Assessment of the Medication Errors by Nurses in an Emergency Department: A Cross-Sectional Study

Assessment of the Medication Errors by Nurses in an... | F1000Research "use strict";function _typeof(t){return(_typeof="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(t){return typeof t}:function(t){return t&&"function"==typeof Symbol&&t.constructor===Symbol&&t!==Symbol.prototype?"symbol":typeof t})(t)}!function(){var t=function(){var t,e,o=[],n=window,r=n;for(;r;){try{if(r.frames.__tcfapiLocator){t=r;break}}catch(t){}if(r===n.top)break;r=r.parent}t||(!function t(){var e=n.document,o=!!n.frames.__tcfapiLocator;if(!o)if(e.body){var r=e.createElement("iframe");r.style.cssText="display:none",r.name="__tcfapiLocator",e.body.appendChild(r)}else setTimeout(t,5);return!o}(),n.__tcfapi=function(){for(var t=arguments.length,n=new Array(t),r=0;r 3&&2===parseInt(n[1],10)&&"boolean"==typeof n[3]&&(e=n[3],"function"==typeof n[2]&&n[2]("set",!0)):"ping"===n[0]?"function"==typeof n[2]&&n[2]({gdprApplies:e,cmpLoaded:!1,cmpStatus:"stub"}):o.push(n)},n.addEventListener("message",(function(t){var e="string"==typeof t.data,o={};if(e)try{o=JSON.parse(t.data)}catch(t){}else o=t.data;var n="object"===_typeof(o)&&null!==o?o.__tcfapiCall:null;n&&window.__tcfapi(n.command,n.version,(function(o,r){var a={__tcfapiReturn:{returnValue:o,success:r,callId:n.callId}};t&&t.source&&t.source.postMessage&&t.source.postMessage(e?JSON.stringify(a):a,"*")}),n.parameter)}),!1))};"undefined"!=typeof module?module.exports=t:t()}(); dataLayer = dataLayer || []; // Standard GTM initialization - Google Consent Mode handles consent automatically (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl+ '>m_auth=hzk0Vc3qFsQYhCrIoHz68A>m_preview=env-1>m_cookies_win=x';f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-MWFK8L5J'); ;window.NREUM||(NREUM={});NREUM.init={distributed_tracing:{enabled:true},privacy:{cookies_enabled:true},ajax:{deny_list:["bam.nr-data.net"]}}; ;NREUM.loader_config={accountID:"438030",trustKey:"438030",agentID:"772317073",licenseKey:"97f8f67f26",applicationID:"772317073"} ;NREUM.info={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net",licenseKey:"97f8f67f26",applicationID:"772317073",sa:1} ;/*! For license information please see nr-loader-spa-1.236.0.min.js.LICENSE.txt */ (()=>{"use strict";var e,t,r={5763:(e,t,r)=>{r.d(t,{P_:()=>l,Mt:()=>g,C5:()=>s,DL:()=>v,OP:()=>T,lF:()=>D,Yu:()=>y,Dg:()=>h,CX:()=>c,GE:()=>b,sU:()=>_});var n=r(8632),i=r(9567);const o={beacon:n.ce.beacon,errorBeacon:n.ce.errorBeacon,licenseKey:void 0,applicationID:void 0,sa:void 0,queueTime:void 0,applicationTime:void 0,ttGuid:void 0,user:void 0,account:void 0,product:void 0,extra:void 0,jsAttributes:{},userAttributes:void 0,atts:void 0,transactionName:void 0,tNamePlain:void 0},a={};function s(e){if(!e)throw new Error("All info objects require an agent identifier!");if(!a[e])throw new Error("Info for ".concat(e," was never set"));return a[e]}function c(e,t){if(!e)throw new Error("All info objects require an agent identifier!");a[e]=(0,i.D)(t,o),(0,n.Qy)(e,a[e],"info")}var u=r(7056);const d=()=>{const e={blockSelector:"[data-nr-block]",maskInputOptions:{password:!0}};return{allow_bfcache:!0,privacy:{cookies_enabled:!0},ajax:{deny_list:void 0,enabled:!0,harvestTimeSeconds:10},distributed_tracing:{enabled:void 0,exclude_newrelic_header:void 0,cors_use_newrelic_header:void 0,cors_use_tracecontext_headers:void 0,allowed_origins:void 0},session:{domain:void 0,expiresMs:u.oD,inactiveMs:u.Hb},ssl:void 0,obfuscate:void 0,jserrors:{enabled:!0,harvestTimeSeconds:10},metrics:{enabled:!0},page_action:{enabled:!0,harvestTimeSeconds:30},page_view_event:{enabled:!0},page_view_timing:{enabled:!0,harvestTimeSeconds:30,long_task:!1},session_trace:{enabled:!0,harvestTimeSeconds:10},harvest:{tooManyRequestsDelay:60},session_replay:{enabled:!1,harvestTimeSeconds:60,sampleRate:.1,errorSampleRate:.1,maskTextSelector:"*",maskAllInputs:!0,get blockClass(){return"nr-block"},get ignoreClass(){return"nr-ignore"},get maskTextClass(){return"nr-mask"},get blockSelector(){return e.blockSelector},set blockSelector(t){e.blockSelector+=",".concat(t)},get maskInputOptions(){return e.maskInputOptions},set maskInputOptions(t){e.maskInputOptions={...t,password:!0}}},spa:{enabled:!0,harvestTimeSeconds:10}}},f={};function l(e){if(!e)throw new Error("All configuration objects require an agent identifier!");if(!f[e])throw new Error("Configuration for ".concat(e," was never set"));return f[e]}function h(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");f[e]=(0,i.D)(t,d()),(0,n.Qy)(e,f[e],"config")}function g(e,t){if(!e)throw new Error("All configuration objects require an agent identifier!");var r=l(e);if(r){for(var n=t.split("."),i=0;i {r.d(t,{D:()=>i});var n=r(50);function i(e,t){try{if(!e||"object"!=typeof e)return(0,n.Z)("Setting a Configurable requires an object as input");if(!t||"object"!=typeof t)return(0,n.Z)("Setting a Configurable requires a model to set its initial properties");const r=Object.create(Object.getPrototypeOf(t),Object.getOwnPropertyDescriptors(t)),o=0===Object.keys(r).length?e:r;for(let a in o)if(void 0!==e[a])try{"object"==typeof e[a]&&"object"==typeof t[a]?r[a]=i(e[a],t[a]):r[a]=e[a]}catch(e){(0,n.Z)("An error occurred while setting a property of a Configurable",e)}return r}catch(e){(0,n.Z)("An error occured while setting a Configurable",e)}}},6818:(e,t,r)=>{r.d(t,{Re:()=>i,gF:()=>o,q4:()=>n});const n="1.236.0",i="PROD",o="CDN"},385:(e,t,r)=>{r.d(t,{FN:()=>a,IF:()=>u,Nk:()=>f,Tt:()=>s,_A:()=>o,il:()=>n,pL:()=>c,v6:()=>i,w1:()=>d});const n="undefined"!=typeof window&&!!window.document,i="undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self.navigator instanceof WorkerNavigator||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis.navigator instanceof WorkerNavigator),o=n?window:"undefined"!=typeof WorkerGlobalScope&&("undefined"!=typeof self&&self instanceof WorkerGlobalScope&&self||"undefined"!=typeof globalThis&&globalThis instanceof WorkerGlobalScope&&globalThis),a=""+o?.location,s=/iPad|iPhone|iPod/.test(navigator.userAgent),c=s&&"undefined"==typeof SharedWorker,u=(()=>{const e=navigator.userAgent.match(/Firefox[/\s](\d+\.\d+)/);return Array.isArray(e)&&e.length>=2?+e[1]:0})(),d=Boolean(n&&window.document.documentMode),f=!!navigator.sendBeacon},1117:(e,t,r)=>{r.d(t,{w:()=>o});var n=r(50);const i={agentIdentifier:"",ee:void 0};class o{constructor(e){try{if("object"!=typeof e)return(0,n.Z)("shared context requires an object as input");this.sharedContext={},Object.assign(this.sharedContext,i),Object.entries(e).forEach((e=>{let[t,r]=e;Object.keys(i).includes(t)&&(this.sharedContext[t]=r)}))}catch(e){(0,n.Z)("An error occured while setting SharedContext",e)}}}},8e3:(e,t,r)=>{r.d(t,{L:()=>d,R:()=>c});var n=r(2177),i=r(1284),o=r(4322),a=r(3325);const s={};function c(e,t){const r={staged:!1,priority:a.p[t]||0};u(e),s[e].get(t)||s[e].set(t,r)}function u(e){e&&(s[e]||(s[e]=new Map))}function d(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:"",t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:"feature";if(u(e),!e||!s[e].get(t))return a(t);s[e].get(t).staged=!0;const r=[...s[e]];function a(t){const r=e?n.ee.get(e):n.ee,a=o.X.handlers;if(r.backlog&&a){var s=r.backlog[t],c=a[t];if(c){for(var u=0;s&&u {let[t,r]=e;return r.staged}))&&(r.sort(((e,t)=>e[1].priority-t[1].priority)),r.forEach((e=>{let[t]=e;a(t)})))}function f(e,t){var r=e[1];(0,i.D)(t[r],(function(t,r){var n=e[0];if(r[0]===n){var i=r[1],o=e[3],a=e[2];i.apply(o,a)}}))}},2177:(e,t,r)=>{r.d(t,{c:()=>f,ee:()=>u});var n=r(8632),i=r(2210),o=r(1284),a=r(5763),s="nr@context";let c=(0,n.fP)();var u;function d(){}function f(e){return(0,i.X)(e,s,l)}function l(){return new d}function h(){u.aborted=!0,u.backlog={}}c.ee?u=c.ee:(u=function e(t,r){var n={},c={},f={},g=!1;try{g=16===r.length&&(0,a.OP)(r).isolatedBacklog}catch(e){}var p={on:b,addEventListener:b,removeEventListener:y,emit:v,get:x,listeners:w,context:m,buffer:A,abort:h,aborted:!1,isBuffering:E,debugId:r,backlog:g?{}:t&&"object"==typeof t.backlog?t.backlog:{}};return p;function m(e){return e&&e instanceof d?e:e?(0,i.X)(e,s,l):l()}function v(e,r,n,i,o){if(!1!==o&&(o=!0),!u.aborted||i){t&&o&&t.emit(e,r,n);for(var a=m(n),s=w(e),d=s.length,f=0;fn,p:()=>i});var n=r(2177).ee.get("handle");function i(e,t,r,i,o){o?(o.buffer([e],i),o.emit(e,t,r)):(n.buffer([e],i),n.emit(e,t,r))}},4322:(e,t,r)=>{r.d(t,{X:()=>o});var n=r(5546);o.on=a;var i=o.handlers={};function o(e,t,r,o){a(o||n.E,i,e,t,r)}function a(e,t,r,i,o){o||(o="feature"),e||(e=n.E);var a=t[o]=t[o]||{};(a[r]=a[r]||[]).push([e,i])}},3239:(e,t,r)=>{r.d(t,{bP:()=>s,iz:()=>c,m$:()=>a});var n=r(385);let i=!1,o=!1;try{const e={get passive(){return i=!0,!1},get signal(){return o=!0,!1}};n._A.addEventListener("test",null,e),n._A.removeEventListener("test",null,e)}catch(e){}function a(e,t){return i||o?{capture:!!e,passive:i,signal:t}:!!e}function s(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;window.addEventListener(e,t,a(r,n))}function c(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2],n=arguments.length>3?arguments[3]:void 0;document.addEventListener(e,t,a(r,n))}},4402:(e,t,r)=>{r.d(t,{Ht:()=>u,M:()=>c,Rl:()=>a,ky:()=>s});var n=r(385);const i="xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx";function o(e,t){return e?15&e[t]:16*Math.random()|0}function a(){const e=n._A?.crypto||n._A?.msCrypto;let t,r=0;return e&&e.getRandomValues&&(t=e.getRandomValues(new Uint8Array(31))),i.split("").map((e=>"x"===e?o(t,++r).toString(16):"y"===e?(3&o()|8).toString(16):e)).join("")}function s(e){const t=n._A?.crypto||n._A?.msCrypto;let r,i=0;t&&t.getRandomValues&&(r=t.getRandomValues(new Uint8Array(31)));const a=[];for(var s=0;s {r.d(t,{Bq:()=>n,Hb:()=>o,oD:()=>i});const n="NRBA",i=144e5,o=18e5},7894:(e,t,r)=>{function n(){return Math.round(performance.now())}r.d(t,{z:()=>n})},7243:(e,t,r)=>{r.d(t,{e:()=>o});var n=r(385),i={};function o(e){if(e in i)return i[e];if(0===(e||"").indexOf("data:"))return{protocol:"data"};let t;var r=n._A?.location,o={};if(n.il)t=document.createElement("a"),t.href=e;else try{t=new URL(e,r.href)}catch(e){return o}o.port=t.port;var a=t.href.split("://");!o.port&&a[1]&&(o.port=a[1].split("/")[0].split("@").pop().split(":")[1]),o.port&&"0"!==o.port||(o.port="https"===a[0]?"443":"80"),o.hostname=t.hostname||r.hostname,o.pathname=t.pathname,o.protocol=a[0],"/"!==o.pathname.charAt(0)&&(o.pathname="/"+o.pathname);var s=!t.protocol||":"===t.protocol||t.protocol===r.protocol,c=t.hostname===r.hostname&&t.port===r.port;return o.sameOrigin=s&&(!t.hostname||c),"/"===o.pathname&&(i[e]=o),o}},50:(e,t,r)=>{function n(e,t){"function"==typeof console.warn&&(console.warn("New Relic: ".concat(e)),t&&console.warn(t))}r.d(t,{Z:()=>n})},2587:(e,t,r)=>{r.d(t,{N:()=>c,T:()=>u});var n=r(2177),i=r(5546),o=r(8e3),a=r(3325);const s={stn:[a.D.sessionTrace],err:[a.D.jserrors,a.D.metrics],ins:[a.D.pageAction],spa:[a.D.spa],sr:[a.D.sessionReplay,a.D.sessionTrace]};function c(e,t){const r=n.ee.get(t);e&&"object"==typeof e&&(Object.entries(e).forEach((e=>{let[t,n]=e;void 0===u[t]&&(s[t]?s[t].forEach((e=>{n?(0,i.p)("feat-"+t,[],void 0,e,r):(0,i.p)("block-"+t,[],void 0,e,r),(0,i.p)("rumresp-"+t,[Boolean(n)],void 0,e,r)})):n&&(0,i.p)("feat-"+t,[],void 0,void 0,r),u[t]=Boolean(n))})),Object.keys(s).forEach((e=>{void 0===u[e]&&(s[e]?.forEach((t=>(0,i.p)("rumresp-"+e,[!1],void 0,t,r))),u[e]=!1)})),(0,o.L)(t,a.D.pageViewEvent))}const u={}},2210:(e,t,r)=>{r.d(t,{X:()=>i});var n=Object.prototype.hasOwnProperty;function i(e,t,r){if(n.call(e,t))return e[t];var i=r();if(Object.defineProperty&&Object.keys)try{return Object.defineProperty(e,t,{value:i,writable:!0,enumerable:!1}),i}catch(e){}return e[t]=i,i}},1284:(e,t,r)=>{r.d(t,{D:()=>n});const n=(e,t)=>Object.entries(e||{}).map((e=>{let[r,n]=e;return t(r,n)}))},4351:(e,t,r)=>{r.d(t,{P:()=>o});var n=r(2177);const i=()=>{const e=new WeakSet;return(t,r)=>{if("object"==typeof r&&null!==r){if(e.has(r))return;e.add(r)}return r}};function o(e){try{return JSON.stringify(e,i())}catch(e){try{n.ee.emit("internal-error",[e])}catch(e){}}}},3960:(e,t,r)=>{r.d(t,{K:()=>a,b:()=>o});var n=r(3239);function i(){return"undefined"==typeof document||"complete"===document.readyState}function o(e,t){if(i())return e();(0,n.bP)("load",e,t)}function a(e){if(i())return e();(0,n.iz)("DOMContentLoaded",e)}},8632:(e,t,r)=>{r.d(t,{EZ:()=>u,Qy:()=>c,ce:()=>o,fP:()=>a,gG:()=>d,mF:()=>s});var n=r(7894),i=r(385);const o={beacon:"bam.nr-data.net",errorBeacon:"bam.nr-data.net"};function a(){return i._A.NREUM||(i._A.NREUM={}),void 0===i._A.newrelic&&(i._A.newrelic=i._A.NREUM),i._A.NREUM}function s(){let e=a();return e.o||(e.o={ST:i._A.setTimeout,SI:i._A.setImmediate,CT:i._A.clearTimeout,XHR:i._A.XMLHttpRequest,REQ:i._A.Request,EV:i._A.Event,PR:i._A.Promise,MO:i._A.MutationObserver,FETCH:i._A.fetch}),e}function c(e,t,r){let i=a();const o=i.initializedAgents||{},s=o[e]||{};return Object.keys(s).length||(s.initializedAt={ms:(0,n.z)(),date:new Date}),i.initializedAgents={...o,[e]:{...s,[r]:t}},i}function u(e,t){a()[e]=t}function d(){return function(){let e=a();const t=e.info||{};e.info={beacon:o.beacon,errorBeacon:o.errorBeacon,...t}}(),function(){let e=a();const t=e.init||{};e.init={...t}}(),s(),function(){let e=a();const t=e.loader_config||{};e.loader_config={...t}}(),a()}},7956:(e,t,r)=>{r.d(t,{N:()=>i});var n=r(3239);function i(e){let t=arguments.length>1&&void 0!==arguments[1]&&arguments[1],r=arguments.length>2?arguments[2]:void 0,i=arguments.length>3?arguments[3]:void 0;return void(0,n.iz)("visibilitychange",(function(){if(t)return void("hidden"==document.visibilityState&&e());e(document.visibilityState)}),r,i)}},1214:(e,t,r)=>{r.d(t,{em:()=>v,u5:()=>N,QU:()=>S,_L:()=>I,Gm:()=>L,Lg:()=>M,gy:()=>U,BV:()=>Q,Kf:()=>ee});var n=r(2177);const i="nr@original";var o=Object.prototype.hasOwnProperty,a=!1;function s(e,t){return e||(e=n.ee),r.inPlace=function(e,t,n,i,o){n||(n="");var a,s,c,u="-"===n.charAt(0);for(c=0;c 2?n-2:0),o=2;o {r(A[T],e,w),r(E[T],e,w)})),r(l._A,"fetch",y),t.on(y+"end",(function(e,r){var n=this;if(r){var i=r.headers.get("content-length");null!==i&&(n.rxSize=i),t.emit(y+"done",[null,r],n)}else t.emit(y+"done",[e],n)})),t}const O={},j=["pushState","replaceState"];function S(e){const t=function(e){return(e||n.ee).get("history")}(e);return!l.il||O[t.debugId]++||(O[t.debugId]=1,s(t).inPlace(window.history,j,"-")),t}var P=r(3239);const C={},R=["appendChild","insertBefore","replaceChild"];function I(e){const t=function(e){return(e||n.ee).get("jsonp")}(e);if(!l.il||C[t.debugId])return t;C[t.debugId]=!0;var r=s(t),i=/[?&](?:callback|cb)=([^&#]+)/,o=/(.*)\.([^.]+)/,a=/^(\w+)(\.|$)(.*)$/;function c(e,t){var r=e.match(a),n=r[1],i=r[3];return i?c(i,t[n]):t[n]}return r.inPlace(Node.prototype,R,"dom-"),t.on("dom-start",(function(e){!function(e){if(!e||"string"!=typeof e.nodeName||"script"!==e.nodeName.toLowerCase())return;if("function"!=typeof e.addEventListener)return;var n=(a=e.src,s=a.match(i),s?s[1]:null);var a,s;if(!n)return;var u=function(e){var t=e.match(o);if(t&&t.length>=3)return{key:t[2],parent:c(t[1],window)};return{key:e,parent:window}}(n);if("function"!=typeof u.parent[u.key])return;var d={};function f(){t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}function l(){t.emit("jsonp-error",[],d),t.emit("jsonp-end",[],d),e.removeEventListener("load",f,(0,P.m$)(!1)),e.removeEventListener("error",l,(0,P.m$)(!1))}r.inPlace(u.parent,[u.key],"cb-",d),e.addEventListener("load",f,(0,P.m$)(!1)),e.addEventListener("error",l,(0,P.m$)(!1)),t.emit("new-jsonp",[e.src],d)}(e[0])})),t}var k=r(5763);const H={};function L(e){const t=function(e){return(e||n.ee).get("mutation")}(e);if(!l.il||H[t.debugId])return t;H[t.debugId]=!0;var r=s(t),i=k.Yu.MO;return i&&(window.MutationObserver=function(e){return this instanceof i?new i(r(e,"fn-")):i.apply(this,arguments)},MutationObserver.prototype=i.prototype),t}const z={};function M(e){const t=function(e){return(e||n.ee).get("promise")}(e);if(z[t.debugId])return t;z[t.debugId]=!0;var r=n.c,o=s(t),a=k.Yu.PR;return a&&function(){function e(r){var n=t.context(),i=o(r,"executor-",n,null,!1);const s=Reflect.construct(a,[i],e);return t.context(s).getCtx=function(){return n},s}l._A.Promise=e,Object.defineProperty(e,"name",{value:"Promise"}),e.toString=function(){return a.toString()},Object.setPrototypeOf(e,a),["all","race"].forEach((function(r){const n=a[r];e[r]=function(e){let i=!1;[...e||[]].forEach((e=>{this.resolve(e).then(a("all"===r),a(!1))}));const o=n.apply(this,arguments);return o;function a(e){return function(){t.emit("propagate",[null,!i],o,!1,!1),i=i||!e}}}})),["resolve","reject"].forEach((function(r){const n=a[r];e[r]=function(e){const r=n.apply(this,arguments);return e!==r&&t.emit("propagate",[e,!0],r,!1,!1),r}})),e.prototype=a.prototype;const n=a.prototype.then;a.prototype.then=function(){var e=this,i=r(e);i.promise=e;for(var a=arguments.length,s=new Array(a),c=0;c e())),t};function m(e,t){i.inPlace(t,["onreadystatechange"],"fn-",E)}function b(){var e=this,t=r.context(e);e.readyState>3&&!t.resolved&&(t.resolved=!0,r.emit("xhr-resolved",[],e)),i.inPlace(e,f,"fn-",E)}if(function(e,t){for(var r in e)t[r]=e[r]}(o,p),p.prototype=o.prototype,i.inPlace(p.prototype,J,"-xhr-",E),r.on("send-xhr-start",(function(e,t){m(e,t),function(e){h.push(e),a&&(y?y.then(A):u?u(A):(w=-w,x.data=w))}(t)})),r.on("open-xhr-start",m),a){var y=c&&c.resolve();if(!u&&!c){var w=1,x=document.createTextNode(w);new a(A).observe(x,{characterData:!0})}}else t.on("fn-end",(function(e){e[0]&&e[0].type===d||A()}));function A(){for(var e=0;e {r.d(t,{t:()=>n});const n=r(3325).D.ajax},6660:(e,t,r)=>{r.d(t,{A:()=>i,t:()=>n});const n=r(3325).D.jserrors,i="nr@seenError"},3081:(e,t,r)=>{r.d(t,{gF:()=>o,mY:()=>i,t9:()=>n,vz:()=>s,xS:()=>a});const n=r(3325).D.metrics,i="sm",o="cm",a="storeSupportabilityMetrics",s="storeEventMetrics"},4649:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageAction},7633:(e,t,r)=>{r.d(t,{Dz:()=>i,OJ:()=>a,qw:()=>o,t9:()=>n});const n=r(3325).D.pageViewEvent,i="firstbyte",o="domcontent",a="windowload"},9251:(e,t,r)=>{r.d(t,{t:()=>n});const n=r(3325).D.pageViewTiming},3614:(e,t,r)=>{r.d(t,{BST_RESOURCE:()=>i,END:()=>s,FEATURE_NAME:()=>n,FN_END:()=>u,FN_START:()=>c,PUSH_STATE:()=>d,RESOURCE:()=>o,START:()=>a});const n=r(3325).D.sessionTrace,i="bstResource",o="resource",a="-start",s="-end",c="fn"+a,u="fn"+s,d="pushState"},7836:(e,t,r)=>{r.d(t,{BODY:()=>A,CB_END:()=>E,CB_START:()=>u,END:()=>x,FEATURE_NAME:()=>i,FETCH:()=>_,FETCH_BODY:()=>v,FETCH_DONE:()=>m,FETCH_START:()=>p,FN_END:()=>c,FN_START:()=>s,INTERACTION:()=>l,INTERACTION_API:()=>d,INTERACTION_EVENTS:()=>o,JSONP_END:()=>b,JSONP_NODE:()=>g,JS_TIME:()=>T,MAX_TIMER_BUDGET:()=>a,REMAINING:()=>f,SPA_NODE:()=>h,START:()=>w,originalSetTimeout:()=>y});var n=r(5763);const i=r(3325).D.spa,o=["click","submit","keypress","keydown","keyup","change"],a=999,s="fn-start",c="fn-end",u="cb-start",d="api-ixn-",f="remaining",l="interaction",h="spaNode",g="jsonpNode",p="fetch-start",m="fetch-done",v="fetch-body-",b="jsonp-end",y=n.Yu.ST,w="-start",x="-end",A="-body",E="cb"+x,T="jsTime",_="fetch"},5938:(e,t,r)=>{r.d(t,{W:()=>o});var n=r(5763),i=r(2177);class o{constructor(e,t,r){this.agentIdentifier=e,this.aggregator=t,this.ee=i.ee.get(e,(0,n.OP)(this.agentIdentifier).isolatedBacklog),this.featureName=r,this.blocked=!1}}},9144:(e,t,r)=>{r.d(t,{j:()=>m});var n=r(3325),i=r(5763),o=r(5546),a=r(2177),s=r(7894),c=r(8e3),u=r(3960),d=r(385),f=r(50),l=r(3081),h=r(8632);function g(){const e=(0,h.gG)();["setErrorHandler","finished","addToTrace","inlineHit","addRelease","addPageAction","setCurrentRouteName","setPageViewName","setCustomAttribute","interaction","noticeError","setUserId"].forEach((t=>{e[t]=function(){for(var r=arguments.length,n=new Array(r),i=0;i 1?r-1:0),i=1;i {e.exposed&&e.api[t]&&o.push(e.api[t](...n))})),o.length>1?o:o[0]}(t,...n)}}))}var p=r(2587);function m(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:{},m=arguments.length>2?arguments[2]:void 0,v=arguments.length>3?arguments[3]:void 0,{init:b,info:y,loader_config:w,runtime:x={loaderType:m},exposed:A=!0}=t;const E=(0,h.gG)();y||(b=E.init,y=E.info,w=E.loader_config),(0,i.Dg)(e,b||{}),(0,i.GE)(e,w||{}),(0,i.sU)(e,x),y.jsAttributes??={},d.v6&&(y.jsAttributes.isWorker=!0),(0,i.CX)(e,y),g();const T=function(e,t){t||(0,c.R)(e,"api");const h={};var g=a.ee.get(e),p=g.get("tracer"),m="api-",v=m+"ixn-";function b(t,r,n,o){const a=(0,i.C5)(e);return null===r?delete a.jsAttributes[t]:(0,i.CX)(e,{...a,jsAttributes:{...a.jsAttributes,[t]:r}}),x(m,n,!0,o||null===r?"session":void 0)(t,r)}function y(){}["setErrorHandler","finished","addToTrace","inlineHit","addRelease"].forEach((e=>h[e]=x(m,e,!0,"api"))),h.addPageAction=x(m,"addPageAction",!0,n.D.pageAction),h.setCurrentRouteName=x(m,"routeName",!0,n.D.spa),h.setPageViewName=function(t,r){if("string"==typeof t)return"/"!==t.charAt(0)&&(t="/"+t),(0,i.OP)(e).customTransaction=(r||"http://custom.transaction")+t,x(m,"setPageViewName",!0)()},h.setCustomAttribute=function(e,t){let r=arguments.length>2&&void 0!==arguments[2]&&arguments[2];if("string"==typeof e){if(["string","number"].includes(typeof t)||null===t)return b(e,t,"setCustomAttribute",r);(0,f.Z)("Failed to execute setCustomAttribute.\nNon-null value must be a string or number type, but a type of was provided."))}else(0,f.Z)("Failed to execute setCustomAttribute.\nName must be a string type, but a type of was provided."))},h.setUserId=function(e){if("string"==typeof e||null===e)return b("enduser.id",e,"setUserId",!0);(0,f.Z)("Failed to execute setUserId.\nNon-null value must be a string type, but a type of was provided."))},h.interaction=function(){return(new y).get()};var w=y.prototype={createTracer:function(e,t){var r={},i=this,a="function"==typeof t;return(0,o.p)(v+"tracer",[(0,s.z)(),e,r],i,n.D.spa,g),function(){if(p.emit((a?"":"no-")+"fn-start",[(0,s.z)(),i,a],r),a)try{return t.apply(this,arguments)}catch(e){throw p.emit("fn-err",[arguments,this,"string"==typeof e?new Error(e):e],r),e}finally{p.emit("fn-end",[(0,s.z)()],r)}}}};function x(e,t,r,i){return function(){return(0,o.p)(l.xS,["API/"+t+"/called"],void 0,n.D.metrics,g),i&&(0,o.p)(e+t,[(0,s.z)(),...arguments],r?null:this,i,g),r?void 0:this}}function A(){r.e(439).then(r.bind(r,7438)).then((t=>{let{setAPI:r}=t;r(e),(0,c.L)(e,"api")})).catch((()=>(0,f.Z)("Downloading runtime APIs failed...")))}return["actionText","setName","setAttribute","save","ignore","onEnd","getContext","end","get"].forEach((e=>{w[e]=x(v,e,void 0,n.D.spa)})),h.noticeError=function(e,t){"string"==typeof e&&(e=new Error(e)),(0,o.p)(l.xS,["API/noticeError/called"],void 0,n.D.metrics,g),(0,o.p)("err",[e,(0,s.z)(),!1,t],void 0,n.D.jserrors,g)},d.il?(0,u.b)((()=>A()),!0):A(),h}(e,v);return(0,h.Qy)(e,T,"api"),(0,h.Qy)(e,A,"exposed"),(0,h.EZ)("activatedFeatures",p.T),T}},3325:(e,t,r)=>{r.d(t,{D:()=>n,p:()=>i});const n={ajax:"ajax",jserrors:"jserrors",metrics:"metrics",pageAction:"page_action",pageViewEvent:"page_view_event",pageViewTiming:"page_view_timing",sessionReplay:"session_replay",sessionTrace:"session_trace",spa:"spa"},i={[n.pageViewEvent]:1,[n.pageViewTiming]:2,[n.metrics]:3,[n.jserrors]:4,[n.ajax]:5,[n.sessionTrace]:6,[n.pageAction]:7,[n.spa]:8,[n.sessionReplay]:9}}},n={};function i(e){var t=n[e];if(void 0!==t)return t.exports;var o=n[e]={exports:{}};return r[e](o,o.exports,i),o.exports}i.m=r,i.d=(e,t)=>{for(var r in t)i.o(t,r)&&!i.o(e,r)&&Object.defineProperty(e,r,{enumerable:!0,get:t[r]})},i.f={},i.e=e=>Promise.all(Object.keys(i.f).reduce(((t,r)=>(i.f[r](e,t),t)),[])),i.u=e=>(({78:"page_action-aggregate",147:"metrics-aggregate",242:"session-manager",317:"jserrors-aggregate",348:"page_view_timing-aggregate",412:"lazy-feature-loader",439:"async-api",538:"recorder",590:"session_replay-aggregate",675:"compressor",733:"session_trace-aggregate",786:"page_view_event-aggregate",873:"spa-aggregate",898:"ajax-aggregate"}[e]||e)+"."+{78:"ac76d497",147:"3dc53903",148:"1a20d5fe",242:"2a64278a",317:"49e41428",348:"bd6de33a",412:"2f55ce66",439:"30bd804e",538:"1b18459f",590:"cf0efb30",675:"ae9f91a8",733:"83105561",786:"06482edd",860:"03a8b7a5",873:"e6b09d52",898:"998ef92b"}[e]+"-1.236.0.min.js"),i.o=(e,t)=>Object.prototype.hasOwnProperty.call(e,t),e={},t="NRBA:",i.l=(r,n,o,a)=>{if(e[r])e[r].push(n);else{var s,c;if(void 0!==o)for(var u=document.getElementsByTagName("script"),d=0;d {s.onerror=s.onload=null,clearTimeout(h);var i=e[r];if(delete e[r],s.parentNode&&s.parentNode.removeChild(s),i&&i.forEach((e=>e(n))),t)return t(n)},h=setTimeout(l.bind(null,void 0,{type:"timeout",target:s}),12e4);s.onerror=l.bind(null,s.onerror),s.onload=l.bind(null,s.onload),c&&document.head.appendChild(s)}},i.r=e=>{"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},i.j=364,i.p="https://js-agent.newrelic.com/",(()=>{var e={364:0,953:0};i.f.j=(t,r)=>{var n=i.o(e,t)?e[t]:void 0;if(0!==n)if(n)r.push(n[2]);else{var o=new Promise(((r,i)=>n=e[t]=[r,i]));r.push(n[2]=o);var a=i.p+i.u(t),s=new Error;i.l(a,(r=>{if(i.o(e,t)&&(0!==(n=e[t])&&(e[t]=void 0),n)){var o=r&&("load"===r.type?"missing":r.type),a=r&&r.target&&r.target.src;s.message="Loading chunk "+t+" failed.\n("+o+": "+a+")",s.name="ChunkLoadError",s.type=o,s.request=a,n[1](s)}}),"chunk-"+t,t)}};var t=(t,r)=>{var n,o,[a,s,c]=r,u=0;if(a.some((t=>0!==e[t]))){for(n in s)i.o(s,n)&&(i.m[n]=s[n]);if(c)c(i)}for(t&&t(r);u {i.r(o);var e=i(3325),t=i(5763);const r=Object.values(e.D);function n(e){const n={};return r.forEach((r=>{n[r]=function(e,r){return!1!==(0,t.Mt)(r,"".concat(e,".enabled"))}(r,e)})),n}var a=i(9144);var s=i(5546),c=i(385),u=i(8e3),d=i(5938),f=i(3960),l=i(50);class h extends d.W{constructor(e,t,r){let n=!(arguments.length>3&&void 0!==arguments[3])||arguments[3];super(e,t,r),this.auto=n,this.abortHandler,this.featAggregate,this.onAggregateImported,n&&(0,u.R)(e,r)}importAggregator(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{};if(this.featAggregate||!this.auto)return;const r=c.il&&!0===(0,t.Mt)(this.agentIdentifier,"privacy.cookies_enabled");let n;this.onAggregateImported=new Promise((e=>{n=e}));const o=async()=>{let t;try{if(r){const{setupAgentSession:e}=await Promise.all([i.e(860),i.e(242)]).then(i.bind(i,3228));t=e(this.agentIdentifier)}}catch(e){(0,l.Z)("A problem occurred when starting up session manager. This page will not start or extend any session.",e)}try{if(!this.shouldImportAgg(this.featureName,t))return void(0,u.L)(this.agentIdentifier,this.featureName);const{lazyFeatureLoader:r}=await i.e(412).then(i.bind(i,8582)),{Aggregate:o}=await r(this.featureName,"aggregate");this.featAggregate=new o(this.agentIdentifier,this.aggregator,e),n(!0)}catch(e){(0,l.Z)("Downloading and initializing ".concat(this.featureName," failed..."),e),this.abortHandler?.(),n(!1)}};c.il?(0,f.b)((()=>o()),!0):o()}shouldImportAgg(r,n){return r!==e.D.sessionReplay||!1!==(0,t.Mt)(this.agentIdentifier,"session_trace.enabled")&&(!!n?.isNew||!!n?.state.sessionReplay)}}var g=i(7633),p=i(7894);class m extends h{static featureName=g.t9;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];if(super(r,n,g.t9,i),("undefined"==typeof PerformanceNavigationTiming||c.Tt)&&"undefined"!=typeof PerformanceTiming){const n=(0,t.OP)(r);n[g.Dz]=Math.max(Date.now()-n.offset,0),(0,f.K)((()=>n[g.qw]=Math.max((0,p.z)()-n[g.Dz],0))),(0,f.b)((()=>{const t=(0,p.z)();n[g.OJ]=Math.max(t-n[g.Dz],0),(0,s.p)("timing",["load",t],void 0,e.D.pageViewTiming,this.ee)}))}this.importAggregator()}}var v=i(1117),b=i(1284);class y extends v.w{constructor(e){super(e),this.aggregatedData={}}store(e,t,r,n,i){var o=this.getBucket(e,t,r,i);return o.metrics=function(e,t){t||(t={count:0});return t.count+=1,(0,b.D)(e,(function(e,r){t[e]=w(r,t[e])})),t}(n,o.metrics),o}merge(e,t,r,n,i){var o=this.getBucket(e,t,n,i);if(o.metrics){var a=o.metrics;a.count+=r.count,(0,b.D)(r,(function(e,t){if("count"!==e){var n=a[e],i=r[e];i&&!i.c?a[e]=w(i.t,n):a[e]=function(e,t){if(!t)return e;t.c||(t=x(t.t));return t.min=Math.min(e.min,t.min),t.max=Math.max(e.max,t.max),t.t+=e.t,t.sos+=e.sos,t.c+=e.c,t}(i,a[e])}}))}else o.metrics=r}storeMetric(e,t,r,n){var i=this.getBucket(e,t,r);return i.stats=w(n,i.stats),i}getBucket(e,t,r,n){this.aggregatedData[e]||(this.aggregatedData[e]={});var i=this.aggregatedData[e][t];return i||(i=this.aggregatedData[e][t]={params:r||{}},n&&(i.custom=n)),i}get(e,t){return t?this.aggregatedData[e]&&this.aggregatedData[e][t]:this.aggregatedData[e]}take(e){for(var t={},r="",n=!1,i=0;i t.max&&(t.max=e),e 2&&void 0!==arguments[2])||arguments[2];super(e,r,j.t,n),c.il&&((0,t.OP)(e).initHidden=Boolean("hidden"===document.visibilityState),(0,N.N)((()=>(0,s.p)("docHidden",[(0,p.z)()],void 0,j.t,this.ee)),!0),(0,O.bP)("pagehide",(()=>(0,s.p)("winPagehide",[(0,p.z)()],void 0,j.t,this.ee))),this.importAggregator())}}var P=i(3081);class C extends h{static featureName=P.t9;constructor(e,t){let r=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(e,t,P.t9,r),this.importAggregator()}}var R,I=i(2210),k=i(1214),H=i(2177),L={};try{R=localStorage.getItem("__nr_flags").split(","),console&&"function"==typeof console.log&&(L.console=!0,-1!==R.indexOf("dev")&&(L.dev=!0),-1!==R.indexOf("nr_dev")&&(L.nrDev=!0))}catch(e){}function z(e){try{L.console&&z(e)}catch(e){}}L.nrDev&&H.ee.on("internal-error",(function(e){z(e.stack)})),L.dev&&H.ee.on("fn-err",(function(e,t,r){z(r.stack)})),L.dev&&(z("NR AGENT IN DEVELOPMENT MODE"),z("flags: "+(0,b.D)(L,(function(e,t){return e})).join(", ")));var M=i(6660);class B extends h{static featureName=M.t;constructor(r,n){let i=!(arguments.length>2&&void 0!==arguments[2])||arguments[2];super(r,n,M.t,i),this.skipNext=0;try{this.removeOnAbort=new AbortController}catch(e){}const o=this;o.ee.on("fn-start",(function(e,t,r){o.abortHandler&&(o.skipNext+=1)})),o.ee.on("fn-err",(function(t,r,n){o.abortHandler&&!n[M.A]&&((0,I.X)(n,M.A,(function(){return!0})),this.thrown=!0,(0,s.p)("err",[n,(0,p.z)()],void 0,e.D.jserrors,o.ee))})),o.ee.on("fn-end",(function(){o.abortHandler&&!this.thrown&&o.skipNext>0&&(o.skipNext-=1)})),o.ee.on("internal-error",(function(t){(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,o.ee)})),this.origOnerror=c._A.onerror,c._A.onerror=this.onerrorHandler.bind(this),c._A.addEventListener("unhandledrejection",(t=>{const r=function(e){let t="Unhandled Promise Rejection: ";if(e instanceof Error)try{return e.message=t+e.message,e}catch(t){return e}if(void 0===e)return new Error(t);try{return new Error(t+(0,D.P)(e))}catch(e){return new Error(t)}}(t.reason);(0,s.p)("err",[r,(0,p.z)(),!1,{unhandledPromiseRejection:1}],void 0,e.D.jserrors,this.ee)}),(0,O.m$)(!1,this.removeOnAbort?.signal)),(0,k.gy)(this.ee),(0,k.BV)(this.ee),(0,k.em)(this.ee),(0,t.OP)(r).xhrWrappable&&(0,k.Kf)(this.ee),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}onerrorHandler(t,r,n,i,o){"function"==typeof this.origOnerror&&this.origOnerror(...arguments);try{this.skipNext?this.skipNext-=1:(0,s.p)("err",[o||new F(t,r,n),(0,p.z)()],void 0,e.D.jserrors,this.ee)}catch(t){try{(0,s.p)("ierr",[t,(0,p.z)(),!0],void 0,e.D.jserrors,this.ee)}catch(e){}}return!1}}function F(e,t,r){this.message=e||"Uncaught error with no additional information",this.sourceURL=t,this.line=r}let U=1;const q="nr@id";function G(e){const t=typeof e;return!e||"object"!==t&&"function"!==t?-1:e===c._A?0:(0,I.X)(e,q,(function(){return U++}))}function V(e){if("string"==typeof e&&e.length)return e.length;if("object"==typeof e){if("undefined"!=typeof ArrayBuffer&&e instanceof ArrayBuffer&&e.byteLength)return e.byteLength;if("undefined"!=typeof Blob&&e instanceof Blob&&e.size)return e.size;if(!("undefined"!=typeof FormData&&e instanceof FormData))try{return(0,D.P)(e).length}catch(e){return}}}var X=i(7243);class W{constructor(e){this.agentIdentifier=e,this.generateTracePayload=this.generateTracePayload.bind(this),this.shouldGenerateTrace=this.shouldGenerateTrace.bind(this)}generateTracePayload(e){if(!this.shouldGenerateTrace(e))return null;var r=(0,t.DL)(this.agentIdentifier);if(!r)return null;var n=(r.accountID||"").toString()||null,i=(r.agentID||"").toString()||null,o=(r.trustKey||"").toString()||null;if(!n||!i)return null;var a=(0,_.M)(),s=(0,_.Ht)(),c=Date.now(),u={spanId:a,traceId:s,timestamp:c};return(e.sameOrigin||this.isAllowedOrigin(e)&&this.useTraceContextHeadersForCors())&&(u.traceContextParentHeader=this.generateTraceContextParentHeader(a,s),u.traceContextStateHeader=this.generateTraceContextStateHeader(a,c,n,i,o)),(e.sameOrigin&&!this.excludeNewrelicHeader()||!e.sameOrigin&&this.isAllowedOrigin(e)&&this.useNewrelicHeaderForCors())&&(u.newrelicHeader=this.generateTraceHeader(a,s,c,n,i,o)),u}generateTraceContextParentHeader(e,t){return"00-"+t+"-"+e+"-01"}generateTraceContextStateHeader(e,t,r,n,i){return i+"@nr=0-1-"+r+"-"+n+"-"+e+"----"+t}generateTraceHeader(e,t,r,n,i,o){if(!("function"==typeof c._A?.btoa))return null;var a={v:[0,1],d:{ty:"Browser",ac:n,ap:i,id:e,tr:t,ti:r}};return o&&n!==o&&(a.d.tk=o),btoa((0,D.P)(a))}shouldGenerateTrace(e){return this.isDtEnabled()&&this.isAllowedOrigin(e)}isAllowedOrigin(e){var r=!1,n={};if((0,t.Mt)(this.agentIdentifier,"distributed_tracing")&&(n=(0,t.P_)(this.agentIdentifier).distributed_tracing),e.sameOrigin)r=!0;else if(n.allowed_origins instanceof Array)for(var i=0;i 2&&void 0!==arguments[2])||arguments[2];super(r,n,Z.t,i),(0,t.OP)(r).xhrWrappable&&(this.dt=new W(r),this.handler=(e,t,r,n)=>(0,s.p)(e,t,r,n,this.ee),(0,k.u5)(this.ee),(0,k.Kf)(this.ee),function(r,n,i,o){function a(e){var t=this;t.totalCbs=0,t.called=0,t.cbTime=0,t.end=E,t.ended=!1,t.xhrGuids={},t.lastSize=null,t.loadCaptureCalled=!1,t.params=this.params||{},t.metrics=this.metrics||{},e.addEventListener("load",(function(r){_(t,e)}),(0,O.m$)(!1)),c.IF||e.addEventListener("progress",(function(e){t.lastSize=e.loaded}),(0,O.m$)(!1))}function s(e){this.params={method:e[0]},T(this,e[1]),this.metrics={}}function u(e,n){var i=(0,t.DL)(r);i.xpid&&this.sameOrigin&&n.setRequestHeader("X-NewRelic-ID",i.xpid);var a=o.generateTracePayload(this.parsedOrigin);if(a){var s=!1;a.newrelicHeader&&(n.setRequestHeader("newrelic",a.newrelicHeader),s=!0),a.traceContextParentHeader&&(n.setRequestHeader("traceparent",a.traceContextParentHeader),a.traceContextStateHeader&&n.setRequestHeader("tracestate",a.traceContextStateHeader),s=!0),s&&(this.dt=a)}}function d(e,t){var r=this.metrics,i=e[0],o=this;if(r&&i){var a=V(i);a&&(r.txSize=a)}this.startTime=(0,p.z)(),this.listener=function(e){try{"abort"!==e.type||o.loadCaptureCalled||(o.params.aborted=!0),("load"!==e.type||o.called===o.totalCbs&&(o.onloadCalled||"function"!=typeof t.onload)&&"function"==typeof o.end)&&o.end(t)}catch(e){try{n.emit("internal-error",[e])}catch(e){}}};for(var s=0;s 1?e[1]=i:e.push(i)}else e[0]&&e[0].headers&&s(e[0].headers,n)&&(this.dt=n);function s(e,t){var r=!1;return t.newrelicHeader&&(e.set("newrelic",t.newrelicHeader),r=!0),t.traceContextParentHeader&&(e.set("traceparent",t.traceContextParentHeader),t.traceContextStateHeader&&e.set("tracestate",t.traceContextStateHeader),r=!0),r}}function x(e,t){this.params={},this.metrics={},this.startTime=(0,p.z)(),this.dt=t,e.length>=1&&(this.target=e[0]),e.length>=2&&(this.opts=e[1]);var r,n=this.opts||{},i=this.target;"string"==typeof i?r=i:"object"==typeof i&&i instanceof Y?r=i.url:c._A?.URL&&"object"==typeof i&&i instanceof URL&&(r=i.href),T(this,r);var o=(""+(i&&i instanceof Y&&i.method||n.method||"GET")).toUpperCase();this.params.method=o,this.txSize=V(n.body)||0}function A(t,r){var n;this.endTime=(0,p.z)(),this.params||(this.params={}),this.params.status=r?r.status:0,"string"==typeof this.rxSize&&this.rxSize.length>0&&(n=+this.rxSize);var o={txSize:this.txSize,rxSize:n,duration:(0,p.z)()-this.startTime};i("xhr",[this.params,o,this.startTime,this.endTime,"fetch"],this,e.D.ajax)}function E(t){var r=this.params,n=this.metrics;if(!this.ended){this.ended=!0;for(var o=0;o 2&&void 0!==arguments[2])||arguments[2];super(e,t,we.t,r),this.importAggregator()}}new class{constructor(e){let t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:(0,_.ky)(16);c._A?(this.agentIdentifier=t,this.sharedAggregator=new y({agentIdentifier:this.agentIdentifier}),this.features={},this.desiredFeatures=new Set(e.features||[]),this.desiredFeatures.add(m),Object.assign(this,(0,a.j)(this.agentIdentifier,e,e.loaderType||"agent")),this.start()):(0,l.Z)("Failed to initial the agent. Could not determine the runtime environment.")}get config(){return{info:(0,t.C5)(this.agentIdentifier),init:(0,t.P_)(this.agentIdentifier),loader_config:(0,t.DL)(this.agentIdentifier),runtime:(0,t.OP)(this.agentIdentifier)}}start(){const t="features";try{const r=n(this.agentIdentifier),i=[...this.desiredFeatures];i.sort(((t,r)=>e.p[t.featureName]-e.p[r.featureName])),i.forEach((t=>{if(r[t.featureName]||t.featureName===e.D.pageViewEvent){const n=function(t){switch(t){case e.D.ajax:return[e.D.jserrors];case e.D.sessionTrace:return[e.D.ajax,e.D.pageViewEvent];case e.D.sessionReplay:return[e.D.sessionTrace];case e.D.pageViewTiming:return[e.D.pageViewEvent];default:return[]}}(t.featureName);n.every((e=>r[e]))||(0,l.Z)("".concat(t.featureName," is enabled but one or more dependent features has been disabled (").concat((0,D.P)(n),"). This may cause unintended consequences or missing data...")),this.features[t.featureName]=new t(this.agentIdentifier,this.sharedAggregator)}})),(0,T.Qy)(this.agentIdentifier,this.features,t)}catch(e){(0,l.Z)("Failed to initialize all enabled instrument classes (agent aborted) -",e);for(const e in this.features)this.features[e].abortHandler?.();const r=(0,T.fP)();return delete r.initializedAgents[this.agentIdentifier]?.api,delete r.initializedAgents[this.agentIdentifier]?.[t],delete this.sharedAggregator,r.ee?.abort(),delete r.ee?.get(this.agentIdentifier),!1}}}({features:[J,m,S,class extends h{static featureName=oe;constructor(t,r){if(super(t,r,oe,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;const n=this.ee;let i;(0,k.QU)(n),this.eventsEE=(0,k.em)(n),this.eventsEE.on(se,(function(e,t){this.bstStart=(0,p.z)()})),this.eventsEE.on(ae,(function(t,r){(0,s.p)("bst",[t[0],r,this.bstStart,(0,p.z)()],void 0,e.D.sessionTrace,n)})),n.on(ce+ne,(function(e){this.time=(0,p.z)(),this.startPath=location.pathname+location.hash})),n.on(ce+ie,(function(t){(0,s.p)("bstHist",[location.pathname+location.hash,this.startPath,this.time],void 0,e.D.sessionTrace,n)}));try{i=new PerformanceObserver((t=>{const r=t.getEntries();(0,s.p)(te,[r],void 0,e.D.sessionTrace,n)})),i.observe({type:re,buffered:!0})}catch(e){}this.importAggregator({resourceObserver:i})}},C,xe,B,class extends h{static featureName=de;constructor(e,r){if(super(e,r,de,!(arguments.length>2&&void 0!==arguments[2])||arguments[2]),!c.il)return;if(!(0,t.OP)(e).xhrWrappable)return;try{this.removeOnAbort=new AbortController}catch(e){}let n,i=0;const o=this.ee.get("tracer"),a=(0,k._L)(this.ee),s=(0,k.Lg)(this.ee),u=(0,k.BV)(this.ee),d=(0,k.Kf)(this.ee),f=this.ee.get("events"),l=(0,k.u5)(this.ee),h=(0,k.QU)(this.ee),g=(0,k.Gm)(this.ee);function m(e,t){h.emit("newURL",[""+window.location,t])}function v(){i++,n=window.location.hash,this[ve]=(0,p.z)()}function b(){i--,window.location.hash!==n&&m(0,!0);var e=(0,p.z)();this[pe]=~~this[pe]+e-this[ve],this[ye]=e}function y(e,t){e.on(t,(function(){this[t]=(0,p.z)()}))}this.ee.on(ve,v),s.on(be,v),a.on(be,v),this.ee.on(ye,b),s.on(ge,b),a.on(ge,b),this.ee.buffer([ve,ye,"xhr-resolved"],this.featureName),f.buffer([ve],this.featureName),u.buffer(["setTimeout"+le,"clearTimeout"+fe,ve],this.featureName),d.buffer([ve,"new-xhr","send-xhr"+fe],this.featureName),l.buffer([me+fe,me+"-done",me+he+fe,me+he+le],this.featureName),h.buffer(["newURL"],this.featureName),g.buffer([ve],this.featureName),s.buffer(["propagate",be,ge,"executor-err","resolve"+fe],this.featureName),o.buffer([ve,"no-"+ve],this.featureName),a.buffer(["new-jsonp","cb-start","jsonp-error","jsonp-end"],this.featureName),y(l,me+fe),y(l,me+"-done"),y(a,"new-jsonp"),y(a,"jsonp-end"),y(a,"cb-start"),h.on("pushState-end",m),h.on("replaceState-end",m),window.addEventListener("hashchange",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("load",m,(0,O.m$)(!0,this.removeOnAbort?.signal)),window.addEventListener("popstate",(function(){m(0,i>1)}),(0,O.m$)(!0,this.removeOnAbort?.signal)),this.abortHandler=this.#e,this.importAggregator()}#e(){this.removeOnAbort?.abort(),this.abortHandler=void 0}}],loaderType:"spa"})})(),window.NRBA=o})(); window.jQuery || document.write(' ') CKEDITOR_BASEPATH='https://f1000research.com/js/vendor/ckeditor/' window.reactTheme = 'research'; window.MathJax = { CommonHTML: { linebreaks: { automatic: true } }, 'HTML-CSS': { linebreaks: { automatic: true } }, SVG: { linebreaks: { automatic: true } }, AuthorInit: function() { MathJax.Hub.Register.MessageHook('End Process', function () { let timeout = false; // holder for timeout id const delay = 250; // delay after event is "complete" to run callback const reflowMath = function() { const dispFormulas = document.querySelectorAll('.disp-formula.panel'); if (!dispFormulas) { return; } for (const dispFormula of dispFormulas) { const child = dispFormula.querySelector('.MathJax_Preview').nextSibling.firstChild; const isMultiline = MathJax.Hub.getAllJax(dispFormula)[0].root.isMultiline; if (dispFormula.offsetWidth < child.offsetWidth || isMultiline) { MathJax.Hub.Queue(['Rerender', MathJax.Hub, dispFormula]); } } }; window.addEventListener('resize', function() { clearTimeout(timeout); // clear the timeout timeout = setTimeout(reflowMath, delay); // start timing for event "completion" }); }); }, }; if (window.location.hash == '#_=_'){ window.location = window.location.href.split('#')[0] } !function(f,b,e,v,n,t,s){if(f.fbq)return;n=f.fbq=function() {n.callMethod? n.callMethod.apply(n,arguments):n.queue.push(arguments)} ;if(!f._fbq)f._fbq=n; n.push=n;n.loaded=!0;n.version='2.0';n.queue=[];t=b.createElement(e);t.async=!0; t.src=v;s=b.getElementsByTagName(e)[0];s.parentNode.insertBefore(t,s)}(window, document,'script','https://connect.facebook.net/en_US/fbevents.js'); fbq('init', '1641728616063202'); fbq('track', "PixelInitialized", {}); (function(h,o,t,j,a,r){ h.hj=h.hj||function(){(h.hj.q=h.hj.q||[]).push(arguments)}; h._hjSettings={hjid:2318163,hjsv:6}; a=o.getElementsByTagName('head')[0]; r=o.createElement('script');r.async=1; r.src=t+h._hjSettings.hjid+j+h._hjSettings.hjsv; a.appendChild(r); })(window,document,'https://static.hotjar.com/c/hotjar-','.js?sv='); search file_upload Submit your research search menu close search Browse Gateways & Collections How to Publish Submit your Research My Submissions Article Guidelines Article Guidelines (New Versions) Open Data, Software and Code Guidelines Open Data and Accessible Source Materials Guidelines (HSS) Open Data, Software and Code Guidelines (PSE) Prepublication Checks Production Process Posters and Slides Guidelines Document Guidelines Article Processing Charges Peer Review Finding Article Reviewers About How it Works For Reviewers Our Advisors Policies Glossary FAQs For Developers Newsroom Contact My Research Submissions Content and Tracking Alerts My Details Sign In file_upload Submit your research { "@context": "https://schema.org", "@type": "ScholarlyArticle", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://f1000research.com/articles/15-521" }, "headline": "Assessment of the Medication Errors by Nurses in an Emergency Department: A Cross-Sectional Study", "datePublished": "2026-04-15T10:29:38", "dateModified": "2026-04-15T10:29:38", "author": [ { "@type": "Person", "name": "Zafar ALI" }, { "@type": "Person", "name": "Anum Fatima QAZI" }, { "@type": "Person", "name": "Mohammad Shahab KHAN" }, { "@type": "Person", "name": "Khurshed ALI" }, { "@type": "Person", "name": "Amir SULTAN" }, { "@type": "Person", "name": "Muhammad ASIM" }, { "@type": "Person", "name": "Zala ." }, { "@type": "Person", "name": "Nauman ARIF" }, { "@type": "Person", "name": "Saima AFAQ" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": " Background Medication errors (MEs) are a global public health concern associated with adverse outcomes, treatment failure, and increased hospital stay. The World Health Organization has declared them endemic. Evidence on ME prevalence in emergency departments (EDs) in resource-limited settings such as Pakistan is scarce. This study aimed to determine the rates, types, and contributing factors of MEs in an ED in Peshawar, Pakistan. Methods A cross-sectional study was conducted from December 2021 to August 2022 among 68 registered nurses, using convenience sampling. Medication practices were observed across four phases: preparation, administration, documentation, and prescription. A total of 1,053 doses were recorded using a direct observation form, covering 11 categories of errors. The Wakefield Questionnaire was applied to assess perceived contributing factors. Data were analyzed using SPSS version 22. Results Medication errors occurred in 53.1% of doses, with the highest rates in the Neuro Trauma (25.4%) and Surgical (24.7%) units. Errors most frequently occurred during preparation (35.7%) and administration (34.9%). The most common error types were wrong time (28%) and wrong technique (20%). Key contributing factors included inadequate nurse staffing, frequent physician order changes, look-alike drug packaging, and patients receiving similar medications. Conclusion Medication errors are frequent in EDs, particularly during preparation and administration. Strengthening nursing competencies, enforcing strict guidelines, and improving coordination are critical to reducing errors and enhancing patient safety. " } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/15-521", "name": "Assessment of the Medication Errors by Nurses in an Emergency Department:..." } } ] } Home Browse Assessment of the Medication Errors by Nurses in an Emergency Department:... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article ALI Z, Fatima QAZI A, KHAN MS et al. Assessment of the Medication Errors by Nurses in an Emergency Department: A Cross-Sectional Study [version 1; peer review: awaiting peer review] . F1000Research 2026, 15 :521 ( https://doi.org/10.12688/f1000research.171032.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Assessment of the Medication Errors by Nurses in an Emergency Department: A Cross-Sectional Study [version 1; peer review: awaiting peer review] Zafar ALI 1 , Anum Fatima QAZI https://orcid.org/0009-0005-4198-3132 1 , Mohammad Shahab KHAN 2 , [...] Khurshed ALI https://orcid.org/0009-0007-2175-8303 3 , Amir SULTAN 4 , Muhammad ASIM 1 , Zala . 1 , Nauman ARIF 1 , Saima AFAQ https://orcid.org/0000-0002-9080-2220 5 Zafar ALI 1 , Anum Fatima QAZI https://orcid.org/0009-0005-4198-3132 1 , [...] Mohammad Shahab KHAN 2 , Khurshed ALI https://orcid.org/0009-0007-2175-8303 3 , Amir SULTAN 4 , Muhammad ASIM 1 , Zala . 1 , Nauman ARIF 1 , Saima AFAQ https://orcid.org/0000-0002-9080-2220 5 PUBLISHED 15 Apr 2026 Author details Author details 1 Institute of Public Health & Social Sciences, Khyber Medical University, Peshawar, Khyber Pakhtunkhwa, 25000, Pakistan 2 Nursing Department, RN Saidu Group of Teaching Hospital, Saidu Medical College, SWAT, Khyber Pakhtunkhwa, Pakistan 3 Nursing Department, The Aga Khan University Medical College Pakistan, Karachi, Sindh, Pakistan 4 Nursing Department, Times University, Multan, Punjab, Pakistan 5 Department of Health sciences, University of York, York, England, UK Zafar ALI Roles: Conceptualization, Investigation, Methodology Anum Fatima QAZI Roles: Writing – Review & Editing Mohammad Shahab KHAN Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – Original Draft Preparation Khurshed ALI Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – Original Draft Preparation Amir SULTAN Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation Muhammad ASIM Roles: Writing – Review & Editing Zala . Roles: Writing – Review & Editing Nauman ARIF Roles: Writing – Review & Editing Saima AFAQ Roles: Funding Acquisition, Supervision OPEN PEER REVIEW REVIEWER STATUS AWAITING PEER REVIEW This article is included in the Health Services gateway. Abstract Background Medication errors (MEs) are a global public health concern associated with adverse outcomes, treatment failure, and increased hospital stay. The World Health Organization has declared them endemic. Evidence on ME prevalence in emergency departments (EDs) in resource-limited settings such as Pakistan is scarce. This study aimed to determine the rates, types, and contributing factors of MEs in an ED in Peshawar, Pakistan. Methods A cross-sectional study was conducted from December 2021 to August 2022 among 68 registered nurses, using convenience sampling. Medication practices were observed across four phases: preparation, administration, documentation, and prescription. A total of 1,053 doses were recorded using a direct observation form, covering 11 categories of errors. The Wakefield Questionnaire was applied to assess perceived contributing factors. Data were analyzed using SPSS version 22. Results Medication errors occurred in 53.1% of doses, with the highest rates in the Neuro Trauma (25.4%) and Surgical (24.7%) units. Errors most frequently occurred during preparation (35.7%) and administration (34.9%). The most common error types were wrong time (28%) and wrong technique (20%). Key contributing factors included inadequate nurse staffing, frequent physician order changes, look-alike drug packaging, and patients receiving similar medications. Conclusion Medication errors are frequent in EDs, particularly during preparation and administration. Strengthening nursing competencies, enforcing strict guidelines, and improving coordination are critical to reducing errors and enhancing patient safety. READ ALL READ LESS Keywords Medication Error, Nurses, Emergency Department, Emergency Services. Corresponding Author(s) Saima AFAQ ( [email protected] ) Close Corresponding author: Saima AFAQ Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2026 ALI Z et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: ALI Z, Fatima QAZI A, KHAN MS et al. Assessment of the Medication Errors by Nurses in an Emergency Department: A Cross-Sectional Study [version 1; peer review: awaiting peer review] . F1000Research 2026, 15 :521 ( https://doi.org/10.12688/f1000research.171032.1 ) First published: 15 Apr 2026, 15 :521 ( https://doi.org/10.12688/f1000research.171032.1 ) Latest published: 15 Apr 2026, 15 :521 ( https://doi.org/10.12688/f1000research.171032.1 ) 1. Introduction Medication administration is a complex, multidisciplinary, and significant process in the emergency departments (ED) of healthcare facilities worldwide. A large number of medications are administered to patients each day in these healthcare facilities. During such complex and multidisciplinary processes, medication errors (MEs) commonly occur and almost 90% of the cases are kept unreported, particularly in emerging countries, potentially leading to severe adverse outcomes for patients with serious multifaceted medical illnesses. 1 , 2 Like the “tip of the iceberg”, reported errors are a small subsection of the sum of all errors. A study revealed that only 1.6% to 38% of MEs are reported among all administered medications, and it is estimated that reported errors constitute only 25% of all errors. 3 Wrong use of medication is one of the most common types of medical errors. 4 Thus, “Medication Error” is defined as any error that occurs during the medication process, including prescribing, distributing, transcribing, administering, and documenting, whether or not it was captured and corrected before reaching the patient or has the potential to harm the patient. 5 Operationally, a “Medication Error” can be termed as wrong (drug, dose, patient, route, documentation, preparation, time, technique), administration of a defunct drug, or omission of a prescribed drug that may be avoided and may cause harm to the patient. In the hospital setting, MEs can occur at any stage of the medication process, including prescribing, preparation, administration, and documentation. 1 , 5 Globally, approximately 10% of patients suffer from medical errors, costing $42 billion annually, which represents 1% of global health expenditure. Thus, the World Health Organisation (WHO) has recognised the issue as an endemic. 6 , 4 MEs cost about $4 billion annually (IOM, 2007) and have a major impact on patient care 2 , 7 Therefore, patient safety has become a significant global public health issue and MEs are increasingly seen as a significant safety risk. 8 , 9 It was reported that between 18.7% and 56% of all hospitalised patients experience MEs at some point during their hospital stay. 10 Medication processing is one of the most sensitive tasks for nurses and they are likely at risk of MEs. Research indicates that nurses spend more than 40% of their time administrating medication. Nurses play an important role among all healthcare groups and are full-time accountable for the care or safety of patients. 11 The errors nurses make can lead to several direct and indirect adverse outcomes. Due to the rapid leap, overcrowding, and instability, the ED is a high risk area for MEs 12 , 5 Consequently, providing accurate information on MEs is the most significant step to avoiding MEs in an ED. Such information could accelerate an acceptable preventive method for safe practices in the future. Therefore, this study aims to determine rates and types of MEs and explore possible risk factors for these errors in the ED. 2. Materials and methods 2.1 Study design and setting This study used a direct observation-based cross-sectional design and was conducted in the ED of a tertiary care hospital in Peshawar from December 2021 to August 2022. The study population included all clinical nurses in the ED who met the inclusion criteria. The ED in this hospital comprises 200 beds and receives nearly 3,000 to 4,000 patients per day seeking initial treatment. 13 In this observational-based study, nurses were randomly selected from the five units of the ED. The ED reported approximately 7.70 lakh patients in 2020. 13 This statistical figure shows that the possibility of MEs is greater in this setting due to its acute dynamic clinical picture, overcrowding, high patient turnover, and excessive workload. 2.2 Sample size The first sample size was based on research studies published by Khowaja et al, where a convenience sample of 1053 doses was monitored through a structured medication observation form. 3 A random selection of observed nurses was made in 68 enrolled participants based on observed shifts, and no prior selection of nurses was made. Each prescribed IV, IM, or subcutaneous medication at one time per patient was counted as a single dose, and all prescribed oral medication at one time per patient was considered as a second separate dose. For the second sample size according to the census, 68 nurses were enrolled in the study to explore their perceptions of risk factors for MEs committed by nurses in the ED. All registered nurses (RNs) directly involved in the medication process were included, while student nurses and nurses who did not agree to participate in the study were excluded. 2.3 Data collection procedure and tools The synopsis of this project was approved by the Advance Studies and Review Board and ORIC of Khyber Medical University. The objectives and aim of the study were clearly defined, and both verbal and written informed consent were taken from the study participants. To minimise the “Hawthorne Effect” the word ‘error’ was not disclosed to RNs during data collection. Three types of questionnaires were used: “Demographic information questionnaire”, “Wakefield questionnaire of factors”, and “Direct medication observation form”. A questionnaire related to demographic information of nurses (i.e. age group, gender, marital status, work experience, education, and job position) and “Wakefield questionnaires of factors” were distributed among the RNs in the five units and were returned to the distributor in the next two to three days. Data was collected using three questionnaires. 1) A questionnaire related to demographic information of nurses (i.e. age group, gender, marital status, work experience, education, and job position). 2) A validated ‘structured medication observation form” (11 items) to determine the frequency and types of medication errors. This tool demonstrated Cronbach’s alpha of 0.780 indicating good reliability. 3) The Wakefield questionnaire (29 Items) to assess the factors contributing to MEs. The tool has been previously used and shown the reliability of (α = 0.76) for questions related to communication (α = 0.80) for packaging, (α = 0.77) for transcription, (α = 0.66) for working conditions (α = 0.66), and (α = 0.66) for pharmacy-related question. 14 The “Direct medication observation form” was used to monitor a sample of 1053 doses from 8:00 AM to 2:00 PM and from 2:00 PM to 8:00 PM in four phases on days other than Sunday, recorded over two months. All ordered doses were conveniently observed and documented, considering ethical considerations. When a potentially harmful drug error was detected before administration, the nurse was requested to review the medication. 2.4 Data analysis The data was analysed using IBM’s Statistical Package for the Social Sciences (SPSS) version 22.0 software. Descriptives and Inferential statistics were performed. Categorical data was reported as frequencies and percentages and continuous data was reported as mean (SD). Associations between the Medication error (Yes/No) and other explanatory variables were tested using the Chi-square test. Multivariate logistic regression was applied to obtain an adjusted odds ratio for potential confounders. A P-value of <0.05 was considered a statistical significance level. 3. Results According to the results of this study, 73.5% of nurses were female, while 26.5% were male. Out of the total number of study participants (N = 68), 55.9% (n = 38) of the registered nurses were unmarried or single, while 44.1% (n = 30) were married. When comparing the education level of the study participants, it was found that the majority of the registered nurses held a diploma in nursing (64.7%), while the rest of the registered nurses had a Bachelor’s degree in nursing (35.3%). The results indicated that 83.8% (n = 57) of registered nurses worked as employees in medical teaching institutes, while 16.2% (n = 11) of registered nurses were civil servants. Working shifts were categorised into four groups, with 48.5% (33) of the registered nurses working in the fixed morning shift, 27.9% (n = 19) in the evening shift, and 1.5% (n = 1) in the night shift, while 22.1% (n = 15) of the registered nurses worked in rotation. The work units were categorised into five units, with 26.5% (n = 18) of the registered nurses assigned to the Orthopedic unit, 25% (n = 17) to the medical unit, 17.6% (n = 12) to Neuro Trauma and Surgical unit, and 13.2% (n = 9) to the CCU unit ( Table 1 ).53.2% (n = 560) of the doses were observed in male patients and 46.8% (n = 493) in female patients. The MEs were detected in 53.1% (n = 559) of doses. The units with the highest probability of MEs were Neuro Trauma 25.4% (n = 142) and Surgical Unit 24.7% (n = 138) ( Figure 1 , and Tables 1 and 2 ). Each wrong dose was further observed across the 11 types of MEs where an additional 1029 errors were collected by further observing 559 wrong doses ( Tables 3 , 4 and 5 ). Table 1. Sociodemographic characteristics of nurses working in the ED. Sociodemographic characteristics of nurses working in the emergency department Variables Frequency Percentage Gender Male 18 26.5% Female 50 73.5% Age (Mean) * 27.8 ± 4.3 Marital Status Single 38 55.9% Married 30 44.1% Education Diploma In Nursing 44 64.7% BS In Nursing 24 35.3% Hospital Status Government 11 16.2% Medical Teaching Institute 57 83.8% Working Shift Morning Shift 33 48.5% Evening Shift 19 27.9% Night Shift 1 1.5% Rotation 15 22.1% Working Units Critical Care Unit 9 13.2% Medical 17 25.0% Neuro-Trauma 12 17.6% Orthopaedic 18 26.5% Surgical 12 17.6% * Age is presented as Mean, while all other variables are expressed in frequencies and percentages. Figure 1. Medication errors departmentally. Table 2. Frequencies and percentages of route of administration of dose observed and shift of dose observation. Variables Frequency Percentage Route Of Administration of Dose Observed Oral 157 14.9% Intravenous, Intramuscular, Subcutaneous 896 85.1% Shift Of Dose Observation Morning Shift 377 35.8% Evening Shift 676 64.2% Table 3. Frequencies of weekly dose observations and MEs. Units Critical care unit Medical Neuro trauma Surgical Orthopedic Total Total Observations Per Week 215 (20.4) 231 (21.9) 232 (22.0) 243 (23.1) 132 (12.5) 1053 (100) Medication Observation Errors Errors (Yes) 68 (12.2) 137 (24.5) 142 (25.4) 138 (24.7) 74 (13.2) 559 (53.1) Phases Of Errors Prescribing 15 (8.1) 26 (5.4) 30 (5.8) 25 (4.7) 8 (3.0) 104 (5.3) Preparation 63 (34.2) 182 (37.9) 177 (34.0) 182 (34.4) 104 (39.1) 708 (35.7) Administration 75 (40.8) 162 (33.7) 180 (34.5) 176 (33.3) 99 (37.2) 692 (34.9) Documentation 31 (16.9) 111 (23.0) 134 (25.7) 146 (27.6) 55 (20.7) 477 (24.1) Total 184 (100) (9.3) 481 (100) (24.3) 521 (100) (26.3) 529 (100) (26.7) 266(100) (13.4) 1981 (100) (100) Table 4. The 11 types of MEs during medication through different phases of the medication process. Type of errors Prescribing Preparation Administration Documentation Wrong Technique 3 (2.9%) 187 (26.4%) 156 (22.6%) 46 (9.7%) Wrong Patient 0 0 6 (0.9%) 0 Wrong Drug 0 5 (0.7%) 9 (1.3%) 2 (0.4%) Wrong Dose 14 (13.4%) 74 (10.4%) 89 (12.9%) 14 (2.9%) Wrong Preparation 0 54 (7.7%) 15 (2.1%) 2 (0.4%) Wrong Time 0 282 (39.9%) 288 (41.6%) 196 (41.1%) Wrong Route 6 (5.8%) 0 4 (0.6%) 2 (0.4%) Wrong Documentation 35 (33.7%) 0 0 102 (21.4%) Omission 0 101 (14.2%) 115 (16.6%) 104 (21.8%) Expired Drug 0 0 0 0 Other 46 (44.2%) 5 (0.7%) 10 (1.4%) 9 (1.9%) Total 104 (100%) 708 (100%) 692 (100%) 477 (100%) Table 5. The types of errors in different units of ED during the medication process. Types of errors Critical care unit Medical unit Neuro trauma unit Surgical unit Orthopedic unit Total Wrong Technique 3 61 51 57 39 211 (20.5%) Wrong Patient 0 1 3 2 0 6 (0.6%) Wrong Drug 3 1 2 3 0 9 (0.9%) Wrong Dose 37 13 25 20 8 103 (10%) Wrong preparation 1 16 12 13 13 55 (5.4%) Wrong Time 16 77 77 85 34 289 (28%) Wrong Route 1 6 1 2 0 10 (1%) Wrong Documentation 8 29 39 43 16 135 (13.1%) Omission 16 29 47 38 22 152 (14.8%) Expired Drug 0 0 0 0 0 0 Other 10 12 22 11 4 59 (5.7%) Total 95 (9.25%) 245 (23.8%) 279 (27.1%) 274 (26.65%) 136 (13.2%) 1029 (100%) Furthermore, each wrong dose was also observed across the 11 types of errors in the Prescription, Preparation, Administration, and Documentation phase and a total of (n = 1981) sub-errors were identified by further observing 559 wrong doses. The preparation phase was the most common phase for errors 35.7% (n = 708), followed by the administration phase 34.9% (n = 692) ( Table 3 ). In sub-errors, the Surgical Unit was the most prone unit to MEs at 26.7% (n = 529) followed by the Neuro Trauma at 26.3% (n = 521) ( Table 3 ). The most repeated type of error was ‘wrong time’ at 28% (n = 289), most commonly observed in the surgical unit (n = 85) and most commonly occurred during the administration phase at 41.6% (n = 288) out of (n = 692) sub-administration errors, followed by ‘wrong technique’ 20% (n = 211), mostly occurred in the medical unit (n = 61) and prevalently observed at preparation phase 26.4% (n = 187) out of (n = 708) sub-preparation errors ( Table 4 ). A detailed description of every medication error is shown in Tables 4 and 5 . In addition, Table 6 (refer to underlying data)revealed that the factors were classified into five subscales. In the Packaging category, 35.5% (n = 24) of registered nurses felt that “different medications look-alike” as the statement of strong agreement on medication errors. In the communication category, the majority of registered nurses, 51.5% (n = 35), strongly agreed with the statement “Physicians frequently change orders”. In the category of pharmacy, the majority of registered nurses 29.4% (n = 20) moderately agreed with the statement “Many patients are on the similar or same medications”; In the category of working conditions “Unit staffing levels are inadequate” was a strongly agreed statement reflected by the majority of registered nurses 60.3% (n = 41). In the Transcription category, 32.4%(n = 22) of the RNs agreed with the statement “Errors are made in the Medication Kardex”. The results of 29 factors were compared in which the majority of registered nurses, 60.3% (n = 41) strongly agreed that “unit staffing levels are inadequate”, followed by a statement that “Nurses are disturbed while administering medications to perform other duties” the second most strongly agreed statement stated by 58.8% (n = 40) of registered nurses. The strongly disagree factor was “Pharmacists are not available 24 hours a day” reflected by most of the registered nurses 50% (n = 34) followed by a statement that “Errors are made in the drug Kardex”. The moderately disagree statement was considered by 33.8% (n = 23) of registered nurses. In Table 7 , the chi-square analysis illustrates the correlation between the socioeconomic demographics of the nurses and the occurrence of dose errors. Notably, the analysis reveals that factors such as gender (p-value: 0.25), marital status (p-value: 0.543), level of education (p-value: 0.218), employment status (p-value: 0.154), working shift (p-value: 0.10), and working unit (p-value: 0.564) were found to be statistically insignificant in their association with dose errors. Table 8 illustrates the association between various factors, such as route of drug administration (p-value <0.001), shift of dose observation (p-value 0.021), unit of dose observation (p-value 0.000), and dose error, which is highly significant. However, the association between the day of dose observation (p-value 0.6) and dose error is insignificant. Table 7. Association between sociodemographics of nurses and dose error. Parameter Dose error P-value No Yes Gender of the nurse Male 10(55.6%) 8(44.4%) 0.25 Female 20(40%) 30(60%) Marital Status Single 18(47.4%) 20(52.6%) 0.543 Married 12(40%) 18(60%) Level Of Education Diploma 17(38.6%) 27(61.4%) 0.218 Bachelor 13(54.2%) 11(45.8%) Employment Status of Nurses Civil Servant 7(63.6%) 4(36.4%) 0.154 MTI Servant 23(40.4%) 34(59.6%) Working Shift of Nurses Morning Shift 17(51.5%) 16(48.5%) 0.10 Evening Shift 10(52.6%) 9(47.4%) Rotation 3(20%) 12(80%) Night Shift 0(0%) 1(100%) Working Unit Of Nurses CCU Unit 2(22.2%) 7(77.8%) 0.564 Medical Unit 7(41.2%) 10(58.8%) Neuro Trauma Unit 7(58.3%) 5(41.7%) Orthopedic Unit 8(44.4%) 10(55.6%) Surgical Unit 6(50%) 6(50%) Table 8. Association between MEs during dose observation factors and dose error. Parameter Dose error P value No Yes Route Of Administration of Observed Dose Oral 106 (67.5%) 51 (32.5%) <.000 IV, IM, SC 388 (43.3%) 508(56.7%) Day Of Dose Observation Monday 70(50.7%) 68(49.3%) 0.678 Tuesday 152(49.4%) 156(50.6%) Wednesday 50(42.0%) 69(58.0%) Thursday 53(46.5%) 61(53.5%) Friday 86(45.3%) 104(54.7%) Saturday 83(45.1%) 101(54.9%) Unit Of Dose Observation CCU 147(68.4%) 68(31.6%) 0.000 Medical Unit 94(40.7%) 137(59.3%) Neuro Trauma Unit 90(38.8%) 142(61.2%) Surgical 105(43.2%) 138(56.8%) Orthopedic 58(43.9%) 74(56.1%) Shift Of Dose Observation Morning Shift 159(42.2%) 218(57.8%) 0.021 Evening Shift 335(49.6%) 341(50.4%) Table 9 presents a significant association between various types of medication errors in different units of the Emergency Department and dose errors. Notably, there is a highly significant association of Wrong Technique During Observation (p-value <0.001), wrong patient during observation (p-value 0.021), wrong drug during observation (p-value 0.005), Wrong Dose During Observation (p-value <0.001), Wrong Preparation During Observation (p-value <0.001), Wrong Time During Observation (p-value <0.001), Wrong Route During Observation (p-value <0.003), Wrong Documentation During Observation (p-value <0.001), and Omission Of Dose During Observation (p-value <0.001) to dose errors. Table 9. Association between types of MEs in various phases of the medication process and dose error. Parameter Dose error P value No Yes Wrong Technique During Observation Yes 0(0.0%) 211(100%) <0.001 No 494(58.7%) 348(41.3%) Wrong Patient During Observation Yes 0(0.0%) 6(100%) 0.021 No 494(47.2%) 553(52.8%) Wrong Drug During Observation Yes 0(0.0%) 9(100%) 0.005 No 494(47.35) 550(52.7%) Wrong Dose During Observation Yes 0(0.0%) 103(100%) <0.001 No 494(52.0%) 456(48.0%) Wrong Preparation During Observation Yes 0(0%) 55(100%) <0.001 No 494(49.5%) 504(50.5%) Wrong Time During Observation Yes 0(0.0%) 289(100%) <0.001 No 494(64.7%) 270(35.3%) Wrong Route During Observation Yes 0(0.0%) 10(100%) <0.003 No 494(47.4%) 549(52.6%) Wrong Documentation During Observation Yes 0(0.0%) 135(100%) <0.001 No 494(53.8%) 424(46.2%) Omission Of Dose During Observation Yes 0(0.0%) 152(100%) <0.001 No 494(54.8%) 407(45.2%) Table 10 (refer to underlying data) illustrates a univariable logistic regression analysis, the factors associated with Medication Administration Errors (MEs) were examined. The findings revealed an association between married women and MEs compared to single women in which married women had more likelihood of MEs than single nurses but insignificant (OR = 1.35; 95% CI: 0.51–3.55; p-value 0.54). Nurses on rotation than those on the morning shift (OR = 4.24; 95% CI: 1.00–1.90; p-value 0.04), nurses employed as MTI servants than those employed as civil servants in the hospitals (OR = 2.59; 95% CI: 1.00–1.90; p-value 0.04, the Neuro Trauma unit compared to other units such as medical unit, CCU, Surgical, and Orthopedic (OR = 3.41; 95% CI: 2.30–5.03; p-value = 0.000), nurses to make MEs when administering medicine via IV, IM, or SC routes than through oral administration (OR = 2.72; 95% CI: 1.90–3.90; p-value = 0.00) had more likelihood and statistically significant however In the multivariable analysis, the medical unit compared to other units (AOR = 2.62; 95% CI 1.72–4.00, p-value = 0.000), Nurses administering medicine via IV, IM, or SC routes than through oral administration (AOR = 1.80; CI 1.20–2.70, p-value 0.004) had more likelihood and were more significant. 4. Discussion This study aimed to find out MEs by observing the real situation in the ED. With regards to MEs in terms of rate or prevalence, this study revealed an error rate of 53.1% which is much higher compared to a study in Aga Khan University Hospital, Pakistan, having a low rate of 5.5%. 3 However, a study in Iran reported an incidence rate of 50.5% in the ED, which is close to the result of this study. 12 Other studies in southern Iran and Ethiopia showed high incidence rates of 68.5% and 62.7% respectively. 5 Consequently, there are inconsistencies between the rates of errors, making it difficult to relate study results, and the same problem was also found in the previous studies. 14 , 15 This variation may be due to variability or irregularity in the method through which the data is collected (questionnaire, interview, observation), and distinction in the definitions of MEs or may be due to the distinction between quality care in public and private hospitals. The problem is that MEs are a public health concern that could lead to patient insecurity and the need for more attention to prevent errors. 14 In terms of types and phases of MEs, this study revealed that the ‘wrong time’, the ‘wrong technique’ during the preparation and administration phase, and the omission of drugs during the administration, documentation, and preparation phase were the most observable types of errors. Our findings are consistent with previous studies. Simiyu et al. revealed that ‘wrong time’ errors are more prevalently observed while nurses administer medications. 17 Harkanen et al. reported that MEs mostly occurred due to ‘wrong techniques’, ‘wrong time’, and omission of medication and documentation. 17 In another study, Dabaghzade F et al. reported administration as the most common phase of errors in the ED and omission as the topmost type of error. 12 The results of this study were found consistent with a systematic review study conducted in eleven Southeast Asian countries. 18 The same results were also found in the previous observational studies respectively. 4 , 17 These results show that nurses committed errors mostly at the time of preparation and administration phase. Therefore, nurses must have sufficient pharmacological knowledge and have full control over the medication process to minimise these types of errors in future. There should be a strong revealing system in the ED for the underlying factors and organised educational program centers based on these factors for nurses to overcome MEs in the ED. Kim J et al. presented that during practice a lot of medication administration instructions and guidelines are not monitored, 17 , 19 additional studies were also found that violated the rules and instructions of medication administration 17 The same problem was found in this study; oral doses were left on patients and their attendants were responsible for self-administration. As a result, based on the previous research, direct observation is considered an effective method for identifying MEs and creating consistent results. 5 , 20 Concerning the nurses’ perceptions of factors related to MEs in the ED, this study categorised twenty-nine factors into five categories. Among these, “working conditions” and “communication” were perceived as the topmost categories with mean values of 4.62 and 4.50. A study presented by Salmani et al reported that communication and working conditions were the two categories of factors that were more involved in MEs as compared to other categories. Furthermore, in the current study working conditions were considered the most prone category and on a Likert scale, the leading factor in this category was “insufficient staffing in the unit” 60.3% of RNs strongly agreed followed by “Nurses are distressed while administering drugs to perform other duties” 58.8%. A study in Iran reported that “ward staff shortage” is the key factor cited by 73% of nurses in this category. 14 Simiyu et al. revealed that “nurses are disturbed in the course of administering drugs to perform other responsibilities” considered the key factor in this category. 16 The results of this study are consistent with the previous studies. Therefore, these results recommended that working condition is the foremost category in MEs. Previous literature revealed that insufficiency in the form of staffing in the clinical areas leads to work burden, exhaustion, and a decline in nurses’ attention that consequently raises the possibility of MEs. 14 So, these findings would be of concern to emergency nursing managers to address and measure the staff’s needs and distress level to reduce MEs in ED. The second topmost category was the communicating category and the most likely factor in this category was “Doctors frequently change orders” 51.5% followed by “Poor communication between RNs and doctors” proposed by 45.6% of RNs. Salmani et al indicated “communication” as the second top category that impacts MEs however, the most dedicated factor in their study was “unclear drug orders” 14 The identified factors in this study are incompatible with the factors that were identified in the previous studies. In prior studies has been shown that installing an electronic system rather than keeping the records manually, especially in the ED of public hospitals, can help to minimise illegibility, ambiguity, and poor communication during the medication process and in such a way the errors can be reduced. 22–24 Packaging was the third category and the most perceived factor in this category was “different medications look-alike”. A study in Kenya reported the same factor that was perceived by the majority of nurses. 16 Another study in Iran also showed the same result. 14 When the medicine is unpacked from its original pack, the chance of errors may be increased with other similar or look-alike medicines, so it should be dispensed directly to patients to avoid errors in the medication process 14 , 16 The resemblance in medicine names, pharmaceutical labels, and packing colour can play a significant role in MEs. 21 In the prior studies, the positive outcome had been achieved in minimising MEs by applying different strategies, therefore the use of various drug-related strategies and compositions, including bold drug names, the use of distinguishable colors, standard fonts and icons can play a vital role in reducing MEs. 22 , 23 In a study by Adam Wondmieneh et al, it was found that nurses working the night shift made 5 times more MEs compared to those working in the morning. However, multivariable analysis in this study indicated that nurses working on rotating shifts made 3.25 times more MEs than those working only in the morning or evening shifts. 24 This study found more MEs by nurses in the medical unit compared to other units. MTI servants also had twice as many MEs as civil servants. However, no previous literature was found on MEs by MTI servants, and there were more MEs in the medical unit. According to this study, multivariable analysis indicated that married women were 1.93 times more likely to make medication errors, but this association was found to be insignificant. This aligns with a study by Seyed Saeed Tabatabaee et al., which found that the relationship between married nurses and MEs was insignificant (p > 0.05). 25 This study found high medication errors (MEs) in the ED, with common errors in preparation and administration. Staffing, communication, and packaging were key concerns. Interventions to address these and explore electronic systems are recommended. Further research is needed on shift rotations and MTI servants’ errors. Limitations of the study: This study is carried out only in the ED of one public tertiary care hospital; the results would be more reliable if carried out in the ED of both types of hospitals (public and private). So, it is not possible to generalise the results or it should be generalised with care and caution. In addition, Observations have been made without external interruptions; there may be some impressions on the clinical performance of nurses, in such conditions, nurses may be more cautious or nervous in the presence of an observer and the chance of MEs may decrease or increase. Strength of the study: The Incidence rate and types of MEs were observed and collected directly at the time of preparation, administration and documentation of the prescribed doses of medications. This study also linked the perceived root causes of MEs in the ED. In our healthcare system, similar to this study, broader-level studies are needed to enhance patient safety and improve the healthcare system. 5. Conclusion EDs are constantly at risk of exposure to MEs due to their dynamic unstable environment. This study found that MEs in an ED are prevalent, and nurses bear a double responsibility for such errors. Furthermore, they are crucial to ensuring patient safety as compared to other workers. As revealed in this study; ‘wrong timing’, ‘wrong technique’, ‘omission of dose’, and ‘wrong documentation’ were the most shared types of errors. The heavy burden of MEs occurred in the preparation and administration phases. Furthermore, the factors that induced MEs in terms of greatest concern were working conditions, communication, and packaging-related factors. MEs were significantly associated with units, routes, and shifts of doses. In general, direct observation is an effective way to control MEs in an ED, as MEs represent a big challenge for healthcare organisations; therefore, it seems important that all tiers including physicians, nurses, clinical pharmacists, and nursing managers involved in the treatment process, must act in line to monitor MEs. Recommendations : Given the positive outcome in the previous studies by implementing strategic recommendations 22 , 23 and as well as in light of the findings of this study, subsequent recommendations can be considered to improve the quality of care such as: 1) Computerised Physician Order Entry is a very beneficial system in the ED, along with Electronic Drug Administration Records involvement by registered nurses. The CPOE and eMAR systems not merely detect and inhibit errors but also avoid delays in prescribing, administration and documentation. 2) The ED must have a full-bodied pharmacy system where the clinical pharmacists prepare prescribed doses of medicines in dilution and then distribute these prepared doses to ED-assigned nurses. 3) Medication error detection software must be installed in every ED. 4) A comparative study of MEs in public and private hospitals should be conducted to gain insight into the rates, types, and causal factors of factual errors. 5) Nursing directors need to be aware of the nurse shortage to control the workload of nurses by providing a sufficient workforce. Ethics and consent This study followed the ethical principles of the Declaration of Helsinki and received approval from the Institutional Review Board (IRB) of Khyber Medical University (Approval No.: Dir/KMU-EB/AM/000853, dated November 10, 2021). Participants were informed about the study’s purpose and procedures, and written informed consent was obtained from all participants prior to data collection. All data were anonymised to ensure confidentiality, and measures were taken to protect the rights and well-being of participants. Informed consent We ensured the ethical standards of our research by obtaining approval from the ASRB of the Institute of Public Health and Social Sciences, KMU, Peshawar, Pakistan. We also secured permission from the respective hospitals and obtained written informed consent from the participants after explaining the purpose of the study to them. Acknowledgement All the registered nurses and other employees of an emergency department are acknowledged for making this research possible. Data availability The datasets generated and analyzed during the current study are openly available in the Figshare repository at https://doi.org/10.6084/m9.figshare.30174583.v2 . 26 The repository includes: • Raw data underlying all reported findings (values behind means, standard deviations, frequencies, and percentages); • Data used to generate tables and figures; • Detailed datasets corresponding to Table 6 and Table 10 (removed from the main manuscript due to size constraints); • Variable definitions and descriptions (e.g., age, gender/sex, occupation, unit, shift); • Extracted values used for analysis; • The study questionnaire and informed consent form (extended data). All data are shared under the Creative Commons Attribution 4.0 International (CC BY 4.0) license and may be freely reused with appropriate attribution to the authors. Reporting guidelines This study was conducted and reported in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for cross-sectional studies. The checklist was used to ensure comprehensive reporting of the study design, participants, methods, results, and interpretation. References 1. None R, None B, Ali S, et al. : Association of medication administration errors with interruption among nurses in public sector tertiary care hospitals. Pakistan journal of medical sciences. 2019 Sept [cited 2025 Sept 21]; 35 (5). Publisher Full Text Reference Source 2. Elden NMK, Ismail A: The Importance of Medication Errors Reporting in Improving the Quality of Clinical Care Services. Global J. Health Sci. 2016 Aug 1; 8 (8): 54510. PubMed Abstract | Publisher Full Text | Free Full Text 3. Khowaja K, Nizar R, Merchant RJ, et al. : A systematic approach of tracking and reporting medication errors at a tertiary care university hospital, Karachi, Pakistan. Ther. Clin. Risk Manag. 2008 Aug; 4 (4): 673–679. Publisher Full Text 4. Izadpanah F, Nikfar S, Bakhshi Imcheh F, et al. : Assessment of Frequency and Causes of Medication Errors in Pediatrics and Emergency Wards of Teaching Hospitals Affiliated to Tehran University of Medical Sciences (24 Hospitals). J. Med. Life. 2018 Oct-Dec; 11 (4): 299–305. PubMed Abstract | Publisher Full Text | Free Full Text 5. Vazin A, Zamani Z, Hatam N: Frequency of medication errors in an emergency department of a large teaching hospital in southern Iran. Drug Healthc Patient Saf. 2014 Dec 11; 6 : 179–184. Publisher Full Text 6. Shenoy R, Scott S, Bhattacharya D: Quantifying and characterising multi-compartment compliance aid provision. Res. Social Adm. Pharm. 2020 Apr; 16 (4): 560–567. Publisher Full Text 7. Graban M: Statistics on healthcare quality and patient safety problems–errors & harm. Retrieved May. 8. Prevalence and causes of wrong time medication administration errors: Experience at a tertiary care hospital in Pakistan.[cited 2024 July 12]. Reference Source 9. Firstenberg MS, Stawicki SP: Teamwork in Healthcare. BoD – Books on Demand; 2021; 192. Publisher Full Text Reference Source 10. Nkurunziza A, Chironda G, Mukeshimana M, et al. : Factors contributing to medication administration errors and barriers to self-reporting among nurses: a review of literature. Rwanda J Med Health Sci. 2019 [cited 2024 July 12]; 2 (3): 294–303. Publisher Full Text Reference Source 11. Frequency, type and causes of medication errors in pediatric wards of hospitals in Yazd, the Central of Iran. Int. J. Pediatr. 2016 [cited 2024 July 12]; 4 (9): 3475–3487. Reference Source 12. Dabaghzadeh F, Rashidian A, Torkamandi H, et al. : Medication errors in an emergency department in a large teaching hospital in tehran. Iran. J. Pharm. Res. 2013 Autumn; 12 (4): 937–942. Reference Source 13. HOME: [cited 2024 July 12]. Reference Source 14. Salmani N, Tafti BF: Frequency, type and causes of medication errors in pediatric wards of hospitals in Yazd, the Central of Iran.2016 Jan 1 [cited 2024 July 12]; 4 (9): 3475–3487. Reference Source 15. Tabatabaee S, Jahromi VK, Asadi M, et al. : Ranking factors contributing to medication error incidents in private hospital: A nurse perspective. international journal of hospital research. 2013 Dec 1; 2 : 187–194. Reference Source 16. Simiyu KN: Nurses’ Medication Administration Errors at Medical Surgical Units. American Journal of Nursing Science. 2018 May 25 [cited 2024 July 12]; 7 (3): 88. Reference Source 17. Härkänen M, Ahonen J, Kervinen M, et al. : The factors associated with medication errors in adult medical and surgical inpatients: a direct observation approach with medication record reviews. Scand. J. Caring Sci. 2015 June; 29 (2): 297–306. PubMed Abstract | Publisher Full Text 18. Salmasi S, Khan TM, Hong YH, et al. : Medication Errors in the Southeast Asian Countries: A Systematic Review. PLoS One. 2015 Sept 4; 10 (9): e0136545. PubMed Abstract | Publisher Full Text | Free Full Text 19. Kim J, Bates DW: Medication administration errors by nurses: adherence to guidelines. J. Clin. Nurs. 2013 Feb; 22 (3–4): 590–598. Publisher Full Text 20. Wilmer A, Louie K, Dodek P, et al. : Incidence of medication errors and adverse drug events in the ICU: a systematic review. Qual. Saf. Health Care. 2010 Oct; 19 (5): e7. PubMed Abstract | Publisher Full Text 21. Jeetu G, Girish T: Prescription drug labeling medication errors: a big deal for pharmacists. J. Young Pharm. 2010 Jan; 2 (1): 107–111. PubMed Abstract | Publisher Full Text | Free Full Text 22. Mieiro DB, de Oliveira BC , da Fonseca REP , et al. : Strategies to minimize medication errors in emergency units: an integrative review. Rev. Bras. Enferm. 2019 Feb; 72 (suppl 1): 307–14. PubMed Abstract | Publisher Full Text 23. Azim M, Khan A, Khan TM, et al. : A cross-sectional study: medication safety among cancer in-patients in tertiary care hospitals in KPK, Pakistan. BMC Health Serv. Res. 2019 Aug 19; 19 (1): 583. PubMed Abstract | Publisher Full Text | Free Full Text 24. Wondmieneh A, Alemu W, Tadele N, et al. : Medication administration errors and contributing factors among nurses: a cross sectional study in tertiary hospitals, Addis Ababa, Ethiopia. BMC Nurs. 2020 Jan 13; 19 : 4. PubMed Abstract | Publisher Full Text | Free Full Text 25. Tabatabaee SS, Ghavami V, Javan-Noughabi J, et al. : Occurrence and types of medication error and its associated factors in a reference teaching hospital in northeastern Iran: a retrospective study of medical records. BMC Health Serv. Res. 2022 Nov 28; 22 (1): 1420. PubMed Abstract | Publisher Full Text | Free Full Text 26. Ali Z: Assessment of the Medication Errors by nurses in an Emergency Department: A cross-sectional study. figshare. 2025. Publisher Full Text Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 15 Apr 2026 ADD YOUR COMMENT Comment Author details Author details 1 Institute of Public Health & Social Sciences, Khyber Medical University, Peshawar, Khyber Pakhtunkhwa, 25000, Pakistan 2 Nursing Department, RN Saidu Group of Teaching Hospital, Saidu Medical College, SWAT, Khyber Pakhtunkhwa, Pakistan 3 Nursing Department, The Aga Khan University Medical College Pakistan, Karachi, Sindh, Pakistan 4 Nursing Department, Times University, Multan, Punjab, Pakistan 5 Department of Health sciences, University of York, York, England, UK Zafar ALI Roles: Conceptualization, Investigation, Methodology Anum Fatima QAZI Roles: Writing – Review & Editing Mohammad Shahab KHAN Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – Original Draft Preparation Khurshed ALI Roles: Conceptualization, Formal Analysis, Investigation, Methodology, Writing – Original Draft Preparation Amir SULTAN Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation Muhammad ASIM Roles: Writing – Review & Editing Zala . Roles: Writing – Review & Editing Nauman ARIF Roles: Writing – Review & Editing Saima AFAQ Roles: Funding Acquisition, Supervision Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (1) version 1 Published: 15 Apr 2026, 15:521 https://doi.org/10.12688/f1000research.171032.1 Copyright © 2026 ALI Z et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article ALI Z, Fatima QAZI A, KHAN MS et al. Assessment of the Medication Errors by Nurses in an Emergency Department: A Cross-Sectional Study [version 1; peer review: awaiting peer review] . F1000Research 2026, 15 :521 ( https://doi.org/10.12688/f1000research.171032.1 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: AWAITING PEER REVIEW AWAITING PEER REVIEW ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Comments on this article Comments (0) Version 1 VERSION 1 PUBLISHED 15 Apr 2026 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status AWAITING PEER REVIEW Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Stay Updated Sign up for content alerts and receive a weekly or monthly email with all newly published articles Register with F1000Research Already registered? Sign in Not now, thanks close PLEASE NOTE If you are an AUTHOR of this article, please check that you signed in with the account associated with this article otherwise we cannot automatically identify your role as an author and your comment will be labelled as a “User Comment”. If you are a REVIEWER of this article, please check that you have signed in with the account associated with this article and then go to your account to submit your report, please do not post your review here. If you do not have access to your original account, please contact us . All commenters must hold a formal affiliation as per our Policies . The information that you give us will be displayed next to your comment. User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions . Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available. I accept the User Comment Terms and Conditions Please confirm that you accept the User Comment Terms and Conditions. Affiliation ✕ refresh Please enter your institution. Note: To add your institution or organisation, start typing the name and then select the correct name from the list. Where applicable, the name will appear in both the original language and in English. Do not paste in the name. If the name does not appear in the drop-down list, we will display the information you have entered. ✕ refresh Country/Region * USA UK Canada China France Germany Afghanistan Aland Islands Albania Algeria American Samoa Andorra Angola Anguilla Antarctica Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Bouvet Island Brazil British Indian Ocean Territory British Virgin Islands Brunei Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Cape Verde Cayman Islands Central African Republic Chad Chile China Christmas Island Cocos (Keeling) Islands Colombia Comoros Congo Cook Islands Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Democratic Republic of the Congo Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Falkland Islands Faroe Islands Federated States of Micronesia Fiji Finland France French Guiana French Polynesia French Southern Territories Gabon Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Heard Island and Mcdonald Islands Holy See (Vatican City State) Honduras Hong Kong Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jersey Jordan Kazakhstan Kenya Kiribati Kosovo (Serbia and Montenegro) Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Macao Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Martinique Mauritania Mauritius Mayotte Mexico Minor Outlying Islands of the United States Moldova Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands Antilles New Caledonia New Zealand Nicaragua Niger Nigeria Niue Norfolk Island North Korea North Macedonia Northern Mariana Islands Norway Oman Pakistan Palau Palestinian Territory Panama Papua New Guinea Paraguay Peru Philippines Pitcairn Poland Portugal Puerto Rico Qatar Reunion Romania Russian Federation Rwanda Saint Helena Saint Kitts and Nevis Saint Lucia Saint Pierre and Miquelon Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Georgia and the South Sandwich Is South Korea South Sudan Spain Sri Lanka Sudan Suriname Svalbard and Jan Mayen Swaziland Sweden Switzerland Syria Taiwan Tajikistan Tanzania Thailand The Gambia The Netherlands Timor-Leste Togo Tokelau Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Turks and Caicos Islands Tuvalu UK USA Uganda Ukraine United Arab Emirates United States Virgin Islands Uruguay Uzbekistan Vanuatu Venezuela Vietnam Wallis and Futuna West Bank and Gaza Strip Western Sahara Yemen Zambia Zimbabwe Please select your country/region. You must enter a comment. Competing Interests Please disclose any competing interests that might be construed to influence your judgment of the article's or peer review report's validity or importance. Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list: Examples of 'Non-Financial Competing Interests' Within the past 4 years, you have held joint grants, published or collaborated with any of the authors of the selected paper. You have a close personal relationship (e.g. parent, spouse, sibling, or domestic partner) with any of the authors. You are a close professional associate of any of the authors (e.g. scientific mentor, recent student). You work at the same institute as any of the authors. You hope/expect to benefit (e.g. favour or employment) as a result of your submission. You are an Editor for the journal in which the article is published. Examples of 'Financial Competing Interests' You expect to receive, or in the past 4 years have received, any of the following from any commercial organisation that may gain financially from your submission: a salary, fees, funding, reimbursements. You expect to receive, or in the past 4 years have received, shared grant support or other funding with any of the authors. You hold, or are currently applying for, any patents or significant stocks/shares relating to the subject matter of the paper you are commenting on. Please state your competing interests The comment has been saved. An error has occurred. Please try again. Cancel Post var lTitle = "Assessment of the Medication Errors by Nurses...".replace("'", ''); var linkedInUrl = "http://www.linkedin.com/shareArticle?url=https://f1000research.com/articles/15-521/v1" + "&title=" + encodeURIComponent(lTitle) + "&summary=" + encodeURIComponent('Read the article by '); var deliciousUrl = "https://del.icio.us/post?url=https://f1000research.com/articles/15-521/v1&title=" + encodeURIComponent(lTitle); var redditUrl = "http://reddit.com/submit?url=https://f1000research.com/articles/15-521/v1" + "&title=" + encodeURIComponent(lTitle); linkedInUrl += encodeURIComponent('ALI Z et al.'); var offsetTop = /chrome/i.test( navigator.userAgent ) ? 4 : -10; var addthis_config = { ui_offset_top: offsetTop, services_compact : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_expanded : "facebook,twitter,www.linkedin.com,www.mendeley.com,reddit.com", services_custom : [ { name: "LinkedIn", url: linkedInUrl, icon:"/img/icon/at_linkedin.svg" }, { name: "Mendeley", url: "http://www.mendeley.com/import/?url=https://f1000research.com/articles/15-521/v1/mendeley", icon:"/img/icon/at_mendeley.svg" }, { name: "Reddit", url: redditUrl, icon:"/img/icon/at_reddit.svg" }, ] }; var addthis_share = { url: "https://f1000research.com/articles/15-521", templates : { twitter : "Assessment of the Medication Errors by Nurses in an Emergency.... ALI Z et al., published by " + "@F1000Research" + ", https://f1000research.com/articles/15-521/v1" } }; if (typeof(addthis) != "undefined"){ addthis.addEventListener('addthis.ready', checkCount); addthis.addEventListener('addthis.menu.share', checkCount); } $(".f1r-shares-twitter").attr("href", "https://twitter.com/intent/tweet?text=" + addthis_share.templates.twitter); $(".f1r-shares-facebook").attr("href", "https://www.facebook.com/sharer/sharer.php?u=" + addthis_share.url); $(".f1r-shares-linkedin").attr("href", addthis_config.services_custom[0].url); $(".f1r-shares-reddit").attr("href", addthis_config.services_custom[2].url); $(".f1r-shares-mendelay").attr("href", addthis_config.services_custom[1].url); function checkCount(){ setTimeout(function(){ $(".addthis_button_expanded").each(function(){ var count = $(this).text(); if (count !== "" && count != "0") $(this).removeClass("is-hidden"); else $(this).addClass("is-hidden"); }); }, 1000); } close How to cite this report {{reportCitation}} Cancel Copy Citation Details $(function(){R.ui.buttonDropdowns('.dropdown-for-downloads');}); $(function(){R.ui.toolbarDropdowns('.toolbar-dropdown-for-downloads');}); $.get("/articles/acj/171032/188570") new F1000.Clipboard(); new F1000.ThesaurusTermsDisplay("articles", "article", "188570"); $(document).ready(function() { $( "#frame1" ).on('load', function() { var mydiv = $(this).contents().find("div"); var h = mydiv.height(); console.log(h) }); var tooltipLivingFigure = jQuery(".interactive-living-figure-label .icon-more-info"), titleLivingFigure = tooltipLivingFigure.attr("title"); tooltipLivingFigure.simpletip({ fixed: true, position: ["-115", "30"], baseClass: 'small-tooltip', content:titleLivingFigure + " " }); tooltipLivingFigure.removeAttr("title"); $("body").on("click", ".cite-living-figure", function(e) { e.preventDefault(); var ref = $(this).attr("data-ref"); $(this).closest(".living-figure-list-container").find("#" + ref).fadeIn(200); }); $("body").on("click", ".close-cite-living-figure", function(e) { e.preventDefault(); $(this).closest(".popup-window-wrapper").fadeOut(200); }); $(document).on("mouseup", function(e) { var metricsContainer = $(".article-metrics-popover-wrapper"); if (!metricsContainer.is(e.target) && metricsContainer.has(e.target).length === 0) { $(".article-metrics-close-button").click(); } }); var articleId = $('#articleId').val(); if($("#main-article-count-box").attachArticleMetrics) { $("#main-article-count-box").attachArticleMetrics(articleId, { articleMetricsView: true }); } }); var figshareWidget = $(".new_figshare_widget"); if (figshareWidget.length > 0) { window.figshare.load("f1000", function(Widget) { // Select a tag/tags defined in your page. In this tag we will place the widget. _.map(figshareWidget, function(el){ var widget = new Widget({ articleId: $(el).attr("figshare_articleId") //height:300 // this is the height of the viewer part. [Default: 550] }); widget.initialize(); // initialize the widget widget.mount(el); // mount it in a tag that's on your page // this will save the widget on the global scope for later use from // your JS scripts. This line is optional. //window.widget = widget; }); }); } close Error Close Add Reset F1000.MICROSERVICES.AFFILIATION = ''; $(document).ready(function () { $('.js-affiliations-form').each((index, form) => { new AffiliationForm({ formId: form.id, institutionErrorSelector: '.comment-enter-institution', departmentErrorSelector: '.comment-enter-department', placeSelector: '.js-add-comment-place', stateSelector: '.js-add-comment-state', zipCodeSelector: '.js-add-comment-zipcode', countrySelector: '.js-add-comment-country', countryErrorSelector: '.comment-enter-country', }); }); }); $(document).ready(function () { var reportIds = { "479111": 0, "479110": 0, "479109": 0, "485956": 0, "479108": 0, "485955": 0, "479107": 0, "485954": 0, "479106": 0, "485953": 0, "479105": 0, "485952": 0, "479104": 0, "479112": 0, "475751": 0, "475759": 0, "475758": 0, "475757": 0, "475756": 0, "475755": 0, "475754": 0, "475753": 0, "475752": 0, "481399": 0, "481398": 0, "481397": 0, "481396": 0, "481395": 0, "475760": 0, "485951": 0, "479103": 0, "485950": 0, "485949": 0, "481404": 0, "485948": 0, "481403": 0, "485947": 0, "481402": 0, "481401": 0, "481400": 0, }; $(".referee-response-container,.js-referee-report").each(function(index, el) { var reportId = $(el).attr("data-reportid"), reportCount = reportIds[reportId] || 0; $(el).find(".comments-count-container,.js-referee-report-views").html(reportCount); }); var uuidInput = $("#article_uuid"), oldUUId = uuidInput.val(), newUUId = "e2f79326-5333-4989-b9a8-52ea13d35463"; uuidInput.val(newUUId); $("a[href*='article_uuid=']").each(function(index, el) { var newHref = $(el).attr("href").replace(oldUUId, newUUId); $(el).attr("href", newHref); }); }); An innovative open access publishing platform offering rapid publication and open peer review, whilst supporting data deposition and sharing. Browse Gateways Collections How it Works Contact For Developers Cookie Notice Privacy Notice RSS Submit Your Research Follow us © 2012-2026 F1000 Research Ltd. ISSN 2046-1402 | Legal | Partner of Research4Life • CrossRef • ORCID • FAIRSharing R.templateTests.simpleTemplate = R.template(' $text $text $text $text $text '); R.templateTests.runTests(); var F1000platform = new F1000.Platform({ name: "f1000research", displayName: "F1000Research", hostName: "f1000research.com", id: "1", editorialEmail: "[email protected]", infoEmail: "[email protected]", usePmcStats: true }); $(function(){R.ui.dropdowns('.dropdown-for-authors, .dropdown-for-about, .dropdown-for-myresearch');}); // $(function(){R.ui.dropdowns('.dropdown-for-referees');}); $(document).ready(function () { if ($(".cookie-warning").is(":visible")) { $(".sticky").css("margin-bottom", "35px"); $(".devices").addClass("devices-and-cookie-warning"); } $(".cookie-warning .close-button").click(function (e) { $(".devices").removeClass("devices-and-cookie-warning"); $(".sticky").css("margin-bottom", "0"); }); $("#tweeter-feed .tweet-message").each(function (i, message) { var self = $(message); self.html(linkify(self.html())); }); $(".partner").on("mouseenter mouseleave", function() { $(this).find(".gray-scale, .colour").toggleClass("is-hidden"); }); }); Sign In Remember me Forgotten your password? Sign In Cancel Email or password not correct. Please try again Please wait... $(function(){ // Note: All the setup needs to run against a name attribute and *not* the id due the clonish // nature of facebox... $("a[id=googleSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("GOOGLE"); $("form[id=oAuthForm]").submit(); }); $("a[id=facebookSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("FACEBOOK"); $("form[id=oAuthForm]").submit(); }); $("a[id=orcidSignInButton]").click(function(event){ event.preventDefault(); $("input[id=oAuthSystem]").val("ORCID"); $("form[id=oAuthForm]").submit(); }); }); If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password. The email address should be the one you originally registered with F1000. Email address not valid, please try again You registered with F1000 via Google, so we cannot reset your password. To sign in, please click here . If you still need help with your Google account password, please click here . You registered with F1000 via Facebook, so we cannot reset your password. To sign in, please click here . If you still need help with your Facebook account password, please click here . Code not correct, please try again Reset password Cancel Email us for further assistance. Server error, please try again. If your email address is registered with us, we will email you instructions to reset your password. If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance. Please wait... Register $(document).ready(function () { signIn.createSignInAsRow($("#sign-in-form-gfb-popup")); $(".target-field").each(function () { var uris = $(this).val().split("/"); if (uris.pop() === "login") { $(this).val(uris.toString().replace(",","/")); } }); });