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Target Based Visual Cues in the Electronic Medical Record System at a High-Volume Academic Medical Institution

Rika Ohkuma (Stanford Health Care), Purnima Krishna (Stanford Health Care), Alicia Wilson (Stanford Health Care), Amy Lu (Stanford School of Medicine, Stanford Health Care)

Background

The implementation of evidence-based, consensus-driven clinical pathways, which has shown to standardize care and improve interdisciplinary communication, was selected as a solution in developing a value-based care approach to address long length of stay (LOS) patients and clinical variation among physicians.

Objectives

We aimed to improve the efficacy and value of our patient care for a better inpatient experience by incorporating evidence-based decision support tools into our electronic medical record (EMR) system.

Methods

A High Value Care analysis using hospital-wide clinical, financial and operational outcomes identified 6 high impact areas with stakeholders’ engagement between September 2016 and December 2017. Patient specific evidence-based care pathways, guidelines, and order sets were developed with multidisciplinary clinical teams. The target LOS was calculated using national benchmarks and institutional historical data. The EMR system interface was customized for each patient population. New features such as internal links to new corresponding care pathways, icons, flags and banners as visual cues were incorporated into medical charts to identify patient eligibility, processes to advance the level of care, and patient specific risk-stratified LOS goals. Built-in logic also pre-selected appropriate orders in order sets based on risk categories of each patient. A custom summary page for a service line was created to increase the efficiency in daily clinical evaluation and documentation. The progress of each project outcome was tracked manually at the beginning, and subsequently automated by building project trackers, which included clinical outcomes, key process metrics and balance metrics. The report is available on an in-hospital interactive analytic dashboard and is distributed monthly to multidisciplinary stakeholders.

Results

Since implementation of an optimized EMR with new clinical decision support tools for 6 initiatives, all projects demonstrated positive clinical results.  The LOS reduction in the projects ranged from 0.3-6.5 days compared to pre-implementation phases between March and October 2017, with an average of 2.5 days, corresponding to a projected annual reduction of 1,328 patient bed days. Through these multidisciplinary efforts, the overall average hospital LOS Index (2016 Vizient Risk Model) excluding the psychiatry service line was 0.903 between September and December 2017, which is a significant decrease from the last fiscal year (1.005, p=0.003) (Figure 1). Case mix index and all cause readmission rate did not show statistically significant changes, from 2.52 to 2.52 (Figure 2) and from 9.9% to 10.6% (Figure 3) respectively.

Conclusion

Appropriate interpretation and utilization of clinical data is essential in the era of value-based care. Consensus and engagement among all clinical stakeholders was a key for success. Frequent communication among multidisciplinary teams in these development processes helped to reduce variation among providers, service lines, and nursing units.

Implications for the Patient

An automated interactive analytic dashboard played an essential role for sustaining this value improvement initiative. Optimizing the EMR system, with embedded clinical care pathways, aligned custom order sets, and clinical decision support tools as visual cues, allowed clinical teams to achieve a better patient care and experience.