A cost comparison study to review community versus acute hospital models of nursing care delivered to oncology patients

Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology

How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve the patient experience are problems faced by all hospitals. At present, the combination of artificial intelligence and the medical field is mainly in the field of disease diagnosis, but lacks successful application in medical management. We distinguish each area of the emergency department by the division of medical links. In the spatial dimension, in this study, the waitlist number in real-time is got by processing videos using image recognition via a convolutional neural network. The congestion rate based on psychology and architecture is defined for measuring crowdedness. In the time dimension, diagnosis time and time-consuming after diagnosis are calculated from visit records. Factors related to congestion are analyzed. A total of 4717 visit records from the emergency department and 1130 videos from five areas are collected in the study. Of these, the waiting list of the pediatric waiting area is the largest, including 10,436 (person-time) people, and its average congestion rate is 2.75, which is the highest in all areas. The utilization rate of pharmacy is low, with an average of only 3.8 people using it at the one time. Its average congestion rate is only 0.16, and there is obvious space waste. It has been found that the length of diagnosis time and the length of time after diagnosis are related to age, the number of diagnoses and disease type. The most common disease type comes from respiratory problems, accounting for 54.3%. This emergency department has congestion and waste of medical resources. People can use artificial intelligence to investigate the congestion in hospitals effectively. Using artificial intelligence methods and traditional statistics methods can lead to better research on healthcare resource allocation issues in hospitals.

A mixed methods analysis of the monitoring of oral anti-cancer therapies

PURPOSE

Oral anti-cancer therapies offer advantages over parenteral therapies in terms of their non-invasive nature and reduced intrusiveness. However, the shift from directly observed administration of these therapies to home administration means that continuous monitoring is needed. The oral anti-cancer therapy market is rapidly growing, with an ever-increasing number of new medicines available for the patients presenting with cancer illnesses. This study aims to (i) evaluate both the cost of providing monitoring consultations of oral anti-cancer therapies, and (ii) to assess the experience of cancer therapy nurses responsible for the monitoring and their opinions of the quality of the service.

METHODS

This study provides a mixed methods evaluation of the monitoring of oral anti-cancer therapies. Nurses were asked to record the time taken for them to perform their monitoring duties, and staff related costs were calculated using publicly available salary data. Patient-related costs were calculated using the Human Capital method. Nurses were asked to discuss their experience of monitoring oral anti-cancer therapies in semi-structured interviews. These interviews were subsequently analysed using thematic analysis.

RESULTS

201 recordings and their associated costs were documented. The median consultation time was 33 min, costing €22.10 using Clinical Nurse Specialist salary figures and €26.51 using Advanced Nurse Practitioner salary figures. The associated patient cost was €14.06. Themes of the effect of Covid-19 on the service, expanding and complicated care package requirements, the need for dedicated oral clinics and the future of the service emerged from the interview data.

CONCLUSION

The monitoring service provided by nurses may be undervalued. The commitment to fully dedicated oral anti-cancer therapy clinics and an increase in staff to align with the ongoing increase in service demand is seen as vital for the continued safe and effective delivery of this specialist cancer service.

A qualitative evaluation of community and acute hospital nursing oncology services in Ireland

PURPOSE

Cancer patients are a particularly vulnerable population group, facing an increase in physical, mental, logistical and financial difficulties. This, as well as Ireland's increased focus on primary care with the Sláintecare health plan, led to the development of the Community Oncology Nursing Programme, where community nurses are trained to provide cancer care in the community. This paper sought to explore the lived experiences of the patients and nurses involved in this programme in order to examine its impact as well as determine facilitators and roadblocks for future development.

METHODS

A qualitative examination of the service was carried out by interviewing cancer patients receiving care as part of the programme as well as the nurses delivering care, both in the community and hospital day-ward. Thematic analysis was used.

RESULTS

Themes of improved patient experience, nurse-patient relationship, the importance of location and roadblocks to further implementation of the programme emerged. There was a universal belief that the programme offered benefits to the patient and improved their care in some manner.

CONCLUSIONS

The Community Oncology Nursing Programme has been well received by both nurses and patients. The service provided by community nurses as part of this programme offers benefits to patients and an improved cancer service.