I am parsing this RSS feed ->https://gh.bmj.com/rss/recent.xmlEach <item> block has 2 elements with name <dc:identifier> :
<item rdf:about="http://gh.bmj.com/cgi/content/short/4/4/e001065?rss=1"><title><![CDATA[Use of routinely collected electronic healthcare data for postlicensure vaccine safety signal detection: a systematic review]]></title><link>http://gh.bmj.com/cgi/content/short/4/4/e001065?rss=1</link><description><![CDATA[<sec><st>Background</st> <p>Concerns regarding adverse events following vaccination (AEFIs) are a key challenge for public confidence in vaccination. Robust postlicensure vaccine safety monitoring remains critical to detect adverse events, including those not identified in prelicensure studies, and to ensure public safety and public confidence in vaccination. We summarise the literature examined AEFI signal detection using electronic healthcare data, regarding data sources, methodological approach and statistical analysis techniques used.</p> </sec> <sec><st>Methods</st> <p>We performed a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Five databases (PubMed/Medline, EMBASE, CINAHL, the Cochrane Library and Web of Science) were searched for studies on AEFIs monitoring published up to 25 September 2017. Studies were appraised for methodological quality, and results were synthesised narratively.</p> </sec> <sec><st>Result</st> <p>We included 47 articles describing AEFI signal detection using electronic healthcare data. All studies involved linked diagnostic healthcare data, from the emergency department, inpatient and outpatient setting and immunisation records. Statistical analysis methodologies used included non-sequential analysis in 33 studies, group sequential analysis in two studies and 12 studies used continuous sequential analysis. Partially elapsed risk window and data accrual lags were the most cited barriers to monitor AEFIs in near real-time.</p> </sec> <sec><st>Conclusion</st> <p>Routinely collected electronic healthcare data are increasingly used to detect AEFI signals in near real-time. Further research is required to check the utility of non-coded complaints and encounters, such as telephone medical helpline calls, to enhance AEFI signal detection.</p> </sec> <sec><st>Trial registration number</st> <p>CRD42017072741</p> </sec>]]></description><dc:creator><![CDATA[ Mesfin, Y. M., Cheng, A., Lawrie, J., Buttery, J. ]]></dc:creator><dc:date>2019-07-08T21:52:19-07:00</dc:date><dc:identifier>info:doi/10.1136/bmjgh-2018-001065</dc:identifier><dc:identifier>hwp:master-id:bmjgh;bmjgh-2018-001065</dc:identifier><dc:publisher>BMJ Publishing Group Ltd</dc:publisher><dc:subject><![CDATA[ Open access ]]></dc:subject><dc:title><![CDATA[Use of routinely collected electronic healthcare data for postlicensure vaccine safety signal detection: a systematic review]]></dc:title><prism:publicationDate>2019-07-08</prism:publicationDate><prism:section>Research</prism:section><prism:volume>4</prism:volume><prism:number>4</prism:number><prism:startingPage>e001065</prism:startingPage><prism:endingPage>e001065</prism:endingPage></item>Out of these 2 elements:
<dc:identifier>info:doi/10.1136/bmjgh-2018-001065</dc:identifier><dc:identifier>hwp:master-id:bmjgh;bmjgh-2018-001065</dc:identifier>I want the one which contains the doi - info:doi/10.1136/bmjgh-2018-001065, but when I use python feedparser (https://pythonhosted.org/feedparser/) I only get the second one, my assumption is it's because it gets the value of the first but then overwrites it when it encounters the second element with same name. Is there any way to prevent this or overcome this issue?
