Interactive Preventive Health Record to Enhance Delivery of Recommended Care: A Randomized Trial

INTRODUCTION

Americans receive only one-half of recommended preventive services.¹ Among the various causes is poor access to reliable information. Patients need evidence-based information about what is recommended—tailored to their individual risk factors (eg, age, sex, combordities, prior testing, family history, health behaviors)—and presented in an understandable format.² They need reminders when services are due, guidance to deal with inconsistent recommendations, and access to decision aids for choices that require shared decision making.^3–5 To act on their choices, patients need written plans and logistical details.^6,7 Clinicians often lack time and resources to provide this information.⁸

One proposed solution is to harness the power of information technology, especially personal health records. For the purposes of this article, personal health records are broadly defined as health information systems used by patients, whereas electronic health records (EHRs) are systems primarily used by clinicians. The existing generation of personal health records can give patients direct access to the EHR of their clinician,^9,10 which is empowering, speeds access to results, and enables patients to discover inaccuracies in their medical record. The next generation of personal health records could offer higher functionality¹¹—assessing patients’ needs by applying the latest evidence-based guidelines and incorporating personal medical data to derive individualized recommendations. Taken further, they could link guidance with personalized evidence-based educational resources and decision aids, community services, logistical details, and reminder systems. Automating this process eases the burden on clinicians and moves much of the prevention process outside the confines of the clinical encounter.

There is, however, a shortage of objective evidence that personal health records can achieve these aims, improve outcomes, or even be used. Fewer than 3% of Americans have an electronic personal health record,¹² and most of these records lack the above-described functionality. Few are integrated into EHRs. The personal health records that are integrated often fail to explain content in lay language. Some offer preventive services recommendations but rely on simple age- and sex-based logic, ignoring other important risk factors.

We developed and tested a higher-functioning personal health record, called an interactive preventive health record (IPHR). The tool is an online, evidence-based, noncommercial patient portal with the capacity to interface with multiple EHRs and perform the above functions.

METHODS

We report a patient-level, randomized, nonblinded, controlled comparison of preventive services delivery for patients who were invited to use the IPHR compared with those who received usual care. The study was approved by the Virginia Commonwealth University Institutional Review Board.

RESULTS

Study Population

Control and intervention patients had similar demographic characteristics (Table 1). During the 66 weeks, 378 (16.8%) of 2,250 intervention patients established an account and received prevention recommendations (users) (Figure 1). Although more patients registered for the IPHR in the first 4 weeks after each mailing, patients continued to register up to 30 weeks after each mailing despite the absence of further prompts.

View this table:

• View inline
• View popup

Table 1

Characteristics of Intervention and Control Patients

• Download figure
• Open in new tab
• Download powerpoint

Figure 1

New interactive preventive health record (IPHR) users based on invitations mailed to patients.

Note: Number of patients who logged onto the IPHR, established an account, and received prevention recommendations. A total of 2,250 invitations were mailed (intervention population).

Nonusers were demographically similar to the control group. Users were older than nonusers (mean age 55.9 years vs 49.5 years, P <.001) and more likely to be male (55.8% vs 48.9%, P = .02), non-Hispanic (97.3% vs 93.1%, P = .02), and college educated (69.9% vs 62.8%, P = .03). Users also had more comorbidities (eg, 38.6% vs 26.1%, P <.001, with hypertension) and were more likely to be daily Internet users (80.7% vs 71.4%, P = .002) than nonusers.

The baseline patient survey response rate was 50.8%; the response rates for the 4-month and 16-month surveys were 46.5% and 48.9%, respectively. Control and intervention patients were equally likely to complete at least 1 survey questionnaire (69.9% vs 67.6%, P = .1), whereas users were more likely than nonusers to complete at least 1 survey questionnaire (89.7% vs 63.1%, P <.001).

DISCUSSION

Patients who were mailed an invitation to use the IPHR were more likely to be up-to-date on all indicated preventive services than were patients who received usual care. When IPHR users were compared with nonusers, the benefits appeared to be substantially greater. In fact, at 16 months, 1 in 4 users were up-to-date on all preventive services—nearly double that of nonusers. Attention to confounding variables is important, but a causal effect from the IPHR is further suggested by large increases in the delivery of specific preventive services for users, such as cancer screening and immunizations, compared with little or no increase in the control and nonuser groups.

The compelling health benefits established by the USPSTF for these preventive services suggests that the increased delivery rates observed in this study would have important implications for reducing morbidity and mortality. The specific services that exhibited the largest increase were those identified by the National Commission on Prevention Priorities as saving the most quality-adjusted life years if delivery were optimized.²⁰ The increased uptake of preventive services observed among users is consistent with the benefits observed for other interventions to promote delivery, such as reminders, self-management support, tailored education, clinician-community linkages, and practice redesign.^21–29 Interestingly, the services most likely to improve were screening tests and immunizations. Changes were not observed for health behavior counseling, even among users. Studies suggest that intensive support is needed to help patients modify lifestyle, something that technology alone is not currently able to accomplish.^30,31 We have previously reported that using technology to refer patients to community-based resources for intensive counseling is associated with a reduction in body mass index and smoking rates.³²

Although the findings of this study are encouraging, only 1 intention-to-treat analysis achieved statistical significance, and the magnitude of change was small. One factor was the small absolute number of IPHR users, which provided inadequate power to show changes in effectiveness outcomes for the entire intervention population. When conducting the power analysis for the study, we assumed, based on pilot work completed in 2004, that 50% of patients mailed an invitation would create an account. In that project, offices directed patients to an IPHR prototype when calling to schedule a wellness visit—78% of invited patients used the prototype. In the current study, however, promotion of the IPHR was more subtle. Invitations were mailed to random patients not associated with an upcoming visit. Practices did not promote the IPHR at visits and did not integrate the tool into routine activities. Subsequent focus groups with non-users found that many did not think the IPHR was intended for them, because they had recently been to the office and heard nothing about it, or they planned to use the IPHR before a visit at a future date.

Recent evidence, in which aggressive promotion of personal health records by 2 large health systems resulted in annual adoption by only 10% to 20% of patients, suggests that our adoption rate (16.8%) is favorable for promotion based on a simple mailed invitation.^33,34 Motivating even more patients to use a personal health record with advanced functionality may require practices to make major changes. To understand the value and relevance to care, patients may need information about the tool, how it works, and why it is important for them. This information is perhaps best explained during the course of multiple patient contacts and reinforced by all health care team members. Practices may need a wide range of resources and tools to inform patients of the new system, such as informational brochures, videos, and links on their practice website. These practice integrations may not be possible unless practices modify daily activities and workflow to include their personal health record. Our contention that a robust practice implementation is necessary for the adoption of the IPHR is a hypothesis we are actively exploring in our current studies.

This study has several important limitations. First, the Northern Virginia patients seen by the study sites were well educated, had high incomes, and were predominantly non-Hispanic whites. Whether findings in this setting would generalize to other populations is unknown. Second, the subgroup analysis, comparing users and nonusers, can be influenced by selection bias. Users were demographically different than nonusers (eg, fewer minorities and higher education), had more chronic illnesses, and were more up-to-date with care at baseline. They may have been more interested in receiving preventive services and may have had better access to care (eg, better health insurance) than non-users. Finally, users were more likely to complete the survey questionnaires than nonusers. Although these limitations are important, only data for diet, exercise, and weight loss counseling derived solely from survey responses; the delivery of all other services was measured with both EHR and survey data. Randomization would eliminate the selection bias for the intention-to-treat analysis. The disparity in baseline utilization rates was controlled by comparing before and after differences in preventive service delivery for users and nonusers. The high socioeconomic status of the study sites does warrant further research to determine whether similar benefits would be seen in other settings.

Increasingly, patient-centered information systems are recommended as an essential tool to improve the delivery of care and health.^28,35–38 The functionality of many systems is lacking, however, and there is insufficient evidence to show that they can support their intended use. This study shows that the IPHR and similar systems can improve important patient outcomes, such as the delivery of evidence-based preventive care. To have a broad impact on public health, attention is needed to ensure that future personal health records can deliver higher levels of functionality, similar to the IPHR, and that a greater proportion of patients and clinicians actively use the systems.

To learn how to use your personal health record for prevention, A How-To Guide for Using Patient-Centered Personal Health Records to Promote Prevention, from the Agency for Healthcare Research and Quality, is available at http://healthit.ahrq.gov/KRIST-IPHR-Guide-0612.pdf.