Implementing an evidence-based computerized decision support system to improve patient care in a general hospital: the CODES study protocol for a randomized controlled trial

Lorenzo Moja, Hernan Polo Friz, Matteo Capobussi, Koren Kwag, Rita Banzi, Francesca Ruggiero, Marien González-Lorenzo, Elisa Giulia Liberati, Massimo Mangia, Peter Nyberg, Ilkka Kunnamo, Claudio Cimminiello, Giuseppe Vighi, Jeremy Grimshaw, Stefanos Bonovas, Lorenzo Moja, Hernan Polo Friz, Matteo Capobussi, Koren Kwag, Rita Banzi, Francesca Ruggiero, Marien González-Lorenzo, Elisa Giulia Liberati, Massimo Mangia, Peter Nyberg, Ilkka Kunnamo, Claudio Cimminiello, Giuseppe Vighi, Jeremy Grimshaw, Stefanos Bonovas

Abstract

Background: Computerized decision support systems (CDSSs) are information technology-based software that provide health professionals with actionable, patient-specific recommendations or guidelines for disease diagnosis, treatment, and management at the point-of-care. These messages are intelligently filtered to enhance the health and clinical care of patients. CDSSs may be integrated with patient electronic health records (EHRs) and evidence-based knowledge.

Methods/design: We designed a pragmatic randomized controlled trial to evaluate the effectiveness of patient-specific, evidence-based reminders generated at the point-of-care by a multi-specialty decision support system on clinical practice and the quality of care. We will include all the patients admitted to the internal medicine department of one large general hospital. The primary outcome is the rate at which medical problems, which are detected by the decision support software and reported through the reminders, are resolved (i.e., resolution rates). Secondary outcomes are resolution rates for reminders specific to venous thromboembolism (VTE) prevention, in-hospital all causes and VTE-related mortality, and the length of hospital stay during the study period.

Discussion: The adoption of CDSSs is likely to increase across healthcare systems due to growing concerns about the quality of medical care and discrepancy between real and ideal practice, continuous demands for a meaningful use of health information technology, and the increasing use of and familiarity with advanced technology among new generations of physicians. The results of our study will contribute to the current understanding of the effectiveness of CDSSs in primary care and hospital settings, thereby informing future research and healthcare policy questions related to the feasibility and value of CDSS use in healthcare systems. This trial is seconded by a specialty trial randomizing patients in an oncology setting (ONCO-CODES).

Trial registration: ClinicalTrials.gov, https://ichgcp.net/clinical-trials-registry/NCT02577198?term=NCT02577198&rank=1.

Keywords: Computerized decision support systems; Electronic health records; Evidence-based medicine; Pragmatic trial; Randomized controlled trial; Reminder systems.

Figures

Fig. 1
Fig. 1
Trial flow chart
Fig. 2
Fig. 2
Screenshot of the CDSS activation button (in red)
Fig. 3
Fig. 3
Screenshot of the CDSS activated online remiders

References

    1. Roshanov PS, Fernandes N, Wilczynski JM, Hemens BJ, You JJ, Handler SM, Nieuwlaat R, Souza NM, Beyene J, Van Spall HG, Garg AX, Haynes RB. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ. 2013;346:f657. doi: 10.1136/bmj.f657.
    1. Schuster M, McGlynn E, Brook R. How good is the quality of health care in the United States? Milbank Q. 2005;83:843–95. doi: 10.1111/j.1468-0009.2005.00403.x.
    1. McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr EA. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348:2635–45. doi: 10.1056/NEJMsa022615.
    1. Osheroff J. Improving medication use and outcomes with clinical decision support: a step-by-step guide. Chicago: The Healthcare Information and Management Systems Society; 2009.
    1. Berner E. Clinical decision support systems: state of the art. AHRQ Publication No. 09-0069-EF. Rockville: Agency for Healthcare Research and Quality; 2009.
    1. Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, Samsa G, Hasselblad V, Williams JW, Musty MD, Wing L, Kendrick AS, Sanders GD, Lobach D. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157:29–43. doi: 10.7326/0003-4819-157-1-201207030-00450.
    1. Ash JS, McCormack JL, Sittig DF, Wright A, McMullen C, Bates DW. Standard practices for computerized clinical decision support in community hospitals: a national survey. J Am Med Inform Assoc. 2012;19:980–7. doi: 10.1136/amiajnl-2011-000705.
    1. Griffey RT, Lo HG, Burdick E, Keohane C, Bates DW. Guided medication dosing for elderly emergency patients using real-time, computerized decision support. J Am Med Inform Assoc. 2012;19:86–93. doi: 10.1136/amiajnl-2011-000124.
    1. Romano MJ, Stafford RS. Electronic health records and clinical decision support systems: impact on national ambulatory care quality. Arch Intern Med. 2011;171:897–903.
    1. Terrell KM, Perkins AJ, Dexter PR, Hui SL, Callahan CM, Miller DK. Computerized decision support to reduce potentially inappropriate prescribing to older emergency department patients: a randomized, controlled trial. J Am Geriatr Soc. 2009;57:1388–94. doi: 10.1111/j.1532-5415.2009.02352.x.
    1. Holbrook A, Thabane L, Keshavjee K, Dolovich L, Bernstein B, Chan D, Troyan S, Foster G, Gerstein H. COMPETE II Investigators. Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial. CMAJ. 2009;181:37–44. doi: 10.1503/cmaj.081272.
    1. Bonnabry P, Despont-Gros C, Grauser D, Casez P, Despond M, Pugin D, Rivara-Mangeat C, Koch M, Vial M, Iten A, Lovis C. A risk analysis method to evaluate the impact of a computerized provider order entry system on patient safety. J Am Med Inform Assoc. 2008;15:453–60. doi: 10.1197/jamia.M2677.
    1. de Lusignan S, Chan T. The development of primary care information technology in the United kingdom. J Ambul Care Manage. 2008;31:201–10. doi: 10.1097/01.JAC.0000324664.88131.d2.
    1. Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, Morton SC, Shekelle PG. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144:742–52. doi: 10.7326/0003-4819-144-10-200605160-00125.
    1. Feldstein AC, Smith DH, Perrin N, Yang X, Rix M, Raebel MA, Magid DJ, Simon SR, Soumerai SB. Improved therapeutic monitoring with several interventions: a randomized trial. Arch Intern Med. 2006;166:1848–54. doi: 10.1001/archinte.166.17.1848.
    1. Sequist TD, Gandhi TK, Karson AS, Fiskio JM, Bugbee D, Sperling M, Cook EF, Orav EJ, Fairchild DG, Bates DW. A randomized trial of electronic clinical reminders to improve quality of care for diabetes and coronary artery disease. J Am Med Inform Assoc. 2005;12:431–7. doi: 10.1197/jamia.M1788.
    1. Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch Intern Med. 2003;163:1409–16. doi: 10.1001/archinte.163.12.1409.
    1. Tamblyn R, Huang A, Perreault R, Jacques A, Roy D, Hanley J, McLeod P, Laprise R. The medical office of the 21st century (MOXXI): effectiveness of computerized decision-making support in reducing inappropriate prescribing in primary care. CMAJ. 2003;169:549–56.
    1. Dexter PR, Perkins S, Overhage JM, Maharry K, Kohler RB, McDonald CJ. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med. 2001;345:965–70. doi: 10.1056/NEJMsa010181.
    1. Moja L, Banzi R. Navigators for medicine: evolution of online point-of-care evidence-based services. Int J Clin Pract. 2011;65:6–11. doi: 10.1111/j.1742-1241.2010.02441.x.
    1. Moja L, Kwag KH, Lytras T, Bertizzolo L, Brandt L, Pecoraro V, Rigon G, Vaona A, Ruggiero F, Mangia M, Iorio A, Kunnamo I, Bonovas S. Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Public Health. 2014;104:e12–e22. doi: 10.2105/AJPH.2014.302164.
    1. Sim I, Gorman P, Greenes RA, Haynes RB, Kaplan B, Lehmann H, Tang PC. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc. 2001;8:527–34. doi: 10.1136/jamia.2001.0080527.
    1. Medilogy S.r.l., Medilogy Decision Support System (MediDSS). . Accessed Apr 2016.
    1. Chan AW, Tetzlaff JM, Altman DG, Laupacis A, Gøtzsche PC, Krleza-Jeric K, Hrobjartsson A, Mann H, Dickersin K, Berlin J, Dore C, Parulekar W, Summerskill W, Groves T, Schulz K, Sox H, Rockhold FW, Rennie D, Moher D. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158:200–7. doi: 10.7326/0003-4819-158-3-201302050-00583.
    1. Chan AW, Tetzlaff JM, Gøtzsche PC, Altman DG, Mann H, Berlin JA, Dickersin K, Hrobjartsson A, Schulz KF, Parulekar WR, Krleza-Jeric K, Laupacis A, Moher D. SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ. 2013;346:e7586. doi: 10.1136/bmj.e7586.
    1. Azienda Ospedaliera di Desio e Vimercate. . Accessed Apr 2016.
    1. Dedalus S.p.A., Tabula Clinica. . Accessed Apr 2016.
    1. Schwartz D, Lellouch J. Explanatory and pragmatic attitudes in therapeutical trials. J Chronic Dis. 1967;20:637–48. doi: 10.1016/0021-9681(67)90041-0.
    1. Zwarenstein M, Treweek S, Gagnier JJ, Altman DG, Tunis S, Haynes B, Oxman AD, Moher D, CONSORT group. Pragmatic Trials in Healthcare (Practihc) group Improving the reporting of pragmatic trials: an extension of the CONSORT statement. BMJ. 2008;337:a2390. doi: 10.1136/bmj.a2390.
    1. Banzi R, Cinquini M, Liberati A, Moschetti I, Pecoraro V, Tagliabue L, Moja L. Speed of updating online evidence based point of care summaries: prospective cohort analysis. BMJ. 2011;343:d5856. doi: 10.1136/bmj.d5856.
    1. Banzi R, Liberati A, Moschetti I, Tagliabue L, Moja L. A review of online evidence-based practice point-of-care information summary providers. J Med Internet Res. 2010;12:e26. doi: 10.2196/jmir.1288.
    1. Duodecim Medical Publications, Evidence-Based Medicine electronic Decision Support (EBMeDS). . Accessed Apr 2016.
    1. Böttiger Y, Laine K, Andersson ML, Korhonen T, Molin B, Ovesjö ML, Tirkkonen T, Rane A, Gustafsson LL, Eiermann B. SFINX-a drug-drug interaction database designed for clinical decision support systems. Eur J Clin Pharmacol. 2009;65:627–33. doi: 10.1007/s00228-008-0612-5.
    1. Brown CA, Lilford RJ. The stepped wedge trial design: a systematic review. BMC Med Res Methodol. 2006;6:54. doi: 10.1186/1471-2288-6-54.
    1. Ageno W, Squizzato A, Ambrosini F, Dentali F, Marchesi C, Mera V, Steidl L, Venco A. Thrombosis prophylaxis in medical patients: a retrospective review of clinical practice patterns. Haematologica. 2002;87:746–50.
    1. Polo Friz H, Molteni M, Del Sorbo D, Pasciuti L, Crippa M, Villa G, Meloni DF, Primitz L, Galli A, Rognoni M, Cavalieri d'Oro L, Arpaia G, Cimminiello C. Mortality at 30 and 90 days in elderly patients with pulmonary embolism: a retrospective cohort study. Intern Emerg Med. 2015;10:431–6. doi: 10.1007/s11739-014-1179-z.
    1. 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;25:146–50. doi: 10.1007/s11239-007-0081-1.
    1. Beeler PE, Kucher N, Blaser J. Sustained impact of electronic alerts on rate of prophylaxis against venous thromboembolism. Thromb Haemost. 2011;106:734–8. doi: 10.1160/TH11-04-0220.
    1. 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;283:2816–21. doi: 10.1001/jama.283.21.2816.
    1. Fiumara K, Piovella C, Hurwitz S, Piazza G, Niles CM, Fanikos J, Paterno M, Labreche M, Stevens LA, Baroletti S, Goldhaber SZ. Multi-screen electronic alerts to augment venous thromboembolism prophylaxis. Thromb Haemost. 2010;103:312–7. doi: 10.1160/TH09-09-0634.
    1. Galanter WL, Thambi M, Rosencranz H, Shah B, Falck S, Lin FJ, Nutescu E, Lambert B. Effects of clinical decision support on venous thromboembolism risk assessment, prophylaxis, and prevention at a university teaching hospital. Am J Health Syst Pharm. 2010;67:1265–73. doi: 10.2146/ajhp090575.
    1. Haut ER, Lau BD, Kraenzlin FS, Hobson DB, Kraus PS, Carolan HT, Haider AH, Holzmueller CG, Efron DT, Pronovost PJ, Streiff MB. Improved prophylaxis and decreased rates of preventable harm with the use of a mandatory computerized clinical decision support tool for prophylaxis for venous thromboembolism in trauma. Arch Surg. 2012;147:901–7. doi: 10.1001/archsurg.2012.2024.
    1. Janus E, Bassi A, Jackson D, Nandurkar H, Yates M. Thromboprophylaxis use in medical and surgical inpatients and the impact of an electronic risk assessment tool as part of a multi-factorial intervention. A report on behalf of the elVis study investigators. J Thromb Thrombolysis. 2011;32:279–87. doi: 10.1007/s11239-011-0602-9.
    1. Kucher N, Puck M, Blaser J, Bucklar G, Eschmann E, Lüscher TF. Physician compliance with advanced electronic alerts for preventing venous thromboembolism among hospitalized medical patients. J Thromb Haemost. 2009;7:1291–6. doi: 10.1111/j.1538-7836.2009.03509.x.
    1. 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;352:969–77. doi: 10.1056/NEJMoa041533.
    1. Lecumberri R, Panizo E, Gomez-Guiu A, Varea S, García-Quetglas E, Serrano M, García-Mouriz A, Marqués M, Gómez-Outes A, Páramo JA. Economic impact of an electronic alert system to prevent venous thromboembolism in hospitalized patients. J Thromb Haemost. 2011;9:1108–15. doi: 10.1111/j.1538-7836.2011.04282.x.
    1. Lecumberri R, Marqués M, Díaz-Navarlaz MT, Panizo E, Toledo J, García-Mouriz A, Páramo JA. Maintained effectiveness of an electronic alert system to prevent venous thromboembolism among hospitalized patients. Thromb Haemost. 2008;100:699–704.
    1. Marco P, Lopez-Abadia E, Lucas J. More on thromboprophylaxis: electronic alerts in hospitalized patients at risk of venous thromboembolism. Thromb Haemost. 2008;100:525–6.
    1. Mitchell JD, Collen JF, Petteys S, Holley AB. A simple reminder system improves venous thromboembolism prophylaxis rates and reduces thrombotic events for hospitalized patients. J Thromb Haemost. 2012;10:236–43. doi: 10.1111/j.1538-7836.2011.04599.x.
    1. 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;119:2196–201. doi: 10.1161/CIRCULATIONAHA.108.841197.
    1. Piazza G, Goldhaber SZ. Computerized decision support for the cardiovascular clinician: applications for venous thromboembolism prevention and beyond. Circulation. 2009;120:1133–7. doi: 10.1161/CIRCULATIONAHA.109.884031.
    1. Sobieraj DM. Development and implementation of a program to assess medical patients’ need for venous thromboembolism prophylaxis. Am J Health Syst Pharm. 2008;65:1755–60. doi: 10.2146/ajhp070598.
    1. Streiff MB, Carolan HT, Hobson DB, Kraus PS, Holzmueller CG, Demski R, Lau BD, Biscup-Horn P, Pronovost PJ, Haut ER. Lessons from the Johns Hopkins Multi-Disciplinary Venous Thromboembolism (VTE) Prevention Collaborative. BMJ. 2012;344:e3935. doi: 10.1136/bmj.e3935.
    1. Barbar S, Noventa F, Rossetto V, Ferrari A, Brandolin B, Perlati M, De Bon E, Tormene D, Pagnan A, Prandoni P. A risk assessment model for the identification of hospitalized medical patients at risk for venous thromboembolism: the Padua prediction score. J Thromb Haemost. 2010;8:2450–7. doi: 10.1111/j.1538-7836.2010.04044.x.
    1. Moxey A, Robertson J, Newby D, Hains I, Williamson M, Pearson SA. Computerized clinical decision support for prescribing: provision does not guarantee uptake. J Am Med Inform Assoc. 2010;17:25–33. doi: 10.1197/jamia.M3170.
    1. Moja L, Liberati E, Galuppo L, Gorli M, Maraldi M, Nanni O, Rigon G, Ruggieri P, Ruggiero F, Scaratti G, Vaona A, Kwag K. Barriers and facilitators to the uptake of computerized clinical decision support systems in specialty hospitals: protocol for a qualitative cross-sectional study. Implement Sci. 2014;9:105. doi: 10.1186/s13012-014-0105-0.
    1. Shojania KG, Jennings A, Mayhew A, Ramsay CR, Eccles MP, Grimshaw J. The effects of on-screen, point of care computer reminders on processes and outcomes of care. Cochrane Database of Systematic Reviews 2009, Issue 3. Art. No.: CD001096. doi:10.1002/14651858.CD001096.pub2.
    1. Kortteisto T, Raitanen J, Komulainen J, Kunnamo I, Makela M, Rissanen P, Kaila M, EBMeDS (Evidence-Based Medicine electronic Decision Support) Study Group Patient-specific computer-based decision support in primary healthcare—a randomized trial. Implement Sci. 2014;9:15. doi: 10.1186/1748-5908-9-15.
    1. Lachin J, Matts J, Wei L. Randomization in clinical trials: conclusions and recommendations. Control Clin Trials. 1988;9:365–74. doi: 10.1016/0197-2456(88)90049-9.
    1. Twisk JWR. Applied longitudinal data analysis for epidemiology: a practical guide. 2. Cambridge: Cambridge University Press; 2013.
    1. World Medical Association Declaration of Helsinki—Ethical principles for medical research involving human subjects. . Accessed Apr 2016.
    1. Taljaard M, Weijer C, Grimshaw JM, Eccles MP, Ottawa Ethics of Cluster Randomised Trials Consensus Group The Ottawa statement on the ethical design and conduct of cluster randomised trials: precis for researchers and research ethics committees. BMJ. 2013;346:f2838. doi: 10.1136/bmj.f2838.
    1. Weijer C, Grimshaw JM, Eccles MP, McRae AD, White A, Brehaut JC, Taljaard M, Ottawa Ethics of Cluster Randomized Trials Consensus Group The Ottawa statement on the ethical design and conduct of cluster randomized trials. PLoS Med. 2012;9:e1001346. doi: 10.1371/journal.pmed.1001346.
    1. Hutton JL. Are distinctive ethical principle required for cluster randomized trials? Stat Med. 2001;20:473–88. doi: 10.1002/1097-0258(20010215)20:3<473::AID-SIM805>;2-D.
    1. Winkens RA, Knottnerus JA, Kester AD, Grol RP, Pop P. Fitting a routine health-care activity into a randomized trial: an experiment possible without informed consent? J Clin Epidemiol. 1997;50:435–9. doi: 10.1016/S0895-4356(96)00422-2.
    1. Medilogy S.r.l., MediDrug. . Accessed Mar 2016.

Source: PubMed

Sponsorer och medarbetare

Medicinska tillstånd

Läkemedelsinterventioner

3
Prenumerera