The Adoption and Use of Health Information Technology in Rural Areas: Results of a National Survey

Singh, Ranjit; Lichter, Michael I.; Danzo, Andrew; Taylor, John S.; Rosenthal, Thomas C.

doi:10.1111/j.1748-0361.2011.00370.x

Cited by 41 publications

(60 citation statements)

References 30 publications

(45 reference statements)

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“…Although previous analysis of national survey data by Singh et al showed that practices in rural areas actually had 3.7 times higher rates of adoption than those in urban areas, our data suggest that RHCs have a uniquely higher chance of not adopting EHR, and may be different in this respect from other practices in rural areas. 15 …”

Section: Discussionmentioning

confidence: 99%

Disparities in Primary Care EHR Adoption Rates

Mack¹,

Zhang²,

Douglas³

et al. 2016

hpu

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This study evaluates electronic health record (EHR) adoption by primary care providers in Georgia to assess adoption disparities according to practice size and type, payer mix, and community characteristics. Frequency variances of EHR “Go Live” status were estimated. Odds ratios were calculated by univariate and multivariate logistic regression models. Large practices and community health centers (CHCs) were more likely to Go Live (>80% EHR adoption) than rural health clinics and other underserved settings (53%). A significantly lower proportion (68.9%) of Medicaid predominant providers had achieved Go Live status and had a 47% higher risk of not achieving Go Live status than private insurance predominant practices. Disparities in EHR adoption rates may exacerbate existing disparities in health outcomes of patients served by these practices. Targeted support such as that provided to CHCs would level the playing field for practices now at a disadvantage.

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Section: Discussionmentioning

confidence: 99%

Disparities in Primary Care EHR Adoption Rates

Mack¹,

Zhang²,

Douglas³

et al. 2016

hpu

View full text Add to dashboard Cite

show abstract

“…1001 completed surveys were received during this process. The survey and data collection are described in more detail in Singh et al [20]. Because this current study investigates the impact of actual EMR usage on health care outcomes, our data analysis only includes the physician offices which had already adopted EMR systems and whose data are complete for all variables included in our model, which lead to 222 observations in our final analysis.…”

Section: Methods Datamentioning

confidence: 99%

“Meaningful Use” of ambulatory EMR: Does it improve the quality and efficiency of health care?

Xiao¹,

Sharman

Singh

et al. 2012

Health Policy and Technology

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“…One advantage of this style of interaction is that it may be more efficient, in terms of time spent interacting with the patient and inputting necessary data during the visit, which leads to minimal time spent charting after the visits. However, physicians who rely on this interaction style may experience challenges in situations where it may be necessary to provide care without technologies (Singh et al, 2012). Other disadvantages are that this group may not be able to communicate empathy appropriately when it is necessary because of the methods they tend to use (multitasking with short verbal and nonverbal interactions).…”

Section: Discussionmentioning

confidence: 99%

Physician interactions with electronic health records in primary care

Asan

Montague

2012

Health Systems

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Objective It is essential to design technologies and systems that promote appropriate interactions between physicians and patients. This study explored how physicians interact with Electronic Health Records (EHRs) to understand the qualities of the interaction between the physician and the EHR that may contribute to positive physician-patient interactions. Study Design Video-taped observations of 100 medical consultations were used to evaluate interaction patterns between physicians and EHRs. Quantified observational methods were used to contribute to ecological validity. Methods Ten primary care physicians and 100 patients from five clinics participated in the study. Clinical encounters were recorded with video cameras and coded using a validated objective coding methodology in order to examine how physicians interact with electronic health records. Results Three distinct styles were identified that characterize physician interactions with the EHR: technology-centered, human-centered, and mixed. Physicians who used a technology-centered style spent more time typing and gazing at the computer during the visit. Physicians who used a mixed style shifted their attention and body language between their patients and the technology throughout the visit. Physicians who used the human-centered style spent the least amount of time typing and focused more on the patient. Conclusion A variety of EHR interaction styles may be effective in facilitating patient-centered care. However, potential drawbacks of each style exist and are discussed. Future research on this topic and design strategies for effective health information technology in primary care are also discussed.

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The Adoption and Use of Health Information Technology in Rural Areas: Results of a National Survey

Abstract: HIT adoption and use in rural primary care offices does not appear to be lower than in urban offices. The situation, however, is dynamic and warrants further monitoring.

Cited by 41 publications

References 30 publications

Disparities in Primary Care EHR Adoption Rates

Disparities in Primary Care EHR Adoption Rates

“Meaningful Use” of ambulatory EMR: Does it improve the quality and efficiency of health care?

Physician interactions with electronic health records in primary care

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