative anesthesia appointment completion and decrease appointment cancellations. We also demonstrate potential shortcomings of telemedicine in serving patients who are older, require interpreter services, or are non-privately insured. These inequities highlight potential avenues to increase equity and access to telemedicine.
PubMed: 38910741
DOI: 10.7759/cureus.60805 -
Journal of the American Medical... Jun 2024This article proposes a framework for examining the ethical and legal concerns for using artificial intelligence (AI) in post-acute and long-term care (PA-LTC). It...
This article proposes a framework for examining the ethical and legal concerns for using artificial intelligence (AI) in post-acute and long-term care (PA-LTC). It argues that established frameworks on health, AI, and the law should be adapted to specific care contexts. For residents in PA-LTC, their social, psychological, and mobility needs should act as a gauge for examining the benefits and risks of integrating AI into their care. Using those needs as a gauge, 4 areas of particular concern are identified. First, the threat that AI poses to the autonomy of residents can undermine their core needs. Second, how discrimination and bias in algorithmic decision-making can undermine Medicare coverage for PA-LTC, causing doctors' recommendations to be ignored and denying residents the care they are entitled to. Third, privacy rules concerning data use may undermine developers' ability to train accurate AI systems, limiting their usefulness in PA-LTC contexts. Fourth, the importance of obtaining consent before AI is used and discussions about how that care should continue if there are concerns about an ongoing decline in cognition. Together, these considerations elevate existing frameworks and adapt them to the context-specific case of PA-LTC. It is hoped that future research will examine the legal implications of these matters in each of these specific cases.
PubMed: 38909630
DOI: 10.1016/j.jamda.2024.105105 -
Annals of Palliative Medicine Jun 2024Radiofrequency ablation (RFA), a minimally invasive procedure for pain reduction, is increasingly used for managing chronic neck pain and headaches. This article offers...
Radiofrequency ablation (RFA), a minimally invasive procedure for pain reduction, is increasingly used for managing chronic neck pain and headaches. This article offers a concise overview of cervical spine RFA. In the context of RFA, heat is applied to specific nerve tissues to interrupt pain signals. Wallarian degeneration occurs as a result of the thermal injury to the nerve. The heat generated by the RFA procedure can damage the nerve fibers, initiating the degenerative process. Wallarian degeneration is a process that occurs in a nerve axon due to the thermal injury, leading to the breakdown and eventual degradation of the axon and its myelin sheath. However, nerves have regeneration capacity, especially the peripheral nerves, which are often the target of RFA for pain management. After Wallarian degeneration takes place, the nerve sheath, or the connective tissue surrounding the nerve, can serve as a scaffold for the growth of new nerve fibers. Over time, these new fibers can regenerate and re-establish connections, potentially restoring nerve function. Three common types are traditional thermal, water-cooled, and pulsed radio frequency ablation. Given the regenerative potential of nerves, these procedures are typically effective for 1 to 2 years, with some variability. Despite a 112% increase in Medicare claims for RFA from 2009 to 2018, it's recommended for patients who respond positively to diagnostic medial branch blocks, with recent guidelines suggesting a single block may be sufficient. Although generally effective, the procedure carries risks, including nerve and tissue injury. Notably, the procedure's increased utilization notably surpasses the most commonly reported prevalence rates of conditions it aims to treat. Moreover, diagnostic blocks performed before cervical RFA also have their risks, such as inadvertent vascular injections leading to seizures or paralysis. In summary, the risks and benefits of cervical RFA must be considered with regards to the patient's comorbidities and specific pain issues. The skill and experience of the practitioner plays a significant role in minimizing these risks. Detailed discussions with healthcare providers about the risks, benefits, and alternatives can help in making an informed decision about the procedure.
PubMed: 38902987
DOI: 10.21037/apm-23-520