Abstract
Problem Statement or Scientific Question: The goal of this study is to identify patients who were being appropriately managed with the four guideline-directed medical therapy (GDMT) pillars, which include renin-angiotensin inhibitors (ACEi/ARB/ARNI), beta-blockers, mineralocorticoid receptor antagonists (MRA) and sodium-glucose cotransporter-2 (SGLT-2) inhibitors, and identify potential gaps in initiating and optimizing GDMT in the inpatient setting.
Background/Project Intent: Initiation and titration of all four classes of GDMT in patients with HFrEF leads to cumulative mortality benefit, reduction in heart failure rehospitalization rates and should be prioritized in any care setting (3). Despite this clinical evidence, inpatient GDMT utilization rates remain as low as 10% in some studies. The purpose of this study is to analyze why the patients with HFrEF were not on maximal tolerated GDMT at discharge and implement strategies to improve utilization.
Methodology: We performed a single-center, retrospective study from January to June 2022 (pre-intervention group) to identify potential reasons for why the patients with HFrEF were not on all four classes of GDMT at discharge. Patients were identified by the HF process improvement committee with reports generated by searching ICD10 codes for HF with an ejection fraction (EF) of ≤40%. We performed chart review via the electronic health record (EHR) to collect data points including age, sex, last known EF, disposition (home, hospice or expired), glomerular filtration rate (GFR), average serum potassium level, average blood pressure and any documentation on why the patient may be exempt from a certain medication for each of the four pillars of GDMT. We then introduced quality improvement (QI) interventions such as providing education to residents, hospitalists, cardiology advanced practice providers (APPs) and pharmacists. The GDMT utilization data was also reviewed monthly by a performance improvement consultant at our facility and emails were sent to each provider for patients who were not discharged on all four pillars of GDMT. Subsequently, we obtained post-intervention data from December 2022 to May 2023 and compared it to the pre-intervention group for analysis. Pearson Chi-square and Mann-Whitney U analysis were used to compare demographic and clinical characteristics between the two time periods. A one-way z test of two population proportions was used to compare beta-blockers, ARNI, ACE/ARB, MRA, and SGLT2i increases/decreases between the two time periods.
Results: This study included a pre-intervention group (n=228) and post-intervention group (n=227) with a total of 455 patients. The total study group consisted of 126 females (27.7%) and 329 males (72.3%). A total of 57 (25%) patients in the pre-intervention group were not on ARNI at discharge without any formal documentation in the EHR. We found that the number of patients discharged on ARNI significantly increased post intervention [83 (36.6%) post-intervention compared to 54 (23.7%) pre-intervention, z=2.99, p=0.001]. A total of 66 (28.9%) patients in the pre-intervention group were not on SGLT2i at discharge without any documentation. We found that the number of patients discharged on SGLT2i also significantly increased post intervention [76 (33.5%) post-intervention compared to 45 (19.7%) pre-intervention, z=3.32, p=< 0.001]. A total of 32 (14.0%) patients in the pre-intervention group were not discharged on MRA without any documentation. We did not see a significant increase of MRA at discharge post-intervention [92 (40.5%) post-intervention versus 86 (37.7%) pre-intervention, z=0.61, p=0.27]. Among patients who were not already on an ARNI, a total of 19 (8.3%) patients were not on ACEi/ARB without any formal documentation in the EHR. We did not see a significant increase of ACEi/ARB at discharge post-intervention [28 (19.6%) post-intervention compared to 41(23.6%) pre-intervention, z=0.86, p=0.19]. A total of 27 (11.8%) patients were not on a BB at discharge without documentation for why they were not on it. We did not see a significant increase of BB at discharge [135 (59.5%) post-intervention vs 130 (57.0%) pre-intervention, z=0.53, p=0.30]. Other documented reasons for not being on GDMT at discharge included symptomatic hypotension, GFR < 30, hyperkalemia with potassium >5mEq/L, terminal/hospice patients, left-ventricular assist device (LVAD)/transplant patients, acute kidney injury, patients who left against medical advice and those who were advised to follow up out-patient.
Value Proposition: Recent studies have shown that in-hospital initiation and titration of all four pillars of GDMT is preferable in all patients admitted with acute heart failure due to lack of outpatient optimization (1). The usage of GDMT helps in reducing rehospitalization, decreases mortality and improves functional capacity. With our QI project, we were able to identify the potential gaps in starting patients on the four foundational classes of GDMT.
Conclusions: Involvement of a process improvement committee alongside a multi-disciplinary team resulted in significant improvement in GDMT utilization. We also saw marked improvement in documentation as to why GDMT was not utilized. There still lies a significant gap in initiating, titrating and utilizing GDMT and further strategies are needed to improve implementation.
References: 1. Dixit, Neal M., et al. “Optimizing guideline-directed medical therapies for heart failure with reduced ejection fraction during hospitalization.” US Cardiology Review (2021). 2. Joseph, Jeeva, et al. "Guideline-directed medical therapy in heart failure patients: impact of focused care provided by a heart failure clinic in comparison to general cardiology out-patient department." The Egyptian Heart Journal 72 (2020): 1-8. 3. Schwann, Alexandra, et al. “Inpatient initiation of HFrEF Therapies.” Journal of American College of Cardiology (2022).
Background/Project Intent: Initiation and titration of all four classes of GDMT in patients with HFrEF leads to cumulative mortality benefit, reduction in heart failure rehospitalization rates and should be prioritized in any care setting (3). Despite this clinical evidence, inpatient GDMT utilization rates remain as low as 10% in some studies. The purpose of this study is to analyze why the patients with HFrEF were not on maximal tolerated GDMT at discharge and implement strategies to improve utilization.
Methodology: We performed a single-center, retrospective study from January to June 2022 (pre-intervention group) to identify potential reasons for why the patients with HFrEF were not on all four classes of GDMT at discharge. Patients were identified by the HF process improvement committee with reports generated by searching ICD10 codes for HF with an ejection fraction (EF) of ≤40%. We performed chart review via the electronic health record (EHR) to collect data points including age, sex, last known EF, disposition (home, hospice or expired), glomerular filtration rate (GFR), average serum potassium level, average blood pressure and any documentation on why the patient may be exempt from a certain medication for each of the four pillars of GDMT. We then introduced quality improvement (QI) interventions such as providing education to residents, hospitalists, cardiology advanced practice providers (APPs) and pharmacists. The GDMT utilization data was also reviewed monthly by a performance improvement consultant at our facility and emails were sent to each provider for patients who were not discharged on all four pillars of GDMT. Subsequently, we obtained post-intervention data from December 2022 to May 2023 and compared it to the pre-intervention group for analysis. Pearson Chi-square and Mann-Whitney U analysis were used to compare demographic and clinical characteristics between the two time periods. A one-way z test of two population proportions was used to compare beta-blockers, ARNI, ACE/ARB, MRA, and SGLT2i increases/decreases between the two time periods.
Results: This study included a pre-intervention group (n=228) and post-intervention group (n=227) with a total of 455 patients. The total study group consisted of 126 females (27.7%) and 329 males (72.3%). A total of 57 (25%) patients in the pre-intervention group were not on ARNI at discharge without any formal documentation in the EHR. We found that the number of patients discharged on ARNI significantly increased post intervention [83 (36.6%) post-intervention compared to 54 (23.7%) pre-intervention, z=2.99, p=0.001]. A total of 66 (28.9%) patients in the pre-intervention group were not on SGLT2i at discharge without any documentation. We found that the number of patients discharged on SGLT2i also significantly increased post intervention [76 (33.5%) post-intervention compared to 45 (19.7%) pre-intervention, z=3.32, p=< 0.001]. A total of 32 (14.0%) patients in the pre-intervention group were not discharged on MRA without any documentation. We did not see a significant increase of MRA at discharge post-intervention [92 (40.5%) post-intervention versus 86 (37.7%) pre-intervention, z=0.61, p=0.27]. Among patients who were not already on an ARNI, a total of 19 (8.3%) patients were not on ACEi/ARB without any formal documentation in the EHR. We did not see a significant increase of ACEi/ARB at discharge post-intervention [28 (19.6%) post-intervention compared to 41(23.6%) pre-intervention, z=0.86, p=0.19]. A total of 27 (11.8%) patients were not on a BB at discharge without documentation for why they were not on it. We did not see a significant increase of BB at discharge [135 (59.5%) post-intervention vs 130 (57.0%) pre-intervention, z=0.53, p=0.30]. Other documented reasons for not being on GDMT at discharge included symptomatic hypotension, GFR < 30, hyperkalemia with potassium >5mEq/L, terminal/hospice patients, left-ventricular assist device (LVAD)/transplant patients, acute kidney injury, patients who left against medical advice and those who were advised to follow up out-patient.
Value Proposition: Recent studies have shown that in-hospital initiation and titration of all four pillars of GDMT is preferable in all patients admitted with acute heart failure due to lack of outpatient optimization (1). The usage of GDMT helps in reducing rehospitalization, decreases mortality and improves functional capacity. With our QI project, we were able to identify the potential gaps in starting patients on the four foundational classes of GDMT.
Conclusions: Involvement of a process improvement committee alongside a multi-disciplinary team resulted in significant improvement in GDMT utilization. We also saw marked improvement in documentation as to why GDMT was not utilized. There still lies a significant gap in initiating, titrating and utilizing GDMT and further strategies are needed to improve implementation.
References: 1. Dixit, Neal M., et al. “Optimizing guideline-directed medical therapies for heart failure with reduced ejection fraction during hospitalization.” US Cardiology Review (2021). 2. Joseph, Jeeva, et al. "Guideline-directed medical therapy in heart failure patients: impact of focused care provided by a heart failure clinic in comparison to general cardiology out-patient department." The Egyptian Heart Journal 72 (2020): 1-8. 3. Schwann, Alexandra, et al. “Inpatient initiation of HFrEF Therapies.” Journal of American College of Cardiology (2022).
Problem Statement or Scientific Question: The goal of this study is to identify patients who were being appropriately managed with the four guideline-directed medical therapy (GDMT) pillars, which include renin-angiotensin inhibitors (ACEi/ARB/ARNI), beta-blockers, mineralocorticoid receptor antagonists (MRA) and sodium-glucose cotransporter-2 (SGLT-2) inhibitors, and identify potential gaps in initiating and optimizing GDMT in the inpatient setting.
Background/Project Intent: Initiation and titration of all four classes of GDMT in patients with HFrEF leads to cumulative mortality benefit, reduction in heart failure rehospitalization rates and should be prioritized in any care setting (3). Despite this clinical evidence, inpatient GDMT utilization rates remain as low as 10% in some studies. The purpose of this study is to analyze why the patients with HFrEF were not on maximal tolerated GDMT at discharge and implement strategies to improve utilization.
Methodology: We performed a single-center, retrospective study from January to June 2022 (pre-intervention group) to identify potential reasons for why the patients with HFrEF were not on all four classes of GDMT at discharge. Patients were identified by the HF process improvement committee with reports generated by searching ICD10 codes for HF with an ejection fraction (EF) of ≤40%. We performed chart review via the electronic health record (EHR) to collect data points including age, sex, last known EF, disposition (home, hospice or expired), glomerular filtration rate (GFR), average serum potassium level, average blood pressure and any documentation on why the patient may be exempt from a certain medication for each of the four pillars of GDMT. We then introduced quality improvement (QI) interventions such as providing education to residents, hospitalists, cardiology advanced practice providers (APPs) and pharmacists. The GDMT utilization data was also reviewed monthly by a performance improvement consultant at our facility and emails were sent to each provider for patients who were not discharged on all four pillars of GDMT. Subsequently, we obtained post-intervention data from December 2022 to May 2023 and compared it to the pre-intervention group for analysis. Pearson Chi-square and Mann-Whitney U analysis were used to compare demographic and clinical characteristics between the two time periods. A one-way z test of two population proportions was used to compare beta-blockers, ARNI, ACE/ARB, MRA, and SGLT2i increases/decreases between the two time periods.
Results: This study included a pre-intervention group (n=228) and post-intervention group (n=227) with a total of 455 patients. The total study group consisted of 126 females (27.7%) and 329 males (72.3%). A total of 57 (25%) patients in the pre-intervention group were not on ARNI at discharge without any formal documentation in the EHR. We found that the number of patients discharged on ARNI significantly increased post intervention [83 (36.6%) post-intervention compared to 54 (23.7%) pre-intervention, z=2.99, p=0.001]. A total of 66 (28.9%) patients in the pre-intervention group were not on SGLT2i at discharge without any documentation. We found that the number of patients discharged on SGLT2i also significantly increased post intervention [76 (33.5%) post-intervention compared to 45 (19.7%) pre-intervention, z=3.32, p=< 0.001]. A total of 32 (14.0%) patients in the pre-intervention group were not discharged on MRA without any documentation. We did not see a significant increase of MRA at discharge post-intervention [92 (40.5%) post-intervention versus 86 (37.7%) pre-intervention, z=0.61, p=0.27]. Among patients who were not already on an ARNI, a total of 19 (8.3%) patients were not on ACEi/ARB without any formal documentation in the EHR. We did not see a significant increase of ACEi/ARB at discharge post-intervention [28 (19.6%) post-intervention compared to 41(23.6%) pre-intervention, z=0.86, p=0.19]. A total of 27 (11.8%) patients were not on a BB at discharge without documentation for why they were not on it. We did not see a significant increase of BB at discharge [135 (59.5%) post-intervention vs 130 (57.0%) pre-intervention, z=0.53, p=0.30]. Other documented reasons for not being on GDMT at discharge included symptomatic hypotension, GFR < 30, hyperkalemia with potassium >5mEq/L, terminal/hospice patients, left-ventricular assist device (LVAD)/transplant patients, acute kidney injury, patients who left against medical advice and those who were advised to follow up out-patient.
Value Proposition: Recent studies have shown that in-hospital initiation and titration of all four pillars of GDMT is preferable in all patients admitted with acute heart failure due to lack of outpatient optimization (1). The usage of GDMT helps in reducing rehospitalization, decreases mortality and improves functional capacity. With our QI project, we were able to identify the potential gaps in starting patients on the four foundational classes of GDMT.
Conclusions: Involvement of a process improvement committee alongside a multi-disciplinary team resulted in significant improvement in GDMT utilization. We also saw marked improvement in documentation as to why GDMT was not utilized. There still lies a significant gap in initiating, titrating and utilizing GDMT and further strategies are needed to improve implementation.
References: 1. Dixit, Neal M., et al. “Optimizing guideline-directed medical therapies for heart failure with reduced ejection fraction during hospitalization.” US Cardiology Review (2021). 2. Joseph, Jeeva, et al. "Guideline-directed medical therapy in heart failure patients: impact of focused care provided by a heart failure clinic in comparison to general cardiology out-patient department." The Egyptian Heart Journal 72 (2020): 1-8. 3. Schwann, Alexandra, et al. “Inpatient initiation of HFrEF Therapies.” Journal of American College of Cardiology (2022).
Background/Project Intent: Initiation and titration of all four classes of GDMT in patients with HFrEF leads to cumulative mortality benefit, reduction in heart failure rehospitalization rates and should be prioritized in any care setting (3). Despite this clinical evidence, inpatient GDMT utilization rates remain as low as 10% in some studies. The purpose of this study is to analyze why the patients with HFrEF were not on maximal tolerated GDMT at discharge and implement strategies to improve utilization.
Methodology: We performed a single-center, retrospective study from January to June 2022 (pre-intervention group) to identify potential reasons for why the patients with HFrEF were not on all four classes of GDMT at discharge. Patients were identified by the HF process improvement committee with reports generated by searching ICD10 codes for HF with an ejection fraction (EF) of ≤40%. We performed chart review via the electronic health record (EHR) to collect data points including age, sex, last known EF, disposition (home, hospice or expired), glomerular filtration rate (GFR), average serum potassium level, average blood pressure and any documentation on why the patient may be exempt from a certain medication for each of the four pillars of GDMT. We then introduced quality improvement (QI) interventions such as providing education to residents, hospitalists, cardiology advanced practice providers (APPs) and pharmacists. The GDMT utilization data was also reviewed monthly by a performance improvement consultant at our facility and emails were sent to each provider for patients who were not discharged on all four pillars of GDMT. Subsequently, we obtained post-intervention data from December 2022 to May 2023 and compared it to the pre-intervention group for analysis. Pearson Chi-square and Mann-Whitney U analysis were used to compare demographic and clinical characteristics between the two time periods. A one-way z test of two population proportions was used to compare beta-blockers, ARNI, ACE/ARB, MRA, and SGLT2i increases/decreases between the two time periods.
Results: This study included a pre-intervention group (n=228) and post-intervention group (n=227) with a total of 455 patients. The total study group consisted of 126 females (27.7%) and 329 males (72.3%). A total of 57 (25%) patients in the pre-intervention group were not on ARNI at discharge without any formal documentation in the EHR. We found that the number of patients discharged on ARNI significantly increased post intervention [83 (36.6%) post-intervention compared to 54 (23.7%) pre-intervention, z=2.99, p=0.001]. A total of 66 (28.9%) patients in the pre-intervention group were not on SGLT2i at discharge without any documentation. We found that the number of patients discharged on SGLT2i also significantly increased post intervention [76 (33.5%) post-intervention compared to 45 (19.7%) pre-intervention, z=3.32, p=< 0.001]. A total of 32 (14.0%) patients in the pre-intervention group were not discharged on MRA without any documentation. We did not see a significant increase of MRA at discharge post-intervention [92 (40.5%) post-intervention versus 86 (37.7%) pre-intervention, z=0.61, p=0.27]. Among patients who were not already on an ARNI, a total of 19 (8.3%) patients were not on ACEi/ARB without any formal documentation in the EHR. We did not see a significant increase of ACEi/ARB at discharge post-intervention [28 (19.6%) post-intervention compared to 41(23.6%) pre-intervention, z=0.86, p=0.19]. A total of 27 (11.8%) patients were not on a BB at discharge without documentation for why they were not on it. We did not see a significant increase of BB at discharge [135 (59.5%) post-intervention vs 130 (57.0%) pre-intervention, z=0.53, p=0.30]. Other documented reasons for not being on GDMT at discharge included symptomatic hypotension, GFR < 30, hyperkalemia with potassium >5mEq/L, terminal/hospice patients, left-ventricular assist device (LVAD)/transplant patients, acute kidney injury, patients who left against medical advice and those who were advised to follow up out-patient.
Value Proposition: Recent studies have shown that in-hospital initiation and titration of all four pillars of GDMT is preferable in all patients admitted with acute heart failure due to lack of outpatient optimization (1). The usage of GDMT helps in reducing rehospitalization, decreases mortality and improves functional capacity. With our QI project, we were able to identify the potential gaps in starting patients on the four foundational classes of GDMT.
Conclusions: Involvement of a process improvement committee alongside a multi-disciplinary team resulted in significant improvement in GDMT utilization. We also saw marked improvement in documentation as to why GDMT was not utilized. There still lies a significant gap in initiating, titrating and utilizing GDMT and further strategies are needed to improve implementation.
References: 1. Dixit, Neal M., et al. “Optimizing guideline-directed medical therapies for heart failure with reduced ejection fraction during hospitalization.” US Cardiology Review (2021). 2. Joseph, Jeeva, et al. "Guideline-directed medical therapy in heart failure patients: impact of focused care provided by a heart failure clinic in comparison to general cardiology out-patient department." The Egyptian Heart Journal 72 (2020): 1-8. 3. Schwann, Alexandra, et al. “Inpatient initiation of HFrEF Therapies.” Journal of American College of Cardiology (2022).
{{ help_message }}
{{filter}}