Impact of National Institutes of Health Gastrointestinal PROMIS Measures in Clinical Practice: Results of a Multicenter Controlled Trial.

OBJECTIVES: The National Institutes of Health (NIH) created the Patient Reported Outcomes Measurement Information System (PROMIS) to allow efficient, online measurement of patient-reported outcomes (PROs), but it remains untested whether PROMIS improves outcomes. Here, we aimed to compare the impact of gastrointestinal (GI) PROMIS measures vs. usual care on patient outcomes. METHODS: We performed a pragmatic clinical trial with an off-on study design alternating weekly between intervention (GI PROMIS) and control arms at one Veterans Affairs and three university-affiliated specialty clinics. Adults with GI symptoms were eligible. Intervention patients completed GI PROMIS symptom questionnaires on an e-portal 1 week before their visit; PROs were available for review by patients and their providers before and during the clinic visit. Usual care patients were managed according to customary practices. Our primary outcome was patient satisfaction as determined by the Consumer Assessment of Healthcare Providers and Systems questionnaire. Secondary outcomes included provider interpersonal skills (Doctors' Interpersonal Skills Questionnaire (DISQ)) and shared decision-making (9-item Shared Decision Making Questionnaire (SDM-Q-9)). RESULTS: There were 217 and 154 patients in the GI PROMIS and control arms, respectively. Patient satisfaction was similar between groups (P>0.05). Intervention patients had similar assessments of their providers' interpersonal skills (DISQ 89.4±11.7 vs. 89.8±16.0, P=0.79) and shared decision-making (SDM-Q-9 79.3±12.4 vs. 79.0±22.0, P=0.85) vs. CONCLUSIONS: This is the first controlled trial examining the impact of NIH PROMIS in clinical practice. One-time use of GI PROMIS did not improve patient satisfaction or assessment of provider interpersonal skills and shared decision-making. Future studies examining how to optimize PROs in clinical practice are encouraged before widespread adoption.

Computer versus physician identification of gastrointestinal alarm features.

OBJECTIVE: It is important for clinicians to inquire about "alarm features" as it may identify those at risk for organic disease and who require additional diagnostic workup. We developed a computer algorithm called Automated Evaluation of Gastrointestinal Symptoms (AEGIS) that systematically collects patient gastrointestinal (GI) symptoms and alarm features, and then "translates" the information into a history of present illness (HPI). Our study's objective was to compare the number of alarms documented by physicians during usual care vs. that collected by AEGIS. METHODS: We performed a cross-sectional study with a paired sample design among patients visiting adult GI clinics. Participants first received usual care by their physicians and then completed AEGIS. Each individual thus contributed both a physician-documented and computer-generated HPI. Blinded physician reviewers enumerated the positive alarm features (hematochezia, melena, hematemesis, unintentional weight loss, decreased appetite, and fevers) mentioned in each HPI. We compared the number of documented alarms within patient using the Wilcoxon signed-rank test. RESULTS: Seventy-five patients had both physician and AEGIS HPIs. AEGIS identified more patients with positive alarm features compared to physicians (53% vs. 27%; p<.001). AEGIS also documented more positive alarms (median 1, interquartile range [IQR] 0-2) vs. physicians (median 0, IQR 0-1; p<.001). Moreover, clinicians documented only 30% of the positive alarms self-reported by patients through AEGIS. CONCLUSIONS: Physicians documented less than one-third of red flags reported by patients through a computer algorithm. These data indicate that physicians may under report alarm features and that computerized "checklists" could complement standard HPIs to bolster clinical care.

Computer-generated vs. physician-documented history of present illness (HPI): results of a blinded comparison.

OBJECTIVES: Healthcare delivery now mandates shorter visits with higher documentation requirements, undermining the patient-provider interaction. To improve clinic visit efficiency, we developed a patient-provider portal that systematically collects patient symptoms using a computer algorithm called Automated Evaluation of Gastrointestinal Symptoms (AEGIS). AEGIS also automatically "translates" the patient report into a full narrative history of present illness (HPI). We aimed to compare the quality of computer-generated vs. physician-documented HPIs. METHODS: We performed a cross-sectional study with a paired sample design among individuals visiting outpatient adult gastrointestinal (GI) clinics for evaluation of active GI symptoms. Participants first underwent usual care and then subsequently completed AEGIS. Each individual thereby had both a physician-documented and a computer-generated HPI. Forty-eight blinded physicians assessed HPI quality across six domains using 5-point scales: (i) overall impression, (ii) thoroughness, (iii) usefulness, (iv) organization, (v) succinctness, and (vi) comprehensibility. We compared HPI scores within patient using a repeated measures model. RESULTS: Seventy-five patients had both computer-generated and physician-documented HPIs. The mean overall impression score for computer-generated HPIs was higher than physician HPIs (3.68 vs. 2.80; P<0.001), even after adjusting for physician and visit type, location, mode of transcription, and demographics. Computer-generated HPIs were also judged more complete (3.70 vs. 2.73; P<0.001), more useful (3.82 vs. 3.04; P<0.001), better organized (3.66 vs. 2.80; P<0.001), more succinct (3.55 vs. 3.17; P<0.001), and more comprehensible (3.66 vs. 2.97; P<0.001). CONCLUSIONS: Computer-generated HPIs were of higher overall quality, better organized, and more succinct, comprehensible, complete, and useful compared with HPIs written by physicians during usual care in GI clinics.

Open source tools in support of a multi-center prospective biomarker study in prostate cancer.

The open source software tools developed at UCLA are the informatics infrastructure supporting translational research efforts of the 11 National Cancer Institutes Prostate SPORE sites. The Codebook is a caBIG compliant application that manages PHI (e.g. names, medical record numbers, etc.) separately from research data. Research data are collected using a flexible clinical trials management suite called pTracker. Our poster will present how these two applications are implemented and function in this prospective multi-center study.