Should analytic digital dashboards be used to track individual nurse performance?

Should analytic digital dashboards be used to track individual nurse performance?

Paula Grech

Eastern Michigan University

NURS 365: Essentials of Professional Practice II for Registered Nurses

Dr. Linda Myler DNP, RN, CHSE-A, CNE

February 21, 2021

Abstract

Individual analytic nurse dashboards are relatively new to the healthcare industry, even though data mining and dashboards have been an essential tool for other industries for decades (McKinsey, 2020). To determine how analytic dashboards impact individual nurse performance and patient outcomes a CINAHL and Google search was conducted on individual nursing performance dashboards. Federal laws that impact the use of big data in healthcare were searched as well. Although literature on analytic nursing dashboards is relatively scant, there is enough to get a sense of the negative and positive consequences of mining nursing performance data and displaying it on a dashboard. For greater context, a search was conducted for literature on personal physician analytic dashboards and health care technology industry forecasting reports that focused on data integration. The results of this inquiry suggest that nursing digital dashboards are in our future; indeed, the influential Agency for Healthcare Research and Quality has funded a study on this very topic. This research paper studies both the benefits and the ramifications of the adoption of personal nurse digital dashboards.

 Keywords: nurse, physician, big data, dashboard, performance metrics, patient outcomes

Should analytic digital dashboards be used to track individual nurse performance?

Have you ever felt that Facebook is reading your mind? The social media giant mines data to influence and predict user behavior with extraordinary accuracy. Data mining and business intelligence -- “big data” -- has been used successfully for decades in other industries. However, when it comes to the healthcare industry, the adoption of analytics lags (McKinsey, 2020). Healthcare organizations are leery of technology innovations; most wait to see how new technologies pan out for other institutions before implementing them (Diana, 2014). They can’t afford to have systems crash or allow patient data to be compromised. But the careful application of data analytics could solve deep-rooted healthcare inefficiencies, such as service-line redundancies, inconsistent patient experience, the fractured payment infrastructure, and standardize clinician performance. These problems lead to poor quality of care, adverse patient outcomes, and increases in costs (McKinsey, 2020). Linnen reports that big data will achieve the Institute for Healthcare Improvement's Triple Aim: improve patient experience and health outcomes while reducing healthcare costs (2016). Because nurses are the largest group of healthcare providers, nursing analytic dashboards could be an integral part of this mission.

One of the primary hindrances to data analytics being embraced by the health care industry is the Health Insurance Portability and Accountability Act (HIPAA). The Federal HIPAA Privacy and Security Rules establish national standards to protect individuals' health information privacy. It applies to health plans, health care clearinghouses, and providers that conduct certain health care transactions electronically (Office for Civil Rights, 2020). The State of Michigan’s Nonprofit Health Care Corporation Reform Act also forbids the patient personal data from unauthorized access (The Nonprofit Health Care Corporation Reform Act, 1980).

While big data hasn’t yet become ubiquitous in health care, there have been inroads. The 2009 Federal Health Information Technology for Economic and Clinical Health Act has led to improvements in quality and patient safety through better diagnostic and therapeutic decision support (Linnen, 2016). When it comes to nursing, data drives nursing unit dashboards that track and measure catheter-associated urinary tract infections and healthcare-associated infections. According to Welton (2016), nurses will be subject to individual performance metrics, standards of practice, and benchmarks through digital dashboards. I’ve experienced my individual nurse dashboard through the Epic charting system; it shows me my door-to-electrocardiogram times, the average length of stay of my patients, and their average acuity. Additional individual nurse metrics are available to managers. Our staff was recently informed that our collective medication scanning was only 96% -- and that it needed to be 99%. Nurses who bring down the average will receive an intervention -- a real-world example of tracking individual nurse performance.

This paper will address the usefulness of nursing dashboards by presenting differing viewpoints on this controversial issue and submit evidence related to their benefits to nurses, patients, and Healthy People 2030. I am an advocate for nurse dashboards, and will outline my reasons in this paper.

Repercussions of Individual Nurse Dashboards

Nursing dashboards are a multifaceted issue, and as with any systemic change, there are implications, some of which may be negative. There are possible repercussions to the individual nurse. For example, digital dashboards have the potential to pull back the curtain on nurse-patient bias (Welton, 2016). What may once may have been a supervisor's hunch or anecdotal evidence of a nurse's performance failure will be backed up with data. However, there is more to be gained than lost with nurse dashboards.

Discrimination of Individual Nurses

There exists the risk of using the data to reach harmful conclusions outside the scope of the dashboard. For example, using unique patient and nurse identifiers, links can be made using the nurse and the patient's race, age, and sex (Welton, 2016). The ability to determine if there was a bias in administering PRN opioids based on these parameters would exist. This could lead to nurse discrimination and perhaps label nurses as "racist", "ageist," and more (Welton, 2016). Other nurse parameters, such as experience can be used to determine the effect on patient outcome. Welton states such databases could also assess how often patient pain assessments are performed and track patient surveillance gaps by individual nurses (2016).

Scapegoating

The contribution of an individual’s data to judge the team's collective productivity could lead to scapegoating of lower-performing nurses. If missed nursing care is isolated to a small number of nurses or individuals, those nurses can be targeted for their lower than expected achievement (Welton, 2016). Clinicians have also expressed concerns about their performance being shared on a dashboard, leading to negative repercussions from other team members if they fail to meet performance criteria (Henry, 2017).

Gaming of the system

Defensiveness could lead to the gaming of the data. According to Henry, users may develop workarounds to ensure the technology fits the existing practices and not the other way around (2017). Clinicians may choose to work with healthy patients rather than sick ones to make their performance stats look good on a dashboard (Henry, 2017). As Welton states, a system designed to track nurse performance needs to be built by nurses instead of insurers and policymakers (2016). If not, dashboards might put profits at odds with patient outcomes. Perron et al. (2017) created physician dashboards with physician input and they found that users exceeded financially incentivized goals. Even as we consider the drawbacks of nurse dashboards, there is evidence individual nurse dashboards promote accountability and improve patient outcomes.

Benefits of Individual Nurse Dashboards

Personal Clinician Improvement

According to Barnum et al. (2019), dashboards operate on control theory, which states that individuals work on a feedback loop comparing their performance to a goal. Therefore dashboards improve clinician practice. According to Topaz and Pruinelli, big data is becoming progressively more common, and influences the way nurses learn and practice (2017). My dashboard inspires me to improve. I can see my door-to-EKG times, my average length of stay, and average patient acuity. This gives me a snapshot of strengths and improvement areas and where I rank in terms of being able to care for critical patients. I get immediate insight into my performance in a real-time, non-biased empirical way. Perron et al. state that their physician dashboard encouraged self-reflection and professional motivation among the users (2017). The dashboard also allowed for feedback and support at the individual physician level and promoted accountability (Perron et al., 2017).

Better Patient Outcomes

Barnum et al., state that studies show that dashboards lead to better patient outcomes (2019). The authors mention a Stanford study that used a dashboard to display compliance with a central venous catheter insert and care bundle on a pediatric intensive care ward and correlated dashboard use to decreased infection rates (Barnum et al., 2019). Boston Children’s Hospital has linked individual physician performance dashboards to patient outcomes for the past ten years (Perron et al., 2017). The dashboard included meaningful and engaging metrics chosen by the physicians used in conjunction with the nationally mandated performance goals. Their study found that fewer children with a Glasgow Coma Score of more than 14 underwent computerized tomography scans of the head.

According to Linnen (2016), early adopters of big data are already using it for precision medicine, for example, linking disease processes to genetics. The author purports that big data in nursing will lead to precision nursing and identify specific patients at risk for nurse-sensitive adverse outcomes (Linnen, 2016).

Ability to Assess the Effect of Staffing Issues

Nurse dashboards will allow administration to assess the effect of staffing levels on patient care directly. Linnen writes that performance problems due to staffing issues such as high ratios would be apparent; for example if all nurses in a particular unit are having difficulty keeping up with their workload, it would be evident on the dashboard that the problem is systemic. This data gives management empirical tools to address staffing issues (2016). Dashboards allow for a better overall understanding of group performance, providing guideposts for better baseline group performance and identifying outliers (Barnum et al., 2019). Managers would be able to identify nurses in need of additional training and provide it, ensuring consistent staff proficiency.

Planning for The Future

Per Dowding (2017), nursing dashboards are in our future; they are on the radar of governing organizations such as the Agency for Healthcare Research and Quality. To optimize their utility, the nurse dashboard of the future demands active input from the end-users, nurses themselves (Linnen, 2016). This requires that a cohort of nurses be educated in informatics. Nurse informaticist positions require a master’s degree which are costly and time-consuming to acquire.

There’s also the issue of standardization: The ANA currently supports 12 different nursing terminology standards (Linnen, 2016). Without one standard, data interoperability will be difficult. I fear that the standard will ultimately be decided by the market reach of the most successful vendors rather than what’s suitable for process. Linnen (2016) also points out that there is a lack of funding for big data interoperability efforts. There are some hopeful indicators that interoperability will be addressed at the federal level. McKinsey states the Centers for Medicare and Medicaid Services and the Office of the National Coordinator for Health Information Technology are making changes to promote data sharing between healthcare organizations (2020). These federal regulatory changes include interoperability of private electronic health record data and increased transparency for consumers. These developments may help eliminate the data silos that have historically prevented end-to-end care analytics and will hopefully promote the use of individual nurse dashboards (McKinsey, 2020).

One of the goals of Healthy People 2030 is to eradicate health disparities and attain health equity for all Americans in the future. (Office of the Secretary, U.S. Department of Health and Human Services, n.d.). Nursing dashboards can help to accomplish this goal by helping to uncover possible nurse-sensitive causes of inequities.

Conclusion

        When we use Facebook, we trade a bit of personal privacy for access to Facebook’s utility. For the sake of the advantages that analytic nurse dashboards provide, nurses make a similar trade. The discomfort that comes from the new transparency that dashboards offer could be mitigated by educating more nurse informaticists to control the processes rather than hospital administrators or the insurance industry (Linnen, 2016; Welton, 2016). Nursing dashboards will improve patient outcomes and help nurses become better clinicians faster. Federal and state governments are pushing healthcare to be more value-based, and consumers want healthcare to be transparent. Nursing dashboards can assist in accomplishing these goals.

References

Barnum, T., Vaez, K., Cesarone, D., & Yingling, C. (2019, November 25). Your data looks good on dashboard. Healthcare Information and Management Systems Society. https://www.himss.org/resources/your-data-looks-good-dashboard

Diana, A. (2014, September 16). Health IT early mover advantage examined. Information Week. https://www.informationweek.com/healthcare/electronic-health-records/health-it-early-mover-advantage-examined/d/d-id/1315774

Dowding, D. (Principal Investigator). (2015-2017). Development of dashboard to provide feedback to home care nurses. (Project No. 1R21HS023855) [Grant]. Agency for Healthcare Research and Quality. https://digital.ahrq.gov/ahrq-funded-projects/development-dashboards-provide-feedback-home-care-nurses 

Henry, S. (2017). Evaluating the effect of clinical dashboards designed to measure and improve the quality of nursing care and patient safety, in a mental health setting. [Unpublished master’s thesis]. University of Dublin.

Linnen, D. (2016). The promise of big data. Improving patient safety and nursing practice. Nursing (46)5, 28-34. doi: 10.1097/01.NURSE.0000482256.71143.09

Office for Civil Rights. (2020, September). The security rule. https://www.hhs.gov/hipaa/for-      professionals/security/index.html

Office for Civil Rights. (2020, December). The HIPAA privacy rule.

https://www.hhs.gov/hipaa/for-professionals/privacy/index.html

Office of Disease Prevention and Health Promotion, Office of the Assistant Secretary for Health, Office of the Secretary, U.S. Department of Health and Human Services. Healthy People 2030.

 https://health.gov/healthypeople

Perron, E., Bachur, R., & Stack, A. (2017). Development, implementation, and use of an emergency physician performance dashboard. Clinical Pediatric Emergency Medicine. (18)2. 115-123. https://doi.org/10.1016/j.cpem.2017.04.004

The Nonprofit Health Care Corporation Reform Act, Act 350 § 550.1406 (1980).

https://www.legislature.mi.gov/(S(ue1lyvr5urs4x25oibuyefnm))/mileg.aspx?page=getObject&objectname=mcl-550-1406#:~:text=(1)%20A%20health%20care%20corporation,proper%20review%20and%20payment%20of

Topaz, M., & Pruinelli, L. (2017). Big data and nursing: implications for the future. Studies in Health Technology and Informatics Vo. 232: Forecasting Informatics Competencies for Nurses in the Future of Connected Health. IOS Press. 165-17. doi:10.3233/978-1-61499-738-2-165

Welton, J. (2016). Nurses and the ethics of big data. Nursing Economics (34)5, 257-259. doi:10.3233/978-1-61499-738-2-165