Exploring Work System Adaptations in Providing Care for Children with Medical Complexity in the Home

Author(s):  
Hanna J. Barton ◽  
Shanmugapriya Loganathar ◽  
Nawang Singhe ◽  
Mary L. Ehlenbach ◽  
Barbara Katz ◽  
...  

Children with medical complexity (CMC) rely on family caregivers to provide advanced medical care in the home. Yet, family caregivers are often under-supported. To better support family caregivers, we must understand and identify the ways that the work system is not designed to support their work. Work system adaptations can uncover where the work system is not designed to support the worker. This study sought to identify and categorize caregiver adaptations to the work system. We conducted 30 home-visit interviews with caregivers of CMC. Inductive content analysis revealed that family caregivers were making work system adaptations on multiple levels including: medical devices, direct care, auxiliary care, and integration of caregiving into everyday life. Our findings imply that family caregivers are attempting to address barriers on multiple levels by adapting the work system. Critical next steps should create system interventions to address the mismatch between the caregivers’ needs and the work system.

Author(s):  
Reid Parks ◽  
Nadia Doutcheva ◽  
Dhivya Umachandran ◽  
Nawang Singhe ◽  
Sofia Noejovich ◽  
...  

Family caregivers use tools and technology to provide care for children with medical complexity (CMC) in the home. It is unclear what barriers families experience when using the tools and technology integral to the care and wellbeing of CMC. Our objective was to identify the barriers family caregivers experience in using tools and technology to provide care to CMC in the home. We used contextual inquiry to interview 30 caregivers in their homes and analyzed our data using a deductive content analysis informed by the patient work system (PWS) model and an inductive content analysis to identify emergent barriers. Through these combined analyses, we identified four categories of barriers families experienced using tools and technology to care for CMC: 1) Access and Cost; 2) Usability, which includes the subcategories Functionality, Tool design, Ease of use, and Reliability; 3) Short-term tool impact; and 4) Long-term tool impact. Our results point to the need for further interventions to reduce or mitigate tools and technology barriers to the in-home care for CMC.


Author(s):  
Hanna Barton ◽  
Ryan Coller ◽  
Sara Finesilver ◽  
Christopher Lunsford ◽  
Rupa S. Valdez ◽  
...  

For vulnerable patient populations, such as children with medical complexity (CMC), the patient journey is fraught with challenges. By providing a range of perspectives including clinicians, a family caregiver, and Human Factors/Ergonomics (HF/E) experts, the present panel will describe the unique opportunities for HF/E to design jointly optimized systems for CMC and their family caregivers, including an explication of some of the specific challenges and complexities related to studying the work of and designing systems for this population. We will also highlight the ways in which HF/E could help in the design of solutions to improve outcomes for families.


2020 ◽  
Vol 4 (1) ◽  
pp. e000671
Author(s):  
Rahul Verma ◽  
Yasna Mehdian ◽  
Neel Sheth ◽  
Kathy Netten ◽  
Jean Vinette ◽  
...  

ObjectiveTo quantify psychosocial risk in family caregivers of children with medical complexity using the Psychosocial Assessment Tool (PAT) and to investigate potential contributing sociodemographic factors.DesignCross-sectional study.SettingFamily caregivers completed questionnaires during long-term ventilation and complex care clinic visits at The Hospital for Sick Children, Toronto, Ontario, Canada.PatientsA total of 136 family caregivers of children with medical complexity completed the PAT questionnaires from 30 June 2017 through 23 August 2017.Main outcome measuresMean PAT scores in family caregivers of children with medical complexity. Caregivers were stratified as ‘Universal’ low risk, ‘Targeted’ intermediate risk or ‘Clinical’ high risk. The effect of sociodemographic variables on overall PAT scores was also examined using multiple linear regression analysis. Comparisons with previous paediatric studies were made using T-test statistics.Results136 (103 females (76%)) family caregivers completed the study. Mean PAT score was 1.17 (SD=0.74), indicative of ‘Targeted’ intermediate risk. Sixty-one (45%) caregivers were classified as Universal risk, 60 (44%) as Targeted risk and 15 (11%) as Clinical risk. Multiple linear regression analysis revealed an overall significant model (p=0.04); however, no particular sociodemographic factor was a significant predictor of total PAT scores.ConclusionFamily caregivers of children with medical complexity report PAT scores among the highest of all previously studied paediatric populations. These caregivers experience significant psychosocial risk, demonstrated by larger proportions of caregivers in the highest-risk Clinical category.


2020 ◽  
Vol 87 ◽  
pp. 103108
Author(s):  
Ephrem Abebe ◽  
Matthew C. Scanlon ◽  
K. Jane Lee ◽  
Michelle A. Chui

Author(s):  
Nadejda Doutcheva ◽  
Hannah Thomas ◽  
Reid Parks ◽  
Ryan Coller ◽  
Nicole Werner

Family caregivers provide critical care for children with medical complexity (CMC) at home, yet homes are still a poorly understood healthcare setting. Home environments include diverse physical environments, technologies, tools, tasks, and people, and are therefore complex work systems. Research suggests that home environments can contribute positively and negatively to both individuals’ well-being and the quality of care that families can provide. Our objective for this study was to determine how the physical environment of the home interacts within a work system to affect outcomes related to in-home care of CMC. We used contextual inquiry to interview 30 caregivers in their homes and analyzed our data using the Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 model. We focused on identifying physical environments’ interactions with other work system components and the resulting CMC outcomes. We identified six categories of outcomes that are influenced by work system interactions within the physical environment: 1) Safe or Unsafe delivery of care; 2) Prepared for or Inability to Respond to Care Crisis; 3) Home Mobility or Inaccessibility; 4) Efficient and Inefficient Care; 5) Inclusion and Isolation from Family; and 6) Socioemotional Comfort and Stress. The physical environment influences a range of outcomes from patient safety to families’ emotional well-being. Our results point to the need for adaptation of SEIPS 2.0 to the home environment by incorporating consideration for family and home-based outcomes into the model.


SLEEP ◽  
2017 ◽  
Vol 40 (suppl_1) ◽  
pp. A339-A340
Author(s):  
K Keilty ◽  
M Ballantyne ◽  
R Amin ◽  
L Beaune ◽  
J Barbita ◽  
...  

2019 ◽  
Vol 24 (Supplement_2) ◽  
pp. e6-e7
Author(s):  
Sarah Lord ◽  
Clara Moore ◽  
Kathy Netten ◽  
Reshma Amin ◽  
Adam Rappaport ◽  
...  

2020 ◽  
Vol 25 (Supplement_2) ◽  
pp. e42-e42
Author(s):  
Rahul Verma ◽  
Yasna Mehdian ◽  
Neel Sheth ◽  
Kathy Netten ◽  
Jean Vinette ◽  
...  

Abstract Background Children with medical complexity (CMC) are defined by their medical fragility, dependence on assistive technology and substantial care needs. Family caregivers of CMC have unique challenges, such as prolonged hospitalizations and poor care coordination, which result in extensive caregiver stress. There is a great need to quantify the level of psychosocial stress and resilience in these caregivers to allow for appropriate allocation of health care resources. The Psychosocial Assessment Tool (PAT) is a brief parent-reported screening tool for measuring psychosocial risk in caregivers of pediatric populations. This is the first study to use the PAT in children with medical complexity. Objectives To quantify psychosocial risk in family caregivers of children diagnosed with medical complexity. To identify predictors of caregiver distress based on their sociodemographic factors. It was hypothesized that the extensive health demands of CMC will result in high amounts of chronic, ongoing caregiver distress relative to the previously studied pediatric populations. Design/Methods This cross-sectional study was conducted at The Hospital for Sick Children, Toronto, Canada. Family caregivers of children with medical complexity completed the PAT questionnaires during regularly scheduled Long-Term Ventilation and Complex Care clinic visits. Based on the overall PAT scores, caregivers were stratified as “Universal” low risk (<1.0), “Targeted” intermediate risk (1.0 to 1.9), or “Clinical” high risk (≥2.0). Multiple linear regression analysis was performed to examine the effect of sociodemographic variables and illness severity on total PAT scores. Comparisons with previous pediatric studies were made using T-test statistics. Results 136 [103 females (76%)] family caregivers completed the study. Mean PAT score was 1.17 (SD = 0.740). 61 (44.85%) caregivers were classified as Universal risk, 60 (44.12%) as Targeted risk, and 15 (11.03%) as Clinical risk. Compared to previously studied pediatric populations, our CMC have the second-highest overall PAT scores, which are also substantially weighted towards the higher risk categories (Table 1). Multiple linear regression analysis demonstrated that subjective report of financial hardship by caregivers is a significant predictor of total PAT scores (p < 0.05). Conclusion Family caregivers of children with medical complexity report PAT scores amongst the highest of all pediatric populations. These caregivers experience significant psychosocial distress, demonstrated by larger proportions of caregivers in the Targeted and Clinical risk categories. Therefore, psychosocial interventions including financial assistance are urgently needed in this population.


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