Nursing Professional Development in Ambulatory Care: A Phenomenological Study

Nursing professional development (NPD) practitioners play an important role in ensuring the quality and safety of nursing care and in guiding nurses through practice transitions. Recently, increasing numbers of NPD practitioners have been employed in ambulatory care settings, yet little is known about how the ambulatory practice setting affects or is affected by NPD practice. The aim of this descriptive phenomenology was to describe how the NPD role is experienced in the ambulatory care setting.

A semi-supervised approach to unobtrusively predict abnormality in breathing patterns using hydraulic bed sensor data in older adults aging in place

Shortness of breath is often considered a repercussion of aging in older adults, as respiratory illnesses like COPD1 or respiratory illnesses due to heart-related issues are often misdiagnosed, under-diagnosed or ignored at early stages. Continuous health monitoring using ambient sensors has the potential to ameliorate this problem for older adults at aging-in-place facilities. In this paper, we leverage continuous respiratory health data collected by using ambient hydraulic bed sensors installed in the apartments of older adults in aging-in-place Americare facilities to find data-adaptive indicators related to shortness of breath. We used unlabeled data collected unobtrusively over the span of three years from a COPD-diagnosed individual and used data mining to label the data. These labeled data are then used to train a predictive model to make future predictions in older adults related to shortness of breath abnormality. To pick the continuous changes in respiratory health we make predictions for shorter time windows (60-s). Hence, to summarize each day's predictions we propose an abnormal breathing index (ABI) in this paper. To showcase the trajectory of the shortness of breath abnormality over time (in terms of days), we also propose trend analysis on the ABI quarterly and incrementally. We have evaluated six individual cases retrospectively to highlight the potential and use cases of our approach.

Cardiovascular sex-differences: insights via physiology-based modeling and potential for noninvasive sensing via ballistocardiography

In this study, anatomical and functional differences between men and women in their cardiovascular systems and how these differences manifest in blood circulation are theoretically and experimentally investigated. A validated mathematical model of the cardiovascular system is used as a virtual laboratory to simulate and compare multiple scenarios where parameters associated with sex differences are varied. Cardiovascular model parameters related with women's faster heart rate, stronger ventricular contractility, and smaller blood vessels are used as inputs to quantify the impact (i) on the distribution of blood volume through the cardiovascular system, (ii) on the cardiovascular indexes describing the coupling between ventricles and arteries, and (iii) on the ballistocardiogram (BCG) signal. The model-predicted outputs are found to be consistent with published clinical data. Model simulations suggest that the balance between the contractile function of the left ventricle and the load opposed by the arterial circulation attains similar levels in females and males, but is achieved through different combinations of factors. Additionally, we examine the potential of using the BCG waveform, which is directly related to cardiovascular volumes, as a noninvasive method for monitoring cardiovascular function. Our findings provide valuable insights into the underlying mechanisms of cardiovascular sex differences and may help facilitate the development of effective noninvasive cardiovascular monitoring methods for early diagnosis and prevention of cardiovascular disease in both women and men.

Mechanism-Driven Modeling to Aid Non-invasive Monitoring of Cardiac Function via Ballistocardiography

Left ventricular (LV) catheterization provides LV pressure-volume (P-V) loops and it represents the gold standard for cardiac function monitoring. This technique, however, is invasive and this limits its applicability in clinical and in-home settings. Ballistocardiography (BCG) is a good candidate for non-invasive cardiac monitoring, as it is based on capturing non-invasively the body motion that results from the blood flowing through the cardiovascular system. This work aims at building a mechanistic connection between changes in the BCG signal, changes in the P-V loops and changes in cardiac function. A mechanism-driven model based on cardiovascular physiology has been used as a virtual laboratory to predict how changes in cardiac function will manifest in the BCG waveform. Specifically, model simulations indicate that a decline in LV contractility results in an increase of the relative timing between the ECG and BCG signal and a decrease in BCG amplitude. The predicted changes have subsequently been observed in measurements on three swine serving as pre-clinical models for pre- and post-myocardial infarction conditions. The reproducibility of BCG measurements has been assessed on repeated, consecutive sessions of data acquisitions on three additional swine. Overall, this study provides experimental evidence supporting the utilization of mechanism-driven mathematical modeling as a guide to interpret changes in the BCG signal on the basis of cardiovascular physiology, thereby advancing the BCG technique as an effective method for non-invasive monitoring of cardiac function.

Combining Physiology-Based Modeling and Evolutionary Algorithms for Personalized, Noninvasive Cardiovascular Assessment Based on Electrocardiography and Ballistocardiography

Purpose: This study proposes a novel approach to obtain personalized estimates of cardiovascular parameters by combining (i) electrocardiography and ballistocardiography for noninvasive cardiovascular monitoring, (ii) a physiology-based mathematical model for predicting personalized cardiovascular variables, and (iii) an evolutionary algorithm (EA) for searching optimal model parameters.

Methods: Electrocardiogram (ECG), ballistocardiogram (BCG), and a total of six blood pressure measurements are recorded on three healthy subjects. The R peaks in the ECG are used to segment the BCG signal into single BCG curves for each heart beat. The time distance between R peaks is used as an input for a validated physiology-based mathematical model that predicts distributions of pressures and volumes in the cardiovascular system, along with the associated BCG curve. An EA is designed to search the generation of parameter values of the cardiovascular model that optimizes the match between model-predicted and experimentally-measured BCG curves. The physiological relevance of the optimal EA solution is evaluated a posteriori by comparing the model-predicted blood pressure with a cuff placed on the arm of the subjects to measure the blood pressure.

Results: The proposed approach successfully captures amplitudes and timings of the most prominent peak and valley in the BCG curve, also known as the J peak and K valley. The values of cardiovascular parameters pertaining to ventricular function can be estimated by the EA in a consistent manner when the search is performed over five different BCG curves corresponding to five different heart-beats of the same subject. Notably, the blood pressure predicted by the physiology-based model with the personalized parameter values provided by the EA search exhibits a very good agreement with the cuff-based blood pressure measurement.

Conclusion: The combination of EA with physiology-based modeling proved capable of providing personalized estimates of cardiovascular parameters and physiological variables of great interest, such as blood pressure. This novel approach opens the possibility for developing quantitative devices for noninvasive cardiovascular monitoring based on BCG sensing.

Noninvasive cardiovascular monitoring based on electrocardiography and ballistocardiography: a feasibility study on patients in the surgical intensive care unit

The time interval between the peaks in the electroccardiogram (ECG) and ballistocardiogram (BCG) waveforms, TEB, has been associated with the pre-ejection period (PEP), which is an important marker of ventricular contractility. However, the applicability of BCG-related markers in clinical practice is limited by the difficulty to obtain a replicable and consistent signal on patients. In this study, we test the feasibility of BCG measurements within a complex clinical setting, by means of an accelerometer under the head pillow of patients admitted to the Surgical Intensive Care Unit (SICU). The proposed technique proved capable of capturing TEB based on the R peaks in the ECG and the BCG in its head-to-toe and dorso- ventral directions. TEB detection was found to be consistent and repeatable both in healthy individuals and SICU patients over multiple data acquisition sessions. This work provides a promising starting point to investigate how TEB changes may relate to the patients' complex health conditions and give additional clinical insight into their care needs.

Primary Care Clinic Nurse Activities with a Telehealth Monitoring System

The purpose of this study was to evaluate differences in the types of nursing activities and communication processes reported in a primary care clinic between patients who used a home-based monitoring system to electronically communicate self-monitored blood glucose and blood pressure values and those who assumed usual care. Data were extracted from electronic medical records from individuals who participated in a randomized controlled trial comparing in-home monitoring and usual care in patients with Type 2 diabetes and hypertension being treated in a primary care clinic. Data about nursing activities initiated by primary care clinic nurses were compared between groups using descriptive statistics and independent t-tests. Significant differences between groups were identified for the direct care nursing activities of providing lifestyle and health education, medication adjustments, and patient follow-up. This study provides evidence of greater nursing activity reported in a primary care clinic in patients who utilized a home-based monitoring system.

Perception of clinical deterioration cues among medical-surgical nurses

AIM

To examine medical-surgical nurses' capacity and tendency to perceive cues indicating clinical deterioration and nursing characteristics influencing deterioration cue perception.

DESIGN

Cross-sectional, explorative study design.

METHODS

Data were collected over 10 weeks between September-November 2017. Medical-surgical nurses completed an online survey consisting of a demographic questionnaire, the Occupational Fatigue, Exhaustion Recovery scale and 50 detection trials. Descriptive statistics and statistical tests were used to describe and interpret data.

FINDINGS

A significant association was found between nurses' capacity and tendency to perceive deterioration cues. As nurses' capacity to perceive deterioration cues increased, nurses were more likely to classify patient cues as indicators of deterioration. Fatigue, education, and certification were not identified as characteristics associated with deterioration cue perception. However, experience was observed to significantly influence nurses' capacity to perceive deterioration cues based on levels of skills acquisition.

CONCLUSION

Study findings imply that future research should be directed at determining whether other individual factors and organizational system dynamics influence deterioration cue perception.

IMPACT

To better understand how nurses perceive deterioration cues, this study integrated concepts from the Situation Awareness model and Signal Detection Theory. Novice, advanced beginner and competent nurses were found to have a lower capacity to perceive deterioration cues compared with proficient and expert nurses. With simulation increasingly being used as a primary teaching modality in nursing, the development of a simulation-based signal detection training intervention may be beneficial in enhancing deterioration cue perception.

Cardiovascular Function and Ballistocardiogram: A Relationship Interpreted via Mathematical Modeling

OBJECTIVE

To develop quantitative methods for the clinical interpretation of the ballistocardiogram (BCG).

METHODS

A closed-loop mathematical model of the cardiovascular system is proposed to theoretically simulate the mechanisms generating the BCG signal, which is then compared with the signal acquired via accelerometry on a suspended bed.

RESULTS

Simulated arterial pressure waveforms and ventricular functions are in good qualitative and quantitative agreement with those reported in the clinical literature. Simulated BCG signals exhibit the typical I, J, K, L, M, and N peaks and show good qualitative and quantitative agreement with experimental measurements. Simulated BCG signals associated with reduced contractility and increased stiffness of the left ventricle exhibit different changes that are characteristic of the specific pathological condition.

CONCLUSION

The proposed closed-loop model captures the predominant features of BCG signals and can predict pathological changes on the basis of fundamental mechanisms in cardiovascular physiology.

SIGNIFICANCE

This paper provides a quantitative framework for the clinical interpretation of BCG signals and the optimization of BCG sensing devices. The present paper considers an average human body and can potentially be extended to include variability among individuals.

Monitoring the Relative Blood Pressure Using a Hydraulic Bed Sensor System

We propose a nonwearable hydraulic bed sensor system that is placed underneath the mattress to estimate the relative systolic blood pressure of a subject, which only differs from the actual blood pressure by a scaling and an offset factor. Two types of features are proposed to obtain the relative blood pressure, one based on the strength and the other on the morphology of the bed sensor ballistocardiogram pulses. The relative blood pressure is related to the actual by a scale and an offset factor that can be obtained through calibration. The proposed system is able to extract the relative blood pressure more accurately with a less sophisticated sensor system compared to those from the literature. We tested the system using a dataset collected from 48 subjects right after active exercises. Comparison with the ground truth obtained from the blood pressure cuff validates the promising performance of the proposed system, where the mean correlation between the estimate and the ground truth is near to 90% for the strength feature and 83% for the morphology feature.

Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing

OBJECTIVES

Measure the clinical effectiveness and cost effectiveness of using sensor data from an environmentally embedded sensor system for early illness recognition. This sensor system has demonstrated in pilot studies to detect changes in function and in chronic diseases or acute illnesses on average 10 days to 2 weeks before usual assessment methods or self-reports of illness.

DESIGN

Prospective intervention study in 13 assisted living (AL) communities of 171 residents randomly assigned to intervention (n=86) or comparison group (n=85) receiving usual care.

METHODS

Intervention participants lived with the sensor system an average of one year.

MEASUREMENTS

Continuous data collected 24 hours/7 days a week from motion sensors to measure overall activity, an under mattress bed sensor to capture respiration, pulse, and restlessness as people sleep, and a gait sensor that continuously measures gait speed, stride length and time, and automatically assess for increasing fall risk as the person walks around the apartment. Continuously running computer algorithms are applied to the sensor data and send health alerts to staff when there are changes in sensor data patterns.

RESULTS

The randomized comparison group functionally declined more rapidly than the intervention group. Walking speed and several measures from GaitRite, velocity, step length left and right, stride length left and right, and the fall risk measure of functional ambulation profile (FAP) all had clinically significant changes. The walking speed increase (worse) and velocity decline (worse) of 0.073 m/s for comparison group exceeded 0.05 m/s, a value considered to be a minimum clinically important difference. No differences were measured in health care costs.

CONCLUSIONS

These findings demonstrate that sensor data with health alerts and fall alerts sent to AL nursing staff can be an effective strategy to detect and intervene in early signs of illness or functional decline.

Evaluating Situation Awareness: An Integrative Review

Situation awareness (SA) refers to the conscious awareness of the current situation in relation to one’s environment. In nursing, loss or failure to achieve high levels of SA is linked with adverse patient outcomes. The purpose of this integrative review is to examine various instruments and techniques used to measure SA among nurses across academic and clinical settings. Computerized database and ancestry search strategies resulted in 40 empirical research reports. Of the reports included in the review, 24 measured SA among teams that included nurses and 16 measured SA solely in nurses. Methods used to evaluate SA included direct and indirect methods. Direct methods included the Situation Awareness Global Assessment Technique and questionnaires. Indirect methods included observer rating instruments and performance outcome measures. To have a better understanding of how nurses’ make decisions in complex work environments, reliable and valid measures of SA is crucial.

Using Embedded Sensors in Independent Living to Predict Gait Changes and Falls

This study explored using Big Data, totaling 66 terabytes over 10 years, captured from sensor systems installed in independent living apartments to predict falls from pre-fall changes in residents' Kinect-recorded gait parameters. Over a period of 3 to 48 months, we analyzed gait parameters continuously collected for residents who actually fell ( n = 13) and those who did not fall ( n = 10). We analyzed associations between participants' fall events ( n = 69) and pre-fall changes in in-home gait speed and stride length ( n = 2,070). Preliminary results indicate that a cumulative change in speed over time is associated with the probability of a fall ( p < .0001). The odds of a resident falling within 3 weeks after a cumulative change of 2.54 cm/s is 4.22 times the odds of a resident falling within 3 weeks after no change in in-home gait speed. Results demonstrate using sensors to measure in-home gait parameters associated with the occurrence of future falls.

A review of verbal order policies in acute care hospitals

BACKGROUND

Although verbal and telephone orders (VOs) are commonly used in the patient care process, there has been little examination of the strategies and tactics used to ensure their appropriate use or how to ensure that they are accurately communicated, correctly understood, initially documented, and subsequently transcribed into the medical record and ultimately carried out as intended. A systematic review was conducted of hospital verbal and telephone order policies in acute care settings.

METHODS

A stratified random sample of hospital verbal and telephone order policy documents were abstracted from critical access, rural, rural referral, and urban hospitals located in Iowa and Missouri and from academic medical centers from across the United States.

FINDINGS

Substantial differences were found across 40 acute care settings in terms of who is authorized to give (including nonlicensed personnel) and take VOs and in terms of time allowed for the prescriber to cosign the VO. When a nonphysician or other licensed prescriber was allowed to communicate VOs, there was no discussion of the process to review the VO before it was communicated in turn to the hospital personnel receiving the order. Policies within several of the same hospitals were inconsistent in terms of the periods specified for prescriber cosignature. Few hospitals required authentication of the identity of the person making telephone VOs, nor the use of practices to improve communication reliability.

CONCLUSION

Careful review and updating of hospital VO policies is necessary to ensure that they are internally consistent and optimize patient safety. The implementation of computerized medical records and ordering systems can reduce but not eliminate the need for VOs.