What Impact Does the Diagnosis of Mild Cognitive Impairment Have on the Wellbeing, Everyday Behavior, and Healthcare Utilization of People and Their Carers? A Systematic Review.

Background: Dementia is a major cause of disability and dependency globally. Mild cognitive impairment (MCI) is considered an early indicator of developing dementia. There are growing efforts to detect and diagnose MCI earlier; consequently, we need to understand the perspectives of individuals and carers regarding the implications of an MCI diagnosis. Objective: To systematically review qualitative literature to understand the impact of a MCI diagnosis on both the individual and their carers, focusing on wellbeing, everyday behaviors, and healthcare utilization. Methods: Key search terms were input into five databases. Studies were included if they were peer-reviewed qualitative research published in English that obtained perspectives of community-dwellers with MCI or carers and focused on either their wellbeing, everyday behaviors and/or healthcare utilization. The protocol was pre-registered on PROSPERO (CRD42021291995). Data was synthesized narratively. Results: Key findings from 15 eligible articles highlighted the negative impact of an MCI diagnosis on the wellbeing of both individuals and carers, due to stigma and limited understanding regarding diagnosis/prognosis. Changes in everyday behavior varied, particularly regarding motivation to engage with physical activity, hobbies and social opportunities. Both individuals and carers were sometimes dissatisfied with healthcare services; ineffective communication during clinical consolations highlighted as a reason for lack of trust in clinicians. Conclusions: Results indicate that an MCI diagnosis impacts both people with MCI and their carers across key facets of life. There is a critical need to effectively communicate the diagnosis and prognosis of MCI to support wellbeing and everyday activities and ensure trust in healthcare services.

Recommendations to advance digital health equity: a systematic review of qualitative studies.

The World Health Organisation advocates Digital Health Technologies (DHTs) for advancing population health, yet concerns about inequitable outcomes persist. Differences in access and use of DHTs across different demographic groups can contribute to inequities. Academics and policy makers have acknowledged this issue and called for inclusive digital health strategies. This systematic review synthesizes literature on these strategies and assesses facilitators and barriers to their implementation. We searched four large databases for qualitative studies using terms relevant to digital technology, health inequities, and socio-demographic factors associated with digital exclusion summarised by the CLEARS framework (Culture, Limiting conditions, Education, Age, Residence, Socioeconomic status). Following the PRISMA guidelines, 10,401 articles were screened independently by two reviewers, with ten articles meeting our inclusion criteria. Strategies were grouped into either outreach programmes or co-design approaches. Narrative synthesis of these strategies highlighted three key themes: firstly, using user-friendly designs, which included software and website interfaces that were easy to navigate and compatible with existing devices, culturally appropriate content, and engaging features. Secondly, providing supportive infrastructure to users, which included devices, free connectivity, and non-digital options to help access healthcare. Thirdly, providing educational support from family, friends, or professionals to help individuals develop their digital literacy skills to support the use of DHTs. Recommendations for advancing digital health equity include adopting a collaborative working approach to meet users' needs, and using effective advertising to raise awareness of the available support. Further research is needed to assess the feasibility and impact of these recommendations in practice.

Key Considerations When Developing and Implementing Digital Technology for Early Detection of Dementia-Causing Diseases Among Health Care Professionals: Qualitative Study.

BACKGROUND: The World Health Organization (WHO) promotes using digital technologies to accelerate global attainment of health and well-being. This has led to a growth in research exploring the use of digital technology to aid early detection and preventative interventions for dementia-causing diseases such as Alzheimer disease. The opinions and perspectives of health care professionals must be incorporated into the development and implementation of technology to promote its successful adoption in clinical practice. OBJECTIVE: This study aimed to explore health care professionals' perspectives on the key considerations of developing and implementing digital technologies for the early detection of dementia-causing diseases in the National Health Service (NHS). METHODS: Health care professionals with patient-facing roles in primary or secondary care settings in the NHS were recruited through various web-based NHS clinical networks. Participants were interviewed to explore their experiences of the current dementia diagnostic practices, views on early detection and use of digital technology to aid these practices, and the challenges of implementing such interventions in health care. An inductive thematic analysis approach was applied to identify central concepts and themes in the interviews, allowing the data to determine our themes. A list of central concepts and themes was applied systematically to the whole data set using NVivo (version 1.6.1; QSR International). Using the constant comparison technique, the researchers moved backward and forward between these data and evolving explanations until a fit was made. RESULTS: Eighteen semistructured interviews were conducted, with 11 primary and 7 secondary care health care professionals. We identified 3 main categories of considerations relevant to health care service users, health care professionals, and the digital health technology itself. Health care professionals recognized the potential of using digital technology to collect real-time data and the possible benefits of detecting dementia-causing diseases earlier if an effective intervention were available. However, some were concerned about postdetection management, questioning the point of an early detection of dementia-causing diseases if an effective intervention cannot be provided and feared this would only lead to increased anxiety in patients. Health care professionals also expressed mixed opinions on who should be screened for early detection. Some suggested it should be available to everyone to mitigate the chance of excluding those who are not in touch with their health care or are digitally excluded. Others were concerned about the resources that would be required to make the technology available to everyone. CONCLUSIONS: This study highlights the need to design digital health technology in a way that is accessible to all and does not add burden to health care professionals. Further work is needed to ensure inclusive strategies are used in digital research to promote health equity.

Road map for clinicians to develop and evaluate AI predictive models to inform clinical decision-making.

BACKGROUND: Predictive models have been used in clinical care for decades. They can determine the risk of a patient developing a particular condition or complication and inform the shared decision-making process. Developing artificial intelligence (AI) predictive models for use in clinical practice is challenging; even if they have good predictive performance, this does not guarantee that they will be used or enhance decision-making. We describe nine stages of developing and evaluating a predictive AI model, recognising the challenges that clinicians might face at each stage and providing practical tips to help manage them. FINDINGS: The nine stages included clarifying the clinical question or outcome(s) of interest (output), identifying appropriate predictors (features selection), choosing relevant datasets, developing the AI predictive model, validating and testing the developed model, presenting and interpreting the model prediction(s), licensing and maintaining the AI predictive model and evaluating the impact of the AI predictive model. The introduction of an AI prediction model into clinical practice usually consists of multiple interacting components, including the accuracy of the model predictions, physician and patient understanding and use of these probabilities, expected effectiveness of subsequent actions or interventions and adherence to these. Much of the difference in whether benefits are realised relates to whether the predictions are given to clinicians in a timely way that enables them to take an appropriate action. CONCLUSION: The downstream effects on processes and outcomes of AI prediction models vary widely, and it is essential to evaluate the use in clinical practice using an appropriate study design.

Digital Endpoints for Assessing Instrumental Activities of Daily Living in Mild Cognitive Impairment: Systematic Review.

BACKGROUND: Subtle impairments in instrumental activities of daily living (IADLs) can be a key predictor of disease progression and are considered central to functional independence. Mild cognitive impairment (MCI) is a syndrome associated with significant changes in cognitive function and mild impairment in complex functional abilities. The early detection of functional decline through the identification of IADL impairments can aid early intervention strategies. Digital health technology is an objective method of capturing IADL-related behaviors. However, it is unclear how these IADL-related behaviors have been digitally assessed in the literature and what differences can be observed between MCI and normal aging. OBJECTIVE: This review aimed to identify the digital methods and metrics used to assess IADL-related behaviors in people with MCI and report any statistically significant differences in digital endpoints between MCI and normal aging and how these digital endpoints change over time. METHODS: A total of 16,099 articles were identified from 8 databases (CINAHL, Embase, MEDLINE, ProQuest, PsycINFO, PubMed, Web of Science, and Scopus), out of which 15 were included in this review. The included studies must have used continuous remote digital measures to assess IADL-related behaviors in adults characterized as having MCI by clinical diagnosis or assessment. This review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS: Ambient technology was the most commonly used digital method to assess IADL-related behaviors in the included studies (14/15, 93%), with passive infrared motion sensors (5/15, 33%) and contact sensors (5/15, 33%) being the most prevalent types of methods. Digital technologies were used to assess IADL-related behaviors across 5 domains: activities outside of the home, everyday technology use, household and personal management, medication management, and orientation. Other recognized domains-culturally specific tasks and socialization and communication-were not assessed. Of the 79 metrics recorded among 11 types of technologies, 65 (82%) were used only once. There were inconsistent findings around differences in digital IADL endpoints across the cognitive spectrum, with limited longitudinal assessment of how they changed over time. CONCLUSIONS: Despite the broad range of metrics and methods used to digitally assess IADL-related behaviors in people with MCI, several IADLs relevant to functional decline were not studied. Measuring multiple IADL-related digital endpoints could offer more value than the measurement of discrete IADL outcomes alone to observe functional decline. Key recommendations include the development of suitable core metrics relevant to IADL-related behaviors that are based on clinically meaningful outcomes to aid the standardization and further validation of digital technologies against existing IADL measures. Increased longitudinal monitoring is necessary to capture changes in digital IADL endpoints over time in people with MCI. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD42022326861; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=326861.

A complex ePrescribing-based Anti-Microbial Stewardship (ePAMS+) intervention for hospitals combining technological and behavioural components: protocol for a feasibility trial.

BACKGROUND: Antimicrobial resistance is a leading global public health threat, with inappropriate use of antimicrobials in healthcare contributing to its development. Given this urgent need, we developed a complex ePrescribing-based Anti-Microbial Stewardship intervention (ePAMS+). METHODS: ePAMS+ includes educational and organisational behavioural elements, plus guideline-based clinical decision support to aid optimal antimicrobial use in hospital inpatients. ePAMS+ particularly focuses on prompt initiation of antimicrobials, followed by early review once test results are available to facilitate informed decision-making on stopping or switching where appropriate. A mixed-methods feasibility trial of ePAMS+ will take place in two NHS acute hospital care organisations. Qualitative staff interviews and observation of practice will respectively gather staff views on the technical component of ePAMS+ and information on their use of ePAMS+ in routine work. Focus groups will elicit staff and patient views on ePAMS+; one-to-one interviews will discuss antimicrobial stewardship with staff and will record patient experiences of receiving antibiotics and their thoughts on inappropriate prescribing. Qualitative data will be analysed thematically. Fidelity Index development will enable enactment of ePAMS+ to be measured objectively in a subsequent trial assessing the effectiveness of ePAMS+. Quantitative data collection will determine the feasibility of extracting data and deriving key summaries of antimicrobial prescribing; we will quantify variability in the primary outcome, number of antibiotic defined daily doses, to inform the future larger-scale trial design. DISCUSSION: This trial is essential to determine the feasibility of implementing the ePAMS+ intervention and measuring relevant outcomes, prior to evaluating its clinical and cost-effectiveness in a full scale hybrid cluster-randomised stepped-wedge clinical trial. Findings will be shared with study sites and with qualitative research participants and will be published in peer-reviewed journals and presented at academic conferences. TRIAL REGISTRATION: The qualitative and Fidelity Index research were approved by the Health and Research Authority and the North of Scotland Research Ethics Service (ref: 19/NS/0174). The feasibility trial and quantitative analysis (protocol v1.0, 15 December 2021) were approved by the London South East Research Ethics Committee (ref: 22/LO/0204) and registered with ISRCTN ( ISRCTN 13429325 ) on 24 March 2022.

Usability and acceptability of wearable technology in the early detection of dementia.

BACKGROUND: The Early Detection of Neurodegeneration (EDoN) is a global initiative that aims to explore the potential of wearable technologies and smartphone applications to detect preclinical dementia, with aspirations to validate a digital toolkit for clinical practice. To enhance the development of an inclusive digital toolkit, we conducted a study to assess the usability and acceptability of different digital devices in people with cognitive impairments and their carers. METHOD: Recruitment was conducted across various UK networks such as Join Dementia Research. Participants received the EDoN toolkit, which includes a smartwatch (Fitbit Charge 4), EEG headband (Dreem 3) and two smartphone applications (Longevity and Mezurio). Guides were provided to support the setup process. Initial interviews were conducted approximately three days after the participant received the devices, to explore initial perspectives regarding the toolkit and experiences of the setup process. Follow-up interviews were conducted two weeks later to explore the acceptability and usability of the toolkit. NVivo was used to thematically analyse the interview transcripts. Emerging themes were discussed and refined by the research group. RESULT: Sixteen semi-structured interviews were conducted with nine participants, at two-time points. Four participants had mild cognitive impairment, two had frontotemporal dementia, one had Alzheimer's and two were carers. We identified three key themes, which centred around usability, acceptability and inequity. Participants expressed the wearable devices were comfortable but individuals with physical disabilities or cognitive impairments struggled to use some devices. Participants valued the feedback the devices provided such as information on sleep and heart rate, although some information was not fully understood. Participants also shared their concerns around detecting preclinical dementia and the increased anxiety around the consequences of this such as "being put in a home". Various inequities of the toolkit were uncovered such as digital exclusion relating to a lack of access to strong WiFi connection, compatible smartphones and poor digital literacy. CONCLUSION: These results are informative for the further development of user-friendly digital tools for the early detection of dementia. Further work is required to ensure a digital toolkit is inclusive and provides information that can be understood by the user.

A Retrospective Review of Serious Surgical Incidents in 5 Large UK Teaching Hospitals: A System-Based Approach.

OBJECTIVES: Surgical incidents are the most common serious patient safety incidents worldwide. We conducted a review of serious surgical incidents recorded in 5 large teaching hospitals located in one London NHS trust to identify possible contributing factors and propose recommendations for safer healthcare systems. METHODS: We searched the Datix system for all serious surgical incidents that occurred in any operating room, excluding critical care departments, and were recorded between October 2014 and December 2016. We used the London Protocol system analysis framework, which involved a 2-stage approach. A brief description of each incident was produced, and an expert panel analyzed these incidents to identify the most likely contributing factors and what changes should be recommended. RESULTS: One thousand fifty-one surgical incidents were recorded, 14 of which were categorized as "serious" with contributing factors relating to task, equipment and resources, teamwork, work environmental, and organizational and management. Operating room protocols were found to be unavailable, outdated, or not followed correctly in 8 incidents studied. The World Health Organization surgical safety checklist was not adhered to in 8 incidents, with the surgical and anesthetic team not informed about faulty equipment or product shortages before surgery. The lack of effective communication within multidisciplinary teams and inadequate medical staffing levels were perceived to have contributed. CONCLUSIONS: Multiple factors contributed to the occurrence of serious surgical incidents, many of which related to human failures and faulty equipment. The use of faulty equipment needs to be recognized as a major risk within departments and promptly addressed.

The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study.

OBJECTIVE: The medication administration process is complex and consequently prone to errors. Closed Loop Medication Administration solutions aim to improve patient safety. We assessed the impact of a novel medication scanning device (MedEye) on the rate of medication administration errors in a large UK Hospital. METHODS: We performed a feasibility before and after study on one ward at a tertiary-care teaching hospital that used a commercial electronic prescribing and medication administration system. We conducted direct observations of nursing drug administration rounds before and after the MedEye implementation. We calculated the rate and type ('timing', 'omission' or 'other' error) of medication administration errors (MAEs) before and after the MedEye implementation. RESULTS: We observed a total of 1069 administrations before and 432 after the MedEye intervention was implemented. Data suggested that MedEye could support a reduction in MAEs. After adjusting for heterogeneity, we detected a decreasing effect of MedEye on overall errors (p = 0.0753). Non-timing errors ('omission' and 'other' errors) reduced from 51 (4.77%) to 11 (2.55%), a reduction of 46.5%, which had borderline significance at the 5% level, although this was lost after adjusting for confounders. CONCLUSIONS: This pilot study detected a decreasing effect of MedEye on overall errors and a reduction in non-timing error rates that was clinically important as such errors are more likely to be associated with harm. Further research is needed to investigate the impact on a larger sample of medications.

Designing Digital Health Technology to Support Patients Before and After Bariatric Surgery: Qualitative Study Exploring Patient Desires, Suggestions, and Reflections to Support Lifestyle Behavior Change.

BACKGROUND: A patient's capability, motivation, and opportunity to change their lifestyle are determinants of successful outcomes following bariatric surgery. Lifestyle changes before and after surgery, including improved dietary intake and physical activity levels, have been associated with greater postsurgical weight loss and improved long-term health. Integrating patient-centered digital technologies within the bariatric surgical pathway could form part of an innovative strategy to promote and sustain healthier behaviors, and provide holistic patient support, to improve surgical success. Previous research focused on implementing digital technologies and measuring effectiveness in surgical cohorts. However, there is limited work concerning the desires, suggestions, and reflections of patients undergoing bariatric surgery. This qualitative investigation explores patients' perspectives on technology features that would support behavior changes during the pre- and postoperative periods, to potentially maintain long-term healthy lifestyles following surgery. OBJECTIVE: This study aims to understand how digital technologies can be used to support patient care during the perioperative journey to improve weight loss outcomes and surgical success, focusing on what patients want from digital technologies, how they want to use them, and when they would be of most benefit during their surgical journey. METHODS: Patients attending bariatric surgery clinics in one hospital in the North of England were invited to participate. Semistructured interviews were conducted with purposively sampled pre- and postoperative patients to discuss lifestyle changes and the use of digital technologies to complement their care. The interviews were audio recorded and transcribed verbatim. Reflexive thematic analysis enabled the development of themes from the data. Ethical approval was obtained from the National Health Service Health Research Authority. RESULTS: A total of 20 patients were interviewed (preoperative phase: 40% (8/20); postoperative phase: 60% (12/20). A total of 4 overarching themes were developed and related to the optimization of technology functionality. These centered on providing tailored content and support; facilitating self-monitoring and goal setting; delivering information in an accessible, trusted, and usable manner; and meeting patient information-seeking and engagement needs during the surgical pathway. Functionalities that delivered personalized feedback and postoperative follow-up were considered beneficial. Individualized goal setting functionality could support a generation of digitally engaged patients with bariatric conditions as working toward achievable targets was deemed an effective strategy for motivating behavior change. The creation of digital package of care checklists between patients and clinicians was a novel finding from this study. CONCLUSIONS: Perceptions of patients undergoing bariatric surgery validated the integration of digital technologies within the surgical pathway, offering enhanced connectedness and support. Recommendations are made relating to the design, content, and functionality of digital interventions to best address the needs of this cohort. These findings have the potential to influence the co-design and integration of person-centered, perioperative technologies.

Eliciting willingness-to-pay to prevent hospital medication administration errors in the UK: a contingent valuation survey.

Medication errors are common in hospitals. These errors can result in adverse drug events (ADEs), which can reduce the health and well-being of patients', and their relatives and caregivers. Interventions have been developed to reduce medication errors, including those that occur at the administration stage. OBJECTIVE: We aimed to elicit willingness-to-pay (WTP) values to prevent hospital medication administration errors. DESIGN AND SETTING: An online, contingent valuation (CV) survey was conducted, using the random card-sort elicitation method, to elicit WTP to prevent medication errors. PARTICIPANTS: A representative sample of the UK public. METHODS: Seven medication error scenarios, varying in the potential for harm and the severity of harm, were valued. Scenarios were developed with input from: clinical experts, focus groups with members of the public and piloting. Mean and median WTP values were calculated, excluding protest responses or those that failed a logic test. A two-part model (logit, generalised linear model) regression analysis was conducted to explore predictive characteristics of WTP. RESULTS: Responses were collected from 1001 individuals. The proportion of respondents willing to pay to prevent a medication error increased as the severity of the ADE increased and was highest for scenarios that described actual harm occurring. Mean WTP across the scenarios ranged from £45 (95% CI £36 to £54) to £278 (95% CI £200 to £355). Several factors influenced both the value and likelihood of WTP, such as: income, known experience of medication errors, sex, field of work, marriage status, education level and employment status. Predictors of WTP were not, however, consistent across scenarios. CONCLUSIONS: This CV study highlights how the UK public value preventing medication errors. The findings from this study could be used to carry out a cost-benefit analysis which could inform implementation decisions on the use of technology to reduce medication administration errors in UK hospitals.

An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events.

AIMS: We aim to seek expert opinion and gain consensus on the risks associated with a range of prescribing scenarios, preventable using e-prescribing systems, to inform the development of a simulation tool to evaluate the risk and safety of e-prescribing systems (ePRaSE). METHODS: We conducted a two-round e-Delphi survey where expert participants were asked to score pre-designed prescribing scenarios using a five-point Likert scale to ascertain the likelihood of occurrence of the prescribing event, likelihood of occurrence of harm and the severity of the harm. RESULTS: Twenty-four experts consented to participate with 15 pand 13 participants completing rounds 1 and 2, respectively. Experts agreed on the level of risk associated with 136 out of 178 clinical scenarios with 131 scenarios categorised as high or extreme risk. CONCLUSION: We identified 131 extreme or high-risk prescribing scenarios that may be prevented using e-prescribing clinical decision support. The prescribing scenarios represent a variety of categories, with drug-disease contraindications being the most frequent, representing 37 (27%) scenarios, and antimicrobial agents being the most common drug class, representing 28 (21%) of the scenarios. Our e-Delphi study has achieved expert consensus on the risk associated with a range of clinical scenarios with most of the scenarios categorised as extreme or high risk. These prescribing scenarios represent the breadth of preventable prescribing error categories involving both basic and advanced clinical decision support. We will use the findings of this study to inform the development of the e-prescribing risk and safety evaluation tool.

Support for Healthcare Professionals After Surgical Patient Safety Incidents: A Qualitative Descriptive Study in 5 Teaching Hospitals.

OBJECTIVE: Patient safety incidents can have a profound effect on healthcare professionals, with some experiencing emotional and psychological distress. This study explored the support medical and nonmedical operating room staff received after being involved in a surgical patient safety incident(s) in 5 UK teaching hospitals. METHODS: An invitation letter and information sheet were e-mailed to all medical and nonmedical operating room staff (N = 927) across the 5 sites. Semistructured interviews were arranged with a range of different healthcare professionals working in operating rooms across a wide variety of surgical specialities. Interviews were audio recorded, transcribed verbatim, and analyzed using an inductive thematic approach. RESULTS: We conducted 45 interviews with medical and nonmedical operating room staff, who emphasized the importance of receiving personalized support soon after the incident. Operating room staff described how the first "go to" people were their peers and reported feeling comforted when their peers empathized with their own experience(s). Other participants found it very difficult to seek support, perceiving it as a sign of weakness. Although family members played an important role in supporting second victims, some participants felt unable to discuss the incident with them, fearing that they might not understand. CONCLUSIONS: There should be clear support structures in place for operating room staff who have been involved in surgical incidents. Health organizations need to offer timely support to frontline staff after these incidents. Senior clinicians should be proactive in offering support to junior colleagues and empathize with their own experiences, thus shifting the competitive culture to one of openness and support.

Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review.

BACKGROUND AND OBJECTIVES: Sepsis is a life-threatening condition that is associated with increased mortality. Artificial intelligence tools can inform clinical decision making by flagging patients at risk of developing infection and subsequent sepsis. This systematic review aims to identify the optimal set of predictors used to train machine learning algorithms to predict the likelihood of an infection and subsequent sepsis. METHODS: This systematic review was registered in PROSPERO database (CRD42020158685). We conducted a systematic literature review across 3 large databases: Medline, Cumulative Index of Nursing and Allied Health Literature, and Embase. Quantitative primary research studies that focused on sepsis prediction associated with bacterial infection in adults in all care settings were eligible for inclusion. RESULTS: Seventeen articles met our inclusion criteria. We identified 194 predictors that were used to train machine learning algorithms, with 13 predictors used on average across all included studies. The most prevalent predictors included age, gender, smoking, alcohol intake, heart rate, blood pressure, lactate level, cardiovascular disease, endocrine disease, cancer, chronic kidney disease (eGFR<60 mL/min), white blood cell count, liver dysfunction, surgical approach (open or minimally invasive), and pre-operative haematocrit < 30 %. All included studies used artificial intelligence techniques, with average sensitivity 75.7 ± 17.88, and average specificity 63.08 ± 22.01. CONCLUSION: The type of predictors influenced the predictive power and predictive timeframe of the developed machine learning algorithm. Predicting the likelihood of sepsis through artificial intelligence can help concentrate finite resources to those patients who are most at risk. Future studies should focus on developing more sensitive and specific algorithms.

Learning from safety incidents in high-reliability organizations: a systematic review of learning tools that could be adapted and used in healthcare.

OBJECTIVE: A high-reliability organization (HRO) is an organization that has sustained almost error-free performance, despite operating in hazardous conditions where the consequences of errors could be catastrophic. A number of tools and initiatives have been used within HROs to learn from safety incidents, some of which have the potential to be adapted and used in healthcare. We conducted a systematic review to identify any learning tools deemed to be effective that could be adapted and used by multidisciplinary teams in healthcare following a patient safety incident. METHODS: This review followed the Preferred Reporting Items for Systematic Reviews and MetaAnalyses for Protocols reporting guidelines and was registered with the PROSPERO (CRD42017071528). A search of databases was carried out in January 2021, from the date of their commencement. We conducted a search on electronic databases such as Web of Science, Science Direct, MEDLINE in Process Jan 1950-present, EMBASE Jan 1974-present, CINAHL 1982-present, PsycINFO 1967-present, Scopus and Google Scholar. We also searched the grey literature including reports from government agencies, relevant doctoral dissertations and conference proceedings. A customized data extraction form was used to capture pertinent information from included studies and Critical Appraisal Skills Programme tool to appraise on their quality. RESULTS: A total of 5921 articles were identified, with 964 duplicate articles removed and 4932 excluded at the title (4055), abstract (510) and full-text (367) stages. Twenty-five articles were included in the review. Learning tools identified included debriefing, simulation, crew resource management and reporting systems to disseminate safety messages. Debriefing involved deconstructing incidents using reflective questions, whilst simulation training involved asking staff to relive the event again by performing the task(s) in a role-play scenario. Crew resource management is a set of training procedures that focus on communication, leadership and decision-making. Sophisticated incident-reporting systems provide valuable information on hazards and were widely recommended as a way of disseminating key safety messages following safety incidents. These learning tools were found to have a positive impact on learning if conducted soon after the incident with efficient facilitation. CONCLUSION: Healthcare organizations should find ways to adapt to the learning tools or initiatives used in HROs following safety incidents. It is challenging to recommend any specific one as all learning tools have shown considerable promise. However, the way these tools or initiatives are implemented is critical, and so further work is needed to explore how to successfully embed them into healthcare organizations so that everyone at every level of the organization embraces them.

Designing the Optimal Digital Health Intervention for Patients' Use Before and After Elective Orthopedic Surgery: Qualitative Study.

BACKGROUND: Health behavior changes made by patients during the perioperative period can impact the outcomes and success of elective surgeries. However, there remains a limited understanding of how best to support patients during this time, particularly through the use of digital health interventions. Recognizing and understanding the potential unmet needs of elective orthopedic surgery patients is central to motivating healthier behavior change, improving recovery, and optimizing overall surgical success in the short and long term. OBJECTIVE: The aim of this study is to explore patient perspectives on technology features that would help support them to change their lifestyle behaviors during the pre- and postoperative periods, and that could potentially maintain long-term healthy lifestyles following recovery. METHODS: Semistructured interviews with pre- and postoperative elective orthopedic patients were conducted between May and June 2020 using telephone and video call-based software. Patient perspectives on the use of digital technologies to complement current surgical care and support with lifestyle behavior changes were discussed. Interviews were audio recorded and transcribed verbatim. Reflexive thematic analysis enabled the development of themes from the data, with QSR NVivo software (version 12) facilitating data management. Ethical approval was obtained from the National Health Service Health Research Authority. RESULTS: A total of 18 participants were interviewed. Four themes were developed from the data regarding the design and functionality of digital technologies to best support the perioperative journey. These center around an intervention's ability to incorporate interactive, user-centered features; direct a descriptive and structured recovery; enable customizable, patient-controlled settings; and deliver both general and specific surgical advice in a timely manner. Interventions that are initiated preoperatively and continued postoperatively were perceived as beneficial. Interventions designed with personalized milestones were found to better guide patients through a structured recovery. Individualized tailoring of preparatory and recovery information was desired by patients with previously high levels of physical activity before surgery. The use of personalized progression-based exercises further encouraged physical recovery; game-like rewards and incentives were regarded as motivational for making and sustaining health behavior change. In-built video calling and messaging features offered connectivity with peers and clinicians for supported care delivery. CONCLUSIONS: Specific intervention design and functionality features can provide better, structured support for elective orthopedic patients across the entire surgical journey and beyond. This study provides much-needed evidence relating to the optimal design and timing of digital interventions for elective orthopedic surgical patients. Findings from this study suggest a desire for personalized perioperative care, in turn, supporting patients to make health behavior changes to optimize surgical success. These findings should be used to influence future co-design projects to enable the design and implementation of patient-focused, tailored, and targeted digital health technologies within modern health care settings.

Digital and Mobile Technologies to Promote Physical Health Behavior Change and Provide Psychological Support for Patients Undergoing Elective Surgery: Meta-Ethnography and Systematic Review.

BACKGROUND: Digital technology has influenced many aspects of modern living, including health care. In the context of elective surgeries, there is a strong association between preoperative physical and psychological preparedness, and improved postoperative outcomes. Health behavior changes made in the pre- and postoperative periods can be fundamental in determining the outcomes and success of elective surgeries. Understanding the potential unmet needs of patients undergoing elective surgery is central to motivating health behavior change. Integrating digital and mobile health technologies within the elective surgical pathway could be a strategy to remotely deliver this support to patients. OBJECTIVE: This meta-ethnographic systematic review explores digital interventions supporting patients undergoing elective surgery with health behavior changes, specifically physical activity, weight loss, dietary intake, and psychological support. METHODS: A literature search was conducted in October 2019 across 6 electronic databases (International Prospective Register of Systematic Reviews [PROSPERO]: CRD42020157813). Qualitative studies were included if they evaluated the use of digital technologies supporting behavior change in adult patients undergoing elective surgery during the pre- or postoperative period. Study quality was assessed using the Critical Appraisal Skills Programme tool. A meta-ethnographic approach was used to synthesize existing qualitative data, using the 7 phases of meta-ethnography by Noblit and Hare. Using this approach, along with reciprocal translation, enabled the development of 4 themes from the data. RESULTS: A total of 18 studies were included covering bariatric (n=2, 11%), cancer (n=13, 72%), and orthopedic (n=3, 17%) surgeries. The 4 overarching themes appear to be key in understanding and determining the effectiveness of digital and mobile interventions to support surgical patients. To successfully motivate health behavior change, technologies should provide motivation and support, enable patient engagement, facilitate peer networking, and meet individualized patient needs. Self-regulatory features such as goal setting heightened patient motivation. The personalization of difficulty levels in virtual reality-based rehabilitation was positively received. Internet-based cognitive behavioral therapy reduced depression and distress in patients undergoing cancer surgery. Peer networking provided emotional support beyond that of patient-provider relationships, improving quality of life and care satisfaction. Patients expressed the desire for digital interventions to be individually tailored according to their physical and psychological needs, before and after surgery. CONCLUSIONS: These findings have the potential to influence the future design of patient-centered digital and mobile health technologies and demonstrate a multipurpose role for digital technologies in the elective surgical pathway by motivating health behavior change and offering psychological support. Through the synthesis of patient suggestions, we highlight areas for digital technology optimization and emphasize the importance of content tailored to suit individual patients and surgical procedures. There is a significant rationale for involving patients in the cocreation of digital health technologies to enhance engagement, better support behavior change, and improve surgical outcomes.

Relationship between labour force satisfaction, wages and retention within the UK National Health Service: a systematic review of the literature.

OBJECTIVES: A systematic review was undertaken to understand the nature of the relationship between the UK National Health Service (NHS) labour force and satisfaction, retention and wages. DESIGN: Narrative systematic review. DATA SOURCES: The literature was searched using seven databases in January 2020: MEDLINE (1996-present), the Cumulative Index to Nursing and Allied Health Literature (CINAHL via EBSCO) (1984-present), Embase (1996-present), PsycINFO (1987-present), ProQuest (1996-present), Scopus (all years) and Cochrane library (all years). We used medical subject headings and key words relating to 'retention', 'satisfaction' and 'wages'. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Primary research studies or reviews that focused on the following relationships within the NHS workforce: wages and job satisfaction, job satisfaction and retention or wages and retention. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers screened all titles, abstracts and full texts, with arbitration by a third reviewer. RESULTS: 27 803 articles were identified and after removing duplicates (n=17 156), articles were removed at the title (n=10 421), abstract (n=150) and full-text (n=45) stages. A total of 31 full-text articles were included. They identified three broad themes, low job satisfaction impacting negatively on job retention, poor pay impacting negatively on staff satisfaction and the limitations of increasing pay as a means of improving staff retention. Several factors affected these relationships, including the environment, discrimination, flexibility, autonomy, training and staffing levels. CONCLUSIONS: This review highlighted how multiple factors influence NHS labour force retention. Pay was found to influence satisfaction, which in turn affected retention. An increase in wages alone is unlikely to be sufficient to ameliorate the concerns of NHS workers. More research is needed to identify the role of autonomy on retention. A system leadership approach underpinned by data is required to implement bespoke job satisfaction improvement strategies to improve retention and achieve the goals of the NHS Long Term Plan.

A systematic review of the impact of health information technology on nurses' time.

OBJECTIVE: Nursing time represents one of the highest costs for most health services. We conducted a systematic review of the literature on the impact of health information technology on nurses' time. MATERIALS AND METHODS: We followed PRISMA guidelines and searched 6 large databases for relevant articles published between Jan 2004 and December 2019. Two authors reviewed the titles, abstracts, and full texts. We included articles that included a comparison group in the design, measured the time taken to carry out documentation or medication administration, documented the quantitative estimates of time differences between the 2, had nurses as subjects, and was conducted in either a care home, hospital, or community clinic. RESULTS: We identified a total of 1647 articles, of which 33 met our inclusion criteria. Twenty-one studies reported the impact of 12 different health information technology (HIT) implementations on nurses' documentation time. Weighted averages were calculated for studies that implemented barcode medication administration (BCMA) and 2 weighted averages for those that implemented EHRs, as these studies used different sampling units; both showed an increase in the time spent in documentation (+22% and +46%). However, the time spent carrying out medication administration following BCMA implementation fell by 33% (P < .05). HIT also caused a redistribution of nurses' time which, in some cases, was spent in more "value-adding" activities, such as delivering direct patient care as well as inter-professional communication. DISCUSSION AND CONCLUSIONS: Most of the HIT systems increased nursing documentation time, although time fell for medication administration following BCMA. Many HIT systems also resulted in nurses spending more time in direct care and "value-adding" activities.

The value of teachable moments in surgical patient care and the supportive role of digital technologies.

Evidence strongly supports improved outcomes following surgery when patients are more physically active, have better dietary intake, or are generally fitter prior to surgery. Having an operation is a major life event for patients, and many are not educated around what they can do as individuals to aid a speedier and more successful recovery following their operation. What if there was a time point before surgery where clinicians could inspire patients to adjust their lifestyles for the better, in order to see fewer complications after surgery? This is where the concept of teachable moments comes into play. This commentary explores the concept of teachable moments and their value in surgical patient care and discusses the potentially under-utilized opportunities on hand to the surgical multidisciplinary team to remotely support patients using digital health technologies.