This was a mixed methods study that used different methodologies for the dashboard design and development, and evaluation of usability. The dashboard described in this study is a component of a larger project that aimed to develop various standards-based health data, digital tools, and strategies for quality improvement [25]. The industry partner was Regis Aged Care (Regis), one of Australia’s largest aged care service providers [25].

Ethical approval was provided by the University of Queensland Human Research Ethics Committee (ID: 2022/HE002362). After accepting invitations to participate in the project, participants were supplied with an information sheet summarizing the project and a consent form for signing prior to data collection. Furthermore, researchers began each workshop/interview by explaining the project aims, procedures, and ethical considerations, including participants’ right to withdraw at any time. Participants were not compensated for participating in the project. All members of the research team adhered to institutional procedures governing research data storage, access, and privacy. Data were transcribed and deidentified using a commercial transcription service.

To evaluate the dashboard usability, we conducted a pilot study designed to assess usability and perceived usefulness of the prototype, rather than to evaluate impact on care quality outcomes (which would require a longer evaluation period). Pilot participants were a convenience sample of 30 end-users in 12 nursing homes, consisting of general managers, regional general managers, clinical care managers, and clinical care specialists. Pilot participants were granted unrestricted access to the dashboard and encouraged to explore it freely. However, to facilitate structured engagement, we provided a monthly task list suggesting specific areas for exploration. Throughout the pilot, we met with participants during their routine monthly quality review meetings to monitor task progression and address user queries or technical issues.

At the conclusion of the pilot, we assessed the dashboard’s usability using the System Usability Scale (SUS) [39], a widely adopted, standardized instrument for evaluating perceived product usability, including HITs [40]. It comprises 10 items rated on a 5-point Likert scale, yielding an overall usability score between 0 and 100 [41,42]. SUS scores below 60 signal poor usability while scores in the 60‐69 range signal fair usability, 70‐79 signal good usability, 80‐84 signal excellent usability, and 85‐100 signal the best achievable usability [43]. In addition to the SUS items, the survey included questions assessing the perceived usefulness of the dashboard for person-centered care, its potential to support quality improvement, and suggestions for improvements. The survey was designed and administered using the Qualtrics platform.

Overall, we conducted 5 workshops for Stages 1‐5: the first 2 workshops for Stages 1‐3 and the next 3 for Stages 2‐5 (see Figure 1). The combination of hands-on exploration and the Think-Aloud approach during in-person workshops was effective at stimulating discussion among the co-design group and facilitating development of new ideas for further enhancement of the dashboard.

Of the 30 individuals invited to participate in the pilot, 29 participants accessed the dashboard at least once during the pilot period, and 16 opened the usability survey (53% response rate) and 14 completed the survey (87.5% completion rate). The average SUS score was 75.2 (SD 16.3), indicating end-users thought usability of the dashboard was good. Among the completed surveys, 85.7% (12/14) of respondents reported being likely or extremely likely to recommend the dashboard to a colleague. An equal proportion (12/14) believed the dashboard would support the delivery of personalized care for residents. Additionally, 92.8% (13/14) agreed or strongly agreed that the dashboard would assist with quality monitoring and improvement activities within Regis.

The drill-through to individual resident-level views was well-received, with participants noting it could help staff quickly identify and prioritize relevant care domains, thereby promoting more person-centered care. In response to a survey item on integrating the dashboard into routine workflows, pilot participants suggested it could be useful for preparing internal quarterly reviews. They also recommended refreshing the data monthly to enable exporting dashboard views for inclusion in monthly clinical quality reports. Participants offered several suggestions for further improvements. However, some of these were contradictory, reflecting differences in personal preferences. For example, while some users preferred listing homes alphabetically when comparing performance, others favored sorting by descending indicator value to highlight the best- or worst-performing homes.

This article describes the design, development, and preliminary evaluation of a dashboard for quality indicator data. To our knowledge, it is the first published study to describe a dashboard specifically designed to support the Australian QI Program in aged care. Workshops were the primary collaboration method in the co-design process, complemented by a flexible, multi-channel approach that maintained momentum by enabling the prompt resolution of minor issues between scheduled sessions.

The multi-level drill-through capability is a key feature of the dashboard, which allows users to explore data at progressively finer levels of detail. This functionality supports a broad range of users across executive, managerial, and clinical roles. By providing secure access to resident-level data, the dashboard supports data-driven personalized care, which is associated with better resident outcomes and higher satisfaction and quality of life [45]. In this way, quality indicator data can be used as an operational asset for continuous quality improvement, enabling a bottom-up approach in which targeted care at the individual resident level may cumulatively contribute to improved performance at both home and organizational levels.

The dashboard requirements that were not specific to our use-case, that is, those that can be generalized to most health care dashboards, were consistent with those in the existing literature [14]. Like participants in other co-designed health care dashboards, co-design participants required functionality for selecting specific data subsets (homes or groups of homes, years, and calendar quarters) to view/compare indicators and multi-level drill-through capability, to have the ability to benchmark homes against group statistics, and to have secure access to resident-level data [14,19,46-48]. The design elements incorporated into the dashboard (radio buttons for navigation, color-coded visuals, line and bar charts, etc) were also consistent with existing literature [19]. The co-design and pilot participants found these design elements to be simple but powerful ways for conveying important details within the data as reported by users of other health care dashboards [19].

A key strength of this study is the participatory, iterative development approach involving stakeholders across organizational executives, managers, and nurses. This enabled the tailoring the dashboard for real-world quality monitoring workflows and to support both performance oversight and resident-level care planning. Another strength is that the pilot was conducted in an operational aged care setting, providing an initial indication of feasibility and usability in practice.

This study has several limitations. First, the pilot evaluation was conducted with a convenience sample within a single aged care provider organization, and only 14 of the 30 participants completed the post-pilot survey. This limits generalizability and introduces the possibility of response and selection bias. Second, the 3-month pilot duration may be insufficient to understand long-term adoption, workflow integration, and sustained use. Third, the evaluation focused on perceived usability and usefulness but not effectiveness; we did not directly measure changes in care quality, staff decision-making, or resident outcomes attributable to dashboard use. Fourth, the prototype relied on manual data uploads and did not include automated data pipelines, which may limit scalability and real-world implementation readiness. Fifth, the dashboard operated on QI Program data, which is collected quarterly and may be too infrequent for timely monitoring of emerging issues in resident care.

Although the findings suggest potential for dashboards to make quality indicators more practical for monitoring care quality and supporting continuous improvement, broader implementation in practice will require technical and organizational development beyond this prototype stage. Future work should progress in 3 stages. First, implementation-ready infrastructure is needed, including a central data warehouse (or equivalent) and automated data pipelines from clinical information system sources. This would improve scalability, reduce manual workload, and enable stronger data quality controls (eg, completeness and timeliness checks). Second, dashboard functionality should be extended to support more frequent refreshes and enhanced analytics such as automated alerts and trend detection (improvements suggested by participants during this pilot). The divergent feedback on interface preferences during the pilot (eg, alphabetical vs performance-based sorting) suggests that usability in this context depends not only on simplicity, but also on flexibility. Future iterations should therefore include user-configurable interface features, such as selectable sort and display options, role-specific default views, and saved filters. These enhancements would better accommodate diverse workflows and user preferences across organizational, home-level, and clinical roles. Third, the dashboard should be evaluated in a larger, multi-site longitudinal study to measure not only usability and adoption but also the impact on quality improvement processes and resident outcomes. Organizations must establish robust governance strategies to mitigate the risk of “tunnel vision”—a phenomenon where attention becomes overly focused on the domains measured by implemented quality indicators at the expense of unmeasured aspects of care [49]. While this is a risk of using indicators for improvement more broadly [49], a dashboard with resident-level views may heighten the effect by directing clinical attention primarily toward the indicators presented on screen. Aged care organizations should also consider expanding the suite of dashboard quality indicators to complement the current QI Program and encompass a broader range of critical resident care domains.

This study holds several lessons for informatics and the aged care sector. A multi-channel collaboration approach helped us gather feedback faster than relying solely on the workshops. The aged care industry, especially in Australia, is highly regulated, and providers occasionally have to attend to short-notice site visits and requests for information from regulators, necessitating immediate and intense activity by executive and operational managers. For this reason, it was common for some co-design participants to suddenly become unavailable for scheduled co-design workshops; however, the fortnightly meeting and emails provided additional avenues and opportunities to capture feedback and contributions. While fortnightly meetings may not be feasible for others, less frequent timeframes may be sufficient (eg, monthly or bimonthly). The feedback gathered from co-design participants using the Think-Aloud technique when interacting with the dashboard during in-person workshops provided richer data than online workshops. The Think-Aloud technique, which has been successful applied in HIT co-design in aged care [50], was particularly effective at stimulating insightful discussions and generation of ideas among co-design participants.

In conclusion, dashboards co-designed with stakeholders have the potential to help aged care organizations operationalize quality indicator data for monitoring care quality and personalized care in residential aged care. Larger and longitudinal evaluations are required to determine their long-term impact on care quality and resident outcomes.