Uncovering the Drivers and Inhibitors of Mobile Health Information Services Usage in the United States

Dr. Arun RaiRegents’ Professor and Harkins Chair

Center for Process Innovation & CIS Department

Robinson College of BusinessGeorgia State University

Atlanta, U.S.A.E-mail: arunrai@gsu.edu

Web site: arunrai.us

3rd International Conference on Transforming Healthcare with IT 31st Aug.-1st Sep. 2012Hyderabad, India

Liwei ChenDoctoral Student

Center for Process InnovationRobinson College of Business, Georgia State University

Atlanta, U.S.A.E-mail: liwei.chen@eci.gsu.edu

Jessica PyeDoctoral Student

Center for Process InnovationRobinson College of Business, Georgia State University

Atlanta, U.S.A.E-mail:jessica.pye@eci.gsu.edu

Study Background

PurposeAdoption status of mHealth in the U.S.

Channel preference between in-person doctor visits and mHealth

What influences adoption and channel preference

ProcedureOnline survey assisted by a market research company

Pilot followed by a large scale study

1132 valid responses

Sample Characteristics

• AgeMean = 45 yrsRange: 18 – 86 years20% over 60 years

Balanced gender distribution

• Income38% < 25 K USD/year30%: >=25 K & <50K/year19%:>= 50K & <75K /year12%: >= 75 K/year

• Education1.6%: Below high school 18.6%: High school (12th std)30.4%: Some college, no degree13.6%: Associate’s degree25.3%: Bachelor’s degree10.5%: Advanced degree

Adoption of mHealth Services

Intention to Use mHealth Services

Mean = 4.09, s.d. = 2.02 Mean= 3.20, s.d.= 2.23

Usage Frequency of mHealth Services

Comparative Snapshot of Mobile Services Adoption

work

Coarse Framing of Channel Preference:In-Person Doctor Visit or mHealth?

Mean= 2.36, s.d.=1.83

Example Item: “My overall feeling is that…”

Digging Deeper into Channel Preference: Substitutes or Complements?Using mHealth as a substitute to doctor visits?

Using mHealth as a complement to doctor visits?

Example Item: • “I am willing to use mobile health services instead of doctor visits”.

Example Item: • “I am willing to use mobile health services in addition to doctor visits”.

47%67%

(I) Candidate Predictors: Health Conditions

Example Item: • “I feel I am…”.

Example Item: • “I feel vulnerable to severe chronic diseases in the next five years”.

Mean=5.29, s.d.=1.46 Mean=4.01, s.d.=2.02

Healthiness Vulnerability78.9% 60.8%

(II) Candidate Predictors : Innovativeness with IT/Mobile Services

Mobile IT innovativeness Usage Innovativeness of Mobile Service

Example Item: “If I heard about a new mobile service, I would look for ways to experiment with it”.

Index Measure: weighted sum of mobile services use, where the weight is

Mean= 21.85, s.d.= 10.06Mean= 4.18, s.d.= 1.93

Predicting Adoption: Intention to Use mHealth Services

Higher intention to use mhealth for those more innovative with IT. Intention becomes stronger for those who are also more vulnerable or more healthy.

Predicting Adoption: Frequency of mHealth Use

Greater frequency of mhealth use by those more innovative with IT. This increases for those who are also more vulnerable or more healthy.

Predicting Channel Preference: mHealth Use as a Substitute to In-Person Doctor Visits

Greater preference for mhealth as a substitute by those more innovative with IT. This increases for those who are also more vulnerable or more healthy.

Predicting Channel Preference: mHealth Use as a Complement to In-Person Doctor Visits

Greater preference for mhealth as a complement by those more innovative with IT. This increases for those who are also more vulnerable or more healthy.

Wrap-Up

mHealth diffusion: 38% initiated use; 19% @ regular use Preference (No surprise): Much stronger preference for doctor visitsPreference (Surprise): 47% favorable to mHealth as a substitute; 67% favorable to mhealth as a complement Adoption/channel preference: Promoted by IT innovativeness and reinforced by health vulnerability and state of healthiness Practical implication: Differentiate mHealth on-boarding and progression strategies based on (i) IT innovativeness, (ii) health vulnerability, and (iii) state of healthiness; shift from coarse demographics to health and IT dispositions

Uncovering the Drivers and Inhibitors of Mobile Health Information Services Usage in the United States

3rd International Conference on Transforming Healthcare with IT 31st Aug.-1st Sep. 2012Hyderabad, India

Dr. Arun Raiarunrai@gsu.edu

Web site: arunrai.us

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