Data Quality and Digitalization

This is in response to a computer guy who wants to digitalize everything in life and matters of importance. I have given a little cross section and at the end a political comment I made during past Donal Trump administration and coronavirus saga where I have written a book in 2020.

It is fast selling in America.

Data Quality and Digitalization 

Data Quality is not a Concept Now

I used to say during my research days if you put garbage in to a computer garbage comes out from the other end.

This invariably happens.

I used to detest meta analysts.

They are the ones who takes sets of  data from others and create a new set of data and assume that the new set is their own creation.

Assumption is a dangerous preoccupation.

It is like religious beliefs.

In reality they have not contributed a single bit of data.

So I collected each piece of data myself and double checked every piece.

No secretary was involved.

I was the secretary.

I was the data collector.

I was the data analyst.

It takes time but reliability stands out.

In big business these three are done by three different guys or girls and a single error is multiplied by three.

Multiple errors leads to multiplex of no validity.

This is where I am against the AI or artificial intelligence.

If you feed inaccurate and inadequate data the outcome is a singularly of nonsense.

Really I was against the medical data formats.

An accurately kept Bed Head Ticket with a ongoing problems and outgoing problems summarised, ideally on weekly basis and if not monthly basis is adequate.

A database is only good enough for retrieving and sorting out two or three cases with identical names.

Nothing more.

The rest becomes redundant statistics.

This does not underscore a simple database kept by a GP with regular contacts of subjects.

Unfortunately most GPS become data collectors and referral agents of substandard quality.

I was obsessed about a database from birth  in my research work but my attempt at extending beyond was futile since the responsibility of tying the knot  was delegated to midwives (mind you, there were a few good ones) who were poorly trained about accuracy, globally, as regards to the biodata collected and recorded on BHTs and the nurses are busy with birth certificates and rest of the clinical work

The final record book was simple but had many errors including the sex of the baby.

Mind you, I cracked the nut.

The global belief is that male babies are bigger and healthy, but in reality the womb of the mother is non discriminatory to the sex of the baby, if Body Mass Indexes (BMII) are compared with the sex (male babies are bit  heavier due their longitudinal scale) of the baby there is no difference irrespective of the sex .

There was no SEX difference except the slight excess of death of male babies of small mothers, who worked until the onset of parturition.Especially so of mothers who were essentially labourers.

The remedy is simple no work after 35 weeks of pregnancy and plenty of sleep and good food.

Iron treatment had no relationship and only two mothers were anaemic (excluded from the main database).

But B vitamins especially soluble ones are important and until.6 months after stopping  breast feeding.

The lactating mother is often neglected and baby is the centre of attraction globally.

 

Regarding Biodata

No immediate cross checks and sometime with inordinate delays due to frequent shift changes.

Palming the buck to next shift is the name of the game.

Whenever I found discrepancy I used to correct them and mothers are really a patient lot in Ceylon but not the fathers.

Instead of a huge database  with errors multiplied but never knowing at which particular point of entry or contact that has happened, a lots of tiny databases with inbuilt validation algorithms are more effective and functional.

It is interesting to know that, a few guys are calling for data quality at entry point.

Like in purifying water by using filters the data pipeline at every point should be narrowed so that very little pass through to the next level.

Less data means easier is to validate and interpret and understand the clinical consequences.

The checking of data quality is a very good step in the right direction.

 

Like diplomats who lie for a living every day of the week and develop fake news for human consumption, media also take the baton forward in the relay cycle but inappropriately magnified.

I am fully with Donald Trump (he with a different objective) attacking the established system which need a total revamp.

For me single voter fraud is big enough and in Ceylon it is systemic and built into the system.

My dead father in law and mother in law voted, probably from heaven, ballot papers taken there, in their luggage to heaven, if not Kamma Compendium.

The above concept is alien to politicians.

They thrive on lies.

Of course people in general love lies in Ceylon especially if magnified by the media.

It is like our 550 Jathaka Katas.

Princess Diana's case in the past and currently "now not royal" Harry's case highlights this scenario in real life.

Unfortunately the medical media also has fallen into this trap deeply and the Coronavirus is a classic example.

Can we believe the data coming from China?

That was my first question when the pandemic begun.

Can we believe WHO?

Can we believe data from Ceylon.

I never believed in our doctored (by the army) data.

The current level of infection is the unfortunate end result.

Do not blame others.

Blame thyself.