a literature review of de qi in clinical studies

A literature review of de qi in clinical studies

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Objectives: De qi is a sensation experienced by a patient or an acupuncturist during acupuncture treatment. Although de qi is considered to be important in acupuncture treatment, there are not many studies about de qi and its character. The purpose of this study is to review de qi questionnaires and evaluate the relationship between de qi and acupuncture points, stimulation and treatment effects. Methods: A search was conducted using three English-language databases (PubMed, Cochrane and ScienceDirect) and seven Korean databases with the keywords 'de qi' and 'needle sensation'. The included studies were then categorised as following: (1) de qi measurement tools, (2) the relationship between de qi and acupuncture points, (3) the relationship between de qi and stimulation, (4) the relationship between de qi and treatment effects and (5) attitudes and opinions toward de qi. Results: Several questionnaires have been developed to evaluate de qi, and the most frequent sensation in those questionnaires was 'heavy' and 'numb'. Although a few studies showed specificity to acupuncture points, information is still lacking to be able to draw a clear conclusion about the relationship between de qi and acupuncture points. Also, greater de qi was elicited in real acupuncture than placebo acupuncture in many studies. The relationship between de qi and treatment effects was controversial. Conclusions: It seems that real acupuncture induced greater de qi than sham acupuncture, and the relationship between de qi, acupuncture points and treatment effects was controversial. However, the current literature evaluating de qi is not sufficient to derive clear conclusions. Further studies with more objective indices and rigorous methodologies are needed.

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Park, J. E., Ryu, Y. H., Liu, Y., Jung, H. J., Kim, A. R., Jung, S. Y., & Choi, S. M. (2013). A literature review of de qi in clinical studies. Acupuncture in Medicine , 31 (2), 132–142. https://doi.org/10.1136/acupmed-2012-010279

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Historical and clinical perspectives on de qi: exposing limitations in the scientific study of de qi

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1 Norwegian School of Health Sciences, Institute of Acupuncture, Kristiania University College , Oslo, Norway .
PMID: 25423501
DOI: 10.1089/acm.2014.0267

De qi is a concept most often associated with patient experiences during needling in acupuncture treatment. A review of the early historical literature on acupuncture shows that texts tended to describe de qi and its associated concept, qi zhi more in terms of practitioner-based phenomena and that this is something more in the realm of the experienced practitioner (i.e., it is skill based). Many modern authors in Asia and the West also describe the importance of practitioner-based experiences in the de qi of acupuncture, further implying that this may lie at the heart of the treatment effects of acupuncture. A review of scientific studies on de qi shows that qualitative studies have focused almost exclusively on patient-based aspects of de qi while quantitative studies have focused exclusively on them. There thus exists a gap in current research on the phenomenon of de qi that possibly reveals weakness in the wider study of acupuncture. It is important that precise qualitative studies of the practitioner-based aspects of de qi begin soon and as they become better understood, quantitative research also is initiated. This research will not only better inform clinical trials and physiologic research of acupuncture in general but could contribute significantly to rethinking of how to train practitioners.

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Evidence-Based Quality Improvement: a Scoping Review of the Literature

Open access
Published: 29 September 2022
Volume 37 , pages 4257–4267, ( 2022 )

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a literature review of de qi in clinical studies

Susanne Hempel PhD 1 , 2 , 6 ,
Maria Bolshakova BS 1 ,
Barbara J. Turner MD 2 ,
Jennifer Dinalo PhD 5 ,
Danielle Rose PhD 3 ,
Aneesa Motala BA 1 , 2 , 6 ,
Ning Fu PhD 1 , 4 ,
Chase G. Clemesha MD 5 ,
Lisa Rubenstein MD 6 &
Susan Stockdale PhD 3

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Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development.

In this scoping review (registration: https://osf.io/hr5bj ) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI?

We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term “EBQI.” Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term “EBQI” with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes.

Conclusions

EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.

Development, characteristics and impact of quality improvement casebooks: a scoping review

Can quality improvement improve the quality of care? A systematic review of reported effects and methodological rigor in plan-do-study-act projects

Searching for qualitative research for inclusion in systematic reviews: a structured methodological review.

Avoid common mistakes on your manuscript.

Evidence-based quality improvement (EBQI) is one of a growing number of strategies used to enhance quality improvement (QI) initiative impacts in clinical practice. EBQI aims to integrate scientific evidence and methods into the QI process while maintaining focus on team-based innovation and problem-solving within real-world settings. Standard healthcare QI approaches focus powerfully on the need for measurement to determine innovation effects, and teams are advised to consult subject matter experts to strengthen their work. 1 , 2 , 3 , 4 , 5 There currently is no standard approach, however, for integrating evidence from relevant pre-existing scientific literature into QI innovation and evaluation. Comprehensive review and critical appraisal of relevant research, for example, is not typically emphasized or conducted. 6 In practice, QI teams often use anecdotal evidence alone to shape innovations, and low-validity methods to evaluate them. 7 EBQI initiatives, as a subset of all QI initiatives, aim to systematically incorporate pre-existing scientific evidence and methods into the QI process as a core focus.

Given its foundation in applying best evidence and distinct focus on collaboration with the practice, EBQI is increasingly recognized as a valuable approach to structure implementation of advances in healthcare delivery. 7 Among other factors, the rapid evolution of partnership improvement initiatives between healthcare organizations and researchers, and the increasing availability of embedded healthcare researchers within healthcare organizations have made EBQI more accessible and attractive to healthcare organizations. 3 , 4 , 5

To date, core elements of EBQI have not been well documented, leaving a critical knowledge gap about components of EBQI and how it differs from other QI approaches. In addition, evidence of the effects of employing EBQI has yet to be synthesized. We found no prior systematic reviews of EBQI, and while individual studies have shown promising results 8 to our knowledge, EBQI has not been evaluated in an evidence synthesis across studies.

This scoping review explores the EBQI literature. We document how EBQI is defined in publications and aimed to identify key components that characterize this methodology across studies. The review catalogues definitions and characteristics of EBQI as currently used in practice. Particular emphasis was on the definition, scope, and use of evidence, i.e., the core aspect of EBQI. We also examined evidence of effectiveness of EBQI. The scoping review was guided by these review questions 10 :

Review question 1: How is EBQI defined?

Review question 2: How is evidence used to inform evidence-informed quality improvement initiatives?

Review question 2a: How is evidence defined in these initiatives?

Review question 2b: What are the components of EBQI?

Review question 3: What is the effectiveness of EBQI to promote uptake of evidence-based practices?

Our objective was to conduct a systematic search to identify the available knowledge, provide a clear description of the methodology, and inform further development of methods for incorporating research evidence into QI initiatives.

The scoping review followed a detailed review protocol. We followed the steps outlined by Arksey and Malloy: (1) determining the research question; (2) identifying relevant studies; (3) selecting studies; (4) charting the data; and (5) collating, summarizing, and reporting the results. 9 In addition, we conducted a consultation exercise to inform and validate findings. The project was deemed exempt by our institutional Human Subject Committee. The protocol was registered in the Open Science Framework and is publicly available. 10 The reporting follows PRISMA-ScR, a PRISMA adaptation for scoping reviews. 11 , 12

Search Strategy

The literature searches are documented in the supplemental digital content ( SDC ). First, a search using the exact terms (“evidence based quality improvement,” “evidence-based quality improvement,” or “EBQI”) was employed to identify publications published to March 2020 that explicitly refer to EBQI in the title, abstract, or keyword of the publication (i.e., the elements that are searchable in research databases). All retrieved publications that used the terminology were included.

Second, we used a broader search strategy aimed at identifying QI initiative evaluations that were not explicitly labeled as EBQI. We assumed that some authors may not use the term “EBQI” even when they have used an evidence-based QI strategy and describe a similar approach in the full-text publication. We applied a string of exclusion criteria to arrive at a manageable sample (see eligibility section), and given the large literature on QI interventions, 19 we searched only for studies published between 2017 and 2020.

We searched PubMed (biomedical literature), CINAHL (nursing and allied health profession literature), and SCOPUS (social sciences). We searched for EBQI publications without date restriction, other QI studies were limited to three years of QI publications as described below in more detail.

Eligibility Criteria

Eligibility criteria were organized in a SPIOS (study design, participants, intervention, outcome, setting) framework; full details are shown in the SDC. Briefly, we applied the following:

EBQI–labeled publications: All publications using EBQI terminology were included in the data abstraction.

Primary care effectiveness subsample: Among EBQI publications, we identified studies reporting effectiveness results for the evaluation of an EBQI initiative. Studies had to report on patient health, and we restricted to primary care to identify a more homogenous sample of research studies.

EBQI–compatible studies: Empirical studies involving U.S. healthcare professionals, reporting on an evaluation of a QI initiative in primary care, and documenting evidence review as part of their methodology to select, design, or implement a QI intervention. Evidence review was defined as a literature review undertaken at the beginning of the project, documentation of locally generated data to determine the need for the intervention (practice-based evidence), and/or utilizing of authoritative sources such as evidence-based clinical practice guidelines. Two independent literature reviewers screened citations and full-text publications; discrepancies were resolved through discussion in the team. Reviewers first excluded all citations that did not indicate an empirical evaluation of a QI initiative. The remaining citations were screened as full-text publication, applying all eligibility criteria described in the SDC (e.g., U.S.-based).

Data Abstraction and Synthesis

Data abstraction was tailored to the review questions. We used ten features in total to characterize the included studies (described in more detail in the SDC ):

Evidence to identify target : using evidence (data) to identify the target of the QI initiative

Iterative : conducting an interactive process for selecting the QI intervention

Engagement of stakeholders : reaching out within the organization to ensure a collaborative process

Evidence to identify intervention : reviewing evidence (research literature or local data) to select effective QI interventions

QI facilitation : use of facilitation of the QI process

Leadership involvement : involving clinical operations leadership in the QI initiative

Priority setting with leadership : setting priorities for the QI initiative together with clinical operations leadership

Frontline engagement : engaging frontline personnel early in the QI initiative

Evidence to determine success : using data to determine the success of the QI initiative

Analytic support : using analytic support to help QI teams

The abstraction domains had been developed by the QI content expert team members drawing on practical and research expertise (SH, ST, BT). The information was collated in evidence tables and component tables allow a concise overview. Effectiveness outcomes were summarized in a random-effects meta-analysis.

Expert Consultation

The preliminary scoping review results were presented to Dr. Lisa Rubenstein, a proponent and conceptual originator of EBQI. The formal consultation step aimed to ensure that the review addresses the right questions, identified all relevant literature, and synthesized the included material appropriately. Dr. Rubenstein was not involved in the planning of the review and assessed methods and results de novo. The consultation exercise resulted in one additional domain (priority setting with leadership) that was added to the data abstraction (see SDC ).

The literature searches identified 2001 citations. Of these, we obtained 496 for full-text inclusion screening. Figure 1 shows the flow diagram.

Flow diagram.

We included 211 publications, detailed in the evidence tables in the SDC. In total, we identified 170 diverse publications that used the term EBQI. SDC Figure 1 plots the number of EBQI publications over time and shows the rapid increase in frequency and popularity of EBQI. Two peaks emerged, one around 2006–2008, the other after 2016. The 170 identified publications are described in detail in an evidence table in the appendix (see SDC Table 1 ) and were used to address review question 1.

Review Question 1 Synthesis: How Is EBQI Defined?

The majority of EBQI–labeled publications did not define EBQI; only 23 of the 170 studies provided a definition or detailed description of the EBQI process. Studies highlighted different aspects of EBQI such as stakeholder engagement 13 or described EBQI broadly as a continuous quality improvement method. 14 Rubenstein et al. 15 defined EBQI as “a continuous quality improvement approach whose goal is translation of research on care delivery models into routine practice.” Figure 2 shows the terms used in the identified publications.

EBQI semantic definition overview.

Review Question 2 Synthesis: How Is Evidence Used to Inform Evidence-Informed Quality Improvement Initiatives?

The second evidence table (SDC Table 2 ) shows all 25 EBQI–labeled studies that reported on an evaluation of a QI initiative (listed first), followed by the 42 EBQI–compatible primary care evaluations, for a total of 67 EBQI–labeled or EBQI–compatible studies. The table shows the wide range of clinical topic areas and interventions addressed and describes their implementation strategy in detail. Across studies, most used published research literature to select interventions to be implemented in the QI initiative.

Review Question 2a Synthesis: How Is Evidence Defined?

In the 25 EBQI–labeled evaluations, 17 studies that provided information on the utilized evidence referred to published literature identified in a literature review. Ten EBQI studies referred to the use of local data. Six studies used expert panels and consensus meetings. Six studies referred to clinical practice guidelines that were reviewed to identify the QI intervention. Studies used these sources either alone or in combination.

Review Question 2b Synthesis: What Are the Components of EBQI?

Table 1 shows the 10 potential EBQI features that we abstracted for each study, the number of features characterizing each study, and the overall frequency of features across studies. EBQI–labeled studies (top half of Table 1 ) are followed by EBQI–compatible studies (bottom half of Table 1 ). Table 2 provides a summary of features across all 67 studies. Across studies, two thirds of studies reported having used evidence to identify an effective intervention, engaging stakeholders, using an iterative development, and involving frontline clinicians. In addition, all 67 identified studies used data to determine the success of the QI initiative.

When we compared features across the subsets, evidence to identify the target of the quality improvement intervention was more frequently reported in EBQI–labeled studies than in EBQI–compatible studies (72% vs 43%). Across EBQI–labeled and EBQI–compatible studies, involvement of leadership in priority setting for the quality improvement target (44% vs 21%) and the provision of analytic support (36% vs 26%) were least frequently reported. EBQI studies consistently reported more EBQI features: the median number of components used within study was 7 for the EBQI–labeled sample (maximum of 10) and 5.5 for the EBQI–compatible sample. The distributions in the two sets differed statistically significantly ( p = 0.037; Mann-Whitney U test).

Review Question 3 Synthesis: EBQI Effectiveness

We abstracted data from all 14 evaluations of primary care QI initiatives that used the term EBQI and that reported on a patient health outcome (SDC Table 3 ). Not all studies provided sufficient detail to allow effect size calculation. None of the studies compared two quality improvement strategies in a head-to-head comparison; hence, the documented effectiveness represents the effectiveness of the combined EBQI and implemented intervention. The forest plot in Figure 3 shows effect estimates for four studies reporting categorical outcomes, expressed as relative risk (RR), that could be combined in a meta-analysis. Studies assessed the implementation of a breast-feeding protocol in primary care, 16 an intervention targeting primary care referrals to smoking cessation clinics, 13 the implementation of collaborative care for depression, 14 and a program to increase adherence to immunization guidelines for adults with diabetes. 17 The effectiveness estimates varied widely by quality improvement target and study, only one of the studies reported a statistically significant effect, but all suggested more improvements in the EBQI group.

EBQI effectiveness.

The scoping review shows that the evidence base for EBQI is growing, and to our knowledge, this is the first study that provides an overview of the available EBQI literature.

We identified EBQI components and their relative frequency, both across EBQI–labeled studies and in comparison to studies that were similar in approach to EBQI without using EBQI terminology. The focus on evidence at multiple stages of the QI initiative and the strong emphasis on engaging stakeholders were key features.

However, “evidence” was often not systematically described in the identified studies. Not all studies reported a review of the evidence to identify a target for the QI initiative (54% across EBQI–labeled and EBQI–compatible studies). This gap calls into question the focus of these studies on using evidence to identify and define QI aims, a critical entry point for introducing evidence into the QI process. Most, but not all (88%) of the studies reviewed evidence to select and shape the QI intervention design, another critical entry point for applying published research, local data, and implementation science knowledge. More complete reporting on evidence use across studies would promote assessment of fidelity to the EBQI process, which is critical to evaluation of the success of the QI initiative and our ability to learn from initiatives across settings. 18

Our review also shows that overall, there is still insufficient information regarding the effectiveness of EBQI. We only found a small number of studies using EBQI that reported on key and patient-centered outcomes, i.e., patient health, and studies addressed substantially different intervention targets, ranging from breast-feeding to depression treatment. We did not find studies that compared EBQI with other quality improvement strategies in head-to-head comparisons; hence, the effect of EBQI in the included studies was invariably confounded with the QI content. It is not known yet how EBQI compares to other quality improvement strategies, in particular quality improvement interventions that are based on anecdotal evidence. Future research should evaluate the comparative effectiveness of EBQI to provide more information on this critical aspect.

Our review has several limitations. While we systematically identified all known EBQI publications, we sampled the literature for EBQI–compatible studies and restricted to those published in recent years and limited to primary care given the large QI literature. 19 The sampling strategy was chosen to obtain a systematic and pragmatic sample that would serve as an exemplar of EBQI–compatible studies. However, it should be noted that earlier approaches were not included, which undoubtedly left out important approaches, and EBQI–compatible approaches in other fields, such as improvements in hospitals in international settings, could have provided additional important information.

We show that EBQI is a promising and growing strategy that aims to integrate prior scientific findings and methods into QI initiatives. Commonly used EBQI features integrate evidence throughout the improvement process, from the initial developmental phase of the QI initiative through to its evaluation. Future research should clearly document EBQI processes to enable better characterization of core initiative features and should assess the comparative effectiveness and success in addressing patient-centered goals.

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The study was funded by the Department of Veteran Affairs. The findings are those of the authors and do not necessarily represent the views of the Department of Veteran Affairs or the United States Government.

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Hempel, S., Bolshakova, M., Turner, B.J. et al. Evidence-Based Quality Improvement: a Scoping Review of the Literature. J GEN INTERN MED 37 , 4257–4267 (2022). https://doi.org/10.1007/s11606-022-07602-5

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http://orcid.org/0000-0003-4318-9555 Emma Jones 1 , 2 ,
Joy Furnival 3 , 4 ,
Wendy Carter 5
1 Clinical Trials Unit , University of Warwick , Coventry , UK
2 Orthopaedic directorate, University Hospitals of Coventry and Warwickshire (NHS Trust) , Coventry , United Kingdom
3 Improvement Directorate, NHS Improvement, Waterloo House , London , UK
4 Health Management Group, Alliance Manchester Business School , University of Manchester , Manchester , UK
5 Maternity Services , Homerton University Hospital NHS Foundation Trust , London , UK
Correspondence to Dr Emma Jones, clinical trials unit, University of Warwick, Coventry CV4 7AL, UK; e.jones.11{at}warwick.ac.uk

Background and aims Summarising quality improvement (QI) research through systematic literature review has great potential to improve patient care. However, heterogeneous terminology, poor definition of QI concepts and overlap with other scientific fields can make it hard to identify and extract data from relevant literature. This report examines the compromises and pragmatic decisions that undertaking literature review in the field of QI requires and the authors propose recommendations for literature review authors in similar fields.

Methods Two authors (EJ and JF) provide a reflective account of their experiences of conducting a systematic literature review in the field of QI. They draw on wider literature to justify the decisions they made and propose recommendations to improve the literature review process. A third collaborator, (WC) co-created the paper challenging author’s EJ and JF views and perceptions of the problems and solutions of conducting a review of literature in QI.

Results Two main challenges were identified when conducting a review in QI. These were defining QI and selecting QI studies. Strategies to overcome these problems include: select a multi-disciplinary authorship team; review the literature to identify published QI search strategies, QI definitions and QI taxonomies; Contact experts in related fields to clarify whether a paper meets inclusion criteria; keep a reflective account of decision making; submit the protocol to a peer reviewed journal for publication.

Conclusions The QI community should work together as a whole to create a scientific field with a shared vision of QI to enable accurate identification of QI literature. Our recommendations could be helpful for systematic reviewers wishing to evaluate complex interventions in both QI and related fields.

quality improvement
continuous quality improvement

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https://doi.org/10.1136/bmjoq-2019-000701

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Introduction

Enthusiasm for quality improvement (QI) in healthcare continues to gather momentum, leading to increasing interest in studies of its effectiveness and to further the development of QI. 1–4 Quality improvement—often shorted to QI—involves making changes to systems and can be used in healthcare to improve specific clinical procedures (such as antibiotic prescribing) or whole care pathways. 3 QI projects are different to clinical research: 1 5–7 they are typically pragmatic and led by local clinicians, 8 often in a single setting, 7 and they tend to be ongoing, or continual, in contrast to research which takes place over a defined period of time. 9 QI can also be conducted as research. QI research has been likened to health services research, which typically aims to examine how care can be delivered to achieve the highest quality of care, 9 and applied research, which can ‘bridge the gap’ (p.1962) 10 between the ideal setting of clinical trials and actual routine care. This paper explores some of the difficulties of reviewing the QI literature.

Policy makers and healthcare staff may use literature reviews to choose QI interventions wisely, thus avoiding implementing changes which are unlikely to provide any benefit. 11 12 Systematic review is one type of literature review which allows the findings and methodological quality of a large number of published articles in a scientific field to be summarised and this remains the gold standard for many decisions made in healthcare. 13 Other types of review including scoping review, narrative review, critical review and systematised review are also important to contextualise and situate research helping to provide a focal point, and to understand the current state of knowledge in a field to prevent research duplication. 14 15

Despite the obvious importance of conducting rigorous reviews, their execution is challenging. 16 The choice of the review approach is contingent on the research question being pursued and its epistemological basis, the time available to conduct the review, the state and quality of the existing literature, and the quality standard required for the review output. 15 Once an appropriate method has been selected, rigorous literature reviewing requires adherence to a series of predefined, reproducible steps to identify, select and critically appraise relevant research. 14 These steps are described in reporting guidelines published by the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) network (such as the Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement), 17 but following such guidance may not always be straightforward when reviewing literature on complex interventions such as QI. 16

Researchers deliberate how to define QI and QI interventions, 18 and QI terminology is vague, inconsistent and variable across disciplines. 19 20 Perhaps as a consequence of this, or a precursor to it, the underlying quality of QI articles and their reporting is known to be poor. 21 22 These definitional issues are not trivial problems. If a systematic review approach cannot capture all relevant literature because it is so difficult to classify articles as ‘QI’, or interventions as ‘QI interventions’, 19 23 24 the review will be incomplete, and less reliable estimates of the effectiveness of QI interventions may be produced. 13 Inconsistent terminology can also make it increasingly difficult for reviewers to assess studies for similarity during meta-analyses. If useful comparisons cannot be made between QI studies, knowledge synthesis becomes even more challenging. 13 25 26 Definitional problems can create similar difficulties for authors using other literature review approaches, including reduced accuracy in article identification and data extraction. Reviewers may seek precedent in the published work of others to hone their own reporting skill, but if others have been faced with inconsistencies, previous confusion can add to the cycle of poor reporting. 27

We each used a different approach to conduct a rigorous literature review within healthcare improvement: (1) Systematic review (EJ). 21 28 (2) Integrative review (JF). 29 EJ examined QI interventions in surgery, and JF examined how improvement capability is conceptualised and assessed. A systematic review attempts to identify experimental and quasiexperimental evidence that fits prespecified eligibility criteria to answer a specific research question. It uses systematic methods designed to minimise bias. 30 An ‘integrative review can precisely represent the state of the current research literature. (It) can be used to … identify the need for future research, build a bridge between related areas of work, … identify a theoretical or conceptual framework’. 31 While our studies were being conducted we were both part of a national programme with biannual learning sets where we could discuss reflections on our ongoing work. We each recorded these in our own reflective research diaries. After we had published our reviews we shared our experiences of conducting them during unstructured discussions over the telephone and by email. Despite different research fields and approaches to literature reviewing, the frustrations we encountered were surprisingly similar.

Our literature reviews required considerable debate to design a suitable search strategy, identify studies which could be defined as QI and categorise interventions into groups. In this account, we describe such debates as a ‘black box’ and we attempt to unravel why debate arose and the compromises and pragmatic solutions we employed to resolve them. We have termed this a ‘black box’ because typically debates such as why some papers were excluded and not others, are not included in scientific reporting, but authors are encouraged to explain when much arbitration was required to resolve disputes. 32 Second, we justify the compromised and perhaps ‘imperfect’ decisions we made. Finally, by sharing what we learnt in the field of QI we make recommendations for others in fields characterised by similar complexity. To improve the credence of the paper, a third collaborator author (WC), challenged views of authors EJ and JF on the problems and solutions of conducting a review of literature in QI. She drew on her experiences of QI research and of writing a narrative synthesis (outside the field of QI) on the perceptions of patients and healthcare workers in women’s’ health. 33

Challenges of conducting a literature review systematically in QI

We identified two main challenges in conducting a review in QI. These were defining QI and selecting QI studies.

Defining QI

We found it challenging to delineate which literature could be described as QI. QI is an ‘emerging’ field of science 19 34 35 and contradicting views on how QI should be defined are commonplace in scientific abstracts 18 19 36 where a large number of terms 37 which change over time 19 20 are being used. Conceptualisation of the term ‘quality improvement’ is also rather unique to the healthcare field. In the engineering and manufacturing industry terms such as total quality management (TQM) and ‘continuous improvement’ are much more common, although how they are used to achieve the aims of QI work in healthcare may be understood differently. Thus, it is not surprising that a single accepted definition of QI is still lacking within healthcare. 38 To add to this, the volume of publications in QI in healthcare is growing, 39 and the work is scattered across different types of journals (QI journals, clinical journals or management journals) 21 and databases. 24 This may be compounded by the lack of agreement as to ‘what is quality?’. 40 41 Therefore, designing a robust review strategy on ‘fuzzy topics’—which are not self-defining—such as quality and QI requires the reviewer to apply judgement to show clear discernment. This may not be a problem which is unique to QI, and we therefore hope that our experiences could be useful to a wider group of researchers.

In addition, QI often uses structured techniques to support the implementation of the intervention, such as Plan-Do-Study-Act (PDSA) cycles. However, while some techniques are related to QI, they may not be easy to define as belonging to the field of ‘QI’. For example, DMAIC (Define, Measure, Analyse, Improve, Control) is commonly used within six sigma and lean six sigma in healthcare, 42 and we define this as belonging to the field of QI. The discipline of Instructional Systems Design also involves five integrated steps: analysis, development, design, implementation and evaluation (ADDIE) 43 and it has been used to solve specific problems in healthcare such as preventing heat loss in patients recovering from surgery. 44 However, ADDIE originates in the field of behavioural psychology and human performance technology (HPT) and is not an easy ‘fit’ in the field of QI. ‘Quality improvement’ and HPT both evolved in the context of a growing emphasis on the importance of a systematic approach to examining the quality of care. 45 However, differences in their lineage can be identified, with HPT being focused on the process of organisational learning and competency, 46 and QI being focused on studying systems and variation within systems. 47 48 Recognising the distinction and similarities between QI and other similar fields is a mindful, defensible way of discerning what ‘counts’ as QI.

During our reflective discussions we realised (EJ, JF) that we had both conducted a scoping review to conceptualise the term ‘quality improvement’. Conceptualising QI early in the review process provided some reassurance unwanted ‘noise’ could be excluded and that all reviewers would consistently identify relevant literature. A third ‘arbitrator’ (WC) helped us to identify what questions we asked during our scoping reviews to resolve the problem of ambiguity in QI:

Who should form our authorship teams? Understanding who publishes research in QI, for example—sociologists, engineers, healthcare professionals—helped us ensure a balanced collection of viewpoints could be brought to our authorship teams. We both worked with clinicians and non-clinicians from different professional backgrounds. EJ (a physiotherapist by background) worked with medical sociologists and an anaesthetist, and JF (an engineer and healthcare manager by background) worked with experts in management and policy.

What research exists on resolving ambiguities in QI ? For example, Rubenstein et al 23 classified QI articles into four types (1) Empirical literature on testing of QI. (2) QI theories and frameworks. (3) QI literature synthesis and meta-analysis. (4) Development and testing of QI-related tools. Each category has strong face validity and is easily recognised.

What search terms have previous QI in healthcare authors used in their published literature reviews? For example—the Health Foundation’s QI evidence scan, 48 and Walshe 20 both review improvement methodologies using a variety of different terms. We both used a variety of different terms for ‘QI’ within searches to capture QI literature. 21 29 We used free-text key words to account for the problem that phrases such as ‘quality improvement’ and ‘continuous improvement’ are sometimes used synonymously.

How is QI defined in the literature?

EJ used consensus meetings with her authorship team to reduce a list of QI definitions ( box 1 ) to one definition deemed to be clear and easy to apply to the literature. Jones et al 21 paraphrased Batalden and Davidoff 49 to define QI as: ‘deliberate structured process of purposeful efforts to make changes that will lead to better outcomes, better system performance, and better professional development’.

In addition to defining QI, JF needed to define ‘improvement capability’ to isolate papers for her review topic. Similarly, literature review revealed no accepted definition. Therefore, Furnival et al (2017) 29 used Whittemore and Knafl’s integrative review method 50 which allows for several perspectives of a topic to be used. Improvement capability was defined as: ‘the organisational ability to intentionally and systematically use improvement approaches, methods and practices, to change processes and products/services to generate improved performance.’ 29

How is QI distinct from, and how does it overlap with, other fields ? To define the field of QI we worked with experts in QI and related fields. EJ adopted values and norms unique to QI in healthcare, distinguishing it as a separate field in order to deploy a specific review methodology in the field of surgery. JF positioned QI across fields, by examining how QI is used in healthcare based on its heritage from manufacturing and industry, partly because JF had a background in engineering, and because there is so much to learn from other fields. The resultant search sought to identify qualitative and quantitative instruments that had been tested across fields and all sectors were included. No date restrictions were used.

EJ contacted experts in related fields such as Human Factors to identify which features could be used to distinguish QI papers and human factors papers from each other. These discussions resulted in a coauthored manuscript with Human Factors and QI experts to expose the similarities and differences between the fields. 51 Conversely, JF acknowledged that HFs (Human Factors) and ergonomics is an integral part of a QI specialist’s skill set, and as such a definition of how QI overlaps (rather than being distinct from) other fields became more important.

We conducted pilot literature searches to ensure a selection of known surgical QI papers 42 and improvement capability papers 52–54 were successfully captured. This verified that EJ’s choice of terms could capture papers which conceptualised QI as relating to a set of values and norms in the healthcare field, and that JF’s choice of terms could capture papers published in both healthcare and related fields.

Selected descriptions of QI in the literature

‘QI is … a process of change in human behaviour, … driven largely by experiential learning’ 87

‘Modern QI concepts had their origins in the statistical process control measurements …the input is a work process needing improvement and the output is a new, improved version of the (existing) work process’ 88

‘Improvement science focuses on systematically and rigorously exploring ‘what works’ to improve quality in healthcare … the focus is … on structured quality improvement approaches, such as plan, do, study, act (PDSA) cycles.’ 48

‘Key elements … are the combination of a ‘change’ (improvement) combined with a ‘method’ (an approach or specific tools) to attain a superior outcome.’ 70

‘The combined and unceasing efforts of everyone—healthcare professionals, patients and their families, researchers, payers, planners and educators—to make the changes that will lead to better patient outcomes (health), better system performance (care) and better professional development.’ 49

‘Better patient experience and outcomes achieved through changing provider behaviour and organisation through using a systematic change method’ 89

The search strategy and databases used by EJ and JF are included in online supplementary file appendix 1 .

Supplemental material

The methods we used to conceptualise the term ‘quality improvement’ have some limitations. For example, asking experts to clarify the nature of QI is subject to heterogeneity in opinions. We also made some concessions. For example, EJ used broad search terms such as ‘quality adj2 improve$’ (where the terms ‘quality’ and variations of ‘improve’ such as ‘improvement’ are identified within two words of each other). This captured titles such as ‘Can quality circles improve hospital-acquired infection control?’, 55 which would not otherwise be identified by ‘quality improvement’. However, this term also captured articles which described quality of care, rather than QI. To overcome problems with specificity, the Medical Subject Headings (MeSH) ‘Quality Improvement/’ and ‘TQM’ are now in use, which guard against the possibility that review teams may not have thought of all relevant synonyms. 56

Additionally, our strategies to resolve ambiguity did not produce perfect classifications. In a relatively new field challenged by inconsistent conceptual and terminological definition, QI can mean different things to different people, depending on professional background, and research aims and intentions. However, documenting which compromises were made and presenting these decisions to others in a discerning, mindful way provides further opportunity for learning which otherwise might be missed. For example, EJ published the review protocol, 28 and registered it with PROSPERO 57 which allows readers to compare the published review with the protocol to check all data were extracted as intended. We both kept a reflective account of decision making. JF used her reflective account to explain that variable conceptualisation and assessment of capability could be eased by employing the integrative method which allows for more than one a priori definition to be used during searching.

Selecting suitable studies in the QI field

Accurately selecting QI studies during a literature review is problematic because it is hard to determine what makes an intervention a ‘QI intervention’. 18 At first glance, any clinical healthcare intervention including pharmaceutical, surgical, physiotherapeutic interventions, for example, could be classed as ‘quality improvement’. All of these interventions aim to improve outcome (quality of life or length of stay, eg), which could in turn impact quality of care. Likewise, checklists, algorithms or pathways are systematic clinical activities that aim to improve outcome. For example, Enhanced Recovery After Surgery (ERAS) pathways combine early mobilisation, intraoperative fluid balance and carbohydrate loading, to achieve an overall effect (reducing surgical stress response to reduce length of stay) which improves a clinical process (surgery). 58–62 Like ERAS pathways, QI work tends to involve the implementation of multiple interventions to improve clinical processes, but ERAS is not routinely referred to as a QI intervention in the literature.

Poor conceptualisation of what makes an intervention a QI intervention prompted EJ to follow the recommendations of Shepperd et al , 16 who suggest that known taxonomies (or rule sets) could aid intervention classification. Jones et al 21 used a taxonomy produced by Shojania et al 63 ( table 1 ). This taxonomy was built on other well-established taxonomies of behaviour change interventions 64–68 after examining QI across a range of medical specialities. 69 Shojania et al 63 describe a QI intervention as something which can improve processes to support clinical activity (such as a reminder system to wash your hands). Therefore, not all interventions to improve quality of care are quality interventions and the content of care (such as a new surgical technique) would not be classed as a QI intervention. 9

View inline

Quality improvement taxonomy

EJ modified Shojania’s original taxonomy to stipulate that a QI intervention must be supported by a QI technique (such as a PDSA cycle) because QI techniques are often cited in the QI literature. 48 70 Not all QI interventions require the use of a QI technique, but EJ and her authorship team used the wider literature to create a pragmatic operationalisation of what constitutes QI. 21

Conversely, JF did not search for interventions, but frameworks and instruments for assessing or measuring improvement capability. However, JF faced similar challenges due to wide heterogeneity in the framework and instrument constructs. Rather than starting out with a narrow conceptualisation of QI and improvement capability, a broader literature was targeted. Keywords were selected to take account of the broad array of terminological heterogeneity across many disciplines, rather than a taxonomy of categories. Therefore this searching strategy required supplementation to identify further high-quality references. 71 72 JF searched across several bibliographical databases with thesaurus terms, MeSH terms and broad-based terms. JF also used citation checking and reference searching to ‘snowball’ iteratively searching backwards and forwards on citations to find more obscure yet relevant articles until saturation was reached. 73 JF operationalised inclusion criteria that improvement capability assessment instruments could only be included within the sample if they had been evaluated at least once and were supported by empirical data. Multiple uses or iterations of the same instrument were discarded.

Our report provides a reflexive, critical overview of the process of reviewing the literature in the field of QI. Through clear documentation of reproducible methods of selecting articles for inclusion (such as using a known taxonomy or method) threats to the validity of our results could be reduced. However, the imperfections of these approaches are well known. Even when a research aid such as taxonomy has been selected, they can be challenging to apply, especially when the terminology used is inconsistent and heterogeneous. 36 37 74 For example, Colquhoun et al 75 explain that one author may use the behaviour change wheel 76 to refer to an intervention as ‘environmental restructuring’, and another may use the EPOC (Cochrane Effective Practice and Organisation of Care) framework 77 to describe the same thing as a ‘structural intervention’. This can exaggerate confusion on how to select and implement the most appropriate taxonomy from the many aids to classification that exist in the literature. 12 Also, the terminology used in Shojania et al ’s 63 taxonomy is not always consistent with the wider QI literature. While more time could have been invested to develop a new set of criteria, the divided opinions of researchers in the field may still have threatened its implementation. Therefore, developing a new taxonomy would have been an ‘over-engineered’ solution which would not necessarily be more helpful than what Jones et al 21 were able to produce. Asking the experts whether they judge their work to sit within the field of QI is also an imperfect indicator of how QI should be defined, yet, the literature is also imperfect.

The methods we suggest to identify scientific publications about QI are not infallible, but they are defensible. There is a large amount of heterogeneity between QI articles in terminology and methodology (diversity in intervention and study design). 42 78–81 A ‘virtually infinite number of combinations of features and local environmental circumstances’ (p.244) 82 also makes the synthesis of QI evidence extremely challenging. Additionally, terms such as QI and improvement capability do not have unproblematic widely agreed meanings. This necessitated judgements to be discerned from a variety of sources including existing literature, expert opinion and personal experience, but these judgements may not be universally accepted within the QI community. For example, EJ’s judgement that QI interventions do not include clinical interventions may be contentious for some, but based on the evidence available and epistemological standpoint, this was deemed wholly appropriate to satisfy the aims of the systematic review.

Recognising the value of a more plural epistemological outlook may also be important for authors reviewing the literature in complex or relatively new scientific fields. EJ followed a systematic review approach which is commonly associated with a positivist approach to gathering and synthesising knowledge. This was well suited to her research question: ‘what is the completeness of reporting of QI interventions in the perioperative literature?’. Conversely, JF adopted a constructivist perspective asking, ‘how is improvement capability conceptualised and assessed?’. While different review questions can drive the method selected for reviewing, the question alone cannot generate a typology of review method. 83 We found value in exploring post hoc the different viewpoints from which we designed our review protocols, recognising their strengths, rather than polarities. Indeed, scholars in the field of QI itself argue that hard scientific evidence needs to be combined with an understanding of beliefs and ‘soft intelligence’ to ensure successful interventions can be spread and adopted within complex organisations such as the National Health Service. 84 85

The problems we describe cannot be resolved immediately but methodological direction is developing. 82 For example, Colquhoun et al , 37 through an international working group, are investigating whether a single consensus on the taxonomic classification of interventions (including QI interventions) is possible. While in clinical practice and research, a degree of uncertainty and creativity can be celebrated to allow thinking to evolve, 86 we suggest that it is important for the QI community as a whole to seek agreement on what constitutes the term QI for two key reasons. First, we must ensure that patients can gain the most benefit from systematic reviews of QI work. To translate the findings of QI into practice, reviewers must be able to identify the QI literature and accurately synthesise it so that robust conclusions may be drawn. Second, agreement on what constitutes QI is needed so that QI research capability can be better facilitated. Organisations offering funding or guidance, may not be able to standardise eligibility for support if they struggle to identify which activities count as improvement and which do not. This may in time relieve the financial and social burden of poor-quality work.

Recommendations

After our reviews were published, we discussed the challenges we faced and how we resolved them during a series of reflective discussions by telephone and email. Through arbitration with a third author (WC), we were able to suggest what other authors could do to ease the process of literature-reviewing in complex fields. Our approach does not offer a definitive solution, but rather a starting point which should be critiqued and refined depending on the review question and aims. Our approach is based on our own reflections of using a systematic approach to reviewing literature in a complex field. There are many existing frameworks and resources (such as the PRISMA statement) to aid review authors, but by using the specific example of QI in healthcare we add to this literature, providing practical examples from our own experience. During our own work, in a field where there is much contention not just about what QI is, but where it fits in a landscape of other sciences, we made pragmatic choices to complete our reviews with finite time and resources. Therefore, we hope that our recommendations can be used as a starting point for authors in similar complex fields to strengthen the practice of systematic and literature reviews:

Maintain transparency and be as thorough as possible (using supplementary materials if required) to expose the challenges you faced to allow the reader to make judgements about the defensibility of your methodological choices.

Assemble a multiprofessional review team (our teams included clinicians, social scientists and engineers).

Ensure the review team can communicate in an open and honest way about uncertainties and compromises.

Conduct a literature scoping exercise to resolve ambiguities in defining the topic and key terms before starting the main review.

Apply a taxonomy or rule to aid classification of concepts.

Contact experts in related fields and authors of papers selected for full-text review to clarify whether a paper meets inclusion criteria if the literature review team cannot agree and ambiguity exists.

Maintain documentation of reflexivity and make this available to experts in your field.

Consider plurality as an approach when working with a multidisciplinary review team.

The QI community should work together as a whole to create a scientific field with a shared vision of what QI is and how literature can be accurately identified to sit within the field of QI . This in turn will allow successful application of solutions, such as those presented in this paper, to enable faster and more accurate identification and synthesis of QI evidence. This will ensure that effective QI work can be adopted rapidly and reliably with greatest impact for patient care. Our recommendations could also be helpful for systematic reviewers wishing to evaluate complex interventions in similar fields.

Acknowledgments

The authors thank Professor Natalie Armstrong (University of Leicester), Professor Graham Martin (THIS (The Healthcare Improvement Studies) Institute, University of Cambridge and the University of Leicester) and Professor Mary Dixon-Woods (The Healthcare Improvement Studies Institute, University of Cambridge) who provided comments on earlier manuscript drafts.

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Contributors EJ planned and managed the overall conduct of this study. EJ, JF and WC contributed to writing the manuscript. EJ submitted the study.

Funding This work was completed with support from three PhD improvement science studentships for EJ, JF and WC from the Health Foundation.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

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J Clin Biochem Nutr
v.73(2); 2023 Sep
PMC10493209

Quality analysis of the clinical laboratory literature and its effectiveness on clinical quality improvement: a systematic review

Ahmed shabbir chaudhry.

1 Department of Medical Quality and Safety Science, Osaka City University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan

2 Department of Intensive Care Medicine, Osaka Women’s and Children’s Hospital, 840 Murodo-cho, Izumi, Osaka 594-1101, Japan

Etsuko Nakagami-Yamaguchi

3 Department of Medical Quality and Safety Science, Osaka Metropolitan University Graduate School of Medicine, 1-4-3 Asahi-machi, Abeno-ku, Osaka 545-8585, Japan

Associated Data

Quality improvement in clinical laboratories is crucial to ensure accurate and reliable test results. With increasing awareness of the potential adverse effects of errors in laboratory practice on patient outcomes, the need for continual improvement of laboratory services cannot be overemphasized. A literature search was conducted on PubMed and a web of science core collection between October and February 2021 to evaluate the scientific literature quality of clinical laboratory quality improvement; only peer-reviewed articles written in English that met quality improvement criteria were included. A structured template was used to extract data, and the papers were rated on a scale of 0–16 using the Quality Improvement Minimum Quality Criteria Set (QI-MQCS). Out of 776 studies, 726 were evaluated for clinical laboratory literature quality analysis. Studies were analyzed according to the quality improvement and control methods and interventions, such as training, education, task force, and observation. Results showed that the average score of QI-MQCS for quality improvement papers from 1981–2000 was 2.5, while from 2001–2020, it was 6.8, indicating continuous high-quality improvement in the clinical laboratory sector. However, there is still room to establish a proper system to judge the quality of clinical laboratory literature and improve accreditation programs within the sector.

Introduction

The robustness of the healthcare system relies upon the clinical laboratory because all the clinical decisions taken on patients by physicians mainly depend upon the clinical lab reports. ( 1 , 2 ) About 70–75% of medical diagnoses are obtained via clinical laboratory reports, making laboratory service quality directly impact healthcare quality. ( 3 , 4 ) Laboratory findings should be precise as possible, also at the same instance; all laboratory operations must be reliable with timely reporting resulting in a beneficial clinical setting. ( 5 ) Negligence during laboratory operations, including processing, assessing, and reporting, can cause severe consequences, including complications, lack of adequate treatment, and delay in correct and timely diagnosis, leading to unnecessary treatment and diagnostic testing. ( 6 – 8 ) A clinical laboratory is a complex set of cultures that include several activity steps, and many people make it unique and saucerful. The comprehensive set of these complex operations occurring during a testing process is called the path of the workflow. ( 9 ) The workflow path in a clinical laboratory initializes with the patient and finishes with reporting and comprehending the results. In any clinical lab setting, it is presumed that mistakes will be made in this process due to the high volume of samples, the limited number of staff, and the different steps implicated in the testing process. ( 10 , 11 ) Errors at any stage of the total testing process (TTP) can result in inaccurate laboratory outcomes. To guarantee the quality of the results, a reliable method for determining errors within the TTP is required. ( 12 )

Significance of quality in the medical laboratory

The term “quality” in the healthcare context has been properly defined by the Institute of Medicine (IOM). ( 13 ) It defines “quality of care as the extent to which health services for individuals and populations increase the probability of desired health outcomes and conform with current professional knowledge.” More recently, quality has been characterized as “doing the right things for the right people, at the right time and doing them right the first time.” In recent years, quality may entail different domains; there appears to be a consensus emerging that quality involves safety, effectiveness, appropriateness, responsiveness or patient-centered care, equity or access, and efficiency.

Importance of standardization

In the context of laboratory medicine, high-quality diagnostic testing (such as for patient safety) is often achieved through the application of standardized processes. Standardization helps to guarantee the accuracy and reproducibility of test outcomes and their appropriate application to the correct patient and also helps to ensure that the results are accurate. The accreditation agencies guarantee crucial points for standardization in laboratory medicine. There are several authorized CLIA accreditation agencies like the College of American Pathologists (CAP), Joint Commission (JCIA), Accreditation Commission for Health Care, Inc (ACHC), and American Association for Laboratory Accreditation, accreditation, which significantly influences quality improvement (QI) in medical laboratory. However, the international organization of standardization ISO is a non-governmental organization that offers a general framework for all procedural sections up to reporting results. Over the years, the establishment and maturity of each agency have brought significant improvement in the medical laboratory sector. The most crucial accreditation is ISO 15189 among all others because ISO 15189 fixates more on laboratory management systems and processes, e.g., The ISO 15189 standard includes requirements linked to the entire testing process, including pre-examination (i.e., pre-analytics), examination (i.e., analytics), and post-examination (i.e., post-analytics). These requirements include developing and implementing standard operating procedures, validation processes, staff training, internal and external quality control (EQC) measures, laboratory setup, and other aspects. In contrast, the other CLIA-approved laboratory accreditation program concentrates more on technical procedures implicated in testing, e.g., policy statement, certification standards, archive standards, and adequate laboratory testing.

The originality of this study

Several systematic analyses have been published on the quality and management of clinical laboratories, but none focus particularly on the overall QI of medical laboratories ( Supplemental Table 1 * ). This leaves a dent in our understanding of QI in clinical laboratory settings. ( 14 , 15 ) Regardless of the number of QIs in a medical laboratory context, the high-quality collective QI systematic review is insufficient, which limits our understating of this field and requires further advancement of QI reporting in the clinical laboratory.

Purpose of the study

This study sought to comprehensively review and evaluate published literature on QI in clinical laboratories. The goal was to provide researchers and professionals with a thorough overview of the present knowledge on quality control (QC) and improvement in medical laboratories. Furthermore, the study sought to determine areas for potential future research and developments in the field of QI in this setting.

Materials and Methods

Study design.

A systematic review is a technique for objectively summarizing prior research through a systematic and replicable process. ( 16 ) This review followed a three-stage design suggested by Tranfield et al. 2003. ( 16 , 17 ) During the planning stage, the choice of databases and keywords and the inclusion and exclusion criteria for selecting contextual articles were identified. The preferred reporting items for systematic reviews and Meta-analyses flow chart (Preferred Reporting Items for Systematic Reviews and Meta-Analyzes) was employed to illustrate selecting articles for inclusion in the final sample.

Data source

To guarantee comprehensive coverage of the literature, multiple databases were applied in the bibliometric analysis. ( 18 , 19 ) In this research, the Web of Science (WOS) core collection and PubMed were chosen for their significance to management and medical research. Three keywords were used to determine relevant articles: “quality control” in any of its forms, terms linked to quality processes such as “quality systems,” “quality improvement,” or “quality management,” and “clinical laboratory” to narrow the focus to the healthcare sector using different databases and these keywords helped to guarantee a comprehensive search of the literature on QC and improvement in clinical laboratories. ( 20 )

Study selection

The present analysis specializes in clinical laboratory QC and improvement research published between 1981 and 2021. To be added, the publication must be a research article and be written in English, with at least a title and summary available. Conference proceedings, letters, notes, reviews, editorials, summaries, and other types of publications were removed from the analysis.

Data processing

Before undertaking the study, we standardized the data to enhance the conformity of the results. We standardized the spelling of the author’s names and the formatting of journal affiliations and other data. We also revised to ensure that citations for each article were not counted multiple times when using both databases. Two authors worked independently to mitigate the risk of errors. Only articles that both reviewers agreed upon were included in the review, as displayed in Fig. 1 .

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PRISMA (preferred reporting items for systematic reviews and meta-analyses)

Quality assessment of literature extracted

The QI Minimum Quality Criteria Set (QI-MQCS) (16) was used to assess this study. The QI-MQCS is employed in the evaluation of QI interventions in healthcare. The QI-MQCS comprises 16 operational and psychometrically dimensions being assessed to present a reliable and accurate assessment of different QI intervention evaluations. Two of the three reviewers in our study individually reviewed the publications. We allocated a score of 1 to each domain with the minimal criterion and a score of 0 to each area that was not satisfied; hence, each article was allocated a score between 0 and 16. The full review committee handled any score disagreements until a consensus was agreed upon. Although the QI-MQCS does not have a set threshold at which the quality of the articles is determined acceptable, “high quality” was defined in this study as a score between 14 and 16. ( 21 )

A total of 776 results were collected from PubMed and WOS bibliographic databases. Of these, 50 were duplicates, and 726 were screened based on their titles and abstracts. After an additional assessment, 224 of the remaining articles were deemed eligible for the QI study, and 53 met the inclusion criteria, as depicted in Fig. 1 . The selected papers were classified into QI ( n = 19) and QC ( n = 33), as presented in Table 1 . Most QI studies were performed in university hospital laboratories ( n = 34), while some of the QC studies were conducted in general community hospital laboratories ( n = 9). There was a great difference in the types of errors detected in these two categories of examinations. Preanalytical errors ( n = 12) were the most prevalent in the QI studies. In contrast, analytical errors ( n = 28) were the most prevalent error in QC studies.

Table 1.

Characteristics of selected papers

		QI	QC
Number of papers		19	33
Institution type	Hospital	6	3
	University hospital	10	24
	Research center	2	0
	University research center	0	1
	Company laboratory	0	2
	Routine clinical laboratories	1	3
Laboratory type	Tertiary care hospital laboratory	1	0
	University hospital laboratory	10	24
	Hospital clinical laboratory	5	3
	Research laboratory	2	0
	Routine clinical laboratory	1	2
	Public and private laboratories	0	1
	University research laboratory	0	1
	Company laboratory	0	2
Focused error type	Preanalytical	12	4
	Analytical	7	28
	Postanalytical	0	1

QI in the clinical laboratory focuses on preserving quality standards. The 19 extracted papers on QI were classified based on their themes, goals, methods, and interventions. The major theme among these papers was the improvement of clinical quality standards lab practice and training in the laboratory ( n = 8), followed by the improvement of problems in the reception area ( n = 5), the improvement of TTP ( n = 4), the management of preanalytical errors ( n = 4), and the evaluation and evolution of quality indicators ( n = 2). Accreditation ( n = 6) was the most prevalent method employed in these QI approaches. In contrast, training and education ( n = 17) were the most common interventions employed to achieve these goals, as highlighted in Table 2 .

Table 2.

Characteristics of quality improvement papers

	Number of papers	19
Theme	Clinical quality standard lab practice and training	8
	Improving the reception area problem	5
	Improvement of TTP	4
	Management of preanalytical errors	4
	Utilization and evolution of quality indicator	2
	Lab workspace initiative	1
	Financial and work volume problems	1
	Ratification of errors	1
Aim	Quality indicators utilization evaluation and evolution	2
	reduction of preanalytical errors	2
	Reduce TAT	1
	Utilization of GCLP guidelines	1
	cost reduction approach	1
	work and workspace improvement techniques	1
	Errors evaluation in terms of sigma metrics	1
	Assessing the level of physician satisfaction with clinical lab reports	1
	Reliability of quality control standards	1
	The method validation process for the new lab setup	1
	Intra and inter-laboratory reproducibility of an ELISA to facilitate Lyme disease diagnosis	1
Methods	Accreditation	6
	Six Sigma/PDSA/DMAIC	10
	QI standards and TQM	3
Intervention	Training/Education	17
	Task force	4
	Observation	1
	Reducing waste	1

PDSA, plan, do, study, act; DMAIC, define, measure, analyze, improve, control; TQM, total quality management.

The retrieved papers were classified based on their objectives, goals, and methods to examine the QC characteristics in the clinical laboratory. The core QC analytical processes in these papers included performance evaluation ( n = 10), QC assessment ( n = 7), improvement of laboratory practices ( n = 3), improvement of quality through the use of the sigma metric ( n = 8), and the QC criteria for susceptibility testing ( n = 7). These processes highlighted the objectives of QC standards in the clinical laboratory. They were implemented using various methods, including accreditation ( n = 22), six sigma ( n = 12), QC practices ( n = 4), statistical approaches ( n = 4), external quality assessment (EQA) ( n = 2), and EQC ( n = 1), as expressed in Table 3 .

Table 3.

Characteristics of quality control papers

	Number of papers	33
Objective	Performance evaluation	10
	Quality control assessment	7
	Laboratory practice improvement	3
	Analytical quality assessment	2
	Execution of training and QC program	1
	Design and implementation of IQC	1
	Evaluated the reliability of serological point-of-care	1
	Evaluation of QC practice	1
	Implementation of QC method	1
	Examines the effects of blood-collection tube additives	1
	QC evaluation of ESR	1
	Periodic analysis of quality control	1
	Standard statistical approach	1
	Identification of biomarker for preanalytical QC	1
	Evaluate the validity of blood lead analysis	1
Aim	Quality improvement through sigma metric	8
	QC criteria of susceptibility testing	7
	Examination of training and QC programs	2
	QC specimens Evaluation	2
	Siemens Dimensions Rxl execution	1
	Calculation of CV and bias	1
	Establishment of IQC based on sigma metric	1
	Validation of Z score indicator	1
	IQC system specification	1
	Evaluate POC tests for EBV	1
	Execution of QC method	1
	CUSUM-Logistic Regression for rapid detection of error	1
	Quality control of Median monitoring	1
	Identification of unsatisfactory scores in the CAP PT surveys	1
	Suggestions Potential biomarker for blood sample quality	1
	Estimation of QC material	1
	Assessment of total testing errors	1
	Identification of disparities	1
Method	Accreditation	22
	Six Sigma	12
	QC Practice	4
	Statistical approach	4
	EQA	2
	EQC/IQC/GQC	3

EQA, external quality assessment; EQC, external quality control; POC, point of care; EBV, Epstein-Barr virus; IQC, internal quality control.

In this systematic review, we evaluated the present state of QI interventions, the frequency of errors in clinical laboratories, and the prevalence of issues in QI reporting by systematically examining QI articles in clinical laboratory contexts. As the number of QI publications in healthcare has elevated, so is the number of QI publications in clinical laboratories. ( 22 ) Laboratory errors can occur at any stage of the TTP and can promote increased healthcare costs, decreased patient satisfaction, delayed diagnosis, misdiagnosis, and adverse risks to patient health. ( 23 ) Despite the increasing automation of laboratory diagnostics, our research discovered that laboratories remain a source of errors that can influence patient care decisions.

Distribution of errors among QI and QC papers

Overall, errors in the preanalytical and postanalytical phases are more prevalent, accounting for most errors. ( 24 ) Errors within the analytical stage are generally fewer. ( 25 , 26 ) Our findings indicate that the frequency of errors within the analytical phase has declined in recent years. We categorized the papers into QI and QC to identify the prevalence of errors in each setting. Our findings revealed that preanalytical errors were most predominant in QI papers, comprising 12 out of 19 papers.

In contrast, analytical errors were mostly observed in QC papers, comprising 28 out of 33 papers, as presented in Table 1 . This disparity may be due to the focus of the papers in each category. QI papers often address training, education on safety teams, and other interventions that involve direct human interaction, such as phlebotomy, which may elucidate the higher prevalence of preanalytical errors in these papers. However, QC papers often assess methods or processes for improvement, such as six sigma, accreditation, QC practices, statistical approaches, and other related methods, which involve more analysis in the context.

GCLP is a potential source for QI

To prevent errors, the clinical laboratory must be accurate and precise in its testing. A quality assurance system based on GCLP guidelines can help with this, but it necessitates the commitment of both management and technical staff. A study executed by Horace Gumba et al. ( 27 ) has revealed that improving the workflow, increasing patient satisfaction, evaluating performance, and improving the test-treatment process can all contribute to QI in the clinical laboratory. Implementing GCLP guidelines also requires effective management, a solid foundation of best practices and a focus on quality culture, and training and education. Another study by Horace Gumba et al. 2018 ( 28 ) indicated that on-site training and education have been found to enhance the implementation of quality management systems considerably. Our previously reported data linked to QI supplement these ideas and propose that writing standard operating procedures, improving documentation practices, implementing GCLP guidelines, conducting improvement projects, and providing training on quality indicators can all be efficient interventions for improving the quality in the clinical laboratory, as expressed in Table 2 .

Performance evaluation

Performance evaluation in clinical laboratories is crucial for guaranteeing test results’ accuracy, precision, and reproducibility. This is typically accomplished through QC materials. These materials, which have prominent values, are used to validate the performance of the laboratory’s test systems. QC materials can be classified into internal and external types. Internal quality control (IQC) materials are used for consistent monitoring of the laboratory’s test systems, while EQC materials are used for comparison to those of other laboratories. A study was carried out by Loh et al. , ( 29 ) analyzed several methods used to assess clinical laboratories’ performance, including QC materials and inter-laboratory comparisons. The study highlighted the importance of constant improvement in the QC of clinical laboratories. Our QC paper intentionally highlights this concept in Table 3 .

Importance of accreditation in clinical laboratory

Accreditation of clinical laboratories is essential for promoting the quality of clinical laboratory practices. Our findings in Table 3 highlight the significance of accreditation in clinical laboratories, which conforms with the findings of research by Alkhenizan et al. ( 30 ) One of the main restrictions to implementing accreditation programs is the skepticism of healthcare professionals, particularly physicians, concerning the impact of accreditation on the quality of healthcare services. ( 31 , 32 ) In healthcare, QI activities are often promoted as part of a total quality management (TQM) strategy, including Kaizen/QI activities in nursing care, medical quality, logistics, administrative work, and patient services. In clinical laboratories, however, the influencing force behind the QI is often linked to accreditation, as it presents formal recognition and certification from a regulatory body that the laboratory is competent and operates effectively. ( 33 )

Influence of accreditation in QI and QC studies

To assess the trend of QI in clinical laboratories, we analyzed papers from 1981 to 2021 and made some intriguing findings. There was relatively minimal research on QI or control from the 1980s to 2000s, possibly due to insufficient quality infrastructure, barriers to globalization, and limited access to modern knowledge. Data categorization revealed that QI and QC trends increased considerably after 2000, suggesting a significant improvement in the laboratory sector. Several possible explanations abound for this trend, including increased awareness of the importance of quality healthcare and developing quality management systems. The most substantial factor is the establishment of accreditation agencies such as ISO 15189 and CAP. CAP and ISO 15189 have greatly impacted the clinical laboratory sector through several initiatives and guidelines. ( 34 ) CAP has had multiple changes from 1994 to 2020, including implementing training and unannounced inspection programs for pathology laboratories, establishing a multiyear initiative to promote the pathology specialty, and introducing CAP 15189 as a voluntary program. ISO 15189 was first published in 2003, offering information on the medical laboratory sector and outlining guidelines for sample procedures, results interpretation, reasonable turnaround times, patient sample collection, and the role of the laboratory in training and educating healthcare staff. It was revised in 2007 to conform with ISO/IEC 17205. A third edition was published in 2012, as depicted in Table 4 , which revised the prior layout and added a section on laboratory information management. ( 35 ) The effects of these changes on QI in clinical laboratories can be seen in our results in Fig. 2 from 2000 onwards, indicating a clear QI trend in medical laboratories.

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Number of QI and QC papers per 5 years from 1981–2020. QC papers were the most published from 2001, indicating the gradual change of quality in clinical laboratory settings.

Table 4.

Introduction of accreditation agencies for the improvement of clinical laboratory

Accreditation agencies	Time frame	Introduction of quality techniques
College of American Pathologists	1946–1996	Certification of hemoglobin standards.
		The professional component in the laboratory.
		Laboratory management index program.
		Cytology policy statement.
		The legal status of pathology.
		Surgical pathology policy.
	1997–2000	Implementation and further advancement of advocating improvement.
	2001–2005	Unannounced inspection programs.
		Several trainings.
	2007–2009	CAP 15189 is a voluntary and non-regulated accreditation to ISO 15189.
		Multiyear initiative.
	2011–2020	Biorepository accreditation program.
		Pathologist quality registry.
		SARS-CoV-2PT.
ISO 15189	First published in 2003	Role of the laboratory in the training and education of health staff.
		Turnaround times.
	Revised in 2007	To align more closely with ISO/IEC 17205.
	Third edition in 2012	Revised the previously published layout and added a new section on laboratory information management.
Joint Commission	2010	Evidence bases lab standards.
		Address the patient safety and quality.
		Survey methodology.

QI-MQCS as a psychometrically tool for quality publication

To determine the QI of clinical laboratory literature, we used the 16 domains of QI-MQCS. ( 21 ) Each paper was evaluated on these domains and scored on a scale of 0 to 16, with a score of 1 given if at least one reason was outlined. The QI papers generally followed the most domains. These papers were then classified by year of publication, and the average QI-MQCS score was determined. A substantial difference in QI-MQCS scores was detected in articles published between 2000 and 2020, as depicted in Fig. 3 . This disparity may be due to the implementation of laboratory QI standards and the accreditation of clinical laboratory facilities, which have been previously outlined.

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This figure illustrates the scoring pattern of QI-MQCS concerning years of publication. The average score of QI-MQCS from 1981–2000 is 2.5, whereas, from 2001–2020, it is 6.8, which reveals the high quality of continuous enhancement in the clinical laboratory sector.

Limitations and strengths

One of the strengths of this analysis is its thorough analysis of all QI-related clinical laboratory papers. The clinical laboratory field is extensive and includes various subfields, but to our knowledge, only 12 reviews have previously addressed QI in the clinical laboratory. This research is the first to thoroughly evaluate all QI-related clinical laboratory papers in one review. There are some limitations to this research. Firstly, the lack of reporting or evaluation of clinical laboratory studies using QI-MQCS limits our comprehension of the QI process. Second, we assessed and scored all papers based on the 16 domains of QI-MQCS, even though some domains may not have been significant to medical laboratories ( Supplemental Table 2 * ). For example, spread (7%), sustainability (3%), penetration (3%), adherence/fidelity (7%), organizational readiness (11%), and intervention description (11%). This is because clinical laboratories do not typically entail delivering interventions or implementing evidence-based interventions in practice and do not usually require the analysis of performance measurements or process systems or developing connections between people.

The major function of the clinical laboratory is to offer diagnostic support to physicians, which can aid in the treatment process and contribute to further progress. However, the QI-MQCS was developed to help stakeholders determine high-quality studies in their field. QI techniques are diverse and distinct from clinical interventions, and the QI-MQCS is a psychometrically tested tool for evaluating the QI-specific characteristics of QI publications. This analysis has possible bias as it did not include other significant databases like Embase and EBSCOhost and only included articles in English.

This study investigated the trend and scope of QI and QC papers in clinical laboratory practice. Our findings revealed that the trend of QI and QC increased markedly after 2000, possibly due to the implementation of laboratory QI standards and the accreditation of clinical laboratory facilities. Our study emphasizes the importance of compliance with good clinical laboratory practice standards and the potential for collaboration between accredited and non-accredited organizations to enhance the quality management system and influence consistent improvement in the clinical laboratory sector.

Author Contributions

This research paper is the culmination of a joint effort between the author, the co-author YI, and the supervisor EN-Y. The study was conceptualized and designed through collaborative discussions between the author and the supervisor. The data collection process was a collaborative effort with significant contributions from YI, who provided valuable data visualization and analysis guidance. The supervisor was crucial in developing and refining the research framework, offering valuable insights that improved study conceptualization. The co-authors reviewed and revised the manuscript and provided critical feedback on presenting findings, including figures and tables.

Acknowledgments

We extend our heartfelt gratitude to the following colleagues for their invaluable contributions and support: Dr. Kaoru Nakatani, Mr. Nozomi Kamamemoto, Ms. Tomoko Honjo, and Mr. Atsushi Tokuwame. Additionally, we would like to acknowledge all those who have been a source of inspiration and motivation throughout the research process.

Abbreviations

DMAIC	define, measure, analyze, improve, control
EQA	external quality assessment
EQC	external quality control
IQC	internal quality control
PDSA	plan, do, study, act
QI	quality improvement
QC	quality control
QI-MQCS	quality improvement Minimum Quality Criteria Set
TQM	total quality management

Conflict of Interest

No potential conflicts of interest were disclosed.

Supplementary Material

DOI: 10.1089/acm.2007.0524
Corpus ID: 17475067

Acupuncture de qi, from qualitative history to quantitative measurement.

J. Kong , R. Gollub , +6 authors T. Kaptchuk
Published in Journal of Alternative and… 31 December 2007

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A literature review of de qi in clinical studies, a review of the methods used for subjective evaluation of de qi., deqi sensation in different kinds of acupuncture.

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Historical and clinical perspectives on de qi: exposing limitations in the scientific study of de qi.

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A literature review of de qi in clinical studies
Abstract. Objectives: De qi is a sensation experienced by a patient or an acupuncturist during acupuncture treatment. Although de qi is considered to be important in acupuncture treatment, there are not many studies about de qi and its character. The purpose of this study is to review de qi questionnaires and evaluate the relationship between ...
A literature review of de qi in clinical studies
Objectives. De qi is a sensation experienced by a patient or an acupuncturist during acupuncture treatment. Although de qi is considered to be important in acupuncture treatment, there are not many studies about de qi and its character. The purpose of this study is to review de qi questionnaires and evaluate the relationship between de qi and acupuncture points, stimulation and treatment effects.
A Literature Review of de qi in clinical studies
De qi is a sensation experienced by a patient or an acupuncturist during acupuncture treatment. Although de qi is considered to be important in acupuncture treatment, there are not many studies about de qi and its character. The purpose of this study is to review de qi questionnaires and evaluate the relationship between de qi and acupuncture points, stimulation and treatment effects.
A Literature Review of de qi in clinical studies
Although de qi is considered to be important in acupuncture treatment, there are not many s... A Literature Review of de qi in clinical studies - Ji-Eun Park, Yeon-Hee Ryu, Yan Liu, Hee-Jung Jung, Ae-Ran Kim, So-Young Jung, Sun-Mi Choi, 2013
A Literature Review of de qi in clinical studies
The included studies were then categorised as following: (1) de qi measurement tools, (2) the relationship between de qi and acupuncture points, (3) the relationship between de qi and stimulation ...
A literature review of de qi in clinical studies
The purpose of this study is to review de qi questionnaires and evaluate the relationship between de qi and acupuncture points, stimulation and treatment effects. ... , title={A literature review of de qi in clinical studies}, author={Jieun Park and Yeonhee Ryu and Yan Liu and Hee Jung Jung and Ae Ran Kim and So-Young Jung and Sun-Mi Choi ...
A literature review of de qi in clinical studies.
Europe PMC is an archive of life sciences journal literature. https://orcid.org
A literature review of de qi in clinical studies
(2013) Park et al. Acupuncture in Medicine. Objectives: De qi is a sensation experienced by a patient or an acupuncturist during acupuncture treatment. Although de qi is considered to be important in acupuncture treatment, there are not many studies about de qi and its character. The purpose of t...
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De Qi refers to a series of sensations experienced when acupuncture is performed at acupoints. De Qi comprises needling sensations felt by the patient, and the sensations perceived by the acupuncturist. Classical Traditional Chinese Medicine theory states that De Qi is closely related to curative effect. In modern studies, the main index that researchers have used to evaluate De Qi was the ...
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De qi is a concept most often associated with patient experiences during needling in acupuncture treatment. A review of the early historical literature on acupuncture shows that texts tended to describe de qi and its associated concept, qi zhi more in terms of practitioner-based phenomena and that this is something more in the realm of the experienced practitioner (i.e., it is skill based).
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A review of scientific studies on de qi shows that qualitative studies have focused almost exclusively on patient-based aspects of de qi while quantitative studies have focused exclusively on them. There thus exists a gap in current research on the phenomenon of de qi that possibly reveals weakness in the wider study of acupuncture. It is important that precise qualitative studies of the ...
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