Decision Support Tools within the Electronic Health Record.

Laboratory tests are an integral part of the electronic health record (EHR). Providing clinical decision support (CDS) for the ordering, collection, reporting, viewing, and interpretation of laboratory testing is a fundamental function of the EHR. The implementation of a sustainable, effective laboratory CDS program requires a commitment to standardization and harmonization of the laboratory dictionaries that are the foundation of laboratory-based CDS. In this review, the authors provide an overview of the tools available within the EHR to improve decision making throughout the entire laboratory testing process, from test order to clinical action.

[1]  R. Schreiber,et al.  Computerised provider order entry adoption rates favourably impact length of stay , 2016, BMJ Health & Care Informatics.

[2]  W. Greg Miller,et al.  Harmonization: the Sample, the Measurement, and the Report , 2014, Annals of laboratory medicine.

[3]  Ramin Khorasani,et al.  An initiative to improve the management of clinically significant test results in a large health care network. , 2013, Joint Commission journal on quality and patient safety.

[4]  Julian H Barth,et al.  Detection of patients with acute kidney injury by the clinical laboratory using rises in serum creatinine: comparison of proposed definitions and a laboratory delta check , 2012, Annals of clinical biochemistry.

[5]  John Fontanesi,et al.  Decoding Laboratory Test Names: A Major Challenge to Appropriate Patient Care , 2012, Journal of General Internal Medicine.

[6]  D. Triulzi,et al.  Trends in RBC ordering and use after implementing adaptive alerts in the electronic computerized physician order entry system. , 2014, American journal of clinical pathology.

[7]  Christiana A Naaktgeboren,et al.  Reducing Test Utilization in Hospital Settings: A Narrative Review , 2018, Annals of laboratory medicine.

[8]  K. Shojania,et al.  ORDER SETS IN HEALTH CARE: A SYSTEMATIC REVIEW OF THEIR EFFECTS , 2012, International Journal of Technology Assessment in Health Care.

[9]  R. Schreiber,et al.  Computerized provider order entry reduces length of stay in a community hospital. , 2014, Applied clinical informatics.

[10]  David W. Bates,et al.  Clinical decision support alert malfunctions: analysis and empirically derived taxonomy , 2017, J. Am. Medical Informatics Assoc..

[11]  J. Szymanski,et al.  Clinical decision support for hematology laboratory test utilization , 2017, International journal of laboratory hematology.

[12]  Rema Padman,et al.  Reducing Provider Cognitive Workload in CPOE Use: Optimizing Order Sets , 2013, MedInfo.

[13]  Elizabeth M. Van Cott Laboratory test interpretations and algorithms in utilization management. , 2014 .

[14]  Andrew Georgiou,et al.  Does Computerised Provider Order Entry Reduce Test Turnaround Times? A Before-and-After Study at Four Hospitals , 2009, MIE.

[15]  Anand S Dighe,et al.  Physician survey of a laboratory medicine interpretive service and evaluation of the influence of interpretations on laboratory test ordering. , 2004, Archives of pathology & laboratory medicine.

[16]  Anand S Dighe,et al.  Creation and Use of an Electronic Health Record Reporting Database to Improve a Laboratory Test Utilization Program , 2018, Applied Clinical Informatics.

[17]  C. Atlin,et al.  Path of least resistance: how computerised provider order entry can lead to (and reduce) wasteful practices , 2018, BMJ open quality.

[18]  Matthew Wolf,et al.  The process of development of a prioritization tool for a clinical decision support build within a computerized provider order entry system: Experiences from St Luke’s Health System , 2016, Health Informatics J..

[19]  Andrew A White,et al.  Use of a computer-based provider order entry (CPOE) intervention to optimize laboratory testing in patients with suspected heparin-induced thrombocytopenia. , 2015, Thrombosis research.

[20]  Dylan S. Small,et al.  Effect of a Price Transparency Intervention in the Electronic Health Record on Clinician Ordering of Inpatient Laboratory Tests: The PRICE Randomized Clinical Trial , 2017, JAMA internal medicine.

[21]  Frank Fear Governance first, technology second to effective CPOE deployment: rapid development of order sets provides the foundation for CPOE, but healthcare organizations first need an effective governance plan built around clinician workflow. , 2011, Health management technology.

[22]  S. Richter,et al.  Implementation of a Clinical Decision Support Tool for Stool Cultures and Parasitological Studies in Hospitalized Patients , 2017, Journal of Clinical Microbiology.

[23]  Irina K Kamis,et al.  Analysis of Daily Laboratory Orders at a Large Urban Academic Center: A Multifaceted Approach to Changing Test Ordering Patterns , 2017, American journal of clinical pathology.

[24]  Ling Li,et al.  Impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: a systematic review and meta-analysis , 2017, J. Am. Medical Informatics Assoc..

[25]  Dean F. Sittig,et al.  Order sets in computerized physician order entry systems: an analysis of seven sites. , 2010, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[26]  James M. Hoffman,et al.  Alert dwell time: introduction of a measure to evaluate interruptive clinical decision support alerts , 2016, J. Am. Medical Informatics Assoc..

[27]  Jessica S. Ancker,et al.  Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system , 2017, BMC Medical Informatics and Decision Making.

[28]  Adam Wright,et al.  Orders on file but no labs drawn: investigation of machine and human errors caused by an interface idiosyncrasy , 2017, J. Am. Medical Informatics Assoc..

[29]  L. Howell,et al.  Can automated alerts within computerized physician order entry improve compliance with laboratory practice guidelines for ordering Pap tests? , 2014, Journal of pathology informatics.

[30]  James H Nichols,et al.  Quality in point-of-care testing , 2003, Expert review of molecular diagnostics.

[31]  Johanna I. Westbrook,et al.  Alert override as a habitual behavior - a new perspective on a persistent problem , 2017, J. Am. Medical Informatics Assoc..

[32]  Mario Plebani,et al.  Harmonization in laboratory medicine: Requests, samples, measurements and reports , 2016, Critical reviews in clinical laboratory sciences.

[33]  Michael G Leu,et al.  Effects of CPOE on Provider Cognitive Workload: A Randomized Crossover Trial , 2012, Pediatrics.

[34]  Parag H Mehta,et al.  Use of Electronic Clinical Decision Support and Hard Stops to Decrease Unnecessary Thyroid Function Testing , 2017, BMJ quality improvement reports.

[35]  Hannu Kautiainen,et al.  Altering a computerized laboratory test order form rationalizes ordering of laboratory tests in primary care physicians , 2016, Int. J. Medical Informatics.

[36]  Eduardo Iturrate,et al.  Optimize Your Electronic Medical Record to Increase Value: Reducing Laboratory Overutilization. , 2016, The American journal of medicine.

[37]  Jorie M. Colbert-Getz,et al.  Impact of Laboratory Charge Display Within the Electronic Health Record Across an Entire Academic Medical Center: Results of a Randomized Controlled Trial , 2017, American journal of clinical pathology.

[38]  J. Baron,et al.  Computerized provider order entry in the clinical laboratory , 2011, Journal of pathology informatics.

[39]  Shalini Batra,et al.  A novel class of laboratory middleware. Promoting information flow and improving computerized provider order entry. , 2010, American journal of clinical pathology.

[40]  L. Feldman,et al.  Impact of nonintrusive clinical decision support systems on laboratory test utilization in a large academic centre , 2018, Journal of evaluation in clinical practice.

[41]  Impact of Continuous Improvement of Laboratory Test Result Comments on Requests for Consultation:  A Case Series. , 2016, American journal of clinical pathology.

[42]  Chad D. Meyerhoefer,et al.  “Reducing unnecessary testing in a CPOE system through implementation of a targeted CDS intervention” , 2013, BMC Medical Informatics and Decision Making.

[43]  Anand S Dighe,et al.  Enhanced creatinine and estimated glomerular filtration rate reporting to facilitate detection of acute kidney injury. , 2015, American journal of clinical pathology.

[44]  Ian Chin-Yee,et al.  Reducing inappropriate ESR testing with computerized clinical decision support , 2016, BMJ quality improvement reports.

[45]  D. Chadwick,et al.  A feasibility study for a clinical decision support system prompting HIV testing , 2017, HIV medicine.

[46]  Erich J. Greene,et al.  Impact of Cost Display on Ordering Patterns for Hospital Laboratory and Imaging Services , 2018, Journal of General Internal Medicine.

[47]  Brett W. Sadowski,et al.  High-Value, Cost-Conscious Care: Iterative Systems-Based Interventions to Reduce Unnecessary Laboratory Testing. , 2017, The American journal of medicine.

[48]  Andrew Georgiou,et al.  The use of computerized provider order entry to improve the effectiveness and efficiency of coagulation testing. , 2011, Archives of pathology & laboratory medicine.

[49]  Joan S. Ash,et al.  Recommendations for Monitoring and Evaluation of In-Patient Computer-based Provider Order Entry Systems: Results of a Delphi Survey , 2007, AMIA.

[50]  Gary W Procop,et al.  The Impact of an Electronic Expensive Test Notification , 2018, American journal of clinical pathology.

[51]  Christopher L. Roy,et al.  Patient Safety Concerns Arising from Test Results That Return after Hospital Discharge , 2005, Annals of Internal Medicine.

[52]  Christian Lovis,et al.  Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review , 2018, JMIR medical informatics.

[53]  Margaret A. Ardolino,et al.  Impact of providing fee data on laboratory test ordering: a controlled clinical trial. , 2013, JAMA internal medicine.

[54]  Anand S Dighe,et al.  Utilization management in a large urban academic medical center: a 10-year experience. , 2011, American journal of clinical pathology.

[55]  Jason Lam,et al.  Monitoring clinical decision support in the electronic health record. , 2017, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

[56]  Natalie M. Pageler,et al.  Use of a Checklist and Clinical Decision Support Tool Reduces Laboratory Use and Improves Cost , 2016, Pediatrics.

[57]  P. Perrotta,et al.  Quality Improvement Intervention for Reduction of Redundant Testing , 2017, Academic pathology.

[58]  Adam Wright,et al.  Use of order sets in inpatient computerized provider order entry systems: A comparative analysis of usage patterns at seven sites , 2012, Int. J. Medical Informatics.

[59]  Carlos Manuel Silva Martins,et al.  The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - a randomized controlled trial , 2017, BMC Medical Informatics and Decision Making.

[60]  Eileen Yoshida,et al.  The Value of Monitoring Clinical Decision Support Interventions , 2018, Applied Clinical Informatics.

[61]  David W. Bates,et al.  Top ten challenges when interfacing a laboratory information system to an electronic health record: Experience at a large academic medical center , 2017, Int. J. Medical Informatics.

[62]  Gary W Procop,et al.  Reducing duplicate testing: a comparison of two clinical decision support tools. , 2015, American journal of clinical pathology.

[63]  Mario Plebani,et al.  Promoting clinical and laboratory interaction by harmonization. , 2014, Clinica chimica acta; international journal of clinical chemistry.

[64]  F. Apple,et al.  Electronic medical record-based performance improvement project to document and reduce excessive cardiac troponin testing. , 2015, Clinical chemistry.

[65]  David W Bates,et al.  "I wish I had seen this test result earlier!": Dissatisfaction with test result management systems in primary care. , 2004, Archives of internal medicine.

[66]  D. Triulzi,et al.  Evaluation of real-time clinical decision support systems for platelet and cryoprecipitate orders. , 2014, American journal of clinical pathology.

[67]  T. Bishop,et al.  The Effect of Charge Display on Cost of Care and Physician Practice Behaviors: A Systematic Review , 2015, Journal of General Internal Medicine.

[68]  Daniel Z. Fang,et al.  Cost and turn-around time display decreases inpatient ordering of reference laboratory tests: a time series , 2014, BMJ quality & safety.

[69]  K. Ekblom,et al.  Introduction of cost display reduces laboratory test utilization. , 2018, The American journal of managed care.

[70]  Michael Blechner,et al.  Analysis of search in an online clinical laboratory manual. , 2006, American journal of clinical pathology.

[71]  J. Marc Overhage,et al.  Research Paper: A Randomized Trial of "Corollary Orders" to Prevent Errors of Omission , 1997, J. Am. Medical Informatics Assoc..

[72]  Rema Padman,et al.  Data-driven Order Set Generation and Evaluation in the Pediatric Environment , 2012, AMIA.

[73]  Michael L Astion,et al.  Improving the value of costly genetic reference laboratory testing with active utilization management. , 2014, Archives of pathology & laboratory medicine.

[74]  N. Dunbar,et al.  Hardwiring patient blood management: harnessing information technology to optimize transfusion practice , 2014, Current opinion in hematology.

[75]  Thomas Abendroth,et al.  Default settings of computerized physician order entry system order sets drive ordering habits , 2015, Journal of pathology informatics.

[76]  Anand S. Dighe,et al.  A novel strategy for evaluating the effects of an electronic test ordering alert message: Optimizing cardiac marker use , 2012, Journal of pathology informatics.

[77]  Matthew L. Rubinstein,et al.  Effectiveness of Practices to Support Appropriate Laboratory Test Utilization , 2018, American journal of clinical pathology.

[78]  Jacquelyn D. Riley,et al.  Improving Molecular Genetic Test Utilization through Order Restriction, Test Review, and Guidance. , 2015, The Journal of molecular diagnostics : JMD.

[79]  Gary W Procop,et al.  Duplicate laboratory test reduction using a clinical decision support tool. , 2014, American journal of clinical pathology.

[80]  A. Jaffe,et al.  Implementation of Clinical Decision Support Rules to Reduce Repeat Measurement of Serum Ionized Calcium, Serum Magnesium, and N-Terminal Pro-B-Type Natriuretic Peptide in Intensive Care Unit Inpatients. , 2016, Clinical chemistry.