More than 50 years of health services research has driven home a core lesson: unintended and inappropriate variations in care are common.1 2 Identification of such variation in obstetrics was the impetus for Archie Cochrane to start his work.3 In this issue of BMJ Quality & Safety, Weiss and colleagues report an intervention developed to address inappropriate variation in aspects of maternal newborn care across Ontario, Canada’s most populous province.4 The intervention involved systematic collection and analysis of administrative data to assess key quality indicators for all hospital births in the province and provision of this data in a ‘dashboard’ back to hospitals.
Measuring quality of care and comparing this against agreed-upon standards of practice or peer performance (ie, audit) and delivery of the results to healthcare professionals and/or administrators (ie, feedback) is a common quality improvement strategy.5 Whether referred...
A massive body of literature characterises the impact of poverty on health outcomes. In 1817, Rene Villermé, a young French surgeon (and later economist-cum-social commentator), demonstrated stark differences in life expectancy across Parisian neighbourhoods or arondissements.1 This demonstration of disparities in basic health outcomes across income levels helped configure our early understanding of the ‘social determinants of health’. These determinants refer to the conditions in which people are born, grow, live, work and age, including income, housing and education, among others. Even 200 years after Villermé, with so many technological advances both within and outside of healthcare, the unequal distribution of resources across society continues to exert tremendous influence on the health outcomes of individuals and their communities.2–5Underappreciated impacts of poverty as a cognitive impediment
In this issue of BMJ Quality and Safety, two papers draw attention...
To assess the effect of the Maternal Newborn Dashboard on six key clinical performance indicators in the province of Ontario, Canada.Design
Interrupted time series using population-based data from the provincial birth registry covering a 3-year period before implementation of the Dashboard and 2.5 years after implementation (November 2009 through March 2015).Setting
All hospitals in the province of Ontario providing maternal-newborn care (n=94).Intervention
A hospital-based online audit and feedback programme.Main outcome measures
Rates of the six performance indicators included in the Dashboard.Results
2.5 years after implementation, the audit and feedback programme was associated with statistically significant absolute decreases in the rates of episiotomy (decrease of 1.5 per 100 women, 95% CI 0.64 to 2.39), induction for postdates in women who were less than 41 weeks at delivery (decrease of 11.7 per 100 women, 95% CI 7.4 to 16.0), repeat caesarean delivery in low-risk women performed before 39 weeks (decrease of 10.4 per 100 women, 95% CI 9.3 to 11.5) and an absolute increase in the rate of appropriately timed group B streptococcus screening (increase of 2.8 per 100, 95% CI 2.2 to 3.5). The audit and feedback programme did not significantly affect the rates of unsatisfactory newborn screening blood samples or formula supplementation at discharge. No statistically significant effects were observed for the two internal control outcomes or the four external control indicators—in fact, two external control indicators (episiotomy and postdates induction) worsened relative to before implementation.Conclusion
An electronic audit and feedback programme implemented in maternal-newborn hospitals was associated with clinically relevant practice improvements at the provincial level in the majority of targeted indicators.
Prior work has not studied the effects of transportation accessibility and patient factors on clinic non-arrival.Objectives
Our objectives were: (1) to evaluate transportation characteristics and patient factors associated with clinic non-arrival, (2) to evaluate the comparability of bus and car drive time estimates, and (3) to evaluate the combined effects of transportation accessibility and income on scheduled appointment non-arrival.Methods
We queried electronic administrative records at an urban general pediatrics clinic. We compared patient and transportation characteristics between arrivals and non-arrivals for scheduled appointments using multivariable modeling.Results
There were 15 346 (29.8%) clinic non-arrivals. In separate car and bus multivariable models that controlled for patient and transit characteristics, we identified significant interactions between income and drive time, and clinic non-arrival. Patients in the lowest quartile of income who were also in the longest quartile of travel time by bus had an increased OR of clinic non-arrival compared with patients in the lowest quartile of income and shortest quartile of travel time by bus (1.55; P<0.01). Similarly, patients in the lowest quartile of income who were also in the longest quartile of travel time by car had an increased OR of clinic non-arrival compared with patients in the lowest quartile of income and shortest quartile of travel time by car (1.21, respectively; P<0.01).Conclusions
Clinic non-arrival is associated with the interaction of longer travel time and lower income.
Emergency hospital admission on weekends is associated with an increased risk of mortality. Previous studies have been limited to examining single years and assessing day—not time—of admission. We used an enhanced longitudinal data set to estimate the ‘weekend effect’ over time and the effect of night-time admission on all-cause mortality rates.Methods
We examined 246 350 emergency spells from a large teaching hospital in England between April 2004 and March 2014. Outcomes included 7-day, 30-day and in-hospital mortality rates. We conducted probit regressions to estimate the impact on the absolute difference in the risk of mortality of two key predictors: (1) admission on weekends (19:00 Friday to 06:59 Monday); and (2) night-time admission (19:00 to 06:59). Logistic regressions were used to estimate ORs for relative mortality risk differences.Results
Crude 30-day mortality rate decreased from 6.6% in 2004/2005 to 5.2% in 2013/2014. Adjusted mortality risk was elevated for all out-of-hours periods. The highest risk was associated with admission on weekend night-times: 30-day mortality increased by 0.6 percentage points (adjusted OR: 1.17, 95% CI 1.10 to 1.25), 7-day mortality by 0.5 percentage points (adjusted OR: 1.23, 95% CI 1.12 to 1.34) and in-hospital mortality by 0.5 percentage points (adjusted OR: 1.14, 95% CI 1.08 to 1.21) compared with admission on weekday daytimes. Weekend night-time admission was associated with increased mortality risk in 9 out of 10 years, but this was only statistically significant (p<0.05) in 5 out of 10 years.Conclusions
There is an increased risk of mortality for patients admitted as emergencies both on weekends and during the night-time. These effects are additive, so that the greatest risk of mortality occurs in patients admitted during the night on weekends. This increased risk appears to be consistent over time, but the effects are small and are not statistically significant in individual hospitals in every year.
To determine whether patients treated in hospital on the weekend report different experiences of care compared with those treated on weekdays.Design
This is a secondary analysis of the 2014 National Health Service (NHS) adult inpatient survey and accident and emergency (A&E) department surveys. Differences were tested using independent samples t-tests and multiple regression, adjusting for patient age group, sex, ethnicity, proxy response, NHS trust, route of admission (for the inpatient survey) and destination on discharge (for the A&E survey).Setting
The inpatient survey included 154 NHS hospital trusts providing overnight care; the A&E survey 142 trusts with major emergency departments.Participants
Three cohorts were analysed: patients attending A&E, admitted to hospital and discharged from hospital. From the inpatient survey’s 59 083 responses, 10 382 were admitted and 11 542 discharged on weekends or public holidays. The A&E survey received 39 320 responses, including 11 542 (29.4%) who attended on the weekend or on public holidays. Weekday and weekend attendees’ response rates were similar once demographic characteristics were accounted for.Main outcome measures
For the A&E survey, six composite dimensions covered waiting times, doctors and nurse, care and treatment, cleanliness, information on discharge, and overall experiences. For the inpatient survey, three questions covered admissions and two dimensions covered information about discharge and about medicines.Results
People attending A&E on weekends were significantly more favourable about ‘doctors and nurses’ and ‘care and treatment’. Inpatients admitted via A&E on a weekend were more positive about the information given to them in A&E than others. Other dimensions showed no differences between people treated on weekdays or on weekends.Conclusions
Patients attending emergency departments or admitted to or discharged from an inpatient episode on weekends and public holidays report similar or more positive experiences of care to other patients after adjusting for patient characteristics.
Recent efforts to reduce patient infection rates emphasise the importance of safety culture. However, little evidence exists linking measures of safety culture and infection rates, in part because of the difficulty of collecting both safety culture and infection data from a large number of nursing homes.Objective
To examine the association between nursing home safety culture, measured with the Nursing Home Survey on Patient Safety Culture (NHSOPS), and catheter-associated urinary tract infection rates (CAUTI) using data from a recent national collaborative for preventing healthcare-associated infections in nursing homes.Methods
In this prospective cohort study of nursing homes, facility staff completed the NHSOPS at intervention start and 11 months later. National Healthcare Safety Network-defined CAUTI rates were collected monthly for 1 year. Negative binomial models examined CAUTI rates as a function of both initial and time-varying facility-aggregated NHSOPS components, adjusted for facility characteristics.Results
Staff from 196 participating nursing homes completed the NHSOPS and reported CAUTI rates monthly. Nursing homes saw a 52% reduction in CAUTI rates over the intervention period. Seven of 13 NHSOPS measures saw improvements, with the largest improvements for ‘Management Support for Resident Safety’ (3.7 percentage point increase in facility-level per cent positive response, on average) and ‘Communication Openness’ (2.5 percentage points). However, these increases were statistically insignificant, and multivariate models did not find significant association between CAUTI rates and initial or over-time NHSOPS domains.Conclusions
This large national collaborative of nursing homes saw declining CAUTI rates as well as improvements in several NHSOPS domains. However, no association was found between initial or over-time NHSOPS scores and CAUTI rates.