The overall objective of this proposal is to test version 3.0 of the Arthritis smartphone app in a 12-month interrupted time series analysis (ITSA) design which will allow us to observe possible differences in visit frequency between the pre-and post-intervention periods as well as between the concurrent control group and those who receive the app. Our central hypothesis is that introduction of the app will reduce visit numbers per month in the group receiving the app, compared with a concurrent control group.

Aim 1: To integrate an app for PsA into the EHR. In current work, user-centered design helped develop an EHR integrated PRO-based app for RA. The roll out of the app has been successful and the investigators now want to expand to focus on integration of a similar app for PsA. The app will use similar PROs, adding in a patient global VAS, as well as a brief psoriasis symptom checklist. The PROMIS Function Short Form, PROMIS Fatigue Short Form, PROMIS Pain Short Form, and the PsAID-12 will be assessed. As well, the Q&A function will be modified to focus on PsA, allowing one to monitor symptom changes for patients using various PsA treatments, focusing on guselkumab, infliximab, golimumab, and ustekinumab. Aim 1 is required for the app testing in Aim 2.

Aim 2: To conduct a single arm interrupted time series of the EHR-integrated PRO app for PsA to assess whether it improves the timeliness of care. After integrating the app into the EHR, the investigators will recruit 100 patients who use one of the following agents: guselkumab, infliximab, golimumab, or ustekinumab. The goal will be to determine whether the app improves visit timeliness. Timeliness will be defined as an increase in the percent of visits with therapeutic changes over a 9-month trial period. A secondary outcome will assess PROs and visit satisfaction. The app allows patients to remotely transmit PRO data to their care team. Patients with very active disease between visits may consider a visit earlier than scheduled. The investigators hypothesize that during the intervention period with app use, patients will experience improved timeliness of PsA care when compared with the 9 months prior to the app use, while maintaining patient-reported clinical outcomes.

Data collection will occur via three methods. First, RA/PsA patients will provide answers to the survey questions through the app on their smartphones or tablets and the ePRO data can be viewed in an administrative dashboard. Second, the app will push an in-basket message to rheumatologists letting them know 1 week before a patient visit that there are ePRO data in Epic to be viewed. If symptoms reach a threshold suggesting poor disease control, then prior to 1 week before the visit the app will send an in-basket message to the rheumatologists letting them know to review patient data to consider an earlier visit. On the other hand, if the ePRO data suggests stable symptoms, the app will push an in-basket message to the rheumatologist 1 week before the next patient visit suggesting that the rheumatologist could consider delaying the visit. The rheumatologist can respond as they see fit or not at all. The last data collection will occur at the end of study when a satisfaction survey will be completed through REDcap electronic consent.

Analysis: The investigators anticipate near complete data, based on our prior studies. However, the investigators will impute missing values using standard imputation methods. Baseline characteristics of enrolled patients will be examined, assessing how well the recruited patients reflect a typical PsA population. The investigators will then examine the distribution of the visit timeliness (primary outcome) across the two time periods (pre and post app). Monthly percentage of visits that qualify as timely will be estimated across the study population. This allows us to assess the slopes during the two time periods. The investigators hypothesize improved timeliness of visits in the 9 months after starting to use the app compared with the pre-app 9 months. Thus, the primary analysis is a comparison of slopes. With respect to the secondary outcomes, the investigators will calculate the change from baseline to 9 months for each of the PROs. The distribution of PROs is typically normal. The investigators will compare baseline to ending values for each PRO using an ANCOVA. with an indicator term for rheumatologist. The investigators hypothesize that during this 9-month study the change in PROs will be within the minimally clinically important difference (i.e., no change).

Inclusion Criteria:

• Be diagnosed with PsA by a board-certified rheumatologist and been seen at least twice in the prior year
• Own a smartphone with either an Android or iPhone operating system
• Be at least 18 years old
• Be English-speaking
• Using guselkumab, infliximab, golimumab or ustekinumab

Exclusion Criteria:

• Patients who do not plan on receiving follow-up care at the Brigham and Women's Arthritis Center will be excluded.

A matched control group will be enrolled from medical records. The data analyst will be blinded to the treatment assignment (i.e., app intervention or matched controls)