'The Issue with that sort of Data?'

Tendedez, Helena; Ferrario, Maria Angela; McNaney, Róisín

doi:10.1145/3311957.3359464

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…While PATs are often enthusiastic about sharing the data with HCPs, "Patients also wanted to use their data to get recognition for their efforts and to show their doctor they take their health plan seriously" [23] HCPs are concerned about a shift of responsibility as they might be more accountable for the data shared by the patients: "Clinicians were concerned that by having continuous access to patient data, they would become responsible for monitoring that data for concerning changes that may be indicative of a mental health crisis, such as a manic episode or a suicide attempt" [24] and feel an obligation to interpret and explain the data: "Simply" receiving patient-generated data around daily symptoms created a feeling of an "obligation to act" for the clinicians" [25]. Moreover, with the capability of remote monitoring, PATs "want to have the ability for their physician to conduct remote monitoring to verify the treatment plan is working and to pick up early warning signs of relapse or deterioration" [26].…”

Section: Patient-provider Relationship (Ppr)mentioning

confidence: 99%

Barriers and Enablers in Integrating Patient-Generated Health Data for Shared Decision-Making Between Healthcare Professionals and Patients: A Scoping Review (Preprint)

V S Pakianathan,

Kumar,

Jayatissa

et al. 2024

Preprint

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BACKGROUND Advancements in technologies and increased adoption of wearables and smartphones by individuals have led to an abundance of patient-generated healthcare data. These data, when used effectively, could help to further augment the process of shared decision-making to enable patient-centred care. However, the possible utilization of patient-generated (health) data (PGHD) introduces complexities and challenges which warrant considering both health care professional and patient perspectives. OBJECTIVE Summarize the relevant works in the past 10 years from the perspectives of the key stakeholders – healthcare professionals (HCPs) and patients (PATs) - on potential barriers and enablers to the integration of PGHD for shared decision-making. By looking at both perspectives, we are able to identify the key challenges and opportunities with PGHD throughout the patient’s journey. METHODS Electronic searches were done 3 databases – PubMed, ACM Digital Library and IEEE. Enablers and barriers mentioned by the stakeholders in included papers were extracted. Thematic analysis was performed using a qualitative analysis software, MaxQDA. The six-stage workflow model initially proposed by West at al was used as a reference for deductive coding. Subsequently, considering barriers and enablers faced by both the HCPs and PATs uncovered various tensions and alignments of perspectives which could be addressed in future work and can inform concepts, designs and development in the area of PGHD for shared decision-making. RESULTS Fifty-three publications were included in the scoping review. Six main overarching themes for barriers and enablers were identified: 1) Patient-Provider Relationship, 2) Patient Characteristics, 3) Organizational Factors, 4) Medical Ethics and Law, 5) Data-driven workflow and 6) Design and Technology. The six-stage workflow was further expanded based on the new findings.to include four additional stages which include contextual considerations outside of traditional clinical environments. In addition to partially corroborating previously established barriers in the six-stage workflow model, several new barriers and enablers were identified throughout all stages. This model helps to further align needs of HCPs and PATs beyond the clinical setting and could benefit system designers who plan to integrate DHTs involving PGHD for shared decision making. CONCLUSIONS This scoping review demonstrates that there are several factors to consider for effectively integrating PGHD in health-related shared decision-making. Notably, such factors extend outside the boundaries of traditional clinical settings. Although there is agreement between HCPs and PATs on certain factors, there are also tensions to be addressed. Our findings suggest that apart from lifting the barriers to the integration of PGHD, there can be a role for digital health technologies in mediating alignment between HCPs and PATs on effectively using PGHD for SDM.

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Section: Patient-provider Relationship (Ppr)mentioning

confidence: 99%

Barriers and Enablers in Integrating Patient-Generated Health Data for Shared Decision-Making Between Healthcare Professionals and Patients: A Scoping Review (Preprint)

V S Pakianathan,

Kumar,

Jayatissa

et al. 2024

Preprint

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“…How should systems structure interactions to assess and cross-check entered data to ensure high veracity that does not burden HCPs (c.f. [40])?…”

Section: Challenges and Research Questionsmentioning

confidence: 99%

“…Future patient-facing tools and services will need to motivate and support patients in their efforts to not only track and share data with the clinicians, but also provide advice [40] and facilitate sense-making and self-reflection to support care decision-making in daily life in collaboration with their carers and HCPs [9]. Patients might further be seeking consolation, encouragement, and other emotional support.…”

Section: Introductionmentioning

confidence: 99%

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Identifying Challenges and Opportunities for Intelligent Data-Driven Health Interfaces to Support Ongoing Care

Knoche

Abdul‐Rahman

Clark

et al. 2023

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

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This workshop will explore future work in the area of intelligent, conversational, data-driven health interfaces both from patients' and health care professionals' perspectives. We aim to bring together a diverse set of experts and stakeholders to jointly discuss the opportunities and challenges at the intersection of public health care provisioning, patient and caretaker empowerment, monitoring provisioning of health care and its quality. This will require AI-supported, conversational decision-making interfaces that adhere to ethical and privacy standards and address issues around agency, control, engagement, motivation, and accessibility. The goal of the workshop is to create a community around intelligent data-driven interfaces and create a road map for their future research.CCS Concepts: • Human-centered computing → Human computer interaction (HCI).

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“…Concerns about responding to data can impact HCPs' desire to integrate data into their workflow [88,[91][92][93]. This relates to the human-data interaction challenge of agency, regarding acting on data and its implications [46].…”

Section: Support and Clear Processes Are Needed When Interacting With...mentioning

confidence: 99%

Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study (Preprint)

Tendedez¹,

Ferrario²,

McNaney³

et al. 2021

Preprint

Self Cite

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BACKGROUND When caring for patients with chronic conditions like Chronic Obstructive Pulmonary Disease (COPD), healthcare professionals (HCPs) rely on multiple data sources to make decisions. Collating and visualizing this data, for example on clinical dashboards, holds potential to support timely and informed decision-making. Most studies about data supported decision-making (DSDM) technologies for healthcare have focused on their technical feasibility or quantitative effectiveness. While these studies are an important contribution to the literature, they do not further our limited understanding of how HCPs engage with these technologies and how they can be designed to support specific contexts of use. To progress our knowledge of this area, we must work with HCPs to explore this space and the real-world complexities of healthcare work and service structures. OBJECTIVE This research aimed to qualitatively explore how DSDM technologies could support HCPs in their decision-making about COPD care. We created a scenario-based research tool, called Respire, that visualized HCPs’ data needs about their COPD patients and services. We used Respire with HCPs to uncover rich and nuanced findings about human-data interaction in this context, focusing on the real-world challenges that HCPs face when carrying out their work and making decisions. METHODS We engaged nine respiratory HCPs from two collaborating healthcare organizations to design Respire. We then used Respire as a tool to investigate human-data interaction in the context of decision-making about COPD care. The study followed a co-design approach that had three stages and spanned two years. The first stage involved five workshops with the HCPs to identify data-interaction scenarios which would support their work. The second stage involved creating Respire, an interactive scenario-based web application that visualized HCPs’ data needs, incorporating feedback from the HCPs. The final stage involved 11 one-to-one sessions with HCPs to use Respire, focusing on how they envisaged it could support their work and decisions about care. RESULTS We found that: (1) HCPs trust data differently depending on where it came from and who recorded it; (2) sporadic and subjective data generated by patients has value but creates challenges for decision-making; and (3) HCPs require support interpreting and responding to new data and its use cases. CONCLUSIONS Our study uncovers important lessons for the design of DSDM technologies to support healthcare contexts. We show that while DSDM technologies have potential to support patient care and healthcare delivery, important sociotechnical and human data interaction challenges influence how these technologies should be designed and deployed. Exploring these considerations during the design process can ensure DSDM technologies are designed with a holistic view of how decision-making and engagement with data occurs in healthcare contexts.

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'The Issue with that sort of Data?'

Cited by 7 publications

References 11 publications

Barriers and Enablers in Integrating Patient-Generated Health Data for Shared Decision-Making Between Healthcare Professionals and Patients: A Scoping Review (Preprint)

Barriers and Enablers in Integrating Patient-Generated Health Data for Shared Decision-Making Between Healthcare Professionals and Patients: A Scoping Review (Preprint)

Identifying Challenges and Opportunities for Intelligent Data-Driven Health Interfaces to Support Ongoing Care

Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study (Preprint)

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