Use of graphical statistical process control tools to monitor and improve outcomes in cardiac surgery

Monitoring of three-phase variations in the mortality of COVID-19 pandemic using control charts: where does Pakistan stand?

BACKGROUND

At the end of December 2019, the world in general and Wuhan, the industrial hub of China, in particular, experienced the COVID-19 pandemic. Massive increment of cases and deaths occurred in China and 209 countries in Europe, America, Australia, Asia and Pakistan. Pakistan was first hit by COVID-19 when a case was reported in Karachi on 26 February 2020. Several methods were presented to model the death rate due to the COVID-19 pandemic and to forecast the pinnacle of reported deaths. Still, these methods were not used in identifying the first day when Pakistan enters or exits the early exponential growth phase.

OBJECTIVE

The present study intends to monitor variations in deaths and identify the growth phases such as pre-growth, growth, and post-growth phases in Pakistan due to the COVID-19 pandemic.

METHODS

New approaches are needed that display the death patterns and signal an alarming situation so that corrective actions can be taken before the condition worsens. To meet this purpose, secondary data on daily reported deaths due to the COVID-19 pandemic have been considered, and the $c$ and exponentially weighted moving average (EWMA) control charts are used To meet this purpose, secondary data on daily reported deaths in Pakistan due to the COVID-19 pandemic have been considered. The $ c$ and exponentially weighted moving average (EWMA) control charts have been used for monitoring variations.

RESULTS

The chart shows that Pakistan switches from the pre-growth to the growth phase on 31 March 2020. The EWMA chart demonstrates that Pakistan remains in the growth phase from 31 March 2020 to 17 August 2020, with some indications signaling a decrease in deaths. It is found that Pakistan moved to a post-growth phase for a brief period from 27 July 2020 to 28 July 2020. Pakistan switches to re-growth phase with an alarm on 31/7/2020, right after the short-term post-growth phase. The number of deaths starts decreasing in August in that Pakistan may approach the post-growth phase shortly.

CONCLUSION

This amalgamation of control charts illustrates a systematic implementation of the charts for government leaders and forefront medical teams to facilitate the rapid detection of daily reported deaths due to COVID-19. Besides government and public health officials, it is also the public's responsibility to follow the enforced standard operating procedures as a temporary remedy of this pandemic in ensuring public safety while awaiting a suitable vaccine to be discovered.

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.

Statistical process monitoring to improve quality assurance of inpatient care

Background

Statistical Process Monitoring (SPM) is not typically used in traditional quality assurance of inpatient care. While SPM allows a rapid detection of performance deficits, SPM results strongly depend on characteristics of the evaluated process. When using SPM to monitor inpatient care, in particular the hospital risk profile, hospital volume and properties of each monitored performance indicator (e.g. baseline failure probability) influence the results and must be taken into account to ensure a fair process evaluation. Here we study the use of CUSUM charts constructed for a predefined false alarm probability within a single process, i.e. a given hospital and performance indicator. We furthermore assess different monitoring schemes based on the resulting CUSUM chart and their dependence on the process characteristics.

Methods

We conduct simulation studies in order to investigate alarm characteristics of the Bernoulli log-likelihood CUSUM chart for crude and risk-adjusted performance indicators, and illustrate CUSUM charts on performance data from the external quality assurance of hospitals in Bavaria, Germany.

Results

Simulating CUSUM control limits for a false alarm probability allows to control the number of false alarms across different conditions and monitoring schemes. We gained better understanding of the effect of different factors on the alarm rates of CUSUM charts. We propose using simulations to assess the performance of implemented CUSUM charts.

Conclusions

The presented results and example demonstrate the application of CUSUM charts for fair performance evaluation of inpatient care. We propose the simulation of CUSUM control limits while taking into account hospital and process characteristics.

EWMA Control Chart Using Repetitive Sampling for Monitoring Blood Glucose Levels in Type-II Diabetes Patients

In this paper, we discuss the application of the exponentially weighted moving average (EWMA) control chart for the monitoring blood glucose in type-II diabetes patients. We present tables for the practical use in healthcare. From the simulation results and a real example, the efficiency of the proposed chart in detecting a shift in diabetic level is compared with the existing chart. It is found that the proposed chart provides a strict method to monitor the diabetic levels in diabetes patients. From the simulation results and a real example, it is concluded that the use of the proposed chart in health care issues may reduce the risk of heart disease by monitoring diabetic levels in an effective way.

Cumulative summation (CUSUM) charts in the monitoring of hypospadias outcomes: a tool for quality improvement initiative

OBJECTIVE

Cumulative summation (CUSUM) charting is a statistical tool that allows an individual surgeon or surgical department to monitor any binary outcome and rapidly detect when complications are outside the acceptable limits. We applied CUSUM statistical analysis to hypospadias repair to utilize the results in our own quality Improvement process.

MATERIALS AND METHODS

An institutional review board-approved retrospective review of all patients who underwent hypospadias repair by a single fellowship trained pediatric urologist at a single institution between September 2004 to July 2009 was performed. To graphically represent the complication rates and to assess for unacceptable rates, the use of CUSUM control charting was employed.

RESULTS

In our retrospective review, there were a total of 184 patients who underwent a total of 203 surgeries. Using CUSUM analysis, our incidence of major complications was within acceptable limits until approximately the first 150 operations had been performed, at which time the complication rate fell below the lower limit, indicating performance exceeded expectations.

CONCLUSION

CUSUM statistical charting was successfully applied to the retrospective monitoring of hypospadias outcomes at our institution. This is the first known publication in which CUSUM charts were used to evaluate complications of hypospadias repair.