A safer place for patients: learning to improve patient safety

1 Every day over one million people are treated successfully by National Health Service (NHS) acute, ambulance and mental health trusts. However, healthcare relies on a range of complex interactions of people, skills, technologies and drugs, and sometimes things do go wrong. For most countries, patient safety is now the key issue in healthcare quality and risk management. The Department of Health (the Department) estimates that one in ten patients admitted to NHS hospitals will be unintentionally harmed, a rate similar to other developed countries. Around 50 per cent of these patient safety incidentsa could have been avoided, if only lessons from previous incidents had been learned. 2 There are numerous stakeholders with a role in keeping patients safe in the NHS, many of whom require trusts to report details of patient safety incidents and near misses to them (Figure 2). However, a number of previous National Audit Office reports have highlighted concerns that the NHS has limited information on the extent and impact of clinical and non-clinical incidents and trusts need to learn from these incidents and share good practice across the NHS more effectively (Appendix 1). 3 In 2000, the Chief Medical Officer’s report An organisation with a memory 1 , identified that the key barriers to reducing the number of patient safety incidents were an organisational culture that inhibited reporting and the lack of a cohesive national system for identifying and sharing lessons learnt. 4 In response, the Department published Building a safer NHS for patients3 detailing plans and a timetable for promoting patient safety. The goal was to encourage improvements in reporting and learning through the development of a new mandatory national reporting scheme for patient safety incidents and near misses. Central to the plan was establishing the National Patient Safety Agency to improve patient safety by reducing the risk of harm through error. The National Patient Safety Agency was expected to: collect and analyse information; assimilate other safety-related information from a variety of existing reporting systems; learn lessons and produce solutions. 5 We therefore examined whether the NHS has been successful in improving the patient safety culture, encouraging reporting and learning from patient safety incidents. Key parts of our approach were a census of 267 NHS acute, ambulance and mental health trusts in Autumn 2004, followed by a re-survey in August 2005 and an omnibus survey of patients (Appendix 2). We also reviewed practices in other industries (Appendix 3) and international healthcare systems (Appendix 4), and the National Patient Safety Agency’s progress in developing its National Reporting and Learning System (Appendix 5) and other related activities (Appendix 6). 6 An organisation with a memory1 was an important milestone in the NHS’s patient safety agenda and marked the drive to improve reporting and learning. At the local level the vast majority of trusts have developed a predominantly open and fair reporting culture but with pockets of blame and scope to improve their strategies for sharing good practice. Indeed in our re-survey we found that local performance had continued to improve with more trusts reporting having an open and fair reporting culture, more trusts with open reporting systems and improvements in perceptions of the levels of under-reporting. At the national level, progress on developing the national reporting system for learning has been slower than set out in the Department’s strategy of 2001 3 and there is a need to improve evaluation and sharing of lessons and solutions by all organisations with a stake in patient safety. There is also no clear system for monitoring that lessons are learned at the local level. Specifically: a The safety culture within trusts is improving, driven largely by the Department’s clinical governance initiative 4 and the development of more effective risk management systems in response to incentives under initiatives such as the NHS Litigation Authority’s Clinical Negligence Scheme for Trusts (Appendix 7). However, trusts are still predominantly reactive in their response to patient safety issues and parts of some organisations still operate a blame culture. b All trusts have established effective reporting systems at the local level, although under-reporting remains a problem within some groups of staff, types of incidents and near misses. The National Patient Safety Agency did not develop and roll out the National Reporting and Learning System by December 2002 as originally envisaged. All trusts were linked to the system by 31 December 2004. By August 2005, at least 35 trusts still had not submitted any data to the National Reporting and Learning System. c Most trusts pointed to specific improvements derived from lessons learnt from their local incident reporting systems, but these are still not widely promulgated, either within or between trusts. The National Patient Safety Agency has provided only limited feedback to trusts of evidence-based solutions or actions derived from the national reporting system. It published its first feedback report from the Patient Safety Observatory in July 2005

Predicting the Risk of Falling with Artificial Intelligence

Predicting the Risk of Falling with Artificial Intelligence Abstract Background: Fall prevention is a huge patient safety concern among all healthcare organizations. The high prevalence of patient falls has grave consequences, including the cost of care, longer hospital stays, unintentional injuries, and decreased patient and staff satisfaction. Preventing a patient from falling is critical in maintaining a patient’s quality of life and averting the high cost of healthcare expenses. Local Problem: Two hospitals\u27 healthcare system saw a significant increase in inpatient falls. The fall rate is one of the nursing quality indicators, and fall reduction is a key performance indicator of high-quality patient care. Methods: This quality improvement evidence-based observational project compared the rate of fall (ROF) between the experimental and control unit. Pearson’s chi-square and Fisher’s exact test were used to analyze and compare results. Qualtrics surveys evaluated the nurses’ perception of AI, and results were analyzed using the Mann-Whitney Rank Sum test. Intervention. Implementing an artificial intelligence-assisted fall predictive analytics model that can timely and accurately predict fall risk can mitigate the increase in inpatient falls. Results: The pilot unit (Pearson’s chi-square = p pp\u3c0.001). Conclusions: AI-assisted automatic fall predictive risk assessment produced a significant reduction if the number of falls, the ROF, and the use of fall countermeasures. Further, nurses’ perception of AI improved after the introduction of FPAT and presentation

Fall prevention intervention technologies: A conceptual framework and survey of the state of the art

In recent years, an ever increasing range of technology-based applications have been developed with the goal of assisting in the delivery of more effective and efficient fall prevention interventions. Whilst there have been a number of studies that have surveyed technologies for a particular sub-domain of fall prevention, there is no existing research which surveys the full spectrum of falls prevention interventions and characterises the range of technologies that have augmented this landscape. This study presents a conceptual framework and survey of the state of the art of technology-based fall prevention systems which is derived from a systematic template analysis of studies presented in contemporary research literature. The framework proposes four broad categories of fall prevention intervention system: Pre-fall prevention; Post-fall prevention; Fall injury prevention; Cross-fall prevention. Other categories include, Application type, Technology deployment platform, Information sources, Deployment environment, User interface type, and Collaborative function. After presenting the conceptual framework, a detailed survey of the state of the art is presented as a function of the proposed framework. A number of research challenges emerge as a result of surveying the research literature, which include a need for: new systems that focus on overcoming extrinsic falls risk factors; systems that support the environmental risk assessment process; systems that enable patients and practitioners to develop more collaborative relationships and engage in shared decision making during falls risk assessment and prevention activities. In response to these challenges, recommendations and future research directions are proposed to overcome each respective challenge.The Royal Society, grant Ref: RG13082

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

Committed to Safety: Ten Case Studies on Reducing Harm to Patients

Presents case studies of healthcare organizations, clinical teams, and learning collaborations to illustrate successful innovations for improving patient safety nationwide. Includes actions taken, results achieved, lessons learned, and recommendations

How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

Complex Care Management Program Overview

This report includes brief updates on various forms of complex care management including: Aetna - Medicare Advantage Embedded Case Management ProgramBrigham and Women's Hospital - Care Management ProgramIndependent Health - Care PartnersIntermountain Healthcare and Oregon Health and Science University - Care Management PlusJohns Hopkins University - Hospital at HomeMount Sinai Medical Center -- New York - Mount Sinai Visiting Doctors Program/ Chelsea-Village House Calls ProgramsPartners in Care Foundation - HomeMeds ProgramPrinceton HealthCare System - Partnerships for PIECEQuality Improvement for Complex Chronic Conditions - CarePartner ProgramSenior Services - Project Enhance/EnhanceWellnessSenior Whole Health - Complex Care Management ProgramSumma Health/Ohio Department of Aging - PASSPORT Medicaid Waiver ProgramSutter Health - Sutter Care Coordination ProgramUniversity of Washington School of Medicine - TEAMcar

Improving the Quality of Electronic Documentation in Critical Care Nursing

Electronic nursing documentation systems can facilitate complete, accurate, timely documentation practices, but without effective policies and procedures in place, a gap in practice exists and quality of care may be impacted. This systematic review of literature examined current evidence regarding electronic nursing documentation quality. General systems theory and the Donabedian model of health care quality provided the framework for the project. Electronic databases PubMed and the Cumulative Index of Nursing and Allied Health were searched for articles addressing electronic nursing documentation practices. The Cochrane systematic review methodology was used to analyze the articles. Articles were excluded if published before 2001 or not in the English language. The search revealed 860 articles of which 35 were included in the final review. Most studies were quasi-experimental involving multiple interventions such as clinical decision support (CDSS), education, and audit and feedback specific documentation foci. The most reported outcomes were an improvement in documentation completeness and correctness. A multifaceted intervention strategy consisting of CDSS, education, and audit and feedback can be used to improve electronic documentation completeness and correctness. Policies and procedures regarding documentation practice should support the intended outcomes. Electronic documentation systems can improve completeness, but care should be taken not to depend on the quantity of documentation alone. Further research may shed light on the importance of concordance or plausibility, and the truth of documentation and ultimately how that can impact social determinates of health and social change