The Elimination of Transfer Distances Is an Important Part of Hospital Design

A knowledge framework for the design of built environment supportive of resilient internal logistics in hospitals

Internal logistics is crucial for hospitals, occurring within facilities that pose constraints and opportunities, demanding resilient performance (RP) to adapt to dynamic conditions and balance safety and efficiency pressures. However, the role of the built environment (BE) to support RP is not explicitly analysed in the hospital logistics literature, which is usually limited to discuss BE in terms of layout and routing issues. To address this gap, this study presents a knowledge framework of BE supportive of RP in internal hospital logistics. The framework was developed based on a study in a large teaching hospital, encompassing 11 service flows of people and supplies between an intensive care unit and other units. Data collection was based on 38 interviews, documents such as floor plans, and observations of logistics activities. Seven BE design principles developed in a previous study, concerned with RP in general but not focused on logistics, were adopted as initial themes for data analysis. Results of the thematic analysis gave rise to a knowledge framework composed of seven design prescriptions and 63 practical examples of BE supportive of RP in hospital internal logistics. The paper discusses how these prescriptions and examples are connected to resilience management. The framework is new in the context of internal hospital logistics and offers guidance to both BE and logistics designers.

Identifying Modifiable Cost Drivers of Outpatient Unicompartmental Knee Arthroplasty With Machine Learning

BACKGROUND

Implementing tools that identify cost-saving opportunities for ambulatory orthopaedic surgeries can improve access to value-based care. We developed and internally validated a machine learning (ML) algorithm to predict cost drivers of total charges after ambulatory unicompartmental knee arthroplasty (UKA).

METHODS

We queried the New York State Ambulatory Surgery and Services database to identify patients who underwent ambulatory, defined as <24 hours of care before discharge, elective UKA between 2014 and 2016. A total of 1,311 patients were included. The median costs after ambulatory UKA were $14,710. Patient demographics and intraoperative parameters were entered into 4 candidate ML algorithms. The most predictive model was selected following internal validation of candidate models, with conventional linear regression as a benchmark. Global variable importance and partial dependence curves were constructed to determine the impact of each input parameter on total charges.

RESULTS

The gradient-boosted ensemble model outperformed all candidate algorithms and conventional linear regression. The major differential cost drivers of UKA identified (in decreasing order of magnitude) were increased operating room time, length of stay, use of regional and adjunctive periarticular analgesia, utilization of computer-assisted navigation, and routinely sending resected tissue to pathology.

CONCLUSION

We developed and internally validated a supervised ML algorithm that identified operating room time, length of stay, use of computer-assisted navigation, regional primary anesthesia, adjunct periarticular analgesia, and routine surgical pathology as essential cost drivers of UKA. Following external validation, this tool may enable surgeons and health insurance providers optimize the delivery of value-based care to patients receiving outpatient UKA.

LEVEL OF EVIDENCE

III.

Key Flow Processes on Wards

Objective:

The aim of the study is to test a new nurse movement route analysis (NMRA) method for measuring nurses’ traffic volume between rooms on wards.

Background:

The World Health Organization calls for urgent investment in nurses. On the other hand, the challenges in the availability, direct care activity, and staffing of registered nurses make increasing the quality of care by process improvement a central objective for nursing.

Method:

The method is based on cellular operations with from/to matrix that describes nurse movements between rooms on a ward. The NMRA can be implemented by traditional manual observation or with a novel internet-of-things solution named SKAnalysis.

Results:

The greatest nurse flows led to patient rooms, nurses’ stations, and medicine rooms. The manual NMRA recorded a total of 3,040 room visits by nurses; visits to patient rooms accounted for 33% of all room visits, while visits to nurses’ stations accounted for 28%, and visits to the medicine room for 10%. The internet-of-things NMRA recorded a total of 25,841 room visits by nurses; patient room visits accounted for about 43% of all room visits, while nurses’ station visits accounted for 26% and medicine room visits for about 8%. Based on the results, researchers present the development examples and priorities for nursing.

Conclusions:

NMRA works and is a new universal method for analyzing nurses’ traffic which is a basic premise for improving working methods and productivity on the wards. Internet-of-things solution makes the implementation of NMRA six times more efficient than by the manual NMRA.

Patient-Flow Analysis for Planning a Focused Hospital Layout: Tampere Heart Hospital Case

OBJECTIVE

The objective of this study is present how a patient movement-based patient-flow analysis is performed for planning the new Heart Hospital of Tampere University Hospital and how patient transfer distances can be shortened by this method.

BACKGROUND

The Heart Hospital had served patients as a service line organization for years. However, the Heart Hospital layout rather looked like functional layout instead of service line layout because the units of the Heart Hospital have been spread out around the large university hospital campus.

METHOD

The flow routes of patients treated over the course of 1 year were analyzed by information technology systems in the hospital planning phase. Then, the proximity ranking of the main functions of the Heart Hospital was made. Layout planning was performed based on the proximity ranking. Nine months after the opening of the new Heart Hospital, the distances between the various hospital functions were calculated for the old Heart Hospital and the new one.

RESULTS

In the old Heart Hospital, patients' transfer distance was 5,654 km (3,513 miles), while the corresponding figure for the new Heart Hospital was 3,797 km (2,359 miles), which means the distance was reduced by 33%.

CONCLUSION

The patient-flow analysis works as it generated substantially shorter patient transfer distances in the new Heart Hospital. Shorter distances have supported more fluent patient flows that, in turn, has contributed higher productivity and quality of care.

The Built Environment Influence on Resilient Healthcare: A Systematic Literature Review of Design Knowledge

OBJECTIVE

The aim of this study was to develop built environment (BE) design knowledge to support resilient healthcare by systematically reviewing the evidence-based design (EBD) literature.

BACKGROUND

Although the EBD literature is vast, it has not made explicit its contribution to resilient healthcare, which is a key component of the highly complex health service.

METHOD

This review followed the steps recommended by the Preferred Reporting Items for Systematic reviews and Meta-Analyses method. After applying the inclusion and exclusion criteria, 43 journal papers were selected. The papers were analyzed in light of five guidelines for coping with complexity, allowing for the development of BE design knowledge that supports resilient healthcare.

RESULTS

The design knowledge compiled by the review was structured according to four levels of abstraction: five design-meta principles, corresponding to the five complexity guidelines, seven design principles, 21 design prescriptions, and 58 practical examples. The design knowledge emphasizes the interactions between the BE as physical infrastructure and the functions that it supports.

CONCLUSIONS

The design knowledge is expected to be useful not only to architects but also to those involved in the functional design of health services as they interact with the BE. Furthermore, our proposal provides a knowledge template that can be continuously updated based on the experience of practitioners and academic research.

Evidence-Based Design for Waiting Space Environment of Pediatric Clinics-Three Hospitals in Shenzhen as Case Studies

This study explores the waiting space environment of pediatric clinics in general hospitals and the relationships between the use of space, behavioral activities and overall satisfaction. Patients often spend a lot of time waiting for doctors, and child patients waiting to be seen are particularly likely to feel bored, depressed and anxious, which negatively affects their overall experience of seeking medical attention. Since the launch of China's second-child policy, the number of children born in China has surged. As medical resources for children are in short supply and of uneven quality, it is urgently necessary to carry out research on optimizing the design of children's waiting space in Chinese hospitals to improve their medical environment and experience.

METHOD

This study identified four first-level indicators and twenty-seven second-level indicators in four dimensions: functional layout (layout and area), flow organization, supporting facilities and environmental details (physical and landscape environment). The research combined subjective and objective methods, including comprehensive observation, a questionnaire survey and interviews, taking three hospitals in Shenzhen as case studies.

RESULTS

The study found that the waiting space in pediatric clinics currently fails to meet key patient needs in areas such as mother and infant rooms, children's play areas and drinking water facilities, and there are widespread problems with the creation of natural environments, such as views of natural scenery from windows and indoor green plants. Six factors were found to significantly positively influence overall satisfaction with waiting space, describing 69.76% of the changes in the respondents' degree of satisfaction with the waiting environment. Supporting facilities and aspects of the physical environment had the greatest influence on overall satisfaction with the waiting space.

CONCLUSION

Optimizing the design of the waiting space in pediatric clinics, with a focus on functional layout, flow organization, supporting facilities and environmental details, can improve overall satisfaction with pediatric waiting rooms. The results are preliminary; they need to be further tested in practice to complete the process of evidence-based design. This will lead to suggestions for refining the design of pediatric waiting units which can be used by architects and hospital administrators.