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Abstract
Problem Statement or Scientific Question: How to efficiently identify the top process improvement opportunities in the Chest Pain - MI Registry™ and concisely share results with stakeholders.
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Problem Statement or Scientific Question: How to efficiently identify the top process improvement opportunities in the Chest Pain - MI Registry™ and concisely share results with stakeholders.
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Little Time for Presentation Prep? Use a Pareto Chart to Focus
Maria Andrew
Affiliations:
null
null
Abstract
Problem Statement or Scientific Question: How to efficiently identify the top process improvement opportunities in the Chest Pain - MI Registry™ and concisely share results with stakeholders.
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Problem Statement or Scientific Question: How to efficiently identify the top process improvement opportunities in the Chest Pain - MI Registry™ and concisely share results with stakeholders.
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
Background/Project Intent: A last minute data request was received to prepare a cardiology service line presentation about the Chest Pain - MI Registry™. A presentation covering this registry had not been made at the hospital since personnel changes. There was a need to engage cardiologists to improve patient outcomes and establish validity of registry metrics. There was also an opportunity to approach the data analysis differently as a new quality improvement specialist supporting cardiology outcomes as well.
Methodology: The data abstractors, quality improvement specialist and department manager convened to strategize presentation focus. The hospital’s R4Q performance for the four composite performance measures 1) Overall AMI performance composite 2) Overall defect free care 3) STEMI performance composite and 4) NSTEMI ending in Q42022 were all at the 50th percentile. To analyze specific components further pareto charts were created for all four performance composites. However, the results for all four composite pareto charts were the same so only one pareto chart was presented. For the data analysis, first the metric for overall defect free care was reviewed. For this metric, the hospital’s average RQ4 performance from the past three quarters Q22022 – Q42022 was 74.6% which was a 26.4% drop in performance from Q12022. Thus, the fourteen metrics within this composite measure were exported individually and filtered to identify the opportunities for improvement. This was done by filtering ‘no’ in the data field ‘included in the numerator’. A table was created with the counts of each metric fall out and a pareto chart was created.
Results: For the R4Q performance ending in Q4 2022, the frequency of the fourteen metrics indicated that cardiac rehabilitation referral from an inpatient setting, high-intensity statin at discharge, and P2Y12 inhibitor at discharge accounted for 60% of the opportunities. The counts for opportunities were as followed Cardiac rehabilitation referral from an inpatient setting N=23; High-Intensity statin at discharge N=8; P2Y12 inhibitor at discharge N=8; Beta Blocker at Discharge N=7; Evaluation of LV systolic function N=6; First medical contact-device time (Stemi only) N= 5; Aspirin at arrival N=3; ACE-1 Or ARB for LVSD at discharge N= 3; Early troponin measurement after NSTEMI N= 1; Immediate angiography after cardiac arrest N= 0; Door-to-Needle Time (Stemi only) N= 0; Door-in door-out time N=0; Reperfusion therapy N=0; and Aspirin at discharge N=0. The first-time approach of presenting the data in the form of a pareto chart at a cardiology service line meeting helped identify that just a few causes were related to the majority of outcomes. Use of the pareto chart as an effective presentation tool to focus on improvement opportunities was quickly adopted by the Cath lab medical director as well.
Value Proposition: Providing a data summary in this format helps focus efforts to create better outcomes for patients in reducing further complications and readmissions.
Conclusions: The pareto chart premise states that approximately 80% of outcomes originate from 20% of causes from many study areas. Using this concept to strategize a hospital’s quality improvement efforts can be an effective means to communicate data. Taking a risk as a new quality improvement specialist/analyst to present data differently can result in hospital leadership engagement and be accomplished quickly.
References: None, online Pareto chart guidance https://statisticsbyjim.com/graphs/pareto-charts/
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