Patients are taking an increasingly active role in their own healthcare delivery. This article describes an influenza management tool as a model for patient-targeted decision-support applications that can be delivered through a patient portal. The Flu Tool is designed to empower patient decision making in several ways. First, by being accessible through a patient portal, the tool's use is patient-initiated and patient-driven. Second, the questions and algorithms included in the triage system are designed to educate patients about the most likely cause of their symptoms. Third, for patients requiring escalation of care, the system design provides specific tools or guidance based on whether or not the patient's primary care services are accessible by the patient portal. For those cases where patients meet criteria for receiving treatment with an antiviral medication and can communicate with providers through a patient portal, treatment can be initiated quickly without a clinic visit.
The Flu Tool was fully deployed during the 2010–2011 influenza season, with limited integration into the MHAV patient portal. Although the Flu Tool was widely used, with its limited integration, it did not take advantage of the connections to the EHR or the integrated patient-provider messaging capabilities unique to a patient portal. We believe that the usage was sufficient to demonstrate a willingness of healthcare consumers to consult patient-targeted decision support; Flu Tool was used four times more often than the number of patients diagnosed with influenza during an inpatient or outpatient clinical encounter at VUMC. The Flu Tool was implemented during the local influenza spike, so there was not much lead-in time to advertise to patients (ie, potential users), and the fact that implementation excluded the messaging integration may have limited usage.
The deployed version did include patient-targeted decision-support algorithms and educational materials, and it provided the patient with general advice about whether they should escalate their level of care, such as whether they needed to see a healthcare provider immediately. Our usage data inform institutional clinical leaders what type of support would be necessary to release a fully integrated version of Flu Tool in MHAV. With full integration, all Flu Tool-initiated messages could be audited in real time to ensure that messages requiring immediate follow-up were addressed in a timely manner. With this service available, it may be possible to allow urgent messaging at any hour or on any day, irrespective of usual business hours. Anecdotal reports from the institutional leadership suggest that the Flu Tool and other patient-targeted decision-support tools have convinced them to consider full 24 h nurse call backup.
The model underlying the Flu Tool can serve as a template and can inform a set of workflows that would support any number of patient-targeted decision-support tools. While the contents and the specific algorithms might change, the infrastructure, policies and procedures should be constant and reusable across the institution, and may generalize to other clinical sites and institutions. By contrast, while the Flu Tool implementation was designed to respect existing workflows, institutional leadership took a relatively conservative view of potential patient risk. As a result, they requested that workflow and staffing results be changed (at some future point) to include 24 h/7 day nursing triage before integration of the Flu Tool with messaging.
As patient portals become more prevalent in settings of healthcare delivery, it will be important to measure their influence on patient-driven decision making. A more complete rollout of the Flu Tool and other portal-based patient-targeted decision-support systems will need to incorporate plans for system evaluation. Investigators have previously posited research agendas for patient portals,108
including evaluations of adoption, architecture, privacy and security, and their use for managing populations of patients. The limited implementation in the 2010–2011 influenza season reduced our ability to perform a formal evaluation. In the current form and during the recent 9-week implementation, the Flu Tool likely had an unmeasurable impact on healthcare utilization. With a deeper and longer implementation that includes links to the MHAV messaging system, it is possible that any impact on outcomes will be measurable. In a study evaluating this, we would likely assess a number of outcome variables, including: user demographics, patterns of algorithm recommendations, rates of MHAV users versus non-users seeking in-person care for influenza-like illness, and possibly rates of acute care and emergency department visits over several seasons. We would also hope to assess qualitative outcomes, including perceptions that patients and healthcare providers have about the Flu Tool and about patient-targeted decision support. It may also be possible to assess a series of quantitative outcomes using pre/post or time-series data obtained through queries of our institutional clinical data warehouse. This research agenda would align with those previously suggested for patient portals by other investigators.108