A systematic approach to equity assessment for digital health interventions: case example of mobile personal health records

Martin C Were; Chaitali Sinha; Caricia Catalani

doi:10.1093/jamia/ocz071

. 2019 Jun 12;26(8-9):884–890. doi: 10.1093/jamia/ocz071

A systematic approach to equity assessment for digital health interventions: case example of mobile personal health records

Martin C Were ^1,^✉, Chaitali Sinha ², Caricia Catalani ^3,⁴

PMCID: PMC7647229 PMID: 31188438

Abstract

Despite the increasing number of digital health interventions in low- and middle-income countries and other low-resource settings, little attention has been paid to systematically evaluating impacts of these interventions on health equity. In this article, we present a systematic approach for assessing equity impacts of digital health interventions modeled after the Health Equity Impact Assessment of the Ontario Ministry of Health and Long-Term Care. The assessment approach has 4 steps that address (1) scope, (2) potential equity impacts, (3) mitigation, (4) monitoring, and (5) dissemination strategies. The approach examines impacts on vulnerable and marginalized populations and considers various social determinants of health. Equity principles outlined by Whitehead and Dahlgren are used to ensure systematic considerations of all potential equity impacts. The digital health evaluation approach that is presented is applied to a case example of mobile personal health record application in Kenya.

Keywords: health equity, digital health, developing countries, personal health records

INTRODUCTION

Every human being has the right to enjoy the highest attainable standard of health.¹^,² The World Health Organization describes equity as “the absence of avoidable, unfair, or remediable differences among groups of people, whether those groups are defined socially, economically, demographically or geographically or by other means of stratification.”³ Moving toward more fair arrangements of services based on needs is a core objective of more equitable health services and systems.⁴ Digital health technologies, which include a range of eHealth and mobile health solutions, have the potential for both positive and negative impacts on health equity.⁵ When implemented without equity considerations, these interventions risk exacerbating existing inequities or creating new ones.⁶

The risk for negative equity impacts of digital health interventions is particularly relevant in rural and underserved areas within developed countries and in low- and middle-income countries (LMICs). LMICs tend to have populations that are more likely to be vulnerable across multiple dimensions and with numerous social determinants working against individual well-being. This intersectional reality of identities and experiences requires special attention on equity impacts of every digital health initiative,⁷ with clear determination made on whether the initiative widens or narrows health disparities and action taken to mitigate negative effects.

Despite the rapid growth in number and scope of digital health interventions in LMICs and other low-resource settings, a commensurate focus on systematically evaluating equity impacts of these interventions has been conspicuously absent. Digital health innovators, implementers, researchers, and decision makers need guidance on a rigorous yet practical approach for identifying, evaluating, and mitigating health equity issues that arise with each intervention. Unfortunately, a comprehensive approach or framework that guides equity evaluations for digital health interventions does not exist.

In this article, we provide a systematic approach for assessing equity impacts of digital health interventions and a stepwise approach for addressing identified issues. We use the case example of mobile personal health record (mPHRs) applications within an LMIC setting to demonstrate how the proposed approach can be applied.

APPROACH TO EQUITY EVALUATION FOR DIGITAL HEALTH INTERVENTIONS

Development of assessment approach

Two dominant methods to developing systematic evaluation approaches exist. One involves creating the approach from scratch informed by existing literature. An alternative approach involves adapting existing relevant approaches, toolkits, and frameworks to the area under evaluation. To develop the proposed approach for equity assessment for digital health interventions, we conducted an integrative literature review.⁸ MCW and CC searched for available English literature on 5 social and health databases including PubMed, Google Scholar, Social Sciences Citation Index, CINAHL, and Scopus, and in gray literature. These searches involved various combinations and permutations of the terms health equity framework/s, health equity toolkits, health equity systematic approach, health equity assessment, and health equity impact. MW and CC read and discussed all identified articles to reach a consensus on content relevant to informing the question at hand. Summation of the results revealed that the Health Equity Impact Assessment (HEIA), created by the Ontario Ministry of Health and Long-Term Care, was highly relevant and easily adaptable for equity impact assessment of digital health initiatives.⁹ The HEIA framework has already been used in a range of equity assessments.^10–13

The HEIA provides 5 steps to guide users through equity assessments, including addressing (1) scope, (2) impacts, (3) mitigation, (4) monitoring, and (5) dissemination strategies. While the HEIA tool is helpful in walking users through steps in identifying potential unintended positive and negative impacts of an intervention, it does not explicitly mention which dimensions of equity need to be evaluated. Users of the HEIA framework who are not familiar with all equity dimensions could inadvertently miss looking at those equity dimensions in their assessment.

To adapt the HEIA framework to the digital health landscape, our team underwent an iterative design and development process, elucidating key concepts and their definitions, and honing assessment prototypes. Where relevant, other appropriate sources, that were identified as part of the literature review, were used as part of the assessment tool development in addition to using the HEIA. The adapted HEIA steps for digital health equity assessments are outlined in Figure 1.

Figure 1. — The Digital Health Equity Assessment process, modified from Health Equity Impact Assessment.⁶

Scoping

The scoping step in digital intervention equity assessment requires the user to “identify affected populations or groups and potential unintended health impacts (positive or negative) on those groups.”⁹ A comprehensive scoping exercise encompasses broad consideration of impacts of the intervention on a wide range of vulnerable or marginalized groups (Supplementary Appendix A). This ensures that unintended equity impacts are not overlooked in these populations.

An additional step in the scoping exercise includes identification of all social determinants of health that need be considered alongside each identified relevant population. Determinants of health are “the range of personal, social, economic and environmental factors that determine the health status of individuals or populations.”¹⁴ These determinants include income and social status, personal health practices and coping skills, social support networks, early childhood development, education and literacy, biological and genetic endowment, employment and working conditions, health services, social environments, gender, physical environments, and culture.¹⁵ Social determinants interact with and impact digital health interventions with resultant equity implications.¹⁶^,¹⁷

Potential impacts

The next step in evaluating equity issues for any digital health intervention involves a systematic assessment of the interaction between the digital health technology and various equity dimensions. To identify these equity dimensions, we adapted the Principles for Policy Action by Whitehead and Dahlgren to directly apply them within the digital health equity assessment tool.⁴ The adapted equity dimensions are outlined in Table 1, with generic details of each dimension available in Whitehead and Dahlgren’s article.⁴ It is essential in any digital health equity assessment to look at how each of the listed dimensions are impacted by the digital health intervention and for each population identified in the scoping step.

Table 1.

Principles of equity relevant to digital health interventions

1) The digital health initiative should strive to level up, not level down.

2) Where appropriate, the digital health initiative should touch on the 3 main approaches to reducing social inequality:

Improve status of those who are disadvantaged
Narrow the health divide
Reduce social inequalities throughout the whole population

3) Digital health initiative should be built on the following equity principles:

Initiatives should not be driven by proﬁt, and patients should never be exploited for proﬁt.
Services should be provided according to need, not ability to pay.

4) Where appropriate, the digital health initiative should strive to provide primary health care to all.

5) Digital health initiative should tackle the fundamental social determinants of health.

6) Digital health initiative should provide voice to the voiceless.

7) Impacts of the digital health initiative should be evaluated separately for men and women.

8) Assessment of the health impacts of the digital health initiative should be done separately for differing race/ethnic, geographic, and socioeconomic communities.

9) The digital health initiative should facilitate equal access to services and ensure that particular communities/populations do not systematically pay more to access services than others.

Open in a new tab

Adapted from Whitehead and Dahlgren’s Concepts and Principles for Tackling Social Inequities in Health.³

Mitigation

Once equity impacts of the digital health intervention on identified groups are identified, evidence-based recommendations to minimize negative impacts and to maximize positive impacts should be developed and implemented. This step ensures negative equity impacts are not inadvertently perpetuated and avoids introduction new inequities.

Monitoring

The monitoring step involves determining how identified mitigation strategies will be monitored. This includes determining whether there was uptake of the recommendations for adjustment made as part of the mitigation strategy, with an additional process assessment to determine whether the assessment approach, as applied, was practical and appropriate for the digital health intervention under evaluation. The resulting monitoring data can then be fed back into refining the digital health intervention.

Dissemination

The dissemination step involves continuous sharing of lessons, results and recommendations for addressing equity issues for the digital health intervention to all relevant stakeholders across multiple channels. Dissemination should target end-users (including patients), care organizations, academic and civil societies, as well as policymakers, among others.

APPLICATION OF EQUITY ASSESSMENT APPROACH

The first step to applying the digital equity assessment tool above involves a clear understanding of the development and implementation details of the digital health initiative, including understanding details of the software application(s), database systems, implementation approaches and support, target populations, stakeholder involvement, and sustainability modeling. Equity assessments should ideally be performed at the earliest stage of the planning, development, or implementation process.

Supplementary Appendix B provides a practical workbook we developed to actualize the outlined assessment steps. Leveraging this workbook, each equity dimension is considered one at a time, with components within its row filled out in the matrix of cells to include project details and analysis of scope, impacts, mitigation strategies, monitoring, and dissemination. The workbook can be self-administered by organizations or used by an independent external party through a rapid assessment approach. Entries within each cell often require refinement as new information is gathered during assessment.

CASE EXAMPLE

The described digital equity evaluation assessment tool was used for an initial assessment and reflection for 5 digital health projects in a cohort funded by the International Development Research Centre.¹⁸^,¹⁹ The assessment was applied to each of the 5 projects to inform different aspects of the digital health intervention design, its governance, and how it meaningfully integrates into existing technical and social processes and systems.²⁰ In the following, we provide a different case example applying the assessment instrument to evaluate equity aspects of a digital health intervention in Kenya.

Case example: mPHR implementation in Kenya

Kenya overview

Kenya is a country in East Africa with a population of more than 50 million individuals and a 2.71% immigration rate.²¹^,²² There are over 40 tribal groups, including marginalized tribes and indigenous communities such as the Ogiek, Sengwer, Maasai, Samburu, El Molo, Turkana, Rendile, Gabra, and the Endorois.²³ Adult literacy rate in 2014 was 78.73%, with literacy rates being significant higher for men (83.78%) compared with women (74.01%).²⁴ In 2018, the country scored 0.700 on the Global Gender Gap Index, ranking 76th in the world.²⁵ The World Bank estimated that in 2015-2016, 35.6% of Kenyans were living below the poverty line (US$1.90 per day in 2011 Purchasing Power Parity),²⁶ with rates being higher in rural areas and in particular counties, especially those located in the northern parts of the country, namely Turkana, Marsabit, Mandera, and Wajir, where poverty rates were over 77%.²⁷ Smartphone penetrance in the country stands at about 26% in 2018,²⁸ with up to 51% of the population accessing the internet through various device types and connections.²⁹ Human immunodeficiency virus (HIV) prevalence was 5.9% in 2017, with rates as high as 15% in counties in the western part of the country, particularly Siaya, Kisumu, Homabay, Migori, Kisiii, and Nyamira counties.³⁰ Inequities are observed in access to HIV and antiretroviral treatment, especially affecting those in rural areas, students, and young population.³¹

Electronic health record systems

The Ministry of Health in Kenya has to date rolled out electronic health record systems (EHRs) at over 800 public health facilities to support HIV care, with the OpenMRS EHRs implemented at over 400 facilities (Figure 2).³²^,³³ With a growing need to improve patient access to their records and engagement in care, there has been consideration to implement a patient-targeted mPHR application tethered to the OpenMRS EHRs. The mPHR leverages increased use of internet-connected smartphones by patients in these settings.³⁴

Figure 2. — Electronic Medical Record Implementation sites for IQCare and KenyaEMR in 2019.

PHRs are “electronic applications used by patients to maintain and manage their health information in a private, secure, and confidential environment.”³⁵ Core features of the proposed mPHR application in Kenya include ability for patients to (1) self-monitor clinical parameters (eg, home blood sugars), (2) receive alerts and notifications (eg, on critical blood sugar levels), (3) receive educational materials, and (4) communicate securely with providers via text, audio and video (Figure 3). The mPHR application, with content in the English language, is to be downloaded by patients into their smartphones, with costs (eg, internet data bundles) borne by patient. Initial implementation of the mPHR will support patients with diabetes, hypertension and/or HIV.

Figure 3. — Architecture of mobile personal health record (mPHR) system tethered to electronic health records.

Equity analysis of mPHR implementation in Kenya

We applied the equity assessment in the planning stages of the mPHR project implementation in Kenya.

mPHR Scoping: Given the LMIC setting, the mPHR implementation will have potential equity impacts on several vulnerable populations, including indigenous communities, age-related groups (children, youths, seniors), disabled populations (eg, visually impaired), non–English-speaking groups, low-income individuals, remote populations without internet access, women living in a largely paternalistic culture, and populations with stigmatizing conditions such as HIV concerned with confidentiality. In developed countries, numerous studies have demonstrated differential uptake of patient portals where people with lower socioeconomic status, racial or ethnic minorities, older individuals, those with disabilities, and those with lower educational levels tend to have lower uptake of and adherence to use of patient portals.³⁶^,³⁷ Uptake and adherence of mPHR for these populations needs to also be considered in the Kenyan context. As such, relevant social determinants of health to be considered alongside these vulnerable populations include income and social status (affordability of smartphones), personal health practices affecting compliance with mPHR use, education and literacy levels, employment and working conditions impacting when and how mPHR is used, gender, and physical environments impacting access and safety of app use.

Potential Impacts: While the mPHR application promises to improve patient access to care services, it has a high risk of increasing inequity for patients who cannot afford smartphones or those without internet access. To this end, the mPHR solution can lead to particular populations being systematically disadvantaged and further marginalized leading to worsening of the health divide. Further, without appropriate checks, patient data gathered from the mPHR application risk being exploited for profit. The implementation also needs to balance a sustainability model (eg, charging for mPHR use) against making the application available for all. The mPHR has the potential to give voice to the voiceless, through improved patient education and self-management. If feedback and rating features are incorporated, the mPHR can enable patients’ views to be heard. It is important to evaluate mPHR usage patterns disaggregated by gender to uncover any concerns in a largely paternalistic implementation setting.

Mitigation: Having done a comprehensive equity scoping and impact evaluation of the mPHR application, it becomes evident that several mitigation strategies should be implemented at both development and implementation stages. To improve access for vulnerable populations, the mPHR can be designed to work with lower-end smartphones, and features such as SMS can be incorporated to provide some services for individuals without smartphones. Voice-enabled features, multilingual capabilities, support for multiple users, security to ensure confidentiality, and user-centered design can mitigate negative equity impacts while promoting positive ones. The mPHR application should be able to function in a fully offline mode, and approaches should be taken to minimize amount and cost of data, with strategies such as downloading items when WiFi access is available. Controls should be placed on secondary data use and on who has access to patient-level data. Further, end-user agreements should be comprehensive, with a focus on protecting patients’ interests.

Monitoring: Automatic monitoring mechanisms implemented as part of the mPHR implementation, including leveraging data analytics, can help monitor various equity impacts, such as access to services. Monitoring should include evaluating differences in use by patient characteristics, sex, and by social determinants of health. Other evaluation mechanisms such as use of qualitative approaches, including interviews with users, providers and decision makers should also be incorporated, to monitor equity impacts of the digital health intervention.

Dissemination: Lessons on equity impacts of the mPHR should be shared with patients, providers, managers, Ministry of Health (MoH), and other policymakers. Further, findings should be disseminated within relevant forums, such as workshops and academic forums. Positive lessons, including paradigm shifts around patient-data ownership can be incorporated into policies.

DISCUSSION

In this article, we describe a systematic approach to equity assessment of digital health interventions, with the goal of optimizing use of these interventions to improve the overall health of people with the greatest need. To achieve the intended goal, the described approach identifies vulnerable populations and decision-making processes surrounding digital health implementations, and provides guidance on how to successfully integrate digital technologies to maximize positive equity impacts, minimize negative impacts, garner support, and disseminate experiences. The work fills an existing gap by providing a practical approach for systematic and comprehensive evaluation of equity impacts of digital health interventions. It also brings to light the fact that developers and implementers of digital health interventions need to consider equity impacts of digital health intervention with as much attention as is often availed to health and health system strengthening impacts of the same interventions.

With an increasing number of initiatives that aim to guide practices for digital development and implementation, our approach provides a much-needed dimension often missing or underemphasized in these initiatives. The Principles for Digital Development provides 9 “‘living’ guidelines designed to help digital development practitioners integrate established best practices into technology-based programs.”³⁸ These guidelines, however, only mention equity and fairness in regards to co-creation, and could be expanded to consider equity dimensions more comprehensively. Another initiative, the World Health Organization’s Classification of Digital Health Interventions, aims to provide a shared language to describe the usage of digital health technology.³⁷ Unfortunately, there is no mention of equity or equity impacts of digital health technology in this classification system, and this only highlights the underemphasis of equity as a key component of any digital health interventions. Equity needs to be part of the shared language in discussing digital health interventions, and hence should be incorporated as a component in the classification system.

This work has a few limitations. First, the proposed approach focuses on providing guidance and recommendations to developer, implementers, and managers of systems, but with no explicit focus on supporting end-user groups. Second, this equity evaluation approach has, thus far, only been validated on 5 SEARCH projects.¹⁸

It is hoped that the described systematic approach for equity assessment of digital health interventions can help to shed more light on equity impacts of these systems and mitigate harm that can be caused by these interventions.

CONCLUSION

A systematic approach to equity assessments for digital health interventions can help in managing equity impacts of digital health interventions. The developed workbook provides a practical and easy-to-use tool to actualize equity assessments for digital health interventions.

FUNDING

The initial development of this equity assessment tool was funded by the International Development Research Centre Grant 106229-003.

AUTHOR CONTRIBUTORS

CS conceived the project, MCW and CC carried out the review and developed the assessment tool, with oversight and supervision by CS. MCW took the lead in writing the manuscript. All authors provided critical feedback and helped shape the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the International Development Research Centre or its Board of Governors.

SUPPLEMENTARY MATERIAL

Supplementary material is available at Journal of the American Medical Informatics Association online.

Supplementary Material

ocz071_Supplementary_Data

Click here for additional data file.^{(73.6KB, zip)}

ACKNOWLEDGMENTS

We would like to acknowledge the input of Professor Elizabeth Heitman in her guidance in this work.

CONFLICT OF INTEREST STATEMENT

None declared.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

ocz071_Supplementary_Data

Click here for additional data file.^{(73.6KB, zip)}

[ocz071-B1] 1. World Health Organization. Constitution of the World Health Organization. 1946. http://whqlibdoc.who.int/hist/official_records/constitution.pdf. Accessed January 8, 2019.

[ocz071-B2] 2. United Nations. Article 25 universal declaration of human rights. https://www.un.org/en/udhrbook/pdf/udhr_booklet_en_web.pdf. Accessed January 8, 2019.

[ocz071-B3] 3. World Health Organization. Health equity. https://www.who.int/topics/health_equity/en/. Accessed January 9, 2019.

[ocz071-B4] 4. WHO Collaborating Centre for Policy Research on Social Determinants of Health, Whitehead M, Dahlgren G. Concepts and principles for tackling social inequities in health: levelling up part 1. 2006. http://www.euro.who.int/__data/assets/pdf_file/0010/74737/E89383.pdf. Accessed January 9, 2019.

[ocz071-B5] 5. Veinot TC, Mitchell H, Ancker JS.. Good intentions are not enough: how informatics interventions can worsen inequality. J Am Med Inform Assoc 2018; 25 (8): 1080–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B6] 6. Sinha C, Schryer-Roy AM.. Digital health, gender and health equity: invisible imperatives. J Public Health (Oxf) 2018; 40 (suppl_2): ii1–5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B7] 7. Crenshaw K. Demarginalizing the intersection of race and sex: a black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum 1989: 139. [Google Scholar]

[ocz071-B8] 8. Pham MT, Rajić A, Greig JD, et al. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synth Methods 2014; 5 (4): 371–85. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B9] 9. Ontario Ministry of Health and Long-Term Care. Health Equity Impact Assessment (HEIA) workbook. Ontario; 2012. http://www.health.gov.on.ca/en/pro/programs/heia/docs/workbook.pdf. Accessed January 8, 2019.

[ocz071-B10] 10. Selick A, Lamoureux A, O’Connor K, Durbin J.. A survey of health equity practices in early psychosis intervention programs: a starting point for improvement. Healthc Policy 2017; 13 (2): 10–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B11] 11. Welch V, Petkovic J, Pardo Pardo J, Rader T, Tugwell P.. Interactive social media interventions to promote health equity: an overview of reviews. Health Promot Chronic Dis Prev Can 2016; 36 (4): 63–75. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B12] 12. Harris-Roxas B, Haigh F, Travaglia J, Kemp L.. Evaluating the impact of equity focused health impact assessment on health service planning: three case studies. BMC Health Serv Res 2014; 14: 371.. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B13] 13. Cooke M, Waite N, Cook K, et al. Incorporating sex, gender and vulnerable populations in a large multisite health research programme: the Ontario Pharmacy Evidence Network as a case study. Health Res Policy Syst 2017; 15 (1): 20.. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ocz071-B14] 14. Healthy People 2020. Determinants of health. https://www.healthypeople.gov/2020/about/foundation-health-measures/Determinants-of-Health. Accessed January 8, 2019.

[ocz071-B15] 15. Government of Canada. What determines health? Ottawa; 2011. http://www.phac-aspc.gc.ca/ph-sp/determinants/index-eng.php – key determinants. Accessed January 8, 2019.

[ocz071-B16] 16. Latulippe K, Hamel C, Giroux D.. Social health inequalities and eHealth: a literature review with qualitative synthesis of theoretical and empirical studies. J Med Internet Res 2017; 19 (4): e136.. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

A systematic approach to equity assessment for digital health interventions: case example of mobile personal health records

Martin C Were

Chaitali Sinha

Caricia Catalani

Abstract

INTRODUCTION