With new technologies for storage, control and analysis, routinely collected health information has become a valuable tool for researching and developing health services. Utilisation of routinely collected data presents many different challenges, such as the quality of the information, proper management of privacy, ethical use of the information in contexts such as research and development, culturally appropriate use of health data and, in the context of New Zealand, the sovereignty of Māori health data.[[1–4]]
The use of routinely collected data has facilitated the monitoring of specific health conditions for epidemiological monitoring and improvement of health systems.[[5]] In New Zealand, analysis of routinely collected national data has been used to develop a clinical risk tool for cardiovascular disease[[6]] and a virtual diabetes register.[[7]] In the field of dementia, routinely collected health data have been used to estimate the prevalence of dementia using national datasets; the findings suggested that the prevalence of dementia in Māori and Pacific Island communities is higher than in other ethnic groups.[[8]] However, community-based dementia prevalence data in New Zealand to test the accuracy of these routinely collected health datasets are scarce.[[9]] At a more local level, studies using routine health data allow statistical adjustment for potential confounding factors such as comorbidity. These studies suggest there are differences in outcomes for Māori and Pacific Islanders living with dementia (for example, utilisation of dementia services and mortality).[[10–13]]
Although routinely collected de-identified data can provide valuable knowledge about the epidemiological characteristics of common chronic diseases in New Zealand, these data have tended to be used without individual consent. To date, there has been little research into peoples’ opinions about the use and treatment of their health information. In Canada, McCormick et al. (2019) conducted an online survey to compare the opinions of people about the use of routinely collected data for health research and reported that close to 80% of the surveyed people felt positive about the use of that information for research.[[14]] Similarly, Colombo et al. (2019) conducted a survey to understand the opinions and attitudes of people about using their data in clinical studies in Italy. Thirty-nine percent of the participants approved access to health data to researchers and professionals, and identified important topics, such as data de-identification, secure archives and access agreements, as essential aspects of the sharing models.[[15]]
In New Zealand, an online survey (Dobson et al., 2021) conducted at Waitematā District Health Board (DHB) investigated patient perspectives, preferences and comfort levels regarding the use of their health data.[[16]] In the population of inpatients and outpatients they found that more than 80% of participants (aged 16 to 95 years) were comfortable with how de-identified health information was used across various scenarios. However, many stated that they would require the information collected to be accurate and stored securely within the health system, that privacy was maintained, and the data were only used for the public good. They also expressed a preference for improved communication and transparency around how their data were used.
Our research group is interested in exploring whether routinely collected data can be used to predict future decline in brain health and/or dementia and what might be done to promote resilience of brain health. The Lancet Commission for Dementia[[17,18]] described 12 modifiable risk factors for dementia—in early life (education), in middle age (hearing loss, TBI, hypertension, alcohol and obesity) and in later life (smoking, depression, social isolation, physical inactivity, air pollution, diabetes). Some of these risk factors could be identified using routine health data and would allow the identification of groups of people at higher risk at a population level, which might inform population-level interventions targeted at reducing risk of disease. The prevalence of dementia is rising rapidly due to global demographic ageing and is expected to triple between 2015 and 2050.[[19]] To date, there is no cure for dementia, so researchers worldwide are attempting to find clinical biomarkers that might provide early identification of people at high risk and hopefully intervene before the onset of irreversible dementia. This is a rapidly developing field, particularly with the growing development of artificial intelligence and machine learning methods for diagnosing and detecting risk factors for various diseases, including dementia, which could be utilised with routinely collected health data.[[20–21]]
The early identification of decline in brain health is a controversial area, as dementia is still a highly stigmatised disease,[[22]] and people may not feel comfortable about their health data being used for this purpose, particularly if they fear being identified as being at risk. For that reason, our research group felt that we could not assume that the findings of Dobson et al.[[16]] (2021) would apply in the specific area of cognitive decline and dementia; thus, we decided to repeat the survey with a focus on brain health.
Our research aimed to explore the attitudes and preferences of people aged 55+ regarding the acceptable use of their de-identified health data and understanding their concerns and comfort in different scenarios related to identification of factors related to cognitive decline and dementia. This would allow New Zealand health institutions and researchers to gain a clearer picture of patients’ attitudes and preferences around the use of their de-identified health data in brain health research.
People aged 55 and over currently engaged with health services in Te Whatu Ora Counties Manukau were invited to participate in the survey. We chose the cut-off at age 55 because, compared to NZ Europeans, the average age of the onset (or recognition) of dementia is younger for Māori or Pacific peoples living in New Zealand.[[10]] We included people living with dementia who were known to the Te Whatu Ora Counties Manukau Memory Team and their caregivers. This was done to ensure we had a good representation of people who had lived experience of dementia (either personal or as a caregiver).
The survey sought to gain an understanding of the opinions of older people about the management of their health information, with the following inclusion criteria:
• Currently resident in New Zealand
• Aged 55 years or older
• Currently using health services in Te Whatu Ora Counties Manukau
These criteria were waived for caregivers of a person living with dementia to ensure their inclusion and representation.
Our survey was based on the survey constructed by Dobson et al. (2021).[[16]] A study advisory group with broad representation—including Māori health expertise—drafted questions for Dobson’s survey. The research group, advised by Dobson, adapted the original questionnaire for our target population, referencing brain health. We also asked people if they were willing to be individually interviewed (Q13 in the survey) so that we could go into more depth regarding specific issues for Māori and Pacific Islanders.
The survey included a total of 13 questions, assessing:
• Perceptions about the current use of health information by the health service (Te Whatu Ora Counties Manukau) across six different scenarios (mandatory question).
• Perceived comfort with the use of health information on a Likert scale from 1 (very uncomfortable) to 5 (very comfortable) across the same six scenarios, plus one extra (mandatory question).
• Free-text comments about their level of comfort with the use of health information.
• Free-text comments about situations where permission should be sought before their health information was combined with other peoples’ to better understand the health of the local population.
• Final comments on the use of health information by Te Whatu Ora Counties Manukau.
• Socio-demographic variables, including year of birth and ethnicity.
All participants received the exact same survey without any randomised items, and adaptive questioning was employed when necessary to minimise the burden on respondents and simplify the complexity of the questions. Also, they could review their answers using the “back button” available in the online questionnaire. The complete survey is available in Appendix 1.
A preliminary survey pilot was conducted to evaluate response times, the relevance of the questions, and the design of the data capture and collection instrument. The final survey was administered in Qualtrics and distributed via an anonymised email link.
In the introduction to the survey, we offered the option of conducting the survey by telephone for those who wished to do so, either in English or in another language: Te Reo Māori, Samoan, Tongan, Mandarin, Cantonese, Hindi or Fijian Hindi.
This research was approved for three years by Auckland Health Research Ethics Committee AH22266 on 18 October 2021.
A link to the online survey was sent by email to outpatients aged 55+ whose email addresses were verified in the Te Whatu Ora Counties Manukau Patient Information Management System (PIMS). The emails were sent to attendees of the Health of Older People outpatient services between 3 January 2019–31 December 2021, including people referred to the memory team, irrespective of the diagnosis made. We invited both patients and their whānau members to be involved in the survey (see survey: Appendix 1). We also specifically invited caregivers of people living with dementia who were current service users of Te Whatu Ora Counties Manukau Memory Team to ensure that their views were included.
Patients (or caregivers of people living with dementia) who wanted to participate but did not wish to complete an online survey were offered the option of an adapted telephone interview. The research assistant conducting the telephone interviews entered the participants’ responses into the online survey in real-time, so that responses remained anonymised, and the information was stored in one database. Participation in the study was entirely voluntary, and no rewards or incentives were offered for taking part. Prior to being granted access to complete the survey, participants were requested to provide their consent.
The analysis of the survey data was descriptive, using frequency tables and graphs. Due to the potential risk of identifying participants based on the ethnicity question, certain categories were combined using the ethnicity prioritisation method as outlined by Statistics NZ and further elucidated by Yao et al. (2022).[[23]] This approach was implemented to ensure the protection of participant privacy and confidentiality. The free-text responses were coded using a simple inductive approach identifying common categories and meanings from the data. The analyses were performed in the statistical software R, version 4.2.1.[[24]]
The survey is reported based on the CHERRIES checklist (Appendix 2).
A total of 326 responses (out of 1,314 emails sent; response rate = 24.8%) were received between 7 June 2022 and 5 October 2022, including 15 from the telephone survey (of which four were completed in Fiji Hindi). Of the responses received, 226/326 (69.3%) were rated as “valid,” as they included complete responses to the two mandatory survey questions. No duplicates were identified.
The socio-demographic characteristics of the sample are presented in Table 1. Respondents were mostly NZ European (64.9%), Māori (11.9%) and Asian (10.9%), and their average age was 74.2 (10.6) years. Forty-two percent of the sample knew of a family/whānau member or friend who had been diagnosed with mild cognitive impairment (MCI) or dementia. With respect to caregivers, it is important to note that the responses provided in the data are anonymised, thus precluding the identification of specific individuals in caregiving roles. At least 15 people were caregivers of people living with dementia who were contacted through the Te Whatu Ora Counties Manukau Memory Team. However, 42% of respondents (n=85) reported having a family member or friend living with dementia, so it is reasonable to assume that at least some of these were also caregivers.
View Tables 1–3, Figures 1–2, Box 1.
Most participants (179/226, 79.2%) believed that Te Whatu Ora Counties Manukau used their health information in the ways described in all of the six different scenarios (see Figure 1 and Table 2), but up to 15% were unaware that health information from the whole population was combined to look at trends and improve services (scenarios E and F). When we separate this information by whether respondents know a family member/friend living with dementia, the trend does not change. The perception of participants regarding the utilisation of their health data across all proposed scenarios remains independent of having a family member or friend who is living with dementia (See Appendix 3, Table 1).
Figure 2 and Table 3 show that between 79.2 and 86.8% of participants were either comfortable or very comfortable in each of the scenarios proposed (A: 80.2% [n=182], B: 81.9% [n=186], C: 86.8% [n=197], D: 86.3% [n=196], E: 80.1% [n=181], F: 83.2% [n=188] and G: 79.2% [n=179]) and 63.3% [n=143]) felt “comfortable” or “very comfortable” across all seven scenarios. In contrast, less than 10% of the respondents felt uncomfortable or very uncomfortable in each of the scenarios presented (A: 7.1% [n=16], B: 8.0% [n=18], C: 5.3% [n=12], D: 5.8% [n=13], E: 8.0% [n=18], F: 7.0% [n=14] and G: 8.4% [n=19]). Four percent (n=9) felt “uncomfortable” or “very uncomfortable” across all of the scenarios. None of the scenarios drew a markedly different response compared to others. Despite the generally high levels of comfort observed (indicated by scores 4 and 5), individuals who have personal knowledge of someone living with dementia exhibit a slight decrease in the frequency of assigning a score of 5 compared to those without such personal connections (see Appendix 3, Table 2).
A total of 54/226 (23.9%) participants commented on their comfort with the use of their health information in the different scenarios. Of those who commented, 57.4% (31/54) felt comfortable with the use of the data in any scenario, although some stated specific conditions for use. Nine respondents (16.7%) were not comfortable, and 14 did not have any relevant comments.
Most expressed the opinion that they were comfortable, provided that health information should be used to improve health services for the local population.
“The wonderful care I have received has been informed, and developed, over time, so am happy that anything learnt about me can be used to help others into the future. Win win!” (Female, 65–74 years, “other” ethnicity)
“As long as it improves the time it takes to get healthcare” (Female, 75–84, NZ European)
Participants were also asked if they had any concerns about how Te Whatu Ora Counties Manukau uses their data, and 141/226 (61.9%) free-text responses were obtained. These overlapped with the level of comfort comments and were analysed together. Most people (102/141, 72.3%) stated that they had no concerns, but 27.7% mentioned scenarios in which they would have concerns. These themes are presented in Box 1.
Sixty-four percent of respondents (144/226) commented on situations where permission would be required before combining health data with other data to better understand the entire population’s health. Of the 144, 45.8% (n=66) said that obtaining permission to combine health data was not required in any situation, and 18.8% (n=27) specified it would not be necessary to obtain permission if data were de-identified, stored securely, not shared publicly and handled only by health professionals/researchers. Nineteen respondents (13.2%) said that permission should always be obtained to combine the data for any situation, and two respondents (1.4%) commented that, although a priori consent was not required, they would like to be informed if their data were used. Nineteen respondents (13.2%) responded that they did not know, or their responses did not correspond to the question asked.
Eleven of the 144 respondents (7.6%) specified other situations where permission should be obtained, for example, if the health information:
• is to be used by people other than health professionals/researchers (n=2)
• contains sensitive health issues or identifiable information (n=5)
• is combined with data from an organisation not related to health (n=1)
• is discussed outside the specific health service that collected it (n=1)
• is used for commercial purposes (n=2)
This study found that 79% of the people surveyed knew that Te Whatu Ora Counties Manukau currently used their routinely collected health information in the ways described in the scenarios, and 63% were comfortable or very comfortable with their data being used as described. Approximately 10% were not comfortable with their data being used in the ways described. Participants expressed concerns about the accuracy of data, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies.
Although the majority of respondents commented that it was not necessary to obtain specific permission for data linkage, there were a range of conditions mentioned that underpinned peoples’ comfort with their health information being combined with the health information of others for secondary purposes: data must be anonymous, not shared outside the health service with the public or sold to private companies such as insurers or pharmaceutical companies, and that patients should be informed beforehand about how data will be used.
Our results align with those presented by Dobson et al.,[[16]] which suggests that older people living in New Zealand have opinions about managing their health data that are similar to that of the wider population. Regarding the current use of health data across the scenarios presented in both Dobson’s study and ours, more than 80% of the participants were comfortable or very comfortable with how their data were being used, and less than 10% were uncomfortable or very uncomfortable. Given that the studies had different populations—Dobson’s study encompassed a wide age range spanning from 16 to 95 years—while the present study specifically focussed on the opinions and preferences of older individuals with a mean age of 74 years. Additionally, Dobson’s study was conducted in Te Whatu Ora Waitematā, whereas the current study took place in Te Whatu Ora Counties Manukau—the finding supports that most people agree with their de-identified data being used for the greater good, as long as key conditions are met around the protection, storage and care of the data. Our findings also coincide with those of Rezaei et al. (2021), who surveyed a sample of healthcare professionals regarding ethical challenges in using health data.[[25]] The main issues were privacy, autonomy and security. Papoutsi et al. (2015) surveyed patients from primary and secondary care settings in West London (United Kingdom)[[26]] and found similar concerns about data inaccuracies, prejudice “about sexual or mental health and being labelled as ‘hypochondriac’ or as having social problems,” and potential security and privacy threats; however, the majority of participants were in favour of using data for personal healthcare provision (89.7%), for health services policy and planning (79.5%), or for research (81.4%). The authors concluded that public participation and transparency are the pillars to establish the limits of the information to be shared and how researchers and medical personnel should access the data.[[26]]
A limitation of our study is the generalisability of the results. According to the 2018 population census,[[27]] the distribution of ethnicity in the Counties Manukau population aged 65+ was 7% Māori, 12% Pacific Islanders, 20% Asian and 60% NZ European. The ethnic breakdown of our sample was partially representative of the local population (12% Māori, 6% Pacific Islanders, 11% Asian and 65% NZ European), but the small sample size did not allow us to fully explore inter-ethnic differences in responses. In addition, about 25% of patients in the Te Whatu Ora Counties Manukau Memory Team have verified email addresses, contributing to the under-representation of different ethnicities in the responses. To address this issue, alternative sampling techniques should be implemented to ensure a more comprehensive representation of all ethnicities.
For Māori people, data should be considered as taonga, which relates to the idea that data are owned collectively by one or more whānau and are covered by rights, with obligations for active protection of that power by the Crown.[[28]] Further work is required to delve deeper into the use of healthcare information and the implications for Māori Data Sovereignty, the inherent rights and interests that Māori have in relation to the collection, ownership and application of Māori data.[[29]] It was notable that several Māori respondents did not agree to their data being used after their death, because one tikanga perspective is that the deceased are tapu and items belonging to the deceased are to be destroyed.[[30]] More work needs to be done to address Māori data concerns, particularly post-mortem data, which are important predictors of mortality and need to be analysed in research. Such concerns might indicate that IT-system design needs to be considered to reflect a culturally responsive system that aligns with the use of routinely collected health data relevant to examination of mate wareware (dementia) from a Māori perspective.[[31]] Current health IT systems are not designed to give patient control over the use of their data (for example, to opt out of research that is deemed not culturally appropriate). Adequately addressing cultural considerations with respect to data use may place demands on IT systems for greater patient control over their data and effective consent mechanisms for the use of their data.
The results of our study suggest that health services need to reflect on how best to use and protect peoples’ health data—a rich resource—while also respecting peoples’ rights to say how their data are used. Our findings are a first step towards describing older peoples’ opinions about how to use their health data for health research around brain health. The next phase of the study will focus on conducting more in-depth individual interviews to gain a deeper understanding of peoples’ opinions in different scenarios regarding the use of their health data. This could be particularly relevant for Māori, Pacific Island and Asian communities, who may possess distinct perspectives that differ from the majority of the survey sample, which predominantly was NZ European (65%).
Our findings indicate that these respondents are supportive of their health information being used for secondary purposes to benefit others, but there are conditions/limitations to this comfort that researchers need to consider, ensuring they use health information in a patient-informed way. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly with respect to Māori cultural considerations.
View Appendices 1–3.
Routinely collected health data can provide rich information for research and epidemiological monitoring of different diseases, but using the data presents many challenges. This study aims to explore the attitudes and preferences of people aged 55 and over regarding the use of their de-identified health data, and their concerns and comfort in different scenarios.
An anonymous online survey was conducted with people aged 55 and over currently engaged with health services in a New Zealand health district during June–October 2022. The survey could be completed online or by telephone and was available in eight languages.
Seventy-nine percent of respondents knew that their health information was currently being used in the ways described in the scenarios, and between 80–87% felt comfortable or very comfortable with their data being used as described in the scenarios. In contrast, 4% (n=9) felt “uncomfortable” or “very uncomfortable” across all of the scenarios. Participants expressed concerns about data accuracy, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies. Some participants identified situations where permission should be required to link data, including being used by people other than health professionals, containing sensitive health issues, or being used for commercial purposes.
This study finds general support from patients for the use of their routinely collected data for secondary purposes as long as its use will benefit the population from which the data are taken. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly concerning Māori cultural considerations.
1) Kalkman S, van Delden J, Banerjee A, et al. Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. J Med Ethics. 2022 Jan;48(1):3-13. doi: 10.1136/medethics-2019-105651.
2) Mursaleen LR, Stamford JA, Jones DA, et al. Attitudes towards data collection, ownership and sharing among patients with Parkinson’s disease. J Parkinsons Dis. 2017;7(3):523-531. doi: 10.3233/JPD-161045.
3) NICE Citizens Council. What ethical and practical issues need to be considered in the use of anonymised information derived from personal care records as part of the evaluation of treatments and delivery of care? [Internet]. London: National Institute for Health and Care Excellence (NICE); 2015 Nov 11. Citizens Council Reports No. 18.
4) Health Research Council of New Zealand. Guidelines for Researchers on Health Research involving Māori [Internet]. Auckland: Health Research Council of New Zealand; 2010 [cited 27 Mar 2023]. Available from: https://www.hrc.govt.nz/resources/guidelines-researchers-health-research-involving-maori.
5) Jorm L. Routinely collected data as a strategic resource for research: priorities for methods and workforce. Public Health Res Pract. 2015 Sep 30;25(4):e2541540. doi: 10.17061/phrp2541540.
6) Pylypchuk R, Wells S, Kerr A, et al. Cardiovascular disease risk prediction equations in 400 000 primary care patients in New Zealand: a derivation and validation study. Lancet. 2018 May 12;391(10133):1897-1907. doi: 10.1016/S0140-6736(18)30664-0.
7) Te Whatu Ora – Health New Zealand. Virtual Diabetes Register: Technical Guide [Internet]. Wellington: Te Whatu Ora – Health New Zealand; 2022 [cited 16 Mar 2023]. Available from: https://www.tewhatuora.govt.nz/publications/virtual-diabetes-register-technical-guide/.
8) Cheung G, To E, Rivera-Rodriguez C, et al. Dementia prevalence estimation among the main ethnic groups in New Zealand: a population-based descriptive study of routinely collected health data. BMJ Open. 2022 Sep 7;12(9):e062304. doi: 10.1136/bmjopen-2022-062304.
9) Ma’u E, Cullum S, Yates S, et al. Dementia Economic Impact Report 2020 [Internet]. Auckland: The University of Auckland,; 2021 [cited 12 Dec 2022]. Available from: https://cdn.alzheimers.org.nz/wp-content/uploads/2021/09/Dementia-Economic-Impact-Report-2020.pdf.
10) Cullum S, Mullin K, Zeng I, et al. Do community-dwelling Māori and Pacific peoples present with dementia at a younger age and at a later stage compared with NZ Europeans? Int J Geriatr Psychiatry. 2018 Aug;33(8):1098-1104. doi: 10.1002/gps.4898.
11) Cullum S, Varghese C, Yates S, et al. Predictors of Aged Residential Care Placement in Patients Newly Diagnosed with Dementia at a New Zealand Memory Service. J Long Term Care. 2021;0(2021):24-32. doi: 10.31389/jltc.46.
12) Cullum S, Varghese C, Coomarasamy C, et al. Predictors of mortality in Māori, Pacific Island, and European patients diagnosed with dementia at a New Zealand Memory Service. Int J Geriatr Psychiatry. 2020 May;35(5):516-524. doi: 10.1002/gps.5266.
13) Ma’u E, Saeed F, Yates S, et al. Do Māori and Pacific Peoples Living with Dementia in New Zealand Receive Equitable Long-Term Care Compared with New Zealand Europeans? J Long Term Care. 2022;0(2022):222-233. doi: 10.31389/jltc.148.
14) McCormick N, Hamilton C, Koehn CL, et al. Canadians’ views on the use of routinely collected data in health research: a patient-oriented cross-sectional survey. CMAJ Open. 2019 Apr 4;7(2):E203-E209. doi: 10.9778/cmajo.20180105.
15) Colombo C, Roberto A, Krleza-Jeric K, et al. Sharing individual participant data from clinical studies: a cross-sectional online survey among Italian patient and citizen groups. BMJ Open. 2019 Feb 19;9(2):e024863. doi: 10.1136/bmjopen-2018-024863.
16) Dobson R, Whittaker R, Wihongi H, et al. Patient perspectives on the use of health information. N Z Med J. 2021 Dec 17;134(1547):48-62.
17) Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet. 2017 Dec 16;390(10113):2673-2734. doi: 10.1016/S0140-6736(17)31363-6.
18) Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020 Aug 8;396(10248):413-446. doi: 10.1016/S0140-6736(20)30367-6.
19) Prince MJ, Wimo A, Guerchet MM, et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends [Internet]. London: Alzheimer’s Disease International (ADI); 2015 Aug [cited 16 Mar 2023]. Available from: https://www.alzint.org/u/WorldAlzheimerReport2015.pdf.
20) Jammeh EA, Carroll CB, Pearson SW, et al. Machine-learning based identification of undiagnosed dementia in primary care: a feasibility study. BJGP Open. 2018 Jun 13;2(2):bjgpopen18X101589. doi: 10.3399/bjgpopen18X101589.
21) Kumar S, Oh I, Schindler S, et al. Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review. JAMIA Open. 2021 Aug 2;4(3):ooab052. doi: 10.1093/jamiaopen/ooab052.
22) Lynch C. World Alzheimer Report 2019: Attitudes to dementia [Internet]. London: Alzheimer’s Disease International (ADI); 2020 [cited 17 Mar 2023]. Available from: https://www.alzint.org/u/WorldAlzheimerReport2019.pdf.
23) Yao ES, Meissel K, Bullen P, et al. Demographic discrepancies between administrative-prioritisation and self-prioritisation of multiple ethnic identifications. Soc Sci Res. 2022 Mar;103:102648. doi: 10.1016/j.ssresearch.2021.102648.
24) R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna: R Foundation for Statistical Computing; 2022 [cited 16 Jan 2023]. Available from: https://www.R-project.org/
25) Rezaei M, Jafari-Sadeghi V, Cao D, Mahdiraji HA. Key indicators of ethical challenges in digital healthcare: A combined Delphi exploration and confirmative factor analysis approach with evidence from Khorasan province in Iran. Technol Forecast Soc Change. 2021;167:120724. doi: 10.1016/j.techfore.2021.120724.
26) Papoutsi C, Reed JE, Marston C, et al. Patient and public views about the security and privacy of Electronic Health Records (EHRs) in the UK: results from a mixed methods study. BMC Med Inform Decis Mak. 2015 Oct 14;15:86:1-15. doi: 10.1186/s12911-015-0202-2.
27) Lees J, Lee M, Winnard D. Demographic Profile: 2018 Census, Population of Counties Manukau [Internet]. Auckland: Counties Manukau Health; 2021 [cited 30 May 2023]. Available from: https://www.countiesmanukau.health.nz/assets/About-CMH/Performance-and-planning/health-status/Demographic-profile-2018-Census-Population-of-Counties-Manukau.pdf.
28) Wilson D. Māori Data Sovereignty and the WAI 2522 Report: A summary of some Māori Data Sovereignty insights from the WAI 2522 Report on the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP). Auckland: The University of Auckland; 2022 [cited 14 Feb 2023].
29) Te Mana Raraunga. What is Māori Data Sovereignty? [Internet]. New Zealand: Te Mana Raraunga; 2023 [cited 27 Mar 2023]. Available from: https://www.temanararaunga.maori.nz/
30) Mead HM. Tikanga Māori: Living by Māori values. Wellington: Huia Publishers; 2016.
31) Dudley M, Menzies O, Elder H, et al. Mate wareware: Understanding ‘dementia’ from a Māori perspective. N Z Med J . 2019 Oct 4;132(1503):66-74.
With new technologies for storage, control and analysis, routinely collected health information has become a valuable tool for researching and developing health services. Utilisation of routinely collected data presents many different challenges, such as the quality of the information, proper management of privacy, ethical use of the information in contexts such as research and development, culturally appropriate use of health data and, in the context of New Zealand, the sovereignty of Māori health data.[[1–4]]
The use of routinely collected data has facilitated the monitoring of specific health conditions for epidemiological monitoring and improvement of health systems.[[5]] In New Zealand, analysis of routinely collected national data has been used to develop a clinical risk tool for cardiovascular disease[[6]] and a virtual diabetes register.[[7]] In the field of dementia, routinely collected health data have been used to estimate the prevalence of dementia using national datasets; the findings suggested that the prevalence of dementia in Māori and Pacific Island communities is higher than in other ethnic groups.[[8]] However, community-based dementia prevalence data in New Zealand to test the accuracy of these routinely collected health datasets are scarce.[[9]] At a more local level, studies using routine health data allow statistical adjustment for potential confounding factors such as comorbidity. These studies suggest there are differences in outcomes for Māori and Pacific Islanders living with dementia (for example, utilisation of dementia services and mortality).[[10–13]]
Although routinely collected de-identified data can provide valuable knowledge about the epidemiological characteristics of common chronic diseases in New Zealand, these data have tended to be used without individual consent. To date, there has been little research into peoples’ opinions about the use and treatment of their health information. In Canada, McCormick et al. (2019) conducted an online survey to compare the opinions of people about the use of routinely collected data for health research and reported that close to 80% of the surveyed people felt positive about the use of that information for research.[[14]] Similarly, Colombo et al. (2019) conducted a survey to understand the opinions and attitudes of people about using their data in clinical studies in Italy. Thirty-nine percent of the participants approved access to health data to researchers and professionals, and identified important topics, such as data de-identification, secure archives and access agreements, as essential aspects of the sharing models.[[15]]
In New Zealand, an online survey (Dobson et al., 2021) conducted at Waitematā District Health Board (DHB) investigated patient perspectives, preferences and comfort levels regarding the use of their health data.[[16]] In the population of inpatients and outpatients they found that more than 80% of participants (aged 16 to 95 years) were comfortable with how de-identified health information was used across various scenarios. However, many stated that they would require the information collected to be accurate and stored securely within the health system, that privacy was maintained, and the data were only used for the public good. They also expressed a preference for improved communication and transparency around how their data were used.
Our research group is interested in exploring whether routinely collected data can be used to predict future decline in brain health and/or dementia and what might be done to promote resilience of brain health. The Lancet Commission for Dementia[[17,18]] described 12 modifiable risk factors for dementia—in early life (education), in middle age (hearing loss, TBI, hypertension, alcohol and obesity) and in later life (smoking, depression, social isolation, physical inactivity, air pollution, diabetes). Some of these risk factors could be identified using routine health data and would allow the identification of groups of people at higher risk at a population level, which might inform population-level interventions targeted at reducing risk of disease. The prevalence of dementia is rising rapidly due to global demographic ageing and is expected to triple between 2015 and 2050.[[19]] To date, there is no cure for dementia, so researchers worldwide are attempting to find clinical biomarkers that might provide early identification of people at high risk and hopefully intervene before the onset of irreversible dementia. This is a rapidly developing field, particularly with the growing development of artificial intelligence and machine learning methods for diagnosing and detecting risk factors for various diseases, including dementia, which could be utilised with routinely collected health data.[[20–21]]
The early identification of decline in brain health is a controversial area, as dementia is still a highly stigmatised disease,[[22]] and people may not feel comfortable about their health data being used for this purpose, particularly if they fear being identified as being at risk. For that reason, our research group felt that we could not assume that the findings of Dobson et al.[[16]] (2021) would apply in the specific area of cognitive decline and dementia; thus, we decided to repeat the survey with a focus on brain health.
Our research aimed to explore the attitudes and preferences of people aged 55+ regarding the acceptable use of their de-identified health data and understanding their concerns and comfort in different scenarios related to identification of factors related to cognitive decline and dementia. This would allow New Zealand health institutions and researchers to gain a clearer picture of patients’ attitudes and preferences around the use of their de-identified health data in brain health research.
People aged 55 and over currently engaged with health services in Te Whatu Ora Counties Manukau were invited to participate in the survey. We chose the cut-off at age 55 because, compared to NZ Europeans, the average age of the onset (or recognition) of dementia is younger for Māori or Pacific peoples living in New Zealand.[[10]] We included people living with dementia who were known to the Te Whatu Ora Counties Manukau Memory Team and their caregivers. This was done to ensure we had a good representation of people who had lived experience of dementia (either personal or as a caregiver).
The survey sought to gain an understanding of the opinions of older people about the management of their health information, with the following inclusion criteria:
• Currently resident in New Zealand
• Aged 55 years or older
• Currently using health services in Te Whatu Ora Counties Manukau
These criteria were waived for caregivers of a person living with dementia to ensure their inclusion and representation.
Our survey was based on the survey constructed by Dobson et al. (2021).[[16]] A study advisory group with broad representation—including Māori health expertise—drafted questions for Dobson’s survey. The research group, advised by Dobson, adapted the original questionnaire for our target population, referencing brain health. We also asked people if they were willing to be individually interviewed (Q13 in the survey) so that we could go into more depth regarding specific issues for Māori and Pacific Islanders.
The survey included a total of 13 questions, assessing:
• Perceptions about the current use of health information by the health service (Te Whatu Ora Counties Manukau) across six different scenarios (mandatory question).
• Perceived comfort with the use of health information on a Likert scale from 1 (very uncomfortable) to 5 (very comfortable) across the same six scenarios, plus one extra (mandatory question).
• Free-text comments about their level of comfort with the use of health information.
• Free-text comments about situations where permission should be sought before their health information was combined with other peoples’ to better understand the health of the local population.
• Final comments on the use of health information by Te Whatu Ora Counties Manukau.
• Socio-demographic variables, including year of birth and ethnicity.
All participants received the exact same survey without any randomised items, and adaptive questioning was employed when necessary to minimise the burden on respondents and simplify the complexity of the questions. Also, they could review their answers using the “back button” available in the online questionnaire. The complete survey is available in Appendix 1.
A preliminary survey pilot was conducted to evaluate response times, the relevance of the questions, and the design of the data capture and collection instrument. The final survey was administered in Qualtrics and distributed via an anonymised email link.
In the introduction to the survey, we offered the option of conducting the survey by telephone for those who wished to do so, either in English or in another language: Te Reo Māori, Samoan, Tongan, Mandarin, Cantonese, Hindi or Fijian Hindi.
This research was approved for three years by Auckland Health Research Ethics Committee AH22266 on 18 October 2021.
A link to the online survey was sent by email to outpatients aged 55+ whose email addresses were verified in the Te Whatu Ora Counties Manukau Patient Information Management System (PIMS). The emails were sent to attendees of the Health of Older People outpatient services between 3 January 2019–31 December 2021, including people referred to the memory team, irrespective of the diagnosis made. We invited both patients and their whānau members to be involved in the survey (see survey: Appendix 1). We also specifically invited caregivers of people living with dementia who were current service users of Te Whatu Ora Counties Manukau Memory Team to ensure that their views were included.
Patients (or caregivers of people living with dementia) who wanted to participate but did not wish to complete an online survey were offered the option of an adapted telephone interview. The research assistant conducting the telephone interviews entered the participants’ responses into the online survey in real-time, so that responses remained anonymised, and the information was stored in one database. Participation in the study was entirely voluntary, and no rewards or incentives were offered for taking part. Prior to being granted access to complete the survey, participants were requested to provide their consent.
The analysis of the survey data was descriptive, using frequency tables and graphs. Due to the potential risk of identifying participants based on the ethnicity question, certain categories were combined using the ethnicity prioritisation method as outlined by Statistics NZ and further elucidated by Yao et al. (2022).[[23]] This approach was implemented to ensure the protection of participant privacy and confidentiality. The free-text responses were coded using a simple inductive approach identifying common categories and meanings from the data. The analyses were performed in the statistical software R, version 4.2.1.[[24]]
The survey is reported based on the CHERRIES checklist (Appendix 2).
A total of 326 responses (out of 1,314 emails sent; response rate = 24.8%) were received between 7 June 2022 and 5 October 2022, including 15 from the telephone survey (of which four were completed in Fiji Hindi). Of the responses received, 226/326 (69.3%) were rated as “valid,” as they included complete responses to the two mandatory survey questions. No duplicates were identified.
The socio-demographic characteristics of the sample are presented in Table 1. Respondents were mostly NZ European (64.9%), Māori (11.9%) and Asian (10.9%), and their average age was 74.2 (10.6) years. Forty-two percent of the sample knew of a family/whānau member or friend who had been diagnosed with mild cognitive impairment (MCI) or dementia. With respect to caregivers, it is important to note that the responses provided in the data are anonymised, thus precluding the identification of specific individuals in caregiving roles. At least 15 people were caregivers of people living with dementia who were contacted through the Te Whatu Ora Counties Manukau Memory Team. However, 42% of respondents (n=85) reported having a family member or friend living with dementia, so it is reasonable to assume that at least some of these were also caregivers.
View Tables 1–3, Figures 1–2, Box 1.
Most participants (179/226, 79.2%) believed that Te Whatu Ora Counties Manukau used their health information in the ways described in all of the six different scenarios (see Figure 1 and Table 2), but up to 15% were unaware that health information from the whole population was combined to look at trends and improve services (scenarios E and F). When we separate this information by whether respondents know a family member/friend living with dementia, the trend does not change. The perception of participants regarding the utilisation of their health data across all proposed scenarios remains independent of having a family member or friend who is living with dementia (See Appendix 3, Table 1).
Figure 2 and Table 3 show that between 79.2 and 86.8% of participants were either comfortable or very comfortable in each of the scenarios proposed (A: 80.2% [n=182], B: 81.9% [n=186], C: 86.8% [n=197], D: 86.3% [n=196], E: 80.1% [n=181], F: 83.2% [n=188] and G: 79.2% [n=179]) and 63.3% [n=143]) felt “comfortable” or “very comfortable” across all seven scenarios. In contrast, less than 10% of the respondents felt uncomfortable or very uncomfortable in each of the scenarios presented (A: 7.1% [n=16], B: 8.0% [n=18], C: 5.3% [n=12], D: 5.8% [n=13], E: 8.0% [n=18], F: 7.0% [n=14] and G: 8.4% [n=19]). Four percent (n=9) felt “uncomfortable” or “very uncomfortable” across all of the scenarios. None of the scenarios drew a markedly different response compared to others. Despite the generally high levels of comfort observed (indicated by scores 4 and 5), individuals who have personal knowledge of someone living with dementia exhibit a slight decrease in the frequency of assigning a score of 5 compared to those without such personal connections (see Appendix 3, Table 2).
A total of 54/226 (23.9%) participants commented on their comfort with the use of their health information in the different scenarios. Of those who commented, 57.4% (31/54) felt comfortable with the use of the data in any scenario, although some stated specific conditions for use. Nine respondents (16.7%) were not comfortable, and 14 did not have any relevant comments.
Most expressed the opinion that they were comfortable, provided that health information should be used to improve health services for the local population.
“The wonderful care I have received has been informed, and developed, over time, so am happy that anything learnt about me can be used to help others into the future. Win win!” (Female, 65–74 years, “other” ethnicity)
“As long as it improves the time it takes to get healthcare” (Female, 75–84, NZ European)
Participants were also asked if they had any concerns about how Te Whatu Ora Counties Manukau uses their data, and 141/226 (61.9%) free-text responses were obtained. These overlapped with the level of comfort comments and were analysed together. Most people (102/141, 72.3%) stated that they had no concerns, but 27.7% mentioned scenarios in which they would have concerns. These themes are presented in Box 1.
Sixty-four percent of respondents (144/226) commented on situations where permission would be required before combining health data with other data to better understand the entire population’s health. Of the 144, 45.8% (n=66) said that obtaining permission to combine health data was not required in any situation, and 18.8% (n=27) specified it would not be necessary to obtain permission if data were de-identified, stored securely, not shared publicly and handled only by health professionals/researchers. Nineteen respondents (13.2%) said that permission should always be obtained to combine the data for any situation, and two respondents (1.4%) commented that, although a priori consent was not required, they would like to be informed if their data were used. Nineteen respondents (13.2%) responded that they did not know, or their responses did not correspond to the question asked.
Eleven of the 144 respondents (7.6%) specified other situations where permission should be obtained, for example, if the health information:
• is to be used by people other than health professionals/researchers (n=2)
• contains sensitive health issues or identifiable information (n=5)
• is combined with data from an organisation not related to health (n=1)
• is discussed outside the specific health service that collected it (n=1)
• is used for commercial purposes (n=2)
This study found that 79% of the people surveyed knew that Te Whatu Ora Counties Manukau currently used their routinely collected health information in the ways described in the scenarios, and 63% were comfortable or very comfortable with their data being used as described. Approximately 10% were not comfortable with their data being used in the ways described. Participants expressed concerns about the accuracy of data, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies.
Although the majority of respondents commented that it was not necessary to obtain specific permission for data linkage, there were a range of conditions mentioned that underpinned peoples’ comfort with their health information being combined with the health information of others for secondary purposes: data must be anonymous, not shared outside the health service with the public or sold to private companies such as insurers or pharmaceutical companies, and that patients should be informed beforehand about how data will be used.
Our results align with those presented by Dobson et al.,[[16]] which suggests that older people living in New Zealand have opinions about managing their health data that are similar to that of the wider population. Regarding the current use of health data across the scenarios presented in both Dobson’s study and ours, more than 80% of the participants were comfortable or very comfortable with how their data were being used, and less than 10% were uncomfortable or very uncomfortable. Given that the studies had different populations—Dobson’s study encompassed a wide age range spanning from 16 to 95 years—while the present study specifically focussed on the opinions and preferences of older individuals with a mean age of 74 years. Additionally, Dobson’s study was conducted in Te Whatu Ora Waitematā, whereas the current study took place in Te Whatu Ora Counties Manukau—the finding supports that most people agree with their de-identified data being used for the greater good, as long as key conditions are met around the protection, storage and care of the data. Our findings also coincide with those of Rezaei et al. (2021), who surveyed a sample of healthcare professionals regarding ethical challenges in using health data.[[25]] The main issues were privacy, autonomy and security. Papoutsi et al. (2015) surveyed patients from primary and secondary care settings in West London (United Kingdom)[[26]] and found similar concerns about data inaccuracies, prejudice “about sexual or mental health and being labelled as ‘hypochondriac’ or as having social problems,” and potential security and privacy threats; however, the majority of participants were in favour of using data for personal healthcare provision (89.7%), for health services policy and planning (79.5%), or for research (81.4%). The authors concluded that public participation and transparency are the pillars to establish the limits of the information to be shared and how researchers and medical personnel should access the data.[[26]]
A limitation of our study is the generalisability of the results. According to the 2018 population census,[[27]] the distribution of ethnicity in the Counties Manukau population aged 65+ was 7% Māori, 12% Pacific Islanders, 20% Asian and 60% NZ European. The ethnic breakdown of our sample was partially representative of the local population (12% Māori, 6% Pacific Islanders, 11% Asian and 65% NZ European), but the small sample size did not allow us to fully explore inter-ethnic differences in responses. In addition, about 25% of patients in the Te Whatu Ora Counties Manukau Memory Team have verified email addresses, contributing to the under-representation of different ethnicities in the responses. To address this issue, alternative sampling techniques should be implemented to ensure a more comprehensive representation of all ethnicities.
For Māori people, data should be considered as taonga, which relates to the idea that data are owned collectively by one or more whānau and are covered by rights, with obligations for active protection of that power by the Crown.[[28]] Further work is required to delve deeper into the use of healthcare information and the implications for Māori Data Sovereignty, the inherent rights and interests that Māori have in relation to the collection, ownership and application of Māori data.[[29]] It was notable that several Māori respondents did not agree to their data being used after their death, because one tikanga perspective is that the deceased are tapu and items belonging to the deceased are to be destroyed.[[30]] More work needs to be done to address Māori data concerns, particularly post-mortem data, which are important predictors of mortality and need to be analysed in research. Such concerns might indicate that IT-system design needs to be considered to reflect a culturally responsive system that aligns with the use of routinely collected health data relevant to examination of mate wareware (dementia) from a Māori perspective.[[31]] Current health IT systems are not designed to give patient control over the use of their data (for example, to opt out of research that is deemed not culturally appropriate). Adequately addressing cultural considerations with respect to data use may place demands on IT systems for greater patient control over their data and effective consent mechanisms for the use of their data.
The results of our study suggest that health services need to reflect on how best to use and protect peoples’ health data—a rich resource—while also respecting peoples’ rights to say how their data are used. Our findings are a first step towards describing older peoples’ opinions about how to use their health data for health research around brain health. The next phase of the study will focus on conducting more in-depth individual interviews to gain a deeper understanding of peoples’ opinions in different scenarios regarding the use of their health data. This could be particularly relevant for Māori, Pacific Island and Asian communities, who may possess distinct perspectives that differ from the majority of the survey sample, which predominantly was NZ European (65%).
Our findings indicate that these respondents are supportive of their health information being used for secondary purposes to benefit others, but there are conditions/limitations to this comfort that researchers need to consider, ensuring they use health information in a patient-informed way. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly with respect to Māori cultural considerations.
View Appendices 1–3.
Routinely collected health data can provide rich information for research and epidemiological monitoring of different diseases, but using the data presents many challenges. This study aims to explore the attitudes and preferences of people aged 55 and over regarding the use of their de-identified health data, and their concerns and comfort in different scenarios.
An anonymous online survey was conducted with people aged 55 and over currently engaged with health services in a New Zealand health district during June–October 2022. The survey could be completed online or by telephone and was available in eight languages.
Seventy-nine percent of respondents knew that their health information was currently being used in the ways described in the scenarios, and between 80–87% felt comfortable or very comfortable with their data being used as described in the scenarios. In contrast, 4% (n=9) felt “uncomfortable” or “very uncomfortable” across all of the scenarios. Participants expressed concerns about data accuracy, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies. Some participants identified situations where permission should be required to link data, including being used by people other than health professionals, containing sensitive health issues, or being used for commercial purposes.
This study finds general support from patients for the use of their routinely collected data for secondary purposes as long as its use will benefit the population from which the data are taken. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly concerning Māori cultural considerations.
1) Kalkman S, van Delden J, Banerjee A, et al. Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. J Med Ethics. 2022 Jan;48(1):3-13. doi: 10.1136/medethics-2019-105651.
2) Mursaleen LR, Stamford JA, Jones DA, et al. Attitudes towards data collection, ownership and sharing among patients with Parkinson’s disease. J Parkinsons Dis. 2017;7(3):523-531. doi: 10.3233/JPD-161045.
3) NICE Citizens Council. What ethical and practical issues need to be considered in the use of anonymised information derived from personal care records as part of the evaluation of treatments and delivery of care? [Internet]. London: National Institute for Health and Care Excellence (NICE); 2015 Nov 11. Citizens Council Reports No. 18.
4) Health Research Council of New Zealand. Guidelines for Researchers on Health Research involving Māori [Internet]. Auckland: Health Research Council of New Zealand; 2010 [cited 27 Mar 2023]. Available from: https://www.hrc.govt.nz/resources/guidelines-researchers-health-research-involving-maori.
5) Jorm L. Routinely collected data as a strategic resource for research: priorities for methods and workforce. Public Health Res Pract. 2015 Sep 30;25(4):e2541540. doi: 10.17061/phrp2541540.
6) Pylypchuk R, Wells S, Kerr A, et al. Cardiovascular disease risk prediction equations in 400 000 primary care patients in New Zealand: a derivation and validation study. Lancet. 2018 May 12;391(10133):1897-1907. doi: 10.1016/S0140-6736(18)30664-0.
7) Te Whatu Ora – Health New Zealand. Virtual Diabetes Register: Technical Guide [Internet]. Wellington: Te Whatu Ora – Health New Zealand; 2022 [cited 16 Mar 2023]. Available from: https://www.tewhatuora.govt.nz/publications/virtual-diabetes-register-technical-guide/.
8) Cheung G, To E, Rivera-Rodriguez C, et al. Dementia prevalence estimation among the main ethnic groups in New Zealand: a population-based descriptive study of routinely collected health data. BMJ Open. 2022 Sep 7;12(9):e062304. doi: 10.1136/bmjopen-2022-062304.
9) Ma’u E, Cullum S, Yates S, et al. Dementia Economic Impact Report 2020 [Internet]. Auckland: The University of Auckland,; 2021 [cited 12 Dec 2022]. Available from: https://cdn.alzheimers.org.nz/wp-content/uploads/2021/09/Dementia-Economic-Impact-Report-2020.pdf.
10) Cullum S, Mullin K, Zeng I, et al. Do community-dwelling Māori and Pacific peoples present with dementia at a younger age and at a later stage compared with NZ Europeans? Int J Geriatr Psychiatry. 2018 Aug;33(8):1098-1104. doi: 10.1002/gps.4898.
11) Cullum S, Varghese C, Yates S, et al. Predictors of Aged Residential Care Placement in Patients Newly Diagnosed with Dementia at a New Zealand Memory Service. J Long Term Care. 2021;0(2021):24-32. doi: 10.31389/jltc.46.
12) Cullum S, Varghese C, Coomarasamy C, et al. Predictors of mortality in Māori, Pacific Island, and European patients diagnosed with dementia at a New Zealand Memory Service. Int J Geriatr Psychiatry. 2020 May;35(5):516-524. doi: 10.1002/gps.5266.
13) Ma’u E, Saeed F, Yates S, et al. Do Māori and Pacific Peoples Living with Dementia in New Zealand Receive Equitable Long-Term Care Compared with New Zealand Europeans? J Long Term Care. 2022;0(2022):222-233. doi: 10.31389/jltc.148.
14) McCormick N, Hamilton C, Koehn CL, et al. Canadians’ views on the use of routinely collected data in health research: a patient-oriented cross-sectional survey. CMAJ Open. 2019 Apr 4;7(2):E203-E209. doi: 10.9778/cmajo.20180105.
15) Colombo C, Roberto A, Krleza-Jeric K, et al. Sharing individual participant data from clinical studies: a cross-sectional online survey among Italian patient and citizen groups. BMJ Open. 2019 Feb 19;9(2):e024863. doi: 10.1136/bmjopen-2018-024863.
16) Dobson R, Whittaker R, Wihongi H, et al. Patient perspectives on the use of health information. N Z Med J. 2021 Dec 17;134(1547):48-62.
17) Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet. 2017 Dec 16;390(10113):2673-2734. doi: 10.1016/S0140-6736(17)31363-6.
18) Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020 Aug 8;396(10248):413-446. doi: 10.1016/S0140-6736(20)30367-6.
19) Prince MJ, Wimo A, Guerchet MM, et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends [Internet]. London: Alzheimer’s Disease International (ADI); 2015 Aug [cited 16 Mar 2023]. Available from: https://www.alzint.org/u/WorldAlzheimerReport2015.pdf.
20) Jammeh EA, Carroll CB, Pearson SW, et al. Machine-learning based identification of undiagnosed dementia in primary care: a feasibility study. BJGP Open. 2018 Jun 13;2(2):bjgpopen18X101589. doi: 10.3399/bjgpopen18X101589.
21) Kumar S, Oh I, Schindler S, et al. Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review. JAMIA Open. 2021 Aug 2;4(3):ooab052. doi: 10.1093/jamiaopen/ooab052.
22) Lynch C. World Alzheimer Report 2019: Attitudes to dementia [Internet]. London: Alzheimer’s Disease International (ADI); 2020 [cited 17 Mar 2023]. Available from: https://www.alzint.org/u/WorldAlzheimerReport2019.pdf.
23) Yao ES, Meissel K, Bullen P, et al. Demographic discrepancies between administrative-prioritisation and self-prioritisation of multiple ethnic identifications. Soc Sci Res. 2022 Mar;103:102648. doi: 10.1016/j.ssresearch.2021.102648.
24) R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna: R Foundation for Statistical Computing; 2022 [cited 16 Jan 2023]. Available from: https://www.R-project.org/
25) Rezaei M, Jafari-Sadeghi V, Cao D, Mahdiraji HA. Key indicators of ethical challenges in digital healthcare: A combined Delphi exploration and confirmative factor analysis approach with evidence from Khorasan province in Iran. Technol Forecast Soc Change. 2021;167:120724. doi: 10.1016/j.techfore.2021.120724.
26) Papoutsi C, Reed JE, Marston C, et al. Patient and public views about the security and privacy of Electronic Health Records (EHRs) in the UK: results from a mixed methods study. BMC Med Inform Decis Mak. 2015 Oct 14;15:86:1-15. doi: 10.1186/s12911-015-0202-2.
27) Lees J, Lee M, Winnard D. Demographic Profile: 2018 Census, Population of Counties Manukau [Internet]. Auckland: Counties Manukau Health; 2021 [cited 30 May 2023]. Available from: https://www.countiesmanukau.health.nz/assets/About-CMH/Performance-and-planning/health-status/Demographic-profile-2018-Census-Population-of-Counties-Manukau.pdf.
28) Wilson D. Māori Data Sovereignty and the WAI 2522 Report: A summary of some Māori Data Sovereignty insights from the WAI 2522 Report on the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP). Auckland: The University of Auckland; 2022 [cited 14 Feb 2023].
29) Te Mana Raraunga. What is Māori Data Sovereignty? [Internet]. New Zealand: Te Mana Raraunga; 2023 [cited 27 Mar 2023]. Available from: https://www.temanararaunga.maori.nz/
30) Mead HM. Tikanga Māori: Living by Māori values. Wellington: Huia Publishers; 2016.
31) Dudley M, Menzies O, Elder H, et al. Mate wareware: Understanding ‘dementia’ from a Māori perspective. N Z Med J . 2019 Oct 4;132(1503):66-74.
With new technologies for storage, control and analysis, routinely collected health information has become a valuable tool for researching and developing health services. Utilisation of routinely collected data presents many different challenges, such as the quality of the information, proper management of privacy, ethical use of the information in contexts such as research and development, culturally appropriate use of health data and, in the context of New Zealand, the sovereignty of Māori health data.[[1–4]]
The use of routinely collected data has facilitated the monitoring of specific health conditions for epidemiological monitoring and improvement of health systems.[[5]] In New Zealand, analysis of routinely collected national data has been used to develop a clinical risk tool for cardiovascular disease[[6]] and a virtual diabetes register.[[7]] In the field of dementia, routinely collected health data have been used to estimate the prevalence of dementia using national datasets; the findings suggested that the prevalence of dementia in Māori and Pacific Island communities is higher than in other ethnic groups.[[8]] However, community-based dementia prevalence data in New Zealand to test the accuracy of these routinely collected health datasets are scarce.[[9]] At a more local level, studies using routine health data allow statistical adjustment for potential confounding factors such as comorbidity. These studies suggest there are differences in outcomes for Māori and Pacific Islanders living with dementia (for example, utilisation of dementia services and mortality).[[10–13]]
Although routinely collected de-identified data can provide valuable knowledge about the epidemiological characteristics of common chronic diseases in New Zealand, these data have tended to be used without individual consent. To date, there has been little research into peoples’ opinions about the use and treatment of their health information. In Canada, McCormick et al. (2019) conducted an online survey to compare the opinions of people about the use of routinely collected data for health research and reported that close to 80% of the surveyed people felt positive about the use of that information for research.[[14]] Similarly, Colombo et al. (2019) conducted a survey to understand the opinions and attitudes of people about using their data in clinical studies in Italy. Thirty-nine percent of the participants approved access to health data to researchers and professionals, and identified important topics, such as data de-identification, secure archives and access agreements, as essential aspects of the sharing models.[[15]]
In New Zealand, an online survey (Dobson et al., 2021) conducted at Waitematā District Health Board (DHB) investigated patient perspectives, preferences and comfort levels regarding the use of their health data.[[16]] In the population of inpatients and outpatients they found that more than 80% of participants (aged 16 to 95 years) were comfortable with how de-identified health information was used across various scenarios. However, many stated that they would require the information collected to be accurate and stored securely within the health system, that privacy was maintained, and the data were only used for the public good. They also expressed a preference for improved communication and transparency around how their data were used.
Our research group is interested in exploring whether routinely collected data can be used to predict future decline in brain health and/or dementia and what might be done to promote resilience of brain health. The Lancet Commission for Dementia[[17,18]] described 12 modifiable risk factors for dementia—in early life (education), in middle age (hearing loss, TBI, hypertension, alcohol and obesity) and in later life (smoking, depression, social isolation, physical inactivity, air pollution, diabetes). Some of these risk factors could be identified using routine health data and would allow the identification of groups of people at higher risk at a population level, which might inform population-level interventions targeted at reducing risk of disease. The prevalence of dementia is rising rapidly due to global demographic ageing and is expected to triple between 2015 and 2050.[[19]] To date, there is no cure for dementia, so researchers worldwide are attempting to find clinical biomarkers that might provide early identification of people at high risk and hopefully intervene before the onset of irreversible dementia. This is a rapidly developing field, particularly with the growing development of artificial intelligence and machine learning methods for diagnosing and detecting risk factors for various diseases, including dementia, which could be utilised with routinely collected health data.[[20–21]]
The early identification of decline in brain health is a controversial area, as dementia is still a highly stigmatised disease,[[22]] and people may not feel comfortable about their health data being used for this purpose, particularly if they fear being identified as being at risk. For that reason, our research group felt that we could not assume that the findings of Dobson et al.[[16]] (2021) would apply in the specific area of cognitive decline and dementia; thus, we decided to repeat the survey with a focus on brain health.
Our research aimed to explore the attitudes and preferences of people aged 55+ regarding the acceptable use of their de-identified health data and understanding their concerns and comfort in different scenarios related to identification of factors related to cognitive decline and dementia. This would allow New Zealand health institutions and researchers to gain a clearer picture of patients’ attitudes and preferences around the use of their de-identified health data in brain health research.
People aged 55 and over currently engaged with health services in Te Whatu Ora Counties Manukau were invited to participate in the survey. We chose the cut-off at age 55 because, compared to NZ Europeans, the average age of the onset (or recognition) of dementia is younger for Māori or Pacific peoples living in New Zealand.[[10]] We included people living with dementia who were known to the Te Whatu Ora Counties Manukau Memory Team and their caregivers. This was done to ensure we had a good representation of people who had lived experience of dementia (either personal or as a caregiver).
The survey sought to gain an understanding of the opinions of older people about the management of their health information, with the following inclusion criteria:
• Currently resident in New Zealand
• Aged 55 years or older
• Currently using health services in Te Whatu Ora Counties Manukau
These criteria were waived for caregivers of a person living with dementia to ensure their inclusion and representation.
Our survey was based on the survey constructed by Dobson et al. (2021).[[16]] A study advisory group with broad representation—including Māori health expertise—drafted questions for Dobson’s survey. The research group, advised by Dobson, adapted the original questionnaire for our target population, referencing brain health. We also asked people if they were willing to be individually interviewed (Q13 in the survey) so that we could go into more depth regarding specific issues for Māori and Pacific Islanders.
The survey included a total of 13 questions, assessing:
• Perceptions about the current use of health information by the health service (Te Whatu Ora Counties Manukau) across six different scenarios (mandatory question).
• Perceived comfort with the use of health information on a Likert scale from 1 (very uncomfortable) to 5 (very comfortable) across the same six scenarios, plus one extra (mandatory question).
• Free-text comments about their level of comfort with the use of health information.
• Free-text comments about situations where permission should be sought before their health information was combined with other peoples’ to better understand the health of the local population.
• Final comments on the use of health information by Te Whatu Ora Counties Manukau.
• Socio-demographic variables, including year of birth and ethnicity.
All participants received the exact same survey without any randomised items, and adaptive questioning was employed when necessary to minimise the burden on respondents and simplify the complexity of the questions. Also, they could review their answers using the “back button” available in the online questionnaire. The complete survey is available in Appendix 1.
A preliminary survey pilot was conducted to evaluate response times, the relevance of the questions, and the design of the data capture and collection instrument. The final survey was administered in Qualtrics and distributed via an anonymised email link.
In the introduction to the survey, we offered the option of conducting the survey by telephone for those who wished to do so, either in English or in another language: Te Reo Māori, Samoan, Tongan, Mandarin, Cantonese, Hindi or Fijian Hindi.
This research was approved for three years by Auckland Health Research Ethics Committee AH22266 on 18 October 2021.
A link to the online survey was sent by email to outpatients aged 55+ whose email addresses were verified in the Te Whatu Ora Counties Manukau Patient Information Management System (PIMS). The emails were sent to attendees of the Health of Older People outpatient services between 3 January 2019–31 December 2021, including people referred to the memory team, irrespective of the diagnosis made. We invited both patients and their whānau members to be involved in the survey (see survey: Appendix 1). We also specifically invited caregivers of people living with dementia who were current service users of Te Whatu Ora Counties Manukau Memory Team to ensure that their views were included.
Patients (or caregivers of people living with dementia) who wanted to participate but did not wish to complete an online survey were offered the option of an adapted telephone interview. The research assistant conducting the telephone interviews entered the participants’ responses into the online survey in real-time, so that responses remained anonymised, and the information was stored in one database. Participation in the study was entirely voluntary, and no rewards or incentives were offered for taking part. Prior to being granted access to complete the survey, participants were requested to provide their consent.
The analysis of the survey data was descriptive, using frequency tables and graphs. Due to the potential risk of identifying participants based on the ethnicity question, certain categories were combined using the ethnicity prioritisation method as outlined by Statistics NZ and further elucidated by Yao et al. (2022).[[23]] This approach was implemented to ensure the protection of participant privacy and confidentiality. The free-text responses were coded using a simple inductive approach identifying common categories and meanings from the data. The analyses were performed in the statistical software R, version 4.2.1.[[24]]
The survey is reported based on the CHERRIES checklist (Appendix 2).
A total of 326 responses (out of 1,314 emails sent; response rate = 24.8%) were received between 7 June 2022 and 5 October 2022, including 15 from the telephone survey (of which four were completed in Fiji Hindi). Of the responses received, 226/326 (69.3%) were rated as “valid,” as they included complete responses to the two mandatory survey questions. No duplicates were identified.
The socio-demographic characteristics of the sample are presented in Table 1. Respondents were mostly NZ European (64.9%), Māori (11.9%) and Asian (10.9%), and their average age was 74.2 (10.6) years. Forty-two percent of the sample knew of a family/whānau member or friend who had been diagnosed with mild cognitive impairment (MCI) or dementia. With respect to caregivers, it is important to note that the responses provided in the data are anonymised, thus precluding the identification of specific individuals in caregiving roles. At least 15 people were caregivers of people living with dementia who were contacted through the Te Whatu Ora Counties Manukau Memory Team. However, 42% of respondents (n=85) reported having a family member or friend living with dementia, so it is reasonable to assume that at least some of these were also caregivers.
View Tables 1–3, Figures 1–2, Box 1.
Most participants (179/226, 79.2%) believed that Te Whatu Ora Counties Manukau used their health information in the ways described in all of the six different scenarios (see Figure 1 and Table 2), but up to 15% were unaware that health information from the whole population was combined to look at trends and improve services (scenarios E and F). When we separate this information by whether respondents know a family member/friend living with dementia, the trend does not change. The perception of participants regarding the utilisation of their health data across all proposed scenarios remains independent of having a family member or friend who is living with dementia (See Appendix 3, Table 1).
Figure 2 and Table 3 show that between 79.2 and 86.8% of participants were either comfortable or very comfortable in each of the scenarios proposed (A: 80.2% [n=182], B: 81.9% [n=186], C: 86.8% [n=197], D: 86.3% [n=196], E: 80.1% [n=181], F: 83.2% [n=188] and G: 79.2% [n=179]) and 63.3% [n=143]) felt “comfortable” or “very comfortable” across all seven scenarios. In contrast, less than 10% of the respondents felt uncomfortable or very uncomfortable in each of the scenarios presented (A: 7.1% [n=16], B: 8.0% [n=18], C: 5.3% [n=12], D: 5.8% [n=13], E: 8.0% [n=18], F: 7.0% [n=14] and G: 8.4% [n=19]). Four percent (n=9) felt “uncomfortable” or “very uncomfortable” across all of the scenarios. None of the scenarios drew a markedly different response compared to others. Despite the generally high levels of comfort observed (indicated by scores 4 and 5), individuals who have personal knowledge of someone living with dementia exhibit a slight decrease in the frequency of assigning a score of 5 compared to those without such personal connections (see Appendix 3, Table 2).
A total of 54/226 (23.9%) participants commented on their comfort with the use of their health information in the different scenarios. Of those who commented, 57.4% (31/54) felt comfortable with the use of the data in any scenario, although some stated specific conditions for use. Nine respondents (16.7%) were not comfortable, and 14 did not have any relevant comments.
Most expressed the opinion that they were comfortable, provided that health information should be used to improve health services for the local population.
“The wonderful care I have received has been informed, and developed, over time, so am happy that anything learnt about me can be used to help others into the future. Win win!” (Female, 65–74 years, “other” ethnicity)
“As long as it improves the time it takes to get healthcare” (Female, 75–84, NZ European)
Participants were also asked if they had any concerns about how Te Whatu Ora Counties Manukau uses their data, and 141/226 (61.9%) free-text responses were obtained. These overlapped with the level of comfort comments and were analysed together. Most people (102/141, 72.3%) stated that they had no concerns, but 27.7% mentioned scenarios in which they would have concerns. These themes are presented in Box 1.
Sixty-four percent of respondents (144/226) commented on situations where permission would be required before combining health data with other data to better understand the entire population’s health. Of the 144, 45.8% (n=66) said that obtaining permission to combine health data was not required in any situation, and 18.8% (n=27) specified it would not be necessary to obtain permission if data were de-identified, stored securely, not shared publicly and handled only by health professionals/researchers. Nineteen respondents (13.2%) said that permission should always be obtained to combine the data for any situation, and two respondents (1.4%) commented that, although a priori consent was not required, they would like to be informed if their data were used. Nineteen respondents (13.2%) responded that they did not know, or their responses did not correspond to the question asked.
Eleven of the 144 respondents (7.6%) specified other situations where permission should be obtained, for example, if the health information:
• is to be used by people other than health professionals/researchers (n=2)
• contains sensitive health issues or identifiable information (n=5)
• is combined with data from an organisation not related to health (n=1)
• is discussed outside the specific health service that collected it (n=1)
• is used for commercial purposes (n=2)
This study found that 79% of the people surveyed knew that Te Whatu Ora Counties Manukau currently used their routinely collected health information in the ways described in the scenarios, and 63% were comfortable or very comfortable with their data being used as described. Approximately 10% were not comfortable with their data being used in the ways described. Participants expressed concerns about the accuracy of data, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies.
Although the majority of respondents commented that it was not necessary to obtain specific permission for data linkage, there were a range of conditions mentioned that underpinned peoples’ comfort with their health information being combined with the health information of others for secondary purposes: data must be anonymous, not shared outside the health service with the public or sold to private companies such as insurers or pharmaceutical companies, and that patients should be informed beforehand about how data will be used.
Our results align with those presented by Dobson et al.,[[16]] which suggests that older people living in New Zealand have opinions about managing their health data that are similar to that of the wider population. Regarding the current use of health data across the scenarios presented in both Dobson’s study and ours, more than 80% of the participants were comfortable or very comfortable with how their data were being used, and less than 10% were uncomfortable or very uncomfortable. Given that the studies had different populations—Dobson’s study encompassed a wide age range spanning from 16 to 95 years—while the present study specifically focussed on the opinions and preferences of older individuals with a mean age of 74 years. Additionally, Dobson’s study was conducted in Te Whatu Ora Waitematā, whereas the current study took place in Te Whatu Ora Counties Manukau—the finding supports that most people agree with their de-identified data being used for the greater good, as long as key conditions are met around the protection, storage and care of the data. Our findings also coincide with those of Rezaei et al. (2021), who surveyed a sample of healthcare professionals regarding ethical challenges in using health data.[[25]] The main issues were privacy, autonomy and security. Papoutsi et al. (2015) surveyed patients from primary and secondary care settings in West London (United Kingdom)[[26]] and found similar concerns about data inaccuracies, prejudice “about sexual or mental health and being labelled as ‘hypochondriac’ or as having social problems,” and potential security and privacy threats; however, the majority of participants were in favour of using data for personal healthcare provision (89.7%), for health services policy and planning (79.5%), or for research (81.4%). The authors concluded that public participation and transparency are the pillars to establish the limits of the information to be shared and how researchers and medical personnel should access the data.[[26]]
A limitation of our study is the generalisability of the results. According to the 2018 population census,[[27]] the distribution of ethnicity in the Counties Manukau population aged 65+ was 7% Māori, 12% Pacific Islanders, 20% Asian and 60% NZ European. The ethnic breakdown of our sample was partially representative of the local population (12% Māori, 6% Pacific Islanders, 11% Asian and 65% NZ European), but the small sample size did not allow us to fully explore inter-ethnic differences in responses. In addition, about 25% of patients in the Te Whatu Ora Counties Manukau Memory Team have verified email addresses, contributing to the under-representation of different ethnicities in the responses. To address this issue, alternative sampling techniques should be implemented to ensure a more comprehensive representation of all ethnicities.
For Māori people, data should be considered as taonga, which relates to the idea that data are owned collectively by one or more whānau and are covered by rights, with obligations for active protection of that power by the Crown.[[28]] Further work is required to delve deeper into the use of healthcare information and the implications for Māori Data Sovereignty, the inherent rights and interests that Māori have in relation to the collection, ownership and application of Māori data.[[29]] It was notable that several Māori respondents did not agree to their data being used after their death, because one tikanga perspective is that the deceased are tapu and items belonging to the deceased are to be destroyed.[[30]] More work needs to be done to address Māori data concerns, particularly post-mortem data, which are important predictors of mortality and need to be analysed in research. Such concerns might indicate that IT-system design needs to be considered to reflect a culturally responsive system that aligns with the use of routinely collected health data relevant to examination of mate wareware (dementia) from a Māori perspective.[[31]] Current health IT systems are not designed to give patient control over the use of their data (for example, to opt out of research that is deemed not culturally appropriate). Adequately addressing cultural considerations with respect to data use may place demands on IT systems for greater patient control over their data and effective consent mechanisms for the use of their data.
The results of our study suggest that health services need to reflect on how best to use and protect peoples’ health data—a rich resource—while also respecting peoples’ rights to say how their data are used. Our findings are a first step towards describing older peoples’ opinions about how to use their health data for health research around brain health. The next phase of the study will focus on conducting more in-depth individual interviews to gain a deeper understanding of peoples’ opinions in different scenarios regarding the use of their health data. This could be particularly relevant for Māori, Pacific Island and Asian communities, who may possess distinct perspectives that differ from the majority of the survey sample, which predominantly was NZ European (65%).
Our findings indicate that these respondents are supportive of their health information being used for secondary purposes to benefit others, but there are conditions/limitations to this comfort that researchers need to consider, ensuring they use health information in a patient-informed way. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly with respect to Māori cultural considerations.
View Appendices 1–3.
Routinely collected health data can provide rich information for research and epidemiological monitoring of different diseases, but using the data presents many challenges. This study aims to explore the attitudes and preferences of people aged 55 and over regarding the use of their de-identified health data, and their concerns and comfort in different scenarios.
An anonymous online survey was conducted with people aged 55 and over currently engaged with health services in a New Zealand health district during June–October 2022. The survey could be completed online or by telephone and was available in eight languages.
Seventy-nine percent of respondents knew that their health information was currently being used in the ways described in the scenarios, and between 80–87% felt comfortable or very comfortable with their data being used as described in the scenarios. In contrast, 4% (n=9) felt “uncomfortable” or “very uncomfortable” across all of the scenarios. Participants expressed concerns about data accuracy, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies. Some participants identified situations where permission should be required to link data, including being used by people other than health professionals, containing sensitive health issues, or being used for commercial purposes.
This study finds general support from patients for the use of their routinely collected data for secondary purposes as long as its use will benefit the population from which the data are taken. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly concerning Māori cultural considerations.
1) Kalkman S, van Delden J, Banerjee A, et al. Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence. J Med Ethics. 2022 Jan;48(1):3-13. doi: 10.1136/medethics-2019-105651.
2) Mursaleen LR, Stamford JA, Jones DA, et al. Attitudes towards data collection, ownership and sharing among patients with Parkinson’s disease. J Parkinsons Dis. 2017;7(3):523-531. doi: 10.3233/JPD-161045.
3) NICE Citizens Council. What ethical and practical issues need to be considered in the use of anonymised information derived from personal care records as part of the evaluation of treatments and delivery of care? [Internet]. London: National Institute for Health and Care Excellence (NICE); 2015 Nov 11. Citizens Council Reports No. 18.
4) Health Research Council of New Zealand. Guidelines for Researchers on Health Research involving Māori [Internet]. Auckland: Health Research Council of New Zealand; 2010 [cited 27 Mar 2023]. Available from: https://www.hrc.govt.nz/resources/guidelines-researchers-health-research-involving-maori.
5) Jorm L. Routinely collected data as a strategic resource for research: priorities for methods and workforce. Public Health Res Pract. 2015 Sep 30;25(4):e2541540. doi: 10.17061/phrp2541540.
6) Pylypchuk R, Wells S, Kerr A, et al. Cardiovascular disease risk prediction equations in 400 000 primary care patients in New Zealand: a derivation and validation study. Lancet. 2018 May 12;391(10133):1897-1907. doi: 10.1016/S0140-6736(18)30664-0.
7) Te Whatu Ora – Health New Zealand. Virtual Diabetes Register: Technical Guide [Internet]. Wellington: Te Whatu Ora – Health New Zealand; 2022 [cited 16 Mar 2023]. Available from: https://www.tewhatuora.govt.nz/publications/virtual-diabetes-register-technical-guide/.
8) Cheung G, To E, Rivera-Rodriguez C, et al. Dementia prevalence estimation among the main ethnic groups in New Zealand: a population-based descriptive study of routinely collected health data. BMJ Open. 2022 Sep 7;12(9):e062304. doi: 10.1136/bmjopen-2022-062304.
9) Ma’u E, Cullum S, Yates S, et al. Dementia Economic Impact Report 2020 [Internet]. Auckland: The University of Auckland,; 2021 [cited 12 Dec 2022]. Available from: https://cdn.alzheimers.org.nz/wp-content/uploads/2021/09/Dementia-Economic-Impact-Report-2020.pdf.
10) Cullum S, Mullin K, Zeng I, et al. Do community-dwelling Māori and Pacific peoples present with dementia at a younger age and at a later stage compared with NZ Europeans? Int J Geriatr Psychiatry. 2018 Aug;33(8):1098-1104. doi: 10.1002/gps.4898.
11) Cullum S, Varghese C, Yates S, et al. Predictors of Aged Residential Care Placement in Patients Newly Diagnosed with Dementia at a New Zealand Memory Service. J Long Term Care. 2021;0(2021):24-32. doi: 10.31389/jltc.46.
12) Cullum S, Varghese C, Coomarasamy C, et al. Predictors of mortality in Māori, Pacific Island, and European patients diagnosed with dementia at a New Zealand Memory Service. Int J Geriatr Psychiatry. 2020 May;35(5):516-524. doi: 10.1002/gps.5266.
13) Ma’u E, Saeed F, Yates S, et al. Do Māori and Pacific Peoples Living with Dementia in New Zealand Receive Equitable Long-Term Care Compared with New Zealand Europeans? J Long Term Care. 2022;0(2022):222-233. doi: 10.31389/jltc.148.
14) McCormick N, Hamilton C, Koehn CL, et al. Canadians’ views on the use of routinely collected data in health research: a patient-oriented cross-sectional survey. CMAJ Open. 2019 Apr 4;7(2):E203-E209. doi: 10.9778/cmajo.20180105.
15) Colombo C, Roberto A, Krleza-Jeric K, et al. Sharing individual participant data from clinical studies: a cross-sectional online survey among Italian patient and citizen groups. BMJ Open. 2019 Feb 19;9(2):e024863. doi: 10.1136/bmjopen-2018-024863.
16) Dobson R, Whittaker R, Wihongi H, et al. Patient perspectives on the use of health information. N Z Med J. 2021 Dec 17;134(1547):48-62.
17) Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet. 2017 Dec 16;390(10113):2673-2734. doi: 10.1016/S0140-6736(17)31363-6.
18) Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020 Aug 8;396(10248):413-446. doi: 10.1016/S0140-6736(20)30367-6.
19) Prince MJ, Wimo A, Guerchet MM, et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends [Internet]. London: Alzheimer’s Disease International (ADI); 2015 Aug [cited 16 Mar 2023]. Available from: https://www.alzint.org/u/WorldAlzheimerReport2015.pdf.
20) Jammeh EA, Carroll CB, Pearson SW, et al. Machine-learning based identification of undiagnosed dementia in primary care: a feasibility study. BJGP Open. 2018 Jun 13;2(2):bjgpopen18X101589. doi: 10.3399/bjgpopen18X101589.
21) Kumar S, Oh I, Schindler S, et al. Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review. JAMIA Open. 2021 Aug 2;4(3):ooab052. doi: 10.1093/jamiaopen/ooab052.
22) Lynch C. World Alzheimer Report 2019: Attitudes to dementia [Internet]. London: Alzheimer’s Disease International (ADI); 2020 [cited 17 Mar 2023]. Available from: https://www.alzint.org/u/WorldAlzheimerReport2019.pdf.
23) Yao ES, Meissel K, Bullen P, et al. Demographic discrepancies between administrative-prioritisation and self-prioritisation of multiple ethnic identifications. Soc Sci Res. 2022 Mar;103:102648. doi: 10.1016/j.ssresearch.2021.102648.
24) R Core Team. R: A Language and Environment for Statistical Computing [Internet]. Vienna: R Foundation for Statistical Computing; 2022 [cited 16 Jan 2023]. Available from: https://www.R-project.org/
25) Rezaei M, Jafari-Sadeghi V, Cao D, Mahdiraji HA. Key indicators of ethical challenges in digital healthcare: A combined Delphi exploration and confirmative factor analysis approach with evidence from Khorasan province in Iran. Technol Forecast Soc Change. 2021;167:120724. doi: 10.1016/j.techfore.2021.120724.
26) Papoutsi C, Reed JE, Marston C, et al. Patient and public views about the security and privacy of Electronic Health Records (EHRs) in the UK: results from a mixed methods study. BMC Med Inform Decis Mak. 2015 Oct 14;15:86:1-15. doi: 10.1186/s12911-015-0202-2.
27) Lees J, Lee M, Winnard D. Demographic Profile: 2018 Census, Population of Counties Manukau [Internet]. Auckland: Counties Manukau Health; 2021 [cited 30 May 2023]. Available from: https://www.countiesmanukau.health.nz/assets/About-CMH/Performance-and-planning/health-status/Demographic-profile-2018-Census-Population-of-Counties-Manukau.pdf.
28) Wilson D. Māori Data Sovereignty and the WAI 2522 Report: A summary of some Māori Data Sovereignty insights from the WAI 2522 Report on the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP). Auckland: The University of Auckland; 2022 [cited 14 Feb 2023].
29) Te Mana Raraunga. What is Māori Data Sovereignty? [Internet]. New Zealand: Te Mana Raraunga; 2023 [cited 27 Mar 2023]. Available from: https://www.temanararaunga.maori.nz/
30) Mead HM. Tikanga Māori: Living by Māori values. Wellington: Huia Publishers; 2016.
31) Dudley M, Menzies O, Elder H, et al. Mate wareware: Understanding ‘dementia’ from a Māori perspective. N Z Med J . 2019 Oct 4;132(1503):66-74.
The full contents of this pages only available to subscribers.
Login, subscribe or email nzmj@nzma.org.nz to purchase this article.