Patients' perception of communication at the interface between primary and secondary care: a cross-sectional survey in 34 countries

Towards understanding and improving medication safety for patients with mental illness in primary care: A multimethod study

INTRODUCTION

Medication safety incidents have been identified as an important target to improve patient safety in mental healthcare. Despite this, the causes of preventable medication safety incidents affecting patients with mental illness have historically been poorly understood, with research now addressing this knowledge gap through a healthcare professional lens. However, patients and carers can also provide complimentary insight into safety issues, and as key stakeholders in healthcare, it is vital to consider their needs when designing effective interventions.

METHODS

A two-stage approach was adopted by (i) conducting three focus groups (FG) comprising 13 patients with mental illness and their carers to develop a holistic picture of medication safety in primary care with extraction of themes guided by the P-MEDS framework; (ii) conducting two separate nominal group consensus workshops with seven patients with mental illness/carers and seven healthcare professionals to identify priority areas for targeted interventions.

RESULTS

Seven themes were identified in the FGs: communication; trust, involvement and respect; continuity and support; access; the healthcare professional; the patient and carer; and the organisation. Priority areas identified for intervention by key stakeholders included improving communication within and between clinical services, enhancing patient support with holistic continuity of care, maximising shared decision-making and empowerment, ensuring timely access to medicines and services, strengthening healthcare professional knowledge regarding mental illnesses and associated medications, and increasing patient dignity and respect.

CONCLUSION

This study has developed a holistic picture of contributors to medication safety incidents affecting patients with mental illness in primary care. This theory was then used by key stakeholders to inform and generate priority recommendations for targeted interventions. These findings can be used to inform future intervention research, as they consider the needs of those who access or work within primary care services.

PATIENT OR PUBLIC CONTRIBUTION

An advisory group consisting of three expert patients with lived experience of mental illness was consulted on the design of both stages of this study. Patients with mental illness and/or their carers were recruited and participated in both stages of this study. Patients/carers aided with data analysis and interpretation during the patient/carer nominal group consensus workshop.

Knowledge, Attitudes, and Practices about Electronic Personal Health Records: A Cross-Sectional Study in a Region of Northern Italy

The Electronic Personal Health Record (EPHR) provides an innovative service for citizens and professionals to manage health data, promoting patient-centred care. It enhances communication between patients and physicians and improves accessibility to documents for remote medical information management. The study aims to assess the prevalence of awareness and acceptance of the EPHR in northern Italy and define determinants and barriers to its implementation. In 2022, a region-wide cross-sectional study was carried out through a paper-based and online survey shared among adult citizens. Univariable and multivariable regression models analysed the association between the outcome variables (knowledge and attitudes toward the EPHR) and selected independent variables. Overall, 1634 people were surveyed, and two-thirds were aware of the EPHR. Among those unaware of the EPHR, a high prevalence of specific socio-demographic groups, such as foreign-born individuals and those with lower educational levels, was highlighted. Multivariable regression models showed a positive association between being aware of the EPHR and educational level, health literacy, and perceived poor health status, whereas age was negatively associated. A higher knowledge of the EPHR was associated with a higher attitude towards the EPHR. The current analysis confirms a lack of awareness regarding the existence of the EPHR, especially among certain disadvantaged demographic groups. This should serve as a driving force for a powerful campaign tailored to specific categories of citizens for enhancing knowledge and usage of the EPHR. Involving professionals in promoting this tool is crucial for helping patients and managing health data.

Using the H2O Automatic Machine Learning Algorithms to Identify Predictors of Web-Based Medical Record Nonuse Among Patients in a Data-Rich Environment: Mixed Methods Study

BACKGROUND

With the advent of electronic storage of medical records and the internet, patients can access web-based medical records. This has facilitated doctor-patient communication and built trust between them. However, many patients avoid using web-based medical records despite their greater availability and readability.

OBJECTIVE

On the basis of demographic and individual behavioral characteristics, this study explores the predictors of web-based medical record nonuse among patients.

METHODS

Data were collected from the National Cancer Institute 2019 to 2020 Health Information National Trends Survey. First, based on the data-rich environment, the chi-square test (categorical variables) and 2-tailed t tests (continuous variables) were performed on the response variables and the variables in the questionnaire. According to the test results, the variables were initially screened, and those that passed the test were selected for subsequent analysis. Second, participants were excluded from the study if any of the initially screened variables were missing. Third, the data obtained were modeled using 5 machine learning algorithms, namely, logistic regression, automatic generalized linear model, automatic random forest, automatic deep neural network, and automatic gradient boosting machine, to identify and investigate factors affecting web-based medical record nonuse. The aforementioned automatic machine learning algorithms were based on the R interface (R Foundation for Statistical Computing) of the H2O (H2O.ai) scalable machine learning platform. Finally, 5-fold cross-validation was adopted for 80% of the data set, which was used as the training data to determine hyperparameters of 5 algorithms, and 20% of the data set was used as the test data for model comparison.

RESULTS

Among the 9072 respondents, 5409 (59.62%) had no experience using web-based medical records. Using the 5 algorithms, 29 variables were identified as crucial predictors of nonuse of web-based medical records. These 29 variables comprised 6 (21%) sociodemographic variables (age, BMI, race, marital status, education, and income) and 23 (79%) variables related to individual lifestyles and behavioral habits (such as electronic and internet use, individuals' health status and their level of health concern, etc). H2O's automatic machine learning methods have a high model accuracy. On the basis of the performance of the validation data set, the optimal model was the automatic random forest with the highest area under the curve in the validation set (88.52%) and the test set (82.87%).

CONCLUSIONS

When monitoring web-based medical record use trends, research should focus on social factors such as age, education, BMI, and marital status, as well as personal lifestyle and behavioral habits, including smoking, use of electronic devices and the internet, patients' personal health status, and their level of health concern. The use of electronic medical records can be targeted to specific patient groups, allowing more people to benefit from their usefulness.

Burnout and job stress of anesthesiologists in the tertiary class A hospitals in Northwest China: A cross-sectional design

Purpose

Our purpose was to assess job stress and burnout among anesthesiologists in the tertiary class A hospitals in Northwest China, analyze the possible causes and adverse consequences of increased job stress and burnout of anesthesiologists in this region, and put forward suggestions in combination with the current national policies.

Methods

We sent 500 electronic questionnaires to all anesthesiologists practicing in the tertiary class A hospitals in Northwest China from 1960 to 2017 on April 2020. A total of 336 (67.2%) questionnaires were returned and could be used for analysis. Burnout and job stress were assessed by using the modified Maslach Burnout Inventory-Human Services Survey and Chinese Perceived Stress Scale, respectively.

Results

First, as for emotional exhaustion, the situations of anesthesiologists with different working years and workloads are different with statistical significance (P < 0.05). Second, as for depersonalization, the situations of anesthesiologists with different ages, professional titles, working years, physical health status, and workload are different (P < 0.05). Third, as for personal accomplishment, the situations of anesthesiologists with different physical health status are different (P < 0.05). Finally, the regression results showed that the longer the fatigue working years and the worse the physical health of anesthesiologists in Northwest China, the more likely these two factors were to cause burnout (P < 0.05), as for job stress, there was a negative correlation between job stress and physical health status (P < 0.05).

Conclusion

Burnout and high job pressure are common among anesthesiologists in tertiary class A hospitals in Northwest China. We should focus on the allocation of labor intensity, pay attention to the physical and mental health of employees, establish targeted incentive mechanism, and improve the system of promotion and income rises for grassroots doctors. This may be not only conducive to the quality of medical care for patients but also conducive to the development of anesthesiology in China.

Trial registration

Identifier: ChiCTR2000031316.

A Bibliometric Analysis and Visualization of Decision Support Systems for Healthcare Referral Strategies

BACKGROUND

The referral process is an important research focus because of the potential consequences of delays, especially for patients with serious medical conditions that need immediate care, such as those with metastatic cancer. Thus, a systematic literature review of recent and influential manuscripts is critical to understanding the current methods and future directions in order to improve the referral process.

METHODS

A hybrid bibliometric-structured review was conducted using both quantitative and qualitative methodologies. Searches were conducted of three databases, Web of Science, Scopus, and PubMed, in addition to the references from the eligible papers. The papers were considered to be eligible if they were relevant English articles or reviews that were published from January 2010 to June 2021. The searches were conducted using three groups of keywords, and bibliometric analysis was performed, followed by content analysis.

RESULTS

A total of 163 papers that were published in impactful journals between January 2010 and June 2021 were selected. These papers were then reviewed, analyzed, and categorized as follows: descriptive analysis (n = 77), cause and effect (n = 12), interventions (n = 50), and quality management (n = 24). Six future research directions were identified.

CONCLUSIONS

Minimal attention was given to the study of the primary referral of blood cancer cases versus those with solid cancer types, which is a gap that future studies should address. More research is needed in order to optimize the referral process, specifically for suspected hematological cancer patients.

Challenges to the provision of specialized care in remote rural municipalities in Brazil

This case study analyses the challenges to providing specialized care in Brazilian remote rural municipalities (RRM). Interviews were conducted with managers from two Brazilian states (Piauí and Bahia). We identified that the distance between municipalities is a limiting factor for access and that significant care gaps contribute to different organizational arrangements for providing and accessing specialized care. Physicians in all the RRMs offer specialized care by direct disbursement to users or sale of procedures to managers periodically, compromising municipal and household budgets. Health regions do not meet the demand for specialized care and exacerbate the need for extensive travel. RRM managers face additional challenges for the provision of specialized care regarding the financing, implementation of cooperative arrangements, and the provision of care articulated in networks to achieve comprehensive care, seeking solutions to the locoregional specificities.

Online Medical Record Nonuse Among Patients: Data Analysis Study of the 2019 Health Information National Trends Survey

BACKGROUND

Online medical records are being used to organize processes in clinical and outpatient settings and to forge doctor-patient communication techniques that build mutual understanding and trust.

OBJECTIVE

We aimed to understand the reasons why patients tend to avoid using online medical records and to compare the perceptions that patients have of online medical records based on demographics and cancer diagnosis.

METHODS

We used data from the Health Information National Trends Survey Cycle 3, a nationally representative survey, and assessed outcomes using descriptive statistics and chi-square tests. The patients (N=4328) included in the analysis had experienced an outpatient visit within the previous 12 months and had answered the online behavior question regarding their use of online medical records.

RESULTS

Patients who were nonusers of online medical records consisted of 58.36% of the sample (2526/4328). The highest nonuser rates were for patients who were Hispanic (460/683, 67.35%), patients who were non-Hispanic Black (434/653, 66.46%), and patients who were older than 65 years (968/1520, 63.6%). Patients older than 65 years were less likely to use online medical records (odds ratio [OR] 1.51, 95% CI 1.24-1.84, P<.001). Patients who were White were more likely to use online medical records than patients who were Black (OR 1.71, 95% CI 1.43-2.05, P<.001) or Hispanic (OR 1.65, 95% CI 1.37-1.98, P<.001). Patients who were diagnosed with cancer were more likely to use online medical records compared to patients with no cancer (OR 1.31, 95% CI 1.11-1.55, 95% CI 1.11-1.55, P=.001). Among nonusers, older patients (≥65 years old) preferred speaking directly to their health care providers (OR 1.76, 95% CI 1.35-2.31, P<.001), were more concerned about privacy issues caused by online medical records (OR 1.79, 95% CI 1.22-2.66, P<.001), and felt uncomfortable using the online medical record systems (OR 10.55, 95% CI 6.06-19.89, P<.001) compared to those aged 18-34 years. Patients who were Black or Hispanic were more concerned about privacy issues (OR 1.42, 1.09-1.84, P=.007).

CONCLUSIONS

Studies should consider social factors such as gender, race/ethnicity, and age when monitoring trends in eHealth use to ensure that eHealth use does not induce greater health status and health care disparities between people with different backgrounds and demographic characteristics.