8 research outputs found

    Developing public health clinical decision support systems (CDSS) for the outpatient community in New York City: our experience

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    <p>Abstract</p> <p>Background</p> <p>Developing a clinically relevant set of quality measures that can be effectively used by an electronic health record (EHR) is difficult. Whether it is achieving internal consensus on relevant priority quality measures, communicating to EHR vendors' whose programmers generally lack clinical contextual knowledge, or encouraging implementation of EHR that meaningfully impacts health outcomes, the path is challenging. However, greater transparency of population health, better accountability, and ultimately improved health outcomes is the goal and EHRs afford us a realistic chance of reaching it in a scalable way.</p> <p>Method</p> <p>In this article, we summarize our experience as a public health government agency with developing measures for a public health oriented EHR in New York City in partnership with a commercial EHR vendor.</p> <p>Results</p> <p>From our experience, there are six key lessons that we share in this article that we believe will dramatically increase the chance of success. First, define the scope and build consensus. Second, get support from executive leadership. Third, find an enthusiastic and competent software partner. Fourth, implement a transparent operational strategy. Fifth, create and test the EHR system with real life scenarios. Last, seek help when you need it.</p> <p>Conclusions</p> <p>Despite the challenges, we encourage public health agencies looking to build a similarly focused public health EHR to create one both for improved individual patient as well as the larger population health.</p

    Humanized Mouse Models for the Preclinical Assessment of Cancer Immunotherapy

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