A Randomized Controlled Trial of a Computer-based Physician Workstation in an Outpatient Setting: Implementation Barriers to Outcome Evaluation

Rotman, Barry L.; Sullivan, Andrea; McDonald, Thomas W.; Brown, Byron W.; DeSmedt, P; Goodnature, Don; Higgins, Michael C.; Suermondt, Henri J.; Young, Charles Y.F.; Owens, Douglas K

doi:10.1136/jamia.1996.97035025

Cited by 48 publications

(31 citation statements)

References 8 publications

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“…Twenty-four RCTs [60-62,65-67,69,71-76,78,80-89] had been included in the previous version of our review [2]. Study authors confirmed or supplemented our data extraction for 53 of 65 included studies (82%) [16-20,23,25-33,35-39,42-45,47-49,53-55,57,58,60-62,65-72,74-76,78,81,83-86,88]. Forty-seven included studies contribute outcomes to this review as well as other CCDSS interventions in the series; four studies [49,56,76,80] to four reviews, 16 studies [16,19,21,28,40,44,45,53,55,59,62,64,68,69,74,77-79,82,85,89] to three reviews, and 27 studies [20,22,23,26,27,29,31,32,34,35,39,41-43,46-48,50,52,54,60,63,66,70,72,75,81,86-88] to two reviews; but we focused here on drug prescribing-relevant outcomes.…”

Section: Resultsmentioning

confidence: 96%

Computerized clinical decision support systems for drug prescribing and management: A decision-maker-researcher partnership systematic review

et al. 2011

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BackgroundComputerized clinical decision support systems (CCDSSs) for drug therapy management are designed to promote safe and effective medication use. Evidence documenting the effectiveness of CCDSSs for improving drug therapy is necessary for informed adoption decisions. The objective of this review was to systematically review randomized controlled trials assessing the effects of CCDSSs for drug therapy management on process of care and patient outcomes. We also sought to identify system and study characteristics that predicted benefit.MethodsWe conducted a decision-maker-researcher partnership systematic review. We updated our earlier reviews (1998, 2005) by searching MEDLINE, EMBASE, EBM Reviews, Inspec, and other databases, and consulting reference lists through January 2010. Authors of 82% of included studies confirmed or supplemented extracted data. We included only randomized controlled trials that evaluated the effect on process of care or patient outcomes of a CCDSS for drug therapy management compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive.ResultsSixty-five studies met our inclusion criteria, including 41 new studies since our previous review. Methodological quality was generally high and unchanged with time. CCDSSs improved process of care performance in 37 of the 59 studies assessing this type of outcome (64%, 57% of all studies). Twenty-nine trials assessed patient outcomes, of which six trials (21%, 9% of all trials) reported improvements.ConclusionsCCDSSs inconsistently improved process of care measures and seldomly improved patient outcomes. Lack of clear patient benefit and lack of data on harms and costs preclude a recommendation to adopt CCDSSs for drug therapy management.

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Section: Resultsmentioning

confidence: 96%

Computerized clinical decision support systems for drug prescribing and management: A decision-maker-researcher partnership systematic review

et al. 2011

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“…40 [1990-99, ambulatory care] Technical problems (15) "The slow speed makes [me] 'uneasy': kind of high stress just sitting there waiting for stuff to come up." 60 (7) "…59% said that they would find the prescribing support useful if it was integrated with their practice computer…" 72 [1990-99, ambulatory care] "…expressed the frustration that different software systems are difficult to integrate." 53 (7) "…nurses and providers displayed substantial confusion regarding delegation of responsibility for satisfying CRs (removing them from the due list)."…”

Section: Provider-related Factors (Table 4)mentioning

confidence: 99%

Computerized clinical decision support for prescribing: provision does not guarantee uptake

Moxey

Robertson

Newby

et al. 2010

Journal of the American Medical Informatics Association

257

244

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There is wide variability in the use and adoption of recommendations generated by computerized clinical decision support systems (CDSSs) despite the benefits they may bring to clinical practice. We conducted a systematic review to explore the barriers to, and facilitators of, CDSS uptake by physicians to guide prescribing decisions. We identified 58 studies by searching electronic databases (1990-2007). Factors impacting on CDSS use included: the availability of hardware, technical support and training; integration of the system into workflows; and the relevance and timeliness of the clinical messages. Further, systems that were endorsed by colleagues, minimized perceived threats to professional autonomy, and did not compromise doctor-patient interactions were accepted by users. Despite advances in technology and CDSS sophistication, most factors were consistently reported over time and across ambulatory and institutional settings. Such factors must be addressed when deploying CDSSs so that improvements in uptake, practice and patient outcomes may be achieved.

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“…Similarly, automated clinical care protocols have been used in England (Herbert et al, 1995) and The Netherlands (Vissers et al, 1996a, b). The clinical practice setting has yet to incorporate the computer as a tool for clinical decisionmaking (Flanagan et al, 1995;Ireland, 1996;Rotman et al, 1996). Problems remain in existing software that deter physician acceptance, including physician downtime for data entry (Hammer et al, 1995), nonstandardized codes for clinician and computer interfacing (Johnson, 1996), perceived problems of maintaining patient and provider confidentiality (Immonen, 1996), protection of records integrity from data hackers (Von Solms, 1996), lack of portability of computer modules (Werner et al, 1995), and poorly designed workstations (Dayhoff et al, 1994).…”

Section: Commentmentioning

confidence: 99%

Maximizing the Adequacy of Medication Treatment in Controlled Trials and Clinical Practice: STAR*D Measurement-Based Care

Trivedi

Rush

Gaynes

et al. 2007

Neuropsychopharmacol

142

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The success of well-developed protocols has been limited in real-world practice, where even effective strategies have not been sufficient to meet patient needs in routine clinical care owing to Axis I and III comorbidities. The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial required that antidepressant medication treatment be optimal regarding dose and duration, yet accommodate flexibility to ensure safety given the wide range of comorbid general medical and psychiatric disorders allowed in the trial. The objective of this study was to develop a measurement-based care (MBC) approach and an automated feedback system to ensure adequate and safe antidepressant treatment delivery suitable for both clinical research and routine practice. Ratings of depressive symptom severity and side-effect frequency, intensity, and burden were obtained at each treatment visit using the MBC system that (1) guided medication dose adjustments and treatment duration, (2) documented clinician adherence to treatment recommendations, and (3) provided prompt feedback to clinicians to enhance appropriate treatment decisions. Physician adherence to protocol-specific treatment was monitored based on measured symptoms and side-effect burden, and dose and duration of antidepressant at each critical decision point during the acute phase treatment of major depression. Feedback was provided at the point of care by the clinical coordinators, assisted by Web-based reports following each treatment visit. On the basis of the first treatment step with citalopram, over 85% of treatment encounters had appropriate fidelity to recommendations. Most deviations from treatment recommendations occurred late in treatment and were often justifiable. MBC proved to be feasible and effective in busy primary and psychiatric settings. This approach signals a paradigm shift toward the use of measurement-based clinical decisions, both at the point of care and following each visit, to deliver optimal pharmacotherapy for depression.

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A Randomized Controlled Trial of a Computer-based Physician Workstation in an Outpatient Setting: Implementation Barriers to Outcome Evaluation

Cited by 48 publications

References 8 publications

Computerized clinical decision support systems for drug prescribing and management: A decision-maker-researcher partnership systematic review

Computerized clinical decision support systems for drug prescribing and management: A decision-maker-researcher partnership systematic review

Computerized clinical decision support for prescribing: provision does not guarantee uptake

Maximizing the Adequacy of Medication Treatment in Controlled Trials and Clinical Practice: STAR*D Measurement-Based Care

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