|Year : 2021 | Volume
| Issue : 2 | Page : 127-134
Making transfusion medicine a journey from good to great by using quality indicators and bringing in continuous quality improvement
Department of Pathology, Pramukhswami Medical College, Bhaikaka University, Anand, Gujarat, India
|Date of Submission||21-Oct-2021|
|Date of Decision||25-Oct-2021|
|Date of Acceptance||29-Oct-2021|
|Date of Web Publication||30-Nov-2021|
Dr. Monica Gupta
Department of Pathology, Pramukhswami Medical College, Bhaikaka University, Karamsad, Anand - 322 120, Gujarat
Source of Support: None, Conflict of Interest: None
From its foundational years, transfusion medicine (TM) has been associated with errors and their reporting. Patient safety and quality were brought to the forefront of health care through the Institute of Medicine's two reports followed by the WHO (2004) forming a world alliance of 140 nations. Error reporting in TM has gradually evolved into continuous quality improvement (CQI) and risk management. The review provides insights into the use of quality indicators (QIs), quality tools, and CQI and the models for improvement in TM. QIs in TM have been identified in the past decade; a comprehensive list is provided by the International Society of Blood Transfusion (2019). Analysis of QIs by different tools aids decision-making. Root cause analysis is best carried out using the 5 Whys along with fishbone analysis. Failure-mode-effect-analysis is useful for risk assessment. A process map helps in identifying bottlenecks in a process. A Pareto diagram identifies the “vital few” problems. Likewise, histogram, run diagrams, scatter diagram, and driver diagram, have their own use. Underperforming indicators need to be taken up for quality improvement projects (QIPs). QIPs are designed and implemented by using any of the models available, depending on the problem on hand: the Model for Improvement, FOCUS-PDCA, Six Sigma, and Lean Six Sigma. The utility of clinical audits in improving the quality of transfusion practices and processes cannot be overemphasized. With a structured approach, “goodness” in TM can be measured, and made better. CQI ensures that the journey does not end at “good to great” but continues to progress from “great to greater.”
Keywords: Lean in transfusion medicine, quality indicators/quality improvement plan/quality tools/Model for Improvement, Six Sigma
|How to cite this article:|
Gupta M. Making transfusion medicine a journey from good to great by using quality indicators and bringing in continuous quality improvement. Glob J Transfus Med 2021;6:127-34
|How to cite this URL:|
Gupta M. Making transfusion medicine a journey from good to great by using quality indicators and bringing in continuous quality improvement. Glob J Transfus Med [serial online] 2021 [cited 2022 Jan 23];6:127-34. Available from: https://www.gjtmonline.com/text.asp?2021/6/2/127/331632
| Introduction|| |
Patient safety and quality were brought to the forefront of health care through the Institute of Medicine's two reports,, “To Err is Human (1999)” and “Crossing the Quality Chasm (2001),” followed by the WHO (2004) forming a world alliance of 140 nations – “First Do No Harm. In contrast, transfusion medicine (TM) has been associated with accidents, errors, and their prevention since Landsteiner's landmark discovery of blood grouping systems. James (1954) classified the hazards of transfusion into those associated with the donor, stored blood, with the act of transfusion, and those due to recipient, respectively.
Total process control in blood banking came in through licensing and pharma industry, and has evolved from error reporting and progressed to continuous quality improvement (CQI) and risk management. The approach to these concepts remains unstructured. This review intends to provide insights into the use of quality indicators (QIs), quality tools, and CQI using models for improvement (MFI).
| Quality Indicators|| |
QIs are defined as measurement tools, screens, or flags that are used as guides to monitor, evaluate, and improve the quality of patient care, clinical support services, and organizational function that affect patient outcomes. QIs are also defined as “a quality management system tool to measure the level of quality concerns (risk identification) and their mitigation.” QIs serve as a basis for monitoring implementation of corrective measures and CQI.
| Identifying Quality Indicators in Transfusion Medicine Processes|| |
Based on the Donabedian model, QIs in health care are classified as structure, process, and outcome indicators. However, in TM, they are better classified according to the TM process. Anyaegbu classified potential QIs in three broad categories and identified QIs by highlighting critical control points and key elements necessary for desired quality outcomes. [Table 1] shows the indicators adapted by the International Society of Blood Transfusion (ISBT) as of March 2019.
|Table 1: ISBT on quality management's quality indicators of blood establishments|
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| Quality Indicator Attributes|| |
The attributes of QIs include objectivity, importance and relevance, potential for use, reliability, and validity., Indicators are expressed as numbers, rates, or averages. The numerator and denominator of QI should be defined. Uniform data collection should be ensured, in line with national/international guidelines.
| Benchmarking, Targets, and Quality Improvement Plan|| |
Identified QIs should be benchmarked with other centers/guidelines and realistic goals set, based on current performance. The targets are incorporated in a quality improvement project (QIP). [Table 2] shows the performance of AD Gorwala Blood Bank, Shree Krishna Hospital, from 2008 to 2021.
|Table 2: Quality Indicators monitored at AD Gorwala Blood Centre since 2008|
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| Data Collection|| |
Standardized data collection sheets/templates/checklists should be used to ensure the accuracy and uniformity of data collection. A customized software with a mechanism for review of data and deviations at defined frequencies aids data capture and saves time. Formats for monthly data collection may be used for different processes (donor area, serology, transfusion-transmissible infection, and component area).
| Monitoring|| |
QIs should be monitored at predefined frequency for trends and detection of deviations. Appropriate corrective and preventive actions (CAPA) should be undertaken. Unexpected/undesirable variation must be shared with the national hemovigilance program as these data are critical for national or global monitoring.
| Risk Assessment and Risk Reduction|| |
This involves identifying potential/recurrent nonconformities and assessment of near misses. Two tools are useful in this context: root cause analysis (RCA) and failure-mode-effect-analysis (FMEA)., Examples for reduction of clinical risk include the use of male plasma only, for reducing the incidence of Transfusion related acute lung injury, identifying vulnerable patients, and ensuring vital sign monitoring for mitigating transfusion-associated circulatory overload.
| Root Cause Analysis and Corrective and Preventive Actions|| |
RCA is carried out for establishing causality when adverse trends are noted for any parameter with necessary CAPA., RCA is carried out by using either the 5 Whys Tool or the cause-and-effect diagram.
| Quality Tools|| |
QI data should be analyzed using statistical/quality tools to assess compliance with the targets and identify areas for improvement. A brief outline of utility of quality tools in CQI in TM is provided. The 5 Whys Tool (Taiichi Ohno) involves asking “Why?” five times, sequentially in response to the first answer, till one reaches the root cause. There may be multiple root causes of a problem; different people who see different parts of the system may answer the questions differently. The 5 Whys has come under criticism for overly simplifying the problem on hand.
| Cause-and-Effect Diagram|| |
Cause-and-effect diagram, also known as Ishikawa or fishbone diagram, graphically displays the relationship of the many causes to the effect, and to each other, helping teams identify areas for improvement. A line runs horizontally from the tail to the head of the fish, where the effect is written. Causes are grouped under the categories of materials, methods, equipment, environment, and people [Figure 1]. The tool is used extensively to reach the root cause of deviations and outliers for indicator data and for detailed analysis of incidents and adverse events.
|Figure 1: Cause-and-effect diagram for IQC outlier of fresh frozen plasma|
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| Failure Modes and Effects Analysis|| |
FMEA is a tool for conducting a systematic, proactive analysis of a process in which harm may occur and prevent it by correcting the processes proactively, rather than reacting to adverse events after failures have occurred [Table 3]. The tool forms the core of risk assessment and risk mitigation. FMEA is particularly useful in evaluating a new process prior to implementation and in assessing the impact of a proposed change to an existing process.
| Flowchart (Process Map)|| |
Flow charts help understand a process in depth through visual representation of its steps, and should be prepared in early phase of improvement work. It helps identify gaps in the process, its bottlenecks, wasteful/unnecessary processes, delays, duplication, breakdowns in communication, and also how to improve the process. Improvement work can be focused on these steps.
| Pareto Chart|| |
The “Pareto principle” is the “80/20 rule” and works on the theory that roughly 80% of the effect comes from 20% (”the vital few”) of the causes. The “vital few” are easily distinguished from the “useful many” by plotting them as a bar diagram. Teams can prioritize and focus improvement efforts on the vital few.
| Driver Diagram|| |
A driver diagram is a visual display of what “drives,” or contributes to, the achievement of a project aim. The diagram portrays the relationship between the overall aims of the project. The primary drivers (sometimes called “key drivers”) contribute directly to achieving the aim. The secondary drivers are components of the primary drivers, and specific change ideas to test for each secondary driver.
| Run Chart and Control Chart|| |
A run chart is a graph of data over time and assesses variations in performance over a period of time and indicates trends. A control chart, with an upper control limit and a lower control limit, distinguishes between common and special causes of variation within a process.
| Scatter Diagram/Plot|| |
Scatter diagrams are used to identify cause-and-effect relationships between two variables. A scatter diagram does not prove causation.
| Project Planning Form|| |
This tool helps teams think systematically about their improvement project. It tracks various elements like Plan-Do-Study-Act (PDSA) cycles. Butch has effectively demonstrated quality improvement tools in TM while discussing two problem areas of the laboratory.
| Continuous Quality Improvement|| |
CQI is a progressive incremental improvement of processes, safety, and patient care. Introduced by Shewhart and propagated by Deming, CQI is an analytical decision-making tool which allows one to see when a process is working predictably and when it is not.
| Models for Continuous Quality Improvement|| |
The most common CQI methodologies used in health care are the API's MFI, FOCUS PDSA, Six Sigma, and Lean strategies. They typically include testing of ideas and redesign of process or technology based on lessons learned. Steps involved in CQI are PDSA cycle., The MFI and FOCUS frameworks have been developed to precede the use of PDSA and PDCA cycles, respectively. PDSA/PDCA cycle involves a sequence of four repetitive steps, Plan-Do-Study/Control-Act [Table 4], eventually leading to exponential improvements., The cycle is repeated again and again as waves of small improvements are considered, tested, evaluated, and incorporated, if effective. Niar et al. used PDCA cycles for bedside transfusions and designed a QIP.
| The Model for Improvement|| |
The MFI asks three fundamental questions before embarking on a QI project, which can be addressed in any order [Figure 2]. This is followed by PDSA cycles to test changes in real work settings to determine if the change is an improvement. [Table 4] demonstrates the application of MFI quality improvement in blood donation and in blood transfusion.
|Figure 2: An example of models for improvement which has incorporated Plan-Do-Study-Act cycles with the aim to reduce the wastage of platelet concentrates at our center. The models for improvement ask three basic questions, followed by Plan-Do-Study-Act cycles. The steps in Plan-Do-Study-Act cycle are shown in the figure|
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| FOCUS-PDCA|| |
This model also has two phases [Table 5]. The “FOCUS” phase focuses attention at the opportunity to improve, and the “PDCA” phase for pursuit of improvement and assessment of effectiveness of the interventions.,
| Six Sigma|| |
Six Sigma is a widely used model that is now making steady inroads into TM., It seeks to improve performance through identifying causes of process defects/errors and eliminating them. At Six Sigma, error rates should be <3.7/million opportunities. [Table 6] demonstrates the use of Six sigma in reducing the quality not sufficient(QNS) collections and in reducing aphaeresis outdates.
| LEAN and LEAN - SIX SIGMA|| |
Originated by Toyota Inc., Japan, this model is essentially geared toward improving process / product / service flow and eliminates waste by identifying and removing nonvalue added steps. Embracing Lean in TM, eliminates waste throughout the entire operational system, while simplifying and improving the processes, resulting in low cost of production and fast throughput times. A few TM establishments have combined Lean and Six Sigma concepts to obtain better quality improvement effects. Such a combination is known as Lean Sigma. An interdisciplinary hospital team (TM, nursing, and anesthesiology) used Lean Sigma methodology and successfully implemented interventions to reduce red blood cell wastage.
| Clinical Audits|| |
Blood transfusion is an important intervention in critically ill patients. However, there is significant variation in transfusion practices, even with institutionalization of transfusion protocols. Audits of transfusion practices have shown improvement in adherence to guidelines and also decreased the number of transfusions. Clinical audits are recognized as effective tools to improve the rationality and effectiveness of bedside transfusion practices.
| Conclusion|| |
TM has progressed from being preoccupied with error detection and analysis, to improving quality, achieving excellence, and preventing errors. It is imperative for any blood center to monitor quality, by identifying QIs which are suited to its processes and quality management system. This is re-emphasized by the release of the revised list of QIs by ISBT in March 2019. The use of quality tools and improvement models provides a structured and scientific approach to problem-solving and quality improvement with objective results. With a structured approach, “goodness” in TM can be measured, and made better. CQI ensures that the journey does not end at “good to great” but continues to progress from “great to greater.”
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]