Long-term experience with setup and implementation of an IHE-based image management and distribution system in intersectoral clinical routine

A multidisciplinary neuro-oncological triage panel reduces the time to referral and treatment for patients with a brain tumor

Background

Regional collaboration and appropriate referral management are crucial in neuro-oncological care. Lack of electronic access to medical records across health care organizations impedes interhospital consultation and may lead to incomplete and delayed referrals. To improve referral management, we have established a multidisciplinary neuro-oncological triage panel (NOTP) with digital image exchange and determined the effects on lead times, costs, and time investment.

Methods

A prospective cohort study was conducted from February 2019 to March 2020. All newly diagnosed patients referred to Brain Tumor Center Amsterdam were analyzed according to referral pathway: (1) standard referral (SR), (2) NOTP. The primary outcome was lead time, defined as time-to-referral, time-to-treatment, and total time (median days [interquartile range]). Secondary outcomes were costs and time investment.

Results

In total, 225 patients were included, of whom 153 had SR and 72 NOTP referral. Patients discussed in the NOTP were referred more frequently for first neurosurgical consultation (44.7% vs 28.8%) or combined neurological and neurosurgical consultation (12.8% vs 2.5%, P = .002). Time-to-referral was reduced for NOTP referral compared to SR (1 [0.25-4] vs 6 [1.5-10] days, P < .001). Total time decreased from 27 [14-48] days for the standard group to 15 [12-38.25] days for the NOTP group (P = .040). Costs and time investment were comparable for both groups.

Conclusion

Implementation of digital referral to a multidisciplinary NOTP is feasible and leads to more swift patient-tailored referrals at comparable costs and time investment as SR. This quality improvement initiative has the potential to improve collaboration and coordination of multidisciplinary care in the field of neuro-oncology.

Utility and Perceived Value of a Provincial Digital Diagnostic Imaging Repository: Multimethod Study

Background

Timely and comprehensive diagnostic image sharing across institutional and regional boundaries can produce multiple benefits while supporting integrated models of care. In Ontario, Canada, the Diagnostic Imaging Common Service (DICS) was created as a centralized imaging repository to enable the sharing and viewing of diagnostic images and associated reports across hospital-based and community-based clinicians throughout the province.

Objective

The aims of this study were as follows: (1) to explore real-world utilization and perceived clinical value of the DICS following the provision of system-wide access and (2) to identify strategies to optimize the technology platform functionality and encourage adoption.

Methods

This multimethod study included semistructured interviews with physicians and administrative stakeholders and descriptive analysis of the current DICS usage data.

Results

In this study, 41 participants were interviewed, that is, 34 physicians and 7 administrative stakeholders. The following 4 key themes emerged: (1) utilization of the DICS depended on the awareness of the technology and the preferred channels for accessing images, which varied widely, (2) clinical responsibilities and available institutional resources were the drivers of utilization (or lack thereof), (3) centralized image repositories were perceived to offer value at the patient, clinician, and health care system levels, and (4) the enabling factors to realize value included aspects of technology infrastructure (ie, available functionality) alongside policy supports. High-volume DICS usage was not evenly distributed throughout the province.

Conclusions

Suboptimal adoption of the DICS was driven by poor awareness and variations in the clinical workflow. Alignment with physician workflow, policy supports, and investment in key technological features and infrastructure would improve functionality and data comprehensiveness, thereby optimizing health system performance, patient and provider experience, population health, and health care costs.