Introduction: Given the ongoing coronavirus disease 2019 (COVID-19) pandemic and the consequent global healthcare crisis, there is an urgent need to better understand risk factors for symptom deterioration and mortality among patients with COVID-19. This systematic review aimed to meet the need by determining the predictive value of chronic diseases for COVID-19 severity and mortality.Methods: We searched PubMed, Embase, Web of Science, and Cumulative Index to Nursing and Allied Health Complete to identify studies published between December 1, 2019, and December 31, 2020. Two hundred and seventeen observational studies from 26 countries involving 624,986 patients were included. We assessed the risk of bias of the included studies and performed a cumulative meta-analysis.Results: We found that among COVID-19 patients, hypertension was a very common condition and was associated with higher severity, intensive care unit (ICU) admission, acute respiratory distress syndrome, and mortality. Chronic obstructive pulmonary disease was the strongest predictor for COVID-19 severity, admission to ICU, and mortality, while asthma was associated with a reduced risk of COVID-19 mortality. Patients with obesity were at a higher risk of experiencing severe symptoms of COVID-19 rather than mortality. Patients with cerebrovascular disease, chronic liver disease, chronic renal disease, or cancer were more likely to become severe COVID-19 cases and had a greater probability of mortality.Conclusions: COVID-19 patients with chronic diseases were more likely to experience severe symptoms and ICU admission and faced a higher risk of mortality. Aggressive strategies to combat the COVID-19 pandemic should target patients with chronic diseases as a priority.

Background China has successfully sustained its universal health insurance coverage over the past decade. Although patient satisfaction has been recognized as an important indicator to measure the performance of insurance programs in China, there is a lack of evidence on how patients with chronic diseases are satisfied with China’s public health insurance programs and whether their satisfaction differs by type of insurance. We aimed to fill the evidence gap. Methods We established a hypothetical model that comprised patients’ awareness of insurance policies, the fulfillment of patients’ expectations of insurance benefits, patients’ perceived value of health insurance coverage, patients’ satisfaction with health insurance programs, patients’ complaints, and trust in health insurance programs. We performed a confirmatory factor analysis by using a structural equation modeling (SEM) approach to examine the hypothesized model. A model-testing survey in 10 tertiary hospitals was conducted between June and October 2018, with a valid sample of 922 insured patients with chronic diseases. Results The SEM model, with good fit indices, showed that patients’ awareness of health insurance policies, insurance program’s fulfillment of expectations, and patients’ perceived value of insurance coverage, positively predicted patient satisfaction (P < 0.01). The fulfillment of patients’ expectations of insurance benefits was the major predictor of satisfaction with health insurance (coefficient = 0.593, P < 0.001), while the patients’ perceived value of insurance coverage had the largest impact on their trust in health insurance (coefficient = 0.409, P < 0.01). Compared to patients with Urban-Rural Resident Basic Medical Insurance, Urban Employee Basic Medical Insurance enrollees had a higher degree of satisfaction with insurance on average (P < 0.01). Despite differences in the degree of satisfaction, the main findings from the SEM were also proved by the multi-group analysis. Conclusions Our findings highlight the importance of incorporating patients’ perceived value as part of the ongoing efforts to increase satisfaction with health insurance by patients, especially those who have chronic diseases. Policymakers are also suggested to formulate evidence-informed reimbursement policies that meet patients’ expectations.

Background: Uterine fibroids are common benign tumors among premenopausal women. High- intensity focused ultrasound (HIFU) is an emerging non-invasive intervention which uses the high-intensity ultrasound waves from ultrasound probes to focus on the targeted fibroids. However, the efficacy of HIFU in comparison with that of other common treatment types in clinical procedure remains unclear.Objective: To investigate the comparative effectiveness and safety of HIFU with other techniques which have been widely used in clinical settings.Methods: We searched the Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Cumulative Index to Nursing &amp; Allied Health Literature, Web of Science, ProQuest Nursing &amp; Allied Health Database, and three Chinese academic databases, including randomized controlled trials (RCTs), non-RCTs, and cohort studies. The primary outcome was the rate of re-intervention, and the GRADE approach was used to interpret the findings.Results: About 18 studies met the inclusion criteria. HIFU was associated with an increased risk of re-intervention rate in comparison with myomectomy (MYO) [pooled odds ratio (OR): 4.05, 95% confidence interval (CI): 1.82–8.9]. The results favored HIFU in comparison with hysterectomy (HYS) on the change of follicle-stimulating hormone [pooled mean difference (MD): −7.95, 95% CI: −8.92–6.98), luteinizing hormone (MD: −4.38, 95% CI: −5.17−3.59), and estradiol (pooled MD: 43.82, 95% CI: 36.92–50.72)]. HIFU had a shorter duration of hospital stay in comparison with MYO (pooled MD: −4.70, 95% CI: −7.46−1.94, p &lt; 0.01). It had a lower incidence of fever (pooled OR: 0.15, 95% CI: 0.06–0.39, p &lt; 0.01) and a lower incidence of major adverse events (pooled OR: 0.04, 95% CI: 0.00–0.30, p &lt; 0.01) in comparison with HYS.Conclusions: High-intensity focused ultrasound may help maintain feminity and shorten the duration of hospital stay. High-quality clinical studies with a large sample size, a long-term follow-up, and the newest HIFU treatment protocol for evaluating the re-intervention rate are suggested to be carried out. Clinical decision should be based on the specific situation of the patients and individual values.

ObjectivesOur study aimed to support evidence-informed policy-making on patient-centred care by investigating preferences for healthcare services among hypertension patients.DesignWe identified six attributes of healthcare services for a discrete choice experiment (DCE), and applied Bayesian-efficient design with blocking techniques to generate choice sets. After conducting the DCE, we used a mixed logit regression model to investigate patients’ preferences for each attribute and analysed the heterogeneities in preferences. Estimates of willingness to pay were derived from regression coefficients.SettingThe DCE was conducted in Jiangsu province and Shanghai municipality in China.ParticipantsPatients aged 18 years or older with a history of hypertension for at least 2 years and who took medications regularly were recruited.ResultsPatients highly valued healthcare services that produced good treatment effects (β=4.502, p<0.001), followed by travel time to healthcare facilities within 1 hour (β=1.285, p<0.001), and the effective physician–patient communication (β=0.771, p<0.001). Continuity of care and minimal waiting time were also positive predictors (p<0.001). However, the out-of-pocket cost was a negative predictor of patients’ choice (β=−0.168, p<0.001). Older adults, patients with good health-related quality of life, had comorbidities, and who were likely to visit secondary and tertiary hospitals cared more about favourable effects (p<0.05). Patients were willing to pay ¥2489 (95% CI ¥2013 to ¥2965) as long as the clinical benefits gained were substantial.ConclusionsOur findings highlight the importance of effective, convenient, efficient, coordinated and patient-centred care for chronic diseases like hypertension. Policy-makers and healthcare providers are suggested to work on aligning the service provision with patients’ preferences.

ObjectivesOur study aimed to inform insurance decision-making in China by investigating patients’ preferences for insurance coverage of new technologies for treating chronic diseases.DesignWe identified six attributes of new medical technologies for treating chronic diseases and used Bayesian-efficient design to generate choice sets for a discrete choice experiment (DCE). After conducting the DCE, we analysed the data by mixed logit regression to examine patient-reported preferences for each attribute.SettingThe DCE was conducted with patients in six tertiary hospitals from four cities in Jiangsu province.ParticipantsPatients aged 18 years or older with a history of diabetes or hypertension and taking medications regularly for more than 1 year were recruited (n=408).ResultsThe technology attributes regarding expected gains in health outcomes from the treatment, high likelihood of effective treatment and low incidence of serious adverse events were significant, positive predictors of choice by the study patients (p<0.01). The out-of-pocket cost was a significant, negative attribute for the entire study sample (β = −0.258, p<0.01) and for the patients with Urban-Rural Residents Basic Medical Insurance (URRBMI) (β = −0.511, p<0.01), but not for all the patients with Urban Employees Basic Medical Insurance (UEBMI) (β = −0.071, p>0.05). The severity of target disease was valued by patients with lower EQ-5D-5L index value as well as URRBMI enrollees.ConclusionsPatients highly valued the health benefits and risks of new technologies, which were closely linked to their feelings of disease and perceptions of health-related quality of life. However, there existed heterogeneity in preferences between URRBMI and UEBMI patients. Further efforts should be made to reduce the gap between insurance schemes and make safe and cost-effective new technologies as a priority for health insurance reimbursement.