A computerized laboratory alerting system

A computerized laboratory alerting system (CLAS) has been developed as part of an ongoing effort to improve the quality of care at LDS Hospital. The system identifies potentially life-threatening conditions on the basis of laboratory findings and then generates appropriate warnings and transmits them to clinicians. Use of the system has led to a significant increase in the proportion of patients in life-threatening situations who have received appropriate care (50.8% before implementation vs. 62.5% afterward, P less than 0.05). Among patients with hypokalemia, falling potassium levels, hyperkalemia, hypokalemia during treatment with digoxin, hyponatremia, falling sodium levels, hypernatremia, hypoglycemia, or hyperglycemia, the average length of time spent in the life-threatening situation has decreased from 30.4 to 15.7 hours (P less than 0.05) and the average length of stay has decreased from 14.6 to 8.8 days (P less than 0.05). There has been little change in the proportion of patients with findings indicating metabolic acidosis who have received appropriate care (32.3 vs. 34.6%). We conclude that CLAS has an important role in patient care at our hospital.     

Exploring performance obstacles of intensive care nurses

High nursing workload, poor patient safety, and poor nursing quality of working life (QWL) are major issues in intensive care units (ICUs). Characteristics of the ICU and performance obstacles may contribute to these issues. The goal of this study was to comprehensively identify the performance obstacles perceived by ICU nurses. We used a qualitative research design and conducted semi-structured interviews with 15 ICU nurses of a medical-surgical ICU. Based on this qualitative study and a previously reported quantitative study, we identified seven main types of performance obstacles experienced by ICU nurses. Obstacles related to the physical environment (e.g., noise, amount of space), family relations (e.g., distractions caused by family, lack of time to spend with family), and equipment (e.g., unavailability, misplacement) were the most frequently experienced performance obstacles. The qualitative interview data provided rich information regarding the factors contributing to the performance obstacles. Overall, ICU nurses experience a variety of performance obstacles in their work on a daily basis. Future research is needed to understand the impact of performance obstacles on nursing workload, nursing QWL, and quality and safety of care.     

A preliminary study on the use of clinical care classification in nursing documentation data sets

This study analyzed and organized the content coverage of the clinical care classification (CCC) system to represent nursing record data in a medical center in Taiwan. The nursing care plan was analyzed using the process of knowledge discovery in the data set. The nursing documentation was mapped based on the full list of nursing diagnoses and interventions available using the CCC system. The result showed that 75.45% of the documented diagnosis terms can be mapped using the CCC system. A total of 21 established nursing diagnoses were recommended for inclusion in the CCC system. The results also showed that 30.72% of assessment/monitor tasks and 31.16% of care/perform tasks were provided by nursing professionals, whereas manage/refer actions accounted for 15.36% of the tasks involved in nursing care. The results showed that the CCC system is a suitable clinical information system for the majority of nursing care documentation, and is useful for determining the patterns in nursing practices.     

The influence of a preventive educational programme on trunk flexion in janitors

The influence of a preventive educational back care programme on the movement patterns of the spine during work was assessed objectively and subjectively in six janitors. Trunk flexion was measured in the subjects using a flexion analyser before they attended a preventive educational back care programme and twice afterwards. The results show that the subjects increased the amount of time spent in an upright position by about a third after the educational programme and maintained this change two and a half to three months later. They also decreased the time spent in moderate and deep forward flexion (37-72 degrees ) by about half and also maintained this decrease at three months. These changes are consistent with a decrease of the mechanical load on the spine. The study emphasises that it is possible to alter movement patterns of the spine, and thereby decrease the load during janitorial work, by a suitably designed educational programme.     

MobileNurse: hand-held information system for point of nursing care

Healthcare information travels with patients and clinicians and therefore the need for information to be ubiquitously available is key to reliable patient care and reliable medical systems. We have implemented MobileNurse, a prototype point-of-care system using PDA. MobileNurse has four modules each of which performs: (1) patient information management; (2) medical order check; (3) nursing recording; and (4) nursing care plan. MobileNurse provides easy input interface and various outputs for nursing records. The system consists of PDAs and a mobile support system (MSS) which supports clinical data exchange between PDAs and hospital information system. Two synchronization modules have been developed to keep the patient data consistent between PDAs and MSS. Clinical trials were performed with six volunteered nurses. They tried MobileNurse for 1-day caring-simulated patients. According to the survey after the trials, most of volunteers agreed that MobileNurse is more helpful and convenient than other non-mobile care systems to check medical orders and retrieve the results of recent clinical tests at the bedside. Through the involvement, we found out that ease-to-use interface is the most critical successful factor for mobile patient care systems.     

Database Based Reasoning for Real Time Monitoring and Data Analysis in Intensive Care Units

The complexity of the monitored data available in modern intensive care units (ICUs) means that they are best processed, for presentation to medical staff, by expert system techniques. This article describes an expert system that has an appropriately designed inference engine, handling the temporal considerations inherent in monitoring and manages data acquisition via a Medical Information Bus. Also, we will describe how we extended our monitoring system in ICUs by writing an interface allowing communication in dynamic SQL with a relational database management system. The extended system facilitates both permanent filing of case data and the use of filed data by the rules of the expert system, and allows automatic intelligent screening of data prior to permanent filing so as to ensure data reliability.     

Nurse staffing: Accurate information at the correct place and time

Nurse Staffing at this 300 bed acute care hospital is based on the results of calculations of patient care needs performed two hours before the beginning of each shift. This allows the central nurse staffing office to balance staffing levels with patient care needs. Forms and procedures are designed so that the quantification of patient care needs is a result of completing a redesigned patient care plan. The patient care needs are translated into a number (acuity points) and recorded onto a preprinted census sheet. This sheet is sent to a central nurse staffing office during the middle of each shift. The nurse staffing office enters the acuity points by patient room number into a microcomputer. The data is then processed into a report that compares the hours of care needed by nursing unit with the actual hours available. This report is available two hours before the next shift begins, allowing the nurse staffing department to adjust staff assignments based on patient care needs. The nurse staffing clerk also updates the data after changes have been made in staff assignments. This provides accurate historical data which is summarized for productivity and budget calculations. The unique combination of the hospitals main computer, redesigned patient care plan, pneumatic tube, and microcomputer have solved a major nurse staffing problem by providing information in an accurate and timely fashion. The program has been in existence since August, 1984. In a time of lower hospital utilization this system has allowed the hospital to control its nursing resource and avoid layoffs. The microcomputer programs where written by the author using the programming language BASIC.     

Balancing documentation and direct patient care activities: A study of a mature electronic health record system

US hospitals now fully embrace electronic documentation systems as a way to reduce medical errors and improve patient safety outcomes. Whether spending time on electronic documentation detracts from the time available for direct patient care, however, is still unresolved. There is no knowledge on the permanent effects of documenting electronically and whether it takes away significant time from patient care when the healthcare information system is mature. To understand the time spent on documentation, direct patient care tasks, and other clinical tasks in a mature information system, we conducted an observational and interview study in a midwestern academic hospital. The hospital implemented an electronic medical record system 11 years ago. We observed 22 health care workers across intensive care units, inpatient floors, and an outpatient clinic in the hospital. Results show that healthcare workers spend more time on documentation activities compared to patient care activities. Clinical roles have no influence on the time spent on documentation. This paper describes results on the time spent between documentation and patient care tasks, and discusses implications for future practice.Relevance to industryThe study applies to healthcare industry that faces immense challenges in balancing documentation activities and patient care activities.     

Case studies of IT sophistication in nursing homes: A mixed method approach to examine communication strategies about pressure ulcer prevention practices

Most nursing homes lack information technology (IT) for supporting clinical work in spite of its potential to improve the safety, quality, and efficiency of nursing home care in the United States. Increased attention to medical error and concern for patient safety have prompted general recommendations to develop sophisticated technologies to support clinical decision making at the point of care, to promote data standards in electronic records, and to develop systems that communicate with each other. However, little is known about what IT applications best support communication and risk assessment practices to improve resident outcomes in nursing homes. Thus, the overall aim of this study was to evaluate how differences in IT sophistication in nursing homes impact communication and use of technology related to skin care and pressure ulcers. We used a mixed method approach to conduct case studies on two nursing homes – one with high IT sophistication and one with low IT sophistication. Observational analysis and social network analysis were used to identify patterns in communication types and locations; also, focus groups were conducted to explore communication strategies used by Certified Nursing Assistants (CNAs) to support pressure ulcer prevention practices. Overall, results from social network analysis of observational data indicate that direct interactions between CNAs and registered nurses (RNs) or licensed practical nurses (LPNs) were more frequent in the low IT sophistication home and occurred in more centralized locations (e.g. the nursing station) compared to the high IT sophistication home. Moreover, these findings are supported by focus group results, which indicate that the high IT sophistication home had more robust and integrated communication strategies (both IT and non IT) that may allow for interactions throughout the facility and require less frequent face to face interactions between CNAs and RNs or LPNs to verify orders or report patient status. Results from this study provide insight into the design and assessment of different forms of communication to support clinical work in NHs.Relevance to industryNurses bear great burdens for nursing home care; yet, issues persist with poor quality, variable performance of caregiving, and lack of implementation of proven care interventions. One new hope for improvement in nursing home care is the introduction of IT to improve communication, clinical decision-making, and quality of care.     

Improved blood glucose control for critically ill subjects

For patients in intensive care units (ICUs), control of blood glucose level is an important factor in reducing serious complications and mortality. Standard protocols for glucose control in ICUs have been based on infrequent glucose measurements, look-up tables to determine the appropriate insulin infusion rates, and bedside administration of the insulin infusion by ICU staff. In this paper a new automatic control strategy is proposed based on frequent glucose measurements and a self-tuning control technique. During a short initial time period when manual glucose control is performed using a standard protocol, a simple dynamic model of the glucose-insulin system is identified in real time using recursive least squares. Then an adaptive PID controller is tuned, based on the model parameters, and the controller is turned on. A simulation study based on detailed physiological models of the glucose-insulin dynamics demonstrates that the proposed control strategy performs better than standard protocols for insulin infusion.     

An ergonomic evaluation of nursing assistants' job in a nursing home.

Thirty-eight nursing assistants (NAs) in a nursing home ranked and rated 16 different patient handling tasks for perceived stresses to the low back. The nursing assistants were observed for 79 4 h shifts and were videotaped for 14 4 h shifts to describe a typical workday and to determine the number of patient-handling tasks performed per shift, the use of assistive devices, and biomechanical stresses to the low back. In addition, data were collected on nursing assistants' and patients' characteristics. The top eight ranked tasks included transferring patient from toilet to wheelchair (WC), WC to toilet, WC to bed, bed to WC, bathtub to WC, chairlift to WC, weighing patients and lifting patients up in bed. The mean ratings of perceived exertion for these tasks were between 'somewhat hard' and 'hard'. The estimated compressive force on L5/S1 disc for the 50th percentile patient weight ranged from 3.7 to 4.9 KN. Nursing assistants worked in teams of two and performed 24 patient transfers per 8 h shift by manually lifting and carrying patients. Assistive devices (a hydraulic lift and gait belt) were used less than 2% of the time. Patient safety and comfort, lack of accessibility, physical stresses associated with the devices, lack of skill, increased transfer time, and lack of staffing were some of the reasons for not using these assistive devices. Environmental barriers (such as confined workplaces, an uneven floor surface, lack of adjustability of beds, stationary railings around the toilet, etc.) made the job more difficult. Nursing assistants had a high prevalence of low-back pain and 51% of nursing assistants visited a health care provider in the last three years for work related low-back pain.     

Information systems variables and management productivity

The companies in the Premier 100 list published by ComputerWorld (CW) in 1994 were classified into groups based on the information productivity index (IPI) computed by Paul Strassmann. Discriminant analysis was used to identify the significant discriminating information systems factors between the two groups. They are: ‘number of years the Chief Information Officer (CIO) has been in the company in that position,’ ‘proportion of software resources spent on client server applications,’ and ‘percentage of software budget spent on new development.’ On average the CIOs in the high productivity group have been with the company for three years, as compared to eight years in the low productivity group. The companies in the high group spent 54% of the software development budget on client server applications, as compared to 35% for the low productivity group. Companies in the high productivity group spent 46% of software budget on in-house development of new applications, as opposed to 60% for the low productivity group.     

Describing nurses' work: combining quantitative and qualitative analysis

OBJECTIVE: To better understand nursing activities and working conditions. BACKGROUND: Nursing practice involves astute clinical decision making and the competent delivery of nursing care procedures. To complete nursing procedures, nurses must simultaneously organize and reorganize priorities and manage changing clinical information for multiple patients. Few researchers have examined the specific nature of nurses' activities and the effect of the environment on their work. METHODS: Quantitative and qualitative methods were used to collect data on 7 nurses engaged in nursing activities. Examples of methods include link analysis, subject matter expert, task analysis, cognitive pathway, and "stacking." Data collection focused on how nurses managed priorities, changing clinical information, and interruptions. RESULTS: The "cognitive pathway" graphically depicts the nature of nurses' work. Specifically, it reveals the shifting of the nurse's attention from patient to patient and the occurrence of interruptions. "Stacking" shows the number of tasks a nurse must balance at any one time. On average, nurses had 10 or more activities waiting to be performed and experienced 3.4 interruptions/hr. CONCLUSION: These methods provide unique insight into the dynamic nature of patient care and nursing work. APPLICATION: Extension of the methods demonstrated here may be useful in guiding efforts to change the work of nursing to better provide quality care and less stressful work environments.     

Assessment of workload and arm position during different work sequences: a study with portable devices on construction workers

It is recognised that work related shoulder pain is overrepresented among construction workers compared to other occupations. Studies have shown that working with hands above shoulder level increases the shoulder load. Most studies have been confined to the laboratory. The present project was carried out to map the muscular engagement and postures of construction workers undertaking ceiling fitting, and to compare the results to those of the laboratory studies. Two ambulatory devices were used, one allowing recording of electromyographic (EMG) signals bilaterally from the trapezius muscle, and the other to record the position of both arms and back by means of measuring the angles between the vertical line and the back and both upper arms. These recordings were performed during 1.5–2 h work sequences. The results show that the work was mostly performed in an upright position, that both arms were used to a similar amount and that the workers for a large proportion of their working time had their upper arms at levels that are considered harmful in view of shoulder load. The EMG data showed that nearly 50% of the work was spent with trapezius activity that exceeded that of the reference contraction used (about 15% of maximal voluntary contraction) and that the time spent in muscular relaxation was 10%. It was concluded that the exposure of construction workers undertaking ceiling fitting meets the criteria formulated on the basis of laboratory experiments with respect to a high risk of acquiring chronic shoulder pain, due to rotator cuff tendinitis.     

Application and roll-out of infinite horizon MPC employing a nonlinear mechanistic model to paper machines

A mechanistic nonlinear model of the wet end of paper machine 6 (PM6) at Norske Skog Saugbrugs, Norway has been developed, and used in an industrial MPC implementation. The MPC uses an infinite horizon criterion, successive linearization of the model, and estimation of states and parameters by an augmented Kalman filter. Variation in important quality variables and consistencies in the wet end have been reduced substantially, compared to the variation prior to the MPC implementation. The MPC also provides better efficiency through faster grade changes, control during sheet breaks and start ups, and better control during periods of poor measurements. From May 2002 of the MPC has been the preferred controller choice for the process operators at PM6.In this paper we also study if the model can be applied to PM4 at Norske Skog Saugbrugs, and PM3 at Norske Skog Skogn, Norway. No structural changes were necessary in order to fit the model to PM4 and PM3 data. The time spent on fitting the PM6 model to PM4 and PM3 is approximately 1% of the time spent on developing the original model. This should be a strong incentive for focusing on mechanistic modeling in industries were there are many similar production lines or units.     

Managing Clinical Use of High-Alert Drugs: A Supervised Learning Approach to Pharmacokinetic Data Analysis

Drug-related problems, particularly those that result from sub- or overtherapeutic doses of high-alert medications, have become a growing concern in clinical medicine. In this paper, we use a model-tree-based regression technique (namely, M5) and support vector machine (SVM) for regression to develop learning-based systems for predicting the adequacy of a vancomycin regimen. We empirically evaluate each system's accuracy in predicting patients' peak and trough concentrations in different clinical scenarios characterized by renal functions and regimen types. Our data consist of 1099 clinical cases that were collected from a major tertiary medical center in southern Taiwan. We also examine the use of bagging for enhancing the prediction power of the respective systems and include in our evaluation a salient one-compartment model for performance benchmark purposes. Overall, our evaluation results suggest that both M5 and SVM are significantly more accurate than the benchmark one-compartment model in predicting patients' peak and trough concentrations across all investigated clinical scenarios. M5 appears to benefit considerably from bagging, which has a positive but seemingly smaller effect on SVM. Taken together, our findings indicate supervised learning techniques that are capable of effectively supporting clinicians' use of vancomycin or similar high-alert drugs in their patient care and management.     

Identifying the timing and duration of collecting patient priorities in an orthopedic clinic

The patient‐centered care model supports patients actively engaging in their care. Typically this involves collecting patient‐reported outcomes and priorities that may not be part of the routine practice. There is a research gap related to whether there is time available within the routine orthopedic medical practice to collect patient‐centered data for immediate use without delaying the overall clinical processes or influencing patient clinical experiences. A time study was conducted to quantify the current patient processes at an orthopedic clinic, and a statistical simulation model was used to evaluate potential changes in patients’ clinical process if a patient‐centered survey were to be implemented. The proportion of simulated patients who would experience delays due to the survey, the durations of their delays, and the average duration of the patient process delay were recorded at each step in the clinical process. The results are presented in terms of the relationship between the time devoted to collecting data and the impact on the patient experience for various survey durations at various process points. This study demonstrates an approach to evaluate how introducing a patient priorities survey (for collecting both patient‐reported outcomes and priorities), which could be used in the same patient visit, might impact the clinical process and introduce process delays.     

Improvement of newborn screening using a fuzzy inference system

This paper presents a decision support system (DSS) called DSScreening to rapidly detect inborn errors of metabolism (IEMs) in newborn screening (NS). The system has been created using the Aide-DS framework, which uses techniques imported from model-driven software engineering (MDSE) and soft computing, and it is available through eGuider, a web portal for the enactment of computerised clinical practice guidelines and protocols.MDSE provides the context and techniques to build new software artefacts based on models which conform to a specific metamodel. It also offers separation of concern, to disassociate medical from technological knowledge, thus allowing changes in one domain without affecting the other. The changes might include, for instance, the addition of new disorders to the DSS or new measures to the computation related to a disorder. Artificial intelligence and soft computing provide fuzzy logic to manage uncertainty and ambiguous situations. Fuzzy logic is embedded in an inference system to build a fuzzy inference system (FIS); specifically, a single-input rule modules connected zero-order Takagi-Sugeno FIS. The automatic creation of FISs is performed by the Aide-DS framework, which is capable of embedding the generated FISs in computerized clinical guidelines. It can also create a desktop application to execute the FIS. Technologically, it supports the addition of new target languages for the desktop applications and the inclusion of new ways of acquiring data.DSScreening has been tested by comparing its predictions with the results of 152 real analyses from two groups: (1) NS samples and (2) clinical samples belonging to individuals of all ages with symptoms that do not necessarily correspond to an IEM. The system has reduced the time needed by 98.7% when compared to the interpretation time spent by laboratory professionals. Besides, it has correctly classified 100% of the NS samples and obtained an accuracy of 70% for samples belonging to individuals with clinical symptoms.