Kai Zheng

Parental Awareness and Use of Online Physician Rating Sites

BACKGROUND AND OBJECTIVE: The US public is increasingly using online rating sites to make decisions about a variety of consumer goods and services, including physicians. We sought to understand, within the context of other types of rating sites, parents’ awareness, perceptions, and use of physician-rating sites for choosing primary care physicians for their children. METHODS: This cross-sectional, nationally representative survey of 3563 adults was conducted in September 2012. Participants were asked about rating Web sites in the context of finding a primary care physician for their children and about their previous experiences with such sites. RESULTS: Overall, 2137 (60%) of participants completed the survey. Among these respondents, 1619 were parents who were included in the present analysis. About three-quarters (74%) of parents were aware of physician-rating sites, and about one-quarter (28%) had used them to select a primary care physician for their children. Based on 3 vignettes for which respondents were asked if they would follow a neighbors recommendation about a primary care physician and using multivariate analyses, respondents exposed to a neighbor’s recommendation and positive online physician ratings were significantly more likely to choose the recommended physician (adjusted odds ratio: 3.0 [95% confidence interval: 2.1–4.4]) than respondents exposed to the neighbor’s recommendation alone. Conversely, respondents exposed to the neighbor’s recommendation and negative online ratings were significantly less likely to choose the neighbor children’s physician (adjusted odds ratio: 0.09 [95% confidence interval: 0.03–0.3]). CONCLUSIONS: Parents are beginning to use online physician ratings, and these ratings have the potential to influence choices of their children’s primary care physician.

Cooperative documentation: the patient problem list as a nexus in electronic health records

The patient Problem List (PL) is a mandated documentation component of electronic health records supporting the longitudinal summarization of patient information in addition to facilitating the coordination of care by multidisciplinary medical teams. In this paper, we report an ethnographic study that examined the institutionalization of the PL. Specifically, we explored: (1) how different groups (primary care providers, inpatient hospitalists, specialists, and emergency doctors) perceived the purposes of the PL differently; (2) how these deviated perceptions might affect their use of the PL; and (3) how the technical design of the PL facilitated or hindered the clinical practices of these groups. We found significant ambiguity regarding the definition, benefits, and use of the PL across different groups. We also found that certain groups (e.g. primary care providers) had developed effective cooperative strategies regarding the use of the PL; however, suboptimal usage was common among other user types, which could have a profound impact on quality of care and safety. Based on these findings, we provide suggestions to improve the design of the PL, particularly on strengthening its support on longitudinal and cooperative clinical practices.

Applying multiple methods to assess the readability of a large corpus of medical documents.

Medical documents provided to patients at the end of an episode of care, such as discharge summaries and referral letters, serve as an important vehicle to convey critical information to patients and families. Increasingly, healthcare institutions are also experimenting with granting patients direct electronic access to other types of clinical narratives that are not typically shared unless explicitly requested, such as progress notes. While these efforts have great potential to improve information transparency, their value can be severely diminished if patients are unable to read and thus unable to properly interpret the medical documents shared to them. In this study, we approached the problem by contrasting the readability of two types of medical documents: referral letters vs. other genres of narrative clinician notes not explicitly intended for direct viewing by patients. To establish a baseline for comparison, we also computed readability scores of MedlinePlus articles - exemplars of fine patient education materials carefully crafted for lay audiences. We quantified document readability using four different measures. Differences in the results obtained through these measures are also discussed.

Computational Ethnography: Automated and Unobtrusive Means for Collecting Data In Situ for Human–Computer Interaction Evaluation Studies

Computational ethnography is an emerging family of methods for conducting human–computer interaction (HCI) studies in healthcare. Computational ethnography often leverages automated and less obtrusive means for collecting in situ data that reflect end users’ true, unaltered behaviors of interacting with a software system or a device in naturalistic settings. In this chapter, we introduce the concept of computational ethnography and common types of digital trace data available in healthcare environments, as well as commonly used approaches to analyzing computational ethnographical data. At the end of the chapter, we use two use cases to illustrate how this new family of methods has been applied in healthcare to study end users’ interactions with technological interventions in their everyday routines.

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine

OBJECTIVEnThe utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs).nnnMATERIALS AND METHODSnThe query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model.nnnRESULTSnThe search engines performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks.nnnDISCUSSION AND CONCLUSIONnChallenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge.

Ease of adoption of clinical natural language processing software

OBJECTIVEnIn recognition of potential barriers that may inhibit the widespread adoption of biomedical software, the 2014 i2b2 Challenge introduced a special track, Track 3 - Software Usability Assessment, in order to develop a better understanding of the adoption issues that might be associated with the state-of-the-art clinical NLP systems. This paper reports the ease of adoption assessment methods we developed for this track, and the results of evaluating five clinical NLP system submissions.nnnMATERIALS AND METHODSnA team of human evaluators performed a series of scripted adoptability test tasks with each of the participating systems. The evaluation team consisted of four expert evaluators with training in computer science, and eight end user evaluators with mixed backgrounds in medicine, nursing, pharmacy, and health informatics. We assessed how easy it is to adopt the submitted systems along the following three dimensions: communication effectiveness (i.e., how effective a system is in communicating its designed objectives to intended audience), effort required to install, and effort required to use. We used a formal software usability testing tool, TURF, to record the evaluators interactions with the systems and think-aloud data revealing their thought processes when installing and using the systems and when resolving unexpected issues.nnnRESULTSnOverall, the ease of adoption ratings that the five systems received are unsatisfactory. Installation of some of the systems proved to be rather difficult, and some systems failed to adequately communicate their designed objectives to intended adopters. Further, the average ratings provided by the end user evaluators on ease of use and ease of interpreting output are -0.35 and -0.53, respectively, indicating that this group of users generally deemed the systems extremely difficult to work with. While the ratings provided by the expert evaluators are higher, 0.6 and 0.45, respectively, these ratings are still low indicating that they also experienced considerable struggles.nnnDISCUSSIONnThe results of the Track 3 evaluation show that the adoptability of the five participating clinical NLP systems has a great margin for improvement. Remedy strategies suggested by the evaluators included (1) more detailed and operation system specific use instructions; (2) provision of more pertinent onscreen feedback for easier diagnosis of problems; (3) including screen walk-throughs in use instructions so users know what to expect and what might have gone wrong; (4) avoiding jargon and acronyms in materials intended for end users; and (5) packaging prerequisites required within software distributions so that prospective adopters of the software do not have to obtain each of the third-party components on their own.

Paper versus EHR: simplistic comparisons may not capture current reality

The recent study by Taft and colleagues, which explores communication differences in paper versus electronic health records (EHRs), was both interesting and timely.1 EHRs are becoming a focal point for healthcare delivery in the US, yet the impact of EHRs on the patient-provider relationship remains poorly understood. Communication is at the heart of this relationship, and providers are concerned about the potential for EHRs to reduce the quality of their communications with patients.2,3nnWe would like to provide additional thoughts on Taft etxa0al .’s reported findings and put them into a broader context. First, it is interesting to note that the authors found that EHRs fostered better communications with patients across nearly all measures. However, we wonder what might explain why a physician would greet a patient more warmly when walking into an exam room with a laptop computer vs. a paper chart. This …

Assessing the Effects of Computer-Based Documentation on Parent-Provider Communication

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