ICD-1 (Well….near enough)

I’ve taken a slight diversion while looking at Health Information Exchanges (HIE). HIE’s allow clinical information to follow a patient around the healthcare system. What is clear is that the task is made a lot easier if health data is stored in a standardised way. That is a function of the SNOMED/SNOP terminologies. However it is also a feature of the International Classification of Diseases which allows for the communication of diseases using codings.

In previous posts, we looked at the origins of the International Classification of Diseases in the 1893 congress of the International Statistical Institute. The original classification wasn’t a classification of disease but causes of death. The distinction is subtle. Not all diseases necessarily lead to death. Not all causes of death are diseases. In any case, at that point in time the classification scheme reflected the knowledge of the time which has been greatly expanded over the past 120 years.

We are now on ICD-10 and moving towards ICD-11. In previous posts, we looked at the original classification of causes of deaths. So the first revision, we might think of as ICD-1. The only problem there is that ICD now stands for the International Classification of Diseases. Strictly speaking therefore the first revision of the International Causes of Death is not ICD-1 but a revision of Bertillon’s Classification of Causes of Death. For the sake of convenience it seems nevertheless to be considered as ICD-1.

So what did ICD-1 look like? Well the World Health Organisation have an archived copy of ‘ICD-1’ found at their historical collections webpage. The classification is written in French. The revision was again headed by Dr Jacques Bertillon. There are 179 causes of death listed. The causes are classified in several ways – according to the system in the body, the stage in life as well as miscellaneous causes.

On a slightly separate note, there is a reference to the collection of population data by statistical bodies in many countries. The total population included is estimated at 121 million people.

On reflection there is some similarity between the compilation of statistical health data and the storage of health information in databases. There is utility in quantifying this information so as to more easily analyse or store it. There are however additional ways of managing the information which capture more qualitative (intuitive) aspects. The quantification and taxonomising of health information has led to a very stable information infrastructure.

Appendix A – Other Posts in the Series on Health Information Exchanges

A Literature Review of 40 years of SNOMED

Arizona Statewide Health Information Exchange

A History of The Health Information Exchange in Pennsylvania

The Arkansas Health Information Exchange – SHARE

The California Health Information Exchange – Cal Index

Creating a Health Information Exchange in Arizona

Health Information Exchanges

Health Information Exchanges and Chronic Conditions

HIPPA and Health Information Exchanges

ICD-11 and SNOMED CT®

ICD-SNOMED-CT® Harmonisation

Körner Data and SNOMED: A Snapshot from 1988

Mapping ICD 9 (or 10) to SNOMED CT®

Over 1 Million Relationships: SNOMED CT ®

Standardisation of Health Information Technology in New Zealand

Statisticians were Responsible for the Development of an International Classification of Diseases

Why Do We Need Electronic Record Systems to Talk to Each Other

Appendix B – Definition of Health Information Exchange

This is the definition of the Health Information Exchange that I use (Hersh et al, 2015)

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

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

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