Regenstrief Institute's Medical Gopher: A next-generation homegrown electronic medical record system

Duke, Jon; Morea, Justin; Mamlin, Burke W.; Martin, Douglas K.; Simonaitis, Linas; Takesue, Blaine Y.; Dixon, Brian E.; Dexter, Paul

doi:10.1016/j.ijmedinf.2013.11.004

Cited by 30 publications

(31 citation statements)

References 8 publications

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“…The Regenstrief Institute maintains clinician-facing technologies for Eskenazi, specifically its Gopher® order-entry and note-writing 27,28 and Careweb data viewer. 18 Careweb is the only means by which data in Eskenazi EHRs and the INPC can be viewed by providers, and it does so by four methods via tabs on Careweb's main menu: 1) display all patient data in reverse chronological order; 2) display free-text notes and reports in reverse chronologic order; 3) create and display customized flowsheets of numeric and/or coded data by selecting categories from a menu or typing in specific whole or partial term names from a local dictionary 3 ; and 4) via Careweb's Google-like search tool, Chart Search, 18 where entering any partial or full word or phrase yields displays of discrete data or free-text reports containing that term/phrase (with much built-in synonymy) in reverse chronologic order.…”

Section: Careweb Data Displaysmentioning

confidence: 99%

“…17 Under this program, the Regenstrief Institute developed a Web-based system whereby patients could record their preferences for who could access specific data in their EHRs. Regenstrief developers then modified their existing EHR viewer called Careweb® 18 to allow patients' preferences to guide what EHR information providers can see. Careweb is the sole means for viewing data in the INPC and the EHR maintained by Eskenazi Health, an urban public health system in Indianapolis.…”

Section: Introductionmentioning

confidence: 99%

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Provider Responses to Patients Controlling Access to their Electronic Health Records: A Prospective Cohort Study in Primary Care

et al. 2014

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INTRODUCTION:Applying Fair Information Practice principles to electronic health records (EHRs) requires allowing patient control over who views their data. METHODS: We designed a program that captures patients' preferences for provider access to an urban health system's EHR. Patients could allow or restrict providers' access to all data (diagnoses, medications, test results, reports, etc.) or only highly sensitive data (sexually transmitted infections, HIV/AIDS, drugs/alcohol, mental or reproductive health). Except for information in free-text reports, we redacted EHR data shown to providers according to patients' preferences. Providers could "break the glass" to display redacted information. We prospectively studied this system in one primary care clinic, noting redactions and when users "broke the glass," and surveyed providers about their experiences and opinions. RESULTS: Eight of nine eligible clinic physicians and all 23 clinic staff participated. All 105 patients who enrolled completed the preference program. Providers did not know which of their patients were enrolled, nor their preferences for accessing their EHRs. During the 6-month prospective study, 92 study patients (88 %) returned 261 times, during which providers viewed their EHRs 126 times (48 %). Providers "broke the glass" 102 times, 92 times for patients not in the study and ten times for six returning study patients, all of whom had restricted EHR access. Providers "broke the glass" for six (14 %) of 43 returning study patients with redacted data vs. zero among 49 study patients without redactions (p=0.01). Although 54 % of providers agreed that patients should have control over who sees their EHR information, 58 % believed restricting EHR access could harm provider-patient relationships and 71 % felt quality of care would suffer. CONCLUSIONS: Patients frequently preferred restricting provider access to their EHRs. Providers infrequently overrode patients' preferences to view hidden data. Providers believed that restricting EHR access would adversely impact patient care. Applying Fair Information Practice principles to EHRs will require balancing patient preferences, providers' needs, and health care quality.KEY WORDS: fair information practices; electronic health records; patient preferences; quality of care.

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Section: Careweb Data Displaysmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Provider Responses to Patients Controlling Access to their Electronic Health Records: A Prospective Cohort Study in Primary Care

et al. 2014

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“…5,6 We modified Regenstrief's existing program, called Careweb®, 7 which is used to view data in the INPC and the EHR, and is maintained by Regenstrief for Eskenazi Health, a large urban public teaching health system. For this study, we targeted a single Eskenazi primary care clinic where all physicians and clinic staff are employed by Eskenazi Medical Group.…”

Section: Methods and System Design Principles Settingmentioning

confidence: 99%

“…We therefore created three multidisciplinary project teams: (a) the Bioethics Team consisted of bioethicists and clinicians who identified points to consider when designing and implementing a system whereby patients could exercise their rights under Fair Information Practices 2 ; (b) the Patient Preference Team included informaticists and behavioral scientists who assessed patients' desires for controlling EHR access 3 and designed a user-friendly system for recording their preferences for displaying EHR information 8 ; and (c) the Technical Team was comprised of Regenstrief Institute EHR developers who created CareWeb 7 and designed and implemented modifications whereby patients' preferences would govern display of their EHR data.…”

Section: Methods and System Design Principles Settingmentioning

confidence: 99%

Designing a System for Patients Controlling Providers’ Access to their Electronic Health Records: Organizational and Technical Challenges

et al. 2014

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“…Clinical alerts-a kind of clinical decision support-are routinely used in prescribing patient medications via computerized physician order entry (CPOE) systems [5]. The most common type of clinical alerts is Drugdrug interaction (DDI) alerts (Figure 1).…”

Section: Introductionmentioning

confidence: 99%

Endorsement, Prior Action, and Language

Chattopadhyay

Duke

Bolchini

2016

Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems

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The safe prescribing of medications via computerized physician order entry routinely relies on clinical alerts. Alert compliance, however, remains surprisingly low, with up to 95% often ignored. Prior approaches, such as improving presentational factors in alert design, had limited success, mainly due to physicians' lack of trust in computerized advice. While designing trustworthy alert is key, actionable design principles to embody elements of trust in alerts remain little explored. To mitigate this gap, we introduce a model to guide the design of trust-based clinical alerts-based on what physicians value when trusting advice from peers in clinical activities. We discuss three key dimensions to craft trusted alerts: using colleagues' endorsement, foregrounding physicians' prior actions, and adopting a suitable language. We exemplify our approach with emerging alert designs from our ongoing research with physicians and contribute to the current debate on how to design effective alerts to improve patient safety.

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Regenstrief Institute's Medical Gopher: A next-generation homegrown electronic medical record system

Cited by 30 publications

References 8 publications

Provider Responses to Patients Controlling Access to their Electronic Health Records: A Prospective Cohort Study in Primary Care

Provider Responses to Patients Controlling Access to their Electronic Health Records: A Prospective Cohort Study in Primary Care

Designing a System for Patients Controlling Providers’ Access to their Electronic Health Records: Organizational and Technical Challenges

Endorsement, Prior Action, and Language

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