Nevin Manimala

Am J Manag Care. 2024 May;30(5):230-236. doi: 10.37765/ajmc.2024.89540.

ABSTRACT

OBJECTIVES: Regular users of the emergency department (ED) include both patients who could be better served in lower-acuity settings and those with high-severity conditions. ED use decreased during the COVID-19 pandemic, but patterns among regular ED users are unknown. To determine the impact of the COVID-19 pandemic on this population, we examined quarterly postpandemic ED utilization among prepandemic regular ED users. Key subgroups included prepandemic ED users with regular visits for (1) low-severity conditions and (2) high-severity conditions.

STUDY DESIGN: An event study design with COVID-19 and historic controls cohorts.

METHODS: We identified 4710 regular ED users at baseline and followed their ED utilization for 7 quarters. We used a generalized estimating equations model to compare the relative quarterly percent difference in ED visit rates between the COVID-19 and historic controls cohorts.

RESULTS: The first postpandemic quarter was associated with the largest decline in ED visits, at -36.0% (95% CI, -42.0% to -29.3%) per regular ED user overall, -52.2% (95% CI, -69.4% to -25.3%) among high-severity users, and -29.6% (95% CI, -39.8% to -17.8%) among low-severity users. However, use did not statistically differ from expected levels after 5 quarters among all regular ED users, 1 quarter among high-severity users, and 3 quarters among regular low-severity users.

CONCLUSIONS: Initial reductions among regular high-severity ED users raise concern for harm from delayed or missed care but did not result in increased high-severity visits later. Nonsustained declines among regular low-severity ED users suggest barriers to and opportunities for redirecting nonurgent ED use to lower-acuity settings.

PMID:38748930 | DOI:10.37765/ajmc.2024.89540

Am J Manag Care. 2024 May;30(5):218-223. doi: 10.37765/ajmc.2024.89539.

ABSTRACT

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.

PMID:38748929 | DOI:10.37765/ajmc.2024.89539

Am J Manag Care. 2024 May;30(5):210-217. doi: 10.37765/ajmc.2024.89538.

ABSTRACT

OBJECTIVE: To examine the association between missed CMS Star Ratings quality measures for medication adherence over 3 years for diabetes, hypertension, and hyperlipidemia medications (9 measures) and health care utilization and relative costs.

STUDY DESIGN: Retrospective cohort study.

METHODS: The study examined eligible patients who qualified for the diabetes, statin, and renin-angiotensin system antagonist medication adherence measures in 2018, 2019, and 2020 and were continuously enrolled in a Medicare Advantage prescription drug plan from 2017 through 2021. A total of 103,900 patients were divided into 4 groups based on the number of adherence measures missed (3 medication classes over 3 years): (1) missed 0 measures, (2) missed 1 measure, (3) missed 2 or 3 measures, and (4) missed 4 or more measures. To achieve a quality measure, patients had to meet the Pharmacy Quality Alliance 80% threshold of proportion of days covered during the calendar year.

RESULTS: The mean age of the cohort was 71.1 years, and 49.9% were female. Compared with patients who missed 0 of 9 adherence measures, those who missed 1 measure, 2 or 3 measures, and 4 or more measures experienced 12% to 26%, 22% to 42%, and 24% to 50% increased risks, respectively, of all-cause and diabetes-related inpatient stays and all-cause and diabetes-related emergency department visits (all P values < .01). Additionally, patients who missed 1, 2 or 3, and 4 or more adherence measures experienced 14%, 19%, and 20% higher monthly medical costs, respectively.

CONCLUSIONS: Missing Star Ratings quality measures for medication adherence was associated with an increased likelihood of health care resource utilization and increased costs for patients taking medications to treat diabetes, hypertension, and hyperlipidemia.

PMID:38748928 | DOI:10.37765/ajmc.2024.89538

Am J Manag Care. 2024 May 1;30(5):e165-e168. doi: 10.37765/ajmc.2024.89544.

ABSTRACT

OBJECTIVES: Given the problematic fragmentation of care for patients with end-stage kidney disease (ESKD), a kidney care organization and an integrated health system within a large accountable care organization partnered to best utilize their individual capabilities to collaborate around their shared patients in a coordinated care approach. Ultimately, the goal of the program is to allow care teams to achieve the triple aim of improving the patient experience, improving clinical outcomes, and reducing the total cost of health care.

STUDY DESIGN: This is a retrospective examination of the first year of the Shared Patient Care Coordination (SPCC) program.

METHODS: The analysis consisted of 2 parts. First, rates of hospitalizations and emergency department visits were compared between the SPCC patients and other patients of the integrated health system who had ESKD but did not participate in SPCC. Second, rates of clinical indicators-central venous catheter (CVC) use, home dialysis, advance care planning, and missed dialysis treatments-were benchmarked vs normative data taken by bootstrap sampling of the kidney care organization’s patient population.

RESULTS: Overall, dialysis patients participating in the SPCC program had a 15% lower rate of hospital admissions than those not participating ( P = .02). Additionally, the bootstrap analysis showed that by the second year, dialysis patients in the program had favorable rates (above the 95th percentile) of CVC use, dialysis treatment absenteeism, and completion of advance care plans.

CONCLUSIONS: Enhanced and structured communication between dialysis providers and patient care teams provides a unique opportunity to coordinate patient-centered care and improve patient outcomes.

PMID:38748917 | DOI:10.37765/ajmc.2024.89544

Am J Manag Care. 2024 May 1;30(5):e147-e156. doi: 10.37765/ajmc.2024.89542.

ABSTRACT

OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative care management (CoCM) models target MDD treatment in primary care, but how best to prioritize patients for CoCM to prevent frequent ED utilization remains unclear. This study aimed to develop and validate a risk identification model to proactively detect patients with MDD in CoCM at high risk of frequent (≥ 3) ED visits.

STUDY DESIGN: This retrospective cohort study utilized electronic health records from Mayo Clinic’s primary care system to develop and validate a machine learning-based risk identification model. The model predicts the likelihood of frequent ED visits among patients with MDD within a 12-month period.

METHODS: Data were collected from Mayo Clinic’s primary care system between May 1, 2006, and December 19, 2018. Risk identification models were developed and validated using machine learning classifiers to estimate frequent ED visit risks over 12 months. The Shapley Additive Explanations model identified variables driving frequent ED visits.

RESULTS: The patient population had a mean (SD) age of 39.78 (16.66) years, with 30.3% being male and 6.1% experiencing frequent ED visits. The best-performing algorithm (elastic-net logistic regression) achieved an area under the curve of 0.79 (95% CI, 0.74-0.84), a sensitivity of 0.71 (95% CI, 0.57-0.82), and a specificity of 0.76 (95% CI, 0.64-0.85) in the development data set. In the validation data set, the best-performing algorithm (random forest) achieved an area under the curve of 0.79, a sensitivity of 0.83, and a specificity of 0.61. Significant variables included male gender, prior frequent ED visits, high Patient Health Questionnaire-9 score, low education level, unemployment, and use of multiple medications.

CONCLUSIONS: The risk identification model has potential for clinical application in triaging primary care patients with MDD in CoCM, aiming to reduce future ED utilization.

PMID:38748915 | DOI:10.37765/ajmc.2024.89542

Braz J Cardiovasc Surg. 2024 May 15;39(4):e20220453. doi: 10.21470/1678-9741-2022-0453.

ABSTRACT

INTRODUCTION: The analysis of patients submitted to heart surgery at three assessment times has been insufficiently described in the literature.

OBJECTIVE: To analyze chest expansion, maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), distance traveled on the six-minute walk test (6MWT), and quality of life in the preoperative period, fourth postoperative day (4th PO), and 30th day after hospital discharge (30th-day HD) in individuals submitted to elective heart surgery.

METHODS: A descriptive, analytical, cross-sectional study was conducted with 15 individuals submitted to elective heart surgery between 2016 and 2020 who did not undergo any type of physiotherapeutic intervention in Phase II of cardiac rehabilitation. The outcome variables were difference in chest expansion (axillary, nipple, and xiphoid), MIP, MEP, distance on 6MWT, and quality of life. The assessment times were preoperative period, 4th PO, and 30th-day HD.

RESULTS: Chest expansion diminished between the preoperative period and 4th PO, followed by an increase at 30th-day HD. MIP, MEP, and distance traveled on the 6MWT diminished between the preoperative period and 4th PO, with a return to preoperative values at 30th-day HD. General quality of life improved between the preoperative period and 4th PO and 30th-day HD. An improvement was found in the social domain between the preoperative period and the 30th-day HD.

CONCLUSION: Heart surgery causes immediate physical deficit, but physical functioning can be recovered 30 days after hospital discharge, resulting in an improvement in quality of life one month after surgery.

PMID:38748911 | DOI:10.21470/1678-9741-2022-0453

Clin Chem Lab Med. 2024 May 16. doi: 10.1515/cclm-2024-0124. Online ahead of print.

ABSTRACT

OBJECTIVES: Patient-based real-time quality control (PBRTQC) is an alternative tool for laboratories that has gained increasing attention. Despite the progress made by using various algorithms, the problems of data volume imbalance between in-control and out-of-control results, as well as the issue of variation remain challenges. We propose a novel integrated framework using anomaly detection and graph neural network, combining clinical variables and statistical algorithms, to improve the error detection performance of patient-based quality control.

METHODS: The testing results of three representative analytes (sodium, potassium, and calcium) and eight independent variables of patients (test date, time, gender, age, department, patient type, and reference interval limits) were collected. Graph-based anomaly detection network was modeled and used to generate control limits. Proportional and random errors were simulated for performance evaluation. Five mainstream PBRTQC statistical algorithms were chosen for comparison.

RESULTS: The framework of a patient-based graph anomaly detection network for real-time quality control (PGADQC) was established and proven feasible for error detection. Compared with classic PBRTQC, the PGADQC showed a more balanced performance for both positive and negative biases. For different analytes, the average number of patient samples until error detection (ANPed) of PGADQC decreased variably, and reductions could reach up to approximately 95 % at a small bias of 0.02 taking calcium as an example.

CONCLUSIONS: The PGADQC is an effective framework for patient-based quality control, integrating statistical and artificial intelligence algorithms. It improves error detection in a data-driven fashion and provides a new approach for PBRTQC from the data science perspective.

PMID:38748888 | DOI:10.1515/cclm-2024-0124

JMIR Public Health Surveill. 2024 May 15;10:e47626. doi: 10.2196/47626.

ABSTRACT

BACKGROUND: Beyond the direct effect of COVID-19 infection on young people, the wider impact of the pandemic on other infectious diseases remains unknown.

OBJECTIVE: This study aims to assess changes in the incidence and mortality of 42 notifiable infectious diseases during the pandemic among children and adolescents in China, compared with prepandemic levels.

METHODS: The Notifiable Infectious Disease Surveillance System of China was used to detect new cases and fatalities among individuals aged 5-22 years across 42 notifiable infectious diseases spanning from 2018 to 2021. These infectious diseases were categorized into 5 groups: respiratory, gastrointestinal and enterovirus, sexually transmitted and blood-borne, zoonotic, and vector-borne diseases. Each year (2018-2021) was segmented into 4 phases: phase 1 (January 1-22), phase 2 (January 23-April 7), phase 3 (April 8-August 31), and phase 4 (September 1-December 31) according to the varying intensities of pandemic restrictive measures in 2020. Generalized linear models were applied to assess the change in the incidence and mortality within each disease category, using 2018 and 2019 as the reference.

RESULTS: A total of 4,898,260 incident cases and 3701 deaths were included. The overall incidence of notifiable infectious diseases decreased sharply during the first year of the COVID-19 pandemic (2020) compared with prepandemic levels (2018 and 2019), and then rebounded in 2021, particularly in South China. Across the past 4 years, the number of deaths steadily decreased. The incidence of diseases rebounded differentially by the pandemic phase. For instance, although seasonal influenza dominated respiratory diseases in 2019, it showed a substantial decline during the pandemic (percent change in phase 2 2020: 0.21, 95% CI 0.09-0.50), which persisted until 2021 (percent change in phase 4 2021: 1.02, 95% CI 0.74-1.41). The incidence of gastrointestinal and enterovirus diseases decreased by 33.6% during 2020 but rebounded by 56.9% in 2021, mainly driven by hand, foot, and mouth disease (percent change in phase 3 2021: 1.28, 95% CI 1.17-1.41) and infectious diarrhea (percent change in phase 3 2020: 1.22, 95% CI 1.17-1.28). Sexually transmitted and blood-borne diseases were restrained during the first year of 2021 but rebounded quickly in 2021, mainly driven by syphilis (percent change in phase 3 2020: 1.31, 95% CI 1.23-1.40) and gonorrhea (percent change in phase 3 2020: 1.10, 95% CI 1.05-1.16). Zoonotic diseases were not dampened by the pandemic but continued to increase across the study period, mainly due to brucellosis (percent change in phase 2 2020: 0.94, 95% CI 0.75-1.16). Vector-borne diseases showed a continuous decline during 2020, dominated by hemorrhagic fever (percent change in phase 2 2020: 0.68, 95% CI 0.53-0.87), but rebounded in 2021.

CONCLUSIONS: The COVID-19 pandemic was associated with a marked decline in notifiable infectious diseases in Chinese children and adolescents. These effects were not sustained, with evidence of a rebound to prepandemic levels by late 2021. To effectively address the postpandemic resurgence of infectious diseases in children and adolescents, it will be essential to maintain disease surveillance and strengthen the implementation of various initiatives. These include extending immunization programs, prioritizing the management of sexually transmitted infections, continuing feasible nonpharmaceutical intervention projects, and effectively managing imported infections.

PMID:38748469 | DOI:10.2196/47626

J Med Internet Res. 2024 May 15;26:e48564. doi: 10.2196/48564.

ABSTRACT

BACKGROUND: The information epidemic emerged along with the COVID-19 pandemic. While controlling the spread of COVID-19, the secondary harm of epidemic rumors to social order cannot be ignored.

OBJECTIVE: The objective of this paper was to understand the characteristics of rumor dissemination before and after the pandemic and the corresponding rumor management and debunking mechanisms. This study aimed to provide a theoretical basis and effective methods for relevant departments to establish a sound mechanism for managing network rumors related to public health emergencies such as COVID-19.

METHODS: This study collected data sets of epidemic rumors before and after the relaxation of the epidemic prevention and control measures, focusing on large-scale network rumors. Starting from 3 dimensions of rumor content construction, rumor propagation, and rumor-refuting response, the epidemic rumors were subdivided into 7 categories, namely, involved subjects, communication content, emotional expression, communication channels, communication forms, rumor-refuting subjects, and verification sources. Based on this framework, content coding and statistical analysis of epidemic rumors were carried out.

RESULTS: The study found that the rumor information was primarily directed at a clear target audience. The main themes of rumor dissemination were related to the public’s immediate interests in the COVID-19 field, with significant differences in emotional expression and mostly negative emotions. Rumors mostly spread through social media interactions, community dissemination, and circle dissemination, with text content as the main form, but they lack factual evidence. The preferences of debunking subjects showed differences, and the frequent occurrence of rumors reflected the unsmooth channels of debunking. The χ² test of data before and after the pandemic showed that the P value was less than .05, indicating that the difference in rumor content before and after the pandemic had statistical significance.

CONCLUSIONS: This study’s results showed that the themes of rumors during the pandemic are closely related to the immediate interests of the public, and the emotions of the public accelerate the spread of these rumors, which are mostly disseminated through social networks. Therefore, to more effectively prevent and control the spread of rumors during the pandemic and to enhance the capability to respond to public health crises, relevant authorities should strengthen communication with the public, conduct emotional risk assessments, and establish a joint mechanism for debunking rumors.

PMID:38748460 | DOI:10.2196/48564

Age Ageing. 2024 May 1;53(5):afae094. doi: 10.1093/ageing/afae094.

ABSTRACT

BACKGROUND: The first wave of COVID led to an alarmingly high mortality rate among nursing home residents (NHRs). In hospitalised patients, the use of anticoagulants may be associated with a favourable prognosis. However, it is unknown whether the use of antithrombotic medication also protected NHRs from COVID-19-related mortality.

OBJECTIVES: To investigate the effect of current antithrombotic therapy in NHRs with COVID-19 on 30-day all-cause mortality during the first COVID-19 wave.

METHODS: We performed a retrospective cohort study linking electronic health records and pharmacy data in NHRs with COVID-19. A propensity score was used to match NHRs with current use of therapeutic dose anticoagulants to NHRs not using anticoagulant medication. The primary outcome was 30-day all-cause mortality, which was evaluated using a logistic regression model. In a secondary analysis, multivariable logistic regression was performed in the complete study group to compare NHRs with current use of therapeutic dose anticoagulants and those with current use of antiplatelet therapy to those without such medication.

RESULTS: We included 3521 NHRs with COVID-19 based on a positive RT-PCR for SARS-CoV-2 or with a well-defined clinical suspicion of COVID-19. In the matched propensity score analysis, NHRs with current use of therapeutic dose anticoagulants had a significantly lower all-cause mortality (OR = 0.73; 95% CI: 0.58-0.92) compared to NHRs who did not use therapeutic anticoagulants. In the secondary analysis, current use of therapeutic dose anticoagulants (OR: 0.62; 95% CI: 0.48-0.82) and current use of antiplatelet therapy (OR 0.80; 95% CI: 0.64-0.99) were both associated with decreased mortality.

CONCLUSIONS: During the first COVID-19 wave, therapeutic anticoagulation and antiplatelet use were associated with a reduced risk of all-cause mortality in NHRs. Whether these potentially protective effects are maintained in vaccinated patients or patients with other COVID-19 variants, remains unknown.

PMID:38748450 | DOI:10.1093/ageing/afae094