Clinician-identified problems and solutions for delayed diagnosis in primary care: a PRIORITIZE study

Smart medical report: efficient detection of common and rare diseases on common blood tests

Introduction

The integration of AI into healthcare is widely anticipated to revolutionize medical diagnostics, enabling earlier, more accurate disease detection and personalized care.

Methods

In this study, we developed and validated an AI-assisted diagnostic support tool using only routinely ordered and broadly available blood tests to predict the presence of major chronic and acute diseases as well as rare disorders.

Results

Our model was tested on both retrospective and prospective datasets comprising over one million patients. We evaluated the diagnostic performance by (1) implementing ensemble learning (mean ROC-AUC.9293 and mean DOR 63.96); (2) assessing the model's sensitivity via risk scores to simulate its screening effectiveness; (3) analyzing the potential for early disease detection (30-270 days before clinical diagnosis) through creating historical patient timelines and (4) conducting validation on real-world clinical data in collaboration with Synlab Hungary, to assess the tool's performance in clinical setting.

Discussion

Uniquely, our model not only considers stable blood values but also tracks changes from baseline across 15 years of patient history. Our AI-driven automated diagnostic tool can significantly enhance clinical practice by recognizing patterns in common and rare diseases, including malignancies. The models' ability to detect diseases 1-9 months earlier than traditional clinical diagnosis could contribute to reduced healthcare costs and improved patient outcomes. The automated evaluation also reduces evaluation time of healthcare providers, which accelerates diagnostic processes. By utilizing only routine blood tests and ensemble methods, the tool demonstrates high efficacy across independent laboratories and hospitals, making it an exceptionally valuable screening resource for primary care physicians.

Equipping computational pathology systems with artifact processing pipelines: a showcase for computation and performance trade-offs

BACKGROUND

Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures result in the introduction of artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs). Artifacts are diagnostically irrelevant areas and may result in wrong predictions from deep learning (DL) algorithms. Therefore, detecting and excluding artifacts in the computational pathology (CPATH) system is essential for reliable automated diagnosis.

METHODS

In this paper, we propose a mixture of experts (MoE) scheme for detecting five notable artifacts, including damaged tissue, blur, folded tissue, air bubbles, and histologically irrelevant blood from WSIs. First, we train independent binary DL models as experts to capture particular artifact morphology. Then, we ensemble their predictions using a fusion mechanism. We apply probabilistic thresholding over the final probability distribution to improve the sensitivity of the MoE. We developed four DL pipelines to evaluate computational and performance trade-offs. These include two MoEs and two multiclass models of state-of-the-art deep convolutional neural networks (DCNNs) and vision transformers (ViTs). These DL pipelines are quantitatively and qualitatively evaluated on external and out-of-distribution (OoD) data to assess generalizability and robustness for artifact detection application.

RESULTS

We extensively evaluated the proposed MoE and multiclass models. DCNNs-based MoE and ViTs-based MoE schemes outperformed simpler multiclass models and were tested on datasets from different hospitals and cancer types, where MoE using (MobileNet) DCNNs yielded the best results. The proposed MoE yields 86.15 % F1 and 97.93% sensitivity scores on unseen data, retaining less computational cost for inference than MoE using ViTs. This best performance of MoEs comes with relatively higher computational trade-offs than multiclass models. Furthermore, we apply post-processing to create an artifact segmentation mask, a potential artifact-free RoI map, a quality report, and an artifact-refined WSI for further computational analysis. During the qualitative evaluation, field experts assessed the predictive performance of MoEs over OoD WSIs. They rated artifact detection and artifact-free area preservation, where the highest agreement translated to a Cohen Kappa of 0.82, indicating substantial agreement for the overall diagnostic usability of the DCNN-based MoE scheme.

CONCLUSIONS

The proposed artifact detection pipeline will not only ensure reliable CPATH predictions but may also provide quality control. In this work, the best-performing pipeline for artifact detection is MoE with DCNNs. Our detailed experiments show that there is always a trade-off between performance and computational complexity, and no straightforward DL solution equally suits all types of data and applications. The code and HistoArtifacts dataset can be found online at Github and Zenodo , respectively.

Hidden systems in primary care cancer detection: an embedded qualitative intervention development study

BACKGROUND

UK cancer mortality is worse than in many other high-income countries, partly because of diagnostic delays in primary care.

AIM

To understand beliefs and behaviours of GPs, and systems of general practice teams, to inform the Think Cancer! intervention development.

DESIGN AND SETTING

An embedded qualitative study guided by behaviour change models (COM-B [Capability, Opportunity, Motivation - Behaviour] and theoretical domains framework [TDF]) in primary care in Wales, UK.

METHOD

Twenty qualitative, semi-structured telephone interviews with GPs were undertaken and four face-to-face focus groups held with practice teams. Framework analysis was used and results were mapped to multiple, overlapping components of COM-B and TDF.

RESULTS

Three themes illustrate complex, multilevel referral considerations facing GPs and practice teams; external influences and constraints; and the role of practice systems and culture. Tensions emerged between individual considerations of GPs (Capability and Motivation) and context-dependent external pressures (Opportunity). Detecting cancer was guided not only by external requirements, but also by motivational factors GPs described as part of their cancer diagnostics process. External influences on the diagnosis process often resulted from the primary-secondary care interface and social pressures. GPs adapted their behaviour to deal with this disconnect. Positive practice culture and supportive practice-based systems ameliorated these tensions and complexity.

CONCLUSION

By exploring individual GP behaviours together with practice systems and culture we contribute new understanding about how cancer diagnosis operates in primary care and how delays can be improved. We highlight commonly overlooked dynamics and tensions that are experienced by GPs as a tension between individual decision making (Capability and Motivation) and external considerations, such as pressures in secondary care (Opportunity).

Comparative Analysis of Large Language Models in Emergency Plastic Surgery Decision-Making: The Role of Physical Exam Data

In the U.S., diagnostic errors are common across various healthcare settings due to factors like complex procedures and multiple healthcare providers, often exacerbated by inadequate initial evaluations. This study explores the role of Large Language Models (LLMs), specifically OpenAI's ChatGPT-4 and Google Gemini, in improving emergency decision-making in plastic and reconstructive surgery by evaluating their effectiveness both with and without physical examination data. Thirty medical vignettes covering emergency conditions such as fractures and nerve injuries were used to assess the diagnostic and management responses of the models. These responses were evaluated by medical professionals against established clinical guidelines, using statistical analyses including the Wilcoxon rank-sum test. Results showed that ChatGPT-4 consistently outperformed Gemini in both diagnosis and management, irrespective of the presence of physical examination data, though no significant differences were noted within each model's performance across different data scenarios. Conclusively, while ChatGPT-4 demonstrates superior accuracy and management capabilities, the addition of physical examination data, though enhancing response detail, did not significantly surpass traditional medical resources. This underscores the utility of AI in supporting clinical decision-making, particularly in scenarios with limited data, suggesting its role as a complement to, rather than a replacement for, comprehensive clinical evaluation and expertise.

Diabetes mellitus and associated factors among HIV-positive patients at primary health care facilities in Harare, Zimbabwe: a descriptive cross-sectional study

BACKGROUND

Highly active antiretroviral therapy (HAART) has improved the life expectancy of people living with HIV (PLWH) and has increased the risk of chronic non-communicable diseases. Comorbid HIV and diabetes mellitus (DM) significantly increase cardiovascular disease and mortality risk. This study aimed to determine the prevalence of type 2 diabetes mellitus among HIV-positive patients receiving HAART in Zimbabwe and its associated risk factors.

METHODS

This cross-sectional study was conducted at eight primary healthcare facilities in Harare, Zimbabwe, between January 2022 and March 2023. Non-probability convenience sampling was used to recruit adult HIV-positive patients undergoing HAART attending the facilities. Data were captured on clinical history and socio-demographic and behavioral characteristics, and analyzed using descriptive statistics to determine DM prevalence rates. Additionally, bivariate and multivariate logistic regression models were employed to examine factors associated with HIV and DM comorbidities.

RESULTS

A total of 450 participants were included in this study, of which 57.6% (n = 259) were female. The majority were married (73.8%) and older than 35 years (80.2%). Most participants had completed high school (87.6%) and 68.9% were employed either formally or self-employed. The prevalence of diabetes mellitus (DM) was 14.9%. HIV/DM comorbidity was more prevalent in patients who were female, self-employed, and smoked (p < 0.05). Multivariate logistic regression analysis revealed that the factors associated with DM-HIV comorbidity were gender, age, education, marital status, employment status, smoking, physical activities, duration of HAART, and diet. Age, level of education, marital status, and occupation were not associated with HIV-DM comorbidity. Obesity (body mass index > 30 kg/m2), smoking, and alcohol consumption were associated with an increased risk of DM. Regular physical activity is associated with a reduced risk of DM.

CONCLUSION

A substantial burden of DM was found in PLWH. The intersectoral integration approach is advocated, and active screening for DM is recommended. Gender-specific interventions are necessary to target diseases and health behaviors that differ between men and women. These interventions should be customized to the specific diseases and behaviors of each group.

Diagnostic Delay in Paediatric Inflammatory Bowel Disease-A Systematic Investigation

Diagnostic delays (time from the first symptoms to diagnosis) are common in inflammatory bowel disease (IBD) and may lead to worse disease progression and treatment outcomes. This study aimed to determine the duration of diagnostic delays (DD) and to explore associated factors in a cohort of children with IBD in New Zealand. In this study, patients with IBD diagnosed as children and their parents/caregivers completed questionnaires on the patients’ medical history, diagnostic experience, and demographic characteristics. The parent/caregiver questionnaire also included the Barriers to Care Questionnaire (BCQ). Patients’ healthcare data was reviewed to summarise the history of clinical visits and determine symptoms. Total DD, healthcare DD, patient DD and parent DD were derived from the primary dataset. Factors associated with the different types of DD were explored with a series of simple linear and logistical ordinal regressions. A total of 36 patients (Crohn’s disease 25, ulcerative colitis 10; male 17) were included. They were diagnosed at a median age of 12 years (interquartile range (IQR) 10−15 years). Total healthcare delay (from first healthcare visit to formal diagnosis) was median (IQR) 15.4 (6.5−34.2) months. The median (IQR) specialist-associated delay was 4.5 (0−34) days. Higher household income was associated with shorter healthcare delay (p < 0.018), while lower overall BCQ scores (indicating more barriers experienced) were associated with longer total healthcare DD. Higher scores in each subscale of BCQ (Skills; Pragmatics; Expectations; Marginalization; Knowledge and Beliefs) were also significantly associated with shorter total healthcare delay (p < 0.04). This study found substantial diagnostic delays in paediatric patients with IBD and identified significant associations between longer total healthcare diagnostic delays and overall household income and higher self-reported barriers to accessing healthcare.

Effectiveness of a Mobile Technology-Supported Self-Reflective Course in Communication Behaviors for Outpatient Nurses

Background Communication is a core competency for outpatient nurses. This study investigated the effectiveness of a mobile technology-supported self-reflective (MTS) course in communication behaviors among outpatient nurses. Method This quasi-experimental study used a convenience sample of 78 outpatient nurses (experimental group = 39; control group = 39). The experimental group completed the MTS communication course. Communication behaviors were evaluated before, 1 week after, and 1 month after the course. Results There was no significant difference in communication behaviors between the groups before the intervention. One week after the intervention, communication behavior scores significantly increased in both groups without significant between-group differences (p > .05). One month after the intervention, the experimental group showed significantly higher communication behavior scores (p < .05). Both groups demonstrated high learning satisfaction. Conclusion The MTS communication course was successful in promoting effective outpatient nurse-patient communication. Health care facilities may want to incorporate the MTS course into their orientation program. [J Contin Educ Nurs. 2022;53(6):279-288.].

Priorities for family physician and general practitioner recruitment and retention in Singapore: a PRIORITIZE study

Background

A shortage of primary care physicians has been reported in many countries. Primary care systems are diverse and the challenges leading to a decline in workforce are at times context-specific and require tailored solutions. Inviting frontline clinicians to share their insights can help identify optimal strategies for a particular setting. To determine priorities for family physicians’ and general practitioners’ recruitment and retention in Singapore, we invited primary care physicians to rank pertinent strategies using PRIORITIZE, a transparent, systematic priority-setting approach.

Methods

The study advisory board, consisting of representatives of Singapore’s key primary care stakeholders, determined the criteria for prioritising of general practitioners (GPs) and family physicians (FPs) recruitment and retention strategies in Singapore. A comprehensive list of GPs and FPs recruitment and retention strategies was extracted from a recent systematic review of the relevant literature. A questionnaire listing the strategies and the scoring criteria was administered online to doctors practicing in public and private sector in Singapore. Respondents’ scores were combined to create a ranked list of locally most relevant strategies for improving GPs and FPs recruitment and retention.

Results

We recruited a diverse sample of 50 GPs and FPs practicing in a variety of primary care settings, many with a range of additional professional responsibilities. Around 60 and 66% of respondents thought that there was a problem with recruitment and retention of GPs and FPs in Singapore, respectively. Strategies focusing on promoting primary care by emphasizing the advantages and enhancing the status of the profession as well as training-related strategies, such as sub-specialisation and high-quality rotations were considered priorities for improving recruitment. For retention of GPs and FPs, improving working conditions by increasing GPs’ and FPs’ salary and recognition, as well as varying or reducing time commitment, were seen as the most important strategies. The ranking between physicians working in public and private sector was mostly similar, with nine out of the top ten recruitment and retention strategies being the same.

Conclusion

Primary care physicians’ ranking of recruitment and retention strategies for GPs and FPs in Singapore provide important insight into the challenges and the solutions as seen by the members of the profession themselves. This information can guide future policy and decision making in this area.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-021-01570-1.

A survey of outpatient Internal Medicine clinician perceptions of diagnostic error

Background Little is known about how practicing Internal Medicine (IM) clinicians perceive diagnostic error, and whether perceptions are in agreement with the published literature. Methods A 16-question survey was administered across two IM practices: one a referral practice providing care for patients traveling for a second opinion and the other a traditional community-based primary care practice. Our aim was to identify individual- and system-level factors contributing to diagnostic error (primary outcome) and conditions at greatest risk of diagnostic error (secondary outcome). Results Sixty-five of 125 clinicians surveyed (51%) responded. The most commonly perceived individual factors contributing to diagnostic error included atypical patient presentations (83%), failure to consider other diagnoses (63%) and inadequate follow-up of test results (53%). The most commonly cited system-level factors included cognitive burden created by the volume of data in the electronic health record (EHR) (68%), lack of time to think (64%) and systems that do not support collaboration (40%). Conditions felt to be at greatest risk of diagnostic error included cancer (46%), pulmonary embolism (43%) and infection (37%). Conclusions Inadequate clinician time and sub-optimal patient and test follow-up are perceived by IM clinicians to be persistent contributors to diagnostic error. Clinician perceptions of conditions at greatest risk of diagnostic error may differ from the published literature.

Microneedle-based devices for point-of-care infectious disease diagnostics

Recent infectious disease outbreaks, such as COVID-19 and Ebola, have highlighted the need for rapid and accurate diagnosis to initiate treatment and curb transmission. Successful diagnostic strategies critically depend on the efficiency of biological sampling and timely analysis. However, current diagnostic techniques are invasive/intrusive and present a severe bottleneck by requiring specialist equipment and trained personnel. Moreover, centralised test facilities are poorly accessible and the requirement to travel may increase disease transmission. Self-administrable, point-of-care (PoC) microneedle diagnostic devices could provide a viable solution to these problems. These miniature needle arrays can detect biomarkers in/from the skin in a minimally invasive manner to provide (near-) real-time diagnosis. Few microneedle devices have been developed specifically for infectious disease diagnosis, though similar technologies are well established in other fields and generally adaptable for infectious disease diagnosis. These include microneedles for biofluid extraction, microneedle sensors and analyte-capturing microneedles, or combinations thereof. Analyte sampling/detection from both blood and dermal interstitial fluid is possible. These technologies are in their early stages of development for infectious disease diagnostics, and there is a vast scope for further development. In this review, we discuss the utility and future outlook of these microneedle technologies in infectious disease diagnosis.

Validation and initial results of surveys exploring perspectives on risks and solutions for diagnostic and medication errors in primary care in Sweden

OBJECTIVE

To (1) validate and (2) display initial results of surveys to health care professionals and patients on the importance and mitigation of specified risks for diagnostic and medication errors.

DESIGN

For validation, psychometric properties were analysed by assessment of construct validity and internal consistency by factor analysis. Non-parametric analyses were used concerning areas of risk, and top ranking of solutions were reported descriptively.

SETTING

Primary health care in Sweden.

PARTICIPANTS

Health care professionals (HCPs); including physicians, nurses and practice managers, as well as patients who had experienced diagnostic or medication errors.

MAIN OUTCOME MEASURES

Psychometric properties of the surveys. Median ratings for risks and top rankings of solutions for professionals and patients.

RESULTS

There were 939 respondents to the HCP survey. Construct validity resulted in a model with four dimensions: Patient-provider level; Support systems for every day clinical work; Shared information and cooperation between different caregivers; Risks in the environment. Internal consistency was acceptable with Cronbach's α values above 0.7. Confirmatory factor analysis generally showed an acceptable fit. Initial results from the professionals showed the importance of continuity of care, a nationwide on-line medical platform and cooperation in transfer of care. The patient survey could not be validated because of low response rate.

CONCLUSION

The HCP survey showed some contradicting results regarding model fit and may be tentatively acceptable but validity needs further study. HCP survey answers indicated that relational continuity of care and a nationwide on-line medical platform are highly valued. Current awareness Health care professionals and patients are rather untapped sources of knowledge regarding patient safety in primary health care Main statements Validation is performed on a new survey capturing rating of risks and solutions. The validation of the health care professional survey is tentatively acceptable. Survey answers indicate that health care professionals' and patients' perspectives are complementary.

The paralyzing legal costs of facial nerve injury in head and neck tumors

PURPOSE

Facial nerve paralysis from head and neck tumors can result from disease progression or iatrogenic causes, leading to litigation. The aim of this study was to investigate lawsuits regarding facial paralysis as a consequence of these tumors to understand and better educate physicians behind the reasons for litigation.

METHODS

Jury verdict reviews were obtained from the Westlaw database from 1985 to 2018. Gathered data, including verdicts, litigation reasons, defendant specialties, and amounts awarded, were analyzed via Statistical Package for the Social Sciences.

RESULTS

Of the 26 lawsuits analyzed, the leading reason for litigation was failure to diagnose (53.8%), followed by iatrogenic injury (34.6%). The average award was $2,704,470. Otolaryngologists were the most common defendants. Defendants that included an otolaryngologist had shorter delays of diagnosis compared to those that did not (p < 0.05).

CONCLUSION

Failure to diagnose parotid injury was the leading cause of litigation. In instances where the jury found for the plaintiff, the amount was material. There were equivalent incidences of cases in favor of plaintiffs and defendants.

Patient and provider perspectives on reducing risk of harm in primary health care: a qualitative questionnaire study in Sweden

Objective: To explore how patients, that had experienced harm in primary care, and how primary providers and practice managers understood reasons for harm and possibilities to reduce risk of harm.Design: Inductive qualitative analysis of structured questionnaires with free text answers.Setting: Primary health care in Sweden.Patients/subjects: Patients (n = 22) who had experienced preventable harm in primary health care, and primary care providers and practice managers, including 15 physicians, 20 nurses and 24 practice managers.Main outcome measures: Categories and overarching themes from the qualitative analysis.Results: The three categories identified as important for safety were continuity of care, communication and competence. With flaws in these, risks were thought to be greater and if these were strengthened the risks could be reduced. The overarching theme for the patient was the experience of being neglected, like not having been properly examined. The overarching theme for primary care providers and practice managers was lack of continuity of care.Conclusion: Primary care providers, practice managers and patients understood the risks and how to reduce the risks of patient safety problems as related to three main categories: continuity of care, communication and competence. Future work towards a safer primary health care could therefore benefit from focusing on these areas.Key pointsCurrent awareness:  • Patients and primary care providers are rather untapped sources of knowledge regarding patient safety in primary health care.Main statements:  • Patients understood the risk of harm as stemming from that they were not properly examined.  • Primary care providers understood the risk of harm to a great extent as stemming from poor continuity of care.  • Patients, primary care providers and practice managers believed continuity, communication and competence play an important role in reducing risks.

Signed, Sealed, Delivered: Increasing Patient Notification of Test Results in an Internal Medicine Resident Continuity Clinic

OBJECTIVES

Informing patients of their test results is an important patient safety issue, yet many physicians perform dismally in this regard. Residents often face additional barriers to communicating test results to patients. We wanted to determine whether streamlining the notification process, communicating expectations, and having residents audit their performance would increase result notification rates.

METHODS

We used a quasi-experimental design, and a single-group before-and-after intervention. Our multifold intervention consisted of development and standardization of a notification process in the electronic medical record, an education component, and a self-audit component. During a 15-minute session, we educated residents on the use of the new process. We also restated expectations regarding notifying patients of their results. Residents audited their own charts for a period before the intervention and during a second, postintervention period. An independent review of notification rates took place simultaneously as well as during an additional period several months later.

RESULTS

In total, 87 residents were eligible for participation. All 87 completed the project, giving a 100% participation rate. Resident-reported laboratory test notification rates increased from 16% to 91%; other test result rates increased from 33% to 84%. The three independent reviews showed laboratory test notification rates increased from 18.5% to 71.7% to 87.1%, and notification of other test results increased from 23.5% to 66.7% to 91.7%.

CONCLUSIONS

Baseline rates of notification for diagnostic tests results were low, but streamlining the notification process, clearly stating expectations for using it, and using resident self-audit can improve notification rates.

The Use of Artificially Intelligent Self-Diagnosing Digital Platforms by the General Public: Scoping Review

BACKGROUND

Self-diagnosis is the process of diagnosing or identifying a medical condition in oneself. Artificially intelligent digital platforms for self-diagnosis are becoming widely available and are used by the general public; however, little is known about the body of knowledge surrounding this technology.

OBJECTIVE

The objectives of this scoping review were to (1) systematically map the extent and nature of the literature and topic areas pertaining to digital platforms that use computerized algorithms to provide users with a list of potential diagnoses and (2) identify key knowledge gaps.

METHODS

The following databases were searched: PubMed (Medline), Scopus, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers, Google Scholar, Open Grey, and ProQuest Dissertations and Theses. The search strategy was developed and refined with the assistance of a librarian and consisted of 3 main concepts: (1) self-diagnosis; (2) digital platforms; and (3) public or patients. The search generated 2536 articles from which 217 were duplicates. Following the Tricco et al 2018 checklist, 2 researchers screened the titles and abstracts (n=2316) and full texts (n=104), independently. A total of 19 articles were included for review, and data were retrieved following a data-charting form that was pretested by the research team.

RESULTS

The included articles were mainly conducted in the United States (n=10) or the United Kingdom (n=4). Among the articles, topic areas included accuracy or correspondence with a doctor's diagnosis (n=6), commentaries (n=2), regulation (n=3), sociological (n=2), user experience (n=2), theoretical (n=1), privacy and security (n=1), ethical (n=1), and design (n=1). Individuals who do not have access to health care and perceive to have a stigmatizing condition are more likely to use this technology. The accuracy of this technology varied substantially based on the disease examined and platform used. Women and those with higher education were more likely to choose the right diagnosis out of the potential list of diagnoses. Regulation of this technology is lacking in most parts of the world; however, they are currently under development.

CONCLUSIONS

There are prominent research gaps in the literature surrounding the use of artificially intelligent self-diagnosing digital platforms. Given the variety of digital platforms and the wide array of diseases they cover, measuring accuracy is cumbersome. More research is needed to understand the user experience and inform regulations.

[Effectiveness of a new model of telephone derivation shared between primary care and hospital care]

Objetivo

Averiguar si la derivación telefónica desde Atención Primaria a consultas externas de Medicina Interna (CCEE de MI) reduce días de espera, con respecto a la derivación presencial. Averiguar la aceptación de la consulta telefónica por parte de los médicos de familia (MF) de Atención Primaria y de sus pacientes.

Diseño

Ensayo clínico controlado aleatorizado sin enmascaramiento.

Emplazamiento

Área de Gestión Sanitaria Norte de Huelva.

Participantes

Ciento cincuenta y cuatro pacientes.

Intervenciones

Los pacientes de los MF del grupo experimental fueron derivados vía telefónica (salvo cumplimiento criterios exclusión) y los del grupo control vía presencial.

Mediciones

Número de días desde la solicitud de derivación hasta la consulta en MI. Número de derivaciones telefónicas y presenciales. Número de médicos y de pacientes rechazados. Causas de los rechazos.

Resultados

Diferencia estadísticamente significativa, estimándose en 27 (21-34) días entre ambos grupos. De los 58 MF, 8 prealeatorización, y 6 de los 20 asignados al grupo experimental rechazaron participar por «suponer consumo excesivo de tiempo y esfuerzo». Para un 50% de los pacientes derivados por los 14 MF que quedaron finalmente en el grupo experimental se rechazó la vía telefónica, siendo la complejidad de los pacientes la principal causa.

Conclusiones

La derivación telefónica reduce considerablemente los días de espera para CCEE de MI, elimina las principales barreras de la consulta telefónica a tiempo real, no supuso un mayor gasto de tiempo ni de esfuerzo para los médicos y no se consideró tan beneficiosa en pacientes complejos.

Prioritizing problems in and solutions to homecare safety of people with dementia: supporting carers, streamlining care

BACKGROUND

Dementia care is predominantly provided by carers in home settings. We aimed to identify the priorities for homecare safety of people with dementia according to dementia health and social care professionals using a novel priority-setting method.

METHODS

The project steering group determined the scope, the context and the criteria for prioritization. We then invited 185 North-West London clinicians via an open-ended questionnaire to identify three main problems and solutions relating to homecare safety of people with dementia. 76 clinicians submitted their suggestions which were thematically synthesized into a composite list of 27 distinct problems and 30 solutions. A group of 49 clinicians arbitrarily selected from the initial cohort ranked the composite list of suggestions using predetermined criteria.

RESULTS

Inadequate education of carers of people with dementia (both family and professional) is seen as a key problem that needs addressing in addition to challenges of self-neglect, social isolation, medication nonadherence. Seven out of top 10 problems related to patients and/or carers signalling clearly where help and support are needed. The top ranked solutions focused on involvement and education of family carers, their supervision and continuing support. Several suggestions highlighted a need for improvement of recruitment, oversight and working conditions of professional carers and for different home safety-proofing strategies.

CONCLUSIONS

Clinicians identified a range of suggestions for improving homecare safety of people with dementia. Better equipping carers was seen as fundamental for ensuring homecare safety. Many of the identified suggestions are highly challenging and not easily changeable, yet there are also many that are feasible, affordable and could contribute to substantial improvements to dementia homecare safety.