Literature DB >> 10495097

Personalized health care and business success: can informatics bring us to the promised land?

J G Ozbolt1.   

Abstract

Perrow's models of organizational technologies provide a framework for analyzing clinical work processes and identifying the management structures and informatics tools to support each model. From this perspective, health care is a mixed model in which knowledge workers require flexible management and a variety of informatics tools. A Venn diagram representing the content of clinical decisions shows that uncertainties in the components of clinical decisions largely determine which type of clinical work process is in play at a given moment. By reducing uncertainties in clinical decisions, informatics tools can support the appropriate implementation of knowledge and free clinicians to use their creativity where patients require new or unique interventions. Outside health care, information technologies have made possible breakthrough strategies for business success that would otherwise have been impossible. Can health informatics work similar magic and help health care agencies fulfill their social mission while establishing sound business practices? One way to do this would be through personalized health care. Extensive data collected from patients could be aggregated and analyzed to support better decisions for the care of individual patients as well as provide projections of the need for health services for strategic and tactical planning. By making excellent care for each patient possible, reducing the "inventory" of little-needed services, and targeting resources to population needs, informatics can offer a route to the "promised land" of adequate resources and high-quality care.

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Year:  1999        PMID: 10495097      PMCID: PMC61380          DOI: 10.1136/jamia.1999.0060368

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  6 in total

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  6 in total
  3 in total

1.  Health informatics: linking investment to value.

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Journal:  J Am Med Inform Assoc       Date:  1999 Sep-Oct       Impact factor: 4.497

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  3 in total

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