Identifying Consumer’s Needs of Health Information Technology through an Innovative Participatory Design Approach among English- and Spanish-speaking Urban Older Adults

R. Lucero; B. Sheehan; P. Yen; O. Velez; D. Nobile-Hernandez; V. Tiase

doi:10.4338/ACI-2014-07-RA-0058

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2014; 05(04): 943-957
DOI: 10.4338/ACI-2014-07-RA-0058

Research Article

Schattauer GmbH

Identifying Consumer’s Needs of Health Information Technology through an Innovative Participatory Design Approach among English- and Spanish-speaking Urban Older Adults

R. Lucero

¹Columbia University, School of Nursing, New York, NY

,

B. Sheehan

¹Columbia University, School of Nursing, New York, NY

,

P. Yen

²The Ohio State University, College of Medicine, Biomedical Informatics, Columbus, OH

,

O. Velez

³IFC International, Rockville, MD

,

D. Nobile-Hernandez

⁴ARC XVI Fort Washington, New York, NY

,

V. Tiase

⁵NewYork-Presbyterian Hospital, Department of Information Technology, New York, NY 10032

› Author Affiliations

Abstract

Summary

Objectives: We describe an innovative community-centered participatory design approach, Consumer-centered Participatory Design (C²PD), and the results of applying C²PD to design and develop a web-based fall prevention system.

Methods: We conducted focus groups and design sessions with English- and Spanish-speaking community-dwelling older adults. Focus group data were summarized and used to inform the context of the design sessions. Descriptive content analysis methods were used to develop categorical descriptions of design session informant’s needs related to information technology.

Results: The C²PD approach enabled the assessment and identification of informant’s needs of health information technology (HIT) that informed the development of a falls prevention system. We learned that our informants needed a system that provides variation in functions/content; differentiates between actionable/non-actionable information/structures; and contains sensory cues that support wide-ranging and complex tasks in a varied, simple, and clear interface to facilitate self-management.

Conclusions: The C²PD approach provides community-based organizations, academic researchers, and commercial entities with a systematic theoretically informed approach to develop HIT innovations. Our community-centered participatory design approach focuses on consumer’s technology needs while taking into account core public health functions.

Citation: Lucero RJ, Sheehan B, Yen P-Y, Velez O, Nobile-Hernandez DL, Tiase VL. Identifying consumer’s needs of health hnformation technology through an innovative participatory design approach among English-and Spanish-speaking urban older adults. Appl Clin Inf 2014; 5: 943–957

http://dx.doi.org/10.4338/ACI-2014-07-RA-0058

Keywords

Consumer health information - medical informatics - health information management - community-based participatory research - personal health records

Full Text

References

References
1 Zickuhr K, Madden M. Older Adults and Internet Use. Washington, DC: Pew Research Center; 2012
2 Fox S. Health Topics. Washington, DC: Pew Research Center; 2011
3 Feil EG, Glasgow RE, Boles S, McKay HG. Who participates in Internet-based self-management programs? A study among novice computer users in a primary care setting. The Diabetes Educator 2000; 26: 806-811.
4 Brennan PF. Personal health information management systems. In: Saranto K, Brennan PF, Casey A. editors. 10th international nursing informatics congress. Helsinki: Kuopio University Library; 2009. p. 31-40.
5 Portnoy DB, Scott-Sheldon LA, Johnson BT, Carey MP. Computer-delivered interventions for health promotion and behavioral risk reduction: a meta-analysis of 75 randomized controlled trials, 1988–2007. Preventive Medicine 2008; 47: 3-16.
6 Kwon HS, Cho JH, Kim HS, Song BR, Ko SH, Lee JM, Kim SR, Chang SA, Kim HS, Cha BY, Lee KW, Son HY, Lee JH, Lee WC, Yoon KH. Establishment of blood glucose monitoring system using the internet. Diabetes Care 2004; 27: 478-483.
7 Cho JH, Chang SA, Kwon HS, Choi YH, Ko SH, Moon SD, Yoo SJ, Song KH, Son HS, Kim HS, Lee Wc, Cha BY, Son HY, Yoon KH. Long-term effect of the Internet-based glucose monitoring system on HbA1c reduction and glucose stability: a 30-month follow-up study for diabetes management with a ubiquitous medical care system. Diabetes Care 2006; 29: 2625-2631.
8 Levetan CS, Dawn KR, Robbins DC, Ratner RE. Impact of computer-generated personalized goals on HbA(1c). Diabetes Care 2002; 25: 2-8.
9 Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, Peters AL, Tsapas A, Wender R, Mathews DR. American Diabetes Association; European Assocation for the Study of Diabetes. Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care 2012; 35: 1364-1379.
10 Kenny RA, Rubenstein LZ, Tinetti ME, Brewer K, Cameron KA, Capezuti EA. Summary of the updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. Journal of the American Geriatrics Society 2011; 59: 148-157.
11 World Health Organization.. Assessment of Fracture Risk and Its Application to Screening for Postmenopausal Osteoporosis. Geneva: WHO Press,; 1994
12 Dykes PC, Carroll DL, Hurley A, Lipsitz S, Benoit A, Chang F, Meltzer S, Tsurikova R, Zuyov L, Middleton B. Fall prevention in acute care hospitals: a randomized trial. Journal of the American Medical Association 2010; 304: 1912-1912.
13 World Health Organization.. WHO Global Report on Falls Prevention in Older Age. Geneva: WHO Press,; 2007
14 Liang W, Liu Y, Weng X, Wang YC, Wang SP. An epidemiological study on injury of the community-dwelling elderly in Beijin. Chinese Journal of Disease Control and Prevention 2004; 8: 489-492.
15 Litao L, Shengyong W, Shong Y. A study on risk factors for falling down in elderly people of rural areas in Laizhou city. Chines Journal of Geriatrics 2002; 21: 370-372.
16 Liu S, Li J, Cheng Y, Mao AM, Hu XY, Shi H. Body function and fall related factors of the elderly in community. Journal of Nursing Science 2004; 19: 5-7.
17 Weiping M, Lihua Y. Analysis of risk factors for elderly falls. Chinese Journal of Behavioural Medical Science 2002; 11: 697-699.
18 Yoshida H, Kim H. Frequency of falls and their prevention. Journal of Clinical Calcium, 2006; 16: 1444-1450.
19 Reyes-Ortiz CA, Al Snih S, Markides KS. Falls among elderly persons in Latin America and the Caribbean and among elderly Mexican-Americans. Revista Panamericana de Salud Publica 2005; 17: 362-369.
20 U. S. Department of Health and Human Services. Healthy People 2010 final review. Washington, DC: U. S. Government Printing Office; 2012
21 Cummings SR, Kelsey JL, Nevitt MC, O’Dowd KJ. Epidemiology of osteoporosis and osteoporotic fractures. Epidemiologic Reviews 1985; 7: 178-208.
22 Mahoney JE, Palta M, Johnson J, Jalaluddin M, Gray S, Park S. Temporal association between hospitalization and rate of falls after discharge. Archives of Internal Medicine 2000; 160: 2788-2795.
23 Federal Interagency Forum on Aging-Related Statistics. Older Americans 2012: Key indicators of well-being. Washington, DC: U. S. Government Printing Office; 2012
24 File T. Computer and internet use in the United States. Washington, DC: U. S. Census Bureau; 2013. p. P20-568.
25 Zhang J, Patel VL, Johnson KA, Smith JW. Designing Human-Centered Distributed Information Systems. IEEE Intelligent Systems. 2002 September/October: 42-47.
26 Israel BA, Schulz AJ, Parker EA, Becker AB. Review of community-based research: assessing partnership approaches to improve public health. Annual Review of Public Health 1998; 19: 173-202.
27 Hatch J, Moss N, Sara A, Presley-Cantrell L, Mallory C. Community research: Partnership in Black communities. American Jouranl of Preventive Medicine 1993; 9: 27-31.
28 Eng E, Blanchard L. Action-oriented community diagnosis: A health education tool, 1990–91. International Quarterly of Community Health Eduction 2006; 26: 141-158.
29 Zhang J, Walji MF. TURF: Toward a unified framework of EHR usability. Journal of Biomedical Informatics 2011; 44: 1056-1067.
30 Hill KD, Schwarz JA, Kalogeropoulos AJ, Gibson SJ. Fear of falling revisited. Archives of Physical Medicine and Rehabilitation 1996; 77: 1025-1029.
31 Zhang J. Human-centered computing in health information systems, part 1: Analysis and design. Journal of Biomedical Informatics 2005; 38: 1-3.
32 Chipman SF, Schraagen JM, Shalin VL. Introduction to cognitive task analysis. In: Schraagen JM, Chip-man SF, Shalin VL. editors. Cognitive task analysis. Lawrence. Mahway, NJ: Erlbaum Associates, Inc.; 2000. p. 3-23.
33 Zhang JJ. A representational analysis of relational information displays. International Journal of Human-Computer Studies 1996; 45: 59-74.
34 Krippendorff K. Content analysis: An introduction to its methodology. London: Sage; 1980
35 Zhang J, Norman DA. Representations in distributed cognitive tasks. Cognitive Science 1994; 18: 87-122.
36 Blomberg J, Burrell M, Guest G. An ethnographic approach to design. In: Jacko JA, and Sears A. editors. The human-computer interaction handbook: Fundamentals, evolving technologies and emerging applications. Mahway, NJ: Lawrence Erlbaum Associates; 2003. p. 965-986.
37 Lustria MLA, Kazmer MM, Glueckauf RL, Hawkins RP, Randeree E, Rosario IB, McLaughlin C, Redmond S. Participatory design of a health informatics system for rural health practitioners and disadvantaged women. Journal of the American Society for Information Science and Technology 2010; 61: 2243-2243.
38 Siek KA, Khan DU, Ross SE, Haverhals LM, Meyers J, Cali SR. Designing a personal health application for older adults to manage medications: a comprehensive case study. Journal of Medical Systems 2011; 35: 1099-1121.
39 Siek KA, Ross SE, Khan DU, Haverhals LM, Cali SR, Meyers J. Colorado are tablet: the design of an inter-operable personal health application to help older adults with multimorbidity manage their medications. Journal of Biomedical Informatics 2010; 43: p. S22-S26.
40 Conklin J, Kothari A, Stolee P, Chambers L, Forbes D, Le Clair K. Knowledge-to-action processes in SHRTN collaborative communities of practice: A study protocol. Implementation Science 2011; 6: 12.
41 Welch JL, Siek KA, Connelly KH, Astroth KS, McManus MS, Scott L, Heo S, Kraus MA. Merging health literacy with computer technology: Self-managing diet and fluid intake among adult hemodialysis patients. Patient Education and Counseling 2010; 79: 192-198.
42 Alpay LL, Toussaint PJ, Ezendam NPM, Rovekamp TAJM, Graafmans WC, Westendorp RGJ. Easing Internet access of health information for elderly users. Health Informatics Journal 2004; 10: 185-194.
43 Hollan J, Hutchins E, Kirsh D. Distributed cognition: Toward a new foundation for human-computer interaction research. ACM Transactions on Computer-Human Interaction 2000; 7: 174-196.
44 Kolb DA. Experiential Learning. Englewood Cliffs, NJ: Prentice Hall; 1984
45 Wright PC, Fields RE, and Harrison MD. Analyzing human-computer interaction as distributed cognition: The resources model. Human-Computer Interaction 2000; 15: 1-41.
46 Carroll JM, Rosson MB. Participatory design in community informatics. Design Studies 2007; 28: 243-261.
47 Solomon G. Distributed cognitions: Psychological and educational considerations. Cambridge, United Kingdom: Cambridge University Press; 1996
48 Dearden A, Rizvi H. Parcipatory IT design and participatory development: A comparative review. In: PDC 2008 Conference Proceedings. Methods. Proceedings of the Tenth Anniversary Conference on Participa-tory Design. 2008. Oct 1–4; Bloomington, Indiana; USA: p. 81-91.
49 Bossen C, Christensen LR, Gronvall E, Vestergaard LS. CareCoor: Augmenting the coordination of cooperative home care work. International Journal of Medical Informatics 2013; 82: e189-e199.
50 Das A, Svanæs D. Human-centred methods in the design of an e-health solution for patients undergoing weight loss treatment. International Journal of Medical Informatics 2013; 82: 1075-1091.
51 Demirbilek O, Demirkan H. Universal product design involving elderly users: a participatory design model. Applied Ergonomics 2004; 35: 361-370.
52 Meiland FJM, Hattink BJ, Overmars-Marx T, de Boer ME, Jedlitschka A, Ebben PW. et al. Participation of end users in the design of assistive technology for people with mild to severe cognitive problem: the European Rosetta project. International Psychogeriatrics 2014; 26: 769-779.
53 Scandurra I, Sjolinder M. Participatory Design With Seniors: Design of Future Services and Iterative Refinements of Interactive eHealth Services for Old Citizens. Med 2.0 2013. 2: e12.
54 Ho MR, Smyth TN, Kam M, Dearden A. Human-computer interaction for development: The past, present, and future. Information Technologies and International Development 2009. 5: 1-18.
55 Shneiderman B. Leonardo’s laptop: Human needs and the new computing technologies. Cambridge, MA: MIT Press; 2002
56 Hochheiser H, Lazar J. HCI and societal issues: A framework for engagement. International Journal of Human-Computer Interaction 2007; 23: 339-374.
57 Zickuhr K, Smith A. Digital differences. Pew Research Center; Washington, DC: 2012
58 American Public Health Association [Internet]. Washington, DC: American Public Health Association; c2014. 10 essesntial public health services. Available from: http://www.apha.org/programs/standards/per formancestandardsprogram/resexxentialservices.htm