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Language of Improvement: Metrics, Key Performance Indicators, Benchmarks, Analytics, Scorecards, and Dashboards
EDITORIAL
Language of Improvement: Metrics, Key Performance Indicators, Benchmarks, Analytics, Scorecards, and Dashboards JOY DON BAKER, PhD, RN-BC, CNOR, CNE, NEA-BC, EDITOR-IN-CHIEF
P
erioperative nurses must know what data to collect, how to interpret it, and how to select the best methods of analysis to make quality, actionoriented decisions, such as determining which product creates the best outcomes for a particular patient population (eg, elderly patients undergoing hip procedures) or how to improve staffing mix based on the surgical case load per day. The complexity of data that nurses manage continues to increase. Nurses generate simple forms to track procedure or supply information or show the progress of a quality improvement project. Rules develop out of continued use of the form to ensure consistency of the documentation. For example, all nurses use the same indicator to record the start of a patient procedure, such as “patient enters the OR.” The consistency in recording the start times allows for accurate comparison to the scheduled start times for the patient procedures. There must be a system in place for storage and retrieval of the data for analysis purposes. Nurses know and understand the critical components of their practice. Therefore, it is important for nurses to clarify and determine the most important elements of complex data so they can generate reliable and valid reports that provide insights on which to base best-practice decisions.1
Turning massive amounts of data into useable information for improvement is key to improving patient care. Large databases can be helpful when evaluating patient care best practices and provide a business advantage when adequate storage and management of data systems are in place for maximizing the
speed of translation of data, which increases the ability to “determine root causes of failures, issues, and defects, potentially saving billions of dollars annually”2(p20) and potentially improving patient care. Variable best-practice sources (ie, literature, hospital policies) should be incorporated to improve the integrity of the end report on which decisions are based, therefore making it “easier to separate the signal from the noise,”2(p20) or as the old adage suggests, the “trees from the forest.” Meaningful results produced from purposeful and accurate data are the foundation from which significant analysis for relevant change occurs.2 Comparison information on a variety of improvement topics for exploration can be found in large data sources, such as the 11 Hospital Consumer Assessment of Healthcare Providers and Systems key topics or the Surgical Care Improvement Project core measures.3,4
METRICS, KEY PERFORMANCE INDICATORS, BENCHMARKS, AND ANALYTICS Specific elements for collecting, monitoring, and analyzing results for quality decision making in the perioperative setting are defined in this section. This section clarifies the terms metrics, key performance indicators (KPIs), benchmarks, and analytics and weaves together organizational and perioperative nursing examples.
http://dx.doi.org/10.1016/j.aorn.2015.07.015 ª AORN, Inc, 2015
www.aornjournal.org
AORN Journal j 223
Baker
September 2015, Vol. 102, No. 3
Metrics
Benchmarks
A metric is a specific measurement standard,5 such as the start time (ie, when the patient entered the room) for the first procedure of the day. Savvy organizations select the best metrics to track that are appropriate to what the organizational staff members wish to measure (eg, patient satisfaction, instrument and equipment defects, percentage of on-time starts).2 A set of metrics that nurses use often are vital signs (eg, blood pressure, pulse, respirations, temperature). However, simply having the metric for each vital sign does not provide complete information on which to base a decision; therefore, it is important to have additional information to support decision making, such as KPIs.
Benchmarks use the selected KPIs and expand on them to provide the means to evaluate similar items and determine if they are comparable. For example, a nurse takes the patient’s vital signs and acquires these metrics: a blood pressure of 164/100 mm Hg, a pulse of 100 beats per minute, a respiration rate of 25 breaths per minute, and a temperature of 100 F (37.8 C). At a glance, the nurse recognizes there is a problem because of the set of benchmarks he or she has learned regarding normal human physiology: blood pressure should be 120/80 mm Hg, the pulse should be 50 to 80 beats per minute, the respiration rate should be 16 to 20 breaths per minute, and the temperature should be 98.6 F (37 C). Organizational benchmarking is similar in that it is a means of “comparing a metric with a gold standard or best practice, or other internal or external reference point”5(p42) for evaluation purposes. Lang5 suggests a seven-step method to benchmark for improvement.
Key Performance Indicators “A KPI is a metric that embeds performance targets so organizations can chart progress toward goals.”6(p10) An example of an organizational target is the amount of revenue by year end, which can be tracked using minimum and maximum acceptable ranges and charted monthly to reflect progression toward that end goal.6 A clinical KPI might be total cholesterol level for a patient. The patient Mr Jones is informed that his total cholesterol level is 220; however, knowing only the number does not help the patient or health care provider understand the relevance of the number. It is important to know that “less than 200 mg/dL is desirable, 200 to 239 mg/dL is borderline high, and 240 mg/dL and above is considered high.”7 Therefore, the target maximum for Mr Jones’ cholesterol level would be any value less than 200 mg/dL. Tracking the value over time assists with understanding the progress made when taking various actions to manage a specific KPI. Selecting the KPIs for an organization is based on the goals of the organization; the goals should relate to the stability of processes, the structure supporting the systems (eg, standards driving the practice), and outcomes (eg, patient satisfaction, employee effectiveness).2 Best indicators assist in problem solving and lead to preventive actions (eg, prevention of patient falls) rather than corrective actions after an incident or episode has occurred.2 Data retrieved from multiple sources as a part of the KPI set assist health care providers in finding preventive answers and solutions to: (1) “enable cost savings and time reductions,” (2) “speed new product development,” and (3) “make smarter business decisions.”2(p24) It is important to focus on organizational priorities that create long-term value for patients, families, payers, and employees, as well as the organization. 224 j AORN Journal
1. 2. 3. 4. 5.
6. 7.
Identify goals. Identify the audience. Identify the data sources. Evaluate data quality: trustworthiness and validity. Develop a plan for reporting: in person or in writing, background or contextual information required to explain any limitations. Consider possible outcomes: decisions, action steps, additional investigation required to learn more about anomalous results. Improve. Correct data to use, report, or benchmark usefulness, additional audiences that need included in reporting.5(p42-44)
Analytics: Stages and Drivers Davenport and Harris define analytics as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact based management to drive decisions and actions.”8(p7) Analytics encompasses the transformation of data into actions following comprehensive examination that relates to the organization’s needs or problems to be solved and supports decision making.8 The four stages of analytics include
data, analysis, insights, and action.9(p314)
Drivers of analytics relate specifically to resources available to acquire and maintain the data, as well as the people necessary to sustain the analytics processes. These drivers center on data, software, process, and people available for the development of sustainable and useful analytics.9
www.aornjournal.org
September 2015, Vol. 102, No. 3
Analytics begins with the collection, extraction, and manipulation of data.9 For example, the data needed to determine procedure start times may come from radio-frequency identification used in a patient’s armband that is scanned when the patient enters an OR. It is critical to know that the data are relevant, reliable, and representative of what is to be measured and provide clear linkage with the strategy.2,10 Schultz suggests using the following questions to aid in determining reliability.
Why is data being collected? What data will be collected? What data collection tools and methods will be used? How will the data be collected? How will we know the right data have been collected? Where should data collection take place? When will the data be collected and for how long? Who will be responsible for collecting the data? Who will compile and analyze data collection results?2(p25)
The next stage in analytics is analysis, which includes the methods of visualization or graphical representation of key performance metrics, predictive modeling techniques, and optimization strategies to summarize the data for delving into problems or root causes.6,9 The analysis stage incorporates software that generates spreadsheets and statistical packages to aid in interpretation and reporting, and processes must be established and implemented to guide the development of tools for decision making and KPI management. It is imperative to identify individuals within the perioperative setting who have the needed skills or means to gain the required knowledge to create and use the analytics.9 Determining and describing insights is the next stage; this includes exploration into reflection on past occurrences, future expectations, and the goal or target based on the analysis of the operational data that identifies the actions necessary to resolve a problem.6,9 The final stage is taking action and making “operational decisions,” determining “process changes,” and finalizing “strategic formulations.”9(p314) Analytics is more data driven and less expensive to obtain than in the past. Increased data access can also increase motivation to perform additional analytics. It is also important to maintain the insights and decision rules in the systems to provide consistency regardless of whether the initial individuals who set the rules change roles or jobs. In addition, this consistency is important to allow all members of the health care team access to work from the same definitions to understand the data in relation to patients and their needs.9
www.aornjournal.org
Editorial
SCORECARDS AND DASHBOARDS The terms scorecard and dashboard are frequently interchanged11 and represent “different types of visual display mechanisms within a performance management system that convey critical performance information at a glance.”6(p9) Using scorecards and dashboards for purposes such as “strategic, tactical, and day-to-day operations, coupled with internal and external best-practice benchmarks, provide the framework for targeting improvement opportunities and evoking improvement changes to the perioperative process.”3(p2) A dashboard is a tool for monitoring operational performance processes, and scorecards focus on the progression of tactical and strategic goals. “Dashboards also tend to display charts and tables with conditional formatting, whereas scorecards use graphical symbols and icons to represent the status and trends of key metrics.”6(p9)
Scorecards A scorecard is a game metaphor with the intent of putting points on a board.10 Using scorecards bridges gaps between short-term objectives, such as financial measures, and longterm strategies and planning.1,2 Scorecard implementation “involves translating the strategic vision into targeted metrics, adapting strategic objectives into specific short-term activities, and creating a mechanism for review to better align strategy with activities that support it.”1(p20) Metrics for scorecard tactical and strategic visual displays appear in time measurements such as real time, hourly, daily, weekly, or monthly and indicate trends.11 The most time-relevant and customer-centered elements are tracked and displayed often, making them competitively vital for both customers and other stakeholders.11 Schonberger suggests managers should, “React often to short lag-time metrics, less often to those with intermediate lag, and seldom for metrics with long lag time.”11(p12-13) Figure 1 shows a scorecard with a
Figure 1. Scorecard illustrating the number of surgical patients in 2015. AORN Journal j 225
Baker
Figure 2. Dashboards illustrate variation using stoplights, colors, and icons. single metric graph of the number of surgical patients by month for the current year, which might be used to explore seasonal variation that could affect staffing, such as an increased spike in procedures in December that may be directly related to patient falls caused by ice during that winter and correspond to an increase in hip replacement procedures.
Dashboards Glancing at the car dashboard while driving is the metaphor for using dashboards in business and in perioperative nursing. An organizational dashboard “measures [its] velocity relative to the external environment.”10(p24) A strategic dashboard focuses attention on analysis and reflection for quality decision making to improve performance.10 Alerts are established for marking change in status using such things as stoplights, change in color, or icons6 (Figure 2). “Dashboards consolidate key performance indicators into a single visual display that offers an at-a-glance window into overall business performance. The most effective dashboards
Figure 3. Dashboard illustrating the number of surgical patients in 2015 with target line based on benchmark data from other facilities for comparison. 226 j AORN Journal
September 2015, Vol. 102, No. 3
are good at emphasizing critical data, while still providing enough context to draw a meaningful assessment.”1(p20) Figure 3 illustrates a dashboard showing the same surgical patient data from the scorecard previously mentioned with the targeted benchmarked thresholds for facilities with a similar number of ORs. This dashboard also depicts a slight upward trend in patients even with the given erratic data points, which may be caused by factors such as seasonal elements or an OR closed for repairs for one month. However, an individual must interpret and analyze the graphics from a dashboard to generate new ideas and perspectives for changes and patient improvement.
Scorecard and Dashboard Use in Perioperative Settings One metric captured in perioperative settings across the country is the number of surgical patients per day, week, month, and year. Tracking these data over a year in monthly increments provides a scorecard of trending data. Additional elements such as number/month for the previous year and projections for year to date based on the year-todate data would be assistive in the scorecard for purposes of analysis. When two metrics such as the number of “surgical patients” is used with the number of “on-time OR procedure starts” for a given time frame (eg, one month), a comparison point (percentage) establishes a location on the operational dashboard (eg, 90% of the patients entered the OR on time). Determining benchmarks such as comparison to other hospitals in the same system or external to the system from other large databases can establish ranges for thresholds and the results can demonstrate the need for continuous performance improvement. For example, the upper threshold might be set at 95%, and the lower threshold at 90%. Anything above 95% would show on the dashboard as green, anything in the range of 91% to 94% would show as yellow, and any number 90% or below would show as red. If the information demonstrates a negative trend (eg, several months of data points in the red), immediate action may be required. Monitoring without taking any action may be necessary to determine whether the single month that scored 94% is an outlier, with the subsequent months all in the green range. Other examples of benchmarks involving patients could be the revenue for each patient or the number of minutes per surgical procedure. Overlaying targets from selected benchmarks of organizations similar in size and case mix and then connecting these to the overall strategy of the system is the subsequent
www.aornjournal.org
September 2015, Vol. 102, No. 3
Editorial
move toward validating and using the information presented for evidence-based decision making.
CONCLUSION Perioperative nurses and leaders use trending data to support decision making, specifically processes tied to “patient flow, patient safety, patient quality of care, and stakeholders’ satisfaction (i.e. patient, physician/surgeon, nurse, perioperative staff, and hospital administration).”3(p1) Understanding and monitoring the various metrics using scorecards and dashboards to paint effective and useful pictures may lead to improved outcomes in perioperative settings.
References 1. Mayfield M, Martinez M, Pansard C, Serr R, Shields J, Wong S. Battling the demons of complexity: design thinking in a business context. Des Manage Rev. 2012;23(2):18-26. 2. Schultz JR. Big data are, after all, just data. Perf Improv. 2014; 53(5):20-25. 3. Ryan J, Doster B, Daily S, Lewis C. A balanced perspective to perioperative process management aligned to hospital strategy. Int J Healthc Inf Syst Inform. 2014;9(4):1-19. 4. HCAHPS Fact Sheet (CAHPS Hospital Survey). Hospital Consumer Assessment of Healthcare Providers and Systems. http://www .hcahpsonline.org/Files/HCAHPS_Fact_Sheet_June_2015.pdf. Accessed June 3, 2015. 5. Lang L. Benchmarking to inform planning: the EDUCAUSE core data service. EDUCAUSE Rev. 2015;50(3):40-48.
www.aornjournal.org
6. Eckerson WW. Deploying dashboards and scorecards. TDWI Best Practice Report. The Data Warehousing Institute. https://www.micro strategy.com/Strategy/media/downloads/solutions/TDWI-Best -Practices-Report-Deploying-Dashboards-and-Scorecards.pdf. Accessed June 3, 2015. 7. Cholesterol levels: what you need to know. NIH Medline Plus. http://www.nlm.nih.gov/medlineplus/magazine/issues/summer12/ articles/summer12pg6-7.html. Accessed June 5, 2015. 8. Davenport TH, Harris JG. Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business School Publishing Corporation; 2007. 9. Liberatore MJ, Luo W. The analytics movement: implications for operations research. Interfaces. 2010;40:313-324. 10. Allio MK. Strategic dashboards: designing and deploying them to improve implementation. Strategy & Leadership. 2012;40(5): 24-31. 11. Schonberger RJ. Time-relevant metrics in an era of continuous process improvement: the balanced scorecard revisited. Quality Management Journal. 2013;20(3):10-18.
Joy Don Baker, PhD, RN-BC, CNOR, CNE, NEA-BC, is the editor-in-chief of the AORN Journal and a clinical professor at the University of Texas at Arlington, College of Nursing and Health Innovation. Dr Baker has no declared affiliation that could be perceived as posing a potential conflict of interest in the publication of this article.
AORN Journal j 227
Language of Improvement: Metrics, Key Performance Indicators, Benchmarks, Analytics, Scorecards, and Dashboards JOY DON BAKER, PhD, RN-BC, CNOR, CNE, NEA-BC, EDITOR-IN-CHIEF
P
erioperative nurses must know what data to collect, how to interpret it, and how to select the best methods of analysis to make quality, actionoriented decisions, such as determining which product creates the best outcomes for a particular patient population (eg, elderly patients undergoing hip procedures) or how to improve staffing mix based on the surgical case load per day. The complexity of data that nurses manage continues to increase. Nurses generate simple forms to track procedure or supply information or show the progress of a quality improvement project. Rules develop out of continued use of the form to ensure consistency of the documentation. For example, all nurses use the same indicator to record the start of a patient procedure, such as “patient enters the OR.” The consistency in recording the start times allows for accurate comparison to the scheduled start times for the patient procedures. There must be a system in place for storage and retrieval of the data for analysis purposes. Nurses know and understand the critical components of their practice. Therefore, it is important for nurses to clarify and determine the most important elements of complex data so they can generate reliable and valid reports that provide insights on which to base best-practice decisions.1
Turning massive amounts of data into useable information for improvement is key to improving patient care. Large databases can be helpful when evaluating patient care best practices and provide a business advantage when adequate storage and management of data systems are in place for maximizing the
speed of translation of data, which increases the ability to “determine root causes of failures, issues, and defects, potentially saving billions of dollars annually”2(p20) and potentially improving patient care. Variable best-practice sources (ie, literature, hospital policies) should be incorporated to improve the integrity of the end report on which decisions are based, therefore making it “easier to separate the signal from the noise,”2(p20) or as the old adage suggests, the “trees from the forest.” Meaningful results produced from purposeful and accurate data are the foundation from which significant analysis for relevant change occurs.2 Comparison information on a variety of improvement topics for exploration can be found in large data sources, such as the 11 Hospital Consumer Assessment of Healthcare Providers and Systems key topics or the Surgical Care Improvement Project core measures.3,4
METRICS, KEY PERFORMANCE INDICATORS, BENCHMARKS, AND ANALYTICS Specific elements for collecting, monitoring, and analyzing results for quality decision making in the perioperative setting are defined in this section. This section clarifies the terms metrics, key performance indicators (KPIs), benchmarks, and analytics and weaves together organizational and perioperative nursing examples.
http://dx.doi.org/10.1016/j.aorn.2015.07.015 ª AORN, Inc, 2015
www.aornjournal.org
AORN Journal j 223
Baker
September 2015, Vol. 102, No. 3
Metrics
Benchmarks
A metric is a specific measurement standard,5 such as the start time (ie, when the patient entered the room) for the first procedure of the day. Savvy organizations select the best metrics to track that are appropriate to what the organizational staff members wish to measure (eg, patient satisfaction, instrument and equipment defects, percentage of on-time starts).2 A set of metrics that nurses use often are vital signs (eg, blood pressure, pulse, respirations, temperature). However, simply having the metric for each vital sign does not provide complete information on which to base a decision; therefore, it is important to have additional information to support decision making, such as KPIs.
Benchmarks use the selected KPIs and expand on them to provide the means to evaluate similar items and determine if they are comparable. For example, a nurse takes the patient’s vital signs and acquires these metrics: a blood pressure of 164/100 mm Hg, a pulse of 100 beats per minute, a respiration rate of 25 breaths per minute, and a temperature of 100 F (37.8 C). At a glance, the nurse recognizes there is a problem because of the set of benchmarks he or she has learned regarding normal human physiology: blood pressure should be 120/80 mm Hg, the pulse should be 50 to 80 beats per minute, the respiration rate should be 16 to 20 breaths per minute, and the temperature should be 98.6 F (37 C). Organizational benchmarking is similar in that it is a means of “comparing a metric with a gold standard or best practice, or other internal or external reference point”5(p42) for evaluation purposes. Lang5 suggests a seven-step method to benchmark for improvement.
Key Performance Indicators “A KPI is a metric that embeds performance targets so organizations can chart progress toward goals.”6(p10) An example of an organizational target is the amount of revenue by year end, which can be tracked using minimum and maximum acceptable ranges and charted monthly to reflect progression toward that end goal.6 A clinical KPI might be total cholesterol level for a patient. The patient Mr Jones is informed that his total cholesterol level is 220; however, knowing only the number does not help the patient or health care provider understand the relevance of the number. It is important to know that “less than 200 mg/dL is desirable, 200 to 239 mg/dL is borderline high, and 240 mg/dL and above is considered high.”7 Therefore, the target maximum for Mr Jones’ cholesterol level would be any value less than 200 mg/dL. Tracking the value over time assists with understanding the progress made when taking various actions to manage a specific KPI. Selecting the KPIs for an organization is based on the goals of the organization; the goals should relate to the stability of processes, the structure supporting the systems (eg, standards driving the practice), and outcomes (eg, patient satisfaction, employee effectiveness).2 Best indicators assist in problem solving and lead to preventive actions (eg, prevention of patient falls) rather than corrective actions after an incident or episode has occurred.2 Data retrieved from multiple sources as a part of the KPI set assist health care providers in finding preventive answers and solutions to: (1) “enable cost savings and time reductions,” (2) “speed new product development,” and (3) “make smarter business decisions.”2(p24) It is important to focus on organizational priorities that create long-term value for patients, families, payers, and employees, as well as the organization. 224 j AORN Journal
1. 2. 3. 4. 5.
6. 7.
Identify goals. Identify the audience. Identify the data sources. Evaluate data quality: trustworthiness and validity. Develop a plan for reporting: in person or in writing, background or contextual information required to explain any limitations. Consider possible outcomes: decisions, action steps, additional investigation required to learn more about anomalous results. Improve. Correct data to use, report, or benchmark usefulness, additional audiences that need included in reporting.5(p42-44)
Analytics: Stages and Drivers Davenport and Harris define analytics as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact based management to drive decisions and actions.”8(p7) Analytics encompasses the transformation of data into actions following comprehensive examination that relates to the organization’s needs or problems to be solved and supports decision making.8 The four stages of analytics include
data, analysis, insights, and action.9(p314)
Drivers of analytics relate specifically to resources available to acquire and maintain the data, as well as the people necessary to sustain the analytics processes. These drivers center on data, software, process, and people available for the development of sustainable and useful analytics.9
www.aornjournal.org
September 2015, Vol. 102, No. 3
Analytics begins with the collection, extraction, and manipulation of data.9 For example, the data needed to determine procedure start times may come from radio-frequency identification used in a patient’s armband that is scanned when the patient enters an OR. It is critical to know that the data are relevant, reliable, and representative of what is to be measured and provide clear linkage with the strategy.2,10 Schultz suggests using the following questions to aid in determining reliability.
Why is data being collected? What data will be collected? What data collection tools and methods will be used? How will the data be collected? How will we know the right data have been collected? Where should data collection take place? When will the data be collected and for how long? Who will be responsible for collecting the data? Who will compile and analyze data collection results?2(p25)
The next stage in analytics is analysis, which includes the methods of visualization or graphical representation of key performance metrics, predictive modeling techniques, and optimization strategies to summarize the data for delving into problems or root causes.6,9 The analysis stage incorporates software that generates spreadsheets and statistical packages to aid in interpretation and reporting, and processes must be established and implemented to guide the development of tools for decision making and KPI management. It is imperative to identify individuals within the perioperative setting who have the needed skills or means to gain the required knowledge to create and use the analytics.9 Determining and describing insights is the next stage; this includes exploration into reflection on past occurrences, future expectations, and the goal or target based on the analysis of the operational data that identifies the actions necessary to resolve a problem.6,9 The final stage is taking action and making “operational decisions,” determining “process changes,” and finalizing “strategic formulations.”9(p314) Analytics is more data driven and less expensive to obtain than in the past. Increased data access can also increase motivation to perform additional analytics. It is also important to maintain the insights and decision rules in the systems to provide consistency regardless of whether the initial individuals who set the rules change roles or jobs. In addition, this consistency is important to allow all members of the health care team access to work from the same definitions to understand the data in relation to patients and their needs.9
www.aornjournal.org
Editorial
SCORECARDS AND DASHBOARDS The terms scorecard and dashboard are frequently interchanged11 and represent “different types of visual display mechanisms within a performance management system that convey critical performance information at a glance.”6(p9) Using scorecards and dashboards for purposes such as “strategic, tactical, and day-to-day operations, coupled with internal and external best-practice benchmarks, provide the framework for targeting improvement opportunities and evoking improvement changes to the perioperative process.”3(p2) A dashboard is a tool for monitoring operational performance processes, and scorecards focus on the progression of tactical and strategic goals. “Dashboards also tend to display charts and tables with conditional formatting, whereas scorecards use graphical symbols and icons to represent the status and trends of key metrics.”6(p9)
Scorecards A scorecard is a game metaphor with the intent of putting points on a board.10 Using scorecards bridges gaps between short-term objectives, such as financial measures, and longterm strategies and planning.1,2 Scorecard implementation “involves translating the strategic vision into targeted metrics, adapting strategic objectives into specific short-term activities, and creating a mechanism for review to better align strategy with activities that support it.”1(p20) Metrics for scorecard tactical and strategic visual displays appear in time measurements such as real time, hourly, daily, weekly, or monthly and indicate trends.11 The most time-relevant and customer-centered elements are tracked and displayed often, making them competitively vital for both customers and other stakeholders.11 Schonberger suggests managers should, “React often to short lag-time metrics, less often to those with intermediate lag, and seldom for metrics with long lag time.”11(p12-13) Figure 1 shows a scorecard with a
Figure 1. Scorecard illustrating the number of surgical patients in 2015. AORN Journal j 225
Baker
Figure 2. Dashboards illustrate variation using stoplights, colors, and icons. single metric graph of the number of surgical patients by month for the current year, which might be used to explore seasonal variation that could affect staffing, such as an increased spike in procedures in December that may be directly related to patient falls caused by ice during that winter and correspond to an increase in hip replacement procedures.
Dashboards Glancing at the car dashboard while driving is the metaphor for using dashboards in business and in perioperative nursing. An organizational dashboard “measures [its] velocity relative to the external environment.”10(p24) A strategic dashboard focuses attention on analysis and reflection for quality decision making to improve performance.10 Alerts are established for marking change in status using such things as stoplights, change in color, or icons6 (Figure 2). “Dashboards consolidate key performance indicators into a single visual display that offers an at-a-glance window into overall business performance. The most effective dashboards
Figure 3. Dashboard illustrating the number of surgical patients in 2015 with target line based on benchmark data from other facilities for comparison. 226 j AORN Journal
September 2015, Vol. 102, No. 3
are good at emphasizing critical data, while still providing enough context to draw a meaningful assessment.”1(p20) Figure 3 illustrates a dashboard showing the same surgical patient data from the scorecard previously mentioned with the targeted benchmarked thresholds for facilities with a similar number of ORs. This dashboard also depicts a slight upward trend in patients even with the given erratic data points, which may be caused by factors such as seasonal elements or an OR closed for repairs for one month. However, an individual must interpret and analyze the graphics from a dashboard to generate new ideas and perspectives for changes and patient improvement.
Scorecard and Dashboard Use in Perioperative Settings One metric captured in perioperative settings across the country is the number of surgical patients per day, week, month, and year. Tracking these data over a year in monthly increments provides a scorecard of trending data. Additional elements such as number/month for the previous year and projections for year to date based on the year-todate data would be assistive in the scorecard for purposes of analysis. When two metrics such as the number of “surgical patients” is used with the number of “on-time OR procedure starts” for a given time frame (eg, one month), a comparison point (percentage) establishes a location on the operational dashboard (eg, 90% of the patients entered the OR on time). Determining benchmarks such as comparison to other hospitals in the same system or external to the system from other large databases can establish ranges for thresholds and the results can demonstrate the need for continuous performance improvement. For example, the upper threshold might be set at 95%, and the lower threshold at 90%. Anything above 95% would show on the dashboard as green, anything in the range of 91% to 94% would show as yellow, and any number 90% or below would show as red. If the information demonstrates a negative trend (eg, several months of data points in the red), immediate action may be required. Monitoring without taking any action may be necessary to determine whether the single month that scored 94% is an outlier, with the subsequent months all in the green range. Other examples of benchmarks involving patients could be the revenue for each patient or the number of minutes per surgical procedure. Overlaying targets from selected benchmarks of organizations similar in size and case mix and then connecting these to the overall strategy of the system is the subsequent
www.aornjournal.org
September 2015, Vol. 102, No. 3
Editorial
move toward validating and using the information presented for evidence-based decision making.
CONCLUSION Perioperative nurses and leaders use trending data to support decision making, specifically processes tied to “patient flow, patient safety, patient quality of care, and stakeholders’ satisfaction (i.e. patient, physician/surgeon, nurse, perioperative staff, and hospital administration).”3(p1) Understanding and monitoring the various metrics using scorecards and dashboards to paint effective and useful pictures may lead to improved outcomes in perioperative settings.
References 1. Mayfield M, Martinez M, Pansard C, Serr R, Shields J, Wong S. Battling the demons of complexity: design thinking in a business context. Des Manage Rev. 2012;23(2):18-26. 2. Schultz JR. Big data are, after all, just data. Perf Improv. 2014; 53(5):20-25. 3. Ryan J, Doster B, Daily S, Lewis C. A balanced perspective to perioperative process management aligned to hospital strategy. Int J Healthc Inf Syst Inform. 2014;9(4):1-19. 4. HCAHPS Fact Sheet (CAHPS Hospital Survey). Hospital Consumer Assessment of Healthcare Providers and Systems. http://www .hcahpsonline.org/Files/HCAHPS_Fact_Sheet_June_2015.pdf. Accessed June 3, 2015. 5. Lang L. Benchmarking to inform planning: the EDUCAUSE core data service. EDUCAUSE Rev. 2015;50(3):40-48.
www.aornjournal.org
6. Eckerson WW. Deploying dashboards and scorecards. TDWI Best Practice Report. The Data Warehousing Institute. https://www.micro strategy.com/Strategy/media/downloads/solutions/TDWI-Best -Practices-Report-Deploying-Dashboards-and-Scorecards.pdf. Accessed June 3, 2015. 7. Cholesterol levels: what you need to know. NIH Medline Plus. http://www.nlm.nih.gov/medlineplus/magazine/issues/summer12/ articles/summer12pg6-7.html. Accessed June 5, 2015. 8. Davenport TH, Harris JG. Competing on Analytics: The New Science of Winning. Boston, MA: Harvard Business School Publishing Corporation; 2007. 9. Liberatore MJ, Luo W. The analytics movement: implications for operations research. Interfaces. 2010;40:313-324. 10. Allio MK. Strategic dashboards: designing and deploying them to improve implementation. Strategy & Leadership. 2012;40(5): 24-31. 11. Schonberger RJ. Time-relevant metrics in an era of continuous process improvement: the balanced scorecard revisited. Quality Management Journal. 2013;20(3):10-18.
Joy Don Baker, PhD, RN-BC, CNOR, CNE, NEA-BC, is the editor-in-chief of the AORN Journal and a clinical professor at the University of Texas at Arlington, College of Nursing and Health Innovation. Dr Baker has no declared affiliation that could be perceived as posing a potential conflict of interest in the publication of this article.
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