Motivating and engaging frontline providers in measuring and improving team clinical performance

How does nursing-sensitive indicator feedback with nursing or interprofessional teams work and shape nursing performance improvement systems? A rapid realist review

BACKGROUND

Care quality varies between organizations and even units within an organization. Inadequate care can have harmful financial and social consequences, e.g. nosocomial infection, lengthened hospital stays or death. Experts recommend the implementation of nursing performance improvement systems to assess team performance and monitor patient outcomes as well as service efficiency. In practice, these systems provide nursing or interprofessional teams with nursing-sensitive indicator feedback. Feedback is essential since it commits teams to improve their practice, although it appears somewhat haphazard and, at times, overlooked. Research findings suggest that contextual dynamics, initial system performance and feedback modes interact in unknown ways. This rapid review aims to produce a theorization to explain what works in which contexts, and how feedback to nursing or interprofessional teams shape nursing performance improvement systems.

METHODS

Based on theory-driven realist methodology, with reference to an innovative combination of Actor-Network Theory and Critical Realist philosophy principles, this realist rapid review entailed an iterative procedure: 8766 documents in French and English, published between 2010 and 2018, were identified via 5 databases, and 23 were selected and analysed. Two expert panels (scientific and clinical) were consulted to improve the synthesis and systemic modelling of an original feedback theorization.

RESULTS

We identified three hypotheses, subdivided into twelve generative configurations to explain how feedback mobilizes nursing or interprofessional teams. Empirically founded and actionable, these propositions are supported by expert panels. Each configuration specifies contextualized mechanisms that explain feedback and team outcomes. Socially mediated mechanisms are particularly generative of action and agency.

CONCLUSIONS

This rapid realist review provides an informative theoretical proposition to embrace the complexity of nursing-sensitive indicator feedback with nursing or interdisciplinary teams. Building on general explanations previously observed, this review provides insight into a deep explanation of feedback mechanisms.

SYSTEMATIC REVIEW REGISTRATION

Prospero CRD42018110128 .

Purpose, Subject, and Consumer Comment on "Perceived Burden Due to Registrations for Quality Monitoring and Improvement in Hospitals: A Mixed Methods Study"

Zegers and colleagues' study codifies the perceived burden of quality monitoring and improvement stemming from the work by clinicians of registering (documenting) quality information in the medical record. We agree with Zegers and colleagues' recommendation that a smaller, more effective and curated set of measures is needed to reduce burden, confusion, and expense. We further note that focusing on validity of clinical evidence behind individual measures is critical, but insufficient. We therefore extend Zegers and colleagues' work through a pragmatic, tripartite heuristic. To assess the value of and curate a targeted set of performance measures, we propose concentrating on the relationships among three factors: (1) The purpose of the performance measure, (2) the subject being evaluated, and (3) the consumer using information for decision-making. Our proposed tripartite framework lays the groundwork for executing the evidence-based recommendations proposed by Zegers et al, and provides a path forward for more effective healthcare performance-measurement systems.

An evidence-based, structured, expert approach to selecting essential indicators of primary care quality

BACKGROUND

The purpose of this article is to illustrate the application of an evidence-based, structured performance measurement methodology to identify, prioritize, and (when appropriate) generate new measures of health care quality, using primary care as a case example. Primary health care is central to the health care system and health of the American public; thus, ensuring high quality is essential. Due to its complexity, ensuring high-quality primary care requires measurement frameworks that can assess the quality of the infrastructure, workforce configurations, and processes available. This paper describes the use of the Productivity Measurement and Enhancement System (ProMES) to compile a targeted set of such measures, prioritized according to their contribution and value to primary care.

METHODS

We adapted ProMES to select and rank existing primary care measures according to value to the primary care clinic. Nine subject matter experts (SMEs) consisting of clinicians, hospital leaders and national policymakers participated in facilitated expert elicitation sessions to identify objectives of performance, corresponding measures, and priority rankings.

RESULTS

The SMEs identified three fundamental objectives: access, patient-health care team partnerships, and technical quality. The SMEs also selected sixteen performance indicators from the 44 pre-vetted, currently existing measures from three different data sources for primary care. One indicator, Team 2-Day Post Discharge Contact Ratio, was selected as an indicator of both team partnerships and technical quality. Indicators were prioritized according to value using the contingency functions developed by the SMEs.

CONCLUSION

Our article provides an actionable guide to applying ProMES, which can be adapted to the needs of various industries, including measure selection and modification from existing data sources, and proposing new measures. Future work should address both logistical considerations (e.g., data capture, common data/programming language) and lingering measurement challenges, such as operationalizating measures to be meaningful and interpretable across health care settings.

Improving team coordination in primary-care settings via multifaceted team-based feedback: a non-randomised controlled trial study

Background

Coordination is critical to successful team-based health care. Most clinicians, however, are not trained in effective coordination or teamwork. Audit and feedback (A&F) could improve team coordination, if designed with teams in mind.

Aim

The effectiveness of a multifaceted, A&F-plus-debrief intervention was tested to establish whether it improved coordination in primary care teams compared with controls.

Design & setting

Case-control trial within US Veterans Health Administration medical centres.

Method

Thirty-four primary care teams selected from four geographically distinct hospitals were compared with 34 administratively matched control teams. Intervention-arm teams received monthly A&F reports about key coordination behaviours and structured debriefings over 7 months. Control teams were followed exclusively via their clinical records. Outcome measures included a coordination composite and its component indicators (appointments starting on time, timely recall scheduling, emergency department utilisation, and electronic patient portal enrolment). Predictors included intervention arm, extent of exposure to intervention, and degree of multiple team membership (MTM).

Results

Intervention teams did not significantly improve over control teams, even after adjusting for MTM. Follow-up analyses indicated cross-team variability in intervention fidelity; although all intervention teams received feedback reports, not all teams attended all debriefings. Compared with their respective baselines, teams with high debriefing exposure improved significantly. Teams with high debriefing exposure improved significantly more than teams with low exposure. Low exposure teams significantly increased patient portal enrolment.

Conclusion

Team-based A&F, including adequate reflection time, can improve coordination; however, the effect is dose dependent. Consistency of debriefing appears more critical than proportion of team members attending a debriefing for ensuring implementation fidelity and effectiveness.

Assessment of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) Program for Improving Quality of Care for Transient Ischemic Attack: A Nonrandomized Cluster Trial

IMPORTANCE

Patients with transient ischemic attack (TIA) are at high risk of recurrent vascular events. Timely management can reduce that risk by 70%; however, gaps in TIA quality of care exist.

OBJECTIVE

To assess the performance of the Protocol-Guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) intervention to improve TIA quality of care.

DESIGN, SETTING, AND PARTICIPANTS

This nonrandomized cluster trial with matched controls evaluated a multicomponent intervention to improve TIA quality of care at 6 diverse medical centers in 6 geographically diverse states in the US and assessed change over time in quality of care among 36 matched control sites (6 control sites matched to each PREVENT site on TIA patient volume, facility complexity, and quality of care). The study period (defined as the data period) started on August 21, 2015, and extended to May 12, 2019, including 1-year baseline and active implementation periods for each site. The intervention targeted clinical teams caring for patients with TIA.

INTERVENTION

The quality improvement (QI) intervention included the following 5 components: clinical programs, data feedback, professional education, electronic health record tools, and QI support.

MAIN OUTCOMES AND MEASURES

The primary outcome was the without-fail rate, which was calculated as the proportion of veterans with TIA at a specific facility who received all 7 guideline-recommended processes of care for which they were eligible (ie, anticoagulation for atrial fibrillation, antithrombotic use, brain imaging, carotid artery imaging, high- or moderate-potency statin therapy, hypertension control, and neurological consultation). Generalized mixed-effects models with multilevel hierarchical random effects were constructed to evaluate the intervention associations with the change in the mean without-fail rate from the 1-year baseline period to the 1-year intervention period.

RESULTS

Six facilities implemented the PREVENT QI intervention, and 36 facilities were identified as matched control sites. The mean (SD) age of patients at baseline was 69.85 (11.19) years at PREVENT sites and 71.66 (11.29) years at matched control sites. Most patients were male (95.1% [154 of 162] at PREVENT sites and 94.6% [920 of 973] at matched control sites at baseline). Among the PREVENT sites, the mean without-fail rate improved substantially from 36.7% (58 of 158 patients) at baseline to 54.0% (95 of 176 patients) during a 1-year implementation period (adjusted odds ratio, 2.10; 95% CI, 1.27-3.48; P = .004). Comparing the change in quality at the PREVENT sites with the matched control sites, the improvement in the mean without-fail rate was greater at the PREVENT sites than at the matched control sites (36.7% [58 of 158 patients] to 54.0% [95 of 176 patients] [17.3% absolute improvement] vs 38.6% [345 of 893 patients] to 41.8% [363 of 869 patients] [3.2% absolute improvement], respectively; absolute difference, 14%; P = .008).

CONCLUSIONS AND RELEVANCE

The implementation of this multifaceted program was associated with improved TIA quality of care across the participating sites. The PREVENT QI program is an example of a health care system using QI strategies to improve performance, and may serve as a model for other health systems seeking to provide better care.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02769338.

The ELIAS framework: A prescription for innovation and change

Healthcare is a complex adaptive system with multiple stakeholders and dynamic environments. Therefore, healthcare organizations must continuously learn, innovate, adapt, and co-evolve to be successful. This article describes a systematic, comprehensive, and holistic performance management framework that healthcare managers can use to achieve these goals. The framework involves the ongoing assessment, modification, or replacement of current programs or services aimed at adapting successfully to achieve the organization's strategic objectives. This is engendered by the presence of a culture that is premised on continuous learning and innovation. The foundation of the framework is based on accountability, the organization's strategy, and its culture. This then acts as the basis for an ongoing process of measurement, disconfirmation, contextualization, implementation, and routinization that enhances learning, innovation, adaptation, and sustainability within the healthcare organization.

The protocol-guided rapid evaluation of veterans experiencing new transient neurological symptoms (PREVENT) quality improvement program: rationale and methods

BACKGROUND

Transient ischemic attack (TIA) patients are at high risk of recurrent vascular events; timely management can reduce that risk by 70%. The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) developed, implemented, and evaluated a TIA quality improvement (QI) intervention aligned with Learning Healthcare System principles.

METHODS

This stepped-wedge trial developed, implemented and evaluated a provider-facing, multi-component intervention to improve TIA care at six facilities. The unit of analysis was the medical center. The intervention was developed based on benchmarking data, staff interviews, literature, and electronic quality measures and included: performance data, clinical protocols, professional education, electronic health record tools, and QI support. The effectiveness outcome was the without-fail rate: the proportion of patients who receive all processes of care for which they are eligible among seven processes. The implementation outcomes were the number of implementation activities completed and final team organization level. The intervention effects on the without-fail rate were analyzed using generalized mixed-effects models with multilevel hierarchical random effects. Mixed methods were used to assess implementation, user satisfaction, and sustainability.

DISCUSSION

PREVENT advanced three aspects of a Learning Healthcare System. Learning from Data: teams examined and interacted with their performance data to explore hypotheses, plan QI activities, and evaluate change over time. Learning from Each Other: Teams participated in monthly virtual collaborative calls. Sharing Best Practices: Teams shared tools and best practices. The approach used to design and implement PREVENT may be generalizable to other clinical conditions where time-sensitive care spans clinical settings and medical disciplines.

TRIAL REGISTRATION

clinicaltrials.gov: NCT02769338 [May 11, 2016].

Quality improvement and emergency laparotomy care: what have we learnt from recent major QI efforts?

More than 1.53 million adults undergo inpatient surgery in the UK NHS. Patients undergoing emergency abdominal surgery have a much greater risk of death than patients admitted for elective surgery. Widespread variations in key standards of care between hospitals exist and are associated with differences in mortality rates.Recently there have been three large-scale initiatives to improve quality of care for emergency laparotomy patients: the National Emergency Laparotomy Audit, the enhanced perioperative care for high-risk patients trial and the Emergency Laparotomy Collaborative. Here we provide a critical review of what we currently know about the use of structured methods for improving the quality of healthcare services, with reference to the three initiatives. We find that using structured methods to improve care is the hallmark of quality improvement but attention must too be paid to the context in which these methods are used.