In this study, patients using an electronic application focused on medications within a PHR had greater concordance between documented and patient-reported medication regimens and fewer unexplained discrepancies with potential for severe harm. There was no difference in the total number of preventable or ameliorable ADEs or in the duration of ameliorable ADEs.
We believe that the PG Medications Module encouraged patients to review their medication regimen as displayed in the ambulatory EHR and note discrepancies, and it activated PCPs to update the medication list. The results of the survey suggest that it may also have led to discussions about medication adherence and potential side effects. The intervention seemed particularly effective at decreasing unexplained discrepancies with potential for severe harm, perhaps because these caught the attention of PCPs and led to action.
On the other hand, some intervention patients still experienced potentially harmful medication discrepancies (0.24 per patient in the intervention arm). That 71% of eligible patients submitted a medications eJournal suggests that it was generally well accepted, but further improvements in usability might have increased that rate. We know that PCPs and practice staff did not open medications eJournals in 23% of cases, and they may not have accurately documented all they discussed with patients. Practices were expected to use the module when they signed up for the Prepare for Care study, but this decision was made by practice leaders with variable buy-in from individual providers. PCPs were trained in the use of the module and were encouraged to use it, but in the end, use was left to provider discretion. The module was designed to integrate with provider workflow (eg, automatically appearing instead of the usual medications screen when an eJournal had been submitted), but apparently some PCPs never opened a medications screen at all during some visits (eg, only opening the note-writing screen and importing the medication list into their note). Also, to our knowledge, the module was rarely used by other practice staff.
We were not surprised that the total number of preventable ADEs did not differ in the two study arms. Only a small number of ADEs were judged to be completely preventable (1.5% of all ADEs in this study), and causes are often multifactorial, requiring multi-faceted interventions. More feasible is decreasing the duration of ameliorable ADEs, but because only a proportion of ADEs in this study were ameliorable (58%), the study was likely under-powered to detect a difference.
Most EHR-connected PHRs facilitate patient–provider communication, completion of administrative tasks, and sharing of portions of the EHR with patients. Studies of such PHRs have shown effects on patient–physician collaboration18
and patient access to care.19
Studies of other interventions of ambulatory medication safety have focused on pharmacist interventions and mostly provider-centric health information technology (HIT) tools such as e-prescribing.20
To our knowledge, this study is one of the few examples of a patient-centric HIT tool focused on improving medication safety and one of the only successful ones.
This study has several limitations. First, it should be emphasized that this was an on-treatment analysis that evaluated a small proportion of patients compared with the over 120 000 patients theoretically eligible to participate in this study. To estimate the effect in all patients, the 9% absolute difference in the discordance rate should at least be multiplied by the 71% adherence rate (those who actually submitted a medications eJournal), that is, 6.4%. Because adherence might be less among the 82% of patients who had a PG account but chose not to participate in the study, the actual effect size would likely be smaller than that. Finally, this intervention was only effective among active PG users. At the time of the study, the rate of PG use was 18%. As of March 2011, with marketing and time, the rate was 35% and continues to increase.
This study has several other limitations. As suggested above, the low enrollment rate in PG in general and with this study in particular limits the generalizability of the findings, perhaps to particularly motivated early adopters of technology. The large number of people who did not participate in the medications sub-study also limits generalizability, although at least differences between participants and non-participants were similar in the two study arms. Second, this study was conducted in one medical system using internally developed software. However, the 11 primary care practices in this study had considerable heterogeneity, and such technology could be adopted by other EHRs that have associated PHRs. Third, as noted above, the sample size of the medications sub-study was small and had limited power to detect clinically important differences in some secondary outcomes. Fourth, we did not compare patient-reported medication regimens or documented regimens to a gold standard, that is, what a patient's providers collectively think the patient should be taking. This regimen does not usually exist anywhere and would require interviews with all providers (ideally, simultaneously) at the time of data collection.
Finally, there is no ideal comparison group to the patients in the intervention arm. On the one hand, a comparison of patients who submitted eJournals in both arms adjusts for potential confounding due to factors that lead to eJournal submission in general, such as comfort with technology and willingness to communicate asynchronously with providers. However, the reasons why a patient may submit a medications eJournal are likely different than the reasons why a patient may submit an eJournal about family history or health maintenance. Specifically, patients who submit a medications eJournal are prescribed more medications than those who do not, and they may be more likely to have potentially harmful medication discrepancies, an effect not seen among those offered a health maintenance eJournal. This is why we instead chose to match patients based on visit date, visit type, and comparable practice. In the secondary analysis of eJournal submitters only, the effects of the intervention on medication discordance were virtually identical to the main effects; the loss of statistical significance in discrepancies with potential for severe harm may reflect the difference described above between eJournal submitters and non-submitters in the different study arms, a loss of statistical power, unmeasured confounding, or a combination of these factors.
Future work is needed to increase patient enrollment in PHRs and to close the well-documented ‘digital divide’ between users and non-users of HIT.22
Improvements to the design of the patient side of the application might further increase submission of eJournals. Further work is also needed to better integrate the Medications Module with provider workflow, perhaps with further improvements to the PCP side of the application (eg, prompting review of the module from the EMR notes screen) and through changes in practice design (eg, team-based care in which other clinical staff members review medications eJournal information with patients prior to final vetting of the information by PCPs). Issues of provider expectations, training, and buy-in would also need to be addressed to maximize the effectiveness of the intervention. From a research standpoint, larger studies conducted in various healthcare systems and using multiple EHR/PHR platforms would establish the role of this kind of technology with greater generalizability.
In conclusion, when used, an interactive tool within a PHR focused on medications was able to decrease the discordance of documented and patient-reported medication regimens and reduce discrepancies with potential for severe harm. This technology shows promise, and further studies should be conducted integrating this kind of tool into other EHR platforms and evaluating its effects on medication safety.