Gatekeeper family doctors operating a decentralized referral prioritization system: Uncovering improvements in system resilience through a grounded-based approach

Making resilience explicit in FRAM: Shedding light on desired outcomes

“…FRAM models commonly shed light on resilience characteristics of systems (Patriarca et al, 2020). However, despite the contributions of earlier studies (see Section 2.2) they have limitations such as: (i) their modeling of successful performance is usually concerned with everyday work (Patriarca et al, 2020), rather than events that have a clearly defined and desired endpoint, likewise accidents (i.e., when the injury or damage is the endpoint); (ii) they usually take an overly descriptive and ad‐hoc approach for analyzing the role played by resilience (e.g., Arcuri et al, 2020; Saldanha et al, 2020), which makes it difficult the comparison between case studies; and (iii) the FRAM steps are more often than not applied according to the original proposal by Hollnagel (2012), which leaves the consideration of resilience insights implicit and too much dependent on the experience of the analyst (Patriarca et al, 2020)—for example, inclusion of functions relevant to resilience, recognition of variabilities that exist despite desired outcomes, and concern with practical recommendations to sustain good performance.…”

“…The four abilities of resilient systems proposed by Hollnagel (2017) have been widely used for the modeling of resilience (e.g., Arcuri et al, 2020; Bertoni et al, 2021; Chuang et al, 2020). They are (Hollnagel, 2017): (i) the ability to respond, which implies knowing what to do, or being able to respond to regular and irregular changes, disturbances, and opportunities; (ii) the ability to monitor, which implies knowing what to look for, or being able to monitor what could seriously affect the system performance in the near term, positively or negatively; (iii) the ability to learn, which implies knowing what has happened, or being able to learn from experience, in particular to acquire the right lessons from the right experience; and (iv) the ability to anticipate, which implies knowing what to expect, or being able to prepare for developments further into the future, such as disruptions, constraints or opportunities.…”

“…A common approach has been the development of methods for the identification of functions that are a key for resilient performance (Falegnami et al, 2020; Raben et al, 2018). Others, such as Arcuri et al (2020) have stressed the quantification of the level of resilience in a system at a certain time, based on the corresponding FRAM model. In turn, the study by Aguilera et al (2016) exemplifies a typical FRAM application for the qualitatively modeling of performance variabilities (in oil spill response, in that case), as a basis for improving system resilience.…”

“…Although not making explicit reference to resilience, the FRAM model developed in that study presents functions relevant to resilience, for example, sense‐making functions (Saldanha et al, 2020). Arcuri et al (2020) take another approach when using the FRAM for modeling resilience in a referral prioritization system in the public health sector. In this case, the FRAM model had only four functions, each named according to one of the four resilience abilities proposed by Hollnagel (2017).…”

Telehealth to support referral management in a universal health system: a before-and-after study

“…Regional centers responsible for referral management have their own protocols to prioritize cases on waiting lists in detriment to a simple first come, first served model [ 14 ]. Regional experiences include the promotion of the coordination of care by PHC providers, who act as gatekeepers to specialized care [ 15 ]. Even provided these measures, in several localities the first come, first served model still predominates, making the flow of patients possibly unfair and time-consuming.…”