Incentives for Computerized Care: How Can Hospitals Navigate Tech Without Compromising Patient Outcomes?

Allen Curreri: Incentives for Computerized Care (1)

 

It’s not exactly a new insight to say that technology is the future. Both science and the popular imagination have been anticipating the development of super smart tech for decades, tech that will help us live longer, better lives on almost every front. So much of what was once science fiction is now almost within our grasp — already, doctors are working in tandem with specialized computer programs to provide better, more accurate treatment for their willing patients. Just like in the movies, however, this powerful technology can backfire if we don’t take the time to understand it properly and think critically about its integration.

 

Clinical decision support systems (CDSSs), or electronic systems “designed to help healthcare professionals to make clinical decisions” (Musen, Middleton, & Greenes, 2014) are a rapidly developing field of technology, and they are poised to change medicine forever. Overall, the adaptation and implementation of CDSS technologies has been greeted with positive acclaim. The research community widely believes that CDSS implementation will help to improve emergency medical care (Dinh & Chu, 2006; Tang & Ng, 2006; Walsh & Abelson, 2008), and physicians and nurses in acute care settings have a positive perception of CDSSs (Archambault et al., 2012).

 

Even the US Department of Health and Human Services believes CDSS use will benefit patient outcomes, claiming that the technology “represents one of the most promising tools to mitigate the ever-increasing complexity of the day-to-day care practice of medicine” (HealthIT.gov, 2014). The government further states: “When implemented successfully, CDS can assure that all patients in a practice receive appropriate and timely preventive services. The effective use of a clinical decision support system means patients get the right tests, the right medications, and the right treatment, particularly for chronic conditions” (HealthIT.gov, 2014) Legislators have so much faith in this statement that they have incentivized the use of CDSSs: first in 2009 in the Health Information Technology for Economic and Clinical Health Act, which earmarked “as much as $36.5 billion in spending to create a nationwide network of electronic health records” and for the promotion and expansion of health information technology, including CDSSs (O’Harrow, 2009); second, in the Protecting Access to Medicare Act of 2014, which created Medicare mandates which limit reimbursement for services, specifically in regards to advanced diagnostic imaging exams, to physicians who had consulted a government-approved CDSS (Keen, 2014).

 

The problem is, there is no empirical evidence that CDSSs improve patient outcomes, physician performance, or a hospital’s cost efficiency. Bright et al. (2012) and Garg et al. (2005) both conducted systematic reviews to determine what, if any, effect CDSS implementation had on those three factors, and neither study uncovered discernible performance improvements. According to Berner (2009), “Although the CDS systems can frequently provide useful advice, the advice is not foolproof” (17).  Berner (2009) found that physician overrides, patient error, and other factors could contribute to CDSS inefficiency, and that CDSS implementation studies overall have found patient outcome results mixed with a need for further study.

 

Regulation on these systems is limited as well, with the FDA classifying most CDSSs as “health management health IT,” a category which does not require regulatory oversight from the FDA (Keen, 2014). This lack of oversight allows for CDSS developers to quickly create products without extensive testing and put them on the market where it is possible that they may be ineffective or even cause patient harm.

 

Administrators and physicians cannot ignore the lack of firm evidence of CDSS benefits, but they also cannot ignore the incentives they receive to use them. CDSS implementation and use increases reimbursement amounts, which all but forces physicians and hospitals to use them (Keen, 2014). The Health Information Technology for Economic and Clinical Health Act (HITECH) of 2009 stipulated that by 2015, healthcare providers had to show “meaningful use” of health information technologies, including CDSS, or their Medicare reimbursements would decrease in 2016 (CDC, 2016).

 

As it is fiscally irresponsible to ignore HITECH and other legislation which reduces Medicare reimbursement, hospital administrators must implement and enforce the use of CDSSs. Where administrators can take control is in which CDSS they pick to use and the best practices they create around CDSS use.

 

My research is based on the theory that a best practice of encouraging mindfulness will help physicians and healthcare providers to make the most of CDSS technology without compromising patient outcomes. My previous, quantitative study revealed that physicians who use IT tools (broadly defined in that study) more frequently were rated as lower performing (β = -.329, p = 002). Mindfulness, however, dampened this effect. This suggests that mindfulness may be one factor that influences CDSS use, leading to increased physician performance.

 

Mindfulness is “the capacity to be aware of one’s internal condition and external situation as fully and as consciously as possible” (Coget & Keller, 2010: 69).  Whereas CDSS use may decrease mindfulness by discouraging context awareness (France et al. 2005), mindfulness may increase physician performance (Lovell 2015; Martín-Asuero & García-Banda 2010; Westphal et al. 2015). My previous study found that mindful physicians use IT differently from less mindful physicians, and these differences have a positive impact on overall physician performance.

 

One reason for this is that mindfulness helps to encourage focus outside of a routine. CDSS use relies strongly on routine, creating automatic task executions that are vulnerable to any changes or deviations (Butler & Gray, 2006). Without discipline and awareness, these routines may allow the mind to be less aware of situational information and instead function on a metaphorical autopilot. According to Butler & Gray (2006), routines can be “helpful when they provide options, but detrimental when they hinder detection of changes in the task or environment” (214). Practicing mindfulness allows for physicians to detect those changes, which in turn creates a dynamic system of decision making that allows for both routine-based reliability and mindfulness-based reliability for the best possible outcome.

 

In addition to encouraging mindfulness within medical settings, administrators should also seek to better understand the effects of CDSS implementation before making it widespread. Technology changes quickly, and what may be de rigueur today may be outdated tomorrow. However, hasty adoption of CDSS technologies may bring compromised patient outcomes with it as physicians and medical staff struggle to quickly adapt. Due to the lack of strong evidence of CDSS’s ability to improve physician performances and patient outcomes (Garg et al., 2005; Bright et al., 2012), administrators must use prudence and caution when deciding to implement new CDSSs.

 

Clinical decision making is a complex process, and CDSSs are already crucial tools in many patient care environments in the United States. To make the most of these government-mandated tools, physicians and other healthcare practitioners may benefit from adopting mindfulness in addition to CDSSs.

 

 

 

References

Archambault, P. M., Bilodeau, A., Gagnon, M.-P., Aubin, K., Lavoie, A., Lapointe, J., Poitras, J., Croteau, S., Pham-Dinh, M., & Légaré, F. (2012). Health care professionals’ beliefs about using wiki-based reminders to promote best practices in trauma care. Journal of Medical Internet Research, 14(2): 273-294.

Berner, E.S. (2009) Clinical decision support systems: State of the Art. AHRQ Publication No. 09-0069-EF.

Bright, T. J., Wong, A., Dhurjati, R., Bristow, E., Bastian, L., Coeytaux, R. R., Samsa, G., Hasselblad, V., Williams, J. W., & Musty, M. D. (2012). Effect of clinical decision-support systems: a systematic review. Annals of internal medicine, 157(1): 29-43.

Butler, B. S. & Gray, P. H. (2006). Reliability, mindfulness, and information systems. Mis Quarterly: 211-224.

CDC. (2016, May 26). “Meaningful Use.” Retrieved October 07, 2016.

Coget, J.-F. & Keller, E. (2010). The critical decision vortex: Lessons from the emergency room. Journal of Management Inquiry, 19(1): 56-67.

Dinh, M. & Chu, M. (2006). Evolution of health information management and information technology in emergency medicine. Emergency Medicine Australasia, 18(3): 289-294.

France, D. J., Levin, S., Hemphill, R., Chen, K., Rickard, D., Makowski, R., Jones, I., & Aronsky, D. 2005. Emergency physicians’ behaviors and workload in the presence of an electronic whiteboard. International journal of medical informatics, 74(10): 827-837.

Garg, A. X., Adhikari, N. K., McDonald, H., Rosas-Arellano, M. P., Devereaux, P., Beyene, J., Sam, J., & Haynes, R. B. (2005). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. Jama, 293(10): 1223-1238.

HealthIT.gov. (2014, February 27). “Implementing a Clinical Decision Support Rule.” Retrieved October 07, 2016.

Keen, C. E. (2014). “The clinical decision-support mandate: Now what?” Radiology Business. Retrieved October 7, 2016.

Lovell, B. (2015). When I say … mindfulness. Medical education, 49(7): 653-655.

Martín-Asuero, A., & García-Banda, G. (2010). The mindfulness-based stress reduction program (MBSR) reduces stress-related psychological distress in healthcare professionals. The Spanish journal of psychology, 13(02): 897-905.

Musen, M. A., Middleton, B., & Greenes, R. A. (2014). Clinical decision-support systems, Biomedical informatics: 643-674.

O’Harrow, R. (2009, May 16). “The machinery behind health-care reform.” The Washington Post.

Tang, H. & Ng, J. H. K. (2006). Googling for a diagnosis—use of Google as a diagnostic aid: internet based study. Bmj, 333(7579): 1143-1145.

Walsh, C. & Abelson, H. T. (2008). Medical professionalism: Crossing a generational divide. Perspectives in biology and medicine, 51(4): 554-564.

Westphal, M., Bingisser, M., Feng, T., Wall, M., Blakley, E., Bingisser, R., & Kleim, B. (2015). Protective benefits of mindfulness in emergency room personnel. Journal of affective disorders, 17579-85.

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