See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/235970177 Making Sense – From Complex Systems Theories, Models and Analytics to Adapting Actions and Practices in Health and Health Care Chapter · January 2013 CITATIONS 4 READS 401 2 authors: Some of the authors of this publication are also working on these related projects: Fractal Physiology View project MonashWatch program View project Carmel Mary Martin Monash Health 155 PUBLICATIONS 1,433 CITATIONS SEE PROFILE Joachim Sturmberg University of Newcastle 229 PUBLICATIONS 1,413 CITATIONS SEE PROFILE All content following this page was uploaded by Carmel Mary Martin on 31 July 2014. The user has requested enhancement of the downloaded file.
Transcript
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/235970177
Making Sense – From Complex Systems Theories, Models and Analytics to
Adapting Actions and Practices in Health and Health Care
Chapter · January 2013
CITATIONS
4
READS
401
2 authors:
Some of the authors of this publication are also working on these related projects:
Fractal Physiology View project
MonashWatch program View project
Carmel Mary Martin
Monash Health
155 PUBLICATIONS 1,433 CITATIONS
SEE PROFILE
Joachim Sturmberg
University of Newcastle
229 PUBLICATIONS 1,413 CITATIONS
SEE PROFILE
All content following this page was uploaded by Carmel Mary Martin on 31 July 2014.
The user has requested enhancement of the downloaded file.
Common to complex systems are two funda-mental themes—the universal interconnectedness and interdependence of all phenomena, and the intrinsically dynamic nature of reality [ 2 ] . “ At each level of complexity we encounter systems that are integrated, self-organizing wholes consisting
of smaller parts and, at the same time, acting as parts of larger wholes ” (Capra [ 3 ] ).
Many of the original health complexity lead-ers, like Plesek, Dooley, Berwick, and Lindberg, have pioneered the approaches that led to many diverse pathways to health improvement. But have these ideas been suf fi ciently adopted by decision makers to make a difference [ 4 ] ? We stand at crossroads in relation to health systems evidence, funding and organization, particularly in the USA. Many cherished reductionist ideas about the nature of disease and illness and how systems should be organized to improve health outcomes have not delivered their promises, e.g. “disease management carve outs,” and are found to be costly, fragmenting, and ineffective [ 5 ] . In addition, comparative metrics have revealed many unintended and unwelcome consequences such as widening health inequities, overtreatment, and poor access to care to name a few [ 6, 7 ] . However, the opportunity to in fl uence policy and practice has never been greater, as major shifts in
C. M. Martin (*) Department of Public Health and Primary Care , Trinity College , College Green, Dublin D2 , Ireland e-mail: [email protected]
J. P. Sturmberg Department of General Practice , Monash University , Melbourne , VIC , Australia
The Newcastle University, Newcastle , PO Box 3010, Wamberal, NSW 2260, Australia e-mail: [email protected]
45 Making Sense: From Complex Systems Theories, Models, and Analytics to Adapting Actions and Practices in Health and Health Care
Carmel M. Martin and Joachim P. Sturmberg
1 Writer and management consultant who studies organiza-tional behavior. Her approach includes systems thinking, theories of change, chaos theory, leadership, and the learn-ing organization: particularly its capacity to self-organize.
It is the theory that decides what we can observe.
Albert Einstein [ 1 ]
Theories rarely arise as patient inferences forced by accumulated facts. Theories are mental constructs potentiated by complex external prods (including, in idealized cases, a commanding push from empirical reality). But the prods often include dreams, quirks, and errors—just as we may obtain crucial bursts of energy from foodstuffs or pharmaceuticals of no objective or enduring value. Great truth can emerge from small error. Evolution is thrilling, liberating, and correct .
By Stephen Jay Gould
I think a major act of leadership right now, call it a radical act, is to create the places and processes so people can actually learn together, using our experiences.
Margaret J. Wheatley 1
798 C.M. Martin and J.P. Sturmberg
healthcare provision are being forced by the international fi nancial crises [ 8 ] .
Futile medicine or care is a relatively new term to describe a medical procedure or treatment that cannot achieve its stated goals or produce its expected bene fi ts with an acceptable level of probability regardless of repetition and duration of treatment [ 9 ] . For example, disease manage-ment, based on “evidence-based” guidelines and protocols, has failed to produce the desired out-comes, as person-centred care was “written out of the script” [ 10 ] . Simultaneously, the costs of health care are growing exponentially and have reached prohibitively high levels internationally, and in the USA in particular. Futile or unhelpful care processes have been identi fi ed as the major source, illustrating the unintended consequences of a large-scale systems change [ 11 ] .
John Sterman [ 12 ] and other systems dynam-ics thinkers have demonstrated that the failure of all major health system reforms has been foresee-able as the most basic consequences of a change on the neighboring agents have not been taken note of. Despite these repeated and overwhelm-ing failures, the health sector has been very slow to adopt complex adaptive systems theory and science. What has attracted considerable interest, as it largely focuses on cost control, has been lean management approaches, developed for manu-facturing by Toyota [ 13 ] . “Health reform,” not having its own theoretical underpinning, made the all too common mistake of implementing solutions decontextualized from its environment.
45.1 Perturbing Conversations About Complex Health Systems
Making health systems truly patient-centric, adapt-able and responsive requires acknowledgement of their complex adaptive nature. We require ongoing conversations and several ways of sense-making to understand and respond to the dynamics arising from the systems self-organizing properties which requires ongoing learning.
Three themes underlying the workings of health systems are explored: the notion of
innocent information; the continual process of making sense of the values and assumptions in health care; and the ever increasing content and changing context of health systems knowledge.
45.1.1 Prevailing Assumptions
Current mainstream evidence is seen through a particular lens that views problems and solutions as simple or complicated, and for which evi-dence-based solutions are available, and that there is a good business model for all the activi-ties in health care for investors and governments. This view assumes that every problem is reduc-ible if only enough research is conducted and the evidence is appropriately assembled. Recently, and prefaced with an “of course,” proponents of this worldview argued that this linear and static evidence should be contextualized by human eth-ics and values [ 14 ] . On the other hand, with health care being increasingly delivered by industrial business or government conglomerates, these values are increasing dollar bottom lines [ 15 ] .
However, no healthcare system is static, linear, and appropriately assembled. Polarities, contradic-tions, and tensions in values arise from the “speci fi c perspectives” associated with the “special exper-tise” of the various “workers” in the healthcare sys-tem. These phenomena result in nonlinear dynamics, the constituent attribute of systems containing feed-back loops; this is the norm in all “socially deter-mined” systems, including healthcare systems.
Though there is no doubt that simple and com-plicated approaches to certain health service problems, like the time-out procedure in the oper-ating room to ensure the right patient is receiving the right operation, have been highly successful. The fundamental of simple and complicated approaches is the checklist, hailed as a major dis-ruptive innovation in health care, and has been copied from “the cockpit environment of planes” and “the pit stop” in motor car racing circuits [ 16 ] . Implemented as the “model for practice,” particu-larly in the operating room and emergency depart-ment environments, it has dramatically improved health-outcomes, reduced complications and saved lives. As in “the cockpit” checklist
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approaches to ensure the “proper predetermined” procedures focus individuals and teams to always perform the “correct simple and/or complicated steps” in a timely fashion.
However, the push to implement checklists to all healthcare environments has not proved particularly successful outside of these types of complicated instrumental activities. In particular, the attempt to transform primary care into “a sum of checklists,” such that if boxes are ticked pay-ments follow, 2 has not improved outcomes beyond existing trends such as the UK Quality and Outcomes Framework [ 17– 19 ] . What works well in some domains of health care such as operating theatres does not work well in many others such as primary care practices. Checking checklists, as pushed by some, is reduction ad absurdum .
45.1.2 Complexity Assumptions
Many technical as well as value questions will never be easily answered in their dynamic and ever changing challenging environments. We should re fl ect on our ancestors’ approaches that used many different skills in observing and responding to patterns in nature in order to live and survive by listening, feeling, and sensing. These are particu-larly useful strategies where phenomena are unpre-dictable, but need to be managed.
Making sense of options and dilemmas in a realistic time frame is essential to inform decision making in a complex healthcare system environ-ment [ 3 ] . How do we determine how to make sense of different approaches in and across differ-ent healthcare sectors? We suggest that learning
to engage with sense making dialogues and knowledge developments that aid decision mak-ing in complex adaptive clinical practice and health systems management. This is the way for-ward to address the pressing challenges as healthcare systems continue to struggle to adapt to changing internal and external constraints [ 20 ] .
Complexity science is a disciplined approach to studying complex adaptive systems. Complexity science provides a sophisticated approach to studying the complex adaptive sys-tems composed of numerous, varied, simultane-ously interacting parts or “agents,” from molecules or bacteria in a biological process, to individuals or businesses in an economy. Informatics leverages computing power and sophisticated software tools to signi fi cantly enhance decision making by applying analytical methodologies to massive amounts of data. Together, Complexity Science and Informatics, have impacted every industry from manufactur-ing to biotechnology, and can be leveraged for healthcare delivery and health system reform.
45.2 Sensemaking or Sense-making
Sensemaking [ 21 ] or Sense-Making [ 20 ] , 3 is essentially the process of people giving mean-ing to their experience, based on identi fi cation of patterns —either internal or external [ 22 ] . A pattern is a particular arrangement of ele-ments that constitute a model to be used or emulated. Patterns are patterns if they can do something, if they can cause something to occur with some regularity . … a pattern [is] an arrangement that expresses a reproducible and meaningful relationship between relatively independent components [ 23 ] . Although studied for centuries, and an essential part of biological
2 In 2004 a new contract between Primary Care Trusts (PCTs) and General Practitioner (GP) practices was nego-tiated. The new contract‘s centerpiece, the Quality and Outcomes Framework (QOF), included 146 check list tar-gets in four domains (clinical, organizational, patient experience, and other services), which are revised periodi-cally. The cost of QOF, around £600 million in the fi rst year, and around £1 billion thereafter, formed part of the planned increased investment in primary medical care ser-vices. “To date, there is no evidence that the high expendi-ture on QOF can be linked to improvements in health outcomes. The high expenditure on the program makes it critical to be sure that the performance improvement is not achieved at the expense of other more valuable initiatives, services, or nonmeasurable aspects of patient care.” [ 14 ]
3 The term “sensemaking” has primarily marked three dis-tinct but related research areas since the 1970s: Sensemaking was introduced to human–computer interac-tion by PARC researchers Russell, Ste fi k, Pirolli, and Card in 1993, to information science by Brenda Dervin, and organizational studies by Karl Weick. In information science the term is most often written as “sense-making.” In both cases, the concept has been used to bring together insights drawn from philosophy, sociology, and cognitive science (especially social psychology) [ 22 ] .
800 C.M. Martin and J.P. Sturmberg
survival mechanisms, “sensemaking” has devel-oped in distinct but related research areas since the 1970s.
Distinct but related research areas relevant to understanding health include the disciplines of mathematics, biological modeling, philosophy, sociology and cognitive sciences, communica-tion studies, complexity sciences, informatics, and knowledge engineering. Of particular impor-tance to making sense of patterns in different domains applicable to human health are:
Communications—Brenda Dervin [ • 20 ], Intelligence and multi-ontology sense- making: • the Cyen fi n framework—Dave Snowden [ 24 ], Organizational studies—Karl Weick [ • 25 ], Mathematical modeling—Bruce West [ • 26 ] , Stephen Guastello [ 27 ] , David Katerndahl [ 28 ] , and others, and Arti fi cial intelligence and informatics pattern • recognition—Eric Horwitz [ 29 ] , data-min-ing—David Riañ o [ 30 ] , and computational linguistics—Carl Vogel [ 31 ] Sensemaking has emerged as an area of inter-
disciplinary study in response to practical chal-lenges of knowledge management in health systems. It has three major streams pertaining to: the individual and real-time communications; orga-nizational sense making; and intelligence as in strategy, policy, and business [ 32 ] . In addition, mathematics, statistics, and computational systems are producing prediction with feedback models to help explain and understand emerging patterns in real world systems, especially in the fi elds of bioin-formatics, health informatics, and health system dynamics. Sense making is about identifying pat-terns and their meanings, so that best individual or collective responses can be made.
45.2.1 Patient-Centered Care Case Study: Applying Sense-Making
In order to demonstrate sense-making implica-tions, a real clinical case study is provided as an example. An extract from a care worker report January 27, 2012 describes brief narratives of “health and wellness” from the perspective of a chronically ill couple. It challenges the prevailing notion of protocol-based disease management.
Eileen Murphy (a 68-year-old lady who has suffered a bipolar type syndrome since her stroke and has multiple physical complaints)— Doing better today apart from a pain in her right eye, she thought it was the start of a migraine. Got advice from her pharmacist and has taken x2 paracetamol for same (had only taken them a few minutes before I rang) so she was hoping that would help. She is wearing a corset for her back. She was just discharged from hospital yesterday following 2 days in hospital for her “ collapse. ” Eileen may be going into respite next Monday for a week, home for a break on the weekend; and then back in again for 2 weeks. She was to be assessed between today/tomorrow re same at her house. If she deteriorates, she is to contact her PCP. She rates her health today as 8/10 .
Mick Murphy (Eileen’s husband and care-giver under stress with pressures of caregiving and his own medical problems include alcohol dependency)— In great form today, went to Alcoholics Anonymous meeting last night and really enjoyed it, (it always seems to give Mick a boost when he attends). He was a little stiff fi rst thing this morning when he woke up but was fi ne after an hour and no pain or soreness from fall yesterday. Is hoping wife Eileen gets into respite for a while this will give him a little break at home (although he will still be running errands for her while she is in respite). Granddaughter is doing fi ne so this is a weight off Mick’s mind. Feels a hundred per cent today 10/10.
45.2.2 Sense-Making: Dervin’s Concept of “Innocent Information”
Dervin is a leading theorist in the fi eld of com-munications. Her sense-making theory and research have arisen to address the gaps, tensions, and even contradictions among different ways of knowing and different levels of information in complex systems. The conceptual framework for sense-making [ 20 ] encompasses polarities that disrupt decision making and how conceptualiza-tions of information impede its development and use (Fig. 45.1 ).
“ Innocent information ” is a deliberate misnomer for idealized information that is true,
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value-free, and objective. Yet, in the real world, information is always socially constructed and subject to assumptions, bias, and distortions. The pervasive polarities of our times are shaped in particular directions by dominant professional, political, economic, and media discourses.
Dervin categorizes the main polarities as clear versus fuzzy, complicated versus complex and nonlinear, objective versus subjective, and research versus practice. These polarities are highly pertinent to the assumptions we make in our everyday discourses in medicine and health care. Dervin’s polarities can be modi fi ed for our purposes as:
Order versus chaos, • Explicit (quantitative) versus implicit (qualita-• tive and sensing) pattern recognition, Information (tacit) versus evidence (explicit), •
Autonomy versus collaboration, • Cognitive versus emotional, • Rule bound versus intuitive, • Mind versus body, and • Community versus individual. •
45.2.2.1 The Case Study: Personal Journeys Through Dervin’s Lens
The journey. The trajectory of Mick and Eileen’s processes to cope with Eileen’s psychological and physical state ( body and mind ) encompasses Mick’s drinking in the past and Eileen’s numer-ous hospital admissions. Although not drinking now, Mick is still vulnerable and he is recovering from a recent fall. Eileen has limited motivation or capacity for self-managing her health.
Bridges and Gaps . Mick’s narratives—Eileen is in and out of hospital and respite care, and he is
Fig. 45.1 Dr. Dervins original artwork of the Sense-Making Metaphor (reproduced under Wikimedia Commons)
802 C.M. Martin and J.P. Sturmberg
not happy about that. He feels that his wife is getting progressively worse mentally despite all her counseling and hospital admissions. Mick is going out walking as normal. Eileen’s narratives range from describing totally excellent health to major excursions in erratic behavior. “ while talk-ing to <Mick> on the phone, Eileen picked up the extension and was listening in and was shouting down the phone that he was a liar and a cheat and then hung up. ” Eileen fl uctuates in her self-care and smokes and does not take her medication properly and has had hospital admissions and admissions to respite care on a monthly basis.
Sense-making. Mick wants Eileen to go into permanent care. He feels well when she is being cared for by others, as she can become abusive and very demanding. Eileen wants to sell the house but still return to the community. Her cur-rent trajectory despite government subsidies is very expensive on the family fi nances.
Outcomes for the individuals . What makes this couple feel well today? The outcome that they both desired has been put in place albeit only in the short term—a hospital admission for Eileen.
The situation is at least temporarily resolved with brief institutional placement. There are fuzzy areas of interpersonal relationships and mutual dependence and frustration. The commu-nication of need is not innocent information , as the couple must express their wants for the caring burden to shift in such terms that the health system can diagnose and implement an appro-priate action.
Health, illness, and quality of life have been viewed through reductive lenses, similar to dis-ease approaches. Yet, the situation, meaning and process of construction of the individual experi-ence is highly personal and contextual. There is social and emotional and physical relief for both Eileen and Mick, and for a short time at least, both rate their health as very good, even though they have a poor outlook.
“Innocent information” about Eileen’s medical and psychiatric condition exists in the medical records mapping and de fi ning her clinical care. However, it is not innocent information that is pre-sented to the clinical providers, but information
constructed through the eyes of major actors and across many polarities. Information is an ongoing fl ow and dynamic. It is only by taking charge and con fi guring information that we can design truly responsive and ef fi cient care.
45.2.3 Sense-Making: The Cyne fi n Framework
Kurtz and Snowden [ 33 ] , based on a dynamic understanding of knowledge, view knowledge generation and knowledge management as a sense-making process. They used the Welsh term Cyne fi n (pronounced kun-ev’in) to describe the nature of knowledge simultaneously as a thing and a fl ow—knowledge being in constant fl ux. They explained the meaning of Cyne fi n in the following terms:
It is more properly understood as the place of our multiple af fi liations, the sense that we all, indi-vidually and collectively, have many roots, cultural, religious, geographic, tribal, and so forth. We can never be fully aware of the nature of those af fi liations, but they profoundly in fl uence what we are. The name seeks to remind us that all human interactions are strongly in fl uenced and fre-quently determined by the patterns of our multi-ple experiences, both through the direct in fl uence of personal experience and through collective experience expressed as stories (emphasis is ours) [ 33 ] .
A loose translation of the term is “ place of belonging ,” which is re fl ected in the Cyne fi n framework’s fi ve domains—the known where cause and effect relationships are generally linear, empirical, and not disputed; the knowable where cause and effect relationships exist but may not be fully known or only known by experts, gained through systematic methodolo-gies, and relies on trust; the complex or emer-gent, where cause and effect relationships can be perceived but not clearly de fi ned or predicted and events are fully understood only in retro-spect; the chaotic or random where no apparent cause and effect relationships are evident; and the central space of disorder where con fl icting views reside resulting from different perspec-tives on the same issue.
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“Medical knowledge is inherently uncertain, and we require a context-driven fl exible approach to knowledge discovery and application, in clini-cal practice as well as in health service plan-ning ” [ 34 ] . Thus, it is of utmost importance to understand “ knowledge” as a personal construct achieved through sense making. Speci fi c knowl-edge aspects temporarily reside in either one of four domains—the known, knowable, complex, or chaotic, but new knowledge can only be cre-ated by challenging the known by moving it in and looping it through the other domains ” [ 34 ] .
The knowledge distribution in medicine is depicted in Figure 45.2 . Different disciplines pre-dominantly practice and operate within one speci fi c domain, utilizing speci fi c knowledge dynamics. Standardization is achieved by devel-oping and adhering to protocols and checklists,
guidelines provide some discretion in decision making, pattern recognition relies to a large extent on sensing change before objective fea-tures are clearly evident, and “educated interven-tions” are the prerogative for chaotic situations. It is, however, important to realize that “[t] hough in clinical care we may operate predominately in one knowledge domain, we also will operate some of the time in the others ” [ 34 ] .
Complex adaptive systems science views knowledge simultaneously as a thing and a fl ow, as constructed, as well as constantly changing. Health knowledge is simultaneously explicit and implicit with certain aspects already well known and easily transferable, and others that are not yet fully known and must still be learned. At the same time, certain knowledge aspects are pre-dominantly concerned with content, whereas oth-
Fig. 45.2 The Cyne fi n model of knowledge in medicine
804 C.M. Martin and J.P. Sturmberg
ers deal with context. While some fi elds like primary care act predominantly in a complex person-centered environment and surgery acts in a simple and complicated environment, all require the whole gamut of knowledge types. The skill and art of sense making in clinical care and in healthcare systems is to identify different domains and knowledge fl ows to facilitate appropriate practices.
45.2.3.1 The Case Study—Clinical Practice: Simple, Complicated, or Complex
The following day, the situation progresses and Mick becomes ill as Eileen leaves for respite care. The strain of caregiving takes its toll, but also there is an element of guilt and loss.
Mick Murphy — Looking forward to having a break from Eileen for a few days. Exhausted today and has a bit of a cold, has been running around all morning trying to get Eileen ready to go into respite. Thinks he will be fi ne in a day or 2. Mick will be collecting some prescriptions from GP later in the week so if not feeling well then he will have a check-up with GP.
Eileen Murphy — ok as per Mick ’ s assessment. Went into respite today and will be there until Friday afternoon, they don ’ t have a bed over the weekend so Eileen will be home and will return to respite the following Monday for x2 weeks.
45.2.3.2 The Importance of Narratives According to Charon et al. [ 35 ] , there are three fundamental tensions upon which medicine fi nds itself (when coming from a medical evidence paradigm)—how to manage health when there is known and unknown lack of evidence, how to particularize the universal or average case from statistical analyses to the individual journey, and how to personalize or embody the evidence about the body for an individual experience and of the patient journey. Their formulation of “Narrative-Based Medicine” complements “Evidence-Based Medicine” in that:
Clinical evidence examines the known and unknown. Clinical circumstances integrate the uni-versal and particular. Patients’ values speak to both body and self. By virtue of its capacity to recognize
the tensions fully, narrative medicine can lend to evidence-based medicine the methods of respect-ing its three circles of attention [ 35 ] .
What is the evidence base that is the simple and complicated knowledge with which the clini-cal care system should manage the care of Eileen and Mick? Is it as straightforward as the right side of the Cyne fi n framework being integrated with the left side?
Can we identify evidence-based interventions that will improve outcomes and can we make sense of the narratives of Mike and Eileen? Is there best practice or even better practice in this case?
Cyne fi n thinking would probably have preferred integrating a variety of different stakeholder per-spectives and values, before unilaterally establish-ing what is best [ 36 ] . Reducing the known to the reductionist paradigm of science as “evidence” curtails a broader understanding of what is known and unknown about the nature of health. For exam-ple, interventions have demonstrated that better outcomes of care—signi fi cant decrease in hospital-izations, and signi fi cant decrease in emergency department visits, were associated with programs that had complex adaptive system characteristics—agents who learn, interconnections between agents, self-organization, i.e., order is created without explicit hierarchical direction; and coevolution, i.e., the patient, the healthcare providers and health system, and the environment in fl uence each other’s development [ 34 ] .
Perhaps, we will fi nd more useful information if we re fl ect on Bury’s types of patient narrative:
• Contingent narratives —belief about the ori-gins of disease, proximate causes in the illness journey, and the immediate impact of illness on physical health. Contingent narratives are most closely aligned with medical care and are personal and explanatory. Thus, health and ill-ness are intensely personal matters [ 37 ] . • Moral narratives —The second type of narra-tive identi fi ed by Bury [ 38 ] are moral narra-tives which explore the relation between the person, his/her illness, and his/her social iden-tity. This implies a threat to the individual’s inner and social being by the biological components of their own body. An individual experiences loss during falling ill. The worst biographical events are ones that bring about
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the loss of part of the individual’s and affect both function and survival. • Core narratives —The third type of narrative is a “core narrative” [ 38 ] that evokes the lay persons’ connection with the prevailing cul-tural meanings pertaining to illness and suffer-ing. Here, narratives can be seen to be “heroic, tragic, ironic, comic, or regressive-progressive.” In relation to the content of narratives, partic-
ularly the contingent, Martin [ 39 ] has pragmati-cally identi fi ed three narrative streams appropriate to clinical care: 1. Narratives of the person, their life stages, and,
if applicable, their caregiver. 2. Narratives of the body and the disease and ill-
ness that describe the trajectory through all phases of the illness.
3. Narratives of the treatment journey—from prevention to palliation such narratives include the personal narratives of the physicians, nurses, and all healthcare team members involved in patients’ healthcare journeys.
45.2.3.3 Returning to the Case Study Eileen’s narrative expresses her vulnerability, while Mick has a stoic and heroic narrative. Yet, when she goes into respite care, he becomes ill and “runs around looking for antibiotics” to keep him well. Both their bodies and minds are failing in different ways, due to the intense pressures of Eileen’s mental condition. It is a story of deterio-ration; yet hope that support through respite care will bring relief. There is no narrative about dis-ease on the devastation that disabling conditions have wrought—what is the root cause of what is making them ill? Thus, clinical care is challenged to make sense of how to “heal” people with com-plex states of health and illness, without proto-cols and standards to follow.
The polarities between the objective biomedi-cal and the subjective well being as the dominant discourses between health professionals and patients are evident. It would be futile to expect major changes in health outcomes for this couple, yet major improvements in improving quality of life and alleviating illness can be achieved by respite and supportive care in the case of this
couple. The tensions and contradictions of want-ing to be apart and yet wanting to stay together are delicately balanced.
45.2.4 Weick and Sensemaking
Weick, a leading theorist in organizations sought to uncover simple patterns underlying what appears to be complex organizational behavior [ 21 ] . The central approach to his ideas and theory building was to fi nd patterns that edit particulars into a more compact summary that allows people (including theorists) to anticipate and thread their way through the complexities of everyday social life. It is important to know that the project has been based on three central assumptions regard-ing communication practice (a) that it is possible to design and implement communication systems and practices that are responsive to human needs; (b) that it is possible for humans to enlarge their communication repertoires to pursue this vision; and (c) that achieving these outcomes requires the development of communication-based meth-odological approaches [ 40 ] . Environments coex-ist and to a large extent are created by the organization—the organization does not play a passive observational role but an active role in sense making and adaptation. Organizational sys-tems theory sees healthcare organizations as a living adaptive “organism” [ 41 ] . Fluctuations or contingencies from the environment are adjusted to by organizational change. The nature of change can be strategic—in health systems (e.g., offering new ways of care delivery), tactical (e.g., devel-oping closer relationships between key players and incentives) or cultural (e.g., offering staff training and support for change) [ 18 ] (Fig. 45.3 ).
45.2.4.1 The Case Study: Changing Personal Journeys Applying Weick’s Lens
The original healthcare organization—the hospi-tal—cared for the ill, the vulnerable, and the poor. As the modern Medical Industrial Complex (MIC) emerged due to ecological changes in technolo-gies, culture, and expectation, hospitals and healthcare organizations changed. Standardized
806 C.M. Martin and J.P. Sturmberg
work processes and practice became the norm for mass delivery of health care. This process ignores the enactment, organizing, and sensemaking feed-back loops identi fi ed by Jennings [ 41 ]. Yet like the earlier QOF example, results in high expenditures on standardized activities at the expense of other more valuable initiatives, services, or nonmeasur-able aspects of patient care . In this case, there are no ways to deal with the care of Eileen and Mick, who fall outside the metrics, yet utilize signi fi cant public and private resources. How can we sensi-tize health systems to the real ecology of real patient journeys, rather than to the pro fi t margins of large and small investors? The Medicare Innovation Fund is seeking to transform American medicine and health care to do just that, but it needs to make progress on sensitizing care incen-tives to respond to more complex cases [ 42, 43 ] .
45.2.4.2 Implications for Healthcare Practice
Taking on leadership in complex health organiza-tions, Thygeson, Morrissey, and Ulstad [ 44 ] using organizational complexity models, espoused ini-tially by Heifetz [ 45 ] , translate organizational learn-ing into adaptive leadership in the doctor–patient relationship. These approaches seek to make sense of emerging identities, enactments, and dynamic feedback between the external and internal health
system ecology. Adaptive leadership by de fi nition straddles the polarities, tensions and contradictions of the clinical encounter, and the higher levels of clinical care and healthcare organizations. It will be interesting to see how the work of the clini-cian, demonstrated by Katerndahl et al. [ 46 ] , evolves with more emerging frameworks and innovative leadership models.
45.2.4.3 The Case Study: Applying the New Lens
In relation to the case study, the organizations that treat and manage the care of Eileen and Mick need to recognize the real nature of their journey, rather that deliver standardized “disease manage-ment,” standardized “behavioral health,” and standardized chronic illness “self-management,” which have no impact on their deterioration.
The ecology of health care will continue to change rapidly. The democratization of social media and networking and the pervasive pressure from internet technologies, which increasingly shifts the process of personal meaning making, to online and collective sensemaking. However, will this participation be truly innocent or will the loudest voices rather than the voices of the disempowered, chronically ill, and less educated be swamped by others more articulate and well resourced.
Fig. 45.3 The relationship among enactment, organizing and sensemaking (Source: Jennings and Greenwood 2002 [ 40 ] who adapted from Weick 1979;139 [ 41 ])
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45.2.5 Another Way of Sensemaking: Informatics, Computations and Modeling
Alan Turing, Benoit Mandelbrot, and John von Neumann among others pioneered the mathemat-ical and computational analyses of complex sys-tems. An important aspect of their work is the appreciation of the initial condition of the system before entering new information; even very small difference at the start can result in very major dif-ferences after even few iterations. Adding new information to a system impacts on its feedback processes which in turn shape the behavior of complex interacting systems.
Some systems with many interactions among highly differentiated parts produce surprisingly simple, predictable behavior (such as a program-mable mechanical routine or process), while oth-ers generate behavior that may be impossible to predict, even though these systems feature simple laws and few actors or agents (e.g., the mathematic equation resulting in the Mandelbrot set) [ 47 ] .
This early work has been taken further by others and forms the basis for modern information systems in health care [ 48 ] . Being able to handle a vast amount of clinical data has the potential to bring about large improvements in clinical, admin-istrative, and fi nancial healthcare delivery.
Analyzing large datasets, particularly where the data have been merged from several sources, intro-duces problems of data integrity and noise. The challenge is to transform these data into informa-tion that then can be turned into new knowledge.
Machine learning and predictive modeling are techniques used in data mining 4 and have the potential to facilitate the examination of the dynamics of disease and the improvement of clini-cal quality. By its nature the fi eld of complex adap-tive systems deals with environments that change because of the interactions that have occurred in the past . Health informatics and bioinformatics already successfully use machine learning meth-ods to stratify patients who need intensive support to keep them from having multiple expensive hos-pitalizations [ 49 ] yet such analytics can only go so far in understanding the complexities of the human journey and relationships (Fig. 45.4 ).
45.2.5.1 The Case Study: Applying this Lens
In our case study, in order to understand how Mick and Eileen arrived at their current health destina-tions, it is important to understand the initial
Fig. 45.4 Example of Machine Learning Concepts (See Chap. 27 Table 27.1 for more information)
4 For example, cluster analysis, principle component anal-ysis, decision tree learning, Bayesian network models, arti fi cial neural networks, and genetic programming.
808 C.M. Martin and J.P. Sturmberg
conditions of their situation. Eileen was involved in a car accident, with Mick driving, which resulted in her injured spine. Their complex relationship, his drinking, her bipolar diagnosis all stem from the car accident—the initial condition —for their current “organization” of their life.
A healthcare system whose initial condition is a small business model that morphs into a large business model, has as its key internal attractor “ fi nancial gain”, which makes adapting to the “external health needs of people” a tension, if not a contradiction. Service strategies and patient need and expectation are unlikely to meet.
45.2.5.2 Changing the Organization of Practice, Research, and Knowledge
The introduction of clinical changes is a cyclic task, meaning that the processes under examina-tion operate in an environment that is not static. Traditional linear methods of analysis cannot address the nonlinearity and recursive feedback loops, that complexity and chaos theory and arti fi cial intelligence and machine learning are designed to achieve [ 50 ] .
Continuous fl ow of information is now possible and increasingly essential. The time it takes to cycle and feedback information must be as short as possible—and real time in many situations. On the other hand, one needs time for systems to reach some level of stability in order to function well and this takes time. Re fl ection is needed, even in sys-tems like healthcare delivery that are fast paced.
Although these technologies greatly enhance information fl ow and information quality, this does not automatically equate to providing better knowledge that would result in wise decisions. Cilliers pointed to the importance of a certain slowness for the effective and ef fi cient function-ing of a complex adaptive system [ 51 ] . Sturmberg and Cilliers highlighted the implications of such slowness to medical practice—time is required to humanize medical care [ 52 ] .
Health 2.0, the Democratization of Health Care The rapid developments within the communica-tions and electronics industries have challenged
our views about health and disease and the roles and responsibilities of patients and doctors. One of the outcomes is Health 2.0 , which has resulted in a “democratization” of medical knowledge. Though this both disrupts old ways of “doing business” and provides “new opportunities,” it has its very real own problems. Hughes et al. [ 53 ] highlight four major problems that require care-ful attention: the lack of clear de fi nitions; the loss of control over information as perceived by doc-tors; the safety and accuracy of information; and issues of ownership and privacy of the informa-tion collected.
Providing healthcare workers and their clini-cal systems the ability to detect when an abnor-mal condition has occurred and immediately address the problem is central to Health 2.0 . This enables operations to build-in quality at each pro-cess and to separate men and machines for more ef fi cient work (Fig. 45.5 ).
Continuous Quality Improvement in Health Care Many of the continuous quality improvement strategies in healthcare have been adopted from the Toyota Production System (see Appendix). Jidoka, along with just-in-time, are the two pil-lars of this system. Jidoka is sometimes called autonomation, meaning automation with human intelligence. It is a quality control process that involves four principles: (1) detect the abnor-mality; (2) stop; (3) fi x or correct the immediate condition; and (4) investigate the root cause and install a countermeasure. It is a system of pro-duction that makes and delivers just what is needed, just when it is needed, and just in the amount needed. Continuous improvement of an entire value stream or an individual process can create more value with less waste. There are two levels of improvement: (1) system or fl ow improvements that focus on the overall value stream and (2) process improvements that focus on individual processes. These approaches have, e.g., been applied in clinical delivery of better timed insulin administration systems [ 54 ] , as well as quality improvement in organi-zational behavior [ 55 ] .
80945 Making Sense: From Complex Systems Theories, Models, and Analytics to Adapting Actions…
Solving “Wicked” Problems The Complex Network Electronic Knowledge Translation Research Mode l 5 [ 56 ] represents an attempt to address complex problems, like health promotion, using a social organizing approach based on complexity science, social learning the-ories, design thinking, and models of knowledge exchange, translation, and integration. The model, developed by Norman and his colleagues, approaches sense making across polarities of knowledge and values by mobilizing the diverse strengths and knowledge of multiple key stake-holders. The “new” knowledge about complex problems provides the basis for creating viable response options within the constraints of exist-ing public health and healthcare practices.
45.3 Discussion
Sense-making emerges as a transdisciplinary process. The seamless exchange of knowledge and research approaches across traditional disci-plinary silos provides new ways of conceptualiz-ing and addressing systemic questions and solutions [ 21 ] .
Key components that contribute to sense- making include [ 22 ] the following:
Identifying polarities, contradictions and ten-• sions in health systems knowledge—including nonlinear linear patterns in quantitative research, diverse values and perspectives, Identifying the predominant appropriate pat-• terns for different health related activities—from checklists to probing and sensing, and to creative problem solving, Developing the intellectual foundation for • multiple ways of knowing with a neutral space for negotiation, discourse and con fl ict resolu-tion; with the development of A system of values that is open, participatory, • respectful and focused on the “real world” of individuals, and Principles for communication and leadership. • “Innocent information” that is shaped by the
pervasive polarities of our times and the direc-tions by dominant professional, political, eco-nomic, and media discourses, must be continually challenged by democratizing processes of sense-making and decision making. Increasingly, this should be accomplished by engaging patient as central to the process.
Around a time of major health system reform, primary care doctors in the USA are re fl ecting on
Fig. 45.5 A model of Health2.0 (reproduced under Wikimedia Commons)
5 For more details, see Norman and Yip., Chap. 34 .
the increased “complexity” in their everyday clinical encounters as reported in the US doctor’s “National Ambulatory Medical Care Survey” database. Katerndahl, Parchman, and Wood pro-vided an analysis of doctor sense-making on the nature of “complexity” in primary care practices, based on these responses [ 28 ] . What doctors mean by “complexity” is fuzzy and potentially not objective or accurate, and whether they mean complicated or complex in the sense of complex-ity science is not clear. In a recently published analysis of the same National Ambulatory Medical Care Survey database, Katerndahl et al. propose a historical and innovative analysis of the (informational, computational, and cognitive) complexity of doctors’ reporting of their con-sultations [ 28 ] . In the US context, primary care doctors are perceived by decision makers to operate a lower order of cognitive sophistication compared to other medical specialties such as cardiology or psychiatry. However, when shifting the perspective from relative work value based on the severity of illness or disturbance of a con-strained bodily system such as in cardiology or psychiatry with a limited range of problems and therapies to analyzing diversity and variability of clinical processes [ 28 ] , family medicine patterns demonstrated a greater diversity of diagnostic and knowledge inputs with more treatments and other outputs and less time to process these cogni-tive steps.
They represent another form of sense making with nonlinear modeling using information theory and computational complexity. A series of polarities and questions emerge for further research and analy-sis, and ultimately decision and policy making.
Are these data accurate or inaccurate, clear or unclear, complex or complicated? Does increas-ing diagnostic and therapeutic diversity, and broadening scope of practice from cradle to grave in rapidly changing social contexts, amount to increasing complexity and thus increased work value for family medicine? Further in-depth analysis of the actual work of decision making and sense-making in clinical practice by doctors, patients and others, linked to current research on clinical decision support,
would produce valuable outputs [ 13 ] . This would provide interesting insights into work activities across clinical specialties and health systems. Of course whether the relative “complexity” of work can be based on linear descriptors of work though is arguable.
45.4 Conclusions: A Complex Systems Framework for a Vision for Healthcare
In order to make positive changes in a shared manner with patients to improve their health, it is important to have a theoretical framework to understand the system and system level states, in which their health journey takes place. The framework of the “complex adaptive system” de fi nes the scope, boundaries, and limits; it locates the current state in relation to shared vision, values, and goals [ 57 ] .
The vision and goals of a system provide leverage points where speci fi c interventions are most likely to be effective for a “whole of sys-tems” change, and thus a greatest potential for improvement of system performance [ 58 ] . The key unit of knowledge and understanding is the pattern that cuts across linear and nonlinear rep-resentations of the real world in the form of evi-dence, narrative and stories, tacit and explicit information and experiences.
A framework for understanding and interven-ing in the system of an individual patient narra-tive would contain four types of leverage points around pattern identi fi cation at different health system levels: 1. Values/beliefs leverage points
Related to the intrinsic philosophy that is • fundamental to the individual’s experi-ence of care.
2. Goals leverage points Related to the expectations and intended • outcomes of interventions change.
3. Information leverage points Related to the availability of narrative • feedback to health professionals and system stakeholders.
81145 Making Sense: From Complex Systems Theories, Models, and Analytics to Adapting Actions…
4. Structures leverage points Related to speci fi ed roles, responsibili-• ties, and authorities that de fi ne the bound-aries of the patient journey and enable a healthcare provider to perform their functions.
Sensemaking about different levers in health systems range from the micro- to the macro-levels, all of which are highly interconnected (Fig. 45.6 ).
In conclusion, there are narratives and a range of emerging typologies of narratives. In order to make sense of these narratives, it is important to identify a clear frame of reference with the aim of locating the narratives under consideration in their appropriate theoretical, conceptual and operational frameworks. Only then, one can iden-tify and make sense of the rich patterns that emerge from our patients’ stories in everyday practice, and link them to the increasingly com-plex knowledge of interdependencies of human biology and environments. Clinical care and
larger health ecosystems inevitably shape and should be shaped by their patients’ narratives and experiences.
45.5 Appendix
The underlying principles, called the Toyota Way, have been out-lined by Toyota as follows: Continuous improvement
• Challenge (We form a long-term vision, meeting challenges with courage and creativity to realize our dreams.) • Kaizen (We improve our business operations continuously, always driving for innovation and evolution.) • Genchi Genbutsu (Go to the source to fi nd the facts to make correct decisions.)
Respect for people • Respect (We respect others, make every effort to understand each other, take responsibility and do our best to build mutual trust.) • Teamwork (We stimulate personal and professional growth, share the opportunities of development and maximize indi-vidual and team performance.)
External observers have summarized the principles of the Toyota Way as:
Long-term philosophy • Base your management decisions on a long-term philosophy, • even at the expense of short-term fi nancial goals.
The right process will produce the right results
Fig. 45.6 Sense making with different approaches at multiple interconnected health system layers within a complex adaptive systems framework
812 C.M. Martin and J.P. Sturmberg
Create continuous process fl ow to bring problems to the • surface. Use the “pull” system to avoid overproduction. • Level out the workload (heijunka). (Work like the tortoise, not • the hare.) Build a culture of stopping to fi x problems, to get quality right • from the fi rst. Standardized tasks are the foundation for continuous improve-• ment and employee empowerment. Use visual control so no problems are hidden. •
Use only reliable, thoroughly tested technology that serves your people and processes.
Add value to the organization by developing your people and • partners Grow leaders who thoroughly understand the work, live the • philosophy, and teach it to others. Develop exceptional people and teams who follow your com-• pany’s philosophy. Respect your extended network of partners and suppliers by • challenging them and helping them improve.
Go and see for yourself to thoroughly understand the situation • (Genchi Genbutsu). Make decisions slowly by consensus, thoroughly considering • all options (Nemawashi); implement decisions rapidly. Become a learning organization through relentless re fl ection • (Hansei) and continuous improvement (Kaizen).
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