INTRODUCTION

The art and praxis of care management is a contextually embedded one; not only is it reliant on the nature of the care giver-patient relationship but also the coming together of a tethered eco-system of location, information and infrastructure. While penetration of the internet of things is providing opportunities for creating tools to diagnose patient conditions and care plan interventions, caregiving offers specific challenges related to the situational and the emotional hubris surrounding the roles and relations between caregivers and the patient who are united by more than the bond of caregiving. Alongside the emotional and exhausting interpersonal exchanges that happen in caregiving scenarios, multiple caregivers, including non-professional, informal and familial caregivers are needed to loop the eco-system of care management. The use of pervasive computing for perpetual and assured gathering of patient data presents an opportunity to not only have deeper understanding of patient’s condition but also to engage various stakeholders in caregiving ecosystems; perhaps to even engender patient-centric technologies with humane overtones.

This paper will offer an instantiation of how ethnographic methods have approached big data – by big data we mean various types of quantifiable data in a caregiving situation encompassing key persons, stakeholders, caregiving practices and contextual contingencies. Making a case for big data and ethnography as a relationship in generating interpretative insights based on human behaviors [what Curran [2013] references as ‘Big Ethnographic Data’] we dwell on a research contribution towards transforming consumer centric healthcare services. In the attempt to offer a method to consistently monitor and capture a data eco-system in the everyday of a patient-caregiver relationship, we offer an account of the capture and intermeshing of different types and quality of data sources and their gainful deflection into a methodological protocol for ethnographic engagements. We call this the ‘360° feedback’ ethnography and elaborate its underlying methodological process in this paper. In a sense this paper is less about the ethnography and more about an approach assimilating the sensibilities of big data and ‘thick data’.

Previous research (Fiore-silfvast and Neff 2013) talks about data valences in digital health data ecosystems, and comments about the relevancy of data in social, organizational and institutional scenarios. Even if patient mediated or pervasively captured patient-end health data, such as the one proposed by Human API (Baek et.al. 2013), are obtained simultaneously, the impact of invisible work (Unruh and Pratt 2008) and the caregiver’s participation (Corbin and Strauss 1985) in chronic disease management remains, well, invisible! Perhaps the live nature of every care activity can provide a 360° knowledge of care delivery and further improve care interventions [Interestingly, in the domain of customer experience consulting, ethnographers (Slobin and Cherkasky 2010) have emphasized data acquisition to gathering customers’ experiential understanding. They call this “360 view of my customer”]. Given the diverse profiles of caregivers, multitudes of processes and information exchanges, and the longitudinal nature of chronic disease progression, having a 360° view of the care ecosystem becomes even more important.

An ethnographic study with 22 patients from 18 families in three tier-two [ cities with under a million population] in India foregrounded the study to capture the eco-system of care management knowledge – the latter included a plethora of players and their relationship to care management. We chose smaller cities where care giving is more familial and not outsourced to a hospital [ more common in the big metropolises of India due to better hospital infrastructure ]but nonetheless intersect with professional caregiving practices. It gave us a snapshot of the dynamic challenges faced by caregivers within a family and a window to think about opportunistic technology interventions. Our initial assumption centred around non-adherence to medication, unobserved disease symptoms and missing information requiring continuous involvement, attention, and coordinated dialogue exchanges among and between the diverse sets of patient – caregiver duos. Moreover, whether remote or situated, caregiving is mediated through psychic-emotional closeness between the caregiver and patient with consequences for care outcomes. There is a critical need for building communication strategies catering to a caregiver’s involvement in the care process, integrating their knowledge and experience in a specific patient monitoring ecosystem. We address this gap capturing patient and caregiver knowledge into a caregiving ontology (CO).¹ The knowledge categories we generated about caregiving protocols and ensuing relationships are directly informed by our ethnographic observations of caregiving in the Indian family.

Ethnographic vignettes gathered from homes and contextual scenarios presented motley arrangements of between caregiver-patient relationship dynamics. We explain these scenarios through a trust-persuasion relationship quadrant, representing the different scenarios and extent of trust and persuasive strategies among patient and caregivers depending on care availability and the nature of caregiver-patient kinship /social ties. We further substantiate our findings via a technology probe called iSwear including the patient-caregiver communication repertory, a feedback mechanism about the patient’s everyday care regime, patient information about physical activity and adherence or the lack of it to everyday medicine in-take and consequent changes in communication patterns caused to regular patient – caretaker communication behaviours. We created knowledge categories of care [we also call it care ontology, CO]that considers, not just the patient’s clinical and activity data but the collaborative nature of caregiving, multiple care communication protocols entailing accurate and generative knowledge of a care ecosystem. The knowledge categories or CO, are built from accounts of patient data which are periodic [sometimes self-recorded or fetched from the wearable we designed], and caregiver data such as situated availability, knowledge and extent of participation in care. Contextual interviews during the iSwear pilot study and logs fetched from iSwear helped us to map caregiver profiles based on care contribution and patient-caregiver trust levels. While Caregiver profiles and their relationship to the patient were vital , capturing right amounts of patient care feedback data, at critical moments of caregiving helped to comprehend not only a specific care ecosystem but to evolveg a generalizable and ontological understanding of communication practices in the patient-caregiver everyday repertory. And, we call this ‘a ‘360° Feedback’ ethnography of chronic Care knowledge generation’.

This paper is arranged to reflect the primacy of the ethnographic process in framing caregiving praxis and knowledge categories of care management. We begin with an in-situ understanding of familial care giving segueing into design implications and the actual building of the wearable iSwear aiding communication protocols of chronic care management. We then elaborate the generation of a care ontology/CO, focussed on the centrality of the caregiver’s relationship to the patient, routines/praxis of caregiving and types of everyday communication protocols between the care giver and patient. We reiterate that this paper is as much a piece on the ethnographic method as it is an approach to synthesise ethnographic insights with the generation of a data eco-system.

OVERVIEW

Over the last decade studies have emerged around social, economic, and health concerns of general ageing (Vines et.al. 2015) and chronic diseases in particular (Wanger et.al. 1999). Patient compliance in health care is one of the significant factors under research scrutiny. We begin the literature review with an overview of Chronic Disease Management (CDM) and the role of caregiver in care delivery. We move on to the social and structural context in the family caregiving scenario in order to understand the relationship dynamics in caregiving, role-playing, construction of trust and their effects on patient motivation and emotional support. Finally, we look at how technologies have evolved to assist chronic disease management, and how this data could benefit care interventions.