Implementing a New Electronic Health Record System in a University Hospital : The Effect on Reported Medication Errors

Closed-loop electronic medication management systems (EMMS) have been seen as a potential technology to prevent medication errors (MEs), although the research on them is still limited. The aim of this paper was to describe the changes in reported MEs in Helsinki University Hospital (HUS) during and after implementing an EPIC-based electronic health record system (APOTTI), with the first features of a closed-loop EMMS. MEs reported from January 2018 to May 2021 were analysed to identify changes in ME trends with quantitative analysis. Severe MEs were also analysed via qualitative content analysis. A total of 30% (n = 23,492/79,272) of all reported patient safety incidents were MEs. Implementation phases momentarily increased the ME reporting, which soon decreased back to the earlier level. Administration and dispensing errors decreased, but medication reconciliation, ordering, and prescribing errors increased. The ranking of the TOP 10 medications related to MEs remained relatively stable. There were 92 severe MEs related to APOTTI (43% of all severe MEs). The majority of these (55%, n = 53) were related to use and user skills, 24% (n = 23) were technical failures and flaws, and 21% (n = 21) were related to both. Using EMMS required major changes in the medication process and new technical systems and technology. Our medication-use process is approaching a closed-loop system, which seems to provide safer dispensing and administration of medications. However, medication reconciliation, ordering, and prescribing still need to be improved.Peer reviewe

Implementing a New Electronic Health Record System in a University Hospital : The Effect on Reported Medication Errors

Closed-loop electronic medication management systems (EMMS) have been seen as a potential technology to prevent medication errors (MEs), although the research on them is still limited. The aim of this paper was to describe the changes in reported MEs in Helsinki University Hospital (HUS) during and after implementing an EPIC-based electronic health record system (APOTTI), with the first features of a closed-loop EMMS. MEs reported from January 2018 to May 2021 were analysed to identify changes in ME trends with quantitative analysis. Severe MEs were also analysed via qualitative content analysis. A total of 30% (n = 23,492/79,272) of all reported patient safety incidents were MEs. Implementation phases momentarily increased the ME reporting, which soon decreased back to the earlier level. Administration and dispensing errors decreased, but medication reconciliation, ordering, and prescribing errors increased. The ranking of the TOP 10 medications related to MEs remained relatively stable. There were 92 severe MEs related to APOTTI (43% of all severe MEs). The majority of these (55%, n = 53) were related to use and user skills, 24% (n = 23) were technical failures and flaws, and 21% (n = 21) were related to both. Using EMMS required major changes in the medication process and new technical systems and technology. Our medication-use process is approaching a closed-loop system, which seems to provide safer dispensing and administration of medications. However, medication reconciliation, ordering, and prescribing still need to be improved.Peer reviewe

Dose error reduction software in medication safety risk management - optimising the smart infusion pump dosing limits in neonatal intensive care unit prior to implementation

Background Smart infusion pumps with dose error reduction software can be used to prevent harmful medication errors. The aim of this study was to develop a method for defining and assessing optimal dosing limits in a neonatal intensive care unit's smart infusion pump drug library by using simulation-type test cases developed based on medication error reports. Methods This mixed-methods study applied both qualitative and quantitative methods. First, wrong infusion rate-related medication errors reported in the neonatal intensive care unit during 2018-2019 were explored by quantitative descriptive analysis and qualitative content analysis to identify the error mechanisms. The researchers developed simulation-type test cases with potential errors, and a literature-based calculation formula was used to set upper soft limits to the drug library. The limits were evaluated by conducting programming of pumps without errors and with potential errors for two imaginary test patients (1 kg and 3.5 kg). Results Of all medication errors reported in the neonatal intensive care unit, 3.5% (n = 21/601) involved an error or near-miss related to wrong infusion rate. Based on the identified error mechanisms, 2-, 5-, and 10-fold infusion rates, as well as mix-ups between infusion rates of different drugs, were established as test cases. When conducting the pump programming for the test cases (n = 226), no alerts were triggered with infusion rates responding to the usual dosages (n = 32). 73% (n = 70/96) of the erroneous 2-, 5-, and 10-fold infusion rates caused an alert. Mix-ups between infusion rates triggered an alert only in 24% (n = 24/98) of the test cases. Conclusions Simulation-type test cases can be applied to assess the appropriateness of dosing limits within the neonatal intensive care unit's drug library. In developing the test cases, combining hospital's medication error data to other prospective data collection methods is recommended to gain a comprehensive understanding on mechanisms of wrong infusion rate errors. After drug library implementation, the alert log data and drug library compliance should be studied to verify suitability of dosing limits.Peer reviewe

Lääkehoitoa toteutetaan monessa eri toimintaympäristössä

Teema : riskilääkkeet – onko niitä

Apteekkien lääkityksen tarkistuspalvelussa tunnistetut asiakkaiden itsehoitovalmisteiden käyttöön liittyvät ongelmat lääkehoidoissa

English summaryPeer reviewe

Tieto lääkityksestä on turvallisen hoidon perusta

Ajantasainen tieto lääkityksestä löytyy vain harvoin valmiina tietojärjestelmistä. Olennaista on, kuinka potilas todellisuudessa käyttää lääkkeitään

"Vaaralliset" lääkkeet

Korjattu 12.12.2017 ks. oikaisu www.laakarilehti.fi > SisällysluettelotLääkkeitä, joiden käyttöön liittyy erityisiä turvallisuusriskejä, kutsutaan riskilääkkeiksi tai suuren riskin lääkkeiksi. Vaikka ne eivät välttämättä aiheuta enempää vaaratapahtumia kuin muutkaan lääkkeet, virheellisen käytön seuraukset ovat todennäköisemmin vakavia

Severe medication errors - A challenge for patient safety

A medication error (ME) is any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer. Severe medication errors are the most unwanted outcome of the medication use process causing severe harm or even being fatal to the patient. Considering how common intervention medication treatment is in health care, and how many people use medicines daily, severe MEs are relatively rare. Still, they are an untenable global burden from individual patient and professional, public health, and economic perspectives. Although severe MEs typically occur because of complex error processes, including multiple errors and contributing factors, their preventability may have great potential. For successful prevention, we need to understand error processes and learn from them using different kinds of ME data and analysis methods to build up safer practices and systemic defenses for prospective risk management. This doctoral thesis study aimed to have insights into severe MEs to find ways to learn from them and prevent them. The thesis consists of three studies, two focusing on analyzing and developing methods to investigate severe ME data derived from a national authority register (Studies I, II). The third study evaluated the implementation process of selected safe medication practices in hospitals within 11 EU countries, focusing on facilitators and barriers to implementation (Study III). System-based risk management approach to human error by Reason was applied as a theoretical framework. Studies I and II were based on retrospective document analysis of medication-related complaints and authoritative statements investigated by the National Supervisory Authority for Welfare and Health (Valvira) in Finland in 2013-2017 (n=58). The goal was to evaluate how the extensive incident documentation gathered for authority purposes applies to learning from severe MEs. Study I investigated characteristics of severe MEs reported to Valvira, the error processes, settings, and the preventability of errors. The majority (83%, n=48/58) of the incidents concerned patients over 60 years. Most likely the errors occurred in prescribing (n=38; 47%), followed by administration (n=15, 19%) and monitoring (n=14, 17%). The error process often included multiple failures (n=24; 41%) or health care professionals (n=16; 28%). Antithrombotic agents (n=17; 13%), opioids (n=10, 8%), and antipsychotics (n=10, 8%) were the therapeutic groups most involved in the errors. Almost all error cases (91%, n=53) were assessed as likely or potentially preventable. In 60% (n=35) of the cases, the organization reported actions taken to improve medication safety after the occurrence of the investigated incident. Although several classification systems for MEs have been established, they do not apply well to classifying severe MEs. Therefore, Study II focused on exploring the applicability of a cause-based drug-related problem (DRP) classification system by Basger et al. (2015) for classifying severe MEs. In total, 100 MEs were identified from Valvira’s ME case reports (n=58) by using the Basger et al. DRP classification system. In 53% (n=31) of the cases, more than one ME was identified, with the mean number of MEs identified being 1.7 per case. It was possible to classify all MEs according to aggregated DRP system, and only a small proportion (8%, n=8) were classified in the category “Other,” indicating that the cause of the ME could not be classified as a specific cause-based category. Study III was carried out as part of the European Network for Patient Safety (EUNetPas) project in 2008-2010. The objective was to investigate facilitators and barriers in the implementation process of seven selected medication safety practices (MSPs). The selected practices were: two different versions of medicine bed dispensation; safety vest; discharge medication list for patients; medication reconciliation at patient discharge; medication reconciliation at patient admission and patient discharge; and sleep card. The MSPs were implemented across 55 hospitals within 11 European Union countries that participated in the project. The participating hospitals submitted an evaluation report (n=75) describing the implementation process of a chosen practice(s) in their organization. The reports were analyzed with qualitative inductive content analysis. Of those hospitals that started the implementation, 78% (n=52) reported that they were able to implement the practice as described or as modified within the given timeframe. The major reported barrier to implementation was difficulties encountered in changing the work processes because of the new practice. Facilitators for successful implementation were the existence of a safety culture, national guidelines and projects, expert support, sufficient resources, electronic patient records, and interprofessional cooperation. As demonstrated in this doctoral study, MEs reported to a national health care supervisory authority are valuable and unique information sources of severe errors, and this data should be regarded as a part of national incident reporting and learning systems. Analysis of severe MEs with complex processes have a great potential to develop health care organizations´ systems, processes, resources, and competencies, if we have adequate methods to investigate the existing ME data. The aggregated DRP classification system with some modifications has the potential for analyzing and describing MEs and their causes, especially producing more sensitive and selective information for learning from severe MEs. The other part of the study demonstrated that medication safety practices are transferable across different organizations and countries. However, successful implementation requires selecting the right practice for the right medication safety risk, the presence of a safety culture, and sufficient resources and professionals.Lääkityspoikkeamalla tarkoitetaan mitä tahansa esitettävissä olevaa tapahtumaa, joka voi johtaa lääkkeen epäasianmukaiseen käyttöön tai haittaan potilaalla. Vakavissa lääkityspoikkeamissa haitta potilaalle on vakava ja siksi ne ovatkin lääkehoitoprosessin epätoivotuin, vaikkakin suhteellisen harvinainen lopputulos. Tämän kolmesta eri osatutkimuksesta koostuvan väitöskirjatutkimuksen tavoitteena oli tutkia millaisia ovat vakavat lääkityspoikkeamat sekä löytää keinoja niistä oppimiseen ja niiden estämiseen. Tutkimukset I ja II perustuivat Sosiaali- ja terveysalan lupa- ja valvontavirasto Valviran lääkehoitoon liittyvien kanteluiden ja viranomaislausuntojen analyysiin ajanjaksolta 2013-2017 (n=58). Tutkimus I tutki Valviran aineiston ja vakavien lääkityspoikkeamien taustatekijöitä, lääkityspoikkeamien luonnetta, poikkeaman toimintaympäristöä sekä arvioi poikkeamien ennalta estettävyyttä. Pääosa lääkityspoikkeamista (83 %, n=48/58) koski yli 60-vuotiaita potilaita. Lääkityspoikkeamat liittyivät yleisimmin lääkkeen määräämiseen (n=38; 47 %), lääkkeenantoon (n=15, 19 %) ja lääkehoidon seurantaan (n=14, 17 %). Antitromboottiset lääkeaineet (n=17; 13 %), opioidit (n=10, 8 %), ja antipsykootit (n=10, 8 %) olivat lääkityspoikkeamissa yleisimmin toistuneet lääkeaineryhmät. Lähes kaikki poikkeamatapaukset (91 %, n=53) arvioitiin todennäköisesti tai mahdollisesti estettäviksi. Tutkimus II selvitti voisiko lääkehoidon ongelmien luokitteluun kehitettyä syypohjaista luokittelumenetelmää soveltaa myös vakavien lääkityspoikkeamien luokitteluun. Luokittelua käyttäen Valviran tapauskuvauksista (n=58) tunnistettiin yhteensä 100 lääkityspoikkeamaa. Kaikki tunnistetut lääkityspoikkeamat pystyttiin luokittelemaan lääkehoidon ongelmille tarkoitetulla luokittelulla tuottaen tarkempaa tietoa lääkityspoikkeamien syistä. Tutkimus III toteutettiin osana European Network for Patient Safety (EUNetPas) projektia (2008-2010) ja siihen osallistui 55 sairaalaa 11 eri EU-maassa. Tutkimuksen tavoitteena oli tunnistaa projektiin valitun seitsemän lääkitysturvallisuuskäytännön (kaksi erilaista käytäntöä lääkkeiden jakamiseen potilaan vierellä; lääkkeidenjakoliivi; kotiutusvaiheen lääkelista; lääkityksen ajantasaistaminen potilaan kotiutuessa; lääkityksen ajantasaistaminen potilaan saapuessa ja kotiutuessa; unilääkeprotokolla) implementointia edistäneitä ja estäneitä tekijöitä. Yksi yleisimmistä implementointia estäneistä tekijöistä oli haasteet vanhojen työprosessien muuttamisessa. Implementointia edistäneitä tekijöitä olivat erityisesti olemassa oleva turvallisuuskulttuuri, kansalliset suositukset ja projektit, asiantuntijatuki, riittävät resurssit, elektroniset potilastietojärjestelmät ja moniammatillinen yhteistyö. Tietoa vakavista lääkityspoikkeamista kertyy Valviraan ja sen avulla on mahdollista tunnistaa kansallisia lääkitysturvallisuushaasteita sekä kehittää lääkitysturvallisuutta, kunhan meillä on oikeat menetelmät tiedon analysoimiseksi. Lääkitysturvallisuuskäytäntöjä pystytään jakamaan kansainvälisten projektien avulla, mutta onnistunut implementointi vaatii oikein valitun käytännön, turvallisuuskulttuurin sekä asianmukaisia resursseja ja ammattilaisia

Lääkemääräysten kliininen kaksoistarkistus - uusi toimintatapa sairaalassa

Helsingin yliopistollisessa sairaalassa pilotoidussa kliinisessä kaksoistarkistuksessa farmaseutti esitti muutosta lääkitykseen 5 %:iin lääkemääräyksistä.Niistä 85 % toteutettiin