Dataset Information

Implementing glucose control in intensive care: a multicenter trial using statistical process control.

ABSTRACT:

Background

Glucose control (GC) with insulin decreases morbidity and mortality of critically ill patients. In this study we investigated GC performance over time during implementation of GC strategies within three intensive care units (ICUs) and in routine clinical practice.

Methods

All adult critically ill patients who stayed for >24 h between 1999 and 2007 were included. Effects of implementing local GC guidelines and guideline revisions on effectiveness/efficiency-related indicators, safety-related indicators, and protocol-related indicators were measured.

Results

Data of 17,111 patient admissions were evaluated, with 714,141 available blood glucose levels (BGL) measurements. Mean BGL, time to reach target, hyperglycemia index, sampling frequency, percentage of hyperglycemia events, and in-range measurements statistically changed after introducing GC in all ICUs. The introduction of simple rules on GC had the largest effect. Subsequent changes in the protocol had a smaller effect than the introduction of the protocol itself. As soon as the protocol was introduced, in all ICUs the percentage of hypoglycemia events increased. Various revisions were implemented to reduce hypoglycemia events, but levels never returned to those from pre-implementation. More intensive implementation strategies including the use of a decision support system resulted in better control of the process.

Conclusion

There are various strategies to achieve GC in routine clinical practice but with variable success. All of them were associated with an increase in hypoglycemia events, but GC was never stopped. Instead, these events have been accepted and managed. Statistical process control is a useful tool for monitoring phenomena over time and captures within-institution changes.

SUBMITTER: Eslami S

PROVIDER: S-EPMC2926931 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Hyperglycemia during critical illness is common, and intravenous insulin therapy (IIT) to normalize blood glucose improves outcomes in selected populations. Methods differ widely in complexity, insulin dosing approaches, efficacy, and rates of hypoglycemia. We developed a simple bedside-computerized decision support protocol (eProtocol-insulin) that yields promising results in the development center. We examined the effectiveness and safety of this tool in six adult and five pediatric intensive care units (ICUs) in other centers.We required attending physicians of eligible patients to independently intend to use intravenous insulin to normalize blood glucose. We used eProtocol-insulin for glucose control for a duration determined by the clinical caregivers. Adults had an anticipated length of stay of 3 or more days. In pediatric ICUs, we also required support or intended support with mechanical ventilation for greater than 24 hours or with a vasoactive infusion. We recorded all instances in which eProtocol-insulin instructions were not accepted and all blood glucose values. An independent data safety and monitoring board monitored study results and subject safety. Bedside nurses were selected randomly to complete a paper survey describing their perceptions of quality of care and workload related to eProtocol-insulin use.Clinicians accepted 93% of eProtocol-insulin instructions (11,773/12,645) in 100 adult and 48 pediatric subjects. Forty-eight percent of glucose values were in the target range. Both of these results met a priori-defined efficacy thresholds. Only 0.18% of glucose values were < or =40 mg/dl. This is lower than values reported in prior IIT studies. Although nurses reported eProtocol-insulin required as much work as managing a mechanical ventilator, most nurses felt eProtocol-insulin had a low impact on their ability to complete non-IIT nursing activities.A multicenter validation demonstrated that eProtocol-insulin is a valid, exportable tool that can assist clinicians in achieving control of glucose in critically ill adults and children.

Project description:BACKGROUND:Surgical site infections (SSIs) cause significant patient suffering. Surveillance and feedback of SSI rates is an evidence-based strategy to reduce SSIs, but traditional surveillance methods are slow and prone to bias. The objective of this cluster randomized controlled trial (RCT) is to determine if using optimized statistical process control (SPC) charts for SSI surveillance and feedback lead to a reduction in SSI rates compared to traditional surveillance. METHODS:The Early 2RIS Trial is a prospective, multicenter cluster RCT using a stepped wedge design. The trial will be performed in 29 hospitals in the Duke Infection Control Outreach Network (DICON) and 105 clusters over 4 years, from March 2016 through February 2020; year one represents a baseline period; thereafter, 8-9 clusters will be randomized to intervention every 3?months over a 3-year period using a stepped wedge randomization design. All patients who undergo one of 13 targeted procedures at study hospitals will be included in the analysis; these procedures will be included in one of six clusters: cardiac, orthopedic, gastrointestinal, OB-GYN, vascular, and spinal. All clusters will undergo traditional surveillance for SSIs; once randomized to intervention, clusters will also undergo surveillance and feedback using optimized SPC charts. Feedback on surveillance data will be provided to all clusters, regardless of allocation or type of surveillance. The primary endpoint is the difference in rates of SSI between the SPC intervention compared to traditional surveillance and feedback alone. DISCUSSION:The traditional approach for SSI surveillance and feedback has several major deficiencies because SSIs are rare events. First, traditional statistical methods require aggregation of measurements over time, which delays analysis until enough data accumulate. Second, traditional statistical tests and resulting p values are difficult to interpret. Third, analyses based on average SSI rates during predefined time periods have limited ability to rapidly identify important, real-time trends. Thus, standard analytic methods that compare average SSI rates between arbitrarily designated time intervals may not identify an important SSI rate increase on time unless the "signal" is very strong. Therefore, novel strategies for early identification and investigation of SSI rate increases are needed to decrease SSI rates. While SPC charts are used throughout industry and healthcare to improve and optimize processes, including other types of healthcare-associated infections, they have not been evaluated as a tool for SSI surveillance and feedback in a randomized trial. TRIAL REGISTRATION:ClinicalTrials.gov NCT03075813 , Registered March 9, 2017.

Project description:BackgroundClinical pathways can enhance care quality, promote patient safety and optimize resource utilization. However, they are infrequently utilized in intensive care. This study aimed to explain the implementation process of a clinical pathway based on a bottom-up approach in an intensive care context.MethodsThe setting was an 11-bed general intensive care unit in Sweden. An action research project was conducted to implement a clinical pathway for patients on mechanical ventilation. The project was managed by a local interprofessional core group and was externally facilitated by two researchers. Grounded theory was used by the researchers to explain the implementation process. The sampling in the study was purposeful and theoretical and included registered nurses (n31), assistant nurses (n26), anesthesiologists (n11), a physiotherapist (n1), first- and second-line managers (n2), and health records from patients on mechanical ventilation (n136). Data were collected from 2011 to 2016 through questionnaires, repeated focus groups, individual interviews, logbooks/field notes and health records. Constant comparative analysis was conducted, including both qualitative data and descriptive statistics from the quantitative data.ResultsA conceptual model of the clinical pathway implementation process emerged, and a central phenomenon, which was conceptualized as 'Struggling for a feasible tool,' was the core category that linked all categories. The phenomenon evolved from the 'Triggers' ('Perceiving suboptimal practice' and 'Receiving external inspiration and support'), pervaded the 'Implementation process' ('Contextual circumstances,' 'Processual circumstances' and 'Negotiating to achieve progress'), and led to the process 'Output' ('Varying utilization' and 'Improvements in understanding and practice'). The categories included both facilitating and impeding factors that made the implementation process tentative and prolonged but also educational.ConclusionsThe findings provide a novel understanding of a bottom-up implementation of a clinical pathway in an intensive care context. Despite resonating well with existing implementation frameworks/theories, the conceptual model further illuminates the complex interaction between different circumstances and negotiations and how this interplay has consequences for the implementation process and output. The findings advocate a bottom-up approach but also emphasize the need for strategic priority, interprofessional participation, skilled facilitators and further collaboration.

Project description:Ageing societies and a rising prevalence of dementia are associated with increasing demand for care home places. Monitoring technologies (e.g. bed-monitoring systems; wearable location-tracking devices) are appealing to care homes as they may enhance safety, increase resident freedom, and reduce staff burden. However, there are ethical concerns about the use of such technologies, and it is unclear how they might be implemented to deliver their full range of potential benefits.This study explored facilitators and barriers to the implementation of monitoring technologies in care homes.Embedded multiple-case study with qualitative methods.Three dementia-specialist care homes in North-West England.Purposive sample of 24 staff (including registered nurses, clinical specialists, senior managers and care workers), 9 relatives and 9 residents.36 semi-structured interviews with staff, relatives and residents; 175h of observation; resident care record review. Data collection informed by Normalization Process Theory, which seeks to account for how novel interventions become routine practice. Data analysed using Framework Analysis.Findings are presented under three main themes: 1. Reasons for using technologies: The primary reason for using monitoring technologies was to enhance safety. This often seemed to override consideration of other potential benefits (e.g. increased resident freedom) or ethical concerns (e.g. resident privacy); 2. Ways in which technologies were implemented: Some staff, relatives and residents were not involved in discussions and decision-making, which seemed to limit understandings of the potential benefits and challenges from the technologies. Involvement of residents appeared particularly challenging. Staff highlighted the importance of training, but staff training appeared mainly informal which did not seem sufficient to ensure that staff fully understood the technologies; 3. Use of technologies in practice: Technologies generated frequent alarms that placed a burden upon staff, but staff were able to use their contextual knowledge to help to counter some of this burden. Some technologies offered a range of data-gathering capabilities, but were not always perceived as useful complements to practice.Implementation of monitoring technologies may be facilitated by the extent to which the technologies are perceived to enhance safety. Implementation may be further facilitated through greater involvement of all stakeholders in discussions and decision-making in order to deepen understandings about the range of potential benefits and challenges from the use of monitoring technologies. Staff training might need to move beyond functional instruction to include deeper exploration of anticipated benefits and the underlying rationale for using monitoring technologies.