Utilizing eHealth and Telemedicine Technologies to Enhance Access and Quality of Consultations: It's Not What You Say, It's the Way You Say It

Digital solutions to follow up on discharged new parents-A systematic literature review

New parents and their newborns are followed up after discharge either through home visits from midwives/nurses or using information and communication technology. This follow-up focuses on individual needs related to breastfeeding and infant feeding, practical advice on caring for babies, supporting and strengthening the new mother's knowledge and self-confidence concerning child development and parenting skills, and supporting the relationship between parents and baby. This systematic review aims to integrate available research results that describe new parents' experiences when health and care providers used telemedicine as a platform for follow-up after discharge from the childbirth department. This literature review was conducted following the PRISMA statement and was prospectively registered in PROSPERO CRD42021236912. The studies were identified through the following databases: AMED, Academic, EMBASE, Google Scholar, Ovid MEDLINE via PubMed, Cochrane database, and CINAHL. Results from these studies were compiled using thematic analysis. A total of 886 studies were identified. Screening resulted in eight studies that met the inclusion criteria. Thematic analysis produced the following themes: a) Flexibility and convenience of digital support, b) Digital literacy, c) Parents feeling safe with digital support, and d) Adequate substitute for physical meetings. New parents who live in a home environment with a relaxed atmosphere and around-the-clock digital support experience a sense of control, security, full attention, and encouragement. Digital follow up at home has proven effective because it can meet the support needs of new parents when necessary.

Delivering Biopsychosocial Health Care Within Routine Care: Spotlight-AQ Pivotal Multicenter Randomized Controlled Trial Results

BACKGROUND

Annual national diabetes audit data consistently shows most people with diabetes do not consistently achieve blood glucose targets for optimal health, despite the large range of treatment options available.

AIM

To explore the efficacy of a novel clinical intervention to address physical and mental health needs within routine diabetes consultations across health care settings.

METHODS

A multicenter, parallel group, individually randomized trial comparing consultation duration in adults diagnosed with T1D or T2D for ≥6 months using the Spotlight-AQ platform versus usual care. Secondary outcomes were HbA1c, depression, diabetes distress, anxiety, functional health status, and healthcare professional burnout. Machine learning models were utilized to analyze the data collected from the Spotlight-AQ platform to validate the reliability of question-concern association; as well as to identify key features that distinguish people with type 1 and type 2 diabetes, as well as important features that distinguish different levels of HbA1c.

RESULTS

n = 98 adults with T1D or T2D; any HbA1c and receiving any diabetes treatment participated (n = 49 intervention). Consultation duration for intervention participants was reduced in intervention consultations by 0.5 to 4.1 minutes (3%-14%) versus no change in the control group (-0.9 to +1.28 minutes). HbA1c improved in the intervention group by 6 mmol/mol (range 0-30) versus control group 3 mmol/mol (range 0-8). Moderate improvements in psychosocial outcomes were seen in the intervention group for functional health status; reduced anxiety, depression, and diabetes distress and improved well-being. None were statistically significant. HCPs reported improved communication and greater focus on patient priorities in consultations. Artificial Intelligence examination highlighted therapy and psychological burden were most important in predicting HbA1c levels. The Natural Language Processing semantic analysis confirmed the mapping relationship between questions and their corresponding concerns. Machine learning model revealed type 1 and type 2 patients have different concerns regarding psychological burden and knowledge. Moreover, the machine learning model emphasized that individuals with varying levels of HbA1c exhibit diverse levels of psychological burden and therapy-related concerns.

CONCLUSION

Spotlight-AQ was associated with shorter, more useful consultations; with improved HbA1c and moderate benefits on psychosocial outcomes. Results reflect the importance of a biopsychosocial approach to routine care visits. Spotlight-AQ is viable across health care settings for improved outcomes.

Feasibility of Spotlight Consultations Tool in Routine Care: Real-World Evidence

BACKGROUND

Burnout in people with diabetes and healthcare professionals (HCPs) is at an all-time high. Spotlight AQ, a novel "smart" adaptive patient questionnaire, is designed to improve consultations by rapidly identifying patient priorities and presenting these in the context of best-practice care pathways to aid consultations. We aimed to determine Spotlight AQ's feasibility in routine care.

MATERIALS AND METHODS

The Spotlight prototype tool was trialed at three centers: two UK primary care centers and one US specialist center (June-September 2020). Participants with type 1 (T1D) or type 2 diabetes (T2D) completed the questionnaire prior to their routine consultations. Results were immediately available and formed the basis of the clinical discussion and decision-making within the clinic visit.

RESULTS

A convenience sample of 49 adults took part, n=31 T1D, (n=18 female); and n=18 T2D (n=10 male, n=4 female, n=4 gender unreported). Each identified two priority concerns. "Psychological burden of diabetes" was the most common priority concern (T1D n = 27, 87.1%) followed by "gaining more skills about particular aspects of diabetes" (T1D n=19, 61.3%), "improving support around me" (n=8, 25.8%) and "diabetes-related treatment issues" (n=8, 25.8%). Burden of diabetes was widespread as was lack of confidence around self-management. Similarly, psychological burden of diabetes was the primary concern for participants with T2D (n=18,100%) followed by "gaining more skills about aspects of diabetes" (n=7, 38.9%), "improving support around me" (n=7, 38.9%) and "diabetes-related treatment issues" (n=4; 22.2%).

CONCLUSIONS

Spotlight AQ is acceptable and feasible for use in routine care. Gaining more skills and addressing the psychological burden of diabetes are high-priority areas that must be addressed to reduce high levels of distress.

Telehealth in type 1 diabetes

PURPOSE OF REVIEW

The role of telehealth in the care of people with type 1 diabetes (T1D) has expanded dramatically during the coronavirus pandemic, and is expected to remain a major care delivery modality going forward. This review explores the landscape of recent evidence for telehealth in T1D care.

RECENT FINDINGS

Telemedicine for routine T1D care has shown equivalence to standard in-person care, with respect to glycemic control, while also increasing access, convenience, and satisfaction. Telehealth use promotes increased engagement of adolescents with T1D. Telehealth platforms have successfully been used in the care of microvascular complications and to support mental health related to diabetes. Machine learning and advanced decision support will increasingly be used to augment T1D care, as recent evidence suggests increasing capabilities to improve glycemic control. A spectrum of digital connected care services are emerging to support people with diabetes with daily management of diabetes. Finally, policy and systems are required that promote data interoperability, telemedicine provision, and reimbursement to support the ongoing growth of telehealth in T1D.

SUMMARY

A developing field of evidence supports use of telehealth in T1D. As this care modality scales, it has the potential to increase access to high-quality diabetes care for many people with T1D.