Background Electronic Medical Records (EMRs) are one of a range of digital health solutions that are key enablers of the data revolution transforming the health sector. They offer a wide range of benefits to health professionals, patients, researchers and other key stakeholders. However, effective implementation has proved challenging. Methods A qualitative methodology was used in the study. Interviews were conducted with 12 clinical and administrative staff of a cancer centre at one-month pre-launch and eight clinical and administrative staff at 12-months post-launch of an EMR. Data from the interviews was collected via audio recording. Audio recordings were transcribed, de-identified and analysed to identify staff experiences with the EMR. Results Data from the pre-implementation interviews were grouped into four categories: 1) Awareness and understanding of EMR; 2) Engagement in launch process; 3) Standardisation and completeness of data; 4) Effect on workload. Data from the post-launch interviews were grouped into six categories: 1) Standardisation and completeness of data; 2) Effect on workload; 3) Feature completeness and functionality; 4) Interaction with technical support; 5) Learning curve; 6) Buy-in from staff. Two categories: Standardisation and completeness of data and effect on workload were common across pre and post-implementation interviews. Conclusion Findings from this study contribute new knowledge on barriers and enablers to the implementation of EMRs in complex clinical settings. Barriers to successful implementation include lack of technical support once the EMR has launched, health professional perception the EMR increases workload, and the learning curve for staff adequately familiarize themselves with using the EMR.

Background A large quantity of data is collected during the delivery of cancer care. However, once collected, these data are difficult for health professionals to access to support clinical decision making and performance review. There is a need for innovative tools that make clinical data more accessible to support health professionals in these activities. One approach for providing health professionals with access to clinical data is to create the infrastructure and interface for a clinical dashboard to make data accessible in a timely and relevant manner. Objective This study aimed to develop and evaluate 2 prototype dashboards for displaying data on the identification and management of lymphedema. Methods The study used a co-design framework to develop 2 prototype dashboards for use by health professionals delivering breast cancer care. The key feature of these dashboards was an approach for visualizing lymphedema patient cohort and individual patient data. This project began with 2 focus group sessions conducted with members of a breast cancer multidisciplinary team (n=33) and a breast cancer consumer (n=1) to establish clinically relevant and appropriate data for presentation and the visualization requirements for a dashboard. A series of fortnightly meetings over 6 months with an Advisory Committee (n=10) occurred to inform and refine the development of a static mock-up dashboard. This mock-up was then presented to representatives of the multidisciplinary team (n=3) to get preliminary feedback about the design and use of such dashboards. Feedback from these presentations was reviewed and used to inform the development of the interactive prototypes. A structured evaluation was conducted on the prototypes, using Think Aloud Protocol and semistructured interviews with representatives of the multidisciplinary team (n=5). Results Lymphedema was selected as a clinically relevant area for the prototype dashboards. A qualitative evaluation is reported for 5 health professionals. These participants were selected from 3 specialties: surgery (n=1), radiation oncology (n=2), and occupational therapy (n=2). Participants were able to complete the majority of tasks on the dashboard. Semistructured interview themes were categorized into engagement or enthusiasm for the dashboard, user experience, and data quality and completeness. Conclusions Findings from this study constitute the first report of a co-design process for creating a lymphedema dashboard for breast cancer health professionals. Health professionals are interested in the use of data visualization tools to make routinely collected clinical data more accessible. To be used effectively, dashboards need to be reliable and sourced from accurate and comprehensive data sets. While the co-design process used to develop the visualization tool proved effective for designing an individual patient dashboard, the complexity and accessibility of the data required for a cohort dashboard remained a challenge.

Aim: Multidisciplinary team (MDT) meetings can facilitate optimal lung cancer care, yet details of structured data collection and feedback remain sparse. This study aimed to investigate data collection and the impact of feedback to lung cancer MDTs. Methods:A mixed-methods study using pre and post-test surveys, semistructured interviews, and observation to evaluate data collection and response to modeled data feedback in three Australian lung cancer MDTs at different locations and development stage (site A: outer metropolitan, established; site B, outer metropolitan, new; and site C, inner metropolitan, established). Results: MDT attendees (range 13-25) discussed 5-8 cases per meeting. All sites collected data prospectively (80% prepopulated) into local oncology medical information systems. The pretest survey had 17 respondents in total (88% clinicians). At sites A and C, 100% of respondents noted regular data audits, occasional at site B. Regular audit data included number of cases, stage, final diagnosis, and time to diagnosis and treatment. The post-test survey had 25 respondents in total, all clinicians. The majority (88-96%) of respondents found modeled data easy to interpret, relevant to clinical practice and the MDT, and welcomed future regular data presentations (as rated on a 5-point Likert scale mean weighted average 4.5 where > 4 demonstrates agreement). Semistructured interviews identified five major themes for MDTs: current practice, attitudes, enablers, barriers, and benefits for the MDT.Conclusions: MDT teams exhibited positive responses to modeled data feedback. Key characteristics of MDT data were identified and may assist with future team research and development. K E Y W O R D S data feedback, data quality, health data, lung neoplasm, multidisciplinary teams Asia-Pac J Clin Oncol. 2020;16:45-55. c

Historically, quality measurement analyses utilize manual chart abstraction from data collected primarily for administrative purposes. These methods are resource-intensive, time-delayed, and often lack clinical relevance. Electronic Medical Records (EMRs) have increased data availability and opportunities for quality measurement. However, little is known about the effectiveness of Measurement Feedback Systems (MFSs) in utilizing EMR data. This study explores the effectiveness and characteristics of EMR-enabled MFSs in tertiary care. The search strategy guided by the PICO Framework was executed in four databases. Two reviewers screened abstracts and manuscripts. Data on effect and intervention characteristics were extracted using a tailored version of the Cochrane EPOC abstraction tool. Due to study heterogeneity, a narrative synthesis was conducted and reported according to PRISMA guidelines. A total of 14 unique MFS studies were extracted and synthesized, of which 12 had positive effects on outcomes. Findings indicate that quality measurement using EMR data is feasible in certain contexts and successful MFSs often incorporated electronic feedback methods, supported by clinical leadership and action planning. EMR-enabled MFSs have the potential to reduce the burden of data collection for quality measurement but further research is needed to evaluate EMR-enabled MFSs to translate and scale findings to broader implementation contexts.