The radiology digital dashboard: effects on report turnaround time

Utilizing the open-source programming language Python to create interactive Quality Assurance dashboards for diagnostic and screening performance in Cytology

INTRODUCTION

Effective feedback on cytology performance relies on navigating complex laboratory information system data, which is prone to errors and lacks flexibility. As a comprehensive solution, we used the Python programming language to create a dashboard application for screening and diagnostic quality metrics.

MATERIALS AND METHODS

Data from the 5-year period (2018-2022) were accessed. Versatile open-source Python libraries (user developed program code packages) were used from the first step of LIS data cleaning through the creation of the application. To evaluate performance, we selected 3 gynecologic metrics: the ASC/LSIL ratio, the ASC-US/ASC-H ratio, and the proportion of cytologic abnormalities in comparison to the total number of cases (abnormal rate). We also evaluated the referral rate of cytologists/cytotechnologists (CTs) and the ratio of thyroid AUS interpretations by cytopathologists (CPs). These were formed into colored graphs that showcase individual results in established, color-coded laboratory "goal," "borderline," and "attention" zones based on published reference benchmarks. A representation of the results distribution for the entire laboratory was also developed.

RESULTS

We successfully created a web-based test application that presents interactive dashboards with different interfaces for the CT, CP, and laboratory management (https://drkvcsstvn-dashboards.hf.space/app). The user can choose to view the desired quality metric, year, and the anonymized CT or CP, with an additional automatically generated written report of results.

CONCLUSIONS

Python programming proved to be an effective toolkit to ensure high-level data processing in a modular and reproducible way to create a personalized, laboratory specific cytology dashboard.

Developing public health surveillance dashboards: a scoping review on the design principles

BACKGROUND

Public Health Dashboards (PHDs) facilitate the monitoring and prediction of disease outbreaks by continuously monitoring the health status of the community. This study aimed to identify design principles and determinants for developing public health surveillance dashboards.

METHODOLOGY

This scoping review is based on Arksey and O'Malley's framework as included in JBI guidance. Four databases were used to review and present the proposed principles of designing PHDs: IEEE, PubMed, Web of Science, and Scopus. We considered articles published between January 1, 2010 and November 30, 2022. The final search of articles was done on November 30, 2022. Only articles in the English language were included. Qualitative synthesis and trend analysis were conducted.

RESULTS

Findings from sixty-seven articles out of 543 retrieved articles, which were eligible for analysis, indicate that most of the dashboards designed from 2020 onwards were at the national level for managing and monitoring COVID-19. Design principles for the public health dashboard were presented in five groups, i.e., considering aim and target users, appropriate content, interface, data analysis and presentation types, and infrastructure.

CONCLUSION

Effective and efficient use of dashboards in public health surveillance requires implementing design principles to improve the functionality of these systems in monitoring and decision-making. Considering user requirements, developing a robust infrastructure for improving data accessibility, developing, and applying Key Performance Indicators (KPIs) for data processing and reporting purposes, and designing interactive and intuitive interfaces are key for successful design and development.

Theory of radiologist interaction with instant messaging decision support tools: A sequential-explanatory study

Radiology specific clinical decision support systems (CDSS) and artificial intelligence are poorly integrated into the radiologist workflow. Current research and development efforts of radiology CDSS focus on 4 main interventions, based around exam centric time points-after image acquisition, intra-report support, post-report analysis, and radiology workflow adjacent. We review the literature surrounding CDSS tools in these time points, requirements for CDSS workflow augmentation, and technologies that support clinician to computer workflow augmentation. We develop a theory of radiologist-decision tool interaction using a sequential explanatory study design. The study consists of 2 phases, the first a quantitative survey and the second a qualitative interview study. The phase 1 survey identifies differences between average users and radiologist users in software interventions using the User Acceptance of Information Technology: Toward a Unified View (UTAUT) framework. Phase 2 semi-structured interviews provide narratives on why these differences are found. To build this theory, we propose a novel solution called Radibot-a conversational agent capable of engaging clinicians with CDSS as an assistant using existing instant messaging systems supporting hospital communications. This work contributes an understanding of how radiologist-users differ from the average user and can be utilized by software developers to increase satisfaction of CDSS tools within radiology.

Identifying and prioritizing the key performance indicators for hospital management dashboard at a national level: Viewpoint of hospital managers

Participation of main users in identifying key performance indicators (KPIs) for management dashboards contributes to their success. The aim of this study was to identify and prioritize the KPIs of hospital management dashboards from the viewpoint of hospital managers. This study was conducted on managers of public hospitals at a national level in Iran in 2020. Data were collected using a self-administrated questionnaire. The KPIs were classified into five categories, namely financial, operational, human resources, safety and quality of care, services provided to patients. A total of 234 hospital managers participated in this study. Totally, 25 KPIs were determined for the hospital management dashboard, including the patient falls rate, waiting time for patients in the emergency department, patient satisfaction, total hospital revenue, financial balance, bed occupancy rate, patients' discharge with own agreement, average length of stay, and personnel satisfaction. For designing hospital management dashboards, the domains of services provided to patients, safety and quality of care, financial resources, human resources, and operational are important from the hospital managers' viewpoint, respectively. The results of this study can be helpful for developers of business intelligence tools, such as hospital management dashboards, to visualize the most important indicators for managers.

Requirements and challenges of hospital dashboards: a systematic literature review

Background

Today, the use of data in administrative and clinical processes is quite challenging due to the large volume of data, data collection from various sources, and lack of data structure. As a data management tool, dashboards play an important role in timely visual display of critical information on key performances.

Objectives

This systematic review aimed to identify functional and non-functional requirements, as well as challenges of using dashboards in hospitals.

Methods

In this systematic review, four databases, including the Web of Science, PubMed, EMBASE, and Scopus, were searched to find relevant articles from 2000 until May 30, 2020. The final search was conducted on May 30, 2020. Data collection was performed using a data extraction form and reviewing the content of relevant studies on the potentials and challenges of dashboard implementation.

Results

Fifty-four out of 1254 retrieved articles were selected for this study based on the inclusion and exclusion criteria. The functional requirements for dashboards included reporting, reminders, customization, tracking, alert creation, and assessment of performance indicators. On the other hand, the non-functional requirements included the dashboard speed, security, ease of use, installation on different devices (e.g., PCs and laptops), integration with other systems, web-based design, inclusion of a data warehouse, being up-to-data, and use of data visualization elements based on the user’s needs. Moreover, the identified challenges were categorized into four groups: data sources, dashboard content, dashboard design, implementation, and integration in other systems at the hospital level.

Conclusion

Dashboards, by providing information in an appropriate manner, can lead to the proper use of information by users. In order for a dashboard to be effective in clinical and managerial processes, particular attention must be paid to its capabilities, and the challenges of its implementation need to be addressed.

Digital dashboards: a speech pathology case study

The introduction of electronic medical records has created vast opportunities in relation to data storage, visibility and extraction. In Allied Health the collection, storage, display and reporting of service statistics is a key opportunity to utilise the capabilities of the electronic medical record to reduce clinician time completing data entry, improve accuracy and visibility of available data and maximise opportunities to view and utilise service statistic information in clinical and operational decision making. This case study describes service statistic capture and extraction for a speech pathology department, pre- and post- the introduction of a digital dashboard. A new Allied Health digital dashboard was created via clinicians and informaticians working collaboratively to define service delivery elements for data extraction and design dashboard functionality. Descriptive comparison of data capture pre- and post- dashboard implementation was undertaken. The integration of service statistic information into a digital dashboard was found to support service statistic reporting, improve ease of access, and provide greater visibility and timeliness of service information.

Developing dashboards for performance improvement in cytopathology

INTRODUCTION

Cytopathology has well-defined and objective quality metrics for monitoring the performance of cytopathologists (CPs) and cytotechnologists (CTs). We transformed these metrics into dashboards for real-time visualization and on-demand feedback.

METHODS

Dashboards were constructed with data from the previous 10 calendar years using the software Tableau. The dashboards for CPs were designed to display 2 gynecologic metrics and 1 nongynecologic metric: the ASCUS:SIL ratio, the percentage of high-risk human papillomavirus (HPV)-positive ASCUS interpretations (HPV+ ASCUS rate), and the proportion of AUS/FLUS thyroid interpretations. CT dashboards were designed to include these plus 2 others: the percentage of Papanicolaou tests referred for CP review and the percentage of Papanicolaou tests interpreted as unsatisfactory. Established professional benchmarks or standard deviations were used to set color-coded "goal," "borderline," and "attention" zones.

RESULTS

Personal dashboards were successfully developed and implemented for CPs and CTs in the laboratory, with results that are automatically updated every week, requiring minimal curation. Each CP and CT has a unique link that allows them access to their results at any time. Color-coded displays show the individual their quality metrics over the past 10 years, with a snapshot of data from the past 3 months. The laboratory director has a unique link that allows the director access to results for each individual and the laboratory in aggregate.

CONCLUSIONS

Personalized dashboards enable individuals to access their performance metrics on demand and examine recent performance as well as patterns over time. This facilitates self-motivation to improve performance and adhere to professional benchmarks.

Requirements for a Dashboard to Support Quality Improvement Teams in Pain Management

Pain management is often considered lower priority than many other aspects of health management in hospitals. However, there is potential for Quality Improvement (QI) teams to improve pain management by visualising and exploring pain data sets. Although dashboards are already used by QI teams in hospitals, there is limited evidence of teams accessing visualisations to support their decision making. This study aims to identify the needs of the QI team in a UK Critical Care Unit (CCU) and develop dashboards that visualise longitudinal data on the efficacy of patient pain management to assist the team in making informed decisions to improve pain management within the CCU. This research is based on an analysis of transcripts of interviews with healthcare professionals with a variety of roles in the CCU and their evaluation of probes. We identified two key uses of pain data: direct patient care (focusing on individual patient data) and QI (aggregating data across the CCU and over time); in this paper, we focus on the QI role. We have identified how CCU staff currently interpret information and determine what supplementary information can better inform their decision making and support sensemaking. From these, a set of data visualisations has been proposed, for integration with the hospital electronic health record. These visualisations are being iteratively refined in collaboration with CCU staff and technical staff responsible for maintaining the electronic health record. The paper presents user requirements for QI in pain management and a set of visualisations, including the design rationale behind the various methods proposed for visualising and exploring pain data using dashboards.

Magnetic resonance imaging quality control, quality assurance and quality improvement

Quality in MR imaging is a comprehensive process that encompasses scanner performance, clinical processes for efficient scanning and reporting, as well as data-driven improvement involving measurement of key performance indicators. In this paper, the authors review this entire process. This article provides a framework for establishing a successful MR quality program. The collective experiences of the authors across a spectrum of pediatric hospitals is summarized here.

Active Reprioritization of the Reading Worklist Using Artificial Intelligence Has a Beneficial Effect on the Turnaround Time for Interpretation of Head CT with Intracranial Hemorrhage

Purpose

To determine how to optimize the delivery of machine learning techniques in a clinical setting to detect intracranial hemorrhage (ICH) on non-contrast-enhanced CT images to radiologists to improve workflow.

Materials and Methods

In this study, a commercially available machine learning algorithm that flags abnormal noncontrast CT examinations for ICH was implemented in a busy academic neuroradiology practice between September 2017 and March 2019. The algorithm was introduced in three phases: (a) as a "pop-up" widget on ancillary monitors, (b) as a marked examination in reading worklists, and (c) as a marked examination for reprioritization based on the presence of the flag. A statistical approach, which was based on a queuing theory, was implemented to assess the impact of each intervention on queue-adjusted wait and turnaround time compared with historical controls.

Results

Notification with a widget or flagging the examination had no effect on queue-adjusted image wait (P > .99) or turnaround time (P = .6). However, a reduction in queue-adjusted wait time was observed between negative (15.45 minutes; 95% CI: 15.07, 15.38) and positive (12.02 minutes; 95% CI: 11.06, 12.97; P < .0001) artificial intelligence-detected ICH examinations with reprioritization. Reduced wait time was present for all order classes but was greatest for examinations ordered as routine for both inpatients and outpatients because of their low priority.

Conclusion

The approach used to present flags from artificial intelligence and machine learning algorithms to the radiologist can reduce image wait time and turnaround times.© RSNA, 2021See also the commentary by O'Connor and Bhalla in this issue.

Informatics and the Challenge of Determinism

Motivation: There is a paradox at the heart of informatics where practical implementation generally fails to understand the socio-technical impact of novel technologies and disruptive innovation when adopted in ‘real-world’ systems. This phenomenon, termed technological determinism, is manifested in a time-lag between the adoption of novel technologies and an understanding of the underlying theory which develops following research into their adoption. Methods: We consider informatics theory as it relates to: social informatics and how humans’ function in society, the relationship between society and technology, information systems, information systems design, and human–computer interactions. The challenges posed by novel technologies and disruptive innovation are considered as they relate to information systems and information systems design. Open research questions with directions for future research are discussed with an introduction to and our proposed approach to socio-technical information system design. Significance: We conclude that the adoption of disruptive innovation presents both opportunities and threats for all stakeholders in computerised systems. However, determinism is a topic requiring research to generate a suitable level of understanding and technological determinism remains a significant challenge.

Assessing the Training Costs and Work of Diagnostic Radiology Residents Using Key Performance Indicators - An Observational Study

RATIONALE AND OBJECTIVES

To quantify the costs and work of diagnostic radiology (DR) residents using the radiology key performance indicator turn-around time (TAT) as the outcome measure.

MATERIALS AND METHODS

In an Institutional Review Board-approved study, the annual cost of a DR resident was determined using salary, benefits, and a cost allocation of faculty effort. The volume of cases reported in the 2015-16 academic year and median and interquartile range (IQR) TAT for a trainee preliminary (Complete to Prelim, C-P) or an attending final (Complete to Final, C-F) radiology report were measured and stratified by time of day and patient location. Wilcoxon rank-sum tests were used (significance, p values < 0.05).

RESULTS

The annual cost of a DR resident was $99,109, 34% greater than direct salary/benefits and 27% of the direct salary/benefits cost of an attending. The total per minute cost of rendering care was $4.36 with both trainee ($0.70/minute) and faculty ($3.66/minute). Residents participated in 139,084/235,417 (59%) imaging studies. The C-P TAT was 74 (IQR, 27-180) minutes compared to 51 (IQR, 18-129) minutes C-F TAT of faculty working alone and C-F TAT of 213 (IQR, 71-469) minutes with a resident (p < 0.001). The C-P TAT vs C-F TAT between 4 pm-9 am and weekends with residents is 44 (IQR, 18-119) minutes vs 60 (IQR, 18-179) minutes without.

CONCLUSION

The cost of training DR residents exceeds the salary and benefits allocated to their training. Residents increase the absolute professional labor cost of caring for a patient. Overall TAT is slower with residents but the care delivered by residents after-hours is faster.

Development, implementation and preliminary evaluation of clinical dashboards in a department of anesthesia

Clinical dashboards summarize indicators of high-volume patient data in a concise, user-friendly visual format. There are few studies of the use of dashboards to improve professional practice in anesthesiology. The objective of the present study was to describe the user-centered development, implementation and preliminary evaluation of clinical dashboards dealing with anesthesia unit management and quality assessment in a French university medical center. User needs and technical requirements were identified in end user interviews and then synthesized. Several representations were then developed (according to good visualization practice) and submitted to end users for appraisal. Lastly, dashboards were implemented and made accessible for everyday use via the medical center’s network. After a period of use, end user feedback on the dashboard platform was collected as a system usability score (range 0 to 100). Seventeen themes (corresponding to 29 questions and 42 indicators) were identified. After prioritization and feasibility assessment, 10 dashboards were ultimately implemented and deployed. The dashboards variously addressed the unit’s overall activity, compliance with guidelines on intraoperative hemodynamics, ventilation and monitoring, and documentation of the anesthesia procedure. The mean (standard deviation) system usability score was 82.6 (11.5), which corresponded to excellent usability. We developed clinical dashboards for a university medical center’s anesthesia units. The dashboards’ deployment was well received by the center’s anesthesiologists. The dashboards’ impact on activity and practice after several months of use will now have to be assessed.

The impact of home care nurses' numeracy and graph literacy on comprehension of visual display information: implications for dashboard design

Objective

To explore home care nurses' numeracy and graph literacy and their relationship to comprehension of visualized data.

Materials and Methods

A multifactorial experimental design using online survey software. Nurses were recruited from 2 Medicare-certified home health agencies. Numeracy and graph literacy were measured using validated scales. Nurses were randomized to 1 of 4 experimental conditions. Each condition displayed data for 1 of 4 quality indicators, in 1 of 4 different visualized formats (bar graph, line graph, spider graph, table). A mixed linear model measured the impact of numeracy, graph literacy, and display format on data understanding.

Results

In all, 195 nurses took part in the study. They were slightly more numerate and graph literate than the general population. Overall, nurses understood information presented in bar graphs most easily (88% correct), followed by tables (81% correct), line graphs (77% correct), and spider graphs (41% correct). Individuals with low numeracy and low graph literacy had poorer comprehension of information displayed across all formats. High graph literacy appeared to enhance comprehension of data regardless of numeracy capabilities.

Discussion and Conclusion

Clinical dashboards are increasingly used to provide information to clinicians in visualized format, under the assumption that visual display reduces cognitive workload. Results of this study suggest that nurses' comprehension of visualized information is influenced by their numeracy, graph literacy, and the display format of the data. Individual differences in numeracy and graph literacy skills need to be taken into account when designing dashboard technology.

Using Feedback Intervention Theory to Guide Clinical Dashboard Design

The provision of feedback to clinicians and organizations on the quality of care they provide is thought to influence clinician and organizational behavior leading to care improvements. Clinical Dashboards use data visualization techniques to provide feedback to individuals on their performance compared to quality metrics. In this paper we outline a theoretical approach to the design of a clinical dashboard; Feedback Intervention Theory (FIT). Priorities for feedback were identified using focus groups with home care nurses (n=61). Individual variation in graph literacy and numeracy among nurses and their ability to comprehend visualized data displays were evaluated using an online survey. The results from the focus group and survey were used to inform a prototype dashboard which was evaluated for usability with a separate sample of home care nurses. FIT provided a theoretical base for the dashboard design to ensure feedback that should positively impact clinician behavior.

Developing a hospital-wide quality and safety dashboard: a qualitative research study

Background

Several countries have national policies and programmes requiring hospitals to use quality and safety (QS) indicators. To present an overview of these indicators, hospital-wide QS (HWQS) dashboards are designed. There is little evidence how these dashboards are developed. The challenges faced to develop these dashboards in Dutch hospitals were retrospectively studied.

Methods

24 focus group interviews were conducted: 12 with hospital managers (n=25; 39.7%) and 12 support staff (n=38; 60.3%) in 12 of the largest Dutch hospitals. Open and axial codings were applied consecutively to analyse the data collected.

Results

A heuristic tool for the general development process for HWQS dashboards containing five phases was identified. In phase 1, hospitals make inventories to determine the available data and focus too much on quantitative data relevant for accountability. In phase 2, hospitals develop dashboard content by translating data into meaningful indicators for different users, which is not easy due to differing demands. In phase 3, hospitals search for layouts that depict the dashboard content suited for users with different cognitive abilities and analytical skills. In phase 4, hospitals try to integrate dashboards into organisational structures to ensure that data are systematically reviewed and acted on. In phase 5, hospitals want to improve the flexibility of their dashboards to make this adaptable under differing circumstances.

Conclusion

The literature on dashboards addresses the technical and content aspects of dashboards, but overlooks the organisational development process. This study shows how technical and organisational aspects are relevant in development processes.

An Electronic Dashboard to Monitor Patient Flow at the Johns Hopkins Hospital: Communication of Key Performance Indicators Using the Donabedian Model

Efforts to monitoring and managing hospital capacity depend on the ability to extract relevant time-stamped data from electronic medical records and other information technologies. However, the various characterizations of patient flow, cohort decisions, sub-processes, and the diverse stakeholders requiring data visibility create further overlying complexity. We use the Donabedian model to prioritize patient flow metrics and build an electronic dashboard for enabling communication. Ten metrics were identified as key indicators including outcome (length of stay, 30-day readmission, operating room exit delays, capacity-related diversions), process (timely inpatient unit discharge, emergency department disposition), and structural metrics (occupancy, discharge volume, boarding, bed assignation duration). Dashboard users provided real-life examples of how the tool is assisting capacity improvement efforts, and user traffic data revealed an uptrend in dashboard utilization from May to October 2017 (26 to 148 views per month, respectively). Our main contributions are twofold. The former being the results and methods for selecting key performance indicators for a unit, department, and across the entire hospital (i.e., separating signal from noise). The latter being an electronic dashboard deployed and used at The Johns Hopkins Hospital to visualize these ten metrics and communicate systematically to hospital stakeholders. Integration of diverse information technology may create further opportunities for improved hospital capacity.

Information architecture for a patient-specific dashboard in head and neck tumor boards

PURPOSE

Overcoming the flaws of current data management conditions in head and neck oncology could enable integrated information systems specifically tailored to the needs of medical experts in a tumor board meeting. Clinical dashboards are a promising method to assist various aspects of the decision-making process in such cognitively demanding scenarios. However, in order to provide extensive and intuitive assistance to the participating physicians, the design and development of such a system have to be user-centric. To accomplish this task, conceptual methods need to be performed prior to the technical development and integration stages.

METHODS

We have conducted a qualitative survey including eight clinical experts with different levels of expertise in the field of head and neck oncology. According to the principles of information architecture, the survey focused on the identification and causal interconnection of necessary metrics for information assessment in the tumor board.

RESULTS

Based on the feedback by the clinical experts, we have constructed a detailed map of the required information items for a tumor board dashboard in head and neck oncology. Furthermore, we have identified three distinct groups of metrics (patient, disease and therapy metrics) as well as specific recommendations for their structural and graphical implementation.

CONCLUSION

By using the information architecture, we were able to gather valuable feedback about the requirements and cognitive processes of the tumor board members. Those insights have helped us to develop a dashboard application that closely adapts to the specified needs and characteristics, and thus is primarily user-centric.

A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance

Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

Evaluation of Effective Dashboards: Key Concepts and Criteria

OBJECTIVE

The aim of this study is to offer appropriate criteria to evaluate effective dashboards for healthcare organizations.

METHOD

In a Delphi study, a team of information technology consultants were asked to determine a set of user interface requirements for evaluating, building or selecting the dashboard. In the first round, a list of main features or criteria to be used was determined based on the panel's rating,.

RESULTS

In this study, it was revealed that a set of key criteria for evaluating the dashboards can be used for all types of dashboards. These criteria were classified into 7 main categories including user customization, knowledge discovery, security, information delivery, alerting, visual design, and integration and system connectivity.

CONCLUSION

Choosing good criteria for selecting effective dashboards for healthcare organizations is very critical because these organizations follow a data-intensive and technology-driven environment. This study revealed the importance of key criteria which can guarantee development of an evaluation checklist.

Concept and implementation of a study dashboard module for a continuous monitoring of trial recruitment and documentation

BACKGROUND

The difficulty of managing patient recruitment and documentation for clinical trials prompts a demand for instruments for closely monitoring these critical but unpredictable processes. Increasingly adopted Electronic Data Capture (EDC) applications provide novel opportunities to reutilize stored information for an efficient management of traceable trial workflows. In related clinical and administrative settings, so-called digital dashboards that continuously visualize time-dependent parameters have recently met a growing acceptance. To investigate the technical feasibility of a study dashboard for monitoring the progress of patient recruitment and trial documentation, we set out to develop a propositional prototype in the form of a separate software module.

METHODS

After narrowing down functional requirements in semi-structured interviews with study coordinators, we analyzed available interfaces of a locally deployed EDC application, and designed the prototypical study dashboard based on previous findings. The module thereby leveraged a standardized export format in order to extract and import relevant trial data into a clinical data warehouse. Web-based reporting tools then facilitated the definition of diverse views, including diagrams of the progress of patient accrual and form completion at different granularity levels. To estimate the utility of the dashboard and its compatibility with current workflows, we interviewed study coordinators after a demonstration of sample outputs from ongoing trials.

RESULTS

The employed tools promoted a rapid development. Displays of the implemented dashboard are organized around an entry page that integrates key metrics for available studies, and which links to more detailed information such as study-specific enrollment per center. The interviewed experts commented that the included graphical summaries appeared suitable for detecting that something was generally amiss, although practical remedies would mostly depend on additional information such as access to the original patient-specific data. The dependency on a separate application was seen as a downside. Interestingly, the prospective users warned that in some situations knowledge of specific accrual statistics might undermine blinding in a subtle yet intricate fashion, so ignorance of certain patient features was seen as sometimes preferable for reproducibility.

DISCUSSION

Our proposed study dashboard graphically recaps key progress indicators of patient accrual and trial documentation. The modular implementation illustrates the technical feasibility of the approach. The use of a study dashboard might introduce certain technical requirements as well as subtle interpretative complexities, which may have to be weighed against potential efficiency gains.

A novel concept for integrating and delivering health information using a comprehensive digital dashboard: An analysis of healthcare professionals' intention to adopt a new system and the trend of its real usage

OBJECTIVE

To introduce a new concept of medical dashboard system called BESTBoard. Such a system was implemented in all wards in a tertiary academic hospital to explore the development process, core designs, functions, usability and feasibility.

METHODS

The task-force team made user interface designs for 6 months based on a need analysis. Hardware configuration and software development was carried out for 3 months. We conducted a survey of 383 physicians and nurses to determine the usability and feasibility of the system.

RESULTS

In March 2012, the system was installed in all wards, including the intensive care units, emergency rooms, operation rooms, and even delivery rooms. Healthcare professionals had access to all information of EHRs optimized for a large 55-inch touchscreen. The satisfaction rate of BESTBoard users was high, with a mean of 3.3 points. Voluntary users tended to consider BESTBoard as a good system that is useful for team round visits, interdisciplinary team approach, and collecting the status of the hospital rooms. Elderly users didn't tend to think of BESTBoard as a useful tool for interdisciplinary team approach and collecting the status of the hospital rooms. Greater expectations regarding work performance affected the users' attitudes positively. A positive attitude toward using the system resulted in consistent real usage and health care professionals' satisfaction with the new dashboard system.

CONCLUSIONS

A new concept of hospital dashboard system proved to be feasible and useful in delivering health information to healthcare professionals. A positive attitude and an expectation regarding work performance were important factors for intention to use the system. This finding can serve for developing new systems to present health information effectively. Further studies will be needed to evaluate the extent to which BESTBoard can have a positive impact on clinical care outcomes and work performance.

Interface design recommendations for computerised clinical audit and feedback: Hybrid usability evidence from a research-led system

BACKGROUND

Audit and Feedback (A&F) is a widely used quality improvement technique that measures clinicians' clinical performance and reports it back to them. Computerised A&F (e-A&F) system interfaces may consist of four key components: (1) Summaries of clinical performance; (2) Patient lists; (3) Patient-level data; (4) Recommended actions. There is a lack of evidence regarding how to best design e-A&F interfaces; establishing such evidence is key to maximising usability, and in turn improving patient safety.

AIM

To evaluate the usability of a novel theoretically-informed and research-led e-A&F system for primary care (the Performance Improvement plaN GeneratoR: PINGR).

OBJECTIVES

(1) Describe PINGR's design, rationale and theoretical basis; (2) Identify usability issues with PINGR; (3) Understand how these issues may interfere with the cognitive goals of end-users; (4) Translate the issues into recommendations for the user-centred design of e-A&F systems.

METHODS

Eight experienced health system evaluators performed a usability inspection using an innovative hybrid approach consisting of five stages: (1) Development of representative user tasks, Goals, and Actions; (2) Combining Heuristic Evaluation and Cognitive Walkthrough methods into a single protocol to identify usability issues; (3) Consolidation of issues; (4) Severity rating of consolidated issues; (5) Analysis of issues according to usability heuristics, interface components, and Goal-Action structure.

RESULTS

A final list of 47 issues were categorised into 8 heuristic themes. The most error-prone heuristics were 'Consistency and standards' (13 usability issues; 28% of the total) and 'Match between system and real world' (n=10, 21%). The recommended actions component of the PINGR interface had the most usability issues (n=21, 45%), followed by patient-level data (n=5, 11%), patient lists (n=4, 9%), and summaries of clinical performance (n=4, 9%). The most error-prone Actions across all user Goals were: (1) Patient selection from a list; (2) Data identification from a figure (both population-level and patient-level); (3) Disagreement with a system recommendation.

CONCLUSIONS

By contextualising our findings within the wider literature on health information system usability, we provide recommendations for the design of e-A&F system interfaces relating to their four key components, in addition to how they may be integrated within a system.

From Information Management to Information Visualization: Development of Radiology Dashboards

OBJECTIVE

The development and implementation of a dashboard of medical imaging department (MID) performance indicators.

METHOD

Several articles discussing performance measures of imaging departments were searched for this study. All the related measures were extracted. Then, a panel of imaging experts were asked to rate these measures with an open ended question to seek further potential indicators. A second round was performed to confirm the performance rating. The indicators and their ratings were then reviewed by an executive panel. Based on the final panel's rating, a list of indicators to be used was developed. A team of information technology consultants were asked to determine a set of user interface requirements for the building of the dashboard. In the first round, based on the panel's rating, a list of main features or requirements to be used was determined. Next, Qlikview was utilized to implement the dashboard to visualize a set of selected KPI metrics. Finally, an evaluation of the dashboard was performed.

RESULTS

92 MID indicators were identified. On top of this, 53 main user interface requirements to build of the prototype of dashboard were determined. Then, the project team successfully implemented a prototype of radiology management dashboards into study site. The visual display that was designed was rated highly by users.

CONCLUSION

To develop a dashboard, management of information is essential. It is recommended that a quality map be designed for the MID. It can be used to specify the sequence of activities, their related indicators and required data for calculating these indicators. To achieve both an effective dashboard and a comprehensive view of operations, it is necessary to design a data warehouse for gathering data from a variety of systems. Utilizing interoperability standards for exchanging data among different systems can be also effective in this regard.

Using Arden Syntax for the creation of a multi-patient surveillance dashboard

OBJECTIVE

Most practically deployed Arden-Syntax-based clinical decision support (CDS) modules process data from individual patients. The specification of Arden Syntax, however, would in principle also support multi-patient CDS. The patient data management system (PDMS) at our local intensive care units does not natively support patient overviews from customizable CDS routines, but local physicians indicated a demand for multi-patient tabular overviews of important clinical parameters such as key laboratory measurements. As our PDMS installation provides Arden Syntax support, we set out to explore the capability of Arden Syntax for multi-patient CDS by implementing a prototypical dashboard for visualizing laboratory findings from patient sets.

METHODS AND MATERIAL

Our implementation leveraged the object data type, supported by later versions of Arden, which turned out to be serviceable for representing complex input data from several patients. For our prototype, we designed a modularized architecture that separates the definition of technical operations, in particular the control of the patient context, from the actual clinical knowledge. Individual Medical Logic Modules (MLMs) for processing single patient attributes could then be developed according to well-tried Arden Syntax conventions.

RESULTS

We successfully implemented a working dashboard prototype entirely in Arden Syntax. The architecture consists of a controller MLM to handle the patient context, a presenter MLM to generate a dashboard view, and a set of traditional MLMs containing the clinical decision logic. Our prototype could be integrated into the graphical user interface of the local PDMS. We observed that with realistic input data the average execution time of about 200ms for generating dashboard views attained applicable performance.

CONCLUSION

Our study demonstrated the general feasibility of creating multi-patient CDS routines in Arden Syntax. We believe that our prototypical dashboard also suggests that such implementations can be relatively easy, and may simultaneously hold promise for sharing dashboards between institutions and reusing elementary components for additional dashboards.

A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard

INTRODUCTION

management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard.

METHODS

the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified.

RESULTS

the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers.

CONCLUSION

the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process.

The effectiveness of service delivery initiatives at improving patients' waiting times in clinical radiology departments: a systematic review

We reviewed the literature for the impact of service delivery initiatives (SDIs) on patients' waiting times within radiology departments. We searched MEDLINE, EMBASE, CINAHL, INSPEC and The Cochrane Library for relevant articles published between 1995 and February, 2013. The Cochrane EPOC risk of bias tool was used to assess the risk of bias on studies that met specified design criteria. Fifty-seven studies met the inclusion criteria. The types of SDI implemented included extended scope practice (ESP, three studies), quality management (12 studies), productivity-enhancing technologies (PETs, 29 studies), multiple interventions (11 studies), outsourcing and pay-for-performance (one study each). The uncontrolled pre- and post-intervention and the post-intervention designs were used in 54 (95%) of the studies. The reporting quality was poor: many of the studies did not test and/or report the statistical significance of their results. The studies were highly heterogeneous, therefore meta-analysis was inappropriate. The following type of SDIs showed promising results: extended scope practice; quality management methodologies including Six Sigma, Lean methodology, and continuous quality improvement; productivity-enhancing technologies including speech recognition reporting, teleradiology and computerised physician order entry systems. We have suggested improved study design and the mapping of the definitions of patient waiting times in radiology to generic timelines as a starting point for moving towards a situation where it becomes less restrictive to compare and/or pool the results of future studies in a meta-analysis.

Building blocks for a clinical imaging informatics environment

Over the past 20 years, imaging informatics has been driven by the widespread adoption of radiology information and picture archiving and communication and speech recognition systems. These three clinical information systems are commonplace and are intuitive to most radiologists as they replicate familiar paper and film workflow. So what is next? There is a surge of innovation in imaging informatics around advanced workflow, search, electronic medical record aggregation, dashboarding, and analytics tools for quality measures (Nance et al., AJR Am J Roentgenol 200:1064-1070, 2013). The challenge lies in not having to rebuild the technological wheel for each of these new applications but instead attempt to share common components through open standards and modern development techniques. The next generation of applications will be built with moving parts that work together to satisfy advanced use cases without replicating databases and without requiring fragile, intense synchronization from clinical systems. The purpose of this paper is to identify building blocks that can position a practice to be able to quickly innovate when addressing clinical, educational, and research-related problems. This paper is the result of identifying common components in the construction of over two dozen clinical informatics projects developed at the University of Maryland Radiology Informatics Research Laboratory. The systems outlined are intended as a mere foundation rather than an exhaustive list of possible extensions.

A design protocol to develop radiology dashboards

Aim:

The main objective of this descriptive and development research was to introduce a design protocol to develop radiology dashboards.

Material and methods:

The first step was to determine key performance indicators for radiology department. The second step was to determine required infrastructure for implementation of radiology dashboards. Infrastructure was extracted from both data and technology perspectives. The third step was to determine main features of the radiology dashboards. The fourth step was to determine the key criteria for evaluating the dashboards. In all these steps, non-probability sampling methods including convenience and purposive were employed and sample size determined based on a persuasion model.

Results:

Results showed that there are 92 KPIs, 10 main features for designing dashboards and 53 key criteria for dashboards evaluation. As well as, a Prototype of radiology management dashboards in four aspects including services, clients, personnel and cost-income were implemented and evaluated. Applying such dashboards could help managers to enhance performance, productivity and quality of services in radiology department.

Dashboards for improving patient care: review of the literature

AIM

This review aimed to provide a comprehensive overview of the current state of evidence for the use of clinical and quality dashboards in health care environments.

METHODS

A literature search was performed for the dates 1996-2012 on CINAHL, Medline, Embase, Cochrane Library, PsychInfo, Science Direct and ACM Digital Library. A citation search and a hand search of relevant papers were also conducted.

RESULTS

One hundred and twenty two full text papers were retrieved of which 11 were included in the review. There was considerable heterogeneity in implementation setting, dashboard users and indicators used. There was evidence that in contexts where dashboards were easily accessible to clinicians (such as in the form of a screen saver) their use was associated with improved care processes and patient outcomes.

CONCLUSION

There is some evidence that implementing clinical and/or quality dashboards that provide immediate access to information for clinicians can improve adherence to quality guidelines and may help improve patient outcomes. However, further high quality detailed research studies need to be conducted to obtain evidence of their efficacy and establish guidelines for their design.

How Budget Issues Affect Technologists

Departmental budgets create active issues that positively or negatively affect the technologist's everyday practice. This literature review was conducted to determine if technologists' quality of care and radiation safety were at risk and if examination productivity was affected. Midwestern State University's library database was searched for the most recent literature concerning these issues using CINAHL, Academic Search Complete, and MEDLINE databases. The literature used for this review found that a department with a minimalist budget negatively affected technologists' occupational attitude and job satisfaction because of budget cuts and lack of communication between management and employees; this adversely affected the quality of care given. Radiation protection practices were noncompliant in some facilities with a poor budget because educational programs could not be funded and adequate shielding resources were not provided, which increased the risk of unnecessary radiation exposure to personnel and patients. In contrast, a department with generous funds that had continuing education programs available showed compliance with radiation protection. Furthermore, departments with a strong budget that included purchasing a picture archiving computer system created a more simplistic workflow, increased patient throughput, and increased examination productivity. It was found that budgets should be correctly distributed in order to create optimal occupational success for a department because working under a minimalist budget ultimately affects many aspects of technologists' day-to-day practice. Because of the age of the most current articles, a need to conduct research focusing on recent changes affecting budgetary concerns has been shown.

Improvement in reporting skills of radiology residents with a structured reporting curriculum

RATIONALE AND OBJECTIVES

Radiology residents must acquire dictation and reporting skills to meet Accreditation Council for Graduate Medical Examination requirements and provide optimal patient care. Historically, these skills have been taught informally and vary between institutions and among radiologists. A structured curriculum improves resident report quality when using a quantitative grading scheme. This study describes the implementation of such a curriculum and evaluates its utility in tracking resident progress.

MATERIALS AND METHODS

We implemented a three-stage reporting curriculum in our diagnostic radiology residency program in 2009. Stages 1 and 2 involve instruction and formative feedback composed of suggestions for improvement in a 360° format from faculty, peers, and others within the resident's sphere of influence. The third stage involves individual, biannual, written feedback with scored reports specifically assessing four categories: succinctness, spelling/grammar, clarity, and responsible referral. Biannual scores were collected from 2009 to 2013, sorted by year of residency training (R1 to R4), and average training level scores were statistically compared.

RESULTS

Review of 1500 reports over a 4-year period yielded a total of 153 scores: 54, 36, 29, and 34 from R1, R2, R3, and R4 residents, respectively. The mean (standard deviation) scores for R1, R2, R3, and R4 residents were 10.20 (1.06), 10.25 (0.81), 10.5 (0.74), and 10.75 (0.69), respectively. Post hoc analysis identified significant differences between R1 and R4 residents (P = .012) and R2 and R4 residents (P = .009).

CONCLUSIONS

Residents' reporting scores showed significant improvement over the course of their residency training. This indicates that there may be a benefit in using an organized reporting curriculum to track resident progress in producing reports that may improve patient care.

The future of the radiology information system

OBJECTIVE

Today in the hospital setting, several functions of the radiology information system (RIS), including order entry, patient registration, report repository, and the physician directory, have moved to enterprise electronic medical records. Some observers might conclude that the RIS is going away. In this article, we contend that because of the maturity of the RIS market compared with other areas of the health care enterprise, radiology has a unique opportunity to innovate.

CONCLUSION

While most of the hospital enterprise spends the next several years going through the digital transformation converting from paper to a digital format, radiology can leap ahead in its use of analytics and information technology. This article presents a summary of new RIS functions still maturing and open to innovation in the RIS market.

Realizing digital signatures for medical imaging and reporting in a PACS environment

According to Taiwan's legislation pertaining to the protection of electronic data, the creators of electronic medical records (EMR) are solely responsible for the security of EMR. However, actual implementations that fulfill the security standards and requirements for electronic medical record systems are still lacking. Most EMR created from picture archive and communication system are not considered secure, as security protection mechanisms have not yet been granted legal status. This paper describes the details of establishing a digital signature system using Taiwan health professional cards. A digital signature system has been included to ensure quality assurance (QA) operations are controlled by technicians, and reporting capabilities have been provided for radiologist. Six imaging modalities and eight types of radiology reports have also been included in the system. Results indicate that the process of creating QA signatures does not have an adverse effect on the workflow of the facility, requiring less time for the signing and verification of radiology reports. This system has already been used routinely online in a real clinical setting for more than 2 years.

Informatics in radiology: Measuring and improving quality in radiology: meeting the challenge with informatics

Quality is becoming a critical issue for radiology. Measuring and improving quality is essential not only to ensure optimum effectiveness of care and comply with increasing regulatory requirements, but also to combat current trends leading to commoditization of radiology services. A key challenge to implementing quality improvement programs is to develop methods to collect knowledge related to quality care and to deliver that knowledge to practitioners at the point of care. There are many dimensions to quality in radiology that need to be measured, monitored, and improved, including examination appropriateness, procedure protocol, accuracy of interpretation, communication of imaging results, and measuring and monitoring performance improvement in quality, safety, and efficiency. Informatics provides the key technologies that can enable radiologists to measure and improve quality. However, few institutions recognize the opportunities that informatics methods provide to improve safety and quality. The information technology infrastructure in most hospitals is limited, and they have suboptimal adoption of informatics techniques. Institutions can tackle the challenges of assessing and improving quality in radiology by means of informatics.

Empirical investigation of radiologists' priorities for PACS selection: an analytical hierarchy process approach

Picture archiving and communication systems (PACS) are being widely adopted in radiology practice. The objective of this study was to find radiologists' perspective on the relative importance of the required features when selecting or developing a PACS. Important features for PACS were identified based on the literature and consultation/interviews with radiologists. These features were categorized and organized into a logical hierarchy consisting of the main dimensions and sub-dimensions. An online survey was conducted to obtain data from 58 radiologists about their relative preferences. Analytical hierarchy process methodology was used to determine the relative priority weights for different dimensions along with the consistency of responses. System continuity and functionality was found to be the most important dimension, followed by system performance and architecture, user interface for workflow management, user interface for image manipulation, and display quality. Among the sub-dimensions, the top two features were: security, backup, and downtime prevention; and voice recognition, transcription, and reporting. Structured reporting was also given very high priority. The results point to the dimensions that can be critical discriminators between different PACS and highlight the importance of faster integration of the emerging developments in radiology into PACS.

Email notification combined with off site signing substantially reduces resident approval to faculty verification time

RATIONALE AND OBJECTIVES

Attending radiologist signature time (AST) is a variable and modifiable component of overall report turnaround time. Delays in finalized reports have potential to undermine radiologists' value as consultants and adversely affect patient care. This study was performed to evaluate the impact of notebook computer distribution and daily automated e-mail notification on reducing AST.

MATERIALS AND METHODS

Two simultaneous interventions were initiated in the authors' radiology department in February 2010. These included the distribution of a notebook computer with preloaded software for each attending radiologist to sign radiology reports and daily automated e-mail notifications for unsigned reports. The digital dictation system archive and the radiology information system were queried for all radiology reports produced from January 2009 through August 2010. The time between resident approval and attending radiologist signature before and after the intervention was analyzed. Potential unintended "side effects" of the intervention were also studied.

RESULTS

Resident-authored reports were signed, on average, 2.53 hours sooner after the intervention. This represented a highly significant (P = .003) decrease in AST with all else held equal. Postintervention reports were authored by residents at the same rate (about 70%). An unintended "side effect" was that attending radiologists were less likely to make changes to resident-authored reports after the intervention.

CONCLUSIONS

E-mail notification combined with offsite signing can reduce AST substantially. Notebook computers with preloaded software streamline the process of accessing, editing, and signing reports. The observed decrease in AST reflects a positive change in the timeliness of report signature.

Using PACS audit data for process improvement

Today, all types of data are used in various ways to provide useful information. PACS Audit data have not been typically used as a data source although it includes information that can be used for various purposes such as process improvement (PI). In a typical radiology workflow, examinations do not show up on a radiologist's unread worklist until the examination has been verified. An issue with clinical access to radiology reports was determined to be partly due to delays in the verification step. A PI goal was created to reduce this wait time. PACS audit data were mined using an in-house application to provide workflow time span information, and the particular span from arrived to verified was measured. The report also allowed specific examinations and users to be identified, and these data were used as a PI educational tool. The end result was a dramatic reduction in examinations taking longer than 1 h to be verified which reduced the time for report production and enhanced patient care.

Optimizing the pathology workstation "cockpit": Challenges and solutions

The 21(st) century has brought numerous changes to the clinical reading (i.e., image or virtual pathology slide interpretation) environment of pathologists and it will continue to change even more dramatically as information and communication technologies (ICTs) become more widespread in the integrated healthcare enterprise. The extent to which these changes impact the practicing pathologist differ as a function of the technology under consideration, but digital "virtual slides" and the viewing of images on computer monitors instead of glass slides through a microscope clearly represents a significant change in the way that pathologists extract information from these images and render diagnostic decisions. One of the major challenges facing pathologists in this new era is how to best optimize the pathology workstation, the reading environment and the new and varied types of information available in order to ensure efficient and accurate processing of this information. Although workstations can be stand-alone units with images imported via external storage devices, this scenario is becoming less common as pathology departments connect to information highways within their hospitals and to external sites. Picture Archiving and Communications systems are no longer confined to radiology departments but are serving the entire integrated healthcare enterprise, including pathology. In radiology, the workstation is often referred to as the "cockpit" with a "digital dashboard" and the reading room as the "control room." Although pathology has yet to "go digital" to the extent that radiology has, lessons derived from radiology reading "cockpits" can be quite valuable in setting up the digital pathology reading room. In this article, we describe the concept of the digital dashboard and provide some recent examples of informatics-based applications that have been shown to improve the workflow and quality in digital reading environments.

Augmenting the impact of technology adoption with financial incentive to improve radiology report signature times

PURPOSE

Radiology report signature time (ST) can be a substantial component of total report turnaround time. Poor turnaround time resulting from lengthy ST can adversely affect patient care. The combination of technology adoption with financial incentive was evaluated to determine if ST improvement can be augmented and sustained.

METHODS

This prospective study was performed at a 751-bed, urban, tertiary care adult teaching hospital. Test-site imaging volume approximated 48,000 examinations per month. The radiology department has 100 trainees and 124 attending radiologists serving multiple institutions. Over a study period of 4 years and 4 months, three interventions focused on radiologist signature performance were implemented: 1) a notification paging application that alerted radiologists when reports were ready for signature, 2) a picture archiving and communications systems (PACS)-integrated speech recognition report generation system, and 3) a departmental financial incentive to reward radiologists semiannually for ST performance. Signature time was compared before and after the interventions. Wilcoxon and linear regression statistical analyses were used to assess the significance of trends.

RESULTS

Technology adoption (paging plus speech recognition) reduced median ST from >5 to <1 hour (P < .001) and 80th-percentile ST from >24 to 15 to 18 hours (P < .001). Subsequent addition of a financial incentive further improved 80th-percentile ST to 4 to 8 hours (P < .001). The gains in median and 80th-percentile ST were sustained over the final 31 months of the study period.

CONCLUSIONS

Technology interventions coupled with financial incentive can result in synergistic and sustainable improvement in radiologist report-signing behavior. The addition of a financial incentive leads to better performance than that achievable through technology alone.

Effect of anesthesia and sedation on pediatric MR imaging patient flow

PURPOSE

To determine the effect of sedative and anesthetic administration on the duration and costs of pediatric magnetic resonance (MR) imaging.

MATERIALS AND METHODS

This prospective study was approved by the institutional research ethics board; informed consent and/or assent was obtained from all participants or their parents. A patient flow study was conducted in a pediatric MR imaging clinic in which research assistants tracked participants' progress through the clinic. Demographic, visit process, and medication information was collected for 237 participants, categorized as awake, sedated, or anesthetized. The data were analyzed to (a) determine total visit duration differences, (b) investigate variations in visit stage durations according to patient type, and (c) estimate visit costs on the basis of human resource and medication use. Linear regression, the Shapiro-Wilk test, the two-tailed t test, and the nonparametric Mann-Whitney test were used.

RESULTS

Complete data sets were obtained for 148 awake, 28 sedated, and 27 anesthetized participants. Data revealed 12 stage sequences among patient visits; dominant sequences differed according to patient category. An awake patient's average visit duration (2 hours 21 minutes) differed significantly from that of sedated (3 hours 38 minutes, P < .001) and anesthetized (4 hours 7 minutes, P < .001) patients; sedated and anesthetized visit durations did not differ significantly (P < .073), although this finding may be attributable to the small sample sizes. Variation in stage durations was also evident within and among patient types. Visit costs for sedated and anesthetized patients were 3.24 and 9.56 times higher, respectively, than those for awake patients. Costs for anesthetized patients were 2.95 times higher than those for sedated patients.

CONCLUSION

Visit durations were significantly longer for anesthetized and sedated patients. Anesthetized patients incurred the highest costs, followed by sedated patients.