- Email: [email protected]
The Electronic Medical Record and Computerized Physician Order Entry: Challenges and Opportunities for Pediatrics
The Electronic Medical Record and Computerized Physician Order Entry: Challenges and Opportunities for Pediatrics Nina F. Schor, MD, PhD
I
n the infancy of modern routine medical care, one physician who was holistic, authoritative, and experientially driven, took care of each patient. When physician-tophysician communication was needed, it took place by written note or letter, or by personal verbal interaction.1 Written notes in medical charts were informational, not legal or billing documents, that served to inform and remind the one-and-only-one doctor of his or her findings and decisions. As long as the doctor could read his or her own handwriting or remember what last transpired, all was well. As time passed and medicine matured, care was increasingly provided by multidisciplinary teams. The percentage of the pediatric patient cohort that was chronically ill vastly increased. Hospital and medical office notes became used for billing and legal documentation, as well as interprovider communication. The number of “hand-offs” from one health care provider to another grew enormously. The need for a tool through which to store and share information became critical. Hence, the electronic medical record (EMR).2,3 This proliferation of data has been accompanied and fueled by an increase in volume and complexity of the clinical options available. No one person can master this continuously evolving armamentarium; therefore, to decrease the likelihood of error at any stage in the process between conceptualization of a plan and delivery of the elements of that plan to the patient, computerized physician order entry (CPOE) was born.4 It should not be surprising to anyone that arrival at a solution for voluminous, complex information accrual and distribution creates new and different problems. The benefits of the EMR and CPOE include comprehensive information storage, facility of information retrieval, and availability and uniformity of algorithm-driven care protocols. These serve the needs of the vast majority of children, who are usually healthy, require tracking of growth and preventive health care procedures, and are occasionally sick with common, algorithmically-treated illnesses. Data support the notion that CPOE decreases or eliminates errors in transcription, protocol compliance, and dose determination.5-7 But new problems created by the EMR and CPOE5 are most problematic for the growing number of children with complex, chronic health care needs. These problems include decreased
time for direct information gathering from patients,8 devaluation of creative problem-solving, and worsening care for “outliers” in the population at large. In medical practice, each patient is an “n of 1” research study in which the physician forms a hypothesis and then tests and reframes that hypothesis with each successive element of the work-up. Protocolization of care with “order sets” and macros may discourage consideration of the elements of the clinical picture that make each patient unique.9 As we succeed at eliminating “unwanted variation” in care, we run the risk of eliminating “wanted variation” in care that reflects variation in host and disease phenotypes. The ease with which one carries forward elements of the clinical picture by cutting and pasting into the record what has been written previously by others invites propagation of errors and repetitive inclusion of irrelevant or outdated information. This works against our trainees honing their skills at analyzing and prioritizing information.10 We are faced with electronic macros that obviate analytical thinking and downplay individualization of medical care. In the premacro medical care realm, errors occurred on a random, stochastic basis. The new electronic era breeds errors that result from patients being “nonstandard.” Instead of 1 error in 1000 that affects whoever is the object of that random event, we see 1 error in 10 000 aimed at those whose condition does not fit the standard for which the macro was designed. We live in communities with a rising median age, in a world where healthy, cognitively normal adults form the predominant population. To play only statistics in improving the error-free rate of health care delivery often means to fashion algorithms that ignore children, cognitivelyimpaired individuals, and those who metabolize drugs in unconventional ways.11 No matter what one thinks of the EMR and CPOE, they are doubtless here to stay. It seems society has made the decision that decreasing variation in practice, increasing reliable transmission of information, and enhancing access from anywhere to prior medical records take priority over ensuring that population outliers get the “off-center” care they need.
From the Departments of Pediatrics, Neurology, and Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY The author declares no conflicts of interest.
CPOE EMR
Computerized physician order entry Electronic medical record
0022-3476/$ - see front matter. ª 2016 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jpeds.2016.06.001
5
THE JOURNAL OF PEDIATRICS
www.jpeds.com
The response of pediatricians must be to fashion advantage from adversity. We must seize this opportunity to use the EMR and CPOE to accrue data that continually inform and improve our practice so that they work for us, instead of the other way around. The liability of rendering conventional care to decidedly unconventional patients mandates that algorithms developed for the EMR and CPOE include big box warnings and work-arounds for patients whose age, creatinine clearance, or liver function tests, for example, lie outside of the “average adult” range. Eventually, such black box warnings might pop up as reminders to consider the individual characteristics of a patient whose history includes words like Down syndrome, cerebral palsy, congenital heart disease, or certain birth defects. CPOE in most institutions now includes algorithms for weight-based dosing, and increasingly individualized algorithms should include age-based versions of weight-based dosing, as well.12,13 One proposed automatic generator of order sets iteratively “learns” from the individual user and the evidence base.13 Perhaps the EMRs and CPOE instruments of the future will learn across institutions, as well, and provide access to protocols developed elsewhere using an otherwise institution-specific EMR. This means that policy- and practice-determining committees in every hospital or clinic must include pediatricians whose job it is to ensure that their populations are wellserved by the decisions made. Protocolized care creates both the imperative and the opportunity for raising awareness and attention to the unique health needs and attributes of children and the opportunity for closer collaboration among providers of health care across the age and health spectra. How should we pediatricians combat the repetition of text from one note to the next in a patient’s EMR?3 It would seem that one could build antiplagiarism software that would look for repletion of prior material that is longer than so many contiguous words! Should we reconfigure the EMR to prioritize and highlight new findings and information that actually contributes to the care of the patient? As long as we live and work in a fee-for-service universe that incentivizes inclusion of more and lengthier elements in the written account of each patient encounter, we may be stuck with a problem. It is likely that population management with population-based compensation will go a long way toward ameliorating this
6
Volume 176 problem. And we would all be surprised if it did not create new problems of its own! n Reprint requests: Nina F. Schor, MD, PhD, Departments of Pediatrics, Neurology, and Neuroscience, University of Rochester School of Medicine and Dentistry, Golisano Children’s Hospital, 601 Elmwood Ave, Box 777, Rochester, NY 14642. E-mail: [email protected]
References 1. Graham HK. Relationships in consultation. Calif Med 1953;79:274-8. 2. McDonald CJ, Tierney WM. Computer-stored medical records. Their future role in medical practice. JAMA 1988;259:3433-40. 3. Gummadi S, Housri N, Zimmers TA, Koniaris LG. Electronic medical record: a balancing act of patient safety, privacy and health care delivery. Am J Med Sci 2014;348:238-43. 4. Handler JA, Feied CF, Coonan K, Vozenilek J, Gillam M, Peacock PR Jr, et al. Computerized physician order entry and online decision support. Acad Emerg Med 2004;11:1135-41. 5. Ruano M, Villama~ nan E, Perez E, Herrero A, Alvarez-Sala R. New technologies as a strategy to decrease medication errors: how do they affect adults and children differently? World J Pediatr 2016;12:28-34. 6. MacKay M, Anderson C, Boehme S, Cash J, Zobell J. Frequency and severity of parenteral nutrition medication errors at a large children’s hospital after implementation of electronic ordering and compounding. Nutr Clin Pract 2015;31:195-206. 7. McCrory MC, Strouse JJ, Takemoto CM, Easley RB. Computerized physician order entry improves compliance with a manual exchange transfusion protocol in the pediatric intensive care unit. J Pediatr Hematol Oncol 2014;36:143-7. 8. Carayon P, Wetterneck TB, Alyousef B, Brown RL, Cartmill RS, McGuire K, et al. Impact of electronic health record technology on the work and workflow of physicians in the intensive care unit. Int J Med Inform 2015;84:578-94. 9. Knight AM, Kravet SJ, Harper GM, Leff B. The effect of computerized provider order entry on medical student clerkship experiences. J Am Med Inform Assoc 2005;12:554-60. 10. Bowman S. Impact of electronic health record systems on information integrity: quality and safety implications. Perspect Health Inf Manag 2013;10:1c. 11. Saxena K, Lung BR, Becker JR. Improving patient safety by modifying provider ordering behavior using alerts (CDSS) in CPOE system. AMIA Annu Symp Proc 2011;2011:1207-16. 12. McAlearney AS, Chisolm D, Veneris S, Rich D, Kelleher K. Utilization of evidence-based computerized order sets in pediatrics. Int J Med Inform 2006;75:501-12. 13. Zhang Y, Padman R, Levin JE. Paving the COWpath: data-driven design of pediatric order sets. J Am Med Inform Assoc 2014;21:e304-11.
Schor
I
n the infancy of modern routine medical care, one physician who was holistic, authoritative, and experientially driven, took care of each patient. When physician-tophysician communication was needed, it took place by written note or letter, or by personal verbal interaction.1 Written notes in medical charts were informational, not legal or billing documents, that served to inform and remind the one-and-only-one doctor of his or her findings and decisions. As long as the doctor could read his or her own handwriting or remember what last transpired, all was well. As time passed and medicine matured, care was increasingly provided by multidisciplinary teams. The percentage of the pediatric patient cohort that was chronically ill vastly increased. Hospital and medical office notes became used for billing and legal documentation, as well as interprovider communication. The number of “hand-offs” from one health care provider to another grew enormously. The need for a tool through which to store and share information became critical. Hence, the electronic medical record (EMR).2,3 This proliferation of data has been accompanied and fueled by an increase in volume and complexity of the clinical options available. No one person can master this continuously evolving armamentarium; therefore, to decrease the likelihood of error at any stage in the process between conceptualization of a plan and delivery of the elements of that plan to the patient, computerized physician order entry (CPOE) was born.4 It should not be surprising to anyone that arrival at a solution for voluminous, complex information accrual and distribution creates new and different problems. The benefits of the EMR and CPOE include comprehensive information storage, facility of information retrieval, and availability and uniformity of algorithm-driven care protocols. These serve the needs of the vast majority of children, who are usually healthy, require tracking of growth and preventive health care procedures, and are occasionally sick with common, algorithmically-treated illnesses. Data support the notion that CPOE decreases or eliminates errors in transcription, protocol compliance, and dose determination.5-7 But new problems created by the EMR and CPOE5 are most problematic for the growing number of children with complex, chronic health care needs. These problems include decreased
time for direct information gathering from patients,8 devaluation of creative problem-solving, and worsening care for “outliers” in the population at large. In medical practice, each patient is an “n of 1” research study in which the physician forms a hypothesis and then tests and reframes that hypothesis with each successive element of the work-up. Protocolization of care with “order sets” and macros may discourage consideration of the elements of the clinical picture that make each patient unique.9 As we succeed at eliminating “unwanted variation” in care, we run the risk of eliminating “wanted variation” in care that reflects variation in host and disease phenotypes. The ease with which one carries forward elements of the clinical picture by cutting and pasting into the record what has been written previously by others invites propagation of errors and repetitive inclusion of irrelevant or outdated information. This works against our trainees honing their skills at analyzing and prioritizing information.10 We are faced with electronic macros that obviate analytical thinking and downplay individualization of medical care. In the premacro medical care realm, errors occurred on a random, stochastic basis. The new electronic era breeds errors that result from patients being “nonstandard.” Instead of 1 error in 1000 that affects whoever is the object of that random event, we see 1 error in 10 000 aimed at those whose condition does not fit the standard for which the macro was designed. We live in communities with a rising median age, in a world where healthy, cognitively normal adults form the predominant population. To play only statistics in improving the error-free rate of health care delivery often means to fashion algorithms that ignore children, cognitivelyimpaired individuals, and those who metabolize drugs in unconventional ways.11 No matter what one thinks of the EMR and CPOE, they are doubtless here to stay. It seems society has made the decision that decreasing variation in practice, increasing reliable transmission of information, and enhancing access from anywhere to prior medical records take priority over ensuring that population outliers get the “off-center” care they need.
From the Departments of Pediatrics, Neurology, and Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, NY The author declares no conflicts of interest.
CPOE EMR
Computerized physician order entry Electronic medical record
0022-3476/$ - see front matter. ª 2016 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jpeds.2016.06.001
5
THE JOURNAL OF PEDIATRICS
www.jpeds.com
The response of pediatricians must be to fashion advantage from adversity. We must seize this opportunity to use the EMR and CPOE to accrue data that continually inform and improve our practice so that they work for us, instead of the other way around. The liability of rendering conventional care to decidedly unconventional patients mandates that algorithms developed for the EMR and CPOE include big box warnings and work-arounds for patients whose age, creatinine clearance, or liver function tests, for example, lie outside of the “average adult” range. Eventually, such black box warnings might pop up as reminders to consider the individual characteristics of a patient whose history includes words like Down syndrome, cerebral palsy, congenital heart disease, or certain birth defects. CPOE in most institutions now includes algorithms for weight-based dosing, and increasingly individualized algorithms should include age-based versions of weight-based dosing, as well.12,13 One proposed automatic generator of order sets iteratively “learns” from the individual user and the evidence base.13 Perhaps the EMRs and CPOE instruments of the future will learn across institutions, as well, and provide access to protocols developed elsewhere using an otherwise institution-specific EMR. This means that policy- and practice-determining committees in every hospital or clinic must include pediatricians whose job it is to ensure that their populations are wellserved by the decisions made. Protocolized care creates both the imperative and the opportunity for raising awareness and attention to the unique health needs and attributes of children and the opportunity for closer collaboration among providers of health care across the age and health spectra. How should we pediatricians combat the repetition of text from one note to the next in a patient’s EMR?3 It would seem that one could build antiplagiarism software that would look for repletion of prior material that is longer than so many contiguous words! Should we reconfigure the EMR to prioritize and highlight new findings and information that actually contributes to the care of the patient? As long as we live and work in a fee-for-service universe that incentivizes inclusion of more and lengthier elements in the written account of each patient encounter, we may be stuck with a problem. It is likely that population management with population-based compensation will go a long way toward ameliorating this
6
Volume 176 problem. And we would all be surprised if it did not create new problems of its own! n Reprint requests: Nina F. Schor, MD, PhD, Departments of Pediatrics, Neurology, and Neuroscience, University of Rochester School of Medicine and Dentistry, Golisano Children’s Hospital, 601 Elmwood Ave, Box 777, Rochester, NY 14642. E-mail: [email protected]
References 1. Graham HK. Relationships in consultation. Calif Med 1953;79:274-8. 2. McDonald CJ, Tierney WM. Computer-stored medical records. Their future role in medical practice. JAMA 1988;259:3433-40. 3. Gummadi S, Housri N, Zimmers TA, Koniaris LG. Electronic medical record: a balancing act of patient safety, privacy and health care delivery. Am J Med Sci 2014;348:238-43. 4. Handler JA, Feied CF, Coonan K, Vozenilek J, Gillam M, Peacock PR Jr, et al. Computerized physician order entry and online decision support. Acad Emerg Med 2004;11:1135-41. 5. Ruano M, Villama~ nan E, Perez E, Herrero A, Alvarez-Sala R. New technologies as a strategy to decrease medication errors: how do they affect adults and children differently? World J Pediatr 2016;12:28-34. 6. MacKay M, Anderson C, Boehme S, Cash J, Zobell J. Frequency and severity of parenteral nutrition medication errors at a large children’s hospital after implementation of electronic ordering and compounding. Nutr Clin Pract 2015;31:195-206. 7. McCrory MC, Strouse JJ, Takemoto CM, Easley RB. Computerized physician order entry improves compliance with a manual exchange transfusion protocol in the pediatric intensive care unit. J Pediatr Hematol Oncol 2014;36:143-7. 8. Carayon P, Wetterneck TB, Alyousef B, Brown RL, Cartmill RS, McGuire K, et al. Impact of electronic health record technology on the work and workflow of physicians in the intensive care unit. Int J Med Inform 2015;84:578-94. 9. Knight AM, Kravet SJ, Harper GM, Leff B. The effect of computerized provider order entry on medical student clerkship experiences. J Am Med Inform Assoc 2005;12:554-60. 10. Bowman S. Impact of electronic health record systems on information integrity: quality and safety implications. Perspect Health Inf Manag 2013;10:1c. 11. Saxena K, Lung BR, Becker JR. Improving patient safety by modifying provider ordering behavior using alerts (CDSS) in CPOE system. AMIA Annu Symp Proc 2011;2011:1207-16. 12. McAlearney AS, Chisolm D, Veneris S, Rich D, Kelleher K. Utilization of evidence-based computerized order sets in pediatrics. Int J Med Inform 2006;75:501-12. 13. Zhang Y, Padman R, Levin JE. Paving the COWpath: data-driven design of pediatric order sets. J Am Med Inform Assoc 2014;21:e304-11.
Schor