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Implementation of Resilience Engineering in Health Care: Parallels from the Maintenance World

Posted by Elizabeth Lay, Zachary Woods, Matthieu Branlat on Saturday September 20th, 2014

Implementation of Resilience Engineering in Health Care: Parallels from the Maintenance World

What do health care and mechanical maintenance have in common? A cursory glance would say not much. One system deals with the diagnosis and treatment of human patients while the other deals with diagnosis and maintenance of machines. Dig a bit deeper, beyond biological vs. metal or physiological vs. physics, and you will notice similar pressures, constraints and issues.

Broadly speaking, and similarly to many high-risk, high-consequence domains, the situations organizations face in industrial maintenance as well as in health care are characterized by their uncertain, dynamic and complex nature. More specifically, production goals, schedule pressure, limited resources, strong emphasis on compliance (for safety and quality), checklists, policies, highly specialized professionals, variable workforce, variable workloads, nuisance alarms, implementation of “lean”, “big data” are characteristic of health care as well as of industrial maintenance. Maintainers even talk of turbines as having a “health” or assign gender (“she”) as they troubleshoot issues and prescribe maintenance procedures. Both domains face diagnosis of complex cases and urgency of emergent load: in healthcare, emergency room overload; in maintenance, unplanned power plant outages.

What characterizes resilient organizations in such domains is their ability to prepare for surprises, to adapt in time and to manage interdependencies between their components. If some of the core issues are analogous, we have an opportunity for mutually beneficial learning. To this end, we share our experience implementing practices to increase resilience in maintenance, and we illustrate the transition from guiding principles to practices through one specific example. But before we do this, let us briefly introduce our work.

 

Overview of Turbine Maintenance

With 90+ plants in the US and Canada, Calpine holds the nations'' largest fleet of combined-cycle and cogeneration plants. The work environment is shaped by frequent maintenance requiring plant shutdown (an outage), power price volatility, high cyclic load, and chronic shortages (parts and people). Emergent work, market disturbances (plant going down or weather extremes cause spike in electricity prices). These situations lead to ever greater schedule pressure.  As an independent producer, Calpine seeks to optimize the performance of gas-turbines through modifications, upgrades, third party parts and other configuration conditions that create novel situations.

An ‘outage’ on a combined cycle plant involves crews of 15 to 30 people mobilizing to a power plant site to disassemble, inspect, and reassemble the turbine-generator while the plant staff perform maintenance work on the balance of the plant. It is a complex and demanding operation due to a number of characteristics:

-        The crew is diverse, including contractors with variable skills and knowledge, power plant site personnel, and the power plant owner maintenance group who direct and check critical work. Often this group comes together for the first time on day 1 of the outage.

-        The work requires many specialty tools, often shipped in on several tractor trailers.

-        The plant parts are large, expensive, complicated, with very tight clearances and close tolerances. Operations require lifting heavy components (a typical turbine rotor can weigh 50 to 80 US tons).

-        It is common to be working outdoors in extreme conditions of heat or cold for 12-hour shifts, 7 days a week, under extreme schedule pressure.

 

From essential characteristics of resilience to operational strategies

According to Erik Hollnagel, “the essential characteristic of a resilient system is the ability to adjustits functioning so that it can succeed in different – and difficult – situations.” Such overall abilityis supported by four system abilities: ability to respond, to monitor, to anticipateand to learn. Given the aforementioned potential for novel situations, resource constraints, schedule pressure and, overall, gaps always emerging between imagined and experienced work conditions, success requires that the maintenance system be resilient. Designing systems to be resilient means translating the four abilities above into practices and strategies.

For instance, when adverse events occur, the ability to respond is determined by the availability of resources and sources of expertise. At any plant, at any given time, only the local team experiences the local situation. Due to operations occurring in parallel over large geographic areas and inevitable differences in types and amounts of experience and expertise between teams, the local team has a necessarily bounded range of capabilities to deal with its local situation. When a problem arises, especially a problem of unexpected or unknown nature, a critical issue is how to bring resources with relevant knowledge and expertise to bear, and in time, in order to support the response to the problem. This is similar to situations experienced by hospitals when a medical specialty absent of the location is needed and consults in difficult cases, and has been a driver for approaches such as telemedicine and electronic ICUs.

In the following section, we share Calpine’s approach for addressing that issue and supporting the ability to respond.

 

Real Time Risk Assessment

A novel, complex, and/or difficult situation arises at a power plant and within one hour, a geographically separated, diverse group in terms of knowledge, skills, function level, and roles, convenes via telephone conference to support the plant manager or field lead in coming up with a plan to address the issue. A Knowledge Broker leads participants through structured brainstorming to explore risks and diagnose a problem, agree on and produce a plan that includes actions, decisions, decision authority and accountability, check-in points, iterative solutions, and contingencies. This is a Real Time Risk Assessment.

Real Time Risk Assessments tap into current, diverse knowledge and shared experiences, in an organic, interconnected way and bring it to bear at point and time of need. Real Time Risk Assessments enable responding to the general shape of risk; types and sources of knowledge that help with certain types of problems are identified ahead of time. Participants’ roles are designed for diversity: risk decision owner (responsible for profit and loss), matchmaker (knows what others know), challenger, design expert (what to do), repair expert (how to do), person(s) with related experience, practitioners needing help. Designing for diverse perspectives aims at addressing the wide range of aspects associated with a situation: from understanding the issue to planning for a response, from technical to management matters. Knowledge brokers, the “persons or organizations that facilitate the creation, sharing, and use of knowledge” (Sverrission, 2001) play a critical part in orchestrating and “bridg[ing]” (Garner, 2006) the diverse perspectives across organizational and knowledge boundaries. Meyer (2010) emphasizes that knowledge brokers do more than link knowledge: they facilitate co-creation of knowledge and participate in constructing a common language.

An important outcome our organization has experienced as a result of the implementation of the Real Time Risk Assessment is a shift in how risk is considered and managed. Consider a situation where higher than normal temperatures exist in a turbine disc cavity but it’s not clear what the problem is. The risk decision is to bring the unit down to inspect, possibly finding nothing (certain loss of about half a million USD to pull the turbine cover and uncertain gain), or keep running, risking damaging the turbine (avoiding certain loss but risking significantly higher loss). This type of troubleshooting may be analogous to diagnosing symptoms of illness, weighing the option of exploratory surgery. Historically, risks were assessed by a few people only. Past experience suggests that such situations tended to lead to riskier positions such as continuing to run vs. shutting down to inspect (discounting risk of higher loss to avoid certain sunk cost). In a Real Time Risk Assessment, technical and local experts are still highly influential but benefit from the knowledge and experiences from others. Knowledge Brokers actively probe and bound risks and uncertainty, then follow up to share how situations turned out for the purpose of learning. Note that the exploration of risks and uncertainty include the critical topic of interdependencies, such as impact on schedule or availability of contractors for a particular course of action.  Through facilitation by a person knowledgeable in the language of risk (knowledge broker), the Real Time Risk Assessment process allows revealing risk (which is often obscured, hidden in assumptions and uncertainties, and absent from common dialogue). As a result of a more “mindful” (in the HRO sense) process, decision making tends to shift to less risky positions.

 

Conclusion

This blog describes one instance of implementing Resilience Engineering in the field of mechanical maintenance. This specific practice was selected both to illustrate our approach to the development of practices to increase resilience in our organization, and because of its direct relevance to the domain of healthcare: we see it as an opportunity to ground discussions and mutual learning between these two domains in particular, but also more generally across domains that share similar struggles to develop approaches towards resilience. We will also address during the discussion the important question of the implementation of such practices within an organization, and we will share our approach and experience (successes, challenges) to this aim.

We look forward to our conversation with you!

 

References:                                                   

  • Sverrisson, A. (2001). Translation networks, knowledge brokers, and novelty construction: pragmatic environmentalism in Sweden. Acta Sociologica, 44, 313-327.
  • Blondel, D. (2006). L’emergence des “knowledge brokers” (courtiers de science) et des KIBS: Knowledge-intensive business service. Paper presented at Au Carrefour de la science, de la technologei, de l’economie, de la culture et de la societe: Les métiers ouverts aux docteures par le besoion d’expertise, Institut Henri Poincare, Paris, France
  • Garner, J. T. (2006). It’s not what you know: a transactive memory analysis of knowledge networks at NASA. J. Technical Writing and Communication. Vol. 36(4), 329-351
  • Meyer, M. (2010). The rise of the knowledge broker. Science communication, 32, 118-127.
  • Woods, D. D., & Branlat, M. (2011). Basic Patterns in How Adaptive Systems Fail. In E. Hollnagel, J. Pariès, D. D. Woods, & J. Wreathall (Eds.), Resilience Engineering in Practice (pp. 127–144). Farnham, UK: Ashgate.

 

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