Improving Initiation and Tracking of Research Projects at an Academic Health Center: A Case Study

Identifying Opportunities for Workflow Automation in Health Care: Lessons Learned from Other Industries

Background  Workflow automation, which involves identifying sequences of tasks that can be streamlined by using technology and modern computing, offers opportunities to address the United States health care system's challenges with quality, safety, and efficiency. Other industries have successfully implemented workflow automation to address these concerns, and lessons learned from those experiences may inform its application in health care.

Objective  Our aim was to identify and synthesize (1) current approaches in workflow automation across industries, (2) opportunities for applying workflow automation in health care, and (3) considerations for designing and implementing workflow automation that may be relevant to health care.

Methods  We conducted a targeted review of peer-reviewed and gray literature on automation approaches. We identified relevant databases and terms to conduct the searches across sources and reviewed abstracts to identify 123 relevant articles across 11 disciplines.

Results  Workflow automation is used across industries such as finance, manufacturing, and travel to increase efficiency, productivity, and quality. We found automation ranged from low to full automation, and this variation was associated with task and technology characteristics. The level of automation is linked to how well a task is defined, whether a task is repetitive, the degree of human intervention and decision-making required, and the sophistication of available technology. We found that identifying automation goals and assessing whether those goals were reached was critical, and ongoing monitoring and improvement would help to ensure successful automation.

Conclusion  Use of workflow automation in other industries can inform automating health care workflows by considering the critical role of people, process, and technology in design, testing, implementation, use, and ongoing monitoring of automated workflows. Insights gained from other industries will inform an interdisciplinary effort by the Office of the National Coordinator for Health Information Technology to outline priorities for advancing health care workflow automation.

Incorporating professional recommendations into a graduate-level statistical consulting laboratory: A case study

Introduction:

There has been a recent trend in medical research towards a more collaborative relationship between statisticians and clinical investigators. This has led to an increased focus on the most efficient and effective ways to structure, conduct, and measure the impact of organizations that provide statistical services to clinical investigators. Several recent guidelines and recommendations on the conduct of statistical consulting services(SCSs) have been made in response to this need, focusing on larger SCSs consisting primarily of faculty and staff statisticians. However, the application of these recommendations to consulting services primarily staffed by graduate students, which have the dual role of providing a professional service and training, remains unclear.

Methods:

Guidelines and recommendations, primarily from the Clinical and Translational Science (CTSA) consortium, were applied to a SCS staffed primarily by graduate students in an academic health center. A description of the organizational structure and outcomes after 3 years of operation is presented.

Results:

The guidelines recommended by the CTSA consortium and other groups were successfully incorporated into the graduate consulting laboratory. At almost one new project request per week, the consulting laboratory demonstrated a large bandwidth and had an excellent feedback from investigators.

Conclusions:

Guidelines developed for larger statistical consulting organizations are able to be applied in student-led consultation organizations. Outcomes and recommendations from 3.5 years of operation are used to describe the successes and challenges we have encountered.

Using a process improvement approach to identifying barriers to research in a CTSA hub environment

For the past 4 years, as part of the National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) grant award number UL1TR001436, the Clinical Translational Science Institute of Southeast Wisconsin (CTSI) has used process engineering approaches to identify and understand barriers that local researchers and other stakeholders face when engaging in clinical and translational science. We describe these approaches and present preliminary results. We identified barriers from published and unpublished work at other CTSA hubs, supplemented by surveys and semi-structured interviews of CTSI faculty. We then used a multifaceted approach to organize, visualize, and analyze the barriers. We have identified 27 barriers to date. We ranked their priority for CTSI to address based on the barrier's impact, the feasibility of intervention, and whether addressing the barrier aligned with CTSI's institutional role. This approach provides a systematic framework to scope and address the "barriers to research problem" at CTSI institutions.

A System for an Accountable Data Analysis Process in R

Efficiently producing transparent analyses may be difficult for beginners or tedious for the experienced. This implies a need for computing systems and environments that can efficiently satisfy reproducibility and accountability standards. To this end, we have developed a system, R package, and R Shiny application called adapr (Accountable Data Analysis Process in R) that is built on the principle of accountable units. An accountable unit is a data file (statistic, table or graphic) that can be associated with a provenance, meaning how it was created, when it was created and who created it, and this is similar to the 'verifiable computational results' (VCR) concept proposed by Gavish and Donoho. Both accountable units and VCRs are version controlled, sharable, and can be incorporated into a collaborative project. However, accountable units use file hashes and do not involve watermarking or public repositories like VCRs. Reproducing collaborative work may be highly complex, requiring repeating computations on multiple systems from multiple authors; however, determining the provenance of each unit is simpler, requiring only a search using file hashes and version control systems.

Improving pilot project application and review processes: A novel application of lean six sigma in translational science

Each year our Clinical and Translational Science Award pilot projects program awards approximately $500,000 in translational pilot funding to advance health in South Texas. We identified needs to improve the timeliness, transparency, and efficiency of the review process by surveying applicants. Lean six sigma methodologies, following a "Define, Measure, Analyze, Improve, Control" approach, were used to streamline the pilot project application and review by identifying and removing bottlenecks from process flows. We evaluated the impact of our reorganized review process by surveying applicants and reviewers. Process mapping identified pilot project review as the main source of delay, leading to the implementation of a study section-style review mechanism. After one cycle, 90.3% of pilot applicants and 100% of reviewers were highly satisfied with the new processes and time to award notice was reduced by 2 months. All reviewers familiar with both review processes preferred the study section. We demonstrated how lean six sigma, a methodology not commonly applied in research administration, can be used to evaluate processes in translational science in academic health centers. Through our efforts, we were able to improve timeliness, transparency, and efficiency of the review process.