Brief communication
Seeking health information online: does limited healthcare access matter? Neeraj Bhandari,1 Yunfeng Shi,2 Kyoungrae Jung1 1
Department of Health Policy and Administration, College of Health and Human Development, The Pennsylvania State University, State College, Pennsylvania, USA 2 Center for Health Care and Policy Research, College of Health and Human Development, The Pennsylvania State University, State College, Pennsylvania, USA Correspondence to Neeraj Bhandari, Department of Health Policy and Administration, College of Health and Human Development, The Pennsylvania State University, 604 Ford Building, University Park, State College, Centre County, PA 16802, USA; [email protected] Received 10 September 2013 Revised 17 May 2014 Accepted 5 June 2014 Published Online First 19 June 2014
To cite: Bhandari N, Shi Y, Jung K. J Am Med Inform Assoc 2014;21:1113–1117.
ABSTRACT Consumers facing barriers to healthcare access may use online health information seeking and online communication with physicians, but the empirical relationship has not been sufficiently analyzed. Our study examines the association of barriers to healthcare access with consumers’ health-related information searching on the internet, use of health chat groups, and email communication with physicians, using data from 27 210 adults from the 2009 National Health Interview Survey. Individuals with financial barriers to healthcare access, difficulty getting timely appointments with doctors, and conflicts in scheduling during clinic hours are more likely to search for general health information online than those without these access barriers. Those unable to get timely appointments with physicians are more likely to participate in health chat groups and email physicians. The internet may offer a low-cost source of health information and could help meet the heightened demand for health-related information among those facing access barriers to care.
INTRODUCTION AND BACKGROUND Over the past two decades, the internet has become a widely available source of information,1 2 as well as a key component in clinical informatics, a rapidly growing field aimed at exploring and actualizing the potential of information and communication technology to improve health outcomes.3 One prominent example is the use of patient web portals that enable patients to access their health records, exchange emails with providers, complete administrative forms, receive appointment reminders, and manage medications.4 In the subfield of clinical research informatics, the internet has been used for the recruitment of human subjects in clinical trial research (eg, incorporating interactive informed consent programs for population subgroups with a wide range of learning abilities and skills).5 In a broader context, given its low cost and prevalence, the internet serves as an increasingly important channel for delivering health-related information to consumers, both in patient–physician interactions6–9 (eg, email exchanges) and in general health information searches (eg, health-related content on the internet). For consumers facing barriers to healthcare access, the internet can be a particularly appealing source of health information. The inability to afford needed medical care (eg, due to financial constraints) may prompt some individuals to seek health information from the internet. For example, Pew surveys of internet use indicate that nearly two-fifths of online health information seekers use the information to diagnose their conditions, and
Bhandari N, et al. J Am Med Inform Assoc 2014;21:1113–1117. doi:10.1136/amiajnl-2013-002350
nearly half of them perceive the information as useful in self-treating their symptoms without advice from healthcare professionals.1 Even among those who can and are willing to pay for care, there might be delays in getting needed care for various reasons (eg, long wait times for appointments, scheduling conflicts). In such cases, online health information and virtual communication with peers or providers may be useful. For example, patient web portals have been found to improve patient– provider interactions and increase patient convenience by allowing round-the-clock ability to send messages about perceived non-urgent concerns without visiting the clinic.4 Previous studies have examined the association between online health information seeking and factors correlated with healthcare access such as income, insurance coverage, and travel time to the source of healthcare.10 11 These studies found higher likelihoods of online health information seeking among those with higher income,10 those who had health insurance,11 and those with longer travel times.10 11 However, these factors may not fully capture the nature and extent of healthcare access barriers faced by consumers. For instance, consumers with insurance coverage face a varying level of access problems due to heterogeneity in cost-sharing and individual preferences. Moreover, studies have consistently reported that people in public insurance programs (eg, Medicaid) have difficulty finding physicians willing to take them as new patients,12 and experience longer wait times for appointments.13 On the other hand, consumers may choose to carry little or no insurance coverage simply because they are healthy and predict low or no care utilization. Similarly, in addition to consumers’ access to transport, travel time may reflect other factors such as rural residence rather than healthcare access.14 Furthermore, previous research has not examined how online health information seeking is associated with different types of access problems. For example, the ability to communicate with providers through emails (potentially using web portals) may be especially useful to those who have contact with providers but face certain (nonfinancial) access problems, such as difficulty in scheduling appointments. On the other hand, a general online information search may appeal to those with any type of access problem. Prior literature has not made this distinction. In this study, we examine how consumers’ online health information seeking behavior is related to different types of healthcare access barriers reported by individuals. We analyze three distinct aspects of online health information seeking: (1) general information searching on the internet (eg, 1113
Brief communication using search engines and browsing websites), (2) internet-based peer-to-peer communication ( participating in health chat groups), and (3) patient–physician communications (emailing physicians). Using a two-step analytic framework, we first examine the relationship between barriers to healthcare access and general online health information searching among the overall population, and then we examine the use of chat groups and email communication with care providers among health information searchers.
METHODS This study analyzes data from the National Health Interview Survey (NHIS) conducted in 2009. The NHIS is an annual survey using a nationally representative sample of the noninstitutionalized adult population of the USA, with oversampling of black, Hispanic, and Asian subjects. The survey collects
information on a broad range of health-related topics, including health-related uses of the internet, through in-person household interviews. The response rate was 82.2% at the household level and 65.4% at the individual level. We merged three NHIS data files for our analysis: the Sample Adult data file (demographic characteristics and health status of a randomly selected adult from each family), the Family data file (household level characteristics), and the Person data file (additional individual level characteristics, such as education and income). The final sample consists of 27 210 adults (18 years of age or older). A detailed description of the survey is available on the website of the Centers for Disease Control and Prevention.15 We examine three dependent variables in two steps. The dependent variable in the first step is a binary indicator of whether an individual used the internet to search for health information over the past 12 months (yes=1, no=0). The two
Table 1 Sample characteristics of respondents who used and did not use the internet for health information seeking (N=27 210)*
Variable Barriers to healthcare access† Having financial barriers Unable to contact via phone Unable to get a timely appointment Long wait at doctor’s office Unable to go to clinic when open No transport Self-rated health status Poor Excellent or very good Good or fair Have one or more chronic diseases Age (in years) 18–40 41–60 61–80 >80 Married Minority (non-white) Family income (US$)¶ 100 000 Family size ≤2 (ie, less than or equal to 2) >2 (ie, more than 2) College education Female Employed Have health insurance
Did not use the internet to seek health-related information N=15 601 (57.3%) Percentage
Used the internet for general health-information searching Overall N=11 609 (42.7%) Percentage
Used chat groups N=829 (3.0%) Percentage
Emailed physicians N=1076 (3.9%) Percentage
13.3 2.5 4.8 5.5 2.8 2.7
15.5‡ 3.3‡ 8.7‡ 5.5 4.9‡ 1.5‡
18.0§ 4.8§ 15.0§ 8.0§ 6.2 3.2§
14.4 4.6§ 13.1§ 6.1 6.6§ 1.4
17.0 53.5 29.5 51.3
8.3 68.4 23.3 49.8
14.3 62.4 23.4 51.5
10.3 66.6 23.1 55.9
36.2 34.1 23.0 6.7 57.3 21.3
47.0 39.4 13.1 0.5 66.4 15.2
51.3 36.5 11.5 0.8 64.5 20.2
39.9 44.8 14.7 0.6 69.2 13.5
40.4 30.7 9.4 12.1
20.2 31.8 14.0 28.7
24.5 30.0 11.7 28.4
12.6 26.4 14.1 42.3
54.0 46.0 40.4 46.6 51.8 77.9
50.9 49.1 77.0 57.8 69.8 87.1
50.2 49.8 77.5 62.5 64.0 85.7
55.1 44.9 87.9 57.5 72.6 92.6
*Weighted estimates derived from the National Health Interview Survey (NHIS) 2009, representative of the non-institutionalized adult population in the USA. †Pairwise Pearson correlations between healthcare access barriers are as follows: financial barriers–unable to contact via phone (0.09), financial barriers–unable to get a timely appointment (0.10), financial barriers–long wait at doctor’s office (0.07), financial barriers–unable to go to clinic when open (0.07), financial barriers–no transport (0.08), unable to contact via phone–unable to get a timely appointment (0.45), unable to contact via phone–long wait at doctor’s office (0.31), unable to contact via phone–unable to go to clinic when open (0.25), unable to contact via phone–no transport (0.18), unable to get a timely appointment–long wait at doctor’s office (0.37), unable to get a timely appointment–unable to go to clinic when open (0.33), unable to get a timely appointment–no transport (0.18), long wait at doctor’s office–unable to go to clinic when open (0.28), long wait at doctor’s office–no transport (0.19), and unable to go to clinic when open–no transport (0.18). All correlations are statistically significant at p
Seeking health information online: does limited healthcare access matter? Neeraj Bhandari,1 Yunfeng Shi,2 Kyoungrae Jung1 1
Department of Health Policy and Administration, College of Health and Human Development, The Pennsylvania State University, State College, Pennsylvania, USA 2 Center for Health Care and Policy Research, College of Health and Human Development, The Pennsylvania State University, State College, Pennsylvania, USA Correspondence to Neeraj Bhandari, Department of Health Policy and Administration, College of Health and Human Development, The Pennsylvania State University, 604 Ford Building, University Park, State College, Centre County, PA 16802, USA; [email protected] Received 10 September 2013 Revised 17 May 2014 Accepted 5 June 2014 Published Online First 19 June 2014
To cite: Bhandari N, Shi Y, Jung K. J Am Med Inform Assoc 2014;21:1113–1117.
ABSTRACT Consumers facing barriers to healthcare access may use online health information seeking and online communication with physicians, but the empirical relationship has not been sufficiently analyzed. Our study examines the association of barriers to healthcare access with consumers’ health-related information searching on the internet, use of health chat groups, and email communication with physicians, using data from 27 210 adults from the 2009 National Health Interview Survey. Individuals with financial barriers to healthcare access, difficulty getting timely appointments with doctors, and conflicts in scheduling during clinic hours are more likely to search for general health information online than those without these access barriers. Those unable to get timely appointments with physicians are more likely to participate in health chat groups and email physicians. The internet may offer a low-cost source of health information and could help meet the heightened demand for health-related information among those facing access barriers to care.
INTRODUCTION AND BACKGROUND Over the past two decades, the internet has become a widely available source of information,1 2 as well as a key component in clinical informatics, a rapidly growing field aimed at exploring and actualizing the potential of information and communication technology to improve health outcomes.3 One prominent example is the use of patient web portals that enable patients to access their health records, exchange emails with providers, complete administrative forms, receive appointment reminders, and manage medications.4 In the subfield of clinical research informatics, the internet has been used for the recruitment of human subjects in clinical trial research (eg, incorporating interactive informed consent programs for population subgroups with a wide range of learning abilities and skills).5 In a broader context, given its low cost and prevalence, the internet serves as an increasingly important channel for delivering health-related information to consumers, both in patient–physician interactions6–9 (eg, email exchanges) and in general health information searches (eg, health-related content on the internet). For consumers facing barriers to healthcare access, the internet can be a particularly appealing source of health information. The inability to afford needed medical care (eg, due to financial constraints) may prompt some individuals to seek health information from the internet. For example, Pew surveys of internet use indicate that nearly two-fifths of online health information seekers use the information to diagnose their conditions, and
Bhandari N, et al. J Am Med Inform Assoc 2014;21:1113–1117. doi:10.1136/amiajnl-2013-002350
nearly half of them perceive the information as useful in self-treating their symptoms without advice from healthcare professionals.1 Even among those who can and are willing to pay for care, there might be delays in getting needed care for various reasons (eg, long wait times for appointments, scheduling conflicts). In such cases, online health information and virtual communication with peers or providers may be useful. For example, patient web portals have been found to improve patient– provider interactions and increase patient convenience by allowing round-the-clock ability to send messages about perceived non-urgent concerns without visiting the clinic.4 Previous studies have examined the association between online health information seeking and factors correlated with healthcare access such as income, insurance coverage, and travel time to the source of healthcare.10 11 These studies found higher likelihoods of online health information seeking among those with higher income,10 those who had health insurance,11 and those with longer travel times.10 11 However, these factors may not fully capture the nature and extent of healthcare access barriers faced by consumers. For instance, consumers with insurance coverage face a varying level of access problems due to heterogeneity in cost-sharing and individual preferences. Moreover, studies have consistently reported that people in public insurance programs (eg, Medicaid) have difficulty finding physicians willing to take them as new patients,12 and experience longer wait times for appointments.13 On the other hand, consumers may choose to carry little or no insurance coverage simply because they are healthy and predict low or no care utilization. Similarly, in addition to consumers’ access to transport, travel time may reflect other factors such as rural residence rather than healthcare access.14 Furthermore, previous research has not examined how online health information seeking is associated with different types of access problems. For example, the ability to communicate with providers through emails (potentially using web portals) may be especially useful to those who have contact with providers but face certain (nonfinancial) access problems, such as difficulty in scheduling appointments. On the other hand, a general online information search may appeal to those with any type of access problem. Prior literature has not made this distinction. In this study, we examine how consumers’ online health information seeking behavior is related to different types of healthcare access barriers reported by individuals. We analyze three distinct aspects of online health information seeking: (1) general information searching on the internet (eg, 1113
Brief communication using search engines and browsing websites), (2) internet-based peer-to-peer communication ( participating in health chat groups), and (3) patient–physician communications (emailing physicians). Using a two-step analytic framework, we first examine the relationship between barriers to healthcare access and general online health information searching among the overall population, and then we examine the use of chat groups and email communication with care providers among health information searchers.
METHODS This study analyzes data from the National Health Interview Survey (NHIS) conducted in 2009. The NHIS is an annual survey using a nationally representative sample of the noninstitutionalized adult population of the USA, with oversampling of black, Hispanic, and Asian subjects. The survey collects
information on a broad range of health-related topics, including health-related uses of the internet, through in-person household interviews. The response rate was 82.2% at the household level and 65.4% at the individual level. We merged three NHIS data files for our analysis: the Sample Adult data file (demographic characteristics and health status of a randomly selected adult from each family), the Family data file (household level characteristics), and the Person data file (additional individual level characteristics, such as education and income). The final sample consists of 27 210 adults (18 years of age or older). A detailed description of the survey is available on the website of the Centers for Disease Control and Prevention.15 We examine three dependent variables in two steps. The dependent variable in the first step is a binary indicator of whether an individual used the internet to search for health information over the past 12 months (yes=1, no=0). The two
Table 1 Sample characteristics of respondents who used and did not use the internet for health information seeking (N=27 210)*
Variable Barriers to healthcare access† Having financial barriers Unable to contact via phone Unable to get a timely appointment Long wait at doctor’s office Unable to go to clinic when open No transport Self-rated health status Poor Excellent or very good Good or fair Have one or more chronic diseases Age (in years) 18–40 41–60 61–80 >80 Married Minority (non-white) Family income (US$)¶ 100 000 Family size ≤2 (ie, less than or equal to 2) >2 (ie, more than 2) College education Female Employed Have health insurance
Did not use the internet to seek health-related information N=15 601 (57.3%) Percentage
Used the internet for general health-information searching Overall N=11 609 (42.7%) Percentage
Used chat groups N=829 (3.0%) Percentage
Emailed physicians N=1076 (3.9%) Percentage
13.3 2.5 4.8 5.5 2.8 2.7
15.5‡ 3.3‡ 8.7‡ 5.5 4.9‡ 1.5‡
18.0§ 4.8§ 15.0§ 8.0§ 6.2 3.2§
14.4 4.6§ 13.1§ 6.1 6.6§ 1.4
17.0 53.5 29.5 51.3
8.3 68.4 23.3 49.8
14.3 62.4 23.4 51.5
10.3 66.6 23.1 55.9
36.2 34.1 23.0 6.7 57.3 21.3
47.0 39.4 13.1 0.5 66.4 15.2
51.3 36.5 11.5 0.8 64.5 20.2
39.9 44.8 14.7 0.6 69.2 13.5
40.4 30.7 9.4 12.1
20.2 31.8 14.0 28.7
24.5 30.0 11.7 28.4
12.6 26.4 14.1 42.3
54.0 46.0 40.4 46.6 51.8 77.9
50.9 49.1 77.0 57.8 69.8 87.1
50.2 49.8 77.5 62.5 64.0 85.7
55.1 44.9 87.9 57.5 72.6 92.6
*Weighted estimates derived from the National Health Interview Survey (NHIS) 2009, representative of the non-institutionalized adult population in the USA. †Pairwise Pearson correlations between healthcare access barriers are as follows: financial barriers–unable to contact via phone (0.09), financial barriers–unable to get a timely appointment (0.10), financial barriers–long wait at doctor’s office (0.07), financial barriers–unable to go to clinic when open (0.07), financial barriers–no transport (0.08), unable to contact via phone–unable to get a timely appointment (0.45), unable to contact via phone–long wait at doctor’s office (0.31), unable to contact via phone–unable to go to clinic when open (0.25), unable to contact via phone–no transport (0.18), unable to get a timely appointment–long wait at doctor’s office (0.37), unable to get a timely appointment–unable to go to clinic when open (0.33), unable to get a timely appointment–no transport (0.18), long wait at doctor’s office–unable to go to clinic when open (0.28), long wait at doctor’s office–no transport (0.19), and unable to go to clinic when open–no transport (0.18). All correlations are statistically significant at p
