Personalization and Patient Involvement in Decision Support Systems: Current Trends

Summary

Objectives: This survey aims at highlighting the latest trends (2012-2014) on the development, use, and evaluation of Information and Communication Technologies (ICT) based decision support systems (DSSs) in medicine, with a particular focus on patient-centered and personalized care.

Methods: We considered papers published on scientific journals, by querying PubMed and Web of Science^TM. Included studies focused on the implementation or evaluation of ICT-based tools used in clinical practice. A separate search was performed on computerized physician order entry systems (CPOEs), since they are increasingly embedding patient-tailored decision support. Results: We found 73 papers on DSSs (53 on specific ICT tools) and 72 papers on CPOEs. Although decision support through the delivery of recommendations is frequent (28/53 papers), our review highlighted also DSSs only based on efficient information presentation (25/53). Patient participation in making decisions is still limited (9/53), and mostly focused on risk communication. The most represented medical area is cancer (12%). Policy makers are beginning to be included among stakeholders (6/73), but integration with hospital information systems is still low. Concerning knowledge representation/management issues, we identified a trend towards building inference engines on top of standard data models. Most of the tools (57%) underwent a formal assessment study, even if half of them aimed at evaluating usability and not effectiveness.

Conclusions: Overall, we have noticed interesting evolutions of medical DSSs to improve communication with the patient, consider the economic and organizational impact, and use standard models for knowledge representation. However, systems focusing on patient-centered care still do not seem to be available at large.

Keywords

Decision support systems, clinical - decision aids - decision making, shared - patient-centered care - patient empowerment

 

• References

• 1 Peleg M, Tu S. Decision support, knowledge representation and management in medicine. Yearb Med Inform 2006; 72-80.
• 2 Kachalia A, Mello MM. Defensive medicine--legally necessary but ethically wrong?: Inpatient stress testing for chest pain in low-risk patients. JAMA Intern Med. 2013 Jun 24 173 (Suppl. 12) 1056-7.
• 3 Charles C, Gafni A, Whelan T. Shared decision-making in the medical encounter: what does it mean?. Soc Sci Med 1997; Mar 44 (Suppl. 05) 681-92.
• 4 Stacey D, Légaré F, Col NF, Bennett CL, Barry MJ, Eden KB. et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2014; Jan 28 1.
• 5 Pulley JM, Denny JC, Peterson JF, Bernard GR, Vnencak-Jones CL, Ramirez AH. et al. Operational implementation of prospective genotyping for personalized medicine: the design of the Vanderbilt PREDICT project. Clin Pharmacol Ther 2012; Jul 92 (Suppl. 01) 87-95.
• 6 Kastner M, Straus SE. Application of the Knowledge-to-Action and Medical Research Council frameworks in the development of an osteoporosis clinical decision support tool. J Clin Epidemiol 2012; Nov 65 (Suppl. 11) 1163-70.
• 7 Luo G, Tang C, Thomas SB. Intelligent personal health record: experience and open issues. J Med Syst 2012; Aug 36 (Suppl. 04) 2111-28.
• 8 Hsieh NC, Chang CY, Lee KC, Chen JC, Chan CH. Technological innovations in the development of cardiovascular clinical information systems. J Med Syst 2012; Apr 36 (Suppl. 02) 965-78.
• 9 Chi CL, Nick Street W, Robinson JG, Crawford MA. Individualized patient-centered lifestyle recommendations: an expert system for communicating patient specific cardiovascular risk information and prioritizing lifestyle options. J Biomed Inform 2012; Dec 45 (Suppl. 06) 1164-74.
• 10 Spanakis EG, Chiarugi F, Kouroubali A, Spat S, Beck P, Asanin S. et al. Diabetes Management Using Modern Information and Communication Technologies and New Care Models. Eysenbach G., editor. Interact J Med Res 2012; 1 (Suppl. 02) e8.
• 11 Lindblom K, Gregory T, Wilson C, Flight IH, Zajac I. The impact of computer self-efficacy, computer anxiety, and perceived usability and acceptability on the efficacy of a decision support tool for colorectal cancer screening. J Am Med Inform Assoc 2012; May-Jun 19 (Suppl. 03) 407-12.
• 12 Yu HJ, Lai HS, Chen KH, Chou HC, Wu JM, Dorjgochoo S. et al. A sharable cloud-based pancreaticoduodenectomy collaborative database for physicians: emphasis on security and clinical rule supporting. Comput Methods Programs Biomed 2013; Aug 111 (Suppl. 02) 488-97.
• 13 Ip IK, Schneider L, Seltzer S, Smith A, Dudley J, Menard A. et al. Impact of provider-led, technology-enabled radiology management program on imaging. Am J Med 2013; Aug 126 (Suppl. 08) 687-92.
• 14 Riaño D, Real F, López-Vallverdú JA, Campana F, Ercolani S, Mecocci P. et al. An ontology-based personalization of health-care knowledge to support clinical decisions for chronically ill patients. J Biomed Inform 2012; Jun 45 (Suppl. 03) 429-46.
• 15 Dexheimer JW, Abramo TJ, Arnold DH, Johnson K, Shyr Y, Ye F. et al. Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency department: a randomized clinical trial. Int J Med Inform 2014; Nov 83 (Suppl. 11) 805-13.
• 16 Herwehe J, Wilbright W, Abrams A, Bergson S, Foxhood J, Kaiser M. et al. Implementation of an innovative, integrated electronic medical record (EMR) and public health information exchange for HIV/AIDS. J Am Med Inform Assoc 2012; May-Jun 19 (Suppl. 03) 448-52.
• 17 Goldspiel BR, Flegel WA, DiPatrizio G, Sissung T, Adams SD, Penzak SR. et al. Integrating pharmacogenetic information and clinical decision support into the electronic health record. J Am Med Inform Assoc 2014; May-Jun 21 (Suppl. 03) 522-8.
• 18 Fernández-Breis JT, Maldonado JA, Marcos M, Legaz-García Mdel C, Moner D, Torres-Sospedra J. et al. Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts. J Am Med Inform Assoc 2013; Dec 20 e2 e288-96.
• 19 Klann JG, Anand V, Downs SM. Patient-tailored prioritization for a pediatric care decision support system through machine learning. J Am Med Inform Assoc 2013; Dec 20 e2 e267-74.
• 20 Blank A, Prytherch H, Kaltschmidt J, Krings A, Sukums F, Mensah N. et al. “Quality of prenatal and maternal care: bridging the know-do gap” (QUALMAT study): an electronic clinical decision support system for rural Sub-Saharan Africa. BMC Med Inform Decis Mak 2013 Apr 10 13: 44.
• 21 Duke JD, Morea J, Mamlin B, Martin DK, Simonaitis L, Takesue BY. et al. Regenstrief Institute’s Medical Gopher: a next-generation homegrown electronic medical record system. Int J Med Inform 2014; Mar 83 (Suppl. 03) 170-9.
• 22 Shojanoori R, Juric R. Semantic remote patient monitoring system. Telemed J E Health 2013; Feb 19 (Suppl. 02) 129-36.
• 23 Dixon BE, Simonaitis L, Goldberg HS, Paterno MD, Schaeffer M, Hongsermeier T. et al. A pilot study of distributed knowledge management and clinical decision support in the cloud. Artif Intell Med 2013; Sep 59 (Suppl. 01) 45-53.
• 24 Farmer N. An update and further testing of a knowledge-based diagnostic clinical decision support system for musculoskeletal disorders of the shoulder for use in a primary care setting. J Eval Clin Pract 2014; Oct 20 (Suppl. 05) 589-95.
• 25 Rodríguez-González A, Torres-Niño J, Mayer MA, Alor-Hernandez G, Wilkinson MD. Analysis of a multilevel diagnosis decision support system and its implications: a case study. Comput Math Methods Med 2012; 2012: 367345.
• 26 Johnson KB, Ho YX, Andrew Spooner S, Palmer M, Weinberg ST. Assessing the reliability of an automated dose-rounding algorithm. J Biomed Inform 2013; Oct 46 (Suppl. 05) 814-21.
• 27 Agharezaei Z, Bahaadinbeigy K, Tofighi S, Agharezaei L, Nemati A. Attitude of Iranian physicians and nurses toward a clinical decision support system for pulmonary embolism and deep vein thrombosis. Comput Methods Programs Biomed 2014; Jul 115 (Suppl. 02) 95-101.
• 28 Wang HQ, Li JS, Zhang YF, Suzuki M, Araki K. Creating personalised clinical pathways by semantic interoperability with electronic health records. Artif Intell Med 2013; Jun 58 (Suppl. 02) 81-9.
• 29 Adams P, Nielson H. Evidence based practice: decreasing psychiatric revisits to the emergency department. Issues Ment Health Nurs 2012; Aug 33 (Suppl. 08) 536-43.
• 30 Martínez-Romero M, Vázquez-Naya JM, Pereira J, Pereira M, Pazos A, Baños G. The iOSC3 system: using ontologies and SWRL rules for intelligent supervision and care of patients with acute cardiac disorders. Comput Math Methods Med 2013; 2013: 650671.
• 31 Robbins GK, Lester W, Johnson KL, Chang Y, Estey G, Surrao D. et al. Successful Outcomes of a Clinical Decision Support System in an HIV Practice: A Randomized Controlled Trial. Ann Intern Med 2012; 157 (Suppl. 11) 757-66.
• 32 Lu X, Huang Z, Duan H. Supporting adaptive clinical treatment processes through recommendations. Comput Methods Programs Biomed 2012; Sep 107 (Suppl. 03) 413-24.
• 33 Lin HC, Wu HC, Chang CH, Li TC, Liang WM, Wang JY. A real time online assessment system with modelized architecture on clinical infometrics for patient reported outcomes of prostate cancer. Comput Methods Programs Biomed 2012; Jun 106 (Suppl. 03) 249-59.
• 34 Simon D, Kriston L, von Wolff A, Buchholz A, Vietor C, Hecke T. et al. Effectiveness of a web-based, individually tailored decision aid for depression or acute low back pain: a randomized controlled trial. Patient Educ Couns 2012; Jun 87 (Suppl. 03) 360-8.
• 35 Federer AE, Taylor DC, Mather 3rd. RC. Using evidence-based algorithms to improve clinical decision making: the case of a first-time anterior shoulder dislocation. Sports Med Arthrosc 2013; Sep 21 (Suppl. 03) 155-65.
• 36 LeBlanc A, Ruud KL, Branda ME, Tiedje K, Boehmer KR, Pencille LJ. et al. The impact of decision aids to enhance shared decision making for diabetes (the DAD study): protocol of a cluster randomized trial. BMC Health Serv Res 2012 May 28 12: 130.
• 37 Cox CE, White DB, Abernethy AP. A universal decision support system. Addressing the decision-making needs of patients, families, and clinicians in the setting of critical illness. Am J Respir Crit Care Med 2014 Aug 15 190 (Suppl. 04) 366-73.
• 38 Stein BD, Kogan JN, Mihalyo MJ, Schuster J, Deegan PE, Sorbero MJ. et al. Use of a computerized medication shared decision making tool in community mental health settings: impact on psychotropic medication adherence. Community Ment Health J 2013; Apr 49 (Suppl. 02) 185-92.
• 39 Ogburn T. Shared decision making and informed consent for hysterectomy. Clin Obstet Gynecol 2014; Mar 57 (Suppl. 01) 3-13.
• 40 Newsome A, Sieber W, Smith M, Lillie D. If you build it, will they come? A qualitative evaluation of the use of video-based decision aids in primary care. Fam Med 2012; Jan 44 (Suppl. 01) 26-31.
• 41 Ozanne EM, Howe R, Omer Z, Esserman LJ. Development of a personalized decision aid for breast cancer risk reduction and management. BMC Med Inform Decis Mak 2014 Jan 14 14: 4.
• 42 Blau GE, Orcun S, Laínez JM, Reklaitis GV, Suvannasankha A, Fausel C. et al. Validation of a novel approach for dose individualization in pharmacotherapy using gabapentin in a proof of principles study. Pharmacotherapy 2013; Jul 33 (Suppl. 07) 727-35.
• 43 Herrick DB, Nakhasi A, Nelson B, Rice S, Abbott PA, Saber Tehrani AS. et al. Usability characteristics of self-administered computer-assisted interviewing in the emergency department: factors affecting ease of use, efficiency, and entry error. Appl Clin Inform 2013 Jun 19 4 (Suppl. 02) 276-92.
• 44 Lühr A, Löck S, Roth K, Helmbrecht S, Jakobi A, Petersen JB. et al. Concept for individualized patient allocation: ReCompare--remote comparison of particle and photon treatment plans. Radiat Oncol 2014 Feb 18 9: 59.
• 45 Was A, Wanderer J. Matching clinicians to operative cases: a novel application of a patient acuity score. Appl Clin Inform 2013 Jul 10 4 (Suppl. 03) 445-53.
• 46 Choi J, Kim H. Enhancement of decision rules to increase generalizability and performance of the rule-based system assessing risk for pressure ulcer. Appl Clin Inform 2013 Jun 5 4 (Suppl. 02) 251-66.
• 47 Bailey JE, Wan JY, Mabry LM, Landy SH, Pope RA, Waters TM. et al. Does health information exchange reduce unnecessary neuroimaging and improve quality of headache care in the emergency department?. J Gen Intern Med 2013; Feb 28 (Suppl. 02) 176-83.
• 48 Folks RD, Savir-Baruch B, Garcia EV, Verdes L, Taylor AT. Development of a Relational Database to Capture and Merge Clinical History with the Quantitative Results of Radionuclide Renography. J Nucl Med Technol 2012; 40 (Suppl. 04) 236-243.
• 49 Bennett CC, Hauser K. Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach. Artif Intell Med 2013; Jan 57 (Suppl. 01) 9-19.
• 50 Galea I, Lederer C, Neuhaus A, Muraro PA, Scalfari A, Koch-Henriksen N. et al. A web-based tool for personalized prediction of long-term disease course in patients with multiple sclerosis. Eur J Neurol 2013; Jul 20 (Suppl. 07) 1107-9.
• 51 Dixon BE, Jabour AM, Phillips EO, Marrero DG. An informatics approach to medication adherence assessment and improvement using clinical, billing, and patient-entered data. J Am Med Inform Assoc 2014; May-Jun 21 (Suppl. 03) 517-21.
• 52 Schnall R, Cimino JJ, Bakken S. Development of a prototype continuity of care record with context-specific links to meet the information needs of case managers for persons living with HIV. Int J Med Inform 2012; Aug 81 (Suppl. 08) 549-55.
• 53 Chiarini Tremblay M, Hevner AR, Berndt DJ. Design of an information volatility measure for health care decision making. Decis Support Syst 2012; Jan 52 (Suppl. 02) 331-41.
• 54 Peirson L, Catallo C, Chera S. The Registry of Knowledge Translation Methods and Tools: a resource to support evidence-informed public health. Int J Public Health Aug 2013; 58 (Suppl. 04) 493-500.
• 55 Kuru K, Girgin S, Arda K, Bozlar U. A novel report generation approach for medical applications: the SISDS methodology and its applications. Int J Med Inform 2013; May 82 (Suppl. 05) 435-47.
• 56 Wu R, Boushey R, Potter B, Stacey D. The evaluation of a rectal cancer decision aid and the factors influencing its implementation in clinical practice. BMC Surg 2014 Mar 21 14: 16.
• 57 Carney PH. Information technology and precision medicine. Semin Oncol Nurs 2014; May 30 (Suppl. 02) 124-9.
• 58 Welch BM, Kawamoto K. Clinical decision support for genetically guided personalized medicine: a systematic review. J Am Med Inform Assoc 2013; Mar-Apr 20 (Suppl. 02) 388-400.
• 59 Collins IM, Breathnach O, Felle P. Electronic clinical decision support systems attitudes and barriers to use in the oncology setting. Ir J Med Sci 2012; Dec 181 (Suppl. 04) 521-5.
• 60 Arnold CW, McNamara M, El-Saden S, Chen S, Taira RK, Bui AA. Imaging informatics for consumer health: towards a radiology patient portal. J Am Med Inform Assoc 2013; NovDec 20 (Suppl. 06) 1028-36.
• 61 Lambin P, van Stiphout RG, Starmans MH, Rios-Velazquez E, Nalbantov G, Aerts HJ. et al. Predicting outcomes in radiation oncology--multifactorial decision support systems. Nat Rev Clin Oncol 2013; Jan 10 (Suppl. 01) 27-40.
• 62 Lambin P, Roelofs E, Reymen B, Velazquez ER, Buijsen J, Zegers CM. et al. ‘Rapid Learning health care in oncology’ - an approach towards decision support systems enabling customised radiotherapy’. Radiother Oncol 2013; Oct 109 (Suppl. 01) 159-64.
• 63 Ceriello A, Barkai L, Christiansen JS, Czupryniak L, Gomis R, Harno K. et al. Diabetes as a case study of chronic disease management with a personalized approach: the role of a structured feedback loop. Diabetes Res Clin Pract 2012; Oct 98 (Suppl. 01) 5-10.
• 64 McDermott MS, While AE. Maximizing the healthcare environment: a systematic review exploring the potential of computer technology to promote self-management of chronic illness in healthcare settings. Patient Educ Couns 2013; Jul 92 (Suppl. 01) 13-22.
• 65 Gionfriddo MR, Leppin AL, Brito JP, Leblanc A, Shah ND, Montori VM. Shared decision-making and comparative effectiveness research for patients with chronic conditions: an urgent synergy for better health. J Comp Eff Res 2013; Nov 2 (Suppl. 06) 595-603.
• 66 Friedberg MW, Van Busum K, Wexler R, Bowen M, Schneider EC. A demonstration of shared decision making in primary care highlights barriers to adoption and potential remedies. Health Aff (Millwood) 2013; Feb 32 (Suppl. 02) 268-75.
• 67 Meulendijk M, Spruit M, Drenth-van Maanen C, Numans M, Brinkkemper S, Jansen P. General practitioners’ attitudes towards decision-supported prescribing: an analysis of the Dutch primary care sector. Health Informatics J 2013; Dec 19 (Suppl. 04) 247-63.
• 68 Li AC, Kannry JL, Kushniruk A, Chrimes D, McGinn TG, Edonyabo D. et al. Integrating usability testing and think-aloud protocol analysis with “near-live” clinical simulations in evaluating clinical decision support. Int J Med Inform 2012; Nov 81 (Suppl. 11) 761-72.
• 69 King VJ, Davis MM, Gorman PN, Rugge JB, Fagnan LJ. Perceptions of Shared Decision Making and Decision Aids Among Rural Primary Care Clinicians. Med Decis Making 2012; 32 (Suppl. 04) 636-44.
• 70 Saverno KR, Rochau U, Stenehjem DD, Morley K, Siebert U, Brixner DI. Application of decision-analytic models in personalized medicine for CML treatment decisions made by payers, providers, and patients. J Manag Care Pharm 2012; Jul-Aug 18 (Suppl. 06) 457-63.
• 71 Marcos M, Maldonado JA, Martínez-Salvador B, Boscá D, Robles M. Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility. J Biomed Inform 2013; Aug 46 (Suppl. 04) 676-89.
• 72 Anani N, Chen R, Prazeres Moreira T, Koch S. Retrospective checking of compliance with practice guidelines for acute stroke care: a novel experiment using openEHR’s Guideline Definition Language. BMC Med Inform Decis Mak 2014 May 10 14: 39.
• 73 Horsky J, Schiff GD, Johnston D, Mercincavage L, Bell D, Middleton B. Interface design principles for usable decision support: a targeted review of best practices for clinical prescribing interventions. J Biomed Inform 2012; Dec 45 (Suppl. 06) 1202-16.
• 74 Rodríguez-González A, Torres-Niño J, Valencia-Garcia R, Mayer MA, Alor-Hernandez G. Using experts feedback in clinical case resolution and arbitration as accuracy diagnosis methodology. Comput Biol Med 2013; Sep 43 (Suppl. 08) 975-86.
• 75 Carroll DL, Dykes PC, Hurley AC. An electronic fall prevention toolkit: effect on documentation quality. Nurs Res 2012; Jul-Aug 61 (Suppl. 04) 309-13.
• 76 Kawamoto K, Hongsermeier T, Wright A, Lewis J, Bell DS, Middleton B. Key principles for a national clinical decision support knowledge sharing framework: synthesis of insights from leading subject matter experts. J Am Med Inform Assoc 2013 Jan 1 20 (Suppl. 01) 199-207.
• 77 Rosenbaum BP, Silkin N, Miller RA. Easily configured real-time CPOE Pick Off Tool supporting focused clinical research and quality improvement. J Am Med Inform Assoc 2014; May-Jun 21 (Suppl. 03) 564-8.
• 78 McWilliams B, Triulzi DJ, Waters JH, Alarcon LH, Reddy V, Yazer MH. Trends in RBC ordering and use after implementing adaptive alerts in the electronic computerized physician order entry system. Am J Clin Pathol 2014; Apr 141 (Suppl. 04) 534-41.
• 79 Levick DL, Stern G, Meyerhoefer CD, Levick A, Pucklavage D. Reducing unnecessary testing in a CPOE system through implementation of a targeted CDS intervention. BMC Med Inform Decis Mak 2013 Apr 8 13: 43.
• 80 Leu MG, Morelli SA, Chung OY, Radford S. Systematic update of computerized physician order entry order sets to improve quality of care: a case study. Pediatrics 2013; Mar 131 Suppl 1: S60-7.
• 81 Galanter W, Falck S, Burns M, Laragh M, Lambert BL. Indication-based prescribing prevents wrong-patient medication errors in computerized provider order entry (CPOE). J Am Med Inform Assoc 2013 May 1 20 (Suppl. 03) 477-81.
• 82 Hsu CC, Chou CY, Chou CL, Ho CC, Chen TJ, Chiang SC. et al. Impact of a Warning CPOE System on the Inappropriate Pill Splitting of Prescribed Medications in Outpatients. Plos One 2014 Dec 5 9 (Suppl. 12) e114359.
• 83 Thrall JH. Appropriateness and imaging utilization: “computerized provider order entry and decision support”. Acad Radiol 2014; Sep 21 (Suppl. 09) 1083-7.
• 84 McCrory MC, Strouse JJ, Takemoto CM, Easley RB. Computerized physician order entry improves compliance with a manual exchange transfusion protocol in the pediatric intensive care unit. J Pediatr Hematol Oncol 2014; Mar 36 (Suppl. 02) 143-7.
• 85 Howell LP, MacDonald S, Jones J, Tancredi DJ, Melnikow J. Can automated alerts within computerized physician order entry improve compliance with laboratory practice guidelines for ordering Pap tests?. J Pathol Inform 2014 Sep 30 5: 37.
• 86 Vermeulen KM, van Doormaal JE, Zaal RJ, Mol PG, Lenderink AW, Haaijer-Ruskamp FM. et al. Cost-effectiveness of an electronic medication ordering system (CPOE/CDSS) in hospitalized patients. Int J Med Inform 2014; Aug 83 (Suppl. 08) 572-80.
• 87 Armada ER, Villamañán E, López-de-Sá E, Rosillo S, Rey-Blas JR, Testillano ML. et al. Computerized physician order entry in the cardiac intensive care unit: effects on prescription errors and workflow conditions. J Crit Care 2014; Apr 29 (Suppl. 02) 188-93.
• 88 Mathew G, Kho A, Dexter P, Bloodworth N, Fantz C, Spell N. et al. Concept and development of a discharge alert filter for abnormal laboratory values coupled with computerized provider order entry: a tool for quality improvement and hospital risk management. J Patient Saf 2012; Jun 8 (Suppl. 02) 69-75.
• 89 Shriner AR, Webber EC. Attitudes and perceptions of pediatric residents on transitioning to CPOE. Appl Clin Inform 2014 Aug 13 5 (Suppl. 03) 721-30.
• 90 Cadwallader J, Asirwa C, Li X, Kesterson J, Tier-ney WM, Were MC. Using computerized provider order entry to enforce documentation of tests with pending results at hospital discharge. Appl Clin Inform 2012 Apr 4 3 (Suppl. 02) 154-63.
• 91 Wang HY, Lu CL, Wu MP, Huang MH, Huang YB. Effectiveness of an integrated CPOE decision-supporting system with clinical pharmacist monitoring practice in preventing antibiotic dosing errors. Int J Clin Pharmacol Ther 2012; Jun 50 (Suppl. 06) 375-82.
• 92 Devine EB, Lee CJ, Overby CL, Abernethy N, McCune J, Smith JW. et al. Usability evaluation of pharmacogenomics clinical decision support aids and clinical knowledge resources in a computerized provider order entry system: a mixed methods approach. Int J Med Inform 2014; Jul 83 (Suppl. 07) 473-83.
• 93 Ip IK, Schneider LI, Hanson R, Marchello D, Hultman P, Viera M. et al. Adoption and meaningful use of computerized physician order entry with an integrated clinical decision support system for radiology: ten-year analysis in an urban teaching hospital. J Am Coll Radiol 2012; Feb 9 (Suppl. 02) 129-36.
• 94 Netherton SJ, Lonergan K, Wang D, McRae A, Lang E. Computerized physician order entry and decision support improves ED analgesic ordering for renal colic. Am J Emerg Med 2014; Sep 32 (Suppl. 09) 958-61.
• 95 Mazars N, Milési C, Carbajal R, Mesnage R, Combes C, Rideau Batista Novais A. et al. Implementation of a neonatal pain management module in the computerized physician order entry system. Ann Intensive Care 2012 Aug 22 2 (Suppl. 01) 38.
• 96 Theal J, Protti D. CPOE with evidence-based clinical decision support improves patient outcomes: the journey to date for a Canadian hospital. Healthc Q 2014; 17 (Suppl. 01) 24-9.
• 97 Cresswell KM, Bates DW, Williams R, Morrison Z, Slee A, Coleman J. et al. Evaluation of medium-term consequences of implementing commercial computerized physician order entry and clinical decision support prescribing systems in two ‘early adopter’ hospitals. J Am Med Inform Assoc 2014; Oct 21 e2 e194-202.
• 98 Jung M, Riedmann D, Hackl WO, Hoerbst A, Jaspers MW, Ferret L. et al. Physicians’ perceptions on the usefulness of contextual information for prioritizing and presenting alerts in Computerized Physician Order Entry systems. BMC Med Inform Decis Mak 2012 Oct 2 12: 111.
• 99 Webber EC, Warhurst HM, Smith SS, Cox EG, Crumby AS, Nichols KR. Conversion of a single-facility pediatric antimicrobial steward-ship program to multi-facility application with computerized provider order entry and clinical decision support. Appl Clin Inform 2013 Nov 27 4 (Suppl. 04) 556-68.
• 100 Pageler NM, Franzon D, Longhurst CA, Wood M, Shin AY, Adams ES. et al. Embedding time-limited laboratory orders within computerized provider order entry reduces laboratory utilization. Pediatr Crit Care Med 2013; May 14 (Suppl. 04) 413-9.
• 101 Yazer MH, Triulzi DJ, Reddy V, Waters JH. Effectiveness of a real-time clinical decision support system for computerized physician order entry of plasma orders. Transfusion 2013; Dec 53 (Suppl. 12) 3120-7.
• 102 Patterson ME, Marken PA, Simon SD, Hackman JL, Schaefer RS. Associations between the concurrent use of clinical decision support and computerized provider order entry and the rates of appropriate prescribing at discharge. Appl Clin Inform 2012 May 16 3 (Suppl. 02) 186-96.
• 103 Sampedro B, Hernandez-Lapez C, Ferrandiz JR, Illaro A, Fabrega E, Cuadrado A. et al. Computerized physician order entry-based system to prevent HBV reactivation in patients treated with biologic agents: the PRESCRIB project. Hepatology 2014; Jul 60 (Suppl. 01) 106-13.
• 104 Aita M, Belvedere O, De Carlo E, Deroma L, De Pauli F, Gurrieri L. et al. Chemotherapy prescribing errors: an observational study on the role of information technology and computerized physician order entry systems. BMC Health Serv Res 2013 Dec 17 13: 522.
• 105 Al-Rowibah FA, Younis MZ, Parkash J. The impact of computerized physician order entry on medication errors and adverse drug events. J Health Care Finance 2013; Fall 40 (Suppl. 01) 93-102.
• 106 Long AJ, Chang P. The effect of using the health smart card vs. CPOE reminder system on the prescribing practices of non-obstetric physicians during outpatient visits for pregnant women in Taiwan. Int J Med Inform 2012; Sep 81 (Suppl. 09) 605-11.
• 107 Jacobs BR, Hart KW, Rucker DW. Reduction in Clinical Variance Using Targeted Design Changes in Computerized Provider Order Entry (CPOE) Order Sets: Impact on Hospitalized Children with Acute Asthma Exacerbation. Appl Clin Inform 2012 Feb 8 3 (Suppl. 01) 52-63.
• 108 Davis L, Brunetti L, Lee EK, Yoon N, Cho SH, Suh DC. Effects of computerized physician order entry on medication turnaround time and orders requiring pharmacist intervention. Res Social Adm Pharm 2014; Sep-Oct 10 (Suppl. 05) 756-67.
• 109 Woods AD, Mulherin DP, Flynn AJ, Stevenson JG, Zimmerman CR, Chaffee BW. Clinical decision support for atypical orders: detection and warning of atypical medication orders submitted to a computerized provider order entry system. J Am Med Inform Assoc 2014; May-Jun 21 (Suppl. 03) 569-73.
• 110 Avansino J, Leu MG. Effects of CPOE on provider cognitive workload: a randomized crossover trial. Pediatrics 2012; Sep 130 (Suppl. 03) e547-52.
• 111 Kadakia KC, Leal AD, Seisler DK, Qin R, Fee-Schroeder KC, Grendahl DC. et al. Anti-emetic prescribing practices using a computerized physician order entry system. Support Care Cancer 2014; Jan 22 (Suppl. 01) 217-23.
• 112 Brunette DD, Tersteeg J, Brown N, Johnson V, Dunlop S, Karambay J. et al. Implementation of Computerized Physician Order Entry for Critical Patients in an Academic Emergency Department is Not Associated with a Change in Mortality Rate. West J Emerg Med 2013; Mar 14 (Suppl. 02) 114-20.
• 113 Teufel RJ, Kazley AS, Basco Jr. WT. Is computerized physician order entry use associated with a decrease in hospital resource utilization in hospitals that care for children?. J Med Syst 2012; Aug 36 (Suppl. 04) 2411-20.
• 114 Spaulding TJ, Raghu TS. Impact of CPOE Usage on Medication Management Process Costs and Quality Outcomes. Inquiry 2013; Aug 50 (Suppl. 03) 229-47.
• 115 Househ M, Ahmad A, Alshaikh A, Alsuweed F. Patient safety perspectives: the impact of CPOE on nursing workflow. Stud Health Technol Inform 2013; 183: 367-71.
• 116 Abramson EL, Kaushal R. Computerized provider order entry and patient safety. Pediatr Clin North Am 2012; Dec 59 (Suppl. 06) 1247-55.
• 117 Wright A, Feblowitz JC, Pang JE, Carpenter JD, Krall MA, Middleton B. et al. Use of order sets in inpatient computerized provider order entry systems: a comparative analysis of usage patterns at seven sites. Int J Med Inform 2012; Nov 81 (Suppl. 11) 733-45.
• 118 Hyman D, Laire M, Redmond D, Kaplan DW. The use of patient pictures and verification screens to reduce computerized provider order entry errors. Pediatrics 2012; Jul 130 (Suppl. 01) e211-9.
• 119 Pelayo S, Anceaux F, Rogalski J, Elkin P, Beuscart-Zephir MC. A comparison of the impact of CPOE implementation and organizational determinants on doctor-nurse communications and cooperation. Int J Med Inform 2013; Dec 82 (Suppl. 12) e321-30
• 120 Leung AA, Keohane C, Lipsitz S, Zimlichman E, Amato M, Simon SR. et al. Relationship between medication event rates and the Leapfrog computerized physician order entry evaluation tool. J Am Med Inform Assoc 2013; Jun 20 e1 e85-90.
• 121 Schneider E, Ruggieri P, Fromwiller L, Under-wood R, Gurland B, Yurkschatt C. et al. An electronic safety screening process during inpatient computerized physician order entry improves the efficiency of magnetic resonance imaging exams. Acad Radiol 2013; Dec 20 (Suppl. 12) 1592-7.
• 122 Knight AM, Kravet SJ, Kiyatkin D, Leff B. The effect of computerized provider order entry on medical students’ ability to write orders. Teach Learn Med 2012; 24 (Suppl. 01) 63-70.
• 123 Muzyk AJ, Rivelli SK, Jiang W, Heinz H, Ray-field A, Gagliardi JP. A computerized physician order entry set designed to improve safety of intravenous haloperidol utilization: a retrospective study in agitated hospitalized patients. Drug Saf 2012 Sep 1 35 (Suppl. 09) 725-31.
• 124 Peikari HR, Zakaria MS, Yasin NM, Shah MH, Elhissi A. Role of computerized physician order entry usability in the reduction of prescribing errors. Healthc Inform Res 2013; Jun 19 (Suppl. 02) 93-101.
• 125 Magid S, Forrer C, Shaha S. Duplicate orders: an unintended consequence of computerized provider/physician order entry (CPOE) implementation: analysis and mitigation strategies. Appl Clin Inform 2012 Oct 17 3 (Suppl. 04) 377-91.
• 126 Van der Veen W, de Gier HJ, van der Schaaf T, Taxis K, van den Bemt PM. Risk analysis and user satisfaction after implementation of computerized physician order entry in Dutch hospitals. Int J Clin Pharm 2013; Apr 35 (Suppl. 02) 195-201.
• 127 Schreiber R, Peters K, Shaha SH. Computerized provider order entry reduces length of stay in a community hospital. Appl Clin Inform 2014 Jul 30 5 (Suppl. 03) 685-98.
• 128 Hatfield MD, Cox R, Mhatre SK, Flowers WP, Sansgiry SS. Impact of computerized provider order entry on pharmacist productivity. Hosp Pharm 2014; May 49 (Suppl. 05) 458-65.
• 129 Alsweed F, Alshaikh A, Ahmed A, Yunus F, Househ M. Impact of computerised provider order entry system on nursing workflow, patient safety, and medication errors: perspectives from the front line. Int J Electron Healthc 2014; 7 (Suppl. 04) 287-300.
• 130 Bedouch P, Tessier A, Baudrant M, Labarere J, Foroni L, Calop J. et al. Computerized physician order entry system combined with on-ward pharmacist: analysis of pharmacists’ interventions. J Eval Clin Pract 2012; Aug 18 (Suppl. 04) 911-8.
• 131 Simon SR, Keohane CA, Amato M, Coffey M, Cadet B, Zimlichman E. et al. Lessons learned from implementation of computerized provider order entry in 5 community hospitals: a qualitative study. BMC Med Inform Decis Mak 2013 Jun 24 13: 67.
• 132 Hoonakker PL, Carayon P, Walker JM, Brown RL, Cartmill RS. The effects of Computerized Provider Order Entry implementation on communication in Intensive Care Units. Int J Med Inform 2013; May 82 (Suppl. 05) e107-17.
• 133 Castellanos I, Rellensmann G, Scharf J, Barkle T. Computerized Physician Order Entry (CPOE) in pediatric and neonatal intensive care: Recommendations how to meet clinical requirements. Appl Clin Inform 2012 Feb 15 3 (Suppl. 01) 64-79.
• 134 Chapman AK, Lehmann CU, Donohue PK, Aucott SW. Implementation of computerized provider order entry in a neonatal intensive care unit: Impact on admission workflow. Int J Med Inform 2012; May 81 (Suppl. 05) 291-5.
• 135 Jeon J, Taneva S, Kukreti V, Trbovich P, Easty AC, Rossos PG. et al. Toward successful migration to computerized physician order entry for chemotherapy. Curr Oncol 2014; Apr 21 (Suppl. 02) e221-8.
• 136 Nerich V, Borg C, Villanueva C, Thiery-Vuillemin A, Helias P, Rohrlich PS. et al. Economic impact of prescribing error prevention with computerized physician order entry of injectable antineoplastic drugs. J Oncol Pharm Pract 2013; Mar 19 (Suppl. 01) 8-17.
• 137 Meisenberg BR, Wright RR, Brady-Copertino CJ. Reduction in chemotherapy order errors with computerized physician order entry. J Oncol Pract 2014; Jan 10 (Suppl. 01) e5-9.
• 138 Hanauer DA, Zheng K, Commiskey EL, Duck MG, Choi SW, Blayney DW. Computerized prescriber order entry implementation in a physician assistant-managed hematology and oncology inpatient service: effects on workflow and task switching. J Oncol Pract 2013; Jul 9 (Suppl. 04) e103-14.
• 139 Yang JM, Park YS, Chung SP, Chung HS, Lee HS, You JS. et al. Implementation of a clinical pathway based on a computerized physician order entry system for ischemic stroke attenuates off-hour and weekend effects in the ED. Am J Emerg Med 2014; Aug 32 (Suppl. 08) 884-9.
• 140 Brokel JM, Ward MM, Wakefield DS, Ludwig A, Schwichtenberg T, Atherton D. Changing patient care orders from paper to computerized provider order entry-based process. Comput Inform Nurs 2012; Aug 30 (Suppl. 08) 417-25.
• 141 Cho I, Park H, Choi YJ, Hwang MH. Bates. Understanding the nature of medication errors in an ICU with a computerized physician order entry system. PLoS One 2014; Dec 19 9 (Suppl. 12) e114243.
• 142 Hundt AS, Adams JA, Schmid JA, Musser LM, Walker JM, Wetterneck TB. et al. Conducting an efficient proactive risk assessment prior to CPOE implementation in an intensive care unit. Int J Med Inform 2013; Jan 82 (Suppl. 01) 25-38.
• 143 Zimlichman E, Keohane C, Franz C, Everett WL, Seger DL, Yoon C. et al. Return on investment for vendor computerized physician order entry in four community hospitals: the importance of decision support. Jt Comm J Qual Patient Saf 2013; Jul 39 (Suppl. 07) 312-8.
• 144 Forrester SH, Hepp Z, Roth JA, Wirtz HS, De-vine EB. Cost-effectiveness of a computerized provider order entry system in improving medication safety ambulatory care. Value Health 2014; Jun 17 (Suppl. 04) 340-9.
• 145 Pettit RS, Zimmerman CR, Alaniz C, Dorsch MP. Cost analysis before and after implementation of a computerized physician order entry order form for enoxaparin. P&T 2012; Feb 37 (Suppl. 02) 107-11.
• 146 Slain T, Rickard-Aasen S, Pringle JL, Hegde GG, Shang J, Johnjulio W. et al. Incorporating screening, brief intervention, and referral to treatment into emergency nursing workflow using an existing computerized physician order entry/clinical decision support system. J Emerg Nurs 2014; Nov 40 (Suppl. 06) 568-74.
• 147 Gandhi S, Tyono I, Pasetka M, Trudeau M. Evaluating an oncology systemic therapy computerized physician order entry system using international guidelines. J Oncol Pract 2014; Mar 10 (Suppl. 02) e14-25.
• 148 Blankenship JF, Rogers L, White J, Carey A, Fosnocht D, Hopkins C. et al. Prospective evaluation of the treatment of pain in the ED using computerized physician order entry. Am J Emerg Med 2012; Oct 30 (Suppl. 08) 1613-6.
• 149 Ranji SR, Rennke S, Wachter RM. Computerised provider order entry combined with clinical decision support systems to improve medication safety: a narrative review. BMJ Qual Saf 2014; 23: 773-780.
• 150 Cowan L. Literature review and risk mitigation strategy for unintended consequences of computerized physician order entry. Nurs Econ 2013; Jan-Feb 31 (Suppl. 01) 27-31.
• 151 Belle A, Kon MA, Najarian K. Biomedical informatics for computer-aided decision support systems: a survey. ScientificWorldJournal 2013; 2013: 769639.
• 152 Miller AC, Ziad-Miller A, Elamin EM. Brain death and Islam: the interface of religion, culture, history, law, and modern medicine. Chest 2014; Oct 146 (Suppl. 04) 1092-101.
• 153 Paternotte E, van Dulmen S, van der Lee N, Scherpbier AJ, Scheele F. Factors influencing intercultural doctor-patient communication: a realist review. Patient Educ Couns 2015; Apr 98 (Suppl. 04) 420-45.
• 154 Peleg M. Computer-interpretable clinical guidelines: a methodological review. J Biomed Inform 2013; Aug 46 (Suppl. 04) 744-63.
• 155 Wang D, Peleg M, Tu SW, Boxwala AA, Ogunyemi O, Zeng Q. Greenes et al. Design and Implementation of the GLIF3 guideline execution engine. J Biomed Inform 2004; 37 (Suppl. 03) 305318.
• 156 Sutton DR, Fox J. The Syntax and Semantics of the PROforma guideline modelling language. J Am Med Inform Assoc 2003; SepOct 10 (Suppl. 05) 433-43.
• 157 Rucker DW, Steele AW, Douglas IS, Couderc CA, Hardel GG. Design and Use of a Joint Order Vocabulary Knowledge Representation Tier in a Multi-tier CPOE Architecture. AMIA Annu Symp Proc 2006; 669-73.
• 158 Charani E, Kyratsis Y, Lawson W, Wickens H, Brannigan ET, Moore LS. et al. An analysis of the development and implementation of a smartphone application for the delivery of antimicrobial prescribing policy: lessons learnt. J Antimicrob Chemother 2013; Apr 68 (Suppl. 04) 960-7.
• 159 Lanzola G, Parimbelli E, Micieli G, Cavallini A, Quaglini S. Data quality and completeness in a web stroke registry as the basis for data and process mining. J Healthc Eng 2014; 5 (Suppl. 02) 163-84.
• 160 Beuscart-Zéphir MC, Borycki E, Carayon P, Jaspers MW, Pelayo S. Evolution of human factors research and studies of health information technologies: the role of patient safety. Yearb Med Inform 2013; 8 (Suppl. 01) 67-77.
• 161 Chiarella M, Carney T, Chiarella M, Satchell C, Walton M, Bennett B. et al. Regulating health-care complaints: a literature review. Int J Health Care Qual Assur 2014; 27 (Suppl. 06) 505-18.
• 162 García-Sáez G, Rigla M, Martínez-Sarriegui I, Shalom E, Peleg M, Broens T. et al. Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes. J Diabetes Sci Technol 2014 Mar 6 8 (Suppl. 02) 238-46.
• 163 Sacchi L, Rubrichi S, Rognoni C, Panzarasa S, Parimbelli E, Mazzanti A. et al. From decision to shared-decision: Introducing patients’ preferences into clinical decision analysis. Artif Intell Med 2014 [Epub ahead of print].
• 164 Quaglini S, Shahar Y, Peleg M, Miksch S, Napolitano C, Rigla M. et al. Supporting shared decision making within the MobiGuide project. AMIA Annu Symp Proc 2013 Nov 16 2013: 1175-84.
• 165 Roshanov PS, Fernandes N, Wilczynski JM, Hemens BJ, You JJ, Handler SM. et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ 2013; Feb 14 346.
• 166 Shay LA, Lafata JE. Where is the evidence? A systematic review of shared decision making and patient outcomes. Med Decis Making 2015; Jan 35 (Suppl. 01) 114-31.
• 167 Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR. et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med 2012 Jul 3 157 (Suppl. 01) 29-43.
• 168 McDermott MS, While AE. Maximizing the healthcare environment: a systematic review exploring the potential of computer technology to promote self-management of chronic illness in healthcare settings. Patient Educ Couns 2013; Jul 92 (Suppl. 01) 13-22.