Matching Patient Records in a HIE

Demographic Chart

In their paper Zech, Husk, Moore and Shapiro compare a social care database with records from Healthix. Healthix is a Health Information Exchange in New York. The aim of the research was to see if a simple tuple (data structure) consisting of first and last names and date of birth were sufficient to uniquely identify patients.

What Did The Researchers Find?

The researchers used two measures of how unique the records were

  • The percentage of records which were unique
  • The (average) number of records corresponding to each tuple

The researchers identified 98.81% of 11,240,288 records as having unique tuples. In the HIE, the number of HIE identifiers per tuple was greater than 1 and increased with the number of facilities visited by patients.

What are the Implications of this Study?

Firstly this is an American study. In the UK, patients have a unique identifier – the NHS number. Secondly there was always more than one record (on average) per tuple in the database. This means that the tuple of first and last name and date of birth by itself is insufficient to discriminate records. If the records were being scanned by a human they would be able to look at additional information to discriminate between the records. However the HIE is using algorithms to compare records. This suggests that further fields should be incorporated into the tuple.

Measuring the Degree of Unmatched Patient Records in a Health Information Exchange

There is a paper by Zech, Husk, Moore and Shapiro titled ‘Measuring the Degree of Unmatched Patient Records in a Health Information Exchange Using Exact Matching‘. The researchers answer the question of how you can match patient records across patient databases in a Health Information Exchange.

Patient Records

Patient records are central to the delivery of healthcare and serve a number of functions including the recording of clinical assessments and interventions. Aggregated data is also utilised at a local and national level to inform commissioning.

Electronic Patient Records

The digitisation of patient records offers a number of advantages over paper based records. These advantages include automated backup of records, reduced use of physical storage space (since paper based notes are switched to servers), off-site access to records using mobile devices and the potential to develop analytical clinical support tools which use computers to process clinical data to help improve clinical decisions. Not all healthcare services have electronic patient records but most providers are moving in this direction.

Getting Electronic Patient Records to Talk to Each Other

When patients move between healthcare providers – for instance between primary care and the hospital – they may find that one provider does not have information that the other provider has. There are many providers and many electronic paper record systems. For two systems to talk to each other they have to solve a number of problems. When these problems are solved a patient can move between providers and healthcare information can be accessed by the different providers. A key solution to this problem of health information gaps is the Health Information Exchange (HIE).

The Health Information Exchange

There are many definitions of what a Health Information Exchange is. (Hersh et al, 2015) define a HIE as follows:

Health information exchange (HIE), the electronic sharing of clinical information across the boundaries of health care organizations’

Whilst this definition is simple, the process of sharing clinical information between healthcare organisations is technically complex and encompasses a range of software, hardware and governance issues. The process of helping systems to talk to each other is helped by the development of standards. A set of standards is outlined in the NHS interoperability framework.

Citations

Zech J, Husk G, Moore T, Shapiro JS.Measuring the Degree of Unmatched Patient Records in a Health Information Exchange Using Exact Matching. Appl Clin Inform. 2016 May 11;7(2):330-40. doi: 10.4338/ACI-2015-11-RA-0158. eCollection 2016.

Links to Other Posts in the Health Information Exchange Series

General Posts to Date on Health Information Exchanges

Posts on Examples of Health Information Exchanges

SNOMED CT®/ICD Mapping and Harmonisation Posts

SNOMED CT® Posts

ICD 1-10 Posts

ICD-11 Posts

Index: There are indices for the TAWOP site here and here

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TAWOP Channel: You can follow the TAWOP Channel on YouTube by clicking on this link.

Responses: If you have any comments, you can leave them below or alternatively e-mail justinmarley17@yahoo.co.uk.

Disclaimer: The comments made here represent the opinions of the author and do not represent the profession or any body/organisation. The comments made here are not meant as a source of medical advice and those seeking medical advice are advised to consult with their own doctor. The author is not responsible for the contents of any external sites that are linked to in this blog.

Conflicts of Interest: *For potential conflicts of interest please see the About section

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