DESK REVIEWS | 07.01.04. Are there differences in diagnostic assessment according to geographical areas (rural/urban) and also according to other socio-economic factors?

DESK REVIEW | 07.01.04. Are there differences in diagnostic assessment according to geographical areas (rural/urban) and also according to other socio-economic factors?

We do not have data on this for the country, neither for smaller areas. According to our previous study conducted in one city (São José dos Campos, in São Paulo state), we found that rates of under diagnosis were lower in the rich areas of the city (Nakamura et al., 2015).

References:

Nakamura, A., Opaleye, D., Tani, G., & Ferri, C. P. (2015). Dementia underdiagnosis in Brazil. The Lancet, 385(9966), 418–419. https://doi.org/10.1016/S0140-6736(15)60153-2

Rural-urban division is not applicable in Hong Kong as, according to the World Bank, the urban population accounts for 100% of its total population since 1993.

Local evidence on the impact of socio-economic factors on receiving diagnostic assessment is relatively limited. A study (Tang et al., 2016) comparing the characteristics of early help seekers (i.e., seek help within a year since noticing the first symptom) and late help seekers, finds that the early help seekers are more likely to live in private housing. It also suggests that people with better socio-economic status may facilitate earlier help seeking.

References:

Tang, J. Y. M., Wong, G. H. Y., Ng, C. K. M., Kwok, D. T. S., Lee, M. N. Y., Dai, D. L. K., & Lum, T. Y. S. (2016). Neuropsychological profile and dementia symptom recognition in help-seekers in a community early-detection program in Hong Kong. Journal of the American Geriatrics Society, 64(3), 584-589. http://dx.doi.org/10.1111/jgs.13938

There are differences in diagnostic assessment across the country due to diversity in demographics (rural/urban, region and state) and socioeconomic status. Diagnostic tools have been developed and/or adapted to account for this diversity. The Indian Council of Medical Research (ICMR), Department of Health Research (2021), released a Neurocognitive Tool Box. It is culturally validated and available in 5 Indian languages (Hindi, Bengali, Telugu, Kannada and Malayalam) (ICMR, 2021). The 10/66 Dementia Research Group has developed a cross-culturally validated dementia diagnostic algorithm (Prince et al., 2008). There are also other neuropsychological assessments that have been translated into various regional languages as well as culturally adapted to the Indian context. These include: Addenbrookes Cognitive Examination (ACE) (Version III and Version R), Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessments (MoCA) (Porrselvi and Shankar, 2017).

Table 7.1 shows the Cognitive screening measures with Indian adaptions:

Global Screening Measures Indian adaptation Literacy / socioeconomic background
Mini Mental State Examination Hindi mental state examination (HMSE) Hindi-speaking, illiterate, rural elderly population.
Addenbrooke’s Cognitive Examination-Revised and ACE III Tamil, Hindi, Indian English, Kannada, Telugu, Urdu, Malayalam and Marathi. Literate and illiterate versions.
Montreal Cognitive Assessment (MoCA) Bengali, Kannada, Malayalam, Marathi, Tamil, Telugu, Hindi, and Urdu. Computerized version in development.
Community Screening Instrument for Dementia   Developed for use in primary care settings by non-specialist health workers.
Kolkata Cognitive Screening Battery Bengali Test developed for Kolkata population.
Mattis Dementia Rating Scale Hindi Hindi-speaking Indian population.
Rowland Universal Dementia Assessment tool (RUDAS) Malayalam Kerala state population
Picture-based memory impairment screen Used for all languages Culture-fair (measure cognition without the influence of sociocultural factors), picture-based cognitive screen designed to be administered by non-specialists.

Source: (Porrselvi and Shankar, 2017)

References:

Indian Council of Medical Research (ICMR). 2021. INDIAN COUNCIL OF MEDICAL RESEARCH -NEURO COGNITIVE TOOLBOX (ICMR-NCTB). Available from: http://brandp.in/icmr/index.html

Porrselvi, A.P., Shankar, V., 2017. Status of Cognitive Testing of Adults in India. Ann. Indian Acad. Neurol. 20, 334–340. https://doi.org/10.4103/aian.AIAN_107_17

Prince, M. J., De Rodriguez, J. L., Noriega, L., Lopez, A., Acosta, D., Albanese, E., … & Uwakwa, R. (2008). The 10/66 Dementia Research Group’s fully operationalised DSM-IV dementia computerized diagnostic algorithm, compared with the 10/66 dementia algorithm and a clinician diagnosis: a population validation study. BMC public health, 8(1), 1-12. https://doi.org/10.1186/1471-2458-8-219

To date, we found no guidelines specifying any difference in diagnostic assessment according to geographical areas. However, the practice might differ according to availability of healthcare facilities.

No data was sourced due to a lack of data on dementia diagnosis rates and services in Jamaica.

There are no national or county guidelines in Kenya on dementia management, making clinicians to rely on the typical path described previously. In one of the counties (Makueni) in Kenya, clinicians were trained by the Africa Mental Health Foundation (NGO) using the mental health Global Action Programme (mhGAP) (World Health Organization, 2016) to identify and manage priority conditions such as dementia. However, due to limited mental health budget, it was not possible to roll-out the programme to all the counties in Kenya  (Mutiso, Gitonga, et al., 2018). This makes it difficult to identify any differences in assessment in the different regions.

References:

Mutiso, V. N., Gitonga, I., Musau, A., Musyimi, C. W., Nandoya, E., Rebello, T. J., … Ndetei, D. M. (2018). A step-wise community engagement and capacity building model prior to implementation of mhGAP-IG in a low-and middle-income country: a case study of Makueni County, Kenya. International Journal of Mental Health Systems, 12(1), 1–13. https://doi.org/10.1186/s13033-018-0234-y

World Health Organization. (2016). mhGAP Intervention Guide version 2.0. Geneva, Switzerland. https://www.who.int/publications/i/item/9789241549790

 

No data is available. However, as specialist doctors are scarce and those available work in the main metropolitan areas, we would expect smaller cities and rural areas to have even less people with access to a diagnostic assessment.

While access to diagnostic assessment in primary care is reasonably consistent throughout the country, there is a geographical difference in access to specialist memory service assessments for diagnosis and management of complex cases, with only seven of the 20 DHBs offering this dedicated service (Stone et al., 2019).

References:

Stone C., Copeland B., Collier C., Cheung G. (2019). Memory clinic survey in New Zealand: a second look. Australas Psychiatry. 27(5):486-90. https://doi.org/10.1177/1039856219852299.

As stated previously, there are no dementia-specific monitoring and surveillance data available in South Africa. However, medical attention (including diagnostic assessments) across geographical areas vary considerably, with access to healthcare services in both private and public sectors being concentrated to more urban areas (Competition Commission SA, 2018; Department Planning Monitoring and Evaluation, 2017; Mahlathi & Dlamini, 2015) (see Part 2 also). Furthermore, resources including specialist medical services are skewed to the private sector, accessible only to South Africans who can afford it, and usually of improved socio-economic status.

References:

Competition Commission SA. (2018). Health market injuiry. Available from:  http://www.compcom.co.za/wp-content/uploads/2018/07/Executive-Summary.pdf

Department Planning Monitoring and Evaluation. (2017). Socio-Economic Impact Assessment System (SEIAS) Final Impact Assessment (Phase 2): White Paper on National Health Insurance (Issue May).

Mahlathi, P., & Dlamini, J. (2015). MINIMUM DATA SETS FOR HUMAN RESOURCES FOR HEALTH AND THE SURGICAL WORKFORCE IN SOUTH AFRICA’S HEALTH SYSTEM: A rapid analysis of stock and migration. Available from: http://www.prographic.com/wp-content/uploads/2016/07/0316-south-africa-case-studies-web.pdf