Laurel Despins

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.

Enhanced registered nurse care coordination with sensor technology: Impact on length of stay and cost in aging in place housing

BACKGROUND When planning the Aging in Place Initiative at TigerPlace, it was envisioned that advances in technology research had the potential to enable early intervention in health changes that could assist in proactive management of health for older adults and potentially reduce costs. PURPOSE The purpose of this study was to compare length of stay (LOS) of residents living with environmentally embedded sensor systems since the development and implementation of automated health alerts at TigerPlace to LOS of those who are not living with sensor systems. Estimate potential savings of living with sensor systems. METHODS LOS for residents living with and without sensors was measured over a span of 4.8 years since the implementation of sensor-generated health alerts. The group living with sensors (n = 52) had an average LOS of 1,557 days (4.3 years); the comparison group without sensors (n = 81) was 936 days (2.6 years); p = .0006. Groups were comparable based on admission age, gender, number of chronic illnesses, SF12 physical health, SF12 mental health, Geriatric Depression Scale (GDS), activities of daily living, independent activities of daily living, and mini-mental status examination scores. Both groups, all residents living at TigerPlace since the implementation of health alerts, receive registered nurse (RN) care coordination as the standard of care. DISCUSSION Results indicate that residents living with sensors were able to reside at TigerPlace 1.7 years longer than residents living without sensors, suggesting that proactive use of health alerts facilitates successful aging in place. Health alerts, generated by automated algorithms interpreting environmentally embedded sensor data, may enable care coordinators to assess and intervene on health status changes earlier than is possible in the absence of sensor-generated alerts. Comparison of LOS without sensors TigerPlace (2.6 years) with the national median in residential senior housing (1.8 years) may be attributable to the RN care coordination model at TigerPlace. Cost estimates comparing cost of living at TigerPlace with the sensor technology vs. nursing home reveal potential saving of about

A Review of Verbal Order Policies in Acute Care Hospitals

30,000 per person. Potential cost savings to Medicaid funded nursing home (assuming the technology and care coordination were reimbursed) are estimated to be about

Organizational and Individual Attributes Influencing Patient Risk Detection

87,000 per person. CONCLUSIONS Early alerts for potential health problems appear to enhance the current RN care coordination care delivery model at TigerPlace, increasing LOS for those living with sensors to nearly twice that of those who did not. Sensor technology with care coordination has cost saving potential for consumers and Medicaid.

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

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.

Improving Computerized Charting in an Intensive Care Unit

This study examined organizational and individual variables impacting patient risk detection by Intensive Care Unit nurses and their decision to reduce the risk of failure to rescue. Thirty-four nurses were randomly assigned to two groups. A video of a manager and staff nurse patient safety discussion was used to prime one group to prioritize patient safety. Participants provided demographic information, received end-of-shift report on two fictional patients, experienced 52 alarm trials during a medication preparation scenario, and completed the Safety Attitude Questionnaire. No difference existed in risk detection; however, nurses who perceived their work environment quality to be good correctly ignored a clinically irrelevant alarm more often and were more apt to classify an alarm as irrelevant. They chose to reduce the risk of medication error rather than that of failure to rescue. This information can assist nurses to balance disregarding distractions with responding to potential patient risk signals.

Effect of Patient Acuity of Illness and Nurse Experience on EMR Works in Intensive Care Unit

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:

The purpose of this study is to look deeper into an electronic medical record (EMR) system to find inefficiencies within the overall charting process. Along with collecting observation data on nurses within the University of Missouri Hospital Intensive Care Unit, EMR activity log data was gathered from the EMR system through a real time measurement system (RTMS). By using the RTMS data, the average time for several designated charting activities were analyzed based on different levels of patient sickness and nurse experience. The results showed that there were several significant differences on EMR documentation time in an ICU. The comprehensive findings of this study will help point to areas where improvements can be made in order to optimize efficiency within the EMR charting process and increase time nurses spend in direct patient care, which should in turn increase patient safety as well.

Detection of patient risk by nurses: a theoretical framework.

The objective of this study is to analyze the impact on the nurse’s process time during the electronic medical record (EMR) charting task in an intensive care unit (ICU). The dynamic uncertainty of clinical tasks in the ICU can make it difficult for nurses to take care of critically ill patients. According to the literature, EMR documentation is one of the tasks on which nurses spend most of their time during the shift. To understand and improve the EMR documenting process, a time & motion study was conducted in a medical ICU at the University of Missouri Hospital. Data was collected on processes and standard times of every EMR activity performed by ICU nurses. Based on the results of this study, hierarchical task analysis (HTA) charts were developed and analyzed nurse’s workflow during EMR documentation. After that, a simulation model was developed for documenting in the EMR in an ICU.

Acute pancreatitis: diagnosis and treatment of a potentially fatal condition.

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.