Society: AGA

Attendees should attend this session to learn about practical examples of successful quality improvement projects for integration into their day to day work lives. This session will also provide guidance on how to develop a quality improvement project.

BACKGROUND: Exocrine pancreatic insufficiency (EPI) is common in chronic pancreatitis (CP), pancreatic cancer (PDAC), and post pancreatic resection. Only about 1/3 of these patients are prescribed pancreatic enzyme replacement therapy (PERT), often at an inadequate dose. There is increasing evidence that this leads to increased morbidity and mortality. The aim of this study was to identify practice patterns of EPI treatment , develop and implement an EPIC-based best practice alert (BPA) and smart order set with goal of improving management of EPI.

METHODS: All patients with ICD-10 codes of EPI, CP, and PDAC or CPT code for pancreatic resection, who were seen in either an outpatient or inpatient setting at a tertiary care center from Feb-2018 to June-2022 were included. Appropriate use of PERT was defined as > 40,000 USP units of lipase with each meal. The initial retrospective analysis was conducted prior to implementation of the BPA and smart set from feb-2018 to feb-2020. The BPA and smart set were implemented on Feb-2020 and another analysis was done on patients from feb-2020 to June 2022.

RESULTS: The baseline analysis identified 1,464 patients carrying an ICD-10 code for CP, EPI, PDAC or a CPT code for pancreatic resection whose diagnosis was confirmed by manual chart review . Overall, 837 (57.2%) patients were prescribed PERT. Of those prescribed enzymes, 518 (61.9%) were on a less than minimum therapeutic dose. Overall, 299 (20.4%) patients had a pancreatic elastase checked, 453 (30.9%) had a vitamin D level measured, 156 (10%) had a DEXA ordered, and 801 (54.7%) had a hemoglobin A1c level checked. An order set was designed, with an associated BPA tied to any of these diagnoses or to any order for PERT (Figure 1).The BPA and order set were incorporated into our EPIC system and are now in active use.

A statistically significant increase in the proportion of patients on minimum therapeutic dose of PERT from 61.9 to 72.9% (P=<0.001) was observed. Ordering of pancreatic elastase, A1c, vitamin D, and DEXA increased from 20.4 to 29.9% (P<0.001), 54.7 to 62.1% (P=0.001), 30.9 to 48.1% (P<0.001) and 10 to 18% (P<0.001), respectively after initiation of BPA and smart set. An increase in vitamin D supplementation from 25.5 to 33.4% (P<0.001) and a decrease in the proportion of patients with unknown metabolic bone disease status from 86.8 to 76.8% (P<0.001) was observed.

CONCLUSIONS: The implementation of a BPA and smart set for the management of exocrine pancreatic insufficiency was associated with an improvement in management and monitoring noted by an increase in proportion of patients on minimum therapeutic dose of enzyme as well as by an increase in ordering of pancreatic elastase, A1c, vit D, DEXA scan to monitor disease related complicatons

Background:
Many patients with symptoms of gastroesophageal reflux disease (GERD) despite proton pump inhibitor (PPI) use undergo ambulatory reflux testing, which is ideally performed off therapy in the absence of a prior GERD diagnosis according to Porto Consensus recommendations. However, we previously identified substantial variation in reflux testing patterns among such patients at our institution, with a majority undergoing multichannel intraluminal impedance pH (MII-pH) testing on PPI therapy without previous objective evidence of GERD. We aimed to assess the impact of a novel clinical decision support tool (CDST) on adherence to best practices for GERD testing.

Methods:
We used Define, Measure, Analyze, Improve, and Control (DMAIC) methodology to identify factors associated with MII-pH ordering discordant from best practices, with clinician knowledge gaps and lack of standardization in ordering options as contributors (Figure 1). These results motivated the development of a CDST within the electronic health record (EHR), which was updated to default MII-pH testing off therapy whereas testing on PPI requests designating the prior GERD history. Clinicians may still select testing on PPI by manually entering a justification. We assessed the impact of this intervention on consecutive patients referred for ambulatory MII-pH testing from the inception of the CDST on 1/1/2022 through 10/31/2022. Patients with prior foregut surgery, undergoing testing for lung transplantation, or referred from outside centers without EHR access were excluded. Appropriate statistical tests were used to compare the proportion of patients undergoing ambulatory reflux testing on therapy and concordant with best practices before and after implementation of the CDST.

Results:
There were 567 MII-pH studies evaluated, including 433 studies pre-intervention and 134 post-intervention. Our center performed significantly fewer studies on PPI after the CDST than before (n=25/134, 18.7% vs n=134/433, 30.9%; p<0.01). Of those studies performed on PPI, concordance with best practices increased from 16.4% (n=22/134) to 28.0% (n=7/25) following the intervention. Additionally, the CDST resulted in significantly more clinical management changes after implementation among those tested on therapy (n=31/134, 23.1% vs n=14/25, 56.0%; p<0.01) (Figure 2).

Conclusions:
To address the observed variation in care and MII-pH test ordering that frequently contrasted with best practices, we used DMAIC methodology to develop a CDST. After our intervention, the number of MII-pH studies ordered on PPI was significantly reduced while ordering concordant with the Porto Consensus recommendations and changes in clinical management increased. Our results show a CDST can guide appropriate ambulatory reflux testing protocols and meaningfully impact the clinical management of patients with GERD symptoms.

<b>Figure 1. Ambulatory Reflux Testing Root-Cause Analysis</b>. PPI, proton pump inhibitor. EHR, electronic health record.

Figure 1. Ambulatory Reflux Testing Root-Cause Analysis. PPI, proton pump inhibitor. EHR, electronic health record.

<b>Figure 2. Impact of Clinical Decision Support Tool</b>. PPI, proton pump inhibitor. %, percentage. NS, not significant. ** indicates p<0.01.

Figure 2. Impact of Clinical Decision Support Tool. PPI, proton pump inhibitor. %, percentage. NS, not significant. ** indicates p<0.01.

Background & Aim: Smoking is a major risk factor for multiple gastrointestinal cancers, and adversely affects peptic ulcer disease, gastroesophageal reflux, pancreatitis and Crohn’s disease. Despite key recommendations for diagnosing and treating tobacco use disorder in healthcare settings, the degree to which this is implemented in Gastroenterology (GI) clinics is unknown. We aimed to assess our providers’ practices, identify barriers for implementing evidence-based smoking cessation treatments, and address these barriers by implementing a novel Electronic Health Record (EHR)-assisted tobacco treatment model (ELEVATE) in our GI clinics.

Methods: This is a quality improvement initiative aimed at smoking cessation performed at a major tertiary medical center’s GI clinics. It was given an exempt determination by our hospital's institutional review board (IRB). An online survey was distributed to clinic gastroenterologists regarding their smoking cessation care practices. The US Public Health Service Clinical Practice Guideline Panel recommends the 5A’s (Ask, Advise, Assess, Assist, Arrange) as an evidence-based intervention for smoking cessation. ELEVATE is implemented by the medical assistant, and leverages EPIC EHR functionality to ensure consistent tobacco use assessment and cessation treatment support is provided for all our clinic patients utilizing the 5A’s, as illustrated in Figure 1. ELEVATE module training was implemented in 1/2021. Data were evaluated during pre (7/2020-12/2020) and post (1/2021-6/2021) implementation periods to evaluate the reach and effectiveness of ELEVATE.

Results: 91% (20/22) of GI physicians responded to our survey, and only 20% often assisted patients who smoke with counseling. Lack of a systematic program to offer help to patients was reported by 80% of providers as an extremely/very important barrier limiting their smoking cessation practices. The proportion of current smokers receiving cessation treatment increased from pre-ELEVATE to post-ELEVATE (14.36% to 27.47%, RR=1.90, 95% CI 1.60-2.26, p<0.001). Post-ELEVATE, 14.4% (38/264) of patients with treatment quit smoking, compared to 7.9% (55/697) of patients without treatment (RR=1.89, 95% CI 1.26 – 2.82, p=.0021), as depicted in Figure 2.

Conclusion: Significant barriers including lack of time and support limit GI providers’ smoking cessation practices. The use of a low burden point of care EHR enabled smoking cessation treatment module has led to a significant improvement in the treatment of smoking and subsequent cessation in our clinics. This study sheds light on an often under-recognized source of morbidity in GI patients and identifies an efficient, effective, and scalable strategy to combat tobacco use and improve clinical outcomes in our patients.

Figure 1. EHR-Enabled Evidence-Based Cessation Treatment (ELEVATE) Patient Care Workflow using 5A’s

Figure 1. EHR-Enabled Evidence-Based Cessation Treatment (ELEVATE) Patient Care Workflow using 5A’s

Figure 2. Post-ELEVATE module training tobacco treatment effectiveness

Figure 2. Post-ELEVATE module training tobacco treatment effectiveness

Chien-Huan Chen

Washington University School of Medicine in St. Louis

Appearances