BACKGROUND: Racial and ethnic disparities in health care have been consistently documented in the diagnosis, treatment, and outcomes of many common clinical conditions. There has been an acceleration of health information technology (HIT) implementation in the United States, with health care reform legislation including multiple provisions for collecting and using health information to improve and monitor quality and efficiency in health care. Despite an uneven and generally low level of implementation, research has demonstrated that HIT has the potential to improve quality of care and patient safety. If carefully designed and implemented, HIT also has the potential to eliminate disparities. HIT AND DISPARITIES: Several root causes for disparities are amenable to interventions using HIT, particularly innovations in electronic health records, as well as strategies for chronic disease management. Recommendations regardinghealth care system, provider, and patient factors can help health care organizations address disparities as they adopt, expand, and tailor their HIT systems. In terms of health care system factors, organizations should (1) automate and standardize the collection of race/ethnicity and language data, (2) prioritize the use of the data for identifying disparities and tailoring improvement efforts, (3) focus HIT efforts to address fragmented care delivery for racial/ethnic minorities and limited-English-proficiency patients, (4) develop focused computerized clinical decision support systems for clinical areas with significant disparities, and (5) include input from racial/ethnic minorities and those with limited English proficiency in developing patient HIT tools to address the digital divide. CONCLUSIONS: As investments are made in HIT, consideration must be given to the impact that these innovations have on the quality and cost of health care for all patients, including those who experience disparities.
BACKGROUND: Racial and ethnic disparities in health care have been consistently documented in the diagnosis, treatment, and outcomes of many common clinical conditions. There has been an acceleration of health information technology (HIT) implementation in the United States, with health care reform legislation including multiple provisions for collecting and using health information to improve and monitor quality and efficiency in health care. Despite an uneven and generally low level of implementation, research has demonstrated that HIT has the potential to improve quality of care and patient safety. If carefully designed and implemented, HIT also has the potential to eliminate disparities. HIT AND DISPARITIES: Several root causes for disparities are amenable to interventions using HIT, particularly innovations in electronic health records, as well as strategies for chronic disease management. Recommendations regardinghealth care system, provider, and patient factors can help health care organizations address disparities as they adopt, expand, and tailor their HIT systems. In terms of health care system factors, organizations should (1) automate and standardize the collection of race/ethnicity and language data, (2) prioritize the use of the data for identifying disparities and tailoring improvement efforts, (3) focus HIT efforts to address fragmented care delivery for racial/ethnic minorities and limited-English-proficiency patients, (4) develop focused computerized clinical decision support systems for clinical areas with significant disparities, and (5) include input from racial/ethnic minorities and those with limited English proficiency in developing patientHIT tools to address the digital divide. CONCLUSIONS: As investments are made in HIT, consideration must be given to the impact that these innovations have on the quality and cost of health care for all patients, including those who experience disparities.
Authors: Alex J Fauer; Flora Hoodin; Leah Lalonde; Josh Errickson; Lyndsey Runaas; Tracey Churay; Sajjad Seyedsalehi; Casiana Warfield; Grant Chappell; Kristina Brookshire; Dima Chaar; Ji Youn Shin; Michelle Byrd; John Magenau; David A Hanauer; Sung Won Choi Journal: Support Care Cancer Date: 2018-09-20 Impact factor: 3.603
Authors: Valerie A Lewis; Taressa Fraze; Elliott S Fisher; Stephen M Shortell; Carrie H Colla Journal: Health Aff (Millwood) Date: 2017-01-01 Impact factor: 6.301
Authors: Urmimala Sarkar; Gato I Gourley; Courtney R Lyles; Lina Tieu; Cassidy Clarity; Lisa Newmark; Karandeep Singh; David W Bates Journal: J Gen Intern Med Date: 2016-07-14 Impact factor: 5.128
Authors: Katrina J Serrano; Chan L Thai; Alexandra J Greenberg; Kelly D Blake; Richard P Moser; Bradford W Hesse Journal: Public Health Rep Date: 2016-12-09 Impact factor: 2.792