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.

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.

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.

The national cost of adverse drug events resulting from inappropriate medication-related alert overrides in the United States.

Objective: To estimate the national cost of ADEs resulting from inappropriate medication-related alert overrides in the U.S. inpatient setting. Materials and Methods: We used three different regression models (Basic, Model 1, Model 2) with model inputs taken from the medical literature. A random sample of 40 990 adult inpatients at the Brigham and Women's Hospital (BWH) in Boston with a total of 1 639 294 medication orders was taken. We extrapolated BWH medication orders using 2014 National Inpatient Sample (NIS) data. Results: Using three regression models, we estimated that 29.7 million adult inpatient discharges in 2014 resulted in between 1.02 billion and 1.07 billion medication orders, which in turn generated between 75.1 million and 78.8 million medication alerts, respectively. Taking the basic model (78.8 million), we estimated that 5.5 million medication-related alerts might have been inappropriately overridden, resulting in approximately 196 600 ADEs nationally. This was projected to cost between $871 million and $1.8 billion for treating preventable ADEs. We also estimated that clinicians and pharmacists would have jointly spent 175 000 hours responding to 78.8 million alerts with an opportunity cost of $16.9 million. Discussion and Conclusion: These data suggest that further optimization of hospitals computerized provider order entry systems and their associated clinical decision support is needed and would result in substantial savings. We have erred on the side of caution in developing this range, taking two conservative cost estimates for a preventable ADE that did not include malpractice or litigation costs, or costs of injuries to patients.

Consensus methodology to determine minor ailments appropriate to be directed for management within community pharmacy.

BACKGROUND: National Health Service (NHS) 111, a medical helpline for urgent care used within the England and Scotland, receives significant numbers of patient calls yearly for a range of clinical conditions. Some are considered high acuity and mainly directed to urgent and emergency care. Low acuity conditions are also directed to these costly, overburdened services. Community pharmacy is a recognised setting for effective low acuity condition management and could offer an alternative. OBJECTIVE: To design and evaluate a new NHS111 pathway re-directing patients with low acuity conditions to community pharmacy. METHODS: Two consensus development stakeholder workshops were undertaken. A "low acuity" condition was defined as one that can be clinically assessed by a community pharmacist and requires a treatment and/or advice available within a community pharmacy. Retrospective NHS111 patient data (February-August 2016) from the North East of England and access to the NHS Pathways clinical decision support software were available to stakeholders. The NHS111 data demonstrated the volume of patient calls for these conditions that could have been redirected to community pharmacy. RESULTS: Stakeholders reached consensus that 64 low acuity conditions could be safely redirected to community pharmacy via NHS111. This represented approximately 35,000 patients (11.5% of total) being shifted away from the higher cost settings in the North East region alone during February-August 2016. The stakeholder group discussions provided rationale behind their classifications of conditions to ensure patient safety, the care experience and added value. CONCLUSIONS: The resulting definitive list of low acuity conditions that could be directed to community pharmacy via NHS111 could result in a shift of workload from urgent and emergency care settings. Future work needs to evaluate the cost, clinical outcomes, patient satisfaction of a community pharmacy referral service that has the potential to improve integration of community pharmacy in the wider NHS.

A value set for documenting adverse reactions in electronic health records.

Objective: To develop a comprehensive value set for documenting and encoding adverse reactions in the allergy module of an electronic health record. Materials and Methods: We analyzed 2 471 004 adverse reactions stored in Partners Healthcare's Enterprise-wide Allergy Repository (PEAR) of 2.7 million patients. Using the Medical Text Extraction, Reasoning, and Mapping System, we processed both structured and free-text reaction entries and mapped them to Systematized Nomenclature of Medicine - Clinical Terms. We calculated the frequencies of reaction concepts, including rare, severe, and hypersensitivity reactions. We compared PEAR concepts to a Federal Health Information Modeling and Standards value set and University of Nebraska Medical Center data, and then created an integrated value set. Results: We identified 787 reaction concepts in PEAR. Frequently reported reactions included: rash (14.0%), hives (8.2%), gastrointestinal irritation (5.5%), itching (3.2%), and anaphylaxis (2.5%). We identified an additional 320 concepts from Federal Health Information Modeling and Standards and the University of Nebraska Medical Center to resolve gaps due to missing and partial matches when comparing these external resources to PEAR. This yielded 1106 concepts in our final integrated value set. The presence of rare, severe, and hypersensitivity reactions was limited in both external datasets. Hypersensitivity reactions represented roughly 20% of the reactions within our data. Discussion: We developed a value set for encoding adverse reactions using a large dataset from one health system, enriched by reactions from 2 large external resources. This integrated value set includes clinically important severe and hypersensitivity reactions. Conclusion: This work contributes a value set, harmonized with existing data, to improve the consistency and accuracy of reaction documentation in electronic health records, providing the necessary building blocks for more intelligent clinical decision support for allergies and adverse reactions.

The return on investment of implementing a continuous monitoring system in general medical-surgical units.

OBJECTIVES: To evaluate the cost savings attributable to the implementation of a continuous monitoring system in a medical-surgical unit and to determine the return on investment associated with its implementation. DESIGN: Return on investment analysis. SETTING: A 316-bed community hospital. PATIENTS: Medicine, surgery, or trauma patients admitted or transferred to a 33-bed medical-surgical unit. INTERVENTIONS: Each bed was equipped with a monitoring unit, with data collected and compared in a 9-month preimplementation period to a 9-month postimplementation period. MEASUREMENTS AND MAIN RESULTS: Two models were constructed: a base case model (A) in which we estimated the total cost savings of intervention effects and a conservative model (B) in which we only included the direct variable cost component for the final day of length of stay and treatment of pressure ulcers. In the 5-year return on investment model, the monitoring system saved between $3,268,000 (conservative model B) and $9,089,000 (base model A), given an 80% prospective reimbursement rate. A net benefit of between $2,687,000 ($658,000 annualized) and $8,508,000 ($2,085,000 annualized) was reported, with the hospital breaking even on the investment after 0.5 and 0.75 of a year, respectively. The average net benefit of implementing the system ranged from $224 per patient (model B) to $710 per patient (model A) per year. A multiway sensitivity analyses was performed using the most and least favorable conditions for all variables. In the case of the most favorable conditions, the analysis yielded a net benefit of $3,823,000 (model B) and $10,599,000 (model A), and for the least favorable conditions, a net benefit of $715,000 (model B) and $3,386,000 (model A). The return on investment for the sensitivity analysis ranged from 127.1% (25.4% annualized) (model B) to 601.7% (120.3% annualized) (model A) for the least favorable conditions and from 627.5% (125.5% annualized) (model B) to 1739.7% (347.9% annualized) (model A) for the most favorable conditions. CONCLUSIONS: Implementation of this monitoring system was associated with a highly positive return on investment. The magnitude and timing of these expected gains to the investment costs may justify the accelerated adoption of this system across remaining inpatient non-ICU wards of the community hospital.

A qualitative study identifying the cost categories associated with electronic health record implementation in the UK.

OBJECTIVE: We conducted a prospective evaluation of different forms of electronic health record (EHR) systems to better understand the costs incurred during implementation and the factors that can influence these costs. METHODS: We selected a range of diverse organizations across three different geographical areas in England that were at different stages of implementing three centrally procured applications, that is, iSOFT's Lorenzo Regional Care, Cerner's Millennium, and CSE's RiO. 41 semi-structured interviews were conducted with hospital staff, members of the implementation team, and those involved in the implementation at a national level. RESULTS: Four main overarching cost categories were identified: infrastructure (eg, hardware and software), personnel (eg, training team), estates/facilities (eg, space), and other (eg, training materials). Many factors were felt to impact on these costs, with different hospitals choosing varying amounts and types of infrastructure, diverse training approaches for staff, and different software applications to integrate with the new system. CONCLUSIONS: Improving the quality and safety of patient care through EHR adoption is a priority area for UK and US governments and policy makers worldwide. With cost considered one of the most significant barriers, it is important for hospitals and governments to be clear from the outset of the major cost categories involved and the factors that may impact on these costs. Failure to adequately train staff or to follow key steps in implementation has preceded many of the failures in this domain, which can create new safety hazards.

The causes of prescribing errors in English general practices: a qualitative study.

BACKGROUND: Few detailed studies exist of the underlying causes of prescribing errors in the UK. AIM: To examine the causes of prescribing and monitoring errors in general practice and provide recommendations for how they may be overcome. DESIGN AND SETTING: Qualitative interview and focus group study with purposive sampling of English general practices. METHOD: General practice staff from 15 general practices across three PCTs in England participated in a combination of semi-structured interviews (n = 34) and six focus groups (n = 46). Thematic analysis informed by Reason's Accident Causation Model was used. RESULTS: Seven categories of high-level error-producing conditions were identified: the prescriber, the patient, the team, the working environment, the task, the computer system, and the primary-secondary care interface. These were broken down to reveal various error-producing conditions: the prescriber's therapeutic training, drug knowledge and experience, knowledge of the patient, perception of risk, and their physical and emotional health; the patient's characteristics and the complexity of the individual clinical case; the importance of feeling comfortable within the practice team was highlighted, as well as the safety implications of GPs signing prescriptions generated by nurses when they had not seen the patient for themselves; the working environment with its extensive workload, time pressures, and interruptions; and computer-related issues associated with mis-selecting drugs from electronic pick-lists and overriding alerts were all highlighted as possible causes of prescribing errors and were often interconnected. CONCLUSION: Complex underlying causes of prescribing and monitoring errors in general practices were highlighted, several of which are amenable to intervention.