Health Tracking and Information Sharing in the Patient-Centered Era: A Health Information National Trends Survey (HINTS) Study

Abstract

We examined the current state of digital health tracking and information sharing with health professionals among patients with chronic conditions using data from the National Cancer Institute’s 2018 Health Information National Trends Survey (HINTS). Descriptive statistics were used to examine the characteristics of health tracking and information sharing, Chi-squared tests were used to compare across groups, and multivariate logistic regression models were used to control for covariates. Between 17.4-37.6% of respondents reported sharing information with a health professional through either e-mail, monitoring device, text message, or online medical record message. There were sociodemographic differences across health tracking and information sharing modalities, and patients with chronic conditions disproportionately lacked Internet access, a basic cell phone, smartphone, or tablet compared to those without chronic conditions (p<0.05). This suggests there are sociodemographic and technology-based disparities for health tracking and information sharing for patients with chronic conditions.

Introduction

There is growing use of mobile health (mHealth) technologies, including smartphones, apps, wearable devices, and remote monitoring devices, to capture health-related data. Given the near ubiquity of mobile phones, with 95% of U.S. adults owning a mobile phone and 77% owning a smartphone in 2018¹, digital approaches are a promising way for patients to monitor their health due to their portability and convenience. The ability for patients to access, track, and share health information also provides opportunities for caregivers and care teams to longitudinally monitor behaviors and for interacting with the health system. Sharing health information with the care team facilitates patient-centered care through increased awareness, improved communication, and the ability to capture and transmit patient-generated data to incorporate into clinical care². Further, the secondary use of patient-generated health data (PGHD) has been valuable in accelerating clinical, public health, and research insights^3-5.

There are a number of national initiatives that have set a high priority for promoting data access and sharing for patients. The Centers for Medicare & Medicaid Services Meaningful Use Program (recently renamed the Promoting Interoperability Program) requires eligible professionals and health systems to provide increasing amounts of data access to patients, such as the ability to view, download, or transmit health information to a third party, and to use secure electronic messaging to communicate with health professionals (Stage 1 and 2)⁶. In 2019, patients must have access to their health information using a third-party app of choice through an Application Programming Interface (API)⁷. In February 2019, the Office of the National Coordinator for Health Information Technology also proposed a new rule to support individuals in the secure access, exchange, and use of their health information electronically⁸ to facilitate healthcare system adoption of APIs. This proposed rule discourages information blocking by healthcare systems, payers, and vendors as detailed in the 21^st Century Cures Act⁸. Progress has also been accelerated by the release of an API built on the Fast Healthcare Interoperability Resources (FHIR) standard by the Health Level Seven (HL7) International Argonaut Project⁹, which allows interoperability between electronic health records and apps, such as Apple HealthKit¹⁰. Additionally, the Centers for Medicare & Medicaid Services proposed policy changes to the MyHealthEData¹¹ and Blue Button 2.0¹² initiatives to improve access, data exchange, and care coordination for beneficiaries through APIs and trusted exchange networks¹³. Furthermore, research programs, such as the National Institutes of Health All of Us Research Program, which seeks to create a national research resource to study how individual differences in biology, environment, and lifestyle factors influence health, relies on individuals to share information about their health using APIs and other methods¹⁴.

Being able to leverage patient health data for clinical care relies on a patient’s access, ability, and willingness to collect and share digital data with health systems¹⁵. Several sociodemographic characteristics influence access and use of technologies, such as educational attainment, age, race/ethnicity, health status, and Internet access¹⁶. Understanding the characteristics that could influence digital health tracking and information sharing may allow health professionals to better understand who is likely to share PGHD and identify those who could benefit the most from sharing data. While not all patients will equally benefit from sharing PGHD (e.g., healthy individuals or those with a well-managed condition), data sharing may be particularly important for patients with chronic conditions as digital technologies can facilitate communication, real-time monitoring, or tailored coaching from the care team². Patients with one or more chronic conditions may also have a greater need for health tracking and sharing health information with healthcare professionals^17-20. While there is evidence that health tracking and data sharing may vary across sociodemographic factors, the latest HINTS survey data from 2018 allows the opportunity to extend prior research by expanding on how different communication modalities are associated with sociodemographic characteristics and chronic conditions^20,21. Thus, the objectives of this study were to: 1) describe the current state of health tracking and health information sharing across sociodemographic variables and the number of chronic conditions, and 2) examine the relationship of various modalities through which one can share health information with health professionals among patients with chronic conditions in a nationally representative sample.

Methods

Data were from the National Cancer Institute’s 2018 Health Information National Trends Survey (HINTS) 5 Cycle 2, administered January to May 2018²². HINTS is a survey administered to a nationally representative sample of U.S. adults to measure how individuals access and utilize health information²². Survey questions related to health tracking were selected from the larger survey data set including: 1) “Has your tablet or smartphone helped you track progress on a health-related goal such as quitting smoking, losing weight, or increasing physical activity?”; 2) “Other than a tablet or smartphone, have you used an electronic device to monitor or track your health within the last 12 months? Examples include Fitbit, blood glucose meters, and blood pressure monitors”; 3) “In the past 12 months, have you used your online medical record to download your health information to your computer or mobile device, such as a cell phone or tablet?”; 4) “How many times did you access your online medical record in the last 12 months?” For questions 1-3, responses included “Yes” or “No.” For question 4, responses included “0”, “1 to 2 times”, “3 to 5 times”, “6 to 9 times”, or “10 or more times”²². Survey questions related to health information sharing included the following: 1) “In the past 12 months, have you used a computer, smartphone, or other electronic means to e-mail or [use] the Internet to communicate with a doctor or a doctor’s office?”; 2) “Have you shared health information from either an electronic monitoring device or smartphone with a health professional within the last 12 months?”; 3) “Have you sent a text message to or received a text message from a doctor or other health care professional within the last 12 months?”; 4) “In the past 12 months, have you used your online medical record to securely message health care provider and staff (for example, e-mail)?” Response options for these health information sharing questions were: “Yes”, “No”, “Don’t Know”, or “Not applicable.” “Don’t Know” and “Not applicable” responses were categorized as “No”²². For chronic conditions, respondents were asked whether a healthcare professional had ever diagnosed them with the following: diabetes or high blood sugar; high blood pressure or hypertension; a heart condition such as a heart attack, angina, or congestive heart failure; chronic lung condition, asthma, emphysema, or chronic bronchitis; arthritis or rheumatism; depression or anxiety disorder; or cancer.

All analyses were conducted using survey weighting and jackknife variance estimations provided by HINTS to be nationally representative of the U.S. adult population²². All analyses were conducted using SAS (version 9.4, Cary, NC, U.S.). A variable was created for the number of conditions (0 conditions, 1-2 conditions, or 3+ conditions). Descriptive statistics were used to show the characteristics of health tracking and health information sharing. Chi-squared tests were used to compare across groups of patients with 0, 1-2, and 3 or more chronic conditions. To examine the relationship among patients with chronic condition(s) and various information sharing modalities, four multivariable logistic regression models were used to control for relevant covariates with each model estimating the information sharing modality (e-mail, text message, secure online medical record message, and electronic monitoring device). The multivariate models to estimate information sharing via e-mail, text message, and online medical record message only included respondents who had Internet access, at least a basic cell phone, or had ever been offered access to the medical record by a health care provider or health insurer respectively. In the model to estimate information sharing through an electronic monitoring device or smartphone, all respondents were included because there was no survey question that specifically asked about ownership of an electronic monitoring device or smartphone. All models were adjusted for the following covariates: gender, age, race/ethnicity, region, education, household income, occupation, marital status, time since most recent check-up visit, caregiver status, health insurance status, and chronic conditions.

Results

The final analytic sample was comprised of 2,439 respondents after excluding 1,065 respondents who had incomplete sociodemographic data. To compare differences between included and excluded cases, we conducted a bias analysis which showed that excluded respondents may have been less diverse than the general population and were more likely to be older and female (p<0.05). The sample had 48.33% females and a mean age of 53.02 years with a SD of 19.01 years (see Table 1). Respondents were primarily Caucasian, less than 65 years old, resided in an urban location, completed some college or attained a college degree or more, had a household income over $75,000 per year, visited a doctor for a routine check-up within the past year, and had one or more chronic conditions. The majority of respondents (61.09%) accessed the Internet through multiple networks (e.g., Wi-Fi, cellular, etc.), but 12.25% reported that they did not have access to the Internet. Over half of participants (56.42%) had multiple electronic devices (e.g., smartphone, tablet, etc.). There were 3.60% of respondents that reported that they did not have any electronic devices and 7.36% had only a basic cell phone. Age, race/ethnicity, education, income, occupation, time since most recent check-up visit, being a caregiver, having health insurance, Internet access, and electronic device use were associated with the number of chronic conditions (p<0.05).

Table 1.

Sample characteristics across chronic conditions¹

Characteristics (%)	Total Overall n=2,439	0 Chronic Conditions n=702	1-2 Chronic Conditions n=1,186	3+ Chronic Conditions n=551
Gender
Female	48.33	45.53	48.23	55.76
Male	51.67	54.47	51.77	44.24
Age
18-34	26.32	40.35**	21.56**	5.41**
35-49	28.67	32.72**	27.76**	21.22**
50-64	29.40	22.19**	33.56**	34.75**
65+	15.61	4.74**	17.12**	38.62**
Race/Ethnicity
Caucasian	65.37	59.26*	70.00*	66.52*
African American	10.53	10.26*	9.81*	13.44*
Hispanic	15.61	19.66*	12.49*	15.02*
Other	8.49	10.82*	7.70*	5.02*
Region
Urban	98.79	98.28	99.30	98.49
Rural	1.21	1.72	0.70	1.51
Education
High School or Less	28.59	26.37**	27.28**	38.34**
Some College	40.43	40.06**	40.49**	41.17**
College Degree or More	30.98	33.57**	32.23**	20.49**
Household Income
< $20,000	16.60	14.90**	14.54**	27.36**
$20,000 - $34,999	11.27	10.65**	9.20**	19.24**
$35,000 - $49,999	12.35	8.51**	14.57**	15.22**
$50,000 - $74,999	18.22	16.99**	19.91**	16.11**
> $75,000	41.56	48.95**	41.78**	22.07**
Occupation
Employed	61.29	70.66**	62.26**	34.34**
Unemployed	10.36	14.34**	6.92**	10.94**
Disabled	5.69	0.83**	5.40**	19.01**
Retired	16.12	5.40**	18.67**	35.48**
Other	6.54	8.77**	6.75**	0.23**
Marital Status
Single Married	46.0054.00	47.9352.07	42.9057.10	50.7749.23
Most Recent Check-up
Within the past year	64.26	51.59**	69.64**	79.74**
1-2 years	18.22	23.20**	15.37**	14.38**
3 years or more	17.52	25.21**	14.99**	5.88**
Caregiver (non-professional)
Yes	15.35	13.16*	15.47*	20.56*
No	84.65	86.84*	84.53*	79.44*
Health Insurance
Yes	91.25	86.86**	94.30**	92.91**
No	8.75	13.14**	5.70**	7.09**
Internet Access
Wi-Fi network only	14.63	13.80*	15.01*	15.54*
Cellular network only	3.98	4.43*	3.33*	4.79*
Broadband only	7.68	5.93*	8.74*	8.91*
Dial-up telephone line only	0.37	0.44*	0.15*	0.85*
Multiple Internet networks	61.09	65.85*	60.54*	50.70*
No Internet access	12.25	9.55*	12.23*	19.21*
Device Use
Smartphone only	28.04	28.14**	30.88**	18.90**
Tablet only	4.58	3.76**	4.46**	7.04**
Basic cell phone only	7.36	3.37**	6.58**	19.98**
Multiple devices	56.42	61.12**	55.08**	48.64**
No devices	3.60	3.61**	3.00**	5.44**

¹Chi-squared tests were conducted across the chronic disease groupings. *p < 0.05, **p < 0.01

Health Tracking and Health Information Sharing Characteristics. Health tracking and health information sharing proportions varied across respondents with 0, 1-2, and 3 or more chronic conditions (see Table 2). For health tracking, 43.16% of respondents used a smartphone or tablet to track progress on a health-related goal such as losing weight, quitting smoking, or increasing physical activity. Approximately 11% reported not having smartphone or tablet. Other than a smartphone or tablet, 36.74% of respondents used an electronic device, such as a blood pressure monitor, blood glucose meter, or Fitbit, to track their health within the past 12 months. In terms of accessing online medical records (OMR) at least once in the past 12 months, 31.67% of respondents indicated that they had done so, however only 17.35% downloaded it to a computer or mobile device. Using an electronic device, smartphone, or tablet to track health and accessing or downloading the OMR onto a computer or mobile device were associated with the number of chronic conditions (p<0.05).

Table 2.

Health tracking and information sharing characteristics across chronic conditions¹.

Characteristics (%)	Overall n=2,439	0 Chronic Conditions n=702	1-2 Chronic Conditions n=1,186	3+ Chronic Conditions n=551
Health Tracking
Used a smartphone or tablet to track health-related goal
Yes	43.16	47.67**	43.99**	29.09**
No	45.88	45.35**	46.43**	45.49**
Did not have smartphone/tablet	10.96	6.98**	9.58**	25.42**
Used an electronic device to track health2
Yes	36.74	29.95*	39.92*	44.14*
No	63.26	70.05*	60.08*	55.86*
Accessed Online Medical Record (OMR)2 0	21.71	20.25*	21.25*	26.88*
1-5	25.57	21.85*	29.20*	23.74*
6+	6.10	2.94*	8.05*	8.02*
Did not have access to OMR	46.62	54.96*	41.50*	41.36*
Downloaded OMR onto computer or mobile device2
Yes	17.35	11.76*	21.93*	17.30*
No	36.03	33.28*	36.57*	41.34*
Did not have access to OMR	46.62	54.96*	41.50*	41.36*
Health Information Sharing
Used e-mail or Internet to communicate with a health professional2
Yes	37.61	31.19**	43.95**	34.19**
No	50.14	59.26**	43.82**	46.60**
Did not have Internet access	12.25	9.55**	12.23**	19.21**
Sent or received a text message to/from a health professional2
Yes	30.73	26.15	33.91	33.22
No	65.67	70.24	63.14	62.03
Did not have a basic cell phone	3.60	3.61	2.95	4.75
Shared health information from an electronic monitoring device or smartphone with a health professional2
Yes	17.63	11.15**	20.29**	25.88**
No	82.37	88.85**	79.71**	74.12**
Messaged health professional through OMR2
Yes	17.35	11.76*	21.93*	17.30*
No	36.03	33.28*	36.57*	41.34*
Did not have access to OMR	46.62	54.96*	41.50*	41.36*

¹Chi-squared tests were conducted across the chronic disease groupings.

²Occured within the past 12 months

^*p < 0.05, **p < 0.01

For health information sharing, the most common modality for sharing was e-mail or via the Internet with 37.61% using e-mail or the Internet to communicate with a health professional within the past 12 months. 30.73% of respondents sent/received a text message to/from a health professional, but 3.60% did not have a basic cell phone. There were 17.63% of respondents who shared health information from an electronic monitoring device or smartphone with a health professional. While 17.35% sent a secure message to a health professional through their OMR, nearly half of participants (46.62%) did not have access to their OMR. E-mailing, secure messaging through the OMR, and sharing information from an electronic monitoring device were all associated with the number of chronic conditions (p<0.05).

Health Information Sharing Across Modalities. Sociodemographic characteristics of respondents varied across modalities of health information sharing through e-mail, text message, OMR message, or an electronic monitoring device/smartphone (see Table 3). Across all modalities, individuals with one or more chronic conditions had at least 1.50 or greater odds of sharing health information with a health professional compared to those without chronic conditions (p<0.05). Notably, respondents with three or more chronic conditions had 3.61 higher odds of sharing health information with an electronic device or smartphone with a health professional compared to those without chronic conditions (p<0.01).

Table 3.

Odds ratios (SE) of health information sharing across modalities during the past year.

Characteristics	E-mail or Internet1 n=2,087	Text Message2 n=2,341	OMR Message3 n=1,369	Electronic Device or Smartphone n=2,439
Gender (Referent: Female)
Male	0.71 (0.13)*	0.68 (0.18)*	0.97 (0.24)	0.81 (0.18)
Age (Referent: 18-34) 35-49	1.15 (0.24)	1.13 (0.23)	1.05 (0.34)	0.79 (0.29)
50-64	0.83 (0.21)	1.08 (0.22)	0.76 (0.29)	0.58 (0.27)*
65+	0.57 (0.28)*	0.82 (0.35)	0.75 (0.38)	0.80 (0.31)
Race/Ethnicity (Referent: Caucasian)
African American	1.02 (0.22)	0.90 (0.29)	1.12 (0.35)	1.83 (0.30)*
Hispanic	0.71 (0.22)	0.91 (0.20)	0.88 (0.28)	0.83 (0.26)
Other	1.65 (0.42)	1.33 (0.26)	1.09 (0.40)	1.17 (0.31)
Region (Referent: Urban)
Rural	0.97 (0.94)	1.10 (0.74)	1.51 (0.89)	0.95 (0.79)
Education (Referent: Some College)
High School or Less	0.73 (0.23)	0.68 (0.21)	0.93 (0.37)	0.72 (0.22)
College Degree or More	1.60 (0.17)**	1.26 (0.19)	1.25 (0.30)	0.91 (0.18)
Household Income (Referent: < $20,000)
$20,000 - $34,999	1.15 (0.33)	0.79 (0.50)	1.02 (0.78)	1.47 (0.30)
$35,000 - $49,999	1.23 (0.35)	0.94 (0.57)	0.74 (0.77)	1.23 (0.38)
$50,000 - $74,999	1.83 (0.45)	0.87 (0.57)	1.40 (0.87)	2.50 (0.35)**
< $75,000	3.49 (0.39)**	1.21 (0.60)	2.12 (0.89)	3.13 (0.38)**
Occupation (Referent: Employed)
Unemployed	0.90 (0.27)	0.79 (0.28)	0.89 (0.43)	0.47 (0.41)
Disabled	1.11 (0.40)	0.44 (0.37)*	0.72 (0.57)	0.85 (0.41)
Retired	0.94 (0.23)	0.65 (0.26)	0.69 (0.32)	0.72 (0.19)
Other	1.51 (0.69)	0.82 (0.57)	1.56 (1.16)	0.36 (0.69)
Marital Status (Referent: Married)
Single	0.92 (0.16)	0.72 (0.18)	1.18 (0.23)	1.00 (0.21)
Most Recent Check-up (Referent: Within the past year)
1-2 years	0.79 (0.27)	0.80 (0.20)	0.98 (0.32)	0.54 (0.25)*
3 years or more	0.48 (0.29)**	0.83 (0.24)	0.91 (0.48)	0.45 (0.35)*
Health Insurance (Referent: Yes)
No	1.02 (0.61)	0.41 (0.40)*	0.54 (0.66)	0.74 (0.51)
Caregiver (Referent: Yes)
No	0.87 (0.24)	0.77 (0.20)	0.95 (0.23)	0.71 (0.24)
Chronic Conditions (Referent: 0 conditions)
1-2	2.16 (0.20)**	1.50 (0.16)*	2.12 (0.30)*	2.11 (0.22)**
3+	2.32 (0.26)**	2.05 (0.19)**	2.13 (0.37)*	3.61 (0.29)**

¹Among respondents with Internet access

²Among respondents with at least a basic cell phone

³Among respondents who have ever been offered online access to their medical records by a health care provider or health insurer

*p < 0.05, **p < 0.01

Among respondents with Internet access, those who were male, 65 years and older, or had their most recent check-up three or more years ago had lower odds of e-mailing a health professional. Those who had at least a college degree, household income >$75,000, or had more than one chronic condition had higher odds of e-mailing a health professional. For text messaging with a health professional, those who were male, disabled, or without health insurance had lower odds of texting, while those who had more than one chronic condition had higher odds of texting. In terms of using an OMR for messaging, those who had one or more chronic condition had greater odds of doing so than those without chronic conditions. For sharing information using electronic devices or smartphones, those who were 50-64 years old or those who had their most recent check-up greater than a year ago had lower odds of sharing. Those who were African American, made $50,000 or more, or had more than one chronic condition also had higher odds of sharing information.

Discussion

Principle Findings. Our overall findings confirm prior research about the characteristics of individuals who track and share their digital health information with health professionals and data sharing in the context of chronic conditions. While it is well established that individuals with chronic conditions are more likely to share health information due to increased healthcare system interactions^17-20, this research illustrates that there are disproportionate numbers of patients with chronic conditions without Internet access or a basic cell phone, smartphone, or tablet compared to patients with no chronic conditions. Not surprisingly, this suggests that ownership of electronic devices and the use of the Internet are key factors that limit digital health tracking and information sharing, and that there are disparities between those who may need it the most. We also found differences in health tracking behaviors for those who used a smartphone, tablet, monitoring device, and OMR across groups with no, 1-2, or 3 or more chronic conditions. The majority of respondents without a chronic condition reported using a smartphone or tablet (47.7%). A large proportion of those with three or more chronic conditions used an electronic monitoring device to track their health (44.1%). However, almost half (46.6%) of respondents reported they did not have access to their OMR, which aligns with findings from other studies^21,23. This suggests the need for healthcare systems and payers to promote greater access to OMRs across demographic groups, particularly those with chronic conditions who may need to track their health and share health information as part of managing their health.

Despite multiple national efforts in health data sharing targeted towards healthcare systems and payers, few patients (17.4-37.6% across data sharing variables) actually reported sharing data with a health professional within the past year. The most common modality for data sharing was via e-mail or the Internet, followed by text messaging, an electronic monitoring device or smartphone, and the OMR. Sociodemographic differences among respondents who reported sharing information across different technologies indicate that the digital divide still persists today, but may also potentially reflect patient preferences for different modes of data sharing as well. Our findings extend the current body of evidence by expanding upon how different communication modalities are associated with sociodemographic characteristics and chronic conditions^24-26. In our study, African Americans had almost twice the odds of sharing health information through an electronic monitoring device or smartphone compared to Caucasians. This may be due to a larger proportion of African Americans using their smartphone as their only access to the Internet. Surprisingly, being from a higher income household (>$75,000) did not increase the odds of sharing across all modalities as one might expect. Male respondents also had lower odds of sharing via e-mail/Internet or text messaging but not for sharing using OMR messaging or electronic device/smartphones. These findings suggest the need for health systems to be cognizant of the sociodemographic differences across data sharing modalities so that they may provide tailored support based upon patient preferences and comfort with using various technologies.

Advancements in digital technologies offer unique opportunities for patients to remotely monitor their health and to share these data to inform clinical decision-making. Data sharing could also be accelerated by mitigating infrastructure and technical barriers such as access to broadband Internet and providing technical support to patients to assist them with accessing and using technologies that facilitate tracking and data sharing. Efforts could include tailored patient training materials for various communication modalities, such as e-mail, personal health record, or text messaging since a patient’s preference and proficiency for using these may vary based upon sociodemographic attributes such as age, health literacy, or technology usage²⁷. Trustworthiness and privacy may also limit patients’ willingness to share data with health professionals, so transparent policies that are described in patient-friendly language could help improve patients’ understanding and comfort with data sharing.

Additionally, reimbursement and organizational policies could address barriers to access and information sharing. While much progress has been made to facilitate data sharing, continued efforts focusing on reimbursement, interoperability, and addressing health professionals’ concerns about information sharing will help to advance information sharing. Centers for Medicare & Medicaid Services has made progress in reimbursing health care professionals for communicating and monitoring patients from home with the introduction of three new CPT codes in the 2019 Physician Fee Schedule and Quality Payment Program²⁸. These new codes allow for reimbursement for 20 minutes or more of communication with the patient or caregiver per month, remote monitoring of physiological parameters (e.g., weight, blood pressure, pulse oximetry) with daily recordings or programmed alerts, and patient education and set-up of the devices²⁸. This new reimbursement landscape provides opportunities for enhanced patient-health professional communication, but it is vital to address health professional concerns such as effective use and monitoring of these new data streams^29-31. For example, providing meaningful visualizations and summarizations of the data as well as incentives to incorporate PGHD into routine clinical workflows could help with the use of these data in clinical care³¹. Since reimbursement is tied to patient experience through Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores³², there is also an increasing focus on improving patient satisfaction. Providing access to health tracking and information sharing modalities based on individual’s health or technology needs could improve the patient experience through enhancing communication and care management. In the current healthcare landscape, it is still challenging to operationalize the collection and exchange of digital data across healthcare systems for clinical care, quality, and research. The Office of the National Coordinator for Health Information Technology released a 2019 Interoperability Standards Advisory that updated standards for health data to encourage data exchange among patients and health professionals³³. However, as the U.S. healthcare system continues to shift towards value-based care, greater efforts to increase patient engagement with tracking and data sharing are necessary, and these should align with quality and payer measures.

Limitations. The HINTS survey is a cross-sectional survey, which does not allow for examining causal relationships between variables. The survey is self-reported and lacks variables that may be highly correlated with health tracking and information sharing, such as health literacy, patient activation or engagement, or sociocultural factors. The survey does not assess all the potential modalities of health tracking and communication such as non-electronic mediums (i.e., paper-pencil tracking) which could also be useful in managing conditions. Despite these limitations, this study contributes to health tracking and communication research by expanding upon how various communication modalities are associated with sociodemographic characteristics and chronic conditions in a nationally representative sample of U.S. adults.

Conclusions

Patient access to technologies that enable tracking and sharing of health information is important to facilitate personalized and collaborative care, particularly for patients with chronic conditions. Sociodemographic differences exist across health tracking behaviors and information sharing modalities. Access to the Internet, electronic devices, or smartphones is limited among patients with chronic conditions. Additionally, access to online medical records is still limited to all patients overall. As consumer health technologies become more sophisticated, additional research is needed to determine whether these further widen health disparities, particularly for patients with chronic conditions. Future research should also examine longitudinal trends in tracking health and information sharing as the context and needs of patients evolves over time, as well as their impact on health outcomes.