Objectives:Assess (1) if patients can improve their medical records’ accuracy if effectively engaged using a networked Personal Health Record; (2) workflow efficiency and reliability for receiving and processing patient feedback; and (3) patient feedback’s impact on medical record accuracy.Background:Improving medical record’ accuracy and associated challenges have been documented extensively. Providing patients with useful access to their records through information technology gives them new opportunities to improve their records’ accuracy and completeness. A new approach supporting online contributions to their medication lists by patients of Geisinger Health Systems, an online patient-engagement advocate, revealed this can be done successfully.In late 2011, Geisinger launched an online process for patients to provide electronic feedback on their medication lists’ accuracy before a doctor visit. Patient feedback was routed to a Geisinger pharmacist, who reviewed it and followed up with the patient before changing the medication list shared by the patient and the clinicians.Methods:The evaluation employed mixed methods and consisted of patient focus groups (users, nonusers, and partial users of the feedback form), semi structured interviews with providers and pharmacists, user observations with patients, and quantitative analysis of patient feedback data and pharmacists’ medication reconciliation logs.Findings/Discussion:(1) Patients were eager to provide feedback on their medications and saw numerous advantages. Thirty percent of patient feedback forms (457 of 1,500) were completed and submitted to Geisinger. Patients requested changes to the shared medication lists in 89 percent of cases (369 of 414 forms). These included frequency—or dosage changes to existing prescriptions and requests for new medications (prescriptions and over-the counter). (2) Patients provided useful and accurate online feedback. In a subsample of 107 forms, pharmacists responded positively to 68 percent of patient requests for medication list changes. (3) Processing patient feedback will requires both software algorithms and human interpretation. For the 107 forms subsample, pharmacists accepted patient input in 51 percent of cases where they could not contact the patient. Where the patient was contacted, they accepted feedback from 68 percent. This suggests there may be opportunities to automate feedback filtering and processing for more efficient (and larger scale) medication-list optimization. (4) A supportive overall e-health environment makes acceptance of an online patient feedback system more likely. Review of Geisinger usage data showed patients who completed the medication feedback form had previously accessed MyGeisinger 2.3 times as often as the average patient and initiated secure messages with a clinician 1.35 times as often as patients not involved in the pilot.Conclusions:Patient feedback, placed in a useful workflow, can improve medical record accuracy. Electronic health record (EHR) vendors and developers need to build ...

This paper presents extensions to the work of Bobrow and Webber [Bobrow&Webber 80a, Bobrow&Webber 80b] on semantic interpretation using KL-ONE to represent knowledge. The approach is based on an extended case frame formalism applicable to all types of phrases, not just clauses. The frames are used to recognize semantically acceptable phrases, identify their structure, and, relate them to their meaning representation through translation rules.Approaches are presented for generating KL-ONE structures as the meaning of a sentence, for capturing semantic generalizations through abstract case frames, and for handling pronouns and relative clauses.

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