Artigo Acesso aberto Revisado por pares

Computerized Decision Support for the Cardiovascular Clinician

2009; Lippincott Williams & Wilkins; Volume: 120; Issue: 12 Linguagem: Inglês

10.1161/circulationaha.109.884031

ISSN

1524-4539

Autores

Gregory Piazza, Samuel Z. Goldhaber,

Tópico(s)

Machine Learning in Healthcare

Resumo

HomeCirculationVol. 120, No. 12Computerized Decision Support for the Cardiovascular Clinician Free AccessReview ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessReview ArticlePDF/EPUBComputerized Decision Support for the Cardiovascular ClinicianApplications for Venous Thromboembolism Prevention and Beyond Gregory Piazza and Samuel Z. Goldhaber Gregory PiazzaGregory Piazza From the Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass. and Samuel Z. GoldhaberSamuel Z. Goldhaber From the Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Mass. Originally published22 Sep 2009https://doi.org/10.1161/CIRCULATIONAHA.109.884031Circulation. 2009;120:1133–1137is corrected byCorrectionCase presentation: A 76-year-old woman with coronary artery disease, left ventricular systolic dysfunction (ejection fraction 30%), obesity, and a history of deep vein thrombosis presents with dyspnea and hypoxemia. The combination of physical examination findings of an S3 heart sound, rales in the lower half of both lung fields, and peripheral edema; chest radiograph evidence of cardiomegaly and pulmonary edema; and a pro-brain natriuretic peptide level of 2150 pg/mL (normal <350 pg/mL) confirms the diagnosis of decompensated heart failure. She is admitted to the cardiology service for diuretic therapy and optimization of her heart failure regimen. Although bed rest is included in her written admission orders, the orders do not include venous thromboembolism (VTE) prophylaxis. While entering the orders into the online medical record and provider order-entry program, the medical house officer caring for the patient receives an electronic alert identifying the patient as high-risk for VTE and recommending that she be prescribed prophylaxis.OverviewComputerized decision support systems are finding an increasing number of applications in both the hospital and ambulatory care settings owing to continuing advances in medical informatics technology. A strong foundation in evidence-based medicine and well-established clinical guidelines make the practice of cardiovascular medicine ideally suited to capitalize on the benefits of computerized decision support systems. Computerized decision support strategies have already been implemented successfully in several areas of cardiovascular care, including VTE prevention,1–3 pulmonary embolism risk stratification,4 dyslipidemia screening and treatment,5 and anticoagulation management.6Although most clinicians believe that the use of medical informatics technology, including computerized decision support, should lead to safer, more efficient, and higher-quality care, only a small proportion of US medical centers have adopted such systems.7 Commonly cited barriers to implementation of computerized decision support include the capital investment necessary to purchase medical informatics technology and the resources and dedicated staff required to maintain such systems.7,8 Lack of cultural acceptance of medical informatics technology, limited standardization, and uncertainty of the benefits of computerized decision support represent additional barriers.8,9Proven benefits of computerized decision support include improved patient safety, better disease-specific outcomes, and reductions in healthcare costs. Computerized decision support improves patient safety by reducing medical errors, alerting providers to abnormal test results, and suggesting prophylactic interventions such as VTE prophylaxis.9,10 These systems have also improved outcomes for patients with myocardial infarction, heart failure, and coronary artery disease that requires bypass graft surgery.11 Hospital costs for patients with these disorders are reduced when computerized decision support systems are used.11 Mechanisms for improvement include facilitation of communication between providers, increased access to practice guidelines and reference information, assistance with calculations, performance of real-time safety checks, monitoring of adherence to patient care standards, and tracking of adverse events.9Electronic Alerts for VTE PreventionPatients with cardiovascular disease, especially those with heart failure, are particularly vulnerable to the development of deep vein thrombosis and pulmonary embolism as a result of hospitalization.12,13 Despite published guidelines for the prevention of VTE,14,15 underutilization of prophylaxis in hospitalized medical patients remains a problem in the United States,16 Canada,17 and worldwide.18 At Brigham and Women's Hospital, we undertook a quality improvement initiative to evaluate the effect of an alert-based computerized decision support strategy on prophylaxis use and the subsequent 90-day incidence of symptomatic VTE in high-risk hospitalized patients.2First, we designed a computer program linked to our online medical record and provider order-entry program to identify consecutive hospitalized patients who were at high risk for VTE and for whom prophylaxis was not ordered. The computer program used a weighted scoring system of 8 common VTE risk factors to identify and enroll 2506 eligible high-risk patients for whom an order had not been written for prophylactic measures. They were randomized to an intervention group, for which the responsible physician received an electronic alert on the risk of VTE and recommendation for prophylaxis, or to a control group, for which no alert was issued. Each physician who received an electronic alert was required to acknowledge the notification and could then continue to withhold prophylaxis or, on the same computer screen, order pharmacological or mechanical prophylaxis. The computer alert screen was also linked to the hospital's online Venous Thromboembolism Guidebook, which provided prophylactic regimens for various indications according to published guidelines.19 Patients were followed up for 90 days to determine the incident rate of symptomatic VTE.Electronic alerts more than doubled the rate of VTE prophylaxis orders (33.5% versus 14.5%, P<0.0001) compared with the control group. The risk of symptomatic VTE was reduced by 41% (hazard ratio 0.59, 95% confidence interval 0.43 to 0.81, P=0.001) among patients for whom an electronic alert was issued. No significant differences in mortality or rates of major or minor bleeding were observed between the 2 groups.Although this trial demonstrated the potential power of alert-based computerized decision support systems, these strategies have some important limitations. One particular concern is that the alert might lose efficacy over time, a process known as alert fatigue. At the conclusion of the trial, we discontinued randomization and issued alerts for all patients in a cohort that was at high risk for VTE and for whom prophylaxis was not ordered.20 Compared with the previous randomized controlled trial, electronic alerts maintained efficacy over time and resulted in a similar increase in VTE prophylaxis utilization.20 In another trial of electronic alerts for the prevention of VTE in hospitalized patients, the reduction of VTE events was maintained over time.1Another potential limitation of computerized decision support for disease prevention is that computer algorithms for risk-scoring systems may not capture all factors that increase an individual's risk and therefore may fail to identify at-risk patients. An analysis of a validated VTE risk-scoring system suggested that the integration of additional risk factors would improve sensitivity for patients at the lower end of the risk scale.21 Computerized decision support systems may facilitate more complicated risk-scoring systems because they are ideally suited to perform complex risk calculations that incorporate and weigh numerous risk factors.An additional concern is that electronic alerts may be easy to ignore and that a "human" alerting system may be a more effective form of decision support. We recently designed and conducted a randomized controlled trial of 2493 patients at high risk for VTE but not receiving prophylaxis to evaluate a decision support strategy that used a human rather than an electronic alerting system for the prevention of VTE in hospitalized patients.22 The alert consisted of a direct page from a hospital staff member to the attending physician. The hospital staff member advised the attending physician to prescribe VTE prophylaxis for these high-risk patients. The primary end point was reduction in symptomatic VTE within 90 days of randomization. Although the human alert more than doubled the rate of VTE prophylaxis compared with controls (46.0% versus 20.6%, P<0.0001), the 21% reduction in symptomatic VTE (2.7% versus 3.4%; hazard ratio 0.79, 95% confidence interval 0.50 to 1.25) did not achieve statistical significance and was less than that observed in our previous trial of electronic alerts. Although there was no head-to-head comparison between the 2 alerting modalities, we believe that a computer alerting system is inherently more effective. An electronic alerting system may be more difficult to ignore because the alert occurs at the point of care and forces the clinician to acknowledge the alert before continuing to use the computer.Many of these limitations can be overcome by adapting the computerized decision support strategy to meet the specific clinical need. Various schemas for alert-based decision support for VTE prevention in hospitalized patients can be used to maximize efficacy (Figure). For example, a serial-screen alerting system that forces the provider to explain why prophylactic measures are being omitted and then provides default, or "opt-out," options for VTE prophylaxis may encourage the clinician to reconsider the patient's risk or follow links to reference materials, such as the American College of Chest Physicians practice guidelines for VTE prevention.14Download figureDownload PowerPointFigure. Flow diagram for alert-based computerized decision support strategies for VTE prevention in hospitalized patients.Other Applications in Cardiovascular MedicineComputerized decision support systems have the potential to complement quality improvement initiatives in cardiovascular medicine, such as the American Heart Association's "Get With the Guidelines" program, as well as the goals of the Joint Commission. A wide variety of common cardiovascular conditions could benefit from the application of computerized decision support strategies (Table 1). With a growing population requiring anticoagulation and limited resources to meet this demand, outpatient anticoagulant management may be one of the first areas of cardiovascular care in which computerized decision support systems become critical. Table 1. Potential Applications of Computerized Decision Support Systems in Cardiovascular MedicineAnticoagulation management, including dosing nomogramsManagement of atrial fibrillationStroke managementScreening and treatment of dyslipidemiaPrimary and secondary prevention of coronary artery diseaseRisk stratification and management of acute coronary syndromesRisk stratification for sudden cardiac death after myocardial infarctionVTE prophylaxisRisk stratification of acute pulmonary embolismManagement of heart failure, including cardiac resynchronization therapy and implantable cardiac defibrillator placementA recent 5-year, multicenter, randomized, controlled trial compared the use of a commercial computer-assisted oral anticoagulation dosage program with standard medical staff dosing for the management of 2631 patients across the European Union.6 Primary end points were the relative incidence of clinical bleeding or thrombotic events and time in the target international normalized ratio range. Although the incidence of clinical bleeding or thrombotic events was similar, the time-in-target range improved modestly in the group managed by the computer-assisted dosage program compared with standard care (66.8% versus 63.4%). After adjustment for age, gender, and international normalized ratio, the improvement in the time-in-target range was significant (difference of 3.5%, 95% confidence interval 2.3% to 4.9%, P<0.001).The study also demonstrated an important limitation of computer-assisted anticoagulant dosing. Although the computer program failed to provide a dose on only 5.7% of occasions, medical staff chose to override the suggested dose one third of the time.6 This observation indicates that current computer-assisted warfarin dosing programs may require the backup of experienced clinicians.23 Perhaps with refined dosing algorithms that incorporate warfarin pharmacogenomics,24,25 such computer programs may offer more reliable dosing and help improve patient safety.Current computerized decision support tools for anticoagulant management range from commercial software systems to free Internet-based dosing programs, such as WarfarinDosing.org.26 WarfarinDosing.org takes into account clinical factors such as age, gender, ethnicity, target international normalized ratio, and coadministered medications in addition to warfarin pharmacogenomic data, if available, to provide initiation and maintenance doses.26 The Web site also offers additional decision support tools, including reference materials, patient education resources, and a clinical prediction rule for major bleeding.26Implementation of Computerized Decision SupportClinical trials that focused on the use of computerized decision support as part of quality improvement initiatives have demonstrated several critical requirements for successful implementation (Table 2). First, computerized decision support technology must be integrated as part of a larger quality improvement effort and linked to an incentive system.7,8 Furthermore, a cultural shift toward greater acceptance and incorporation of medical informatics technology is required to encourage consistent use of decision support tools.27 Computerized decision support systems should be integrated into daily workflow and coupled with provider order-entry software.28 Computerized decision support strategies should be limited to key decisions, provide simple messages to avoid alert fatigue, and offer recommendations in addition to assessments.28,29 Alert-based, or automatic, decision support systems are more successful than on-demand, or user-initiated, systems.5,30 Finally, successful implementation of computerized decision support systems should be measured by clinical outcomes, not simply by provider behavior.29Table 2. Keys to Successful Implementation of Computerized Decision Support in the Care of Cardiovascular PatientsIntegrate support into quality improvement and link to an incentive systemFoster a cultural shift toward greater acceptance of medical informatics technologyIntegrate support into daily workflow and couple with provider order entry softwareLimit support to key decisions to avoid alert fatigueOffer recommendations in addition to assessmentsUse alert-based, or automatic, decision support systems rather than on-demand, or user-initiated, systemsMeasure both clinical outcomes and provider behaviorCase presentation: As a result of the electronic alert, the house officer reviewed the online educational material regarding options for VTE prophylaxis and ordered enoxaparin 40 mg SC once daily. The patient was treated successfully for decompensated heart failure and was discharged home after a 4-day hospitalization. During the 90 days of follow-up, she did not experience deep vein thrombosis or pulmonary embolism.This case presentation highlights the benefit of computerized decision support in the routine care of the cardiovascular medicine patient. Computerized decision support strategies have applications in the prevention, diagnosis, and management of common cardiovascular disorders and offer the promise of improved patient safety, better outcomes, and reduced healthcare costs.DisclosuresDr Goldhaber holds a patent for an alert-based computerized decision support program. Dr Piazza reports no conflicts.FootnotesCorrespondence to Gregory Piazza, MD, Cardiovascular Division, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115. E-mail [email protected] References 1 Lecumberri R, Marques M, Diaz-Navarlaz MT, Panizo E, Toledo J, Garcia-Mouriz A, Paramo JA. Maintained effectiveness of an electronic alert system to prevent venous thromboembolism among hospitalized patients. Thromb Haemost. 2008; 100: 699–704.CrossrefMedlineGoogle Scholar2 Kucher N, Koo S, Quiroz R, Cooper JM, Paterno MD, Soukonnikov B, Goldhaber SZ. Electronic alerts to prevent venous thromboembolism among hospitalized patients. N Engl J Med. 2005; 352: 969–977.CrossrefMedlineGoogle Scholar3 Durieux P, Nizard R, Ravaud P, Mounier N, Lepage E. A clinical decision support system for prevention of venous thromboembolism: effect on physician behavior. JAMA. 2000; 283: 2816–2821.CrossrefMedlineGoogle Scholar4 Donze J, Le Gal G, Fine MJ, Roy PM, Sanchez O, Verschuren F, Cornuz J, Meyer G, Perrier A, Righini M, Aujesky D. Prospective validation of the Pulmonary Embolism Severity Index: a clinical prognostic model for pulmonary embolism. Thromb Haemost. 2008; 100: 943–948.CrossrefMedlineGoogle Scholar5 van Wyk JT, van Wijk MA, Sturkenboom MC, Mosseveld M, Moorman PW, van der Lei J. 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Thromb Res. 2007; 119: 145–155.CrossrefMedlineGoogle Scholar18 Cohen AT, Tapson VF, Bergmann JF, Goldhaber SZ, Kakkar AK, Deslandes B, Huang W, Zayaruzny M, Emery L, Anderson FA Jr. Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross-sectional study. Lancet. 2008; 371: 387–394.CrossrefMedlineGoogle Scholar19 Piazza G, Goldhaber SZ. Venous Thromboembolism Guidebook, Fifth Edition. Crit Pathw Cardiol. 2006; 5: 211–227.CrossrefMedlineGoogle Scholar20 Baroletti S, Munz K, Sonis J, Fanikos J, Fiumara K, Paterno M, Goldhaber SZ. Electronic alerts for hospitalized high-VTE risk patients not receiving prophylaxis: a cohort study. J Thromb Thrombolysis. 2008; 25: 146–150.CrossrefMedlineGoogle Scholar21 Arya R, Paneesha S, McManus A, Parsons N, Scriven N, Farren T, Nokes T, Smith H, O'Shaughnessy D, Rose P. More on thromboprophylaxis: quantifying risk for venous thromboembolism. Thromb Haemost. 2009; 101: 791–794.CrossrefMedlineGoogle Scholar22 Piazza G, Rosenbaum EJ, Pendergast W, Jacobson JO, Pendleton RC, McLaren GD, Elliott CG, Stevens SM, Patton WF, Dabbagh O, Paterno MD, Catapane E, Li Z, Goldhaber SZ. Physician alerts to prevent symptomatic venous thromboembolism in hospitalized patients. Circulation. 2009; 119: 2196–2201.LinkGoogle Scholar23 Dorsey JL. Software support for "doing the right thing right." Thromb Haemost. 2009; 101: 413–414.CrossrefMedlineGoogle Scholar24 Klein TE, Altman RB, Eriksson N, Gage BF, Kimmel SE, Lee MT, Limdi NA, Page D, Roden DM, Wagner MJ, Caldwell MD, Johnson JA. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med. 2009; 360: 753–764.CrossrefMedlineGoogle Scholar25 Anderson JL, Horne BD, Stevens SM, Grove AS, Barton S, Nicholas ZP, Kahn SF, May HT, Samuelson KM, Muhlestein JB, Carlquist JF. 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Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005; 293: 1223–1238.CrossrefMedlineGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetailsCited By MacDougall K and Spyropoulos A (2021) Prevention of Venous Thromboembolism in Acutely Ill Medical Patients: A New Era, Seminars in Respiratory and Critical Care Medicine, 10.1055/s-0041-1723018, 42:02, (308-315), Online publication date: 1-Apr-2021. 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Related articlesCorrectionCirculation. 2010;122:e5-e5 September 22, 2009Vol 120, Issue 12 Advertisement Article InformationMetrics https://doi.org/10.1161/CIRCULATIONAHA.109.884031PMID: 19770412 Originally publishedSeptember 22, 2009 PDF download Advertisement SubjectsInformation Technology

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