Agile Methods for Open Source Safety-Critical Software

Adapting agile development practices for hyper-agile environments: lessons learned from a COVID-19 emergency response research project

Agile development is known for efficient software development practices that enable teams to quickly develop software to cope with changing requirements. Although there is evidence that agile practices are helpful in such environments, the literature does not inform us as to whether agile practices can also be beneficial in hyper-agile environments. Such environments are characterized by an extremely fast pace of change with fluid requirements. COVID-19 vaccine distribution is one such problem that governments have had to deal with. To solve this problem, governments need to come up with robust responses by formulating teams that have the capability to provide software solutions enabling information visibility into the vaccine distribution process. Such emergent teams need to quickly understand the distribution process, oftentimes define the process itself because it might be non-existent, and build software systems to solve the problem in a matter of days. Not much is known about how systems can be developed at such a fast pace. We adopt a clinical research methodology and employ agile software development practices to develop such a mission-critical system. In the process of building the system, we learn important lessons that can be used to adapt and extend agile methodologies to be used in hyper-agile development environments. We offer these lessons as important first steps to understanding the best practices needed to develop software systems that have the capability to provide visibility into the unprecedented health challenge of distribution of life-saving COVID-19 vaccine.

Building an outpatient telemedicine care pilot using Scrum-like framework within a medical residency program

OBJECTIVES

A good health care does not only depend on good medical practice, but also needs great management of its resources, which are generally short. In this sense, PROAHSA has been training new health managers since 1972. With the arrival of the COVID-19 pandemic, it was clear that medicine will go through a new phase, where telehealth will be present in this "Improved Normal". This report is about how a pilot teleconsultation study was carried out for HCFMUSP patients through the Scrum-like framework. It is to deploy a pilot of remote assistance involving a doctor and a patient in the Ambulatory of Hepatology and Liver Transplantation of HCFMUSP.

METHODS

We applied the Scrum-like framework to carry out this work with an interdisciplinary multifunctionality team.

RESULTS

A full telemedicine service flow was implemented within eight weeks using existing infrastructure and resources implementing the Scrum methodology. Twenty-three teleconsultations were scheduled and eight guides built.

CONCLUSION

Scrum framework has a great potential to improve the training of students and to conclude pilot projects.

Development and Modification of a Mobile Health Program to Promote Postpartum Weight Loss in Women at Elevated Risk for Cardiometabolic Disease: Single-Arm Pilot Study

BACKGROUND

Pregnancy complications in combination with postpartum weight retention lead to significant risks of cardiometabolic disease and obesity. The majority of traditional face-to-face interventions have not been effective in postpartum women. Mobile technology enables the active engagement of postpartum women to promote lifestyle changes to prevent chronic diseases.

OBJECTIVE

We sought to employ an interactive, user-centered, and participatory method of development, evaluation, and iteration to design and optimize the mobile health (mHealth) Fit After Baby program.

METHODS

For the initial development, a multidisciplinary team integrated evidence-based approaches for health behavior, diet and physical activity, and user-centered design and engagement. We implemented an iterative feedback and design process via 3 month-long beta pilots in which postpartum women with cardiometabolic risk factors participated in the program and provided weekly and ongoing feedback. We also conducted two group interviews using a structured interview guide to gather additional feedback. Qualitative data were recorded, transcribed, and analyzed using established qualitative methods. Modifications based on feedback were integrated into successive versions of the app.

RESULTS

We conducted three pilot testing rounds with a total of 26 women. Feedback from each pilot cohort informed changes to the functionality and content of the app, and then a subsequent pilot group participated in the program. We optimized the program in response to feedback through three iterations leading to a final version.

CONCLUSIONS

This study demonstrates the feasibility of using an interactive, user-centered, participatory method of rapid, iterative design and evaluation to develop and optimize a mHealth intervention program for postpartum women.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02384226; https://www.clinicaltrials.gov/ct2/show/NCT02384226.

Development and Feasibility of a Real-Time Clinical Decision Support System for Traumatic Brain Injury Anesthesia Care

BACKGROUND

Real-time clinical decision support (CDS) integrated with anesthesia information management systems (AIMS) can generate point of care reminders to improve quality of care.

OBJECTIVE

To develop, implement and evaluate a real-time clinical decision support system for anesthetic management of pediatric traumatic brain injury (TBI) patients undergoing urgent neurosurgery.

METHODS

We iteratively developed a CDS system for pediatric TBI patients undergoing urgent neurosurgery. The system automatically detects eligible cases and evidence-based key performance indicators (KPIs). Unwanted clinical events trigger and display real-time messages on the AIMS computer screen. Main outcomes were feasibility of detecting eligible cases and KPIs, and user acceptance.

RESULTS

The CDS system was triggered in 22 out of 28 (79%) patients. The sensitivity of detecting continuously sampled KPIs reached 93.8%. For intermittently sampled KPIs, sensitivity and specificity reached 90.9% and 100%, respectively. 88% of providers reported that CDS helped with TBI anesthesia care.

CONCLUSIONS

CDS implementation is feasible and acceptable with a high rate of case capture and appropriate generation of alert and guidance messages for TBI anesthesia care.

Implementation science approaches for integrating eHealth research into practice and policy

PURPOSE

To summarize key issues in the eHealth field from an implementation science perspective and to highlight illustrative processes, examples and key directions to help more rapidly integrate research, policy and practice.

METHODS

We present background on implementation science models and emerging principles; discuss implications for eHealth research; provide examples of practical designs, measures and exemplar studies that address key implementation science issues; and make recommendations for ways to more rapidly develop and test eHealth interventions as well as future research, policy and practice.

RESULTS

The pace of eHealth research has generally not kept up with technological advances, and many of our designs, methods and funding mechanisms are incapable of providing the types of rapid and relevant information needed. Although there has been substantial eHealth research conducted with positive short-term results, several key implementation and dissemination issues such as representativeness, cost, unintended consequences, impact on health inequities, and sustainability have not been addressed or reported. Examples of studies in several of these areas are summarized to demonstrate this is possible.

CONCLUSIONS

eHealth research that is intended to translate into policy and practice should be more contextual, report more on setting factors, employ more responsive and pragmatic designs and report results more transparently on issues important to potential adopting patients, clinicians and organizational decision makers. We outline an alternative development and assessment model, summarize implementation science findings that can help focus attention, and call for different types of more rapid and relevant research and funding mechanisms.

Rapid, responsive, relevant (R3) research: a call for a rapid learning health research enterprise

Our current health research enterprise is painstakingly slow and cumbersome, and its results seldom translate into practice. The slow pace of health research contributes to findings that are less relevant and potentially even obsolete. To produce more rapid, responsive, and relevant research, we propose approaches that increase relevance via greater stakeholder involvement, speed research via innovative designs, streamline review processes, and create and/or better leverage research infrastructure. Broad stakeholder input integrated throughout the research process can both increase relevance and facilitate study procedures. More flexible and rapid research designs should be considered before defaulting to the traditional two-arm randomized controlled trial (RCT), but even traditional RCTs can be designed for more rapid findings. Review processes for grant applications, IRB protocols, and manuscript submissions can be better streamlined to minimize delays. Research infrastructures such as rapid learning systems and other health information technologies can be leveraged to rapidly evaluate new and existing treatments, and alleviate the extensive recruitment delays common in traditional research. These and other approaches are feasible but require a culture shift among the research community to value not only methodological rigor, but also the pace and relevance of research.