RESUMO
There is a knowledge gap concerning the proper timing for COVID-19 vaccination in cancer patients undergoing chemotherapy. We aimed to evaluate the suitability of the guidelines that recommend waiting at least three months after undergoing chemotherapy before receiving a COVID-19 vaccine. This retrospective cohort study used aggregated data from the TriNetX US Collaboratory network. Participants were grouped into two groups based on the interval between chemotherapy and vaccination. The primary outcome assessed was infection risks, including COVID-19; skin, intra-abdominal, and urinary tract infections; pneumonia; and sepsis. Secondary measures included healthcare utilization and all causes of mortality. Kaplan-Meier analysis and the Cox proportional hazard model were used to calculate the cumulative incidence and hazard ratio (HR) and 95% confidence intervals for the outcomes. The proportional hazard assumption was tested with the generalized Schoenfeld approach. Four subgroup analyses (cancer type, vaccine brand, sex, age) were conducted. Sensitivity analyses were performed to account for competing risks and explore three distinct time intervals. Patients receiving a vaccine within three months after chemotherapy had a higher risk of COVID-19 infection (HR: 1.428, 95% CI: 1.035-1.970), urinary tract infection (HR: 1.477, 95% CI: 1.083-2.014), and sepsis (HR: 1.854, 95% CI: 1.091-3.152) compared to those who adhered to the recommendations. Hospital inpatient service utilization risk was also significantly elevated for the within three months group (HR: 1.692, 95% CI: 1.354-2.115). Adhering to a three-month post-chemotherapy waiting period reduces infection and healthcare utilization risks for cancer patients receiving a COVID-19 vaccine.
RESUMO
OBJECTIVES: Hospital closures became a prevalent phenomenon in Taiwan after the implementation of a national health insurance program. A wide range of causes contributes to the viability of hospitals, but little is known about the situation under universal coverage health systems. The purpose of present study is to recognize the factors that may contribute to hospital survival under the universal coverage health system. STUDY DESIGN: This is a retrospective case-control study. Local community hospitals that contracted with the Bureau of National Health Insurance in 1998 and remained open during the period 1998-2011 are the designated cases. Controls are local community hospitals that closed during the same period. METHODS: Using longitudinal representative health claim data, 209 local community hospitals that closed during 1998-2011 were compared with 165 that remained open. Variables related to institutional characteristics, degree of competition, characteristics of patients and financial performance were analyzed by logistic regression models. RESULTS: Hospitals' survival was positively related to specialty hospital, the number of respiratory care beds, the physician to population ratio, the number of clinics in the same region, a highly competitive market and the occupancy rate of elderly patients in the hospital. Teaching hospitals, investor-owned hospitals, the provision of obstetrics services or home care, and the number of medical centers or other local community hospitals may jeopardize the chance of survival. CONCLUSIONS: Factors-enhanced local hospitals to survive under the universal coverage health system have been identified. Hospital managers could manipulate these findings and adapt strategies for subsistence.
Assuntos
Hospitais Comunitários/estatística & dados numéricos , Cobertura Universal do Seguro de Saúde/estatística & dados numéricos , Fatores Etários , Estudos de Casos e Controles , Competição Econômica , Humanos , Estudos Longitudinais , Características de Residência , Estudos Retrospectivos , Fatores SocioeconômicosRESUMO
INTRODUCTION: To test the hypothesis that the distribution of healthcare services is according to health need can be achieved under a rather open access system. METHODS: The 2001 National Health Interview Survey of Taiwan and National Health Insurance claims data were linked in the study. Health need was defined by self-perceived health status. We used Concentration index to measure need-related inequality in healthcare utilization and expenditure. RESULTS: People with greater health need received more healthcare services, indicating a pro-need character of healthcare distribution, conforming to the meaning of vertical equity. For outpatient service, subjects with the highest health need had higher proportion of ever use in a year than those who had the least health need and consumed more outpatient visits and expenditures per person per year. Similar patterns were observed for emergency services and hospitalization. The concentration indices of utilization for outpatient, emergency services, and hospitalization suggest that the distribution of utilization was related to health need, whereas the preventive service was less related to need. CONCLUSIONS: The universal coverage plus healthcare networking system makes it possible for healthcare to be utilized according to need. Taiwan's experience can serve as a reference for health reform.
Assuntos
Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Necessidades e Demandas de Serviços de Saúde/estatística & dados numéricos , Serviços de Saúde/estatística & dados numéricos , Disparidades em Assistência à Saúde/estatística & dados numéricos , Adulto , Feminino , Gastos em Saúde , Serviços de Saúde/economia , Disparidades em Assistência à Saúde/organização & administração , Humanos , Masculino , Pessoa de Meia-Idade , TaiwanRESUMO
OBJECTIVES: To evaluate the appropriateness of the definition of outpatient-shopping behavior in Taiwanese patients. STUDY DESIGN: Linked study of 3 databases (Taiwan Cancer Registry, National Health Insurance [NHI] claim database, and death registry database). METHODS: Outpatient shopping behavior was defined as making at least 4 or 5 physician visits to confirm a cancer diagnosis. We analyzed patient-related factors and the 5-year overall survival rate of the outpatient-shopping group compared with a nonshopping group. Using the household registration database and NHI database, we determined the proportion of outpatient shopping, characteristics of patients who did and did not shop for outpatient therapy, time between diagnosis and start of regular treatment, and medical service utilization in the shopping versus the nonshopping group. RESULTS: Patients with higher incomes were significantly more likely to shop for outpatient care. Patients with higher comorbidity scores were 1.4 times more likely to shop for outpatient care than patients with lower scores. Patients diagnosed with more advanced cancer were more likely to shop than those who were not. Patients might be more trusting of cancer diagnoses given at higher-level hospitals. The nonshopping groups had a longer duration of survival over 5 years. CONCLUSIONS: Health authorities should consider charging additional fees after a specific outpatient- shopping threshold is reached to reduce this behavior. The government may need to reassess the function of the medical sources network by shrinking it from the original 4 levels to 2 levels, or by enhancing the referral function among different hospital levels.