Susan Croft, Joseph Harding, Tom Bircher, Rebecca Hartshorn
{"title":"我的病人怎么了?自动跟踪病人。","authors":"Susan Croft, Joseph Harding, Tom Bircher, Rebecca Hartshorn","doi":"10.1111/medu.15504","DOIUrl":null,"url":null,"abstract":"<p>Reflection is the process where ‘an individual thinks analytically about … their professional practice with the intention of gaining insight and using the lessons learned to maintain good practice or make improvements when possible’.<span><sup>1</sup></span></p><p>It can be challenging and time consuming to access the information required to reflect upon your clinical practice by reviewing the outcomes of individual patients (referred to as patient follow-up). This is particularly the case for acute specialties such as emergency medicine (EM) where the patient is either discharged or moves on to be cared for by another specialty; and for specialties where (perhaps due to shift patterns) there is disjointed continuity of care.</p><p>Information regarding individual patient's ongoing care is commonly recorded in electronic health records (EHR), providing valuable information on their ongoing management, treatment, final diagnosis and outcome.</p><p>This study aimed to automate the process of patient follow up, so rather than individual EM clinician's keeping patient details and manually searching files to find out what happened next/the final diagnosis, this process was automated.</p><p>A novel automated system was developed that provided EM clinicians working at the Northern General Hospital (NGH), Sheffield with patient follow-up information. This collected information from two EHRs in use: ‘Lorenzo’ and ‘ICE’ to generate a list of patients reviewed by each individual clinician and relevant patient outcome data.</p><p>This information was sent by weekly email to EM clinicians of all grades.</p><p>Detailed patient information was presented in separate tables (‘Admissions’, ‘Re-attendances’, ‘Deaths’, ‘Handovers’ and ‘Senior Reviews’).</p><p>For each patient information collected included ‘ED diagnosis’, ‘Destination’ (admitting specialty), ‘Inpatient final diagnosis’ and ‘Length of admission’ (nights).</p><p>This process was implemented in December 2020 and is ongoing. Clinicians experience and opinions on this system was collected via surveys in February 2021 and February 2023. Surveys were opt-in, anonymous, carried out online using Google Forms, available for a two-week period, and distributed by email. They contained single-answer, multiple-choice, and open free text questions.</p><p>Clinicians used the information for workplace-based assessments, supervisor meetings, discussion with peers and to facilitate collection of patient feedback.</p><p>The qualitative feedback was also positive ‘It's brilliant, informative and helpful for me as an established consultant to reflect on the cases I see and advise on’.</p><p>Routine Electronic Health Care record data can be used innovatively to provide feedback on individual patients to healthcare staff to support their reflection, learning and improve patient care.</p><p><b>Susan Croft:</b> Formal analysis; supervision; writing – original draft; writing – review and editing; data curation. <b>Joseph Harding:</b> Conceptualization; investigation; methodology; formal analysis; software; writing – original draft; writing – review and editing; data curation; project administration. <b>Tom Bircher:</b> Conceptualization; investigation; methodology; software; supervision; data curation; writing – review and editing. <b>Rebecca Hartshorn:</b> Formal analysis; writing – review and editing; data curation; project administration.</p><p>None.</p><p>None required.</p>","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":"58 11","pages":"1379-1380"},"PeriodicalIF":4.9000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/medu.15504","citationCount":"0","resultStr":"{\"title\":\"What happened to my patient? 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This is particularly the case for acute specialties such as emergency medicine (EM) where the patient is either discharged or moves on to be cared for by another specialty; and for specialties where (perhaps due to shift patterns) there is disjointed continuity of care.</p><p>Information regarding individual patient's ongoing care is commonly recorded in electronic health records (EHR), providing valuable information on their ongoing management, treatment, final diagnosis and outcome.</p><p>This study aimed to automate the process of patient follow up, so rather than individual EM clinician's keeping patient details and manually searching files to find out what happened next/the final diagnosis, this process was automated.</p><p>A novel automated system was developed that provided EM clinicians working at the Northern General Hospital (NGH), Sheffield with patient follow-up information. This collected information from two EHRs in use: ‘Lorenzo’ and ‘ICE’ to generate a list of patients reviewed by each individual clinician and relevant patient outcome data.</p><p>This information was sent by weekly email to EM clinicians of all grades.</p><p>Detailed patient information was presented in separate tables (‘Admissions’, ‘Re-attendances’, ‘Deaths’, ‘Handovers’ and ‘Senior Reviews’).</p><p>For each patient information collected included ‘ED diagnosis’, ‘Destination’ (admitting specialty), ‘Inpatient final diagnosis’ and ‘Length of admission’ (nights).</p><p>This process was implemented in December 2020 and is ongoing. Clinicians experience and opinions on this system was collected via surveys in February 2021 and February 2023. Surveys were opt-in, anonymous, carried out online using Google Forms, available for a two-week period, and distributed by email. They contained single-answer, multiple-choice, and open free text questions.</p><p>Clinicians used the information for workplace-based assessments, supervisor meetings, discussion with peers and to facilitate collection of patient feedback.</p><p>The qualitative feedback was also positive ‘It's brilliant, informative and helpful for me as an established consultant to reflect on the cases I see and advise on’.</p><p>Routine Electronic Health Care record data can be used innovatively to provide feedback on individual patients to healthcare staff to support their reflection, learning and improve patient care.</p><p><b>Susan Croft:</b> Formal analysis; supervision; writing – original draft; writing – review and editing; data curation. <b>Joseph Harding:</b> Conceptualization; investigation; methodology; formal analysis; software; writing – original draft; writing – review and editing; data curation; project administration. <b>Tom Bircher:</b> Conceptualization; investigation; methodology; software; supervision; data curation; writing – review and editing. <b>Rebecca Hartshorn:</b> Formal analysis; writing – review and editing; data curation; project administration.</p><p>None.</p><p>None required.</p>\",\"PeriodicalId\":18370,\"journal\":{\"name\":\"Medical Education\",\"volume\":\"58 11\",\"pages\":\"1379-1380\"},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/medu.15504\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Medical Education\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/medu.15504\",\"RegionNum\":1,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Education","FirstCategoryId":"95","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/medu.15504","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
What happened to my patient? Automated patient follow-up
Reflection is the process where ‘an individual thinks analytically about … their professional practice with the intention of gaining insight and using the lessons learned to maintain good practice or make improvements when possible’.1
It can be challenging and time consuming to access the information required to reflect upon your clinical practice by reviewing the outcomes of individual patients (referred to as patient follow-up). This is particularly the case for acute specialties such as emergency medicine (EM) where the patient is either discharged or moves on to be cared for by another specialty; and for specialties where (perhaps due to shift patterns) there is disjointed continuity of care.
Information regarding individual patient's ongoing care is commonly recorded in electronic health records (EHR), providing valuable information on their ongoing management, treatment, final diagnosis and outcome.
This study aimed to automate the process of patient follow up, so rather than individual EM clinician's keeping patient details and manually searching files to find out what happened next/the final diagnosis, this process was automated.
A novel automated system was developed that provided EM clinicians working at the Northern General Hospital (NGH), Sheffield with patient follow-up information. This collected information from two EHRs in use: ‘Lorenzo’ and ‘ICE’ to generate a list of patients reviewed by each individual clinician and relevant patient outcome data.
This information was sent by weekly email to EM clinicians of all grades.
Detailed patient information was presented in separate tables (‘Admissions’, ‘Re-attendances’, ‘Deaths’, ‘Handovers’ and ‘Senior Reviews’).
For each patient information collected included ‘ED diagnosis’, ‘Destination’ (admitting specialty), ‘Inpatient final diagnosis’ and ‘Length of admission’ (nights).
This process was implemented in December 2020 and is ongoing. Clinicians experience and opinions on this system was collected via surveys in February 2021 and February 2023. Surveys were opt-in, anonymous, carried out online using Google Forms, available for a two-week period, and distributed by email. They contained single-answer, multiple-choice, and open free text questions.
Clinicians used the information for workplace-based assessments, supervisor meetings, discussion with peers and to facilitate collection of patient feedback.
The qualitative feedback was also positive ‘It's brilliant, informative and helpful for me as an established consultant to reflect on the cases I see and advise on’.
Routine Electronic Health Care record data can be used innovatively to provide feedback on individual patients to healthcare staff to support their reflection, learning and improve patient care.
Susan Croft: Formal analysis; supervision; writing – original draft; writing – review and editing; data curation. Joseph Harding: Conceptualization; investigation; methodology; formal analysis; software; writing – original draft; writing – review and editing; data curation; project administration. Tom Bircher: Conceptualization; investigation; methodology; software; supervision; data curation; writing – review and editing. Rebecca Hartshorn: Formal analysis; writing – review and editing; data curation; project administration.
期刊介绍:
Medical Education seeks to be the pre-eminent journal in the field of education for health care professionals, and publishes material of the highest quality, reflecting world wide or provocative issues and perspectives.
The journal welcomes high quality papers on all aspects of health professional education including;
-undergraduate education
-postgraduate training
-continuing professional development
-interprofessional education