Dataset Information

Gastrointestinal disease outbreak detection using multiple data streams from electronic medical records.

ABSTRACT:

Background

Passive reporting and laboratory testing delays may limit gastrointestinal (GI) disease outbreak detection. Healthcare systems routinely collect clinical data in electronic medical records (EMRs) that could be used for surveillance. This study's primary objective was to identify data streams from EMRs that may perform well for GI outbreak detection.

Methods

Zip code-specific daily episode counts in 2009 were generated for 22 syndromic and laboratory-based data streams from Kaiser Permanente Northern California EMRs, covering 3.3 million members. Data streams included outpatient and inpatient diagnosis codes, antidiarrheal medication dispensings, stool culture orders, and positive microbiology tests for six GI pathogens. Prospective daily surveillance was mimicked using the space-time permutation scan statistic in single and multi-stream analyses, and space-time clusters were identified. Serotype relatedness was assessed for isolates in two Salmonella clusters.

Results

Potential outbreaks included a cluster of 18 stool cultures ordered over 5 days in one zip code and a Salmonella cluster in three zip codes over 9 days, in which at least five of six cases had the same rare serotype. In all, 28 potential outbreaks were identified using single stream analyses, with signals in outpatient diagnosis codes most common. Multi-stream analyses identified additional potential outbreaks and in one example, improved the timeliness of detection.

Conclusions

GI disease-related data streams can be used to identify potential outbreaks when generated from EMRs with extensive regional coverage. This process can supplement traditional GI outbreak reports to health departments, which frequently consist of outbreaks in well-defined settings (e.g., day care centers and restaurants) with no laboratory-confirmed pathogen. Data streams most promising for surveillance included microbiology test results, stool culture orders, and outpatient diagnoses. In particular, clusters of microbiology tests positive for specific pathogens could be identified in EMRs and used to prioritize further testing at state health departments, potentially improving outbreak detection.

SUBMITTER: Greene SK

PROVIDER: S-EPMC3377951 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundPersonal electronic health records (PEHRs) allow patients to view, generate, and manage their personal and medical data that are relevant across illness episodes, such as their medications, allergies, immunizations, and their medical, social, and family health history. Thus, patients can actively participate in the management of their health care by ensuring that their health care providers have an updated and accurate overview of the patients' medical records. However, the uptake of PEHRs remains low, especially in terms of patients entering and managing their personal and medical data in their PEHR.ObjectiveThis scoping review aimed to explore the barriers and facilitators that patients face when deciding to review, enter, update, or modify their personal and medical data in their PEHR. This review also explores the extent to which patient-generated and -managed data affect the quality and safety of care, patient engagement, patient satisfaction, and patients' health and health care services.MethodsWe searched the MEDLINE, Embase, CINAHL, PsycINFO, Cochrane Library, Web of Science, and Google Scholar web-based databases, as well as reference lists of all primary and review articles using a predefined search query.ResultsOf the 182 eligible papers, 37 (20%) provided sufficient information about patients' data management activities. The results showed that patients tend to use their PEHRs passively rather than actively. Patients refrain from generating and managing their medical data in a PEHR, especially when these data are complex and sensitive. The reasons for patients' passive data management behavior were related to their concerns about the validity, applicability, and confidentiality of patient-generated data. Our synthesis also showed that patient-generated and -managed health data ensures that the medical record is complete and up to date and is positively associated with patient engagement and patient satisfaction.ConclusionsThe findings of this study suggest recommendations for implementing design features within the PEHR and the construal of a dedicated policy to inform both clinical staff and patients about the added value of patient-generated data. Moreover, clinicians should be involved as important ambassadors in informing, reminding, and encouraging patients to manage the data in their PEHR.