Data users (researchers, scientists) in healthcare institutions need access to integrated healthcare data to conduct timely analysis of diseases to serve the right population at the right time. However, preserving patient privacy and timely access to quality healthcare data is a critical challenge. Current healthcare data governance systems are largely manual. Besides, processing process data requests is extremely slow, often taking months. To address this gap, we designed an honest-broker-based healthcare application to support data users in accessing healthcare data securely and to design a comprehendible process of data governance for data users. This study applied two iterations of a user experience (UX) evaluation of an honest broker prototype. Results show that participants found the new system promising for their research prospects. Implications suggest that technological knowledge should not be a requirement for using healthcare applications to promote broader adoption in the community. This study highlights the necessity of a process to balance the control of access to sensitive data between data providers and users as well as to educate data users on data privacy. Iterative UX studies can be a fruitful approach in gradually uncovering problems and improving the design of complex systems.

OBJECTIVE: The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Networks capture healthcare utilization within their health systems. Here, we describe a reusable environment (GPC Reusable Observable Unified Study Environment [GROUSE]) that integrates hospital and electronic health records (EHRs) data with state-wide Medicare and Medicaid claims and assess how claims and clinical data complement each other to identify obesity and related comorbidities in a patient sample. MATERIALS AND METHODS: EHR, billing, and tumor registry data from 7 healthcare systems were integrated with Center for Medicare (2011-2016) and Medicaid (2011-2012) services insurance claims to create deidentified databases in Informatics for Integrating Biology & the Bedside and PCORnet Common Data Model formats. We describe technical details of how this federally compliant, cloud-based data environment was built. As a use case, trends in obesity rates for different age groups are reported, along with the relative contribution of claims and EHR data-to-data completeness and detecting common comorbidities. RESULTS: GROUSE contained 73 billion observations from 24 million unique patients (12.9 million Medicare; 13.9 million Medicaid; 6.6 million GPC patients) with 1 674 134 patients crosswalked and 983 450 patients with body mass index (BMI) linked to claims. Diagnosis codes from EHR and claims sources underreport obesity by 2.56 times compared with body mass index measures. However, common comorbidities such as diabetes and sleep apnea diagnoses were more often available from claims diagnoses codes (1.6 and 1.4 times, respectively). CONCLUSION: GROUSE provides a unified EHR-claims environment to address health system and federal privacy concerns, which enables investigators to generalize analyses across health systems integrated with multistate insurance claims.

OBJECTIVES: We describe the development of a nursing home information technology (IT) maturity model designed to capture stages of IT maturity. MATERIALS AND METHODS: This study had 2 phases. The purpose of phase I was to develop a preliminary nursing home IT maturity model. Phase II involved 3 rounds of questionnaires administered to a Delphi panel of expert nursing home administrators to evaluate the validity of the nursing home IT maturity model proposed in phase I. RESULTS: All participants (n = 31) completed Delphi rounds 1-3. Over the 3 Delphi rounds, the nursing home IT maturity staging model evolved from a preliminary, 5-stage model (stages 1-5) to a 7-stage model (stages 0-6). DISCUSSION: Using innovative IT to improve patient outcomes has become a broad goal across healthcare settings, including nursing homes. Understanding the relationship between IT sophistication and quality performance in nursing homes relies on recognizing the spectrum of nursing home IT maturity that exists and how IT matures over time. Currently, no universally accepted nursing home IT maturity model exists to trend IT adoption and determine the impact of increasing IT maturity on quality. CONCLUSIONS: A 7-stage nursing home IT maturity staging model was successfully developed with input from a nationally representative sample of U.S. based nursing home experts. The model incorporates 7-stages of IT maturity ranging from stage 0 (nonexistent IT solutions or electronic medical record) to stage 6 (use of data by resident or resident representative to generate clinical data and drive self-management).

Effective care coordination requires risk stratification, but little evidence has been collected about how it impacts clinicians. This care coordination pilot project created a unique opportunity to observe care coordination activities for 10,000 patients over 18 months, before and after risk stratification. Risk stratification feedback increased care coordination contacts with high-risk patients, without decreasing contacts with low-risk patients. The results of this study provide quantitative evidence of the importance of risk stratification in care coordination.

Background: Previous studies have shown that use of search tags in PubMed can significantly improve the performance of information retrieval. The objective of this study was to discover associations among search tags in typical PubMed search sessions. Methods: We performed session segmentation on a full-day PubMed query log, identified the search tags within those sessions, and applied association mining to identify strong associations of search tags. Results: A total of eight maximal frequent-itemsets (i.e. search tags) and 34 strong association rules from these itemsets were discovered. We also estimated that the query refinement occurs frequently (i.e. one query per minute on average) for any session length. Conclusions: The association rules consisting of PubMed search tags can be used to develop an interactive and intelligent PubMed search interface so that the users can build the search query using proper search tags and reduce the frequency of query refinement.