Story 1
There was a small research institute with 20 people. Someone among the staff did an online survey to ask everyone their demographic details (name, age, gender, email address) and their diet.
After four months, another person ran another survey. By then there were 23 people in this institute. This surveyor asked everyone their name, email address, haemoglobin.
Now the director of the institute wanted to connect diet to haemoglobin levels. So they took up the older survey and assumed that since email addresses will probably remain the same, they could use that field to "connect" these databases together. But, alas, there was one person who changed her email from @gmail.com to @institute.org
But never mind. They knew who it was. So they just fixed this by copy pasting rows in a spreadsheet.
Story 2
A survey was done in 20 villages. There were two teams of 5 data collectors who divided the villages equally. They went to households and collected from the people demographic details, answers to a lot of questions about health, and also the GPS location of the households.
Then, 5 months later, the PI got more funding to do a haemoglobin study for 600 people. The PI decided to divide this fund in such a way that 300 people who come to a nearby hospital would get tested and 300 people from the previous survey (6 villages) would get tested.
One of the previous data collection teams was called in. Turns out 5 of those villages were surveyed by the same team in the past. Fresh from the previous survey, they went to these villages and quickly located the households they had previously surveyed. Once they were in, they used the names of the individuals to locate their past record from the surveying app and added haemoglobin values too. But in some households there were no people as they had gone for work.
In the remaining one village, they used the GPS location to find out the households. It was slightly harder, but it was doable because the application with which they collected the data could directly point them to the household location. It worked when the GPS would work. When the GPS wouldn't work, they would look at the names of the people in the households and ask people whether they knew where those houses were. Somehow they made it work.
In the hospital, meanwhile, some of those missing people from these villages had come and they were getting haemoglobin tests. But this data was not being collected.
Story 3
The Government of Karnataka decided to do tribal health research. They collected data (demographics, height, weight, BP). Then they assigned to each individual a unique ID number. Something called Namma-ID. They told them that they should keep these Namma-ID numbers safe and that these would give them benefits in healthcare, etc. And someone in the government had the idea that the data they collected should be available for researchers. Any researcher who signs a confidentiality clause would be given all the data (name, father/husband name (still patriarchal in 2021), home address, village name, Namma-ID, etc included). There was one doctor in the area who got themselves access to this data. This doc narrowed down the data to their own village and the set of people with hypertension and saved that in a spreadsheet.
Every time someone came to their clinic, the doctor would ask if they had a Namma-ID and if so the doctor would look at their height, weight, and BP from the GoK data. If they didn't bring their Namma-ID, the doctor would ask their name and try to search. Sometimes the doctor would have to try various spellings to get the right person's record. But somehow the doctor would find the right record and add more details when that particular visit was over.
Then there were times when people who were new to the village came to the doctor's clinic. The doctor would spend minutes searching for this new person's record. The poor villager would be sitting on the patient's chair wondering why the doctor wasn't asking any question about the health issue.
