Efficacy of a Clinical Decision-Support System in an HIV Practice

Abstract

Background Data to support improved patient outcomes from clinical decision support systems (CDSS) are lacking in HIV care. Objective To conduct a randomized controlled trial testing the efficacy of a CDSS to improve HIV outcomes in an outpatient clinic. Design We conducted a randomized controlled trial where half of each provider’s patients were randomized to interactive or static computer alerts (ClinicalTrials.gov #NCT00678600). Setting The study was conducted at the Massachusetts General Hospital HIV Clinic. Subjects Participants were HIV providers and their HIV-infected patients. Intervention Computer alerts were generated for virologic failure (HIV RNA >400 c/mL after HIV RNA ≤400 c/mL), evidence of suboptimal follow-up, and 11 abnormal laboratory tests. Providers received interactive computer alerts, facilitating appointment rescheduling and repeat laboratory testing, for half of their patients and static alerts for the other half. Measurements The primary endpoint was change in CD4 count. Other endpoints included time-to-clinical event, 6-month suboptimal follow-up, and severe laboratory toxicity. Results Thirty-three HIV providers followed 1,011 HIV-infected patients. For the intervention arm, the mean CD4 count increase was greater (5.3 versus 3.2 cells/mm3/month; difference = 2.0 cells/mm3/month 95% CI [0.1, 4.0], p=0.040) and the rate of 6-month suboptimal follow-up was lower (20.6 versus 30.1 events per 100 patient-years, p=0.022). Median time-to-next scheduled appointment was shorter in the intervention arm after a suboptimal follow-up alert (1.71 versus 3.48 months; p<0.001) and after a toxicity alert (2.79 versus >6 months for control); p=0.072). Ninety-six percent of providers supported adopting the CDSS as part of standard care. Limitations This was a one-year informatics study conducted at a single hospital sub-specialty clinic. Conclusion A CDSS using interactive provider alerts improved CD4 counts and clinic follow-up for HIV-infected patients. Wider implementation of such systems can provide important clinical benefits.

Re-engagement in HIV Care: A Clinical and Public Health Priority

“…These patients were compared to those who simply had anomalies placed in their electronic charts. Suboptimal follow up was reduced from 30% to 20% by using real time informing of the clinician so that patients could be immediately contacted [20]. What seems to be the most important intervention that prevents leaving care is regular contact with the patient, including prior to appointments and follow up after missed appointments.…”

A Rapid Review of eHealth Interventions Addressing the Continuum of HIV Care (2007–2017)

“…Both Perera et al [61] and Kalichman et al [33] demonstrated evidence of efficacy for using eHealth applications to improve HIV medication adherence. This analysis included several studies [48, 52, 58, 61–65] not specifically referenced in this section.…”

The Effects of Computerized Clinical Decision Support Systems on Laboratory Test Ordering: A Systematic Review

“…No study reporting clinical events as an outcome for the evaluation of a CCDSS focused on test ordering for anticoagulation therapy showed a significant effect, including a large multicenter trial conducted by Poller et al 46,47 Although we were unable to pool the results for TTR, only a minority of studies reporting this outcome showed a significant effect. When implemented for the follow-up of HIV testing, Robbins et al 36 found that CCDSSs had a significant effect on improving CD4 cell count. Overall, CCDSSs aimed at improving laboratory test ordering behavior seem to have little or no effect on clinical outcomes.…”

“…23,[38][39][40][41][42][43][44][45] One study (4%) was conducted in Europe and Australia. 46,47 Thirteen studies (57%) evaluated CCDSSs in primary care,* 5 (22%) in hospital outpatient ambulatory care, 26,31,33,36,44 and 5 (22%) in hospital inpatient care. 22,25,32,34 Intervention.-Fifteen different CCDSSs were studied, of which 6 (40%) were focused solely on laboratory testing, † 5 (33%) also included other reminders such as treatment options, [27][28][29]31,39,[41][42][43] and 4 (27%) were not stand-alone systems, but were developed by an EHR software vendor.…”

“…[20][21][22][24][25][26][27][28][29][30][31][32][33][34][35][36][37] Eight studies (35%) were conducted in Europe. 23,[38][39][40][41][42][43][44][45] One study (4%) was conducted in Europe and Australia.…”