The need scoping and prioritization of the medical team to integrate new technologies for inpatient rehabilitation services

Design and process optimization of combined medical and elderly care services: An integrated service blueprint-TRIZ model

China's increasingly aging population is resulting in an imbalance between supply and demand for elderly care resources. The theory of "combined medical and elderly care" (CMEC) has introduced a new perspective in the conception of China's elderly care problems. This study employed the service blueprint, fuzzy failure mode and effects analysis (Fuzzy-FMEA), and the theory of inventive problem solving (TIPS or the Russian acronym TRIZ) for the process optimization of CMEC services in three phases. In the first phase (service process analysis), potential service failure points in the service process were analyzed using the service blueprint technique. In the second phase (service failure diagnosis), Fuzzy-FMEA was applied to diagnose the service failure modes and explore the possible causes and effects. The service failure modes were then prioritized based on fuzzy numbers and the cumulative fuzzy risk priority number (Fuzzy-RPN). Finally, in the third phase (generation of service optimization solutions), the TRIZ parameters, inventive principles, and contradiction matrix were first employed to select TRIZ inventive principles. The selected TRIZ inventive principles were then used to inspire inventive solutions for new service processes. Finally, a case study was conducted on the service processes of elderly care institutions to demonstrate the applicability of the optimization solutions.

Supporting rehabilitation stakeholders in making service delivery decisions: a rapid review of multi-criteria decision analysis methods

PURPOSE

This review aimed to synthesize knowledge about multi-criteria decision analysis methods for supporting rehabilitation service design and delivery decisions, including: (1) describing the use of these methods within rehabilitation, (2) identifying decision types that can be supported by these methods, (3) describing client and family involvement, and (4) identifying implementation considerations.

METHODS

We conducted a rapid review in collaboration with a knowledge partner, searching four databases for peer-reviewed articles reporting primary research. We extracted relevant data from included studies and synthesized it descriptively and with conventional content analysis.

RESULTS

We identified 717 records, of which 54 met inclusion criteria. Multi-criteria decision analysis methods were primarily used to understand the strength of clients' and clinicians' preferences (n = 44), and five focused on supporting decision making. Shared decision making with stakeholders was evident in only two studies. Clients and families were mostly engaged in data collection and sometimes in selecting the relevant criteria. Good practices for supporting external validity were inconsistently reported. Implementation considerations included managing cognitive complexity and offering authentic choices.

CONCLUSIONS

Multi-criteria decision analysis methods are promising for better understanding client and family preferences and priorities across rehabilitation professions, contexts, and caseloads. Further work is required to use these methods in shared decision making, for which increased use of qualitative methods and stakeholder engagement is recommended. IMPLICATIONS FOR REHABILITATIONMulti-criteria decision analysis methods are promising for evidence-based, shared decision making for rehabilitation.However, most studies to date have focused on estimating stakeholder preferences, not supporting shared decision making.Cognitive complexity and modelling authentic and realistic decision choices are major barriers to implementation.Stakeholder-engagement and qualitative methods are recommended to address these barriers.

Preventing COVID-19 from the perspective of industrial information integration: Evaluation and continuous improvement of information networks for sustainable epidemic prevention

COVID-19 is accelerating industrial information integration (III) for sustainable epidemic prevention and innovation design. It is important to emphasize that this interaction makes it reciprocal. To prevent COVID-19, the III of industrial sectors should be strengthened to encourage innovation for sustainable epidemic prevention. Accordingly, we studied the overall dynamic change trend of industrial sectors' information integration networks (IIN), the characteristics of individual IIN, and their influence on IIN performance. In the study, the gravity model and social network analysis were used to determine the variables of industrial sectors' information distance and quality, and to construct the IIN of industrial sectors. The results show that the overall relevance of the IIN of industrial sectors is low, and the network density fluctuates, with high network efficiency and poor stability. Two-way, strong correlation between industrial sectors is relatively low. The spillover effect of industrial sectors in the upstream of the industrial chain is poor, and it is difficult to have a strong information integration driving effect on the downstream industrial sectors. The interplate linkage of the IIN of industrial sectors is insufficient. Compared with point centrality and closeness, improvement of the betweenness centrality of industrial sectors can significantly improve IIN performance.