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Introduction: Myasthenia gravis (MG) is a neuromuscular disease causing extreme muscular fatigue, triggering problems with vision, swallowing, speech, mobility, dexterity, and breathing. This analysis intended to estimate the health-related quality-of-life impact, the medical burden, and the need for caregiver help of people diagnosed with MG. Methods: MyRealWorld-MG (MRW) is an observational study among adults diagnosed with MG in 9 countries. The General Population Norms (POPUP) observational study enrolled representative members of the general population in 8 countries. In both digital studies, respondents entered personal characteristics and provided data on medical conditions, EQ-5D-5L, HUI3, MG-Activities of Daily Living (MG-ADL), sick leave, caregiver help, and medical care utilization. Results: In MRW (n = 1859), 58.4% of respondents had moderate-to-severe MG. Average utility values were lower in MRW versus POPUP (0.739 vs. 0.843 for EQ-5D-5L; 0.493 vs. 0.746 for HUI3), and declined with more severe disease (0.872, 0.707, 0.511 EQ-5D-5L utilities and 0.695, 0.443, 0.168 HUI3 utilities for mild, moderate, and severe MG, respectively). Taking sick leave in the past month was 2.6 times more frequent among people diagnosed with MG compared to the general population (34.4% vs. 13.2%) and four times more people diagnosed with MG reported needing help from a caregiver (34.8% vs. 8.3%). Use of medical care was twice as likely in MRW in comparison with POPUP (51.9% vs. 24.6%). Conclusion: This direct comparison of people diagnosed with MG and the general population using two large international studies revealed significant negative impact of MG. Results were consistent across all outcomes, in all countries.

Universal health coverage (UHC) is an integral part of the United Nations sustainable development goals. The private sector plays a prominent role in achieving UHC, being the primary source of essential medicines for many people. However, many private healthcare facilities in low- and middle-income countries (LMICs) have insufficient stocks of essential medicines. Simultaneously, these same facilities carry excessive quantities of other drugs, leading to obsolescence. This suggests poor inventory control. To propose potential remedies it is vital to fully understand the underlying causes. In semi-structured interviews with managers of private healthcare facilities in Nairobi, we asked them about their (1) inventory control systems, (2) inventory control skills, (3) time/human resource constraints, (4) budget constraints, (5) motivations for inventory control, and (6) suppliers. Our results suggest that the problems are driven by resource limitations (budget and time/human resources), managerial issues (relating to skills and systems), and market mechanisms that limit overage and underage costs. Unavailability at the supplier level and motivations for inventory control are relatively minor issues. We posit that the key causes are interlinked and stem from wider issues in the market and regulatory environment. Our results challenge prevalent beliefs about medicine supply chains in LMICs and lead to novel hypotheses. Testing these hypotheses could improve our understanding of inventory management in private healthcare facilities and aid progress in achieving UHC.

Background: To estimate the additional impact of coping and of being dependent on caregivers, over and above the large effects of disability on utility after ischemic stroke. Methods: A total of 539 patients were recruited into an observational, retrospective study when returning for a check-up between 3 and 36 months after an ischemic stroke. Patients' modified Rankin Scale (mRS), dependency on caregivers, the Brandtstädter and Renner Coping questionnaire (with summary scores: Tenacity of Goal Pursuit (TGP) and Flexible Goal Adjustment (FGA) coping styles), EQ-5D-3 L and co-morbidities were evaluated. Results: In multivariable regression, greater disability (mRS) resulted in large utility losses, between 0.06 for mRS 1 to 0.65 for mRS 5 (p < 0.0001). Dependency on caregivers caused an additional dis-utility of 0.104 (p = 0.0006) which varied by mRS (0.044, 0.060, 0.083, 0.115, 0.150 and 0.173 for mRS 0-5). The effect of coping on utility varied by coping style, by the disability level of the patient and by his or her dependency on caregivers. FGA coping was associated with additional increases in utility (p < 0.0001) over and above the effect of disability and dependency, whereas TGA had no significant impact. FGA coping was associated with larger utility changes among more disabled patients (0.018 to 0.105 additional utility, for mRS 0 to mRS 5 respectively). Dependent patients had more to gain from FGA coping than patients who function independently of caregivers: utility gains were between 0.049 and 0.072 for moderate to high levels of FGA coping. In contrast, the same positive evolution in FGA coping resulted in 0.039 and 0.057 utility gain among independent patients. Finally, we found that important stroke risk factors and co-morbidities, such as diabetes and atrial fibrillation, were not predictors of EQ-5D utility in a multivariable setting. Conclusions: This study suggests that treatment strategies targeting flexible coping styles and decreasing

BACKGROUND: Several Western and Arab countries, as well as over 30 States in the US are using the "All-Patient Refined Diagnosis-Related Groups" (APR-DRGs) with four severity-of-illness (SOI) subcategories as a model for hospital funding. The aim of this study is to verify whether this is an adequate model for funding stroke hospital admissions, and to explore which risk factors and complications may influence the amount of funding. METHODS: A bottom-up analysis of 2496 ischaemic stroke admissions in Belgium compares detailed in-hospital resource use (including length of stay, imaging, lab tests, visits and drugs) per SOI category and calculates total hospitalisation costs. A second analysis examines the relationship between the type and location of the index stroke, medical risk factors, patient characteristics, comorbidities and in-hospital complications on the one hand, and the funding level received by the hospital on the other hand. This dataset included 2513 hospitalisations reporting on 35,195 secondary diagnosis codes, all medically coded with the International Classification of Disease (ICD-9). RESULTS: Total costs per admission increased by SOI (€3710-€16,735), with severe patients costing proportionally more in bed days (86%), and milder patients costing more in medical imaging (24%). In all resource categories (bed days, medications, visits and imaging and laboratory tests), the absolute utilisation rate was higher among severe patients, but also showed more variability. SOI 1-2 was associated with vague, non-specific stroke-related ICD-9 codes as primary diagnosis (71-81% of hospitalisations). 24% hospitalisations had, in addition to the primary diagnosis, other stroke-related codes as secondary diagnoses. Presence of lung infections, intracranial bleeding, severe kidney disease, and do-not-resuscitate status were each associated with extreme SOI (p < 0.0001). CONCLUSIONS: APR-DRG with SOI subclassification is a useful funding model as it clusters strok