Key Performance Indicators in Radiology: You Can’t Manage What You Can’t Measure

Harvey, H. Benjamin; Hassanzadeh, Elmira; Aran, Shima; Rosenthal, Daniel I.; Thrall, James H.; Abujudeh, Hani H.

doi:10.1067/j.cpradiol.2015.07.014

Cited by 31 publications

(18 citation statements)

References 34 publications

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“…11 Most countries reported the use of KPIs, which highlights the progress toward quantification in quality improvement programs. A recent article by Harvey et al 12 suggested that radiology organizations openly publish semi-anonymized KPI data to allow for comparison of these metrics and establishment of performance benchmarks. Indeed, there is a seeming lack of data which renders it difficult to compare KPIs between countries; nevertheless, the top KPIs in our survey were wait times, report turnaround times, productivity, and patient satisfaction.…”

Section: Discussionmentioning

confidence: 99%

An International Survey of Quality and Safety Programs in Radiology

et al. 2020

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Purpose: The aim of this study was to determine the status of radiology quality improvement programs in a variety of selected nations worldwide. Methods: A survey was developed by select members of the International Economics Committee of the American College of Radiology on quality programs and was distributed to committee members. Members responded on behalf of their country. The 51-question survey asked about 12 different quality initiatives which were grouped into 4 themes: departments, users, equipment, and outcomes. Respondents reported whether a designated type of quality initiative was used in their country and answered subsequent questions further characterizing it. Results: The response rate was 100% and represented Australia, Canada, China, England, France, Germany, India, Israel, Japan, the Netherlands, Russia, and the United States. The most frequently reported quality initiatives were imaging appropriateness (91.7%) and disease registries (91.7%), followed by key performance indicators (83.3%) and morbidity and mortality rounds (83.3%). Peer review, equipment accreditation, radiation dose monitoring, and structured reporting were reported by 75.0% of respondents, followed by 58.3% of respondents for quality audits and critical incident reporting. The least frequently reported initiatives included Lean/Kaizen exercises and physician performance assessments, implemented by 25.0% of respondents. Conclusion: There is considerable diversity in the quality programs used throughout the world, despite some influence by national and international organizations, from whom further guidance could increase uniformity and optimize patient care in radiology.

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Section: Discussionmentioning

confidence: 99%

An International Survey of Quality and Safety Programs in Radiology

et al. 2020

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“…We did not consider noncommercial applications that also provide solutions, which are commonly used in research. A radiologist with 10+ years of experience in neuroradiology (AO) performed the coding of the collected data by using codebooks to examine which tasks of radiology [15,16] are targeted by an application and what kind of impacts it can have on these tasks (i.e. 'supporting', 'extending', 'replacing'; Table 1).…”

Section: Data Collection and Codingmentioning

confidence: 99%

Promises of artificial intelligence in neuroradiology: a systematic technographic review

2020

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Purpose To conduct a systematic review of the possibilities of artificial intelligence (AI) in neuroradiology by performing an objective, systematic assessment of available applications. To analyse the potential impacts of AI applications on the work of neuroradiologists. Methods We identified AI applications offered on the market during the period 2017–2019. We systematically collected and structured information in a relational database and coded for the characteristics of the applications, their functionalities for the radiology workflow and their potential impacts in terms of ‘supporting’, ‘extending’ and ‘replacing’ radiology tasks. Results We identified 37 AI applications in the domain of neuroradiology from 27 vendors, together offering 111 functionalities. The majority of functionalities ‘support’ radiologists, especially for the detection and interpretation of image findings. The second-largest group of functionalities ‘extends’ the possibilities of radiologists by providing quantitative information about pathological findings. A small but noticeable portion of functionalities seek to ‘replace’ certain radiology tasks. Conclusion Artificial intelligence in neuroradiology is not only in the stage of development and testing but also available for clinical practice. The majority of functionalities support radiologists or extend their tasks. None of the applications can replace the entire radiology profession, but a few applications can do so for a limited set of tasks. Scientific validation of the AI products is more limited than the regulatory approval.

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“…Key Performance Indicators (KPI), are metrics developed for monitoring diverse processes, tasks, projects or organizations. These are efforts undertaken with the aim of obtaining management results [16].…”

Section: E Monitoring Of Cost Management By Performance Indicatorsmentioning

confidence: 99%

Evaluation of Impact of Cost Information System: A Case Study of Credit Institution and Construction of Houses for Navy Employees

Santos

Oliveira

Veroneze

et al. 2020

EJBMR

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The objective of this work was to evaluate how Federal Government's Cost Information System (CIS) contributed positively in the decision-making of cost management in the Caixa de Construções de Casas para o Pessoal da Marinha (Credit Institution and Construction of Houses for Navy Employees). This research proposed the hypothesis that the variables of the Cost Information System (CIS), classified by this work in System Quality (SIST-Q), Information Quality (Q-INFO) and Perceived Utility (P-UTILI) generate positive effect on decision making in the more efficient allocation of expenses at federal autarchy. The study was carried out through a “Case Study”, using descriptive statistics and the Confirmatory Factor Analysis technique, based on an information systems assessment model widely studied in the literature, proposed by Delone and Mclean. The survey results suggest that there is a moderately consistent scale for measuring the effectiveness of the Cost Information System (CIS), which is made up of the three latent variables: quality of the system, quality of information and perceived utility. It was evaluated that the CIS does not produce results for cost management because the management information extracted from the system is not used for decision making by managers. Additionally, a performance indicator was suggested to monitor federal autarchy's cost management. This work suggests that new research be carried out with other organizations that use the CIS in order to better understand the needs of organizations regarding the adequacy of the System to their needs.

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Key Performance Indicators in Radiology: You Can’t Manage What You Can’t Measure

Cited by 31 publications

References 34 publications

An International Survey of Quality and Safety Programs in Radiology

An International Survey of Quality and Safety Programs in Radiology

Promises of artificial intelligence in neuroradiology: a systematic technographic review

Evaluation of Impact of Cost Information System: A Case Study of Credit Institution and Construction of Houses for Navy Employees

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