Organizational Factors Associated with Health Information Technology Adoption and Utilization Among Home Health / Hospice Agencies

2011 ◽  
Vol 6 (3) ◽  
pp. 46-59 ◽  
Author(s):  
Jordan Mitchell ◽  
Kevin J. Bennett ◽  
Janice Probst
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Point Of Care ◽  
Organizational Factors ◽  
Home Health ◽  
Factors Associated ◽  
For Profit ◽  
Not For Profit ◽  
Emr Adoption

Health information technology (HIT) adoption has been recommended as a method to improve care coordination and promote patient safety. Home health agencies can use HIT to improve coordination of care provided in multiple locations. The purposes of this study are: 1) to determine the EMR adoption rate and use of point of care technology among a US sample of 1,036 home health/hospice facilities, and 2) to identify the organizational factors associated with EMR adoption. Analyses were performed using SAS and SAS-callable SUDAAN. The study found that not-for-profit agencies, regardless of services offered, were more likely to have an EMR system. Use of point of care documentation was associated with not-for-profit status, large patient panels, and having been in business for less than 10 years. This study extends population ecology theory into innovation adoption theories by explaining possible competitive advantages of EMR adoption within home health care.

Organizational Factors Associated with Health Information Technology Adoption and Utilization Among Home Health/Hospice Agencies

2013 ◽  
pp. 73-86
Author(s):  
Jordan Mitchell ◽  
Kevin J. Bennett ◽  
Janice Probst
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Point Of Care ◽  
Organizational Factors ◽  
Home Health ◽  
Factors Associated ◽  
For Profit ◽  
Not For Profit ◽  
Emr Adoption

Health information technology (HIT) adoption has been recommended as a method to improve care coordination and promote patient safety. Home health agencies can use HIT to improve coordination of care provided in multiple locations. The purposes of this study are: 1) to determine the EMR adoption rate and use of point of care technology among a US sample of 1,036 home health/hospice facilities, and 2) to identify the organizational factors associated with EMR adoption. Analyses were performed using SAS and SAS-callable SUDAAN. The study found that not-for-profit agencies, regardless of services offered, were more likely to have an EMR system. Use of point of care documentation was associated with not-for-profit status, large patient panels, and having been in business for less than 10 years. This study extends population ecology theory into innovation adoption theories by explaining possible competitive advantages of EMR adoption within home health care.

Health Information Technology Spending on the Rise

2018 ◽  
pp. 1-14
Author(s):  
Jinhyung Lee ◽  
Hansil Choi
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Health Planning ◽  
Teaching Hospitals ◽  
Health It ◽  
Factors Affecting ◽  
For Profit ◽  
Not For Profit ◽  
Level Data

In this chapter, the authors track health information technology by examining the factors affecting health information technology (IT) expenditure. The authors employed hospital- and patient-level data of the Office of Statewide Health Planning and Development (OSHPD) from 2000 to 2006. The generalized linear model (GLM) was employed with log link and normal distribution and controlled for clustering error. The authors found that not-for-profit and government hospitals, teaching hospitals, competition, and health IT expenditure of neighborhood hospitals were positively associated with health IT expenditure. However, rural hospitals were negatively associated with health IT expenditure. Moreover, the authors found that mean annual health IT expenditure was approximately $7.4 million from 2000-2006. However, it jumped 204% to $15.1 million from 2008-2014.

scholarly journals The Trillion Dollar Conundrum: Complementarities and Health Information Technology

2014 ◽  
Vol 6 (4) ◽  
pp. 239-270 ◽  
Author(s):  
David Dranove ◽  
Chris Forman ◽  
Avi Goldfarb ◽  
Shane Greenstein
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Operating Costs ◽  
Average Effect ◽  
Cost Increase ◽  
Emr Adoption

We examine the heterogeneous relationship between the adoption of EMR and hospital operating costs at thousands of US hospitals between 1996 and 2009. We first document a previously-identified puzzle: Adoption of EMR is associated with a slight cost increase. Drawing on the literature on IT and productivity, we analyze why this average effect arises. We find that: (i) EMR adoption is initially associated with a rise in costs; (ii) EMR adoption at hospitals in IT-intensive locations leads to a decrease in costs after three years; and (iii) Hospitals in other locations experience an increase in costs even after six years. (JEL D24, I11, M15)

Challenges and opportunities from the Agency for Healthcare Research and Quality (AHRQ) research summit on improving diagnosis: a proceedings review

Diagnosis ◽  
2017 ◽  
Vol 4 (2) ◽  
pp. 57-66 ◽  
Author(s):  
Kerm Henriksen ◽  
Chris Dymek ◽  
Michael I. Harrison ◽  
P. Jeffrey Brady ◽  
Sharon B. Arnold
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Organizational Factors ◽  
Diagnostic Error ◽  
Evidence Base ◽  
Healthcare Research ◽  
Diagnostic Process ◽  
Use Of Data ◽  
Challenges And Opportunities

AbstractBackground:TheContent:The goals of the summit were to learn from the insights of participants; examine issues associated with definitions of diagnostic error and gaps in the evidence base; explore clinician and patient perspectives; gain a better understanding of data and measurement, health information technology, and organizational factors that impact the diagnostic process; and identify potential future directions for research.Summary and outlook:Plenary sessions focused on the state of the new diagnostic safety discipline followed by breakout sessions on the use of data and measurement, health information technology, and the role of organizational factors. The proceedings review captures many of the key challenges and areas deserving further research, revealing stimulating yet complex issues.

Factors Affecting Health Information Technology Expenditure in California Hospitals

2018 ◽  
pp. 1437-1449
Author(s):  
Jinhyung Lee
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Health Planning ◽  
Teaching Hospitals ◽  
It Adoption ◽  
Health It ◽  
It Investment ◽  
Factors Affecting ◽  
For Profit

This paper investigates the factors affecting health information technology (IT) investment. Different from previous studies, health IT was measured as the dollar amount of hardware, software and labor related health IT. This study employed Hospital and Patient level data of the Office of Statewide Health Planning and Development (OSHPD) from 2000 to 2006. The generalized linear model (GLM) was employed with log link and normal distribution and controlled for clustering error. This study found that not-for-profit and government hospital, teaching hospitals, competition, health IT expenditure of neighborhood hospitals were positively associated with health IT expenditure. However, rural hospitals were negatively associated with health IT expenditure. Moreover, this study found a significant increase in health IT investment over seven years resulted from increased clinical IT adoption.

scholarly journals Sync for Genes: Making Clinical Genomics Available for Precision Medicine at the Point-of-Care

2020 ◽  
Vol 11 (02) ◽  
pp. 295-302
Author(s):  
Stephanie J. Garcia ◽  
Teresa Zayas-Cabán ◽  
Robert R. Freimuth
Keyword(s):  
Information Technology ◽  
Precision Medicine ◽  
Health Information Technology ◽  
Health Information ◽  
Point Of Care ◽  
Genomic Data ◽  
Health Data ◽  
Lessons Learned ◽  
Data Standards ◽  
Research Initiative

Abstract Background Making genomic data available at the point-of-care and for research is critical for the success of the Precision Medicine Initiative (PMI), a research initiative which seeks to change health care by “tak(ing) into account individual differences in people's genes, environments, and lifestyles.” The Office of the National Coordinator for Health Information Technology (ONC) led Sync for Genes, a program to develop standards that make genomic data available when and where it matters most. This article discusses lessons learned from recent Sync for Genes activities. Objectives The goals of Sync for Genes were to (1) demonstrate exchange of genomic data using health data standards, (2) provide feedback for refinement of health data standards, and (3) synthesize project experiences to support the integration of genomic data at the point-of-care and for research. Methods Four organizations participated in a program to test the Health Level Seven International (HL7®) Fast Healthcare Interoperability Resources (FHIR®) standard, which supports sharing genomic data. ONC provided access to subject matter experts, resources, tools, and technical guidance to support testing activities. Three of the four organizations participated in HL7 FHIR Connectathons to test FHIR's ability to exchange genomic diagnostic reports. Results The organizations successfully demonstrated exchange of genomic diagnostic reports using FHIR. The feedback and artifacts that resulted from these activities were shared with HL7 and made publicly available. Four areas were identified as important considerations for similar projects: (1) FHIR proficiency, (2) developer support, (3) project scope, and (4) bridging health information technology and genomic expertise. Conclusion Precision medicine is a rapidly evolving field, and there is opportunity to continue maturing health data standards for the exchange of necessary genomic data, increasing the likelihood that the standard supports the needs of users.

scholarly journals Experience with decision support system and comfort with topic predict clinicians’ responses to alerts and reminders

2015 ◽  
Vol 23 (e1) ◽  
pp. e125-e130 ◽  
Author(s):  
Nerissa S Bauer ◽  
Aaron E Carroll ◽  
Chandan Saha ◽  
Stephen M Downs
Keyword(s):  
Information Technology ◽  
Quality Improvement ◽  
Decision Support ◽  
Decision Support System ◽  
Health Information Technology ◽  
Health Information ◽  
Support System ◽  
Response Rate ◽  
Factors Associated ◽  
Prompt Response

Abstract Objective Clinicians at our institution typically respond to about half of the prompts they are given by the clinic’s computer decision support system (CDSS). We sought to examine factors associated with clinician response to CDSS prompts as part of a larger, ongoing quality improvement effort to optimize CDSS use. Methods We examined patient, prompt, and clinician characteristics associated with clinician response to decision support prompts from the Child Health Improvement through Computer Automation (CHICA) system. We asked pediatricians who were nonusers of CHICA to rate decision support topics as “easy” or “not easy” to discuss with patients and their guardians. We analyzed these ratings and data, from July 1, 2009 to January 29, 2013, utilizing a hierarchical regression model, to determine whether factors such as comfort with the prompt topic and the length of the user’s experience with CHICA contribute to user response rates. Results We examined 414 653 prompts from 22 260 patients. The length of time a clinician had been using CHICA was associated with an increase in their prompt response rate. Clinicians were more likely to respond to topics rated as “easy” to discuss. The position of the prompt on the page, clinician gender, and the patient’s age, race/ethnicity, and preferred language were also predictive of prompt response rate. Conclusion This study highlights several factors associated with clinician prompt response rates that could be generalized to other health information technology applications, including the clinician’s length of exposure to the CDSS, the prompt’s position on the page, and the clinician’s comfort with the prompt topic. Incorporating continuous quality improvement efforts when designing and implementing health information technology may ensure that its use is optimized.

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