A clinical trial of a knowledge-based medical record.
To meet the needs of primary care physicians caring for patients with HIV infection, we developed a knowledge-based medical record to allow the on-line patient record to play an active role in the care process. These programs integrate the on-line patient record, rule-based decision support, and full-text information retrieval into a clinical workstation for the practicing clinician. To determine whether use of a knowledge-based medical record was associated with more rapid and complete adherence to practice guidelines and improved quality of care, we performed a controlled clinical trial among physicians and nurse practitioners caring for 349 patients infected with the human immuno-deficiency virus (HIV); 191 patients were treated by 65 physicians and nurse practitioners assigned to the intervention group, and 158 patients were treated by 61 physicians and nurse practitioners assigned to the control group. During the 18-month study period, the computer generated 303 alerts in the intervention group and 388 in the control group. The median response time of clinicians to these alerts was 11 days in the intervention group and 52 days in the control group (PJJ0.0001, log-rank test). During the study, the computer generated 432 primary care reminders for the intervention group and 360 reminders for the control group. The median response time of clinicians to these alerts was 114 days in the intervention group and more than 500 days in the control group (PJJ0.0001, log-rank test). Of the 191 patients in the intervention group, 67 (35%) had one or more hospitalizations, compared with 70 (44%) of the 158 patients in the control group (PJ=J0.04, Wilcoxon test stratified for initial CD4 count). There was no difference in survival between the intervention and control groups (P = 0.18, log-rank test). We conclude that our clinical workstation significantly changed physicians' behavior in terms of their response to alerts regarding primary care interventions and that these interventions have led to fewer patients with HIV infection being admitted to the hospital.
Safran
C
C
Department of Medicine, Beth Israel Hospital, Center for Clinical Computing, Harvard Medical School, Boston MA, USA.
Rind
D M
DM
Davis
R B
RB
Sands
D Z
DZ
Caraballo
E
E
Rippel
K
K
Wang
Q
Q
Rury
C
C
Makadon
H J
HJ
Cotton
D J
DJ
D017088:AIDS-Related Opportunistic Infections / Q000175:diagnosis / Q000517:prevention & control; D000328:Adult; D000998:Antiviral Agents / Q000008:administration & dosage; D001291:Attitude of Health Personnel; D018791:CD4 Lymphocyte Count; D003658:Decision Making, Computer-Assisted; D005103:Expert Systems; D015658:HIV Infections / Q000188:drug therapy* / Q000276:immunology / Q000401:mortality; D006751:Hospital Information Systems; D006801:Humans; D016347:Medical Records Systems, Computerized; D010820:Physicians; D017410:Practice Guidelines as Topic; D011787:Quality of Health Care; D017010:Reminder Systems; D018709:Statistics, Nonparametric; D015996:Survival Rate; D015215:Zidovudine / Q000008:administration & dosage
D000998:Antiviral Agents; D015215:Zidovudine