American Journal of Managed Care最新文献

Objectives: To assess whether discharging hospitals' self-reported care transition activities (CTAs) were associated with transitional care management (TCM) claims following discharge to the community and whether CTAs and TCM were associated with better patient outcomes.

Study design: Cross-sectional study of 424,115 hospitalized Medicare fee-for-service beneficiaries 66 years and older who were discharged to the community in 2017 and attributed to 659 hospitals in the 2017-2018 National Survey of Healthcare Organizations and Systems (response rate, 46.5%). Of these beneficiaries, 76,156 were categorized into a Hospital Readmissions Reduction Program (HRRP) cohort based on admission principal diagnoses.

Methods: Using logistic regression, we examined the association between survey-based hospital-reported CTAs and an attributed beneficiary's TCM claim. We assessed the associations between hospital CTAs and TCM and beneficiary spending, utilization, and mortality in linear (continuous outcomes) and logistic (binary outcomes) regressions.

Results: Beneficiaries attributed to hospitals reporting high (top tertile vs bottom tertile) CTA had a higher probability of TCM after discharge by 3 percentage points. TCM was associated with lower 90-day episode spending (-$2803; P < .001) and improved quality (-28.7 30-day readmissions/1000 beneficiaries; P < .001; -29.7 deaths/1000 beneficiaries; P < .001), and greater use of evaluation and management visits (491/1000 beneficiaries; P = .001). Billing for TCM was associated with significantly lower spending, emergency department visits, hospitalizations, readmissions, and 90-day mortality in the HRRP cohort. Significant utilization reductions were estimated for beneficiaries attributed to high-CTA hospitals.

Conclusions: Beyond recent increases in provider TCM compensation and relaxed billing restrictions, hospitals should be encouraged to increase CTA and to enhance care transitions to improve patient outcomes and lower spending.

Objective: To explore the knowledge, attitudes, and practices (KAP) in regard to ChatGPT among health care professionals (HCPs).

Study design: Cross-sectional study.

Methods: This web-based cross-sectional study included HCPs working at the First Affiliated Hospital of Anhui Medical University in China between August 2023 and September 2023. Participants unwilling to use ChatGPT were excluded. Correlations between KAP scores were evaluated by Pearson correlation analysis and structural equation modeling (SEM).

Results: A total of 543 valid questionnaires were collected; of these, 231 questionnaires (42.54%) were completed by male HCPs. Mean (SD) knowledge, attitude, and practice scores were 6.71 (3.24) (range, 0-12), 21.27 (2.73) (range, 6-30), and 47.91 (8.17) (range, 12-60), respectively, indicating poor knowledge (55.92%), positive attitudes (70.90%), and proactive practices (79.85%). The knowledge scores were positively correlated with attitude (Pearson r = 0.216; P < .001) and practice (Pearson r = 0.283; P < .001) scores, and the attitude scores were positively correlated with practice scores (Pearson r = 0.479; P < .001). SEM showed that knowledge influenced attitude positively (β = 0.498; P < .001) but negatively influenced practice part 1 (improving work efficiency and patient experience) (β = -0.301; P < .001), practice part 2 (helping advance medical research) (β = -0.436; P < .001), practice part 3 (assisting HCPs) (β = -0.338; P  < .001), and practice part 4 (the possibilities) (β = -0.242; P < .001). Attitude positively influenced practice part 1 (β = 1.430; P  < .001), practice part 2 (β = 1.581; P < .001), practice part 3 (β = 1.513; P < .001), and practice part 4 (β = 1.387; P < .001).

Conclusion: HCPs willing to use ChatGPT in China showed poor knowledge, positive attitudes, and proactive practices regarding ChatGPT.

Objectives: Most Americans have insurance that uses managed care arrangements. Regulators have long sought to ensure access to care through network adequacy regulations. However, consumers have largely been excluded from conversations about network adequacy. To our knowledge, our study is the first to assess consumer preferences for various definitions of network adequacy including those aimed at supporting health equity and reducing disparities.

Study design: We fielded a large and demographically diverse survey of US adults (N = 4008) from June 30 to July 2, 2023. The survey queried respondents about their perceptions of what adequate provider networks look like in the abstract.

Methods: Analyses were conducted using ordinary least squares regression with survey weights as well as t tests.

Results: Consumers were overwhelmingly supportive of standard definitions of adequacy focused on the number of providers and travel distance. Majorities also favored more expansive, health equity-focused definitions such as public transportation access, cultural competency, and lesbian, gay, bisexual, and transgender (LGBT+)-inclusive care. Being a woman; having higher levels of education, worse health, and recent experiences with the medical system; and ease of completing administrative tasks were relatively consistent positive predictors of supporting more expansive definitions. More controversial definitions saw effects of partisanship and LGBT+ identification. Rurality, insurance status, education, and recent experiences with the medical system affected perceptions of reasonable appointment wait times and travel distances.

Conclusions: Our findings indicate that consumers have broad conceptions of network adequacy. Future work should assess consumer trade-offs in resource-constrained settings as well as perceptions of providers and carriers.

This article examines how predictive analytics can enhance payer initiatives to improve medication adherence. Despite its known impact on health outcomes and costs, medication nonadherence remains a widespread and persistent challenge in health care. Although payers are increasingly involved in addressing nonadherence, traditional approaches typically lead to suboptimal results due to their reactive nature and generic intervention. With improved access to data and more sophisticated machine learning tools, there is a growing opportunity for payers to use predictive analytics to stratify and target members at high risk, predict potential primary and secondary nonadherence, and preemptively intervene with tailored solutions. The potential benefit of this approach includes prevention, not only resolution, of nonadherence and leads to improved health outcomes, reduced health care costs, and increased member satisfaction. The article also discusses potential caveats to consider, such as data sharing, bias mitigation, and regulatory compliance, when implementing predictive analytics in this context.

Objective: Patients with type 2 diabetes (T2D) are at high risk for developing chronic kidney disease (CKD). The onset of incident CKD may complicate glycemic control among these patients. This study aimed to characterize antihyperglycemic medication use after incident CKD onset among patients with T2D to inform disease management.

Study design: Retrospective cohort study.

Methods: Patients with incident CKD and prior T2D were identified from the Optum electronic health records database between March 2013 and September 2021. Patterns of antihyperglycemic use were assessed during the 1-year baseline period and after incident CKD diagnosis and described by baseline hemoglobin A1C (HbA1C) level (controlled [< 7%] vs elevated [≥ 7%]) and CKD severity.

Results: The study consisted of 262,395 patients, of whom 51% had elevated HbA1C. After CKD onset, 23.9% of patients initiated new antihyperglycemics within 1 year. Patients with elevated HbA1C had shorter time to new treatment initiation compared with those with controlled HbA1C (median, 28.7 vs 83.7 months). Patients with elevated urine albumin-to-creatinine ratio (uACR) had shorter median time to new treatment initiation (39.9-42.4 months) than those with normal uACR (59.8 months). Less than 7% of patients with stage 3 CKD and even smaller percentages of patients with higher stages of CKD utilized glucagon-like peptide 1 receptor agonists and sodium-glucose cotransporter 2 inhibitors.

Conclusions: Treatment of T2D was considerably heterogenous by HbA1C level and CKD severity in patients with incident CKD. Current agents may not sufficiently fulfill the unmet need of T2D management in patients with CKD.

Objectives: Despite chronic obstructive pulmonary disease (COPD) being a leading cause of death in the US, there are few COPD measures in current quality programs. The objective of this study was to assess the validity and applicability of the COPD treatment ratio (CTR) as a surrogate marker of COPD exacerbation risk for use in quality measurement. CTR is defined as the ratio of COPD maintenance medications to all COPD medications (maintenance and rescue).

Study design: This retrospective cohort study used 2016-2019 administrative claims from Optum Clinformatics Data Mart to evaluate CTR values over a 12-month baseline period, with exacerbations measured the following year. Patients 40 years or older with Medicare Advantage or commercial insurance and with a COPD diagnosis were included.

Methods: Logistic regression models were used to examine relationships between CTR values and COPD exacerbations. Prediction model performance was evaluated using C statistics, and receiver operating characteristics were used to determine the optimal cut point for CTR.

Results: Of 132,960 patients included in the analysis, 79.5% were Medicare Advantage beneficiaries, and the mean age was 69.6 years. Higher CTR values were significantly associated with reduced risk of any, moderate, and severe exacerbations in the total population and when stratified by insurance type. CTR performed fairly to moderately well in predicting COPD exacerbations. The optimal cut point for COPD exacerbation prediction was 0.7.

Conclusions: Study results substantiated CTR as a valid measure of COPD exacerbation risk and support the use of CTR in quality improvement to drive evidence-based care for individuals with COPD.

The US faces a maternal health crisis as overall maternal mortality rates continue to worsen. HHS, in its Healthy People 2030 report, indicates that women in the US are more likely to die from childbirth than are women in other developed countries. The cost of the maternal health crisis and its associated morbidities is estimated to be $32.3 billion from conception to 5 years postpartum, with $18.7 billion in medical costs and $13.6 billion in nonmedical costs. Under the current health care reimbursement system, health care providers alone have little short-term incentive to bear the cost for solutions or prevention strategies that could change the social and cultural factors affecting maternal outcomes. This article provides an overview of the crisis, along with its economic and societal costs, and the role of prenatal care and premature birth in this escalating problem. The article then proposes maternal navigation for pregnant patients who chronically miss prenatal care appointments as one way to reduce premature births and associated health care costs. Through intentional and focused investment in maternal navigation by payers and providers together, health outcomes can be improved and disparities can be reduced. As a result, payer and provider costs are reduced and the interests of all parties are advanced. A connected system of support that improves health outcomes and reduces health care costs for the most at-risk patients is an essential response to a crisis that affects not only the individual but also society.

Objectives: The number of commercial beneficiaries cared for by accountable care organizations (ACOs) is growing, but the literature examining their trends is nascent.

Study design: We examined commercial claims data from 2019 to 2021 to compare beneficiaries attributed to participants in Medicare Shared Savings Program ACOs with and without a major teaching hospital.

Methods: We calculated mortality and spending by setting for each ACO type by year.

Results: Compared with per-beneficiary rates at nonteaching ACOs, major teaching ACOs have lower mortality rates by up to 2.2 percentage points depending on the patient age group, $283 lower inpatient spending, and lower emergency department utilization in inpatient (-0.008) and outpatient (-0.013) settings, as well as $146 higher overall outpatient spending. Upward trends in mortality and beneficiary risk scores across both ACO types show disruption to health outcomes during COVID-19.

Conclusions: These results provide evidence that ACOs with major teaching hospitals may be more likely to achieve the value-based goals of ACOs. Means to accomplish those goals may include avoiding higher-intensity care and supporting access to lower-cost alternatives where clinically appropriate, such as reducing inpatient and emergency department stays by delivering timely, high-quality outpatient care.

The COVID-19 pandemic accelerated telehealth expansion trends as policy makers instituted flexibilities and coverage changes. Federal telehealth flexibilities expire, however, at the end of 2024. To decide whether to extend those flexibilities, policy makers need information about consumer telehealth preferences, impacts of telehealth on care usage and quality, and telehealth accessibility for the full diversity of patients. Research from one of the nation's largest integrated, value-based health systems provides insights. Findings suggest that telehealth utilization has dropped since the peak of the pandemic but remains higher than prepandemic levels. Telehealth appears to be replacing in-person visits rather than leading to more total visits. Patients generally prefer in-person care but many like having the option to use video- and phone-based telehealth, and both video- and phone-based care appear to be helping patients access primary care. An integrated, value-based care approach may assist a diverse range of patients in accessing telehealth services. Action is still needed, however, to ensure that the full diversity of patients can easily access telehealth offerings. Based on experiences within our health system, we recommend that policy makers maintain public and private payer coverage for video- and phone-based telehealth services; encourage well-designed value-based payment models to simplify and expand telehealth access; improve broadband accessibility and broadband and device affordability so that all patients can access telehealth services; and hold digital health to equivalent high standards for care quality, safety, patient satisfaction, clinical outcomes, and health equity as in-person care.

Objectives: The high costs of cancer care can cause significant harm to patients and society. Prostate cancer, the leading nonskin malignancy in men, is responsible for the second-highest out-of-pocket (OOP) payments among all malignancies. Multiple first-line treatment options exist for metastatic castration-resistant prostate cancer (mCRPC); although their costs vary substantially, comparative effectiveness data are limited. There is little evidence of how gross payments made by insurers and OOP payments made by patients differ by treatment and health plan type and how these payment differences relate to utilization.

Study design: Retrospective cohort study.

Methods: We used IBM MarketScan databases from 2013-2019 to identify men with prostate cancer who initiated treatment with 1 of 6 drugs approved for first-line treatment of mCRPC. We calculated and compared gross and OOP payments and drug utilization across drug and insurance plan types.

Results: We identified 4298 patients who met our inclusion criteria. Insurer payments varied substantially by first-line therapy but were similar across different health plan types, except for docetaxel. OOP payments for a given first-line therapy, in contrast, varied by health plan type. Utilization of first-line therapies varied by plan type in unadjusted analyses, but not after adjusting for patient characteristics.

Conclusions: The extent to which patient OOP payments for drugs reflect differences in gross payments made by insurers varies across health insurance plan types. However, even though OOP payments for the same treatment differ across plan types, treatment choice is not significantly different across type of health insurance after controlling for patient characteristics.