Anticipatory Care in Potentially Preventable Hospitalizations: Making Data Sense of Complex Health Journeys

Abstract

Purpose: Potentially preventable hospitalizations (PPH) are minimized when adults (usually with multiple morbidities ± frailty) benefit from alternatives to emergency hospital use. A complex systems and anticipatory journey approach to PPH, the Patient Journey Record System (PaJR) is proposed.Application: PaJR is a web-based service supporting ≥weekly telephone calls by trained lay Care Guides (CG) to individuals at risk of PPH. The Victorian HealthLinks Chronic Care algorithm provides case finding from hospital big data. Prediction algorithms on call data helps optimize emergency hospital use through adaptive and anticipatory care. MonashWatch deployment incorporating PaJR is conducted by Monash Health in its Dandenong urban catchment area, Victoria, Australia.Theory: A Complex Adaptive Systems (CAS) framework underpins PaJR, and recognizes unique individual journeys, their dependence on historical and biopsychosocial influences, and difficult to predict tipping points. Rosen's modeling relationship and anticipation theory additionally informed the CAS framework with data sense-making and care delivery. PaJR uses perceptions of current and future health (interoception) through ongoing conversations to anticipate possible tipping points. This allows for possible timely intervention in trajectories in the biopsychosocial dimensions of patients as “particulars” in their unique trajectories.Evaluation: Monash Watch is actively monitoring 272 of 376 intervention patients, with 195 controls over 22 months (ongoing). Trajectories of poor health (SRH) and anticipation of worse/uncertain health (AH), and CG concerns statistically shifted at a tipping point, 3 days before admission in the subset who experienced ≥1 acute admission. The −3 day point was generally consistent across age and gender. Three randomly selected case studies demonstrate the processes of anticipatory and reactive care. PaJR-supported services achieved higher than pre-set targets—consistent reduction in acute bed days (20–25%) vs. target 10% and high levels of patient satisfaction.Discussion: Anticipatory care is an emerging trajectory data analytic approach that uses human sense-making as its core metric demonstrates improvements in processes and outcomes. Multiple sources can provide big data to inform trajectory care, however simple tailored data collections may prove effective if they embrace human interoception and anticipation. Admission risk may be addressed with a simple data collections including SRH, AH, and CG perceptions, where practical.Conclusion: Anticipatory care, as operationalized through PaJR approaches applied in MonashWatch, demonstrates processes and outcomes that successfully ameliorate PPH.

How to cope with uncertainty? Start by looking for patterns and emergent knowledge

“…Patterns encompass some random, stochastic as well as some very stable almost linear patterns, however, most patterns in complex systems are ‘in‐between’. These ‘in‐between’ patterns show some ‘remarkably high’ degree of predictability which allows the observer to make sense (for a detailed discussion on sense‐making see Kurtz and Snowden 42 ) of the ‘emerging information’ and to anticipate potential future behaviours 36 …”

“…[28][29][30] This has been successfully applied to all scales of problems. Examples include: understanding the genetic components of aging 31 or the variability of clinical behaviours in glioblastoma multiforme 32 at the microlevel, the understanding of health 33,34 and the trajectory of patients' health and healing journeys, [35][36][37] the management of an epidemic like SARS-CoV-2, 38 improving the health of indigenous people, 39 or ending neglected tropical diseases at the health policy level. 40 An inevitable final question arises: What stands in the way of adopting systems thinking in the medical setting?…”

“…These 'in-between' patterns show some 'remarkably high' degree of predictability which allows the observer to make sense (for a detailed discussion on sense-making see Kurtz and Snowden 42 ) of the 'emerging information' and to anticipate potential future behaviours. 36 In addition, 'path dependence', 'historicity' and 'retrospective coherence' significantly limit the capacity for 'prescriptively' externalizing of research based on assumptions of linearity. Such research can never deliver its findings as knowledge or facts.…”

'False accountability’: The harmful consequences of bureaucratic rigour for aged care residents

“…Anticipatory care that takes particular note of the person's self-rated health, health concerns and anticipated changes in health has shown a reduction in preventable morbidity, hospitalisation and mortality. [13][14][15][16] Effectiveness/complication rates and quality of care/life would be relevant outcome-focused accountability measures to show the performance of an 'aged care facility as a whole'. 17 production, that 'doing things right' will result in the desired outcomes; unfortunately, the reality of aged care shows that it frequently does not.…”

Physiological Balance of the Body: Theory, Algorithms, and Results

“…Im- Based on these indicators, so-called dynamic indicators of resilience (DIORs), an algorithm for assessing the risk of catastrophe for ecological systems has been proposed [11]. In clinical practice, an anticipatory care system for patients approaching a tipping point stage has been successfully tested [12]. To determine the risk groups in the population exposed to unfavorable anthropogenic influences, we have to identify groups demonstrating dramatically increased frequency of fixation of certain pathological processes.…”