Impact of implementation of evidence-based strategies to reduce door-to-balloon time in patients presenting with STEMI: continuous data analysis and feedback using a statistical process control plot

Reducing the Wire Crossing Time in Primary Percutaneous Coronary Angioplasty: A Study From a Tier II City in India

Acute coronary syndrome is a major cause of morbidity and mortality all over the world. Timely intervention in ST-elevation myocardial infarction (STEMI) in the form of primary angioplasty is the gold standard of treatment to reduce mortality and morbidity. “Time is muscle” is the phrase to impress upon the importance of time in treating patients with STEMI. Traditional treatment target included “door to balloon time” of 90 min or less. This “door to balloon time” is now rephrased as the “wire crossing time” (WCT). The European Society of Cardiology (ESC) updated its guidelines further, reducing the target of wire crossing time to 60 min.

The present study is a brief report on the door to wire crossing time status in one of the tertiary care centers of a nonmetro city. Retrospective analysis of case records was done for 79 patients admitted with acute MI who underwent primary angioplasty between November 2018 and June 2019 (pre-corrective action group). Various reasons for the delay, right from the time of the patient reaching the emergency room (ER) to the time of wire crossing, were analysed and measures were taken to reduce the delay. The post-corrective action group comprised 77 patients. The major causes of a prolonged WCT in our setup were delayed diagnosis of STEMI in ER, delay in giving consent by the patient’s relatives, financial issues, and availability of cath lab technicians during the off-duty hour. The delay in WCT in our center was 121 min. Remedial actions were taken to mitigate the problems at each step, which resulted in a reduction of delay by 20 min, i.e., to 101 min leading to a significant difference in the outcome in view of morbidity and mortality.

Statistical process control assessed implementation fidelity of patient-reported outcome measures (PROMs) in routine care

OBJECTIVES

Ensuring implementation fidelity of patient-reported outcome measures (PROMs) in the complex clinical setting remains exigent. We aimed to integrate the routine use of PROM reports in day-to-day patient care and assess the implementation outcomes using statistical process control (SPC) methods.

STUDY DESIGN AND SETTING

This prospective pilot study used an implementation science framework to integrate PROMs. SPC analysis was applied to track patient completion rates and staff acknowledgment rates over time. Daily observational data across clinical areas were collected to assess potential variations.

RESULTS

Data were available from 324 patient encounters over 14 weeks. On average, 78% (52% to 100%) of eligible patients entering the clinic completed the PROMs; staff acknowledged 78% (50-100%) of these patient reports. Most patterns of fluctuation were inside the control frame. Dips in compliance relating to changes in clinic daily routine, including the introduction of the second randomized clinic, were quickly resolved with a structured response.

CONCLUSION

Implementation of PROMs was feasible with reasonable patient completion and staff acknowledgment rates. Fidelity was vulnerable to barriers impacting the daily routine or unusual events in the clinics, suggesting that greater standardization and integration into clinic processes may yet further improve compliance and consistency of reporting.

Process mapping as a framework for performance improvement in emergency general surgery

BACKGROUND

Emergency general surgery conditions are often thought of as being too acute for the development of standardized approaches to quality improvement. However, process mapping, a concept that has been applied extensively in manufacturing quality improvement, is now being used in health care. The objective of this study was to create process maps for small bowel obstruction in an effort to identify potential areas for quality improvement.

METHODS

We used the American College of Surgeons Emergency General Surgery Quality Improvement Program pilot database to identify patients who received nonoperative or operative management of small bowel obstruction between March 2015 and March 2016. This database, patient charts and electronic health records were used to create process maps from the time of presentation to discharge.

RESULTS

Eighty-eight patients with small bowel obstruction (33 operative; 55 nonoperative) were identified. Patients who received surgery had a complication rate of 32%. The processes of care from the time of presentation to the time of follow-up were highly elaborate and variable in terms of duration; however, the sequences of care were found to be consistent. We used data visualization strategies to identify bottlenecks in care, and they showed substantial variability in terms of operating room access.

CONCLUSION

Variability in the operative care of small bowel obstruction is high and represents an important improvement opportunity in general surgery. Process mapping can identify common themes, even in acute care, and suggest specific performance improvement measures.

Using Time Series Analysis to Predict Cardiac Arrest in a PICU

OBJECTIVES

To build and test cardiac arrest prediction models in a PICU, using time series analysis as input, and to measure changes in prediction accuracy attributable to different classes of time series data.

DESIGN

Retrospective cohort study.

SETTING

Thirty-one bed academic PICU that provides care for medical and general surgical (not congenital heart surgery) patients.

SUBJECTS

Patients experiencing a cardiac arrest in the PICU and requiring external cardiac massage for at least 2 minutes.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

One hundred three cases of cardiac arrest and 109 control cases were used to prepare a baseline dataset that consisted of 1,025 variables in four data classes: multivariate, raw time series, clinical calculations, and time series trend analysis. We trained 20 arrest prediction models using a matrix of five feature sets (combinations of data classes) with four modeling algorithms: linear regression, decision tree, neural network, and support vector machine. The reference model (multivariate data with regression algorithm) had an accuracy of 78% and 87% area under the receiver operating characteristic curve. The best model (multivariate + trend analysis data with support vector machine algorithm) had an accuracy of 94% and 98% area under the receiver operating characteristic curve.

CONCLUSIONS

Cardiac arrest predictions based on a traditional model built with multivariate data and a regression algorithm misclassified cases 3.7 times more frequently than predictions that included time series trend analysis and built with a support vector machine algorithm. Although the final model lacks the specificity necessary for clinical application, we have demonstrated how information from time series data can be used to increase the accuracy of clinical prediction models.

Statistical process control: separating signal from noise in emergency department operations

BACKGROUND

Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations.

OBJECTIVE

We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed.

DISCUSSION

SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance.

CONCLUSION

Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine.

The importance of audit to monitor applications of procedures and improve primary angioplasty results

Although clinical trials have demonstrated that primary percutaneous coronary intervention (PPCI) provides better outcomes than thrombolysis for STEMI, it cannot be assumed that similar results can be obtained in day-to-day practice. To determine whether standards are being met, continuous audit of PPCI programmes is necessary, with appropriate feedback to participating centres and operators. Both the MINAP and BCIS national audit projects allow central electronic collection of data on consecutive patients presenting to every hospital involved in the acute management of these patients. Regular programmed feedback is provided to centres performing primary PCI that attempts to take account of statistical variation and differences in case mix between units by making use of funnel plots, statistical process control graphs and risk adjustment models. This reporting of "process" and "outcome" data, both confidentially and within the public domain, has been used to drive up clinical performance and has been associated with steady improvements and reduced inequalities of care.

Hospital-based strategies contributing to percutaneous coronary intervention time reduction in the patient with ST-segment elevation myocardiaI infarction: a review of the "system-of-care" approach

A myriad of hospital-wide initiatives have been implemented with the goal of decreasing door-to-balloon time. Much of the evidence behind the common strategies used is unknown; multiple strategies have been suggested in the reduction to the use of this important time-sensitive intervention. Among 8 primary strategies, 2 have substantial evidence to support their implementation in the attempt to reduce door-to-balloon time in ST-segment elevation myocardial infarction (STEMI), including emergency physician activation of the cardiac catheterization laboratory and prehospital activation of the STEMI alert process. Two strategies have moderate evidence to support their use, including real-time data feedback to team members and team-based approach to STEMI management. The remaining 4 strategies have no quantitative evidence to support their use, including single call to a central paging system, expecting the cardiac catheterization laboratory personnel to arrive within 20 minutes of activation, attending cardiologist on site (within the hospital), and senior management commitment to the project. Although all the STEMI systems of care reviewed are associated with a decreased in time to treatment, only a few have sufficient quantitative evidence to support their implementation. To be effective, the movement to decrease time to treatment of STEMI at any hospital must be composed of an institutional response that includes multiple disciplines. Success also requires active participation from nurses, members of the catheterization team, and hospital leadership.