Figure . Methods depend on the types of investigation. There are three levels of investigation for clinical safety incidents in the Victorian Health Incident Management System.(12) Literature review methods The published and grey literature about current HIT methods of incident investigation was reviewed. Bibliographic databases including Scopus, PubMed and Science Citation Index Expanded from January 2004 to May 2016 were searched. Only English language case studies and analyses of HIT incidents were included. After titular and abstract review, papers were selected for full review. Grey literature was identified by searching the websites of international patient safety agencies and programs such as the US Agency for Healthcare Research and Quality. A narrative synthesis was used to integrate findings into descriptive summaries. Relevant frameworks for studying the safety of HIT were also examined. Findings: Descriptive analysis of all investigations Our search identified 21 investigations of HIT incidents (Appendix A: Summary of the 21 studies investigating HIT incidents). Most of these were aggregate reviews of incidents from a broad range of clinical settings in six countries including the USA, UK, the Netherlands, China, Hong Kong and Australia (86%, n=18). About half (n=10, 48%) involved a range of HIT systems, 33% (n=7) were focused on medication management systems and one related to radiology information systems. Of the 21 investigations, three were in-depth reviews from inpatient settings in the USA. Of these, two related to medications management systems including order entry and bar-coding (13,14) and the other involved an image viewer to track patients in an Emergency Department.(15) Sixteen investigations examined patient outcomes (76%). In 15 of these, there were reports of patient harm and one case study related to a near-miss event (Appendix A: Summary of
Appendix A: Summary of the 21 studies investigating HIT incidents Authors (year) Study period (mths) Source/ case study Country Settings HIT types N Harm, % (death, n) Case study/ incident analyses methods R: reporting format HIT: problem categories C: consequences Summary of findings Horsky et al. (2005) (13) case study USA inpatient CPOE 1 1 - semi-structured interviews with involved clinicians - computer log analysis - usability inspection of CPOE interface - quality assurance reports - case & review notes by Significant Events Committee An elderly patient suffering from hypokalemia or low potassium (serum potassium was 3.1 mEq/L; creatinine, 1.7) became severely hyperkalemic (serum potassium level, 7.8 mEq/L). Wrong, incomplete and missing information in the hospital order entry system resulted in the patient receiving multiple doses of potassium. In total, 316 mEq potassium chloride (KCl) was administered over 42 hours. Technical problems related to software functionality such as suboptimal screen display and lack of automated checking function. Human factors issues were linked with inadequate training and poor familiarity with the system. Landman et al. (2013) (14) case study USA inpatient ED- Image viewer N/A computer log analysis An update to Microsoft Internet Explorer severed the link between the ED tracking board and web-based image viewer. The loss of this link resulted in decreased image viewer access rates for ED patients during the 10 days of the incident (2.8 views/study) compared with image review rates for a similar 10-day period preceding this event (3.8 views/study, p<0.001).
McDonald et al. (2006) (15) case study USA inpatient CPOE 1 - - medical case history - root-cause analyses - interviews with involved patients and clinicians Computerised bar-coding patient identification system was associated with a near miss. Human factor issues involved rule violation and integration with workflow such as missing verbal confirmation of patient identification and entering wrong information into a system. Castro et al. (2016) (23) (42) Sentinel events to The Joint Commission USA inpatient, EHR, CPOE, eMAR, PIS, CDS, imaging, peripheral device, billing, AutoDisp, LIS 120 125^ (66) R: voluntary reports + RCA findings HIT: 4 schemas -AHRQ Common Formats -AHRQ Hazard Manager ontology - Magrabi et al. classification - Sittig and Singh’s sociotechnical model C: 15 categories of sentinel events 120 HIT-related sentinel events from 3,375 reported affecting 125 patients. Contributing factors were most frequently associated with the human-computer interface, workflow and communication, and clinical content–related issues. The three most frequently identified event types were (1) medication errors, (2) wrong-site surgery (including the wrong side, wrong procedure, and wrong patient), and (3) delays in treatment. Cheung et al. (2013) (31) (12) Dutch central medication incidents registration (CMR) The inpatient, outpatient pharmacy CPOE, EHR, AutoDisp, PIS, Infusion pump, eMAR 668 58% (2) R: CMR database HIT: - Magrabi et al. classification - phases of medication process Half of the incidents were associated with use error related wrong entry to the system. Technical problems related to poor design of screens were associated with the most incidents in community pharmacies for choosing the wrong medicine. 2013
concerns (1) Myers et al. (2011) (27) (216) Equipment failure & hazards reported to the FDA USA inpatient All HIT 120 Patient harm including injury, disability and deaths noted but number not specified R: investigations completed by Informatics Patient Safety Office of the Veterans Health Administration HIT: - Sittig and Singh’s sociotechnical model - phases of EHR implementation C: not examined 12 technical problems related to software functionality and system downtime. Consequences reported including delays in diagnosis or treatments, unnecessary or emergency procedures and/or treatment. Samaranayake et al. (2012) (103) (60) incident reporting system Hong Kong inpatient, outpatient CPOE EHR AutoDisp, 243 11 (none reported) R: ad hoc HIT: ad hoc C: reporter classified, local coding scheme Most medication errors related to prescribing and were caused by human factors issues. While, most were detected before reaching the patient, 11% of medication errors reached the patient. 6.1% of the errors reached patients causing minor injury and temporary morbidity requiring intervention. Santell et al. (2009) (28) (54) US MEDMARX USA inpatient, outpatient, long-term care CPOE 43 (3) R: MEDMARX, Uni of Pittsburgh Medical Centre HIT: ad hoc C: reporter classified, National Coordinating Study focussed on medication errors in hybrid systems where manual systems were used in combination with CPOE to process medication orders. Use errors such as partial/omitted typing and rule violations were reported to be the leading cause of prescribing errors.
Council for Medication Error Reporting and Prevention’s (NCC MERP) Index for Categorizing Medication Errors. Schiff et al. (2015) (29) (88) US MEDMARX USA inpatient, outpatient CPOE N/A R: MEDMARX HIT: ad hoc C: not examined Majority of CPOE related medication incidents were associated with use errors during completing prescribing orders. Human factors issues involved rule violation, lack of system and clinical knowledge, and communication issues. Technical problems related to system functionality, interface with other system, and hybrid systems. Stewart et al. (2012) (104) (82) incident reporting system Australia inpatient Radiology systems 21 N/A R: Incident Information Management System (IIMS) HIT: WHO International Classification for Patient Safety (ICPS) C: not examined Most of the HIT-related radiology incidents were associated with human-machine interaction, occurring at data entry, transferring, and output. Incidents also involved use error such as uploading wrong file and duplicated test orders. Warm et al. (2012) (24) (29) State-based patient safety incident reporting system UK inpatient, outpatient, mental health, general practice All HIT 149 34 (none reported) R: National Reporting and Learning System (NRLS), Wales HIT: Magrabi et al. classification C: reporter classified using NRLS categories 77% linked to technical problems e.g. access issues, computer system down/too slow, display issues, and software malfunction. 10% involving human-machine interaction.
Zhan et al. (2006) (30) 2003 (8) US MEDMARX USA inpatient, outpatient CPOE 7,029 5 (none reported) R: MEDMARX HIT: ad hoc C: National Coordinating Council for Medication Error Reporting and Prevention’s (NCC MERP) Index for Categorizing Medication Errors. Technical problems related to faulty computer interface, miscommunication with other systems and inadequate decision support. Human factors issues involved knowledge deficit, distractions, inexperience and data entry errors. ECRI Institute (20) (1.5) Incident reporting study - Deep Dive USA 36 inpatient and outpatient settings EHR, CPOE, eMAR, PIS, CDS, imaging, peripheral device, billing, AutoDisp, LIS 171 6 (3) R: AHRQ’s Common Formats (version 1.2) HIT: Magrabi et al. classification C: reporter classified using National Coordinating Council for Medication Error Reporting and Prevention’s (NCC MERP) Index for Categorizing Medication Errors. 211 HIT problems in 28 categories 56% machine-related 44% human-factors issues A (circumstance that has the capacity to cause harm): 25, 15% B (error occurs but does not reach the patient): 15, 9% C (error reaches the patient but does not cause harm): 52, 30% D (error reaches the patient and requires monitoring to confirm no harm and/or intervention required): 24, 14% E (error contributes to or results in temporary harm to the patient and requires intervention): 3, 2% F (error contributes to or results in temporary harm and requires initial or prolonged hospitalization): 1, 1% G (error contributes to or results in permanent patient harm): 0, 0% H (error requires intervention to sustain life): 1, 1%
I (error may have contributed to or resulted in patient’s death): 3, 2% Pennsylvania Patient Safety Authority (25) 2012 State-based patient safety incident reporting system USA inpatient, outpatient EHR 3,099 0% (1) R: Pennsylvania Patient Safety Reporting System (PA-PSRS). HIT: Magrabi et al. classification C: reporter classified using National Coordinating Council for Medication Error Reporting and Prevention’s (NCC MERP) Index for Categorizing Medication Errors. Majority of EHR-related reports involved errors in human data entry, such as entry of “wrong” data or the failure to enter data, and a few reports indicated technical failures on the part of the EHR system. Incident: Unsafe Conditions (A)= 320, 10% Incident: No Harm (B1-D) =2763, 89% Serious Event: Temporary Harm (E-F)=15, 0% Serious Event: Significant Harm (G-I)= 1, 0% *consequences were available for 68 incidents. Abbreviations: HIT: health information technology; Observ: Observational study ; CPOE: computerised provider order entry; EHR: electronic health record; ePS: electronic prescribing system; CDS: clinical decision support; ADS: automated dispensing system; AutoDisp: automated dispensation of medication; eMAR electronic medication administration record; AED: automated error detection system; PIC: Pharmacy information system; LIS: laboratory information system.