Adoption of healthcare information technology and the impact on clinician behavior

It is widely believed that healthcare information technology (health IT) can improve care and lower costs. However, the pattern and uptake of beneficial features of health IT is poorly understood, and is an important part of realizing the full benefits of health IT. This thesis examines the factors relating to adoption and use of reporting features within an outpatient practice management system. A retrospective observational study was performed utilizing web log data from a practice management and electronic health record system vendor. Two years of data were analyzed on the use of features within the system in two different scenarios: the use of a newly released custom reporting feature among existing clients, and the use of a physician-level monthly report among new clients. Among these two different populations and features, the first use and subsequent utilization exhibited similar patterns. Using the Bass model of technology diffusion to quantify the adoption of these features, it was found that adoption had a low social component (coefficient of imitation) and a high personal component (coefficient of innovation). One physician's use of a feature in his practice did not appear to influence whether a new physician joining the same practice would use the feature. In addition, the earliest users of a feature tended to utilize that feature more often. Practices and providers that used these features performed better across three of four operational and financial metrics. The purchase and installation of a health IT system by an organization does not ensure that individuals within it will fully utilize the system and realize all the benefits.

Department dc:contributor.department

Harvard University--MIT Division of Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2009

Author dc:creator

• Weinstein, Adam, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Teo Forcht Dagi and John Halamka.

• Harvard University--MIT Division of Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/54592

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/54592