Health Information Technology Supporting Adherence Memory Disorder Patients: A Systematic Literature Review.

BACKGROUND: People with memory disorders have difficulty adhering to treatments. With technological advances, it remains important to investigate the potential of health information technology (HIT) in supporting medication adherence among them. OBJECTIVES: This review investigates the role of HIT in supporting adherence to medication and therapies among patients with memory issues. It also captures the factors that impact technology adherence interventions. METHODS: We searched the literature for relevant publications published until March 15, 2023, using technology to support adherence among patients with memory issues (dementia, Alzheimer's, amnesia, mild cognitive impairment, memory loss, etc.). The review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We conducted a quality assessment of the papers following the Mixed Methods Appraisal Tool. RESULTS: Fifteen studies were included after carefully reviewing the 3,773 articles in the search. Methodological quality, as appraised, ranged from 80 to 100% with eight studies rated 100%. The studies overall did not have a high risk of bias. Thus, all of the 15 studies were included. Technologies investigated were classified into four groups based on their impact: therapeutic patient education, simplifying treatment regimens, early follow-up visits and short-term treatment goals, and reminder programs. Different technologies were used (automatic drug dispensers or boxes, mobile health-based interventions, game-based interventions, e-health-based interventions, patient portals, and virtual reality). The factors impacting patients' adherence to technology-based treatment and medication were clustered into human-computer interaction and integration challenges. CONCLUSION: This study contributes to the literature by classifying the technologies that supported medication adherence among patients with memory issues in four groups. It also explores and presents the possible limitations of existing solutions to drive future research in supporting care for people with memory disorders.

Multisensory alarm to benefit alarm identification and decrease workload: a feasibility study.

The poor design of conventional auditory medical alarms has contributed to alarm desensitization, and eventually, alarm fatigue in medical personnel. This study tested a novel multisensory alarm system which aims to help medical personnel better interpret and respond to alarm annunciation during periods of high cognitive load such as those found within intensive care units. We tested a multisensory alarm that combined auditory and vibrotactile cues to convey alarm type, alarm priority, and patient identity. Testing was done in three phases: control (conventional auditory), Half (limited multisensory alarm), and Full (complete multisensory alarm). Participants (N = 19, undergraduates) identified alarm type, priority, and patient identity (patient 1 or 2) using conventional and multisensory alarms, while simultaneously completing a cognitively demanding task. Performance was based on reaction time (RT) and identification accuracy of alarm type and priority. Participants also reported their perceived workload. RT was significantly faster for the Control phase (p < 0.05). Participant performance in identifying alarm type, priority, and patient did not differ significantly between the three phase conditions (p = 0.87, 0.37, and 0.14 respectively). The Half multisensory phase produced the lowest mental demand, temporal demand, and overall perceived workload score. These data suggest that implementation of a multisensory alarm with alarm and patient information may decrease perceived workload without significant changes in alarm identification performance. Additionally, a ceiling effect may exist for multisensory stimuli, with only part of an alarm benefitting from multisensory integration.

Shape Matters: A Neglected Feature of Medication Safety : Why Regulating the Shape of Medication Containers Can Improve Medication Safety.

This paper aims to highlight how to reduce medication errors through the implementation of human factors science to the design features of medication containers. Despite efforts to employ automation for increased safety and decreased workload, medication administration in hospital wards is still heavily dependent on human operators (pharmacists, nurses, physicians, etc.). Improving this multi-step process requires its being studied and designed as an interface in a complex socio-technical system. Human factors engineering, also known as ergonomics, involves designing socio-technical systems to improve overall system performance, and reduces the risk of system, and in particular, operator, failures. The incorporation of human factors principles into the design of the work environment and tools that are in use during medication administration could improve this process. During periods of high workload, the cognitive effort necessary to work through a very demanding process may overwhelm even expert operators. In such conditions, the entire system should facilitate the human operator's high level of performance. Regarding medications, clinicians should be provided with as many perceptual cues as possible to facilitate medication identification. Neglecting the shape of the container as one of the features that differentiates between classes of medications is a lost opportunity to use a helpful characteristic, and medication administration failures that happen in the absence of such intentional design arise from "designer error" rather than "user error". Guidelines that define a container's shape for each class of medication would compel pharmaceutical manufacturers to be compatible and would eliminate the confusion that arises when a hospital changes the supplier of a given medication.

Real-time video communication between ambulance paramedic and scene - a simulation-based study.

INTRODUCTION: Telemedicine has been widely used in various medical settings including in Emergency Medical Services (EMS). The goal of this study was to assess the possible roles of real-time video communication between paramedics and bystanders at scenes of emergency, in the analysis and treatment of patients. METHODS: 44 experienced paramedics participated in a simulation. Participants communicated with the experimenter presenting video clips showing patients that simulated three emergency scenarios: trauma, an unresponsive patient with cardiac arrest, and an opiate overdose. The simulation sessions were conducted through Zoom™, recorded, and then analyzed to document participants' questions, requests, instructions, and their timings during each scenario. RESULTS: The trauma scenario was assessed most promptly, with instructions to handle the bleeding provided by all paramedics. In the unresponsive patient with cardiac arrest scenario, most of the participants achieved a correct initial diagnosis, and in the opiate overdose scenario over half of paramedics sought visual clinical clues for the differential diagnoses of loss of consciousness and their causes. Additional results show the type of assessment, treatment and diagnosis participants provided in each scenario, and their confidence about situation. CONCLUSIONS: The findings show that direct video communication between paramedic and scene may facilitate correct diagnosis, provision of instructions for treatment, and early preparation of medications or equipment. These may decrease time to correct diagnosis and lifesaving treatment and impact patient morbidity and mortality. Moreover, the findings highlight the difference between incidents with higher visual clarity, such as trauma, and conditions that require an extended diagnosis to reveal, such as unresponsive patients. This may also increase the paramedics' mental preparedness for what is expected at the scene.

Improving Healthcare Practice Through the Implementation of Human Factors and Ergonomics Principles.

OBJECTIVE: Present a collection of papers focusing on improving healthcare practice through the implementation of human factors and ergonomics principles that were presented at the International Ergonomics Association (IEA) 2021 international conference. BACKGROUND: The mission of the IEA is to elaborate and advance ergonomics science and practice and to expand its scope of application. METHOD: We reviewed papers that were submitted for presentation at the IEA 2021 international conference and focused on improving healthcare practice through the implementation of human factors and ergonomics principles. RESULTS: The eight papers that are included in this special issue cover varied aspects of human factors application and implementation. CONCLUSION: This special issue provides clear evidence that the science of human factors is relevant and is continuing to grow and so is its implementation in healthcare. APPLICATION: This special issue offers a selection of applied works, providing a wide scope of human factors guidelines, methods, and theories in healthcare work environments.

Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations.

OBJECTIVE: To develop a new model to quantify information management dynamically and to identify factors that lead to information gaps. BACKGROUND: Information management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). Lessons learned from past MCIs indicate that poor information management can lead to increased mortality. Various instruments are used to evaluate information management during MCI training simulations, but the challenge of measuring and improving team leaders' abilities to manage information remains. METHOD: The Dynamic Communication Quantification (DCQ) model was developed based on the knowledge representation typology. Using multi point-of-view synchronized video, the model quantifies and visualizes information management. It was applied to six MCI simulations between 2014 and 2019, to identify factors that led to information gaps, and compared with other evaluation methods. RESULTS: Out of the three methods applied, only the DCQ model revealed two factors that led to information gaps: first, consolidation of numerous casualties from different areas, and second, tracking of casualty arrivals to the medical treatment area and departures from the MCI site. CONCLUSION: The DCQ model allows information management to be objectively quantified. Thus, it reveals a new layer of knowledge, presenting information gaps during an MCI. Because the model is applicable to all MCI team leaders, it can make MCI simulations more effective. APPLICATION: This DCQ model quantifies information management dynamically during MCI training simulations.

Vaccination of the Elderly in Assisted Living by the Israeli Emergency Medical Services.

Emergency Medical Services (EMS) in Israel was called on to vaccinate the most vulnerable population-the elderly in assisted living facilities and their caregivers. Two parameters led the operation: (1) maximum use of the scarce COVID-19 vaccine, and (2) minimizing the time it took to reach this entire population. We present the process of vaccinating 126 245 people in two weeks at 756 locations countrywide, focusing on the planning and logistics of this operation. Resilience, flexible logistics, and dedicated personnel provided an efficient public health operation.

The impact of data quality defects on clinical decision-making in the intensive care unit.

OBJECTIVE: Poor clinical data quality might affect clinical decision making and patient treatment. This study identifies quality defects in clinical data collected automatically by bedside monitoring devices in the Intensive Care Unit (ICU) and examines their effect on clinical decisions. METHODS: Real-world data collected from 7688 patients admitted to the general ICU in a tertiary referral hospital over seven years was retrospectively analyzed. Data quality defect detection methods that use time-series analysis techniques identified two types of data quality defects: (a) completeness: the extent of non-missing values, and (b) validity: the extent of non-extreme values within the continuous range of values. Data quality defects were compared to five scenarios of medication and procedure prescriptions that are common in ICU settings: Blood-pressure reduction, blood-pressure elevation, anesthesia medications, intubation procedures, and muscle relaxant medications. RESULTS: Results from a logistic regression revealed a strong connection between data quality and the clinical interventions examined: lower validity level increased the likelihood of prescription decisions for all five scenarios, and lower completeness level increased the likelihood of prescription decisions for some scenarios. DISCUSSION: The results highlight the possible effect of data quality defects on physicians' decisions. Lower validity of certain key clinical parameters, and in some scenarios lower completeness, correlated with stronger tendency to prescribe medications or perform invasive procedures. CONCLUSIONS: Data quality defects in clinical data affect decision making even without practitioners' awareness. Thus, it is important to emphasize these effects to ICU staff, as well as to medical device manufacturers.

Using a filming protocol to improve video-instructed cardiopulmonary resuscitation.

BACKGROUND: Video communications during cardiopulmonary resuscitation (CPR) can improve the quality of information exchange between a bystander performing CPR and an emergency medical dispatcher (EMD). OBJECTIVE: To improve chest compression effectiveness, a filming protocol instructing video camera placements around a patient was developed. This study measured whether the filming protocol increased chest compressions' effectiveness. METHODS: A simulation study was conducted comparing CPR effectiveness under three conditions: telephone-instructed, video-instructed, and video-instructed with the filming protocol. Twenty-five emergency medical technicians acted as EMDsin the three conditions. A mannequin measured five factors that determined the effectiveness of the chest compressions. RESULTS: Compared with telephone-instructed CPR, the filming protocol improved the proportion of time in which the bystander's hands were in the correct position during chest compressions. Compared with video-instructed CPR, the filming protocol improved both the proportion of time in which the chest was fully released after each compression and the proportion of time in which the compressions were conducted with an appropriate rhythm. The depth and rate of compressions did not improve in the filming protocol condition. CONCLUSIONS: Video-instructed CPR with the filming protocol improves CPR effectiveness compared to telephone- and video-instructed CPR. Detailed implementation can improve new technology introduction.

Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs monitors ranges from 0.72 to 0.99. We applied machine learning (ML) to ICU multi-sensor information to imitate a medical specialist in diagnosing patient condition. We hypothesized that applying this data-driven approach to medical monitors will help reduce the FAR even when data from sensors are missing. An expert-based rules algorithm identified and tagged in our dataset seven clinical alarm scenarios. We compared a random forest (RF) ML model trained using the tagged data, where parameters (e.g., heart rate or blood pressure) were (deliberately) removed, in detecting ICU signals with the full expert-based rules (FER), our ground truth, and partial expert-based rules (PER), missing these parameters. When all alarm scenarios were examined, RF and FER were almost identical. However, in the absence of one to three parameters, RF maintained its values of the Youden index (0.94-0.97) and positive predictive value (PPV) (0.98-0.99), whereas PER lost its value (0.54-0.8 and 0.76-0.88, respectively). While the FAR for PER with missing parameters was 0.17-0.39, it was only 0.01-0.02 for RF. When scenarios were examined separately, RF showed clear superiority in almost all combinations of scenarios and numbers of missing parameters. When sensor data are missing, specialist performance worsens with the number of missing parameters, whereas the RF model attains high accuracy and low FAR due to its ability to fuse information from available sensors, compensating for missing parameters.

Paramedic equipment bags: How their position during out-of-hospital cardiopulmonary resuscitation (CPR) affect paramedic ergonomics and performance.

This study investigates how the positions of paramedic equipment bags affect paramedic performance and biomechanical loads during out-of-hospital Cardiopulmonary Resuscitation (CPR). An experiment was conducted in which 12 paramedic teams (each including two paramedics) performed in-situ simulations of a cardiac-arrest scenario. CPR quality was evaluated using five standard resuscitation measures (i.e., pre- and post-shock pauses, and compression rate, depth and fraction). The spinal loads while lifting, pulling and pushing the equipment bags were assessed using digital human modeling software (Jack) and prediction equation from previous studies. The results highlight where paramedics are currently choosing to position their equipment. They also demonstrate that the positions of the equipment bags affect CPR quality as well as the paramedics' work efficiency, physiological effort and biomechanical loads. The spinal loads ranged from 1901 to 4030N; furthermore, every occasion on which an equipment bag was lifted resulted in spinal forces higher than 3400N, thus exceeding the maximum threshold stipulated by the National Institute for Occupational Safety and Health. 72% of paramedics' postures were categorized as high or very high risk for musculoskeletal disorders by the Rapid Entire Body Assessment. Guidelines related to bag positioning and equipment handling might improve CPR quality and patient outcomes, and reduce paramedics' risk of injury.

Ergonomic design of new paramedic response bags.

A two phase project is described for redesigning and evaluating paramedic response bags, one of the key pieces of equipment used by emergency medical services. Adopting a user-centred approach, Phase I involved first educating active service paramedics about ergonomic principles, and then collaborating with them to conceptualise a new type of response bag, based on separate colour coded kits, each containing related equipment items. Phase II describes a formal evaluation study, involving simulated procedures with a patient mannequin and active service paramedics in a real ambulance. Results indicated subjective preferences for the new bags, where 62% of the paramedics believed it was easier to find equipment in the new bag and 65% preferred the new bags overall. No detrimental effects were attributed to the transition to the new bag. Also discussed are the advantages of the participatory design approach, as well as design guidelines and implications for paramedic operations.

Making Sense of the Cognitive Task of Medication Reconciliation Using a Card Sorting Task.

OBJECTIVE: To explore cognitive strategies clinicians apply while performing a medication reconciliation task, handling incomplete and conflicting information. BACKGROUND: Medication reconciliation is a method clinicians apply to find and resolve inconsistencies in patients' medications and medical conditions lists. The cognitive strategies clinicians use during reconciliation are unclear. Controlled lab experiments can explore how clinicians make sense of uncertain, missing, or conflicting information and therefore support the development of a human performance model. We hypothesize that clinicians apply varied cognitive strategies to handle this task and that profession and experience affect these strategies. METHOD: 130 clinicians participated in a tablet-based experiment conducted in a large American teaching hospital. They were asked to simulate medication reconciliation using a card sorting task (CaST) to organize medication and medical condition lists of a specific clinical case. Later on, they were presented with new information and were asked to add it to their arrangements. We quantitatively and qualitatively analyzed the ways clinicians arranged patient information. RESULTS: Four distinct cognitive strategies were identified ("Conditions first": n = 76 clinicians, "Medications first": n = 7, "Crossover": n = 17, and "Alternating": n = 10). The strategy clinicians applied was affected by their experience (p = .02) but not by their profession. At the appearance of new information, clinicians moved medication cards more frequently (75.2 movements vs. 49.6 movements, p < .001), suggesting that they match medications to medical conditions. CONCLUSION: Clinicians apply various cognitive strategies while reconciling medications and medical conditions. APPLICATION: Clinical information systems should support multiple cognitive strategies, allowing flexibility in organizing information.

Tracking the Progress of Wireless Infusion Pump Drug Library Updates- A Data-Driven Analysis of Pump Update Delays.

Modern smart infusion pumps are wirelessly connected to a network server for easy data communications. The two-way communication allows uploading of infusion data and downloading of drug library updates. We have discovered significant delays in library updates. This research aimed at studying the drug library update process of one vendor pump and the contributing factors of pump update delays. Our data included BD Alaris™ pump status and infusion reports of two hospital systems (92 and 80 days, respectively, in 2015). We analyzed drug library update progressions at the individual device and fleet levels. To complete a library update, a pump goes through two status transitions: from noncurrent to a new library pending, and from pending to current. On average it took five to nine days for 50% of a pump fleet to become current after a new drug library was disseminated. We confirmed factors that affect noncurrent-to-pending time to include time to first power-on and total power-on time. We also found that high pump utilization promotes shorter pending-to-current time. Two distinctive and important steps of a drug library update on Alaris™ pumps are pending a new library and completing the library installation. To avoid potential patient harm caused by infusion pumps without appropriate drug limits due to update delays, hospitals should monitor the progression of a drug library update on its pump fleet. Potential ways to improve drug library updates on a fleet of pumps include better technologies, improved pump user-interface design, and more staff training.

Unintended Patient Safety Risks Due to Wireless Smart Infusion Pump Library Update Delays.

OBJECTIVE: Our previous study showed that the issue of drug library update delays on wireless intravenous (IV) infusion pumps of one major vendor was widespread and significant. However, the impact of such a delay was unclear. The objective of this study was to quantify the impact of pump library update delays on patient safety in terms of missed and false infusion programming alerts. METHODS: The study data sets included infusion logs and drug libraries from three hospitals of one health system from January 2015 to December 2016. We identified limit setting changes of any two consecutive drug library versions. We quantified the impact of using outdated drug limit settings by missed and false infusion programming alerts. RESULTS: Twenty-five updates of the drug library were released within the health system during the 2-year period with an average interval of 28.8 days. After a new library version was issued, it took at least 6 days for 50% of all pumps to become up-to-date and 15 days or more to reach 80%. All three hospitals had at least 16% of all IV infusions programmed with outdated libraries. This resulted in 18%, 24.4%, and 27% of false alerts in the three hospitals, respectively. We identified two cases of missed alert infusions of high-risk medications, propofol, and potassium chloride, which could have negatively impacted patient safety. CONCLUSIONS: These findings support our assumption that potential serious harm can happen when IV infusions are administered with outdated drug limit settings due to delays in drug library updates on the pump.

Prevalence of wireless smart-pump drug library update delays.

PURPOSE: Results of a study to estimate the prevalence and severity of delays in wireless updates of smart-pump drug libraries across a large group of U.S. hospitals are reported. METHODS: A prolonged smart-pump drug library update may result in patient harm if a pump is programmed with an incorrect limit setting at the time of drug administration. A retrospective study was conducted using smart-pump alert data extracted from the Regenstrief National Center for Medical Device Informatics (REMEDI) database. The study sample consisted of 49 hospitals in 5 states across the Midwest and Kentucky operated by 12 health systems; all the facilities used a specific brand of smart pump (BD Alaris, Beckton, Dickinson and Company) capable of generating alert data and had consistently contributed alert data to the REMEDI database over a 2-year period. An update delay was defined as the interval from the time a drug library version was replaced to the time of the last infusion alert triggered by the previous version during the study period. RESULTS: Of the 12 health systems, 11 were found to have had drug library update delays during the study period, with delay medians ranging from 22 to 192 days. The overall delay minimum and maximum durations were 0 and 661 days. CONCLUSION: Substantial delays in completion of wireless updates of smart-pump drug libraries were common across a group of hospitals of various sizes.

Investigating Delays in Updates to Infusion Pump Drug Limit Libraries.

Interoperability is a major challenge in current healthcare systems. It brings big hope for data exchange, but also raises some concern about patient safety. We study the wireless updating of modern infusion pumps and demonstrate the possible flaws in this process. Through analyzing data on drug limit libraries (DLL) versions in one hospital we could identify the delays in distributing DLL updates and the impact these delays might have on patient safety. We found that 31% of all started infusions had used outdated DLL versions, and 22.6% of all alerts were triggered by outdated DLLs. These findings suggest that clinical and operational stakeholders in healthcare systems must address the unreliable interoperability of medical technologies such as seen on infusion pumps. The impact of information inconsistency across healthcare systems might result in use error which would impair patient safety.

Correlating data from different sensors to increase the positive predictive value of alarms: an empiric assessment.

OBJECTIVES: Alarm fatigue from high false alarm rate is a well described phenomenon in the intensive care unit (ICU). Progress to further reduce false alarms must employ a new strategy. Highly sensitive alarms invariably have a very high false alarm rate. Clinically useful alarms have a high Positive-Predictive Value. Our goal is to demonstrate one approach to suppressing false alarms using an algorithm that correlates information across sensors and replicates the ways that human evaluators discriminate artifact from real signal. METHODS: After obtaining IRB approval and waiver of informed consent, a set of definitions, (hypovolemia, left ventricular shock, tamponade, hemodynamically significant ventricular tachycardia, and hemodynamically significant supraventricular tachycardia), were installed in the monitors in a 10 bed cardiothoracic ICU and evaluated over an 85 day study period. The logic of the algorithms was intended to replicate the logic of practitioners, and correlated information across sensors in a way similar to that used by practitioners. The performance of the alarms was evaluated via a daily interview with the ICU attending and review of the tracings recorded over the previous 24 hours in the monitor. True alarms and false alarms were identified by an expert clinician, and the performance of the algorithms evaluated using the standard definitions of sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS: Between 1 and 221 instances of defined events occurred over the duration of the study, and the positive predictive value of the definitions varied between 4.1% and 84%. CONCLUSIONS: Correlation of information across alarms can suppress artifact, increase the positive predictive value of alarms, and can employ more sophisticated definitions of alarm events than present single-sensor based systems.