Staff expectations for the implementation of an electronic health record system: a qualitative study using normalisation process theory

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

Understanding long-term opioid prescribing for non-cancer pain in primary care: A qualitative study

YesBackground: 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.National Institute for Health Research (NIHR) under its Research for Patient Benefit Programme (Grant Reference Number PB-PG- 1010–23041)

The impact of hospital command centre on patient flow and data quality: findings from the UK NHS

YesBackground: In the last six years, hospitals in developed countries have been trialling the use of command centres for improving organisational efficiency and patient care. However, the impact of these Command Centres has not been systematically studied in the past. Methods: It is a retrospective population based study. Participants were patients who visited Bradford Royal Infirmary Hospital, accident and emergency (A&E) department, between Jan 01, 2018 and August 31, 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. Results: 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 minutes (95% CI: 0.35 to 1.4), 3 minutes (95% CI: 2.4 to 3.5), 9.7 minutes (95% CI: 8.4 to 11.0) and 3.1 minutes (95% CI: 2.7 to 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 conclusion of consultation showed an increase of 11.5 minutes (95% CI: 9.2 to 13.9), 12.3 minutes (95% CI: 8.7 to 15.9), 53.4 minutes (95% CI: 48.1 to 58.7) and 50.2 minutes (95% CI: 47.5 to 52.9) for the respective four post-intervention periods. Further, length of stay was not significantly impacted; the change was -8.8hrs (95% CI: -17.6 to 0.08), -8.9hrs (95% CI: -18.6 to 0.65), -1.67hrs (95% CI: -10.3 to 6.9) and -0.54hrs (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. Conclusion: The findings of the study suggest that a command centre package that includes process change and software technology does not appear to have 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.This project is funded by the National Institute for Health Research Health Service and Delivery Research Programme (NIHR129483)

Effect of a hospital command centre on patient safety: an interrupted time series study

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

Effect of a hospital command centre on patient safety: An interrupted time series study

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

Assessment at UK medical schools varies substantially in volume, type and intensity and correlates with postgraduate attainment

BACKGROUND: In the United Kingdom (UK), medical schools are free to develop local systems and policies that govern student assessment and progression. Successful completion of an undergraduate medical degree results in the automatic award of a provisional licence to practice medicine by the General Medical Council (GMC). Such a licensing process relies heavily on the assumption that individual schools develop similarly rigorous assessment policies. Little work has evaluated variability of undergraduate medical assessment between medical schools. That absence is important in the light of the GMC's recent announcement of the introduction of the UKMLA (UK Medical Licensing Assessment) for all doctors who wish to practise in the UK. The present study aimed to quantify and compare the volume, type and intensity of summative assessment across medicine (A100) courses in the United Kingdom, and to assess whether intensity of assessment correlates with the postgraduate attainment of doctors from these schools. METHODS: Locally knowledgeable students in each school were approached to take part in guided-questionnaire interviews via telephone or Skype(TM). Their understanding of assessment at their medical school was probed, and later validated with the assessment department of the respective medical school. We gathered data for 25 of 27 A100 programmes in the UK and compared volume, type and intensity of assessment between schools. We then correlated these data with the mean first-attempt score of graduates sitting MRCGP and MRCP(UK), as well as with UKFPO selection measures. RESULTS: The median written assessment volume across all schools was 2000 min (mean = 2027, SD = 586, LQ = 1500, UQ = 2500, range = 1000-3200) and 1400 marks (mean = 1555, SD = 463, LQ = 1200, UQ = 1800, range = 1100-2800). The median practical assessment volume was 400 min (mean = 472, SD = 207, LQ = 400, UQ = 600, range = 200-1000). The median intensity (minutes per mark ratio) of summative written assessment was 1.24 min per mark (mean = 1.28, SD = 0.30, LQ = 1.11, UQ = 1.37, range = 0.85-2.08). An exploratory analysis suggested a significant correlation of total assessment time with mean first-attempt score on both the knowledge and the clinical assessments of MRCGP and of MRCP(UK). CONCLUSIONS: There are substantial differences in the volume, format and intensity of undergraduate assessment between UK medical schools. These findings suggest a potential for differences in the reliability of detecting poorly performing students, or differences in identifying and stratifying academically equivalent students for ranking in the Foundation Programme Application System (FPAS). Furthermore, these differences appear to directly correlate with performance in postgraduate examinations. Taken together, our findings highlight highly variable local assessment procedures that warrant further investigation to establish their potential impact on students

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Background: Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods: All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results: A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion: Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions

Establishing a primary care audit and feedback implementation laboratory: a consensus study

Background: There is a significant variation among individual primary care providers in prescribing of potentially problematic, low-value medicines which cause avoidable patient harm. Audit and feedback is generally effective at improving prescribing. However, progress has been hindered by research waste, leading to unanswered questions about how to include audit and feedback for specific problems and circumstances. Trials of different ways of providing audit and feedback in implementation laboratories have been proposed as a way of improving population healthcare while generating robust evidence on feedback effects. However, there is limited experience in their design and delivery. Aim: To explore priorities, feasibility, and ethical challenges of establishing a primary care prescribing audit and feedback implementation laboratory. Design and setting: Two-stage Delphi consensus process involving primary care pharmacy leads, audit and feedback researchers, and patient and public. Method: Participants initially scored statements relating to priorities, feasibility, and ethical considerations for an implementation laboratory. These covered current feedback practice, priority topics for feedback, usefulness of feedback in improving prescribing and different types of prescribing data, acceptability and desirability of different organization levels of randomization, options for trial consent, different methods of delivering feedback, and interest in finding out how effective different ways of presenting feedback would be. After receiving collated results, participants then scored the items again. The consensus was defined using the GRADE criteria. The results were analyzed by group and overall score. Results: Fourteen participants reached consensus for 38 out of 55 statements. Addressing antibiotic and opioid prescribing emerged as the highest priorities for action. The panel supported statements around addressing highpriority prescribing issues, taking an “opt-out” approach to practice consent if waiving consent was not permitted, and randomizing at lower rather than higher organizational levels. Participants supported patient-level prescribing data and further research evaluating most of the different feedback methods we presented them with. Conclusions: There is a good level of support for evaluating a wide range of potential enhancements to improve the effects of feedback on prescribing. The successful design and delivery of a primary care audit and feedback implementation laboratory depend on identifying shared priorities and addressing practical and ethical considerations