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Measurement of harms in community care: a qualitative study of use of the NHS Safety Thermometer

Quality and Safety in Health Care Journal -

Objectives

Measurement is a vital part of improvement work. While it is known that the context of improvement work influences its success, less is known about how context affects measurement of underlying harms. We sought to explore the use of a harm measurement tool, the NHS Safety Thermometer (NHS-ST), designed for use across diverse healthcare settings in the particular context of community care.

Methods

This is a qualitative study of 19 National Health Service (NHS) organisations, 7 of which had community service provision. We conducted ethnographic observations of practice and interviews with front-line nursing and senior staff. Analysis was based on the constant comparison method.

Results

Measurement in community settings presents distinct challenges, calling into question the extent to which measures can be easily transferred. The NHS-ST was seen as more appropriate for acute care, not least because community nurses did not have the same access to information. Data collection requirements were in tension with maintaining a relationship of trust with patients. The aim to collect data across care settings acted to undermine perceptions of the representativeness of community data. Although the tool was designed to measure preventable harms, care providers questioned their preventability within a community setting. Different harms were seen as priorities for measurement and improvement within community settings.

Conclusions

Measurement tools are experienced by healthcare staff as socially situated. In the community setting, there are distinct challenges to improving care quality not experienced in the acute sector. Strategies to measure harms, and use of any resulting data for improvement work, need to be cognisant of the complexity of an environment where healthcare staff often have little opportunity to monitor and influence patients.

Successfully reducing newborn asphyxia in the labour unit in a large academic medical centre: a quality improvement project using statistical process control

Quality and Safety in Health Care Journal -

Background

A safe delivery is part of a good start in life, and a continuous focus on preventing harm during delivery is crucial, even in settings with a good safety record. In January 2013, the labour unit at Copenhagen University Hospital, Hvidovre, undertook a quality improvement (QI) project to prevent asphyxia and reduced the percentage of newborns with asphyxia by 48%.

Methods

The change theory consisted of two primary elements: (1) the clinical content, including three clinical bundles of evidence-based care, a ‘delivery bundle’, an ‘oxytocin bundle’ and a ‘vacuum extraction bundle’; (2) an implementation theory, including improving skills in interpretation of cardiotocography, use of QI methods and participation in a national learning network. The Model for Improvement and Deming’s system of profound knowledge were used as a methodological framework. Data on compliance with the care bundles and the number of deliveries between newborns with asphyxia (Apgar <7 after 5 min or pH <7) were analysed using statistical process control.

Results

Compliance with all three clinical care bundles improved to 95% or more, and the percentages of newborns with pH <7 and Apgar <7 after 5 min were reduced by 48% and 31%, respectively. In general, the QI approach strengthened multidisciplinary teamwork, systematised workflow and structured communication around the deliveries. Changes included making a standard memo in the medical record, the use of a bedside whiteboard, bedside handovers, shared decisions with a peer when using an oxytocin infusion and the use of a checklist before vacuum extractions.

Conclusion

This QI project illustrates how aspects of patient safety, such as the prevention of asphyxia, can be improved using QI methods to more reliably implement best practice, even in high-performing systems.

Patient experience of general practice and use of emergency hospital services in England: regression analysis of national cross-sectional time series data

Quality and Safety in Health Care Journal -

Background

The UK Government has introduced several national policies to improve access to primary care. We examined associations between patient experience of general practice and rates of visits to accident and emergency (A&E) departments and emergency hospital admissions in England.

Methods

The study included 8124 general practices between 2011–2012 and 2013–2014. Outcome measures were annual rates of A&E visits and emergency admissions by general practice population, according to administrative hospital records. Explanatory variables included three patient experience measures from the General Practice Patient Survey: practice-level means of experience of making an appointment, satisfaction with opening hours and overall experience (on 0–100 scales). The main analysis used random-effects Poisson regression for cross-sectional time series. Five sensitivity analyses examined changes in model specification.

Results

Mean practice-level rates of A&E visits and emergency admissions increased from 2011–2012 to 2013–2014 (310.3–324.4 and 98.8–102.9 per 1000 patients). Each patient experience measure decreased; for example, mean satisfaction with opening hours was 79.4 in 2011–2012 and 76.6 in 2013–2014. In the adjusted regression analysis, an SD increase in experience of making appointments (equal to 9 points) predicted decreases of 1.8% (95% CI –2.4% to –1.2%) in A&E visit rates and 1.4% (95% CI –1.9% to –0.9%) in admission rates. This equalled 301 174 fewer A&E visits and 74 610 fewer admissions nationally per year. Satisfaction with opening hours and overall experience were not consistently associated with either outcome measure across the main and sensitivity analyses.

Conclusions

Associations between patient experience of general practice and use of emergency hospital services were small or inconsistent. In England, realistic short-term improvements in patient experience of general practice may only have modest effects on A&E visits and emergency admissions.

Task errors by emergency physicians are associated with interruptions, multitasking, fatigue and working memory capacity: a prospective, direct observation study

Quality and Safety in Health Care Journal -

Background

Interruptions and multitasking have been demonstrated in experimental studies to reduce individuals’ task performance. These behaviours are frequently used by clinicians in high-workload, dynamic clinical environments, yet their effects have rarely been studied.

Objective

To assess the relative contributions of interruptions and multitasking by emergency physicians to prescribing errors.

Methods

36 emergency physicians were shadowed over 120 hours. All tasks, interruptions and instances of multitasking were recorded. Physicians’ working memory capacity (WMC) and preference for multitasking were assessed using the Operation Span Task (OSPAN) and Inventory of Polychronic Values. Following observation, physicians were asked about their sleep in the previous 24 hours. Prescribing errors were used as a measure of task performance. We performed multivariate analysis of prescribing error rates to determine associations with interruptions and multitasking, also considering physician seniority, age, psychometric measures, workload and sleep.

Results

Physicians experienced 7.9 interruptions/hour. 28 clinicians were observed prescribing 239 medication orders which contained 208 prescribing errors. While prescribing, clinicians were interrupted 9.4 times/hour. Error rates increased significantly if physicians were interrupted (rate ratio (RR) 2.82; 95% CI 1.23 to 6.49) or multitasked (RR 1.86; 95% CI 1.35 to 2.56) while prescribing. Having below-average sleep showed a >15-fold increase in clinical error rate (RR 16.44; 95% CI 4.84 to 55.81). WMC was protective against errors; for every 10-point increase on the 75-point OSPAN, a 19% decrease in prescribing errors was observed. There was no effect of polychronicity, workload, physician gender or above-average sleep on error rates.

Conclusion

Interruptions, multitasking and poor sleep were associated with significantly increased rates of prescribing errors among emergency physicians. WMC mitigated the negative influence of these factors to an extent. These results confirm experimental findings in other fields and raise questions about the acceptability of the high rates of multitasking and interruption in clinical environments.

Ethical implications of excessive cluster sizes in cluster randomised trials

Quality and Safety in Health Care Journal -

The cluster randomised trial (CRT) is commonly used in healthcare research. It is the gold-standard study design for evaluating healthcare policy interventions. A key characteristic of this design is that as more participants are included, in a fixed number of clusters, the increase in achievable power will level off. CRTs with cluster sizes that exceed the point of levelling-off will have excessive numbers of participants, even if they do not achieve nominal levels of power. Excessively large cluster sizes may have ethical implications due to exposing trial participants unnecessarily to the burdens of both participating in the trial and the potential risks of harm associated with the intervention. We explore these issues through the use of two case studies. Where data are routinely collected, available at minimum cost and the intervention poses low risk, the ethical implications of excessively large cluster sizes are likely to be low (case study 1). However, to maximise the social benefit of the study, identification of excessive cluster sizes can allow for prespecified and fully powered secondary analyses. In the second case study, while there is no burden through trial participation (because the outcome data are routinely collected and non-identifiable), the intervention might be considered to pose some indirect risk to patients and risks to the healthcare workers. In this case study it is therefore important that the inclusion of excessively large cluster sizes is justifiable on other grounds (perhaps to show sustainability). In any randomised controlled trial, including evaluations of health policy interventions, it is important to minimise the burdens and risks to participants. Funders, researchers and research ethics committees should be aware of the ethical issues of excessively large cluster sizes in cluster trials.

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