Implementation and adoption of a health insurance support tool in the electronic health record: A mixed methods analysis within a randomized trial

Abstract Background: In addition to delivering vital health care to millions of patients in the United States, community health centers (CHCs) provide needed health insurance outreach and enrollment support to their communities. We developed a health insurance enrollment tracking tool integrated within the electronic health record (EHR) and conducted a hybrid implementation-effectiveness trial in a CHC-based research network to assess tool adoption using two implementation strategies. Methods: CHCs were recruited from the OCHIN practice-based research network. Seven health center systems (23 CHC clinic sites) were recruited and randomized to receive basic educational materials alone (Arm 1), or these materials plus facilitation (Arm 2) during the 18-month study period, September 2016-April 2018. Facilitation consisted of monthly contacts with clinic staff and utilized audit and feedback and guided improvement cycles. We measured total and monthly tool utilization from the EHR. We conducted structured interviews of CHC staff to assess factors associated with tool utilization. Qualitative data were analyzed using an immersion-crystallization approach with barriers and facilitators identified using the Consolidated Framework for Implementation Research. Results: The majority of CHCs in both study arms adopted the enrollment tool. The rate of tool utilization was, on average, higher in Arm 2 compared to Arm 1 (20.0% versus 4.7%, p <0.01). However, by the end of the study period, the rate of tool utilization was similar in both arms; and observed between-arm differences in tool utilization were largely driven by a single, large health center in Arm 2. Perceived relative advantage of the tool was the key factor identified by clinic staff as driving tool utilization. Implementation climate and leadership engagement were also associated with tool utilization. Conclusions: Using basic education materials and low-intensity facilitation, CHCs quickly adopted an EHR-based tool to support critical outreach and enrollment activities aimed at improving access to health insurance in their communities. Though facilitation carried some benefit, a CHC’s perceived relative advantage of the tool was the primary driver of decisions to implement the tool. Trial Registration: ClinicalTrials.gov: NCT02355262, Posted February 4, 2015

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Implementation and adoption of a health insurance support tool in the electronic health record: A mixed methods analysis within a randomized trial

10.21203/rs.2.15423/v1 ◽

2019 ◽

Author(s):

Brigit Hatch ◽

Carrie Tillotson ◽

Nathalie Huguet ◽

Miguel Marino ◽

Andrea Baron ◽

...

Keyword(s):

Health Insurance ◽

Electronic Health Record ◽

Health Center ◽

The United States ◽

Audit And Feedback ◽

Research Network ◽

Relative Advantage ◽

Health Record ◽

Clinic Staff ◽

Electronic Health

Abstract Background: In addition to delivering vital health care to millions of patients in the United States, community health centers (CHCs) provide needed health insurance outreach and enrollment support to their communities. We developed a health insurance enrollment tracking tool integrated within the electronic health record (EHR) and conducted a hybrid implementation-effectiveness trial in a CHC-based research network to assess tool adoption using two implementation strategies. Methods: CHCs were recruited from the OCHIN practice-based research network. Seven health center systems (23 CHC clinic sites) were recruited and randomized to receive basic educational materials alone (Arm 1), or these materials plus facilitation (Arm 2) during the 18-month study period, September 2016-April 2018. Facilitation consisted of monthly contacts with clinic staff and utilized audit and feedback and guided improvement cycles. We measured total and monthly tool utilization from the EHR. We conducted structured interviews of CHC staff to assess factors associated with tool utilization. Qualitative data were analyzed using an immersion-crystallization approach with barriers and facilitators identified using the Consolidated Framework for Implementation Research. Results: The majority of CHCs in both study arms adopted the enrollment tool. The rate of tool utilization was, on average, higher in Arm 2 compared to Arm 1 (20.0% versus 4.7%, p <0.01). However, by the end of the study period, the rate of tool utilization was similar in both arms; and observed between-arm differences in tool utilization were largely driven by a single, large health center in Arm 2. Perceived relative advantage of the tool was the key factor identified by clinic staff as driving tool utilization. Implementation climate and leadership engagement were also associated with tool utilization. Conclusions: Using basic education materials and low-intensity facilitation, CHCs quickly adopted an EHR-based tool to support critical outreach and enrollment activities aimed at improving access to health insurance in their communities. Though facilitation carried some benefit, a CHC’s perceived relative advantage of the tool was the primary driver of decisions to implement the tool. Trial Registration: ClinicalTrials.gov: NCT02355262, Posted February 4, 2015

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Implementation and adoption of a health insurance support tool in the electronic health record: A mixed methods analysis within a randomized trial

10.21203/rs.2.15423/v2 ◽

2019 ◽

Author(s):

Brigit Hatch ◽

Carrie Tillotson ◽

Nathalie Huguet ◽

Miguel Marino ◽

Andrea Baron ◽

...

Keyword(s):

Health Insurance ◽

Electronic Health Record ◽

Health Center ◽

The United States ◽

Audit And Feedback ◽

Research Network ◽

Relative Advantage ◽

Health Record ◽

Clinic Staff ◽

Electronic Health

Abstract Background: In addition to delivering vital health care to millions of patients in the United States, community health centers (CHCs) provide needed health insurance outreach and enrollment support to their communities. We developed a health insurance enrollment tracking tool integrated within the electronic health record (EHR) and conducted a hybrid implementation-effectiveness trial in a CHC-based research network to assess tool adoption using two implementation strategies. Methods: CHCs were recruited from the OCHIN practice-based research network. Seven health center systems (23 CHC clinic sites) were recruited and randomized to receive basic educational materials alone (Arm 1), or these materials plus facilitation (Arm 2) during the 18-month study period, September 2016-April 2018. Facilitation consisted of monthly contacts with clinic staff and utilized audit and feedback and guided improvement cycles. We measured total and monthly tool utilization from the EHR. We conducted structured interviews of CHC staff to assess factors associated with tool utilization. Qualitative data were analyzed using an immersion-crystallization approach with barriers and facilitators identified using the Consolidated Framework for Implementation Research. Results: The majority of CHCs in both study arms adopted the enrollment tool. The rate of tool utilization was, on average, higher in Arm 2 compared to Arm 1 (20.0% versus 4.7%, p <0.01). However, by the end of the study period, the rate of tool utilization was similar in both arms; and observed between-arm differences in tool utilization were largely driven by a single, large health center in Arm 2. Perceived relative advantage of the tool was the key factor identified by clinic staff as driving tool utilization. Implementation climate and leadership engagement were also associated with tool utilization. Conclusions: Using basic education materials and low-intensity facilitation, CHCs quickly adopted an EHR-based tool to support critical outreach and enrollment activities aimed at improving access to health insurance in their communities. Though facilitation carried some benefit, a CHC’s perceived relative advantage of the tool was the primary driver of decisions to implement the tool. Trial Registration: ClinicalTrials.gov: NCT02355262, Posted February 4, 2015

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Business: The Electronic Health Record: Front Line Experience

Perspectives on Administration and Supervision ◽

10.1044/aas21.1.18 ◽

2011 ◽

Vol 21 (1) ◽

pp. 18-22

Author(s):

Rosemary Griffin

Keyword(s):

Health Care ◽

Information Technology ◽

Electronic Health Record ◽

Financial Incentives ◽

Best Practice ◽

Health Care Systems ◽

The United States ◽

Health Record ◽

Health Trends ◽

Electronic Health

National legislation is in place to facilitate reform of the United States health care industry. The Health Care Information Technology and Clinical Health Act (HITECH) offers financial incentives to hospitals, physicians, and individual providers to establish an electronic health record that ultimately will link with the health information technology of other health care systems and providers. The information collected will facilitate patient safety, promote best practice, and track health trends such as smoking and childhood obesity.

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Targeted Outpatient Fluoroquinolone Intervention utilizing an Integrated Electronic Health Record in the Bureau of Prisons

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.1048 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s402-s402

Author(s):

Deborah Long ◽

Alisha Edmunds ◽

Tyler Campbell ◽

Michael Long

Keyword(s):

Electronic Health Record ◽

Antimicrobial Stewardship ◽

Singular System ◽

Audit And Feedback ◽

Health Record ◽

Prospective Audit ◽

Short Period ◽

Electronic Health ◽

Prospective Audit And Feedback ◽

Bureau Of Prisons

Background: Fluoroquinolones are the perfect target for antimicrobial stewardship programs (ASPs) due to their broad-spectrum nature, poor safety profile, and frequent misuse. In April 2019, the Bureau of Prisons (BOP) created a national antimicrobial stewardship clinical pharmacist consultant program. One of the program’s main initiatives was to screen active fluoroquinolone prescriptions for appropriateness and work with providers to tailor therapy as needed. Since July 2019, pharmacist consultants have utilized a singular system-wide electronic health record (EHR) to conduct fluoroquinolone prospective audit and feedback targeting all BOP sites across the country. The objective was to assess the national impact of prospective audit and feedback on outpatient fluoroquinolone prescriptions utilizing pharmacist consultants and an integrated EHR. Method: Reviews were conducted in a federal correctional setting including 122 BOP sites with an average daily population of 167,308 inmates. The ASP consisted of 7 pharmacists, each assigned a region across the country. Consultant pharmacists were in charge of conducting daily fluoroquinolone reviews within 72 hours of the prescription being written, utilizing a singular system-wide EHR to gain remote access to newly prescribed prescriptions along with all other pertinent information (ie, clinical notes, patient profiles, laboratory, and radiology). Interventions were sent via e-mail. Total fluoroquinolone prescriptions per 1,000 inmates during the preintervention period (July 1, 2018, to September 30, 2018) were compared to the postintervention period (July 1, 2019, to September 30, 2019), after the development of the clinical consultant program. Data were also collected during the 3-month postintervention period to include total fluoroquinolone prescriptions reviewed, total recommendations sent, percentage of recommendations accepted, and intervention types. Results: In total, 833 fluoroquinolone prescriptions of 1, 264 total prescriptions written (66%)were reviewed over the 3-month postintervention period. In total,192 interventions were recommended (23%). Of the interventions recommended, 65 (34%) were accepted. The most common intervention was to stop therapy (41%), followed by changing antibiotic (37%), and shorten therapy duration (8%). Total outpatient fluoroquinolone prescriptions decreased by 1.5 prescriptions per 1,000 patients after the intervention. Conclusions: Pharmacist-driven prospective audit and feedback on a national scale utilizing a singular system-wide EHR resulted in an overall decrease in outpatient fluoroquinolone prescriptions over short period of time.Funding: NoneDisclosures: None

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Perceived efficiency impacts following electronic health record implementation: An exploratory study of an urban community health center network

International Journal of Medical Informatics ◽

10.1016/j.ijmedinf.2010.09.002 ◽

2010 ◽

Vol 79 (12) ◽

pp. 807-816 ◽

Cited By ~ 25

Author(s):

Ann Scheck McAlearney ◽

Julie Robbins ◽

Annemarie Hirsch ◽

Maria Jorina ◽

J. Phil Harrop

Keyword(s):

Electronic Health Record ◽

Community Health ◽

Health Center ◽

Exploratory Study ◽

Urban Community ◽

Community Health Center ◽

Health Record ◽

Electronic Health

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The Development and Piloting of the Ambulatory Electronic Health Record Evaluation Tool: Lessons Learned

Applied Clinical Informatics ◽

10.1055/s-0041-1722917 ◽

2021 ◽

Vol 12 (01) ◽

pp. 153-163

Author(s):

Zoe Co ◽

A. Jay Holmgren ◽

David C. Classen ◽

Lisa P. Newmark ◽

Diane L. Seger ◽

...

Keyword(s):

Decision Support ◽

Electronic Health Record ◽

Medication Safety ◽

Medication Reconciliation ◽

The United States ◽

Health Record ◽

Evaluation Tool ◽

Safety Test ◽

Electronic Health ◽

The Impact

Abstract Background Substantial research has been performed about the impact of computerized physician order entry on medication safety in the inpatient setting; however, relatively little has been done in ambulatory care, where most medications are prescribed. Objective To outline the development and piloting process of the Ambulatory Electronic Health Record (EHR) Evaluation Tool and to report the quantitative and qualitative results from the pilot. Methods The Ambulatory EHR Evaluation Tool closely mirrors the inpatient version of the tool, which is administered by The Leapfrog Group. The tool was piloted with seven clinics in the United States, each using a different EHR. The tool consists of a medication safety test and a medication reconciliation module. For the medication test, clinics entered test patients and associated test orders into their EHR and recorded any decision support they received. An overall percentage score of unsafe orders detected, and order category scores were provided to clinics. For the medication reconciliation module, clinics demonstrated how their EHR electronically detected discrepancies between two medication lists. Results For the medication safety test, the clinics correctly alerted on 54.6% of unsafe medication orders. Clinics scored highest in the drug allergy (100%) and drug–drug interaction (89.3%) categories. Lower scoring categories included drug age (39.3%) and therapeutic duplication (39.3%). None of the clinics alerted for the drug laboratory or drug monitoring orders. In the medication reconciliation module, three (42.8%) clinics had an EHR-based medication reconciliation function; however, only one of those clinics could demonstrate it during the pilot. Conclusion Clinics struggled in areas of advanced decision support such as drug age, drug laboratory, and drub monitoring. Most clinics did not have an EHR-based medication reconciliation function and this process was dependent on accessing patients' medication lists. Wider use of this tool could improve outpatient medication safety and can inform vendors about areas of improvement.

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Clinical decision support alert malfunctions: analysis and empirically derived taxonomy

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocx106 ◽

2017 ◽

Vol 25 (5) ◽

pp. 496-506 ◽

Cited By ~ 21

Author(s):

Adam Wright ◽

Angela Ai ◽

Joan Ash ◽

Jane F Wiesen ◽

Thu-Trang T Hickman ◽

...

Keyword(s):

Decision Support ◽

Electronic Health Record ◽

Medical Informatics ◽

Clinical Decision Support ◽

Quantitative Methods ◽

Clinical Decision ◽

The United States ◽

Health Record ◽

Qualitative And Quantitative Methods ◽

Electronic Health

Abstract Objective To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions. Materials and Methods We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions. Results We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common. Discussion Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS. Conclusion CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

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Use of electronic health record data from diverse primary care practices to identify and characterize patients’ prescribed common medications

Health Informatics Journal ◽

10.1177/1460458218813640 ◽

2018 ◽

Vol 26 (1) ◽

pp. 172-180 ◽

Cited By ~ 1

Author(s):

Allison M Cole ◽

Kari A Stephens ◽

Imara West ◽

Gina A Keppel ◽

Ken Thummel ◽

...

Keyword(s):

Primary Care ◽

Adverse Events ◽

Electronic Health Record ◽

Research Network ◽

Health Record ◽

Electronic Health Record Data ◽

Record Data ◽

Care Practices ◽

Electronic Health ◽

Primary Care Practices

We use prescription of statin medications and prescription of warfarin to explore the capacity of electronic health record data to (1) describe cohorts of patients prescribed these medications and (2) identify cohorts of patients with evidence of adverse events related to prescription of these medications. This study was conducted in the WWAMI region Practice and Research Network (WPRN)., a network of primary care practices across Washington, Wyoming, Alaska, Montana and Idaho DataQUEST, an electronic data-sharing infrastructure. We used electronic health record data to describe cohorts of patients prescribed statin or warfarin medications and reported the proportions of patients with adverse events. Among the 35,445 active patients, 1745 received at least one statin prescription and 301 received at least one warfarin prescription. Only 3 percent of statin patients had evidence of myopathy; 51 patients (17% of those prescribed warfarin) had a bleeding complication. Primary-care electronic health record data can effectively be used to identify patients prescribed specific medications and patients potentially experiencing medication adverse events.

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