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Background: Despite the availability of evidence-based guidance, many patients with type 2 diabetes do not achieve treatment goals.Aim: To guide quality improvement strategies for type 2 diabetes by synthesising qualitative evidence on primary care physicians' and nurses' perceived influences on care.Design and Setting: Systematic review of qualitative studies with findings organised using the Theoretical Domains Framework.Method: Databases searched were MEDLINE, Embase, CINAHL, PsycInfo, and ASSIA from 1980 until March 2014. Studies included were English-language qualitative studies in primary care of physicians' or nurses' perceived influences on treatment goals for type 2 diabetes.Results: A total of 32 studies were included: 17 address general diabetes care, 11 glycaemic control, three blood pressure, and one cholesterol control. Clinicians struggle to meet evolving treatment targets within limited time and resources, and are frustrated with resulting compromises. They lack confidence in knowledge of guidelines and skills, notably initiating insulin and facilitating patient behaviour change. Changing professional boundaries have resulted in uncertainty about where clinical responsibility resides. Accounts are often couched in emotional terms, especially frustrations over patient compliance and anxieties about treatment intensification.Conclusion: Although resources are important, many barriers to improving care are amenable to behaviour change strategies. Improvement strategies need to account for differences between clinical targets and consider tailored rather than 'one size fits all' approaches. Training targeting knowledge is necessary but insufficient to bring about major change; approaches to improve diabetes care need to delineate roles and responsibilities, and address clinicians' skills and emotions around treatment intensification and facilitation of patient behaviour change. [ABSTRACT FROM AUTHOR]

In the last 6 years, hospitals in developed countries have been trialling the use of command centres for improving organizational efficiency and patient care. However, the impact of these command centres has not been systematically studied in the past. It is a retrospective population-based study. Participants were patients who visited the Bradford Royal Infirmary hospital, Accident and Emergency (A&E) Department, between 1 January 2018 and 31 August 2021. Outcomes were patient flow (measured as A&E waiting time, length of stay, and clinician seen time) and data quality (measured by the proportion of missing treatment and assessment dates and valid transition between A&E care stages). Interrupted time-series segmented regression and process mining were used for analysis. A&E transition time from patient arrival to assessment by a clinician marginally improved during the intervention period; there was a decrease of 0.9 min [95% confidence interval (CI): 0.35-1.4], 3 min (95% CI: 2.4-3.5), 9.7 min (95% CI: 8.4-11.0), and 3.1 min (95% CI: 2.7-3.5) during 'patient flow program', 'command centre display roll-in', 'command centre activation', and 'hospital wide training program', respectively. However, the transition time from patient treatment until the conclusion of consultation showed an increase of 11.5 min (95% CI: 9.2-13.9), 12.3 min (95% CI: 8.7-15.9), 53.4 min (95% CI: 48.1-58.7), and 50.2 min (95% CI: 47.5-52.9) for the respective four post-intervention periods. Furthermore, the length of stay was not significantly impacted; the change was -8.8 h (95% CI: -17.6 to 0.08), -8.9 h (95% CI: -18.6 to 0.65), -1.67 h (95% CI: -10.3 to 6.9), and -0.54 h (95% CI: -13.9 to 12.8) during the four respective post-intervention periods. It was a similar pattern for the waiting and clinician seen times. Data quality as measured by the proportion of missing dates of records was generally poor (treatment date = 42.7% and clinician seen date = 23.4%) and did not significantly improve during the intervention periods. The findings of the study suggest that a command centre package that includes process change and software technology does not appear to have a consistent positive impact on patient safety and data quality based on the indicators and data we used. Therefore, hospitals considering introducing a command centre should not assume there will be benefits in patient flow and data quality., (© The Author(s) 2023. Published by Oxford University Press on behalf of International Society for Quality in Health Care.)

The Nursing and Midwifery Council recognises that using simulated practice learning within the pre-registration nursing curriculum is a valuable way for students to develop nursing knowledge and skills. The University of Huddersfield developed simulated placements in the pre-registration nursing curriculum in 2021. Simulated placements are now embedded within all fields of the BSc and MSc programmes, providing structured, innovative learning experiences that embrace online technology in supporting the development of skills and knowledge relevant to all fields of nursing. Developing these placements has provided an opportunity for faculty staff to work collaboratively with clinical colleagues, service users and carers, academics and technologists. This article offers an overview of that work, addressing challenges, operational issues, and insight into some of the activities developed to support students' learning.

Objectives: The Computer-Aided Risk Score for Mortality (CARM) estimates the risk of in-hospital mortality following acute admission to the hospital by automatically amalgamating physiological measures, blood tests, gender, age and COVID-19 status. Our aims were to implement the score with a small group of practitioners and understand their first-hand experience of interacting with the score in situ., Design: Pilot implementation evaluation study involving qualitative interviews., Setting: This study was conducted in one of the two National Health Service hospital trusts in the North of England in which the score was developed., Participants: Medical, older person and ICU/anaesthetic consultants and specialist grade registrars (n=116) and critical outreach nurses (n=7) were given access to CARM. Nine interviews were conducted in total, with eight doctors and one critical care outreach nurse., Interventions: Participants were given access to the CARM score, visible after login to the patients' electronic record, along with information about the development and intended use of the score., Results: Four themes and 14 subthemes emerged from reflexive thematic analysis: (1) current use (including support or challenge clinical judgement and decision making, communicating risk of mortality and professional curiosity); (2) barriers and facilitators to use (including litigation, resource needs, perception of the evidence base, strengths and limitations), (3) implementation support needs (including roll-out and integration, access, training and education); and (4) recommendations for development (including presentation and functionality and potential additional data). Barriers and facilitators to use, and recommendations for development featured highly across most interviews., Conclusion: Our in situ evaluation of the pilot implementation of CARM demonstrated its scope in supporting clinical decision making and communicating risk of mortality between clinical colleagues and with service users. It suggested to us barriers to implementation of the score. Our findings may support those seeking to develop, implement or improve the adoption of risk scores., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Command centres have been piloted in some hospitals across the developed world in the last few years. Their impact on patient safety, however, has not been systematically studied. Hence, we aimed to investigate this., Methods: This is a retrospective population-based cohort study. Participants were patients who visited Bradford Royal Infirmary Hospital and Calderdale & Huddersfield hospitals between 1 January 2018 and 31 August 2021. A five-phase, interrupted time series, linear regression analysis was used., Results: After introduction of a Command Centre, while mortality and readmissions marginally improved, there was no statistically significant impact on postoperative sepsis. In the intervention hospital, when compared with the preintervention period, mortality decreased by 1.4% (95% CI 0.8% to 1.9%), 1.5% (95% CI 0.9% to 2.1%), 1.3% (95% CI 0.7% to 1.8%) and 2.5% (95% CI 1.7% to 3.4%) during successive phases of the command centre programme, including roll-in and activation of the technology and preparatory quality improvement work. However, in the control site, compared with the baseline, the weekly mortality also decreased by 2.0% (95% CI 0.9 to 3.1), 2.3% (95% CI 1.1 to 3.5), 1.3% (95% CI 0.2 to 2.4), 3.1% (95% CI 1.4 to 4.8) for the respective intervention phases. No impact on any of the indicators was observed when only the software technology part of the Command Centre was considered., Conclusion: Implementation of a hospital Command Centre may have a marginal positive impact on patient safety when implemented as part of a broader hospital-wide improvement programme including colocation of operations and clinical leads in a central location. However, improvement in patient safety indicators was also observed for a comparable period in the control site. Further evaluative research into the impact of hospital command centres on a broader range of patient safety and other outcomes is warranted., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.)

The fourth industrial revolution is based on cyber-physical systems and the connectivity of devices. It is currently unclear what the consequences are for patient safety as existing digital health technologies become ubiquitous with increasing pace and interact in unforeseen ways. In this paper, we describe the output from a workshop focused on identifying the patient safety challenges associated with emerging digital health technologies. We discuss six challenges identified in the workshop and present recommendations to address the patient safety concerns posed by them. A key implication of considering the challenges and opportunities for Patient Safety Informatics is the interdisciplinary contribution required to study digital health technologies within their embedded context. The principles underlying our recommendations are those of proactive and systems approaches that relate the social, technical and regulatory facets underpinning patient safety informatics theory and practice.

Introduction: This paper presents a mixed-methods study protocol that will be used to evaluate a recent implementation of a real-time, centralised hospital command centre in the UK. The command centre represents a complex intervention within a complex adaptive system. It could support better operational decision-making and facilitate identification and mitigation of threats to patient safety. There is, however, limited research on the impact of such complex health information technology on patient safety, reliability and operational efficiency of healthcare delivery and this study aims to help address that gap., Methods and Analysis: We will conduct a longitudinal mixed-method evaluation that will be informed by public-and-patient involvement and engagement. Interviews and ethnographic observations will inform iterations with quantitative analysis that will sensitise further qualitative work. Quantitative work will take an iterative approach to identify relevant outcome measures from both the literature and pragmatically from datasets of routinely collected electronic health records., Ethics and Dissemination: This protocol has been approved by the University of Leeds Engineering and Physical Sciences Research Ethics Committee (#MEEC 20-016) and the National Health Service Health Research Authority (IRAS No.: 285933). Our results will be communicated through peer-reviewed publications in international journals and conferences. We will provide ongoing feedback as part of our engagement work with local trust stakeholders., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Background: Global evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and, in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This study explored staff expectations for change and outcome following procurement of a commercial EHR system by a large academic acute NHS hospital in the UK., Methods: Qualitative interviews were conducted with 14 members of hospital staff who represented a variety of user groups across different specialities within the hospital. The four components of Normalisation Process Theory (Coherence, Cognitive participation, Collective action and Reflexive monitoring) provided a theoretical framework to interpret and report study findings., Results: Health professionals had a common understanding for the rationale for EHR implementation (Coherence). There was variation in willingness to engage with and invest time into EHR (Cognitive participation) at an individual, professional and organisational level. Collective action (whether staff feel able to use the EHR) was influenced by context and perceived user-involvement in EHR design and planning of the implementation strategy. When appraising EHR (Reflexive monitoring), staff anticipated short and long-term benefits. Staff perceived that quality and safety of patient care would be improved with EHR implementation, but that these benefits may not be immediate. Some staff perceived that use of the system may negatively impact patient care. The findings indicate that preparedness for EHR use could mitigate perceived threats to the quality and safety of care., Conclusions: Health professionals looked forward to reaping the benefits from EHR use. Variations in level of engagement suggest early components of the implementation strategy were effective, and that more work was needed to involve users in preparing them for use. A clearer understanding as to how staff groups and services differentially interact with the EHR as they go about their daily work was required. The findings may inform other hospitals and healthcare systems on actions that can be taken prior to EHR implementation to reduce concerns for quality and safety of patient care and improve the chance of successful implementation.

Objectives: To examine trends in opioid prescribing in primary care, identify patient and general practice characteristics associated with long-term and stronger opioid prescribing, and identify associations with changes in opioid prescribing., Design: Trend, cross-sectional and longitudinal analyses of routinely recorded patient data., Setting: 111 primary care practices in Leeds and Bradford, UK., Participants: We observed 471 828 patient-years in which all patients represented had at least 1 opioid prescription between April 2005 and March 2012. A cross-sectional analysis included 99 847 patients prescribed opioids between April 2011 and March 2012. A longitudinal analysis included 49 065 patient-years between April 2008 and March 2012. We excluded patients with cancer or treated for substance misuse., Main Outcome Measures: Long-term opioid prescribing (4 or more prescriptions within 12 months), stronger opioid prescribing and stepping up to or down from stronger opioids., Results: Opioid prescribing in the adult population almost doubled for weaker opioids over 2005-2012 and rose over sixfold for stronger opioids. There was marked variation among general practices in the odds of patients stepping up to stronger opioids compared with those not stepping up (range 0.31-3.36), unexplained by practice-level variables. Stepping up to stronger opioids was most strongly associated with being underweight (adjusted OR 3.26, 1.49 to 7.17), increasing polypharmacy (4.15, 3.26 to 5.29 for 10 or more repeat prescriptions), increasing numbers of primary care appointments (3.04, 2.48 to 3.73 for over 12 appointments in the year) and referrals to specialist pain services (5.17, 4.37 to 6.12). Compared with women under 50 years, men under 50 were less likely to step down once prescribed stronger opioids (0.53, 0.37 to 0.75)., Conclusions: While clinicians should be alert to patients at risk of escalated opioid prescribing, much prescribing variation may be attributable to clinical behaviour. Effective strategies targeting clinicians and patients are needed to curb rising prescribing, especially of stronger opioids., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Background: The place of opioids in the management of chronic, non-cancer pain is limited. Even so their use is escalating, leading to concerns that patients are prescribed strong opioids inappropriately and alternatives to medication are under-used. We aimed to understand the processes which bring about and perpetuate long-term prescribing of opioids for chronic, non-cancer pain., Methods: We held semi-structured interviews with patients and focus groups with general practitioners (GPs). Participants included 23 patients currently prescribed long-term opioids and 15 GPs from Leeds and Bradford, United Kingdom (UK). We used a grounded approach to the analysis of transcripts., Results: Patients are driven by the needs for pain relief, explanation, and improvement or maintenance of quality of life. GPs' responses are shaped by how UK general practice is organised, available therapeutic choices and their expertise in managing chronic pain, especially when facing diagnostic uncertainty or when their own approach is at odds with the patient's wishes. Four features of the resulting transaction between patients and doctors influence prescribing: lack of clarity of strategy, including the risk of any plans being subverted by urgent demands; lack of certainty about locus of control in decision-making, especially in relation to prescribing; continuity in the doctor-patient relationship; and mutuality and trust., Conclusions: Problematic prescribing occurs when patients experience repeated consultations that do not meet their needs and GPs feel unable to negotiate alternative approaches to treatment. Therapeutic short-termism is perpetuated by inconsistent clinical encounters and the absence of mutually-agreed formulations of underlying problems and plans of action. Apart from commissioning improved access to appropriate specialist services, general practices should also consider how they manage problematic opioid prescribing and be prepared to set boundaries with patients.