Dataset Information

A modified Delphi study to identify the features of high quality measurement plans for healthcare improvement projects.

ABSTRACT:

Background

The design and execution of measurement in quality improvement (QI) initiatives is often poor. Better guidance on "what good looks like" might help to mitigate some of the problems. We report a consensus-building process that sought to identify which features are important to include in QI measurement plans.

Methods

We conducted a three-stage consensus-building approach: (1) identifying the list of features of measurement plans that were potential candidates for inclusion based on literature review and the study team's experience; (2) a two-round modified Delphi exercise with a panel of experts to establish consensus on the importance of these features; and (3) a small in-person consensus group meeting to finalise the list of features.

Results

A list of 104 candidate questions was generated. A panel of 19 experts in the Delphi reviewed these questions and produced consensus on retaining 46 questions in the first round and on a further 22 in the second round. Thematic analysis of open text responses from the panellists suggested a number of areas of debate that were explicitly considered by the consensus group. The exercise yielded 74 questions (71% of 104) on which there was consensus in five categories of measurement relating to: design, data collection and management, analysis, action, and embedding.

Conclusions

This study offers a consensus-based view on the features of a good measurement plan for a QI project in healthcare. The results may be of use to QI teams, funders and evaluators, but are likely to require further development and testing to ensure feasibility and usefulness.

SUBMITTER: Woodcock T

PROVIDER: S-EPMC6961316 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Publications

A modified Delphi study to identify the features of high quality measurement plans for healthcare improvement projects.

Woodcock Thomas T Adeleke Yewande Y Goeschel Christine C Pronovost Peter P Dixon-Woods Mary M

BMC medical research methodology 20200114 1

<h4>Background</h4>The design and execution of measurement in quality improvement (QI) initiatives is often poor. Better guidance on "what good looks like" might help to mitigate some of the problems. We report a consensus-building process that sought to identify which features are important to include in QI measurement plans.<h4>Methods</h4>We conducted a three-stage consensus-building approach: (1) identifying the list of features of measurement plans that were potential candidates for inclusi ...[more]

PMID: 31937262

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Project description:OBJECTIVES:Healthcare is a complex system, so quality improvement will commonly lead to unintended consequences which are rarely evaluated. In previous qualitative work, we proposed a framework for considering the range of these potential consequences, in terms of their desirability and the extent to which they were predictable or expected during planning. This paper elaborates on the previous findings, using consensus methods to examine what consequences should be identified, why and how to prioritise, evaluate and interpret all identified consequences, and what stakeholders should be involved throughout this process. DESIGN:Two-round modified Delphi consensus study. SETTING AND PARTICIPANTS:Both rounds were completed by 60 panellists from an academic, clinical or management background and experience in designing, implementing or evaluating quality improvement programmes. RESULTS:Panellists agreed that trade-offs (expected undesirable consequences) and unpleasant surprises (unexpected undesirable consequences) should be actively considered. Measurement of harmful consequences for patients, and those with high workload or financial impact was prioritised, and their evaluation could also involve the use of qualitative methods. Clinical teams were agreed as important to involve at all stages, from identifying potential consequences, prioritising which of those to systematically evaluate, undertaking appropriate evaluation and interpreting the findings. Patients were necessary in identifying consequences, managers in identifying and prioritising, and improvement advisors in interpreting the data. CONCLUSION:There was consensus that a balanced approach to considering all the consequences of improvement can be achieved by carefully considering predictable trade-offs from the outset and deliberately pausing after implementation to identify any unexpected surprises and make an informed decision as to whether quantitative or qualitative evaluation is needed and feasible. Stakeholders' roles in in the process of identifying, prioritising, evaluating and interpreting potential consequences should be explicitly addressed within planning and revisited during and after implementation.

Project description:ObjectiveTo explore primary care administrators' perceptions of provincially mandated quality improvement plans, and barriers to and facilitators of using quality improvement plans as tools for improving the quality of primary care.DesignQualitative descriptive study using semistructured interviews.SettingOntario.ParticipantsEleven primary care administrators (ie, executive directors, director of clinical services, office administrators) at 7 family health teams and 4 community health centres.MethodsAll interviews were audiotaped and transcribed verbatim. Data were analyzed deductively to generate a framework based on a conceptual model of structural, organizational, individual, and innovation-related factors that influence the success of improvement initiatives and, inductively, to generate additional themes.Main findingsProvincially mandated quality improvement plans seem to have raised awareness of and provided an overall focus on quality improvement, and have contributed to primary care organizations implementing initiatives to address quality gaps. Four factors that have contributed to the success of quality improvement plans relate to attributes of the quality improvement plans (adaptability and compatibility) and contextual factors (leadership and organizational culture). However, participants expressed that the use of quality improvement plans have not yet led to substantial improvements in the quality of primary care in Ontario, which may be owing to several challenges: poor data quality, lack of staff and physician engagement and buy-in, and lack of resources to support measurement and quality improvement.ConclusionAwareness of and focused attention on the need for high-quality patient care may have increased, but participants expressed that substantial improvements in quality care have yet to be achieved in Ontario. The lack of perceived improvements is likely the result of multifaceted and complex challenges primary care organizations face when trying to improve patient care. To effect positive change, organization- and health system-level efforts are needed to improve measurement capabilities, improve staff and physician engagement, and increase capacity for quality improvement among organizations.

Dataset Information

A modified Delphi study to identify the features of high quality measurement plans for healthcare improvement projects.

Background

Methods

Results

Conclusions

Publications

A modified Delphi study to identify the features of high quality measurement plans for healthcare improvement projects.

Similar Datasets

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