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Original Research |

IMPROVING PATIENT CARE

Efficacy of a Clinical Decision-Support System in an HIV Practice: A Randomized Trial

Gregory K. Robbins, MD, MPH; William Lester, MD; Kristin L. Johnson, MPH; Yuchiao Chang, PhD; Gregory Estey, EdM; Dominic Surrao, MS; Kimon Zachary, MD; Sara M. Lammert, BA; Henry C. Chueh, MD, MS; James B. Meigs, MD, MPH; and Kenneth A. Freedberg, MD, MSc
[+] Article and Author Information

From Massachusetts General Hospital, Harvard University Center for AIDS Research, and Harvard Medical School, Boston, Massachusetts.

Acknowledgment: The authors thank the patients and staff of the Massachusetts General Hospital HIV Clinic.

Grant Support: By the National Institute of Allergy and Infectious Diseases (K01AI062435, K24AI062476, P30AI42851, K24DK080140, and R37AI42006) and the Massachusetts General Hospital Clinical Research Program.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-0054.

Reproducible Research Statement: Study protocol, statistical code, and data set: Available from Dr. Robbins (e-mail, grobbins@partners.org).

Requests for Single Reprints: Gregory K. Robbins, MD, MPH, Massachusetts General Hospital, Division of Infectious Diseases, 55 Fruit Street, Cox 5, Boston, MA 02114; e-mail, grobbins@partners.org.

Current Author Addresses: Dr. Robbins: Massachusetts General Hospital, Division of Infectious Diseases, 55 Fruit Street, Cox 5, Boston, MA 02114.

Drs. Lester and Chueh, Mr. Estey, and Mr. Surrao: Massachusetts General Hospital, Laboratory of Computer Science, 50 Staniford Street, 7th Floor, Boston, MA 02114.

Ms. Johnson: Massachusetts General Hospital, 55 Fruit Street, Cox 5, Boston, MA 02114.

Drs. Chang, Meigs, and Freedberg: Massachusetts General Hospital, Division of General Internal Medicine, 50 Staniford Street, 9th Floor, Boston, MA 02114.

Dr. Zachary and Ms. Lammert: Infectious Disease Associates, Massachusetts General Hospital, 55 Fruit Street, Cox 5, Boston, MA 02114.

Author Contributions: Conception and design: G.K. Robbins, W. Lester, K.L. Johnson, G. Estey, H.C. Chueh, J.B. Meigs, K.A. Freedberg.

Analysis and interpretation of the data: G.K. Robbins, K.L. Johnson, Y. Chang, S.M. Lammert, J.B. Meigs, K.A. Freedberg.

Drafting of the article: G.K. Robbins, W. Lester, K.L. Johnson, G. Estey, H.C. Chueh.

Critical revision of the article for important intellectual content: G.K. Robbins, W. Lester, K.L. Johnson, K. Zachary, S.M. Lammert, J.B. Meigs, K.A. Freedberg.

Final approval of the article: G.K. Robbins, W. Lester, K.L. Johnson, Y. Chang, H.C. Chueh, J.B. Meigs, K.A. Freedberg.

Provision of study materials or patients: G.K. Robbins, K. Zachary, K.A. Freedberg.

Statistical expertise: K.L. Johnson, Y. Chang.

Obtaining of funding: G.K. Robbins, J.B. Meigs, K.A. Freedberg.

Administrative, technical, or logistic support: W. Lester, G. Estey, D. Surrao, S.M. Lammert, H.C. Chueh, J.B. Meigs.

Collection and assembly of data: G.K. Robbins, K.L. Johnson, D. Surrao, S.M. Lammert.


Ann Intern Med. 2012;157(11):757-766. doi:10.7326/0003-4819-157-11-201212040-00003
Text Size: A A A

Background: Data to support improved patient outcomes from clinical decision-support systems (CDSSs) are lacking in HIV care.

Objective: To test the efficacy of a CDSS in improving HIV outcomes in an outpatient clinic.

Design: Randomized, controlled trial. (ClinicalTrials.gov registration number: NCT00678600)

Setting: Massachusetts General Hospital HIV Clinic.

Participants: HIV care providers and their patients.

Intervention: Computer alerts were generated for virologic failure (HIV RNA level >400 copies/mL after a previous HIV RNA level ≤400 copies/mL), evidence of suboptimal follow-up, and 11 abnormal laboratory test results. Providers received interactive computer alerts, facilitating appointment rescheduling and repeated laboratory testing, for half of their patients and static alerts for the other half.

Measurements: The primary end point was change in CD4 cell count. Other end points included time to clinical event, 6-month suboptimal follow-up, and severe laboratory toxicity.

Results: Thirty-three HIV care providers followed 1011 patients with HIV. In the intervention group, the mean increase in CD4 cell count was greater (0.0053 vs. 0.0032 × 109 cells/L per month; difference, 0.0021 × 109 cells/L per month [95% CI, 0.0001 to 0.004]; P = 0.040) and the rate of 6-month suboptimal follow-up was lower (20.6 vs. 30.1 events per 100 patient-years; P = 0.022) than those in the control group. Median time to next scheduled appointment was shorter in the intervention group than in the control group after a suboptimal follow-up alert (1.71 vs. 3.48 months; P < 0.001) and after a toxicity alert (2.79 vs. >6 months; P = 0.072). More than 90% of providers supported adopting the CDSS as part of standard care.

Limitation: This was a 1-year informatics study conducted at a single hospital subspecialty clinic.

Conclusion: A CDSS using interactive provider alerts improved CD4 cell counts and clinic follow-up for patients with HIV. Wider implementation of such systems can provide important clinical benefits.

Primary Funding Source: National Institute of Allergy and Infectious Diseases.

Figures

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Figure 1.

Flow diagram of interactive and static computer alerts.

EMR = electronic medical record; SOF = suboptimal follow-up; TOX = toxicity; VF = virologic failure.

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Figure 2.

Study flow diagram.

The electronic medical record tracks patient case status as active or inactive (loss to follow-up, transferred medical care, or deceased). The patients of participating providers were randomly assigned to the interactive alert intervention group or to the static alert control group. There was no statistical difference in mortality or loss to follow-up, but more patients transferred medical care (“left practice”) during the study in the intervention group than in the control group (1.2% vs. 5.1% of patients; P < 0.001).

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Figure 3.

Mean change in CD4 cell count per month, by providers with evaluable patients in both groups.

* To convert cells/mm3 to ×109 cells/L, multiply by 10−3.

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Figure 4.

Kaplan–Meier analysis of time to next scheduled appointment after the first SOF and TOX alerts.

SOF = suboptimal follow-up; TOX = toxicity.

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