Relationship between Continuity of Care in the Multidisciplinary Treatment of Patients with Diabetes and Their Clinical Results

Situational Analysis of Barriers to Continuity of End-of-Life Care in Urban Areas, Bangkok

This qualitative study was designed to describe the continuity of end-of-life care and identify barriers to continuity in urban Bangkok. Continuity of care is considered an essential part of palliative care to promote the quality of life of patients at the end of life. The majority of studies have been conducted exploring continuity of care in rural communities. However, few studies have focused on urban areas, particularly in big cities. Twelve healthcare providers were the participants, including nurses in inpatient units, and in the Health Community and Continuity of Care Unit, a palliative care physician, and social workers. The data collection consisted of individual interviews, field notes, and observations. Content analysis was used to analyze data and identify barriers. The continuity of end-of-life care in a selected setting was fragmented. Three main barriers to the continuity of end-of-life care consisted of misunderstandings about patients who required palliative care, staff workloads, and incomplete patient information. The development of a comprehensive patient information sheet for communication among a multidisciplinary team could promote continuity of end-of-life care from hospital to home. An interprofessional training course on continuity of end-of-life care is also recommended. Finally, the staff workload should be monitored and managed.

COVID-19 pandemic has disrupted the continuity of care for chronic patients: evidence from a cross-sectional retrospective study in a developing country

BACKGROUND

Any disruption in continuity of care for patients with chronic conditions can lead to poor outcomes for the patients as well as great damage for the community and the health system. This study aims to determine the continuity of care for patients with chronic conditions such as hypertension and diabetes during COVID-19 pandemic.

METHODS

Through a cross-sectional retrospective study, data registered in six health centers in Yazd, Iran were analyzed. Data included the number of patients with chronic conditions (hypertension and diabetes) and average daily admission during a year before COVID-19 pandemic and the similar period after COVID-19 outbreak. The experience of continuity of care was assessed applying a validated questionnaire from a sample of 198 patients. Data analysis was done using SPSS version 25. Descriptive statistics, independent T-Test and Multivariable regression were used for analysis.

FINDINGS

Results indicate that both visit load of the patients with chronic conditions (hypertension and diabetes) and their average daily admission were decreased significantly during a year after COVID-19 pandemic compared to the similar period before COVID-19 outbreak. The moderate average score of the patients` experience towards continuity of care during the pandemic was also reported. Regression analysis showed that age for the diabetes patients and insurance status for the hypertension patients affect the COC mean scores.

CONCLUSION

COVID-19 pandemic causes serious decline in the continuity of care for patients with chronic conditions. Such a deterioration not only can lead to make these patients` condition worse in a long-term period but also it can make irreparable damages to the whole community and the health system. To make the health systems resilient particularly in disasters, serious attention should be taken into consideration among them, developing the tele-health technologies, improving the primary health care capacity, designing the applied responsive models of continuity of care, making multilateral participations and inter-sectoral collaborations, allocating sustainable resources, and enabling the patients with selfcare skills are more highlighted.

Factors Related to the Continuity of Care and Self-Management of Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study in Taiwan

BACKGROUND

Most diabetic patients suffer from chronic diseases affecting their self-management status. This study aims to explore the relationship between the CoC and the self-management of patients with Type 2 Diabetes Mellitus (T2DM) and analyze the predictive factors affecting their self-management.

METHODS

Structured questionnaires were used for data collection. Convenient sampling was adopted to recruit inpatients diagnosed with T2DM in the endocrine ward of a medical hospital in central Taiwan.

RESULTS

A total of 160 patients were recruited. The average age of the patients is 66.60 ± 14.57 years old. Among the four dimensions of the self-management scale, the average score of the problem-solving dimension was the highest, and that of the self-monitoring of blood glucose was the lowest. The analysis results showed that the overall regression model could explain 20.7% of the total variance in self-management.

CONCLUSIONS

Healthcare providers should attach importance to the CoC of T2DM patients and encourage patients to maintain good interaction with healthcare providers during their hospitalization. It is recommended to strengthen CoC for patients with diabetes who are single or with low educational levels in clinical practice to enhance their blood glucose control and improve diabetes self-management.

Serial multiple mediation of treatment adherence and disease activity in the relationship between continuity of care and health outcomes among rheumatoid arthritis patients

OBJECTIVE

To evaluate the effect of continuity of care on health outcomes (quality of life and functionality) in patients with rheumatoid arthritis and to reveal whether treatment adherence and disease activity have a serial multiple mediator role on this relationship.

METHODS

The study was cross-sectional on 440 rheumatoid arthritis patients who applied to a university hospital rheumatology outpatient clinic. Research data were obtained from both the questionnaire method, which is the primary data source, and the patient files, which are the secondary data source. Process analysis was used in the analysis of the data.

RESULTS

It was found that the continuity of care has a direct effect on the quality of life and the functionality. In addition, it is seen that treatment adherence has a single partial mediator role on the relationship between continuity of care and quality of life; It has been determined that treatment adherence and disease activity have both partial single mediation and serial multiple mediation roles on the relationship between continuity of care and functionality.

CONCLUSION

It is thought that these findings will provide clinicians with important data and information in the management of rheumatoid arthritis.

Predicting the Travel Distance of Patients to Access Healthcare Using Deep Neural Networks

OBJECTIVE

Improving geographical access remains a key issue in determining the sufficiency of regional medical resources during health policy design. However, patient choices can be the result of the complex interactivity of various factors. The aim of this study is to propose a deep neural network approach to model the complex decision of patient choice in travel distance to access care, which is an important indicator for policymaking in allocating resources.

METHOD

We used the 4-year nationwide insurance data of Taiwan and accumulated the possible features discussed in earlier literature. This study proposes the use of a convolutional neural network (CNN)-based framework to make predictions. The model performance was tested against other machine learning methods. The proposed framework was further interpreted using Integrated Gradients (IG) to analyze the feature weights.

RESULTS

We successfully demonstrated the effectiveness of using a CNN-based framework to predict the travel distance of patients, achieving an accuracy of 0.968, AUC of 0.969, sensitivity of 0.960, and specificity of 0.989. The CNN-based framework outperformed all other methods. In this research, the IG weights are potentially explainable; however, the relationship does not correspond to known indicators in public health.

CONCLUSIONS

Our results demonstrate the feasibility of the deep learning-based travel distance prediction model. It has the potential to guide policymaking in resource allocation. Clinical and Translational Impact Statement- Deep learning technology is feasible in investigating the distance that patients would travel while accessing care. It is a tool that integrates complex interactive variables with highly imbalanced data distributions.

Effects of turnover and stability of health staff on quality of care in remote communities of the Northern Territory, Australia: a retrospective cohort study

OBJECTIVES

To evaluate the relationship between markers of staff employment stability and use of short-term healthcare workers with markers of quality of care. A secondary objective was to identify clinic-specific factors which may counter hypothesised reduced quality of care associated with lower stability, higher turnover or higher use of short-term staff.

DESIGN

Retrospective cohort study (Northern Territory (NT) Department of Health Primary Care Information Systems).

SETTING

All 48 government primary healthcare clinics in remote communities in NT, Australia (2011-2015).

PARTICIPANTS

25 413 patients drawn from participating clinics during the study period.

OUTCOME MEASURES

Associations between independent variables (resident remote area nurse and Aboriginal Health Practitioner turnover rates, stability rates and the proportional use of agency nurses) and indicators of health service quality in child and maternal health, chronic disease management and preventive health activity were tested using linear regression, adjusting for community and clinic size. Latent class modelling was used to investigate between-clinic heterogeneity.

RESULTS

The proportion of resident Aboriginal clients receiving high-quality care as measured by various quality indicators varied considerably across indicators and clinics. Higher quality care was more likely to be received for management of chronic diseases such as diabetes and least likely to be received for general/preventive adult health checks. Many indicators had target goals of 0.80 which were mostly not achieved. The evidence for associations between decreased stability measures or increased use of agency nurses and reduced achievement of quality indicators was not supported as hypothesised. For the majority of associations, the overall effect sizes were small (close to zero) and failed to reach statistical significance. Where statistically significant associations were found, they were generally in the hypothesised direction.

CONCLUSIONS

Overall, minimal evidence of the hypothesised negative effects of increased turnover, decreased stability and increased reliance on temporary staff on quality of care was found. Substantial variations in clinic-specific estimates of association were evident, suggesting that clinic-specific factors may counter any potential negative effects of decreased staff employment stability. Investigation of clinic-specific factors using latent class analysis failed to yield clinic characteristics that adequately explain between-clinic variation in associations. Understanding the reasons for this variation would significantly aid the provision of clinical care in remote Australia.

Importance of medication adherence in treatment needed diabetic retinopathy

We aim to investigate the role of medication adherence history in treatment needed diabetic retinopathy (TNDR). We conducted a retrospective nested case–control study using 3 population-based databases in Taiwan. The major one was the 2-million-sample longitudinal health and welfare population-based database from 1997 to 2017, a nationally representative random sample of National Health Insurance Administration enrolled beneficiaries in 2010 (LHID2010). The national death registry and national cancer registry were also checked to verify the information. The outcome was defined as the TNDR. The Medication possession ratio (MPR) was defined as the ratio of total days of diabetes mellitus (DM) medication supply divided by total observation days. MPR ≥ 80% was proposed as good medication adherence. The association of MPR and the TNDR was analyzed. Other potential confounders and MPR ratio were also evaluated. A total of (n = 44,628) patients were enrolled. Younger aged, male sex and patients with less chronic illness complexity or less diabetes complication severity tend to have poorer medication adherence. Those with severe comorbidity or participating pay-for-performance program (P4P) revealed better adherence. No matter what the characteristics are, patients with good MPR showed a significantly lower likelihood of leading to TNDR after adjustment with other factors. The protection effect was consistent for up to 5 years. Good medication adherence significantly prevents treatment needed diabetic retinopathy. Hence, it is important to promote DM medication adherence to prevent risks of diabetic retinopathy progression, especially those who opt to have low medication adherence.

Continuity of Care and the Quality of Life among Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study in Taiwan

Background: Understanding factors associated with the quality of life (QoL) of patients with type 2 diabetes (T2DM) is an important health issue. This study aimed to explore the correlation between continuity of care and quality of life in patients with T2DM and to probe for important explanatory factors affecting quality of life. Methods: This study used a cross-sectional correlation research design. Convenience sampling was adopted to recruit 157 patients, aged 20–80 years and diagnosed with T2DM in the medical ward of a regional hospital in central Taiwan. Results: The overall mean (standard deviation, SD) QOL score was 53.42 (9.48). Hierarchical regression linear analysis showed that age, depression, two variables of potential disability (movement and depression), and the inability to see a specific physician or maintain relational continuity with medical providers were important predictors that could effectively explain 62.0% of the variance of the overall QoL. Conclusions: The relationship between patients and physicians and maintaining relational continuity with the medical providers directly affect patients’ QoL during hospitalization and should be prioritized clinically. Timely interventions should be provided for older adult patients with T2DM, depression, or an inability to exercise to maintain their QoL.

Data Analytics in Smart Healthcare: The Recent Developments and Beyond

The concepts of the smart city and the Internet of Things (IoT) have been facilitating the rollout of medical devices and systems to capture valuable information of humanity. A lot of artificial intelligence techniques have been demonstrated to be effective in smart city applications like energy, transportation, retail and control. In recent decade, retardation of the adoption of data analytics algorithms and systems in healthcare has been decreasing, and there is tremendous growth in data analytics research on healthcare data. The results of analytics aim at improving people’s quality of life as well as relieving the issue of medical shortages. In this special issue “Data Analytics in Smart Healthcare”, thirteen (13) papers have been published as the representative examples of recent developments. Guest Editors also highlight some emergent topics and opening challenges in healthcare analytics which follow the visions of the movement of healthcare analytics research.

Team Collaboration Networks and Multidisciplinarity in Diabetes Care: Implications for Patient Outcomes

Prevalence of type 2 diabetes mellitus (T2DM) has almost doubled in recent decades and commonly presents comorbidities and complications. T2DM is a multisystemic disease, requiring multidisciplinary treatment provided by teams working in a coordinated and collaborative manner. The application of social network analysis techniques in the healthcare domain has allowed researchers to analyze interaction between professionals and their roles inside care teams. We studied whether the structure of care teams, modeled as complex social networks, is associated with patient progression. For this, we illustrate a data-driven methodology and use existing social network analysis metrics and metrics proposed for this research. We analyzed appointment and HbA1c blood test result data from patients treated at three primary health care centers, representing six different practices. Patients with good metabolic control during the analyzed period were treated by teams that were more interactive, collaborative and multidisciplinary, whereas patients with worsening or unstable metabolic control were treated by teams with less collaboration and more continuity breakdowns. Results from the proposed metrics were consistent with the previous literature and reveal relevant aspects of collaboration and multidisciplinarity.