Decision-Making to Support Smooth Daily Unit Operation in Perioperative Settings.

Decision-making in daily unit operation in perioperative settings needs to be smooth. Decision support systems are mainly used as help in this situation. These systems reduce the possibility of risks caused by poor communication. But the decisions and dimensions of the decisions made by nurse manager are still unsolved. The aim of our study was to describe the timeframe of the decisions made by nurse managers in the daily unit operation in perioperative settings. The results indicated that nurse managers made operational and tactical decisions. These operational and tactical decisions happened coincide during the nurse managers shift. The nurse managers were repeatly interrupted in decision-making.

Impact of an Atrial Fibrillation Decision Support Tool on thromboprophylaxis for atrial fibrillation.

BACKGROUND: Appropriate thromboprophylaxis for patients with atrial fibrillation (AF) remains a national challenge. METHODS: We hypothesized that provision of decision support in the form of an Atrial Fibrillation Decision Support Tool (AFDST) would improve thromboprophylaxis for AF patients. We conducted a cluster randomized trial involving 15 primary care practices and 1,493 adults with nonvalvular AF in an integrated health care system between April 2014 and February 2015. Physicians in the intervention group received patient-level treatment recommendations made by the AFDST. Our primary outcome was the proportion of patients with antithrombotic therapy that was discordant from AFDST recommendation. RESULTS: Treatment was discordant in 42% of 801 patients in the intervention group. Physicians reviewed reports for 240 patients. Among these patients, thromboprophylaxis was discordant in 63%, decreasing to 59% 1 year later (P = .02). In nonstratified analyses, changes in discordant care were not significantly different between the intervention group and control groups. In multivariate regression models, assignment to the intervention group resulted in a nonsignificant trend toward decreased discordance (P = .29), and being a patient of a resident physician (P = .02) and a higher HAS-BLED score predicted decreased discordance (P = .03), whereas female gender (P = .01) and a higher CHADSVASc score (P = .10) predicted increased discordance. CONCLUSIONS: Among patients whose physicians reviewed recommendations of the decision support tool discordant therapy decreased significantly over 1 year. However, in nonstratified analyses, the intervention did not result in significant improvements in discordant antithrombotic therapy.

Sharable and Comparable Data for Nursing Management.

Nurse leaders and researchers are challenged by the need for sharable and comparable data on the nursing workforce and the processes of patient care. This is significant, as nursing is the largest health care workforce, with significant operational costs. The Nursing Management Minimum Data Set provides a core set of data elements to compare nursing practice across time, diverse health care settings, and geographical areas. Nursing leaders from practice, association, academic, consulting, and industry settings were interviewed to provide perspectives on how the use of standardized data sets can be useful for the profession.

Analysis of variance of communication latencies in anesthesia: comparing means of multiple log-normal distributions.

Anesthesiologists rely on communication over periods of minutes. The analysis of latencies between when messages are sent and responses obtained is an essential component of practical and regulatory assessment of clinical and managerial decision-support systems. Latency data including times for anesthesia providers to respond to messages have moderate (> n = 20) sample sizes, large coefficients of variation (e.g., 0.60 to 2.50), and heterogeneous coefficients of variation among groups. Highly inaccurate results are obtained both by performing analysis of variance (ANOVA) in the time scale or by performing it in the log scale and then taking the exponential of the result. To overcome these difficulties, one can perform calculation of P values and confidence intervals for mean latencies based on log-normal distributions using generalized pivotal methods. In addition, fixed-effects 2-way ANOVAs can be extended to the comparison of means of log-normal distributions. Pivotal inference does not assume that the coefficients of variation of the studied log-normal distributions are the same, and can be used to assess the proportional effects of 2 factors and their interaction. Latency data can also include a human behavioral component (e.g., complete other activity first), resulting in a bimodal distribution in the log-domain (i.e., a mixture of distributions). An ANOVA can be performed on a homogeneous segment of the data, followed by a single group analysis applied to all or portions of the data using a robust method, insensitive to the probability distribution.

Reasons for declining computerized insulin protocol recommendations: application of a framework.

Clinical decision support systems (CDS) can interpret detailed treatment protocols for ICU care providers. In open-loop systems, clinicians can decline protocol recommendations. We capture their reasons for declining as part of ongoing, iterative protocol validation and refinement processes. Even though our protocol was well-accepted by clinicians overall, noncompliance patterns revealed potential protocol improvement targets, and suggested ways to reduce barriers impeding software use. We applied Rita Kukafka and colleagues' (2003) IT implementation framework to identify and categorize reasons documented by ICU nurses when declining recommendations from an insulin-titration protocol. Two methods were used to operationalize the framework: reasons for declining recommendations from actual software use, and a nurse questionnaire. Applying the framework exposed limitations of our data sources, and suggested ways to address those limitations; and facilitated our analyses and interpretations.

Current and future use of ICT for patient care and management in German acute hospitals--a comparison of the nursing and the hospital managers' perspectives.

OBJECTIVES: This study aimed at gaining comprehensive information on the current status of patient care and management applications used in German acute hospitals. Since the degree of ICT coverage in hospitals depends on the attitude of the key decision makers we also wanted to capture their plans and priorities and herewith try to predict future use. METHODS: We therefore conducted a nation-wide survey including all acute hospitals in Germany in which two questionnaires were mailed to each hospital, one to the nursing managers, the other to the hospital managers. RESULTS: Six hundred hospitals participated in the survey which corresponds to an overall response rate of 27.6%. Accounting (84%) was found to be the most prevalent management module. Rostering was implemented in every second hospital. For clinical applications laboratory systems ranked first (69%). Ordering systems were used in nearly every second hospital. Nineteen percent of the hospitals reported employing an electronic patient record, 7% a nursing documentation system. Ranked by their priorities ordering systems hold the first position and care planning the last position. According to their plans, hospital managers, not nursing managers, intend to introduce nursing documentation. In contrast, nursing managers favor ordering and rostering for the near future. CONCLUSIONS: There is still a preponderance of management-oriented systems in German hospitals, yet clinical applications, in particular those supporting communications, will gain ground. The future of documentation systems is unclear, unless they not only provide statistical data for the management but support the clinical process properly.

The G8 Heart Health Projects Database: testing the compatibility of an Internet-based resource with health promotion planning processes.

This study examined the context and processes in which health promotion policy and program decisions are made to ensure that an Internet-based information system on heart health promotion programs provides appropriate information for decision makers' needs and is compatible with their decision-making processes. Five focus groups and six individual interviews were conducted with potential users of and contributors to the G8 Heart Health Projects Database. Results suggest that Internet-based systems such as this are seen as useful tools, but will only be used at certain critical points in program development and then, only when they meet several rigorous criteria. Systems must be completely credible and up-to-date, providing instant answers to complex questions about program design, implementation, and effectiveness, with adequate qualitative information for assessing contextual applicability. Participants also provided information about the conditions required if they were to submit project information to the system.

Measuring the benefit of performance improvement and decision support.

In an effort to provide high quality care in a more cost-effective manner, health care providers have found it necessary to implement a series of decision support strategies designed to improve outcomes of care. While each of these strategies has measurable benefits, each comes along with additional costs. As more and more technology becomes available and more labor resources are devoted to these efforts, it becomes crucial to be able to assess the costs and benefits of these programs. A return-on-investment methodology is used to assess the financial impact of service-related operating expenses compared to revenue gains from service delivery. However, unlike traditional return-on-investment models, in health care, benefits are frequently gained from cost avoidance rather than from revenue enhancement activities. This article will describe a methodology for measuring the direct and indirect costs and qualitative and quantitative benefits of decision support activities.

Linking cost control measures to health care services by using activity-based information.

Canada's health care institutions are under pressure to limit expenditures, maintain or increase productivity, and assimilate new technology. Even though more than 75% of hospital operating expenditures are controllable, according to a study by the Economic Council of Canada, cost systems are needed to provided essential management information. The new Canadian Management Information System (MIS) Guidelines for health care are designed to provide accurate cost measurement of patient treatment and to help managers evaluate the impact of planned program changes on areas of operational responsibility. Other potential benefits of implementing the MIS guidelines include correcting dysfunctional funding of health care units with benchmarking and setting high reporting standards for resource use at the patient level (MIS, 1991). This paper focuses on one important aspect of bringing these costs under control by examining the relation between cost deviations (variances) and underlying cost drivers. Our discussion will lead to the conclusion that incompatibility of DRG methodology and traditional cost accounting models may be an important source of cost variability within diagnostically-related disease groupings.

The use of decision support systems in health facility allocation problems.

Employing Kitchener's Freeport Hospital as a case study, the author introduces decision support systems as possible aids for allocating public health care facilities. The study found that the Dynamic Interactive Network Analysis System (DINAS) was useful in determining Kitchener as the most suitable location for Freeport, based upon a comparison of need throughout Ontario.

Data quality in hospital strategic information systems: a summary of survey findings.

Fundamental changes in health care financing and delivery have resulted in an unprecedented need for data and information. The application of computer technology to daily hospital operations has gone far toward aiding various kinds of organizational decision making. The quality of those decisions, however, is dependent upon the quality of the data delivered by the various information systems used in the course of health care delivery and management. What remains unknown is the extent to which poor data quality occurs and what actions are taken to measure and control data quality in information systems used for strategic decision making. This article summarizes the results of a survey that was conducted for the purpose of explaining what information systems are important to hospital administrators in their strategic decision making, the frequency with which strategic decision makers encounter data quality problems, and what, if any, actions are taken to prevent, control, or correct apparent data quality problems.