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Coded fairy tales at Medical Informatics Europe conference

16 May

Sleeping Beauty_cropped

by Richard Williams, Software Engineer, NIHR Greater Manchester PSTRC

Niels Peek and Richard Williams from the NIHR Greater Manchester PSTRC’s Safety Informatics theme recently attended Medical Informatics Europe (MIE) in Gothenburg, Sweden. MIE is the leading European health informatics conference and saw delegates attending from all corners of the world. While there, Richard beat off stiff competition to win the prestigious Science Slam – a competition held at MIE where contestants have up to 8 minutes to present their work in a humorous and entertaining way.

Richard talked about clinical codes, which clinicians use as a short cut to describe medical concepts e.g. hypertension is represented by the code G2 and Type 2 diabetes by the code C10F. Richard highlighted the absurdity of some clinical codes such as “U102700 – Fall involving ice-skates, skis, roller-skates or skateboards, occurrence on farm”, the dreaded “TE63100 – Moray eel bite”, and that there are no fewer than 11 codes for falling off a cliff including “U10F200 – Fall from cliff, occurrence at school”.

Richard then translated fairy tales into clinical codes – care to guess the following?

1. Female baby (634..12), black magic (13y8.00), wiccan (13yD.00), puberty (ZV21100), accident caused by spinning machine (TG3y500), excessive sleep (1BX1.00), contact with plant thorns and spines and sharp leaves occurrence at other specified place (U12Ay00), concussion with more than 24 hours loss of consciousness and (S603.00)… manual resuscitation (8731.00) …return to pre-existing conscious level (S603.00 cont.), married (1332.00).

2. Newly wed (1332.12), infertility problem (1AZ2.11), specific food craving (E275800), unborn child subject to child protection plan (13Iv000), female baby (634..12), imprisonment (ZV62511), abnormalities of the hair (M242.00), fall from turret (TC25.00), accident caused by plant thorn (TG4y600), foreign body entering into or through eye or natural orifice occurrence at other specified place (U11Qy00), acquired blindness both eyes (F490900), length of time homeless (13D8.00), tearing eyes (1B87.14), patient cured (2129.00).

3. Female baby (634..12), pale colour (1674.00), mother dead (12K3.00), father remarried (13HJ.00), has stepmother (133D100), hunter’s syndrome (C375.12), ran away (13HW.00), mining engineers (058..12), dwarfism (C1z4.00), found dead (R213100), manual resuscitation (8731.00), found dead (R213100), manual resuscitation (8731.00), found dead (R213100), suspected food poisoning (1J8..00), manual resuscitation (8731.00), married (1332.00).

Answers on a postcard.

On a more serious note, the talk also highlighted that the current coding system used in UK general practice (Read Codes) is in the process of changing to SNOMED (an internationally recognised coding system). This is a major project with potential implications for the continuity of patient care if managed poorly, but also with large implications for researchers in the UK who have much experience of working with databases of Read Codes but little experience of working with SNOMED.

What does the future hold? “God only knows (R2yz.11)”.

Controversial care.data programme closed: What did we learn?

12 Jul

by Rebecca Hays, Research Associate in Multimorbidity theme

careData

After a series of delays, the care.data programme has been closed for good. The decision to end this controversial project was announced following the publication of Dame Fiona Caldicott’s review of health and care data security, consent and opt outs.

The height of the controversy came in February 2014, when the programme was put on hold following NHS England’s highly criticised attempt to inform the public about care.data through a national leaflet drop. Issues with this mail out and the lack of clarity about the project became the subject of many news stories, and a popular topic on social media.

My colleague Gavin Daker-White and I were following the debate on Twitter, where a wide range of views and opinions were being expressed. Tweets highlighted the potential benefits of care.data, revealed worries, provided links to more information, and instructions to opt-out. To better understand the strengths and criticisms of the programme, we undertook a qualitative analysis of tweets containing the hashtag #caredata.

Those for and against the programme shared a range of concerns, including the issues reviewed by Dame Fiona Caldicott. Tweets also identified communication failures, confusion about care.data, and a lack of patient-centeredness. We found these concerns were eroding trust in the healthcare system, which, if ignored, could put patient safety at risk.

Many people will be relieved that the care.data programme has been closed but this is not the end of the story for data sharing in the NHS, and lessons need to be learned. Our work also identified the potential benefits of such projects, for patients and other stakeholders, and recommendations for their design and implementation.

For future programmes to be successful, they must actively engage and involve patients in discussions and decisions about who can access their data and how it can be used. People must also be fully informed about both the risks and benefits of data sharing. Thus, we strongly support Dame Fiona Caldicott’s view that “A key aspect of this work must be a dialogue with the public.”

Note:

Rebecca and Gavin’s paper, “The care.data consensus? A qualitative analysis of opinions expressed on Twitter” was published in BMC Public Health in 2015. A plain English summary [pdf] of this publication is available on our website.