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.
Ecological fallacy refers to an erroneous inference about individuals on the basis of findings for the group to which those individuals belong. Suppose analysis of a large database shows that hospitals with a high proportion of long length of stay (LOS) patients also have higher than average in-hospital mortality. This may prompt efforts to reduce mortality among patients with long LOS. But patients with long LOS may not be the ones at higher risk of death. It may be that hospitals with higher mortality (regardless of LOS) also have more long LOS patients—either because of quality problems on both counts or because of unaccounted differences in case mix. To provide more insight how the ecological fallacy influences the evaluation of hospital performance indicators, we assessed whether hospital-level associations between in-hospital mortality, readmission and long LOS reflect patient-level associations.Methods
Patient admissions from the Dutch National Medical Registration (2007–2012) for specific diseases (stroke, colorectal carcinoma, heart failure, acute myocardial infarction and hip/knee replacements in patients with osteoarthritis) were analysed, as well as all admissions. Logistic regression analysis was used to assess patient-level associations. Pearson correlation coefficients were used to quantify hospital-level associations.Results
Overall, we observed 2.2% in-hospital mortality, 8.1% readmissions and a mean LOS of 5.9 days among 8 478 884 admissions in 95 hospitals. Of the 10 disease-specific associations tested, 2 were reversed at hospital-level, 3 were consistent and 5 were only significant at either hospital-level or patient-level. A reversed association was found for stroke: patients with long LOS had 58% lower in-hospital mortality (OR 0.42 (95% CI 0.40 to 0.44)), whereas the hospital-level association was reversed (r=0.30, p<0.01). Similar negative patient-level associations were found for each hospital, but LOS varied across hospitals, thereby resulting in a positive hospital-level association. A similar effect was found for long LOS and readmission in patients with heart failure.Conclusions
Hospital-level associations did not reflect the same patient-level associations in 7 of 10 associations, and were even reversed in 2 associations. Ecological fallacy thus potentially influences interpretation of hospital performance when patient-level associations are not taken into account.
It is usually a grand affair when ‘Ms Noelle’ makes it to clinic. The 52-year-old mother with a history of hepatitis C cirrhosis, hypertension, uterine fibroids and migraines has been in our care for over a year. Even so, each visit still brings a new crisis. Today, we found out that Ms Noelle, the caretaker of a daughter with bipolar disorder and nine grandchildren, had just been evicted from her home. She had been without any income for months, and her applications for temporary cash assistance and disability were denied. Ms Noelle maintained a remarkable ability to keep her family protected and fed despite all this, but we have watched as she became the ultimate victim: she struggled to remember her medications, their doses and indications, and her cirrhosis was frequently on the verge of decompensation during appointments she was barely able to keep. She was overwhelmed by even...
‘Do no harm’ is an enduring principle of medicine, yet people continue to be harmed in the process of being ‘cared for’. Before the 1990s, there was very little understanding that poor quality might be inherent in the structures and processes of the healthcare system.1 Now, as a result of considerable research investment, a great deal is known about, for example, hospital-acquired infection, surgical error, medication error, and the systems and processes that predispose practitioners towards error. Nevertheless, what it means to ‘care’ and how this might carry threats to safety has recently been exemplified by events at Mid Staffordshire NHS Foundation Trust in the UK. Here, there were consistently higher than average mortality rates and poor standards of care in which patients’ most basic needs were routinely overlooked; personal hygiene, nutrition and hydration were not maintained, and patients were treated without compassion or respect for...
Diagnostic errors result in preventable morbidity and mortality. The outpatient setting may be at increased risk, where time constraints, the indolent nature of outpatient complaints and single decision-maker practice models predominate.Methods
We developed a self-administered diagnostic pause to address diagnostic error. Clinicians (physicians and nurse practitioners) in an academic primary care setting received the tool if they were seeing urgent care patients who had previously been seen in the past two weeks in urgent care. We used pre–post-intervention surveys, focus groups and chart audits 6 months after the urgent care visit to assess the impact of the intervention on participant perceptions and actions.Results
We piloted diagnostic pauses in two phases (3 months and 6 months, respectively); 9 physicians participated in the first phase, and 16 physicians and 2 nurse practitioners in the second phase. Subjects received 135 alerts for diagnostic pauses and responded to 82 (61% response). Thirteen per cent of alerts resulted in clinicians reporting new actions as a result of the diagnostic pauses. Thirteen per cent of cases at a 6-month chart audit resulted in diagnostic discrepancies, defined as differences in diagnosis from the initial working diagnosis. Focus groups reported that the diagnostic pauses were brief and fairly well integrated into the overall workflow for evaluation but would have benefited as a real-time application for patients at higher risk for diagnostic error.Conclusion
This pilot represents the first known examination of diagnostic pauses in the outpatient setting, and this work potentially paves the way for more broad-based systems and/or electronic interventions to address diagnostic error.
We would like to extend our gratitude to all of our reviewers for making it possible for BMJ Quality and Safety to publish the highest quality content by providing their rigorous clinical, scientific, or methodological expertise. Their efforts to respect requested deadlines and take the time to provide detailed reviews have also enabled us to achieve excellent turnaround times and offer an excellent service to our authors. Below is a list of all reviewers who have reviewed more than 3 manuscripts for the Journal in 2017. We are grateful to all of our reviewers, and a full list of all of those who have reviewed at least one manuscript for BMJ Quality & Safety can be found online at http://qualitysafety.bmj.com/thank-you-to-our-reviewers/
Low-value care, or patient care that provides no net benefit in specific clinical scenarios, remains one of the most pressing problems in healthcare across the world—namely because it raises costs, causes iatrogenic patient harm, and often interferes with the delivery of high-value care. Many have argued that above all else the primary cause of low-value care lies in an unchecked fee-for-service payment system, which creates a pervasive culture that rewards providers for delivering more care, not necessarily the right care. Results reported by McAlister et al in this issue of BMJ Quality & Safety seem to up-end this belief.1 In their analysis of 3.4 million beneficiaries in the globally-budgeted health system of Alberta, Canada, they found that low-value care commonly occurred—at a rate of approximately 5% of beneficiaries seeking care, and as high as 30% among those aged >75 years. Notably, these rates are comparable to rates in America’s largely...