Closing the Loop on Electronic Referrals: A Quality Improvement Initiative Using the Care Coordination Model

Consultants' and referrers' perceived barriers to closing the cross-institutional referral loop, and perceived impact on clinical care

BACKGROUND

Cross-institutional (external) referrals are prone to communication breakdowns, increasing patient safety risks, clinician burnout, and healthcare costs. To close these external referral loops, referring primary care physicians (PCPs) need to receive patient information from consultants at different healthcare institutions. Although existing studies investigated the early phases of external referral loops, we lack sufficient knowledge about the closing phases of these loops. This knowledge could allow health care institutions to improve care coordination and rates of closed referral loops by implementing socio-technical interventions for patient information exchange throughout a referral loop. Human factors engineering (HFE) provides a systematic approach to advance our understanding of barriers perceived by physicians. Using HFE, our objective was to characterize referring and consulting physicians' barriers to closing referral loops and implications for care.

METHODS

This qualitative cross-sectional study included semi-structured interviews with referrers and external consultants. We used the Systems Engineering Initiative for Patient Safety 2.0 framework to conduct rapid qualitative analyses, determining perceived barriers and related implications. Main measures were consultants' and referrers' perceptions of, and experiences with, barriers to external referrals.

RESULTS

Six referring PCPs and 12 consultants participated from two healthcare systems and four medical specialties. Physicians perceived three main barriers in external referrals: receipt of excessive and unnecessary faxed documents, missing or delayed documentation, and organizational policies regarding information privacy interfering with closing the loop. Compared to internal referrals, physicians reported increased staff burden, patient frustration, and delays in diagnosis with external referrals. Consultants reported the ability to provide the same level of care to patients with internal or external referrals. However, consultants described communication breakdowns that prohibited confirmation of follow-up plan retrieval, initiation, or effectiveness.

CONCLUSION

Physicians reported technological and organizational barriers to closing cross-institutional referral loops. Promises of HIE technology for external referrals have not fully materialized. Among physicians and patients, retrieval and exchange of medical information increases perceived workload, burden, and frustration. These increases are not accurately captured by traditional organizational metrics. This study provides evidence that informs future human factors engineering research to address perceived barriers and guide future HIE design or implementation.

Evidence-Based Quality Improvement: a Scoping Review of the Literature

BACKGROUND

Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development.

METHODS

In this scoping review (registration: https://osf.io/hr5bj ) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI?

RESULTS

We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term "EBQI." Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term "EBQI" with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes.

CONCLUSIONS

EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.

Systems engineering analysis of diagnostic referral closed-loop processes

BACKGROUND

Closing loops to complete diagnostic referrals remains a significant patient safety problem in most health systems, with 65%-73% failure rates and significant delays common despite years of improvement efforts, suggesting new approaches may be useful. Systems engineering (SE) methods increasingly are advocated in healthcare for their value in studying and redesigning complex processes.

OBJECTIVE

Conduct a formative SE analysis of process logic, variation, reliability and failures for completing diagnostic referrals originating in two primary care practices serving different demographics, using dermatology as an illustrating use case.

METHODS

An interdisciplinary team of clinicians, systems engineers, quality improvement specialists, and patient representatives collaborated to understand processes of initiating and completing diagnostic referrals. Cross-functional process maps were developed through iterative group interviews with an urban community-based health centre and a teaching practice within a large academic medical centre. Results were used to conduct an engineering process analysis, assess variation within and between practices, and identify common failure modes and potential solutions.

RESULTS

Processes to complete diagnostic referrals involve many sub-standard design constructs, with significant workflow variation between and within practices, statistical instability and special cause variation in completion rates and timeliness, and only 21% of all process activities estimated as value-add. Failure modes were similar between the two practices, with most process activities relying on low-reliability concepts (eg, reminders, workarounds, education and verification/inspection). Several opportunities were identified to incorporate higher reliability process constructs (eg, simplification, consolidation, standardisation, forcing functions, automation and opt-outs).

CONCLUSION

From a systems science perspective, diagnostic referral processes perform poorly in part because their fundamental designs are fraught with low-reliability characteristics and mental models, including formalised workaround and rework activities, suggesting a need for different approaches versus incremental improvement of existing processes. SE perspectives and methods offer new ways of thinking about patient safety problems, failures and potential solutions.