Clinical decision support system and incidence of delirium in cognitively impaired older adults transferred to intensive care

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Khan BA et al. did a study and the following review is based on that study named "Creating clinical decision support system(CDSS) and incidence of delirium in cognitively impaired older adults transferred to intensive care"[1]


More than 50% of hospitalized adults 65 years and older experience cognitive impairment during their hospital stay.[2] Compared with other patients, these patients are prone to falls,injuries,pressure ulcers,restraints,use of urinary catheters,and inadvertent exposure to agents with anticholinergic properties,all of which can lead to delirium[1],especially in the ICU[2].[3] [4] [5] [6] [7] Delirium in the ICU is an independent predictor of longer stays in the hospital and ICU,increasing healthcare costs and mortality rates.[8] [9]

The Institute of Medicine[3] has recommended integrating information systems into healthcare as a way to improve the safety and quality of care of older patients. Use of a CDSS can improve the process of care, lead to better patient outcomes, reduce medical errors and decrease healthcare costs.[10] [11] [12] The authors' tested the efficacy of a CDSS based intervention that consisted of alerting physicians to the presence of cognitive impairment,recommending early referral to a geriatrician, and suggesting discontinuation of the use of urinary catheters,physical restraints, and anticholinergic drugs in the large randomized Enhancing care for Hospitalized Older Adults with Cognitive Impairment(e-CHAMP trial) which is the first of this kind to study this.[13] The authors' hypothesized that patients randomized to the CDSS intervention would have more referrals to the in-patient geriatric service and reduced exposure to inappropriate anticholinergic medications,urinary catheters,and physical restraints,which in turn contributes to decrease delirium.


Study setting and patients

Patients, at least 65 years old and who speak English, were included in this study if they were transferred to the ICU services from a general medical care area of Wishard memorial hospital and were already enrolled in the e-CHAMP trial between July 1,2006 and March 30,2008. The ICU is 22-bedded with a nurse to patient ratio of 1 to 2 most times and 1 to 1 if necessary.

Procedures and data collection

Regenstrief Medical Record System(RMRS) and GOPHER Provider Order Entry(POE) were used.[14] Trained research personnel used the 10-item short portable mental status questionnaire[15] to determine each patient's cognitive status. Patients with a score of 8 or less on the questionnaire were considered to have cognitive impairment. Delirium was assessed by using Confusion Assessment Method(CAM)[16] at the time of enrollment and every weekday. Each patient's level of co-morbid conditions was assessed by using the validated Charlson Comorbidity Index.[17] With the help of these,eligible patients were automatically randomized in a 1 to 1 ratio to a CDSS intervention group or to usual care.


  • Each time a physician entered an order in GOPHER for a patient randomized to intervention group, the physician received non interruptive alerts of the presence of a cognitive impairment and related events.
  • If a physician ordered use of a urinary catheter,interruptive alerts recommending it's discontinuation were sent
  • If a physician ordered physical restraints,interruptive alerts suggesting that the restraints be replaced by the use of a professional sitter or low-dose trazodone
  • If a physician ordered any of the 18 anticholinergic agents,interruptive alerts suggesting that the drug be stopped,suggesting an alternate medication,or recommending dose modification
  • The physician was required to address the interruptive alert by accepting,rejecting ,or modify any of them.For non-interruptive alerts,the physician just have to use F8 button to exit the screen.[1]

Outcome measures

Measures of interest are orders for consultation with a geriatrician;discontinuation of the 18 potentially inappropriate anticholinergic drugs,urinary catheter,or physical restraints; and occurrence of delirium.[1]

Statistical analysis

A power analysis for 80% power and 2-sided alpha=0.05 disclosed that 242 patients would be needed to detect a 15% difference in the incidence of delirium between the intervention and the control groups.[1]


The study group consisted of 60 patients who were transferred to the ICU for at least one day. The mean age was 74.6 years,45% patients were afro-americans and 52% were women. The study found out that there are no differences between the intervention and control groups in the occurrence of physician orders for consultation with a geriatrician or discontinuation of orders for urinary catheters,physical restraints,and anticholinergic drugs. The 2 groups also did not differ in the incidence of delirium in the ICU,the mean length of hospital stay and survival rate 30 days after discharge.[1]


The authors' study indicate that using a CDSS to influence the behavior of healthcare providers(HCPs) in entering orders for patients with cognitive impairment neither increased orders for geriatric consultation nor decrease the use of urinary catheters,physical restraints,and anticholinergic agents as the use of these in a ICU setting is almost inevitable. The use of CDSS did not reduce the incidence of delirium among older patients with cognitive impairment and who were transferred to ICU.[1]

According to studies by Inouye et al.[18] and Marcantanio et al.,[19] multicomponent interventions have been more effective in preventing delirium but the authors' mutlicomponent proved otherwise. This is partly due to the fact that the authors' study included only 3 risk factors. Also, other pharmacological components such as the usage of sedative-hypnotics like Benzodiazepines, and pain control with Morphine also confabulate this further.[3] [9] [20]

Thus,the use of an intervention to decrease exposure to a greater number of risk factors might be more successful."Alert fatigue" was noted among physicians.Supplementing the CDSS alerts with a human element may be necessary to achieve compliance with the intervention.[1]


Use of a computer-based physicians' CDSS did not change providers practices in the ICU and did not decrease the incidence of delirium in cognitively impaired elderly patients. Future studies with interventions targeting multiple risk factors and using an advanced CDSS with integration of human intelligence may be required to establish this.[1]


I was of the opinion that properly formatted health IT technologies would certainly help improve health care outcomes. This study proved that technology alone would be insufficient,in this case by limiting the inclusion criteria to insufficient amounts would certainly not be useful in assessment of a health care dimension. A properly functional CDSS technology with associated human intelligence are vital for proper assessment of the relevant health care parameters,in this case to check if CDSS helps in reducing cognitive impairment in older adults in ICU and to check if incidence of delirium is reduced.


  1. 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 Khan BA et al. Creating clinical decision support system(CDSS) and incidence of delirium in cognitively impaired older adults transferred to intensive care.Am J Crit Care. 2013 May; 22(3): 257–262. doi: 10.4037/ajcc2013447. Retrieved from
  2. Harwood DM, Hope T, Jacoby R. Cognitive impairment in medical inpatients, I: screening for dementia—is history better than mental state? Age Ageing. 1997;26(1):31–35
  3. 3.0 3.1 Saravay SM, Kaplowitz M, Kurek J, et al. How do delirium and dementia increase length of stay of elderly general medical inpatients? Psychosomatics. 2004;45(3):235–242
  4. Marcantonio ER, Goldman L, Mangione CM, et al. A clinical prediction rule for delirium after elective noncardiac surgery. JAMA. 1994;271(2):134–139
  5. Marcantonio ER, Juarez G, Goldman L, et al. The relationship of postoperative delirium with psychoactive medications. JAMA. 1994;272:1518–1522
  6. Fick DM, Waller JL, Maclean JR, et al. Potentially inappropriate medication use in a Medicare managed care population: association with higher costs and utilization. J Manage Care Pharm. 2001;7(5):407–413
  7. Campbell N, Boustani M, Limbil T, et al. The cognitive impact of anticholinergics: a clinical review. Clin Interv Aging. 2009;4:225–233
  8. Ely EW, Shintani A, Truman B, et al. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA. 2004;291(14):1753–1762
  9. 9.0 9.1 Ouimet S, Kavanagh BP, Gottfried SB, Skrobik Y. Incidence, risk factors and consequences of ICU delirium. Intensive Care Med. 2007;33(1):66–73
  10. Chaudhry B, Wang J, Wu S, et al. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742–752
  11. Osheroff JA, Teich JM, Middleton B, Steen EB, Wright A, Detmer DE. A road map for national action on clinical decision support [published correction appears in J Am Med Inform Assoc. 2007;14(3)389] J Am Med Inform Assoc. 2007;14(2):141–145
  12. McDonald CJ, Hui SL, Smith DM, et al. Reminders to physicians from an introspective computer medical record: a two-year randomized trial. Ann Intern Med. 1984;100:130–138
  13. Boustani MA, Campbell NL, Khan BA. Enhancing care for hospitalized older adults with cognitive impairment: a randomized controlled trial. J Gen Intern Med. 2012;27(5):561–567
  14. McDonald CJ, Overhage JM, Tierney WM, et al. The Regenstrief Medical Record System: a quarter century experience. Int J Med Inform. 1999;54:225–253
  15. Erkinjuntti T, Sulkava R, Wikstrom J, Autio L. Short Portable Mental Status Questionnaire as a screening test for dementia and delirium among the elderly. J Am Geriatr Soc. 1987;35:412–416
  16. Inouye SK, van Dyck CH, Alessi CA, Balkin S, Siegal AP, Horwitz RI. Clarifying confusion: the Confusion Assessment Method. A new method for detection of delirium. Ann Intern Med. 1990;113(12):941–948
  17. Charlson ME, Sax FL, MacKenzie CR, Fields SD, Braham RL, Douglas RG Jr. Assessing illness severity: does clinical judgment work? J Chronic Dis. 1986;39(6):439–452
  18. Inouye SK, Bogardus ST, Jr, Charpentier PA, et al. A multi-component intervention to prevent delirium in hospitalized older patients. N Engl J Med. 1999;340(9):669–676
  19. Marcantonio ER, Flacker JM, Wright RJ, et al. Reducing delirium after hip fracture: a randomized trial. J Am Geriatr Soc. 2001;49(5):516–522
  20. Pandharipande P, Shintani A, Peterson J, et al. Lorazepam is an independent risk factor for transitioning to delirium in intensive care unit patients. Anesthesiology. 2006;104:21–26