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Background To calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients. Methods We analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators. Results NHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors. All elective surgery can be conducted at normal pre-pandemic levels provided the other interventions are sustained, but only if the daily number of COVID-19 patients occupying CC beds is not greater than 1550 in the whole of England. If the other interventions are not maintained, then elective surgery can only be conducted if the number of COVID-19 patients occupying CC beds is not greater than 320. However, there is greater national capacity to treat G&A patients: without interventions, it takes almost 10,000 G&A COVID-19 patients before any G&A elective patients would be unable to be accommodated. Conclusions Unless COVID-19 hospitalisations drop to low levels, there is a continued need to enhance critical care capacity in England with field hospitals, use of private hospitals or deployment of former and newly qualified medical staff to allow some or all elective surgery to take place.

Seventy six senior academics from 11 countries invite The BMJ’s editors to reconsider their policy of rejecting qualitative research on the grounds of low priority. They challenge the journal to develop a proactive, scholarly, and pluralist approach to research that aligns with its stated mission

This work aims to provide a systematic and updated survey of original scientific studies on the effect of the introduction of reference pricing (RP) policies in Organisation for Economic Co-operation and Development (OECD) countries. We searched PubMed, EconLit and Web of Knowledge for articles on RP. We reviewed studies that met the inclusion criteria established in the search strategy. From a total of 468 references, we selected the 35 that met all of the inclusion criteria. Some common themes emerged in the literature. The first was that RP was generally associated with a decrease in the prices of the drugs subject to the policy. In particular, price drops seem to have been experienced in virtually every country that implemented a generic RP (GRP) policy. A GRP policy applies only to products with expired patents and generic competition, and clusters drugs according to chemical equivalence (same form and active compound). More significant price decreases were observed in the sub-markets in which drugs were already facing generic competition prior to RP. Price drops varied widely according to the amount of generic competition and industrial strategies: brand-named drugs originally priced above RP values decreased their prices to a greater extent. A second common theme was that both therapeutic RP (TRP) and GRP have been associated with significant and consistent savings in the first years of application. A third general result is that generic market shares significantly increased whenever the firms producing brand-named drugs did not adopt one of the following strategies: lowering prices to RP values; launching new dosages and/or formulations; or marketing substitute drugs still under patent protection. Finally, concerning TRP, although more evidence is needed, studies based on a large number of patient-level observations showed no association between the RP policy and health outcomes.

We evaluate the impacts of implementing and lifting nonpharmaceutical interventions (NPIs) in US counties on the daily growth rate of COVID-19 cases and compliance, measured through the percentage of devices staying home, and evaluate whether introducing and lifting NPIs protecting selective populations is an effective strategy. We use difference-in-differences methods, leveraging on daily county-level data and exploit the staggered introduction and lifting of policies across counties over time. We also assess heterogenous impacts due to counties’ population characteristics, namely ethnicity and household income. Results show that introducing NPIs led to a reduction in cases through the percentage of devices staying home. When counties lifted NPIs, they benefited from reduced mobility outside of the home during the lockdown, but only for a short period. In the long term, counties experienced diminished health and mobility gains accrued from previously implemented policies. Notably, we find heterogenous impacts due to population characteristics implying that measures can mitigate the disproportionate burden of COVID-19 on marginalized populations and find that selectively targeting populations may not be effective.

According to the World Health Report 2000, health system responsiveness is proposed as one of the three key objectives of any health system. This multi-domain concept describes how well a health system responds to the expectations of their users concerning the non-health enhancing aspects of care.In this study we aim to compare the levels of responsiveness experienced by users of private and publicly managed hospitals in Nigeria, and through these insights, to propose recommendations on how to improve performance on this measure.This quantitative, cross-sectional study uses a questionnaire that is adapted from two responsiveness surveys designed by the World Health Organization (WHO). Researchers collected responses from 520 respondents from four hospitals in Lagos, Nigeria. Analysis of the data using statistical techniques found that significant differences exist between the performance of public and private hospitals on certain domains of responsiveness, with privately operated hospitals performing better where differences exist. Users of private hospitals also reported a higher level of overall satisfaction. Private hospitals were found to perform particularly better on the domains of dignity, waiting times, and travel times. These findings have implications for the management of public hospitals in focusing their efforts on improving their performance in low scoring domains. Performance in these hospitals can be improved by emphasis on staff training and demand management.

ObjectivesTo explore the extent to which doctor-rating websites are known and used among a sample of respondents from London. To understand the main predictors of what makes people willing to use doctor-rating websites.DesignA cross-sectional study.SettingThe Borough of Hammersmith and Fulham, London, England.Participants200 individuals from the borough.Main outcome measuresThe likelihood of being aware of doctor-rating websites and the intention to use doctor-rating websites.ResultsThe use and awareness of doctor-rating websites are still quite limited. White British subjects, as well as respondents with higher income are less likely to use doctor-rating websites. Aspects of the doctor–patient relationship also play a key role in explaining intention to use the websites. The doctor has both a ‘complementary’ and ‘substitute’ role with respect to Internet information.ConclusionsOnline rating websites can play a major role in supporting patients’ informed decisions on which healthcare providers to seek advice from, thus potentially fostering patients’ choice in healthcare. Subjects who seek and provide feedback on doctor-ranking websites, though, are unlikely to be representative of the overall patients’ pool. In particular, they tend to over-represent opinions from non-White British, medium–low-income patients who are not satisfied with their choice of the healthcare treatments and the level of information provided by their GP. Accounting for differences in the users’ characteristics is important when interpreting results from doctor-rating sites.

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