Transparency in Action

The Transparency and Choice guideline explains the importance of ensuring that people understand what's happening with their information, the rights they have to access it and request corrections to it, and the importance of offering people choices whenever we are able to.

This 7-page provides practical advice on what good transparency looks like, and the steps that help to achieve it.

Transparency in Action

It’s easy to have a shorthand for describing things, or alternatively to be technically precise but use jargon.

Sometimes the language around data and information doesn’t mean much to people. Without being clear, or by assuming everyone has the same definition, there can be misunderstandings or confusion, which can make people worried, or can lead to mistakes.

The effort to be transparent can be undermined when people don’t understand what they’ve been told.

This summary suggests some simple ways to explain key terms related to data or information. It also walks through key things to consider when developing communication for service users about their data and information. 

The Policy takes a broad definition of “data and information” to mean any kind of qualitative or quantitative information from, or about, services users regardless of whether it identifies them, could identify them, or doesn’t and can’t.

Keep in mind that even if you, or your organisation don’t directly collect data or information from service users, you still need to provide an explanation that would make sense for them.

See the full Transparency and Choice guideline for more information on good practice in this area.

Types of data and information…

The next few pages gives a short description of common terms used to describe data or information. These are not legal definitions, in fact there isn’t a single 100% agreed on definition for some of these terms.

That is part of the challenge – if those who use data and information aren’t always clear what these words mean then it’s likely that service users won’t know what it means either.

So whether it’s communicating with service users, or with other teams, organisations or professionals you collaborate with, think carefully about using these words without any explanation.

Qualitative

Does it identify people?: Can

Description: Describes things like qualities, characteristics, thoughts or experiences. Sometimes called “stories”, “lived experience”, or “narrative”. The focus is on words or narratives about things that can be seen, felt, and thought, but not easily measured with numbers and statistics.

It can involve numbers, when analysed or used a certain way to “count up” how many people had similar experiences, or think in a similar way about something.

Use: Used for a wide variety of purposes, for example to report on service delivery, the circumstances and outcomes of service users involved with a programme, or in research and analysis.

Also, in the form of case notes, assessments, referral documents etc., qualitative information is the main kind when working directly with service users.

Quantitative

Does it identify people?: Can

Description: Information that is captured mainly as numbers. Things that can be easily counted and measured or “quantified” in a reliable way.

Quantitative data could identify specific people in circumstances where there are very few people being ‘counted’, and the situation means we can guess who they are. For example: the number of All Blacks where 3 brothers have played in the same game = … ? ...

Use: Used for a wide variety of purposes, for example to report on service delivery, the circumstances and outcomes of service users involved with a programme or in research and analysis

Personal

Does it identify people?: Yes/Could

Description: Things that identify who someone is, or could reasonably be used, even if combined with other information, to figure that out. Also known as “identifiable”.  It could include their name, but it might not. It could be other things like;

  • Date of birth, address, or phone number.
  • A unique identifier (e.g. a customer number, National Health Index Number or Work and Income Client Number). These don’t automatically “identify” someone like a name does, but can easily be used to.
  • The stories, experiences and circumstances in things like assessments, referral documents or case notes, because they may be detailed enough to figure out who those experiences are about.

Use:  Mostly used when providing services directly to someone or referring them between agencies.

Can be used in analysis, research, or evaluation situations, but normally only to link to related information.

Non-personal

Does it identify people?: No

Description: Data or information from or about someone that doesn’t and can’t identify who they are. It may have been initially collected as “anonymous” and it was never possible to identify someone with it (slightly different from “de-identified – see below):

  • Ethnicity, gender, age, number of children (if not connected to personal information).
  • General location (like saying they live in Awapuni, Palmerston North – but not the actual address).
  • Things like income level or employment status.
  • Service, support and experience information (e.g. attendance at a parenting course, being a victim of crime, achieving NCEA Level 3).

Remember that non-personal information can still feel ‘personal’ to people. Even if it doesn’t, or can’t, identify specific individuals, people may view it as ‘personal’ because it is about them, their community, and aspects of their life, experiences, and story.

Use: Used for a wide variety of purposes, for example to report on service delivery, the circumstances and outcomes of service users involved with a programme, or in research and analysis.

De-identified

Does it identify people?: No

Description: Can be thought of as a sub-set of non-personal. The difference is that while non-personal may have been collected anonymously to begin with, de-identified data was originally collected or used in an identifiable form. Then identifying parts are removed or hidden in a way that makes it very difficult to identify people.

As with “non-personal”, even without a name this information can feel very personal to the people it is about.

For example an agency collects five pieces of information from a person; name, date or birth, employment status, number of children they care for and qualifications. They provide this to a funding organisation for analysis, but “de-identify” it by removing the names, dates of birth and any other information that would make it possible to identify individual people.

Use: Main use is research and analysis.

Linked or matched

Does it identify people?: Can

Description: When data or information about one person is put together (linked) with their information from another source/agency/organisation.

For research, identifiable information is often linked and then de-identified to create a new set of information that has much more detail about the people that are in it.

Use: Research and analysis can use personal or non-personal/de-identified linked information.

Linked identifiable information can also sometimes be used to make sure someone doesn’t miss out on a service. For example checking that everyone supported by agency A is offered help from agency B.

Aggregated

Does it identify people?: Can

Description: This is when lots of people’s data or information is combined into groups or categories. Personal, non-personal, de-identified information can all be aggregated.

Use: Used in many situations outside of working one to one with a service user or whānau.

Be careful because context matters. Information that you think doesn’t identify someone might be able to in some circumstances.

For example the information; “French male, 41 years old, lives in Tawa with seven children” could easily identify someone in the right context. But “New Zealand European, female, 31 – 40, in Taranaki Region with two children” is very unlikely to identify someone.

Explaining data and information to service users…

The is no one “right” way to explain data and information collection and use to a service user. The context matters a lot. What kind of data or information is being collected, how sensitive or personal it is, how it will be used, who will use it, and any possible consequences or outcomes of using it all come into play. The circumstances or needs of the service users  matter as well when deciding what transparency should look like.

Before thinking about how to communicate with service users it’s important to be crystal clear about what data or information is being collected or used and why that’s necessary. If this isn’t clear it will be hard to explain it in simple and clear ways.

The Purpose Matters guideline and related tools will help you work through this.

Keep it simple and clear...

Here are some simple ways to describe common data or information terms.

  • Personal: “This information is kept in a way that shows who you are.”
  • Non-personal, collected anonymously: “This information is collected in a way that never shows who you are.”
  • De-identified: “This information shows who you are now, but when it is used for X reasons anything that could show who you are is removed.”
  • Linked or matched: “The information about you that we have is put together with information about you that agency X has.”
  • Aggregated: “Your information is put together with the information of everyone who comes to this programme.”

A note about sensitive information

There is no formal definition of sensitive information, though in the social sector it generally means data or information that:

  • is very intimate or emotional
  • could cause harm if used in a biased or prejudiced way
  • is something people would feel strongly about being used without their knowledge and might feel that their trust was breached by it being used or made public.

Even if their names are not included, people can still feel strongly about how information they see as sensitive is used, why it’s used and who gets to see it.

A note about the Privacy Act

The Privacy Act doesn’t require someone to be informed about the use of their personal information or data if it will be used:

  • in a way that won’t identify them,
  • for statistical and research purposes where it won’t be published in a way that would identify them,
  • when it’s unsafe or inappropriate; e.g. it would get in the way of upholding the law.

However, in the social sector the Data Protection and Use Policy encourages transparency about the collection or use of any data or information about service users, even if it doesn’t identify them.

This is because even though someone might not be identifiable, they may still feel the information or data is very personal or it may be sensitive. The possible consequences of misusing, or misinterpreting their information can be significant. Transparency is respectful, it upholds mana, and it helps build trust.

A note about “Research and Statistical Purposes”

Even though “research and statistical purposes” is a term used in the Privacy Act, for a lot of people it’s jargon that doesn’t mean much. It wouldn’t help them understand what happens with their information or data.

It doesn’t clearly explain what the purpose is of using their information or data. It says what is going to happen, “research” or “statistics”, but not what that is about, or for, why it’s happening, what the outcome is meant to be, or how it might help the service user, their whānau, or people in similar situations.

“Research and statistical purposes” can also mean quite different things to the people who are doing the “research” and “statistics”, for example:

  • Analysis and planning to keep the social sector running (funding and contracting, setting budgets or workforce development).
  • Understanding what's happening for New Zealanders, their experiences, challenges, skills, strengths, resources and resilience and what their aspirations or goals are at a group or community level (analytics and research).
  • Understanding how well the social sector is serving New Zealanders and where things might need to change (through evaluations, policy development, programme or service design).

So just saying “research or statistical purposes” isn’t a transparent way to explain why service users’ information or data needs to be collected, or what will happen with it. They should know:

  • Who is doing the research or statistics, or the agency/organisation.
  • What the research or statistics actually is. For example;  what is it exploring or investigating, what is it looking at, what decisions might it be used for, what the potential outcomes and effects are.

Some examples of how to explain data and information use to service users…

Below are some examples of less transparent, and more transparent explanations of data or information use. The aim is a ‘no surprises’ approach – people shouldn’t be surprised about what is recorded about them, what identifies them, how it’s used or which agencies have it. 

Keep in mind there might be some other things to say under another law or policy in a specific context. Such as explaining a service user’s rights under the Health and Disability Code, the Education Act or about information sharing under the Oranga Tamariki Act.

Not so transparent: Your information will be shared with relevant agencies.

More transparent: We will share your personal information (things that show who you are) with:

  • Agency X so they can help you access XXXX services
  • Organisation Y so that XXXXX.
  • With Ministry X so they can later check if you need to be offered Y service.

Not so transparent: Information will be used for research and statistical purposes.

More transparent

  1. We will use information, in a way that doesn’t identify you, in research. This kind of research looks at XXXX.
  2. We provide XXXX information to Ministry XXX. They use it in many ways:
    • To work out how much funding services like this need.
    • To understand how many X professionals need to be trained.
    • To report to government on how XXX programme is working across the country and if it is making a positive difference.
  3. It can be helpful to see the bigger picture of the lives of groups who use this service so we can understand what supports they should get before they need to come here. For this kind of research Agency XXX will put together information we give them about you with other information about you from x,y,z places/agencies. This is done in a very secure way that protects your privacy. Anything that identifies you is removed before it’s used.

Not so transparent: People in our agency will see your information.

More transparent

  1. Only professionals (title or names if possible) who directly work with you, or closely with those who do (the supervisor or XXX, XXX), will see your assessment and notes.
  2. At times people like the administrator/XXX/XXX will access your contact details only.

Not so transparent: Information is used for funding purposes.

More transparent: Information that can’t identify you is given to agency X who funds this programme so they know how the service is going. This includes:

  • The number of people who used the service.
  • How many completed their goals.
  • Characteristic information like; ages, employment status, ethnicity, gender.

Not so transparent: Information is used to link services.

More transparent: Information that identifies you (personal information) is given to Ministry X so they can help Agency Y know if you need XYZ service from them. This includes:

  • your customer number
  • date of birth and name
  • ethnicity and gender.

No information that identifies you will be used for X, Y, Z.

No information about you, even if it doesn’t identify you, will be used for anything except providing you with direct help from our agency.

Keep in mind...

What you tell people about the collection or use of their information is one thing. How you explain it or communicate it is another. Being mindful of the needs and circumstances of service users is key to communicating in a way that makes sense to them.

One of the best things to do is work with others to design explanations for service users.

Ask service users themselves to help work out what to say and how to say it.

If this isn’t possible try to get ideas from service user advocates, community representatives, people who work directly with service users and know their communication needs.

Think about the service users circumstances

  • Do explanations need translation or adapting into different formats, visuals?
  • How should explanations be made accessible to people with disabilities?
  • If children or young people are service users themselves how can this be explained to them?
  • Are service users in crisis? What affect does this have on their ability to think about data and information right now? What has to happen later to make sure things are still transparent?
  • If this was your teenager, your parent or your friend – what would work for them? What needs might they have when it comes to communication?

Use multiple ways to communicate

People read, hear, and understand differently, so consider multiple ways to communicate. For example:

  • Webpages - but remember some service users won’t want to engage online, won’t know that reading the privacy/data section is important, or may not be able to find it even if they are interested.
  • Explanations on forms.
  • Posters in offices, or spaces where service users are.
  • Brochures, fact sheets, or other information for service users.
  • Presentations and discussions.
  • Find natural places to talk about it as part of interacting with service users (like when introducing someone to a service, or when preparing a referral).

Check in

Check in with people that they have a good enough understanding.

Thinking about data and information use isn’t always something people are in a space to do when they first ask for help. But that doesn’t mean they won’t care later on.