scholarly journals Two-year longitudinal assessment of physicians’ perceptions after replacement of a longstanding homegrown electronic health record: does a J-curve of satisfaction really exist?

2016 ◽  
Vol 24 (e1) ◽  
pp. e157-e165 ◽  
Author(s):  
David A Hanauer ◽  
Greta L Branford ◽  
Grant Greenberg ◽  
Sharon Kileny ◽  
Mick P Couper ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Physician Satisfaction ◽  
Health Record ◽  
Longitudinal Assessment ◽  
Safety Communication ◽  
J Curve ◽  
Exam Room ◽  
Ehr Adoption ◽  
Electronic Health ◽  
Prospective Longitudinal

This report describes a 2-year prospective, longitudinal survey of attending physicians in 3 clinical areas (family medicine, general pediatrics, internal medicine) who experienced a transition from a homegrown electronic health record (EHR) to a vendor EHR. Participants were already highly familiar with using EHRs. Data were collected 1 month before and 3, 6, 13, and 25 months post implementation. Our primary goal was to determine if perceptions followed a J-curve pattern in which they initially dropped but eventually surpassed baseline measures. A J-curve was not found for any measures, including workflow, safety, communication, and satisfaction. Only the reminders and alerts measure dropped and then returned to baseline (U-curve); a few remained flatlined. Most dropped and remained below baseline (L-curve). The only measure that remained above baseline was documenting in the exam room with the patient. This study adds to the literature about current controversies surrounding EHR adoption and physician satisfaction.

scholarly journals A Two-Year Longitudinal Assessment of Ophthalmologists’ Perceptions after Implementing an Electronic Health Record System

2016 ◽  
Vol 07 (04) ◽  
pp. 930-945 ◽  
Author(s):  
Joshua Ehrlich ◽  
Monica Michelotti ◽  
Taylor Blachley ◽  
Kai Zheng ◽  
Mick Couper ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Electronic Health Record System ◽  
Health Record ◽  
Longitudinal Assessment ◽  
Record System ◽  
J Curve ◽  
Before And After ◽  
Significant Change ◽  
Electronic Health ◽  
Survey Responses

SummaryObjectives To understand the attitudes and perceptions of ophthalmologists toward an electronic health record (EHR) system, before and after its clinical implementation.Methods Ophthalmologists at a single large academic ophthalmology department were surveyed longitudinally before and after implementation of a new EHR system. The survey measured ophthalmologists’ attitudes toward implementation of a new EHR. Questions focused on satisfaction, efficiency, and documentation. All attending physicians (between 56 and 61 at various time points) in the University of Michigan Department of Ophthalmology and Visual Sciences were surveyed. We plotted positive responses to survey questions and assessed whether perceptions followed a J-curve with an initial decrease followed by an increase surpassing pre-implementation levels.Results Survey responses were received from 32 (52%) ophthalmologists pre-implementation, and 28 (46%) at 3 months, 35 (57%) at 7 months, 40 (71%) at 13 months and 39 (67%) at 24 months post-implementation. After EHR implementation respondents were more likely to express concerns about their ability to create high-quality documentation (p<0.01) and the impact of an electronic health record on meaningful patient interaction (p<0.01). Physicians did not report a significant change in the amount of time spent documenting outside of regular clinical work hours (p=0.54) or on their clinic efficiency and workflow (p=0.97). There was no significant change in overall job satisfaction during the study period (p=0.69). We did not observe a J-curve for any of the survey responses analyzed.Conclusions As ophthalmology practices continue to transition to EHRs, adapting them to their specific culture and needs is important to maintain efficiency and user satisfaction. This study identifies areas of concern to ophthalmologists that may be addressed through education of physicians and customization of software as other practices move forward with EHR implementation.Citation: Ehrlich JR, Michelotti M, Blachley TS, Zheng K, Couper MP, Greenberg GM, Kileny S, Branford GL, Hanauer DA, Weizer JS. A two-year longitudinal assessment of ophthalmologists’ perceptions after implementing an electronic health record system.

scholarly journals Drivers of expectations: Why are Norwegian general practitioners skeptical of a prospective electronic health record?

2021 ◽  
Vol 27 (1) ◽  
pp. 146045822098729
Author(s):  
Morten Hertzum ◽  
Gunnar Ellingsen ◽  
Line Melby
Keyword(s):  
Electronic Health Record ◽  
General Practitioners ◽  
Current System ◽  
Implementation Process ◽  
Health Record ◽  
Early Implementation ◽  
Ehr Adoption ◽  
Electronic Health

While expectations are well-known drivers of electronic health record (EHR) adoption, the drivers of expectations are more elusive. On the basis of interviews with general practitioners (GPs), we investigate how the early implementation process drives their expectations of an EHR that is being implemented in Norway. The GPs’ expectations of the prospective EHR are driven by (a) satisfying experiences with their current system, (b) the transfer of others’ experiences with the prospective EHR, (c) a sense of alignment, or lack thereof, with those in charge of the implementation process, (d) uncertainty about the inclusion of GP needs, and (e) competing technological futures. To manage expectations, starting early is important. Mismanaged expectations produce a need for convincing people to reverse their expectations. This appears to be the situation in Norway, where the GPs are currently skeptical of the prospective EHR.

scholarly journals Measuring Electronic Health Record Use in Primary Care: A Scoping Review

2018 ◽  
Vol 09 (01) ◽  
pp. 015-033 ◽  
Author(s):  
Michael Huang ◽  
Candace Gibson ◽  
Amanda Terry
Keyword(s):  
Primary Care ◽  
Electronic Health Record ◽  
Scoping Review ◽  
Web Sites ◽  
Health Record ◽  
Current State ◽  
Level Of Use ◽  
Ehr Adoption ◽  
Electronic Health ◽  
Citation Databases

Background Simple measures of electronic health record (EHR) adoption may be inadequate to evaluate EHR use; and positive outcomes associated with EHRs may be better gauged when varying degrees of EHR use are taken into account. In this article, we aim to assess the current state of the literature regarding measuring EHR use. Objective This article conducts a scoping review of the literature to identify and classify measures of primary care EHR use with a focus on the Canadian context. Methods We conducted a scoping review. Multiple citation databases were searched, as well as gray literature from relevant Web sites. Resulting abstracts were screened for inclusion. Included full texts were reviewed by two authors. Data from the articles were extracted; we synthesized the findings. Subsequently, we reviewed these results with seven EHR stakeholders in Canada. Results Thirty-seven articles were included. Eighteen measured EHR function use individually, while 19 incorporated an overall level of use. Eight frameworks for characterizing overall EHR use were identified. Conclusion There is a need to create standardized frameworks for assessing EHR use.

Impact of room pooling and electronic health record on patient (pt) wait time, clinic work flow, and pts’/providers’ satisfaction.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18191-e18191
Author(s):  
Saroj Vadhan-Raj ◽  
Xiao Zhou ◽  
Meyyammai Narayanan ◽  
Shawn J Janarthanan ◽  
Mary Daniel ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Wait Time ◽  
Work Flow ◽  
Wait Times ◽  
Health Record ◽  
Allocation Model ◽  
Exam Room ◽  
Negative Effect ◽  
Electronic Health ◽  
The Impact

e18191 Background: Excessive pt wait time can have negative effect on clinic work flow and on pts/ providers satisfaction. Increasing pt volume and limited clinic capacity can lead to long wait times for pts. The purpose of this two-part study was to evaluate the impact of Room Pooling Model (RPM) instead of Room Allocation Model (Part 1) and Electronic Health Record (EHR) on pt wait times in clinic and pts’/providers’ satisfaction (Part 2). Methods: The time studies and pts’/providers’ wait time satisfaction surveys were carried out over 2 weeks before (baseline) and 8 weeks after the implementation of RPM (Part 1), prior to the new EHR system, and 6 months after the implementation of EHR (part 2). All times of when pts, mid-level providers (MLP), and doctors (MDs) entered and exited the exam rooms were collected for 887 pts seen during the clinic. Data was analyzed using JMP and SAS. Results: As described earlier (ASCO 2016, abst 6595), the RPM was associated with increase in the proportion of pts seen by MDs within 30 min from the time roomed in the exam room and improvement in pts’/provider’s satisfaction. Post EHR, there were delays with decrease in the proportion of pts seen within 30 min from the time roomed in. Although the pt satisfaction did not change significantly, the number of times MDs had to wait for an open exam room increased from 8% (5/65) to 24% (14/59, p=0.01). The impact of RPM and EHR on pt times are shown below. The delays to see MDs after EHR were associated with longer time spent with the nurse (from median 4 to 7 min) and delays in seeing MLPs (from 11 to 18 min). Conclusions: These findings indicate that RPM can improve pt wait times. During initial stages of EHR implementation, the increase in pt wait time and reduced clinical efficiencies can be related to learning, and adapting to the new system. These data can be useful to design interventions that can target the areas of delays such as training and redesigning workflow to improve the clinical efficiency. [Table: see text]

Predictors of Physician Satisfaction among Electronic Health Record System Users

2010 ◽  
Vol 32 (1) ◽  
pp. 35-41 ◽  
Author(s):  
Nir Menachemi ◽  
Thomas Powers ◽  
David W. Au ◽  
Robert G. Brooks
Keyword(s):  
Electronic Health Record ◽  
Physician Satisfaction ◽  
Electronic Health Record System ◽  
Health Record ◽  
Record System ◽  
Electronic Health

scholarly journals Physician Satisfaction Following Electronic Health Record Adoption in Three Massachusetts Communities

2012 ◽  
Vol 1 (2) ◽  
pp. e12 ◽  
Author(s):  
Leonie Heyworth ◽  
Fang Zhang ◽  
Chelsea A Jenter ◽  
Rachel Kell ◽  
Lynn A Volk ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Physician Satisfaction ◽  
Health Record ◽  
Electronic Health

scholarly journals The electronic health record audit file: the patient is waiting

2016 ◽  
Vol 24 (e1) ◽  
pp. e28-e34 ◽  
Author(s):  
Annemarie G Hirsch ◽  
J B Jones ◽  
Virginia R Lerch ◽  
Xiaoqin Tang ◽  
Andrea Berger ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Wait Time ◽  
Clinical Encounter ◽  
Health Record ◽  
Clinical Workflow ◽  
Waiting Room ◽  
Exam Room ◽  
Physician Time ◽  
Nurse Time ◽  
Electronic Health

Objective: We describe how electronic health record (EHR) audit files can be used to understand how time is spent in primary care (PC). Materials/methods: We used audit file data from the Geisinger Clinic to quantify elements of the clinical workflow and to determine how these times vary by patient and encounter factors. We randomly selected audit file records representing 36 437 PC encounters across 26 clinic locations. Audit file data were used to estimate duration and variance of: (1) time in the waiting room, (2) nurse time with the patient, (3) time in the exam room without a nurse or physician, and (4) physician time with the patient. Multivariate modeling was used to test for differences by patient and by encounter features. Results: On average, a PC encounter took 54.6 minutes, with 5 minutes of nurse time, 15.5 minutes of physician time, and the remaining 62% of the time spent waiting to see a clinician or check out. Older age, female sex, and chronic disease were associated with longer wait times and longer time with clinicians. Level of service and numbers of medications, procedures, and lab orders were associated with longer time with clinicians. Late check-in and same-day visits were associated with shorter wait time and clinician time. Conclusions: This study provides insights on uses of audit file data for workflow analysis during PC encounters. Discussion: Scalable ways to quantify clinical encounter workflow elements may provide the means to develop more efficient approaches to care and improve the patient experience.

Measuring the Impact of Electronic Health Record Adoption on Charge Capture

2016 ◽  
Vol 74 (5) ◽  
pp. 582-594 ◽  
Author(s):  
Nicholas Edwardson ◽  
Bita A. Kash ◽  
Ramkumar Janakiraman
Keyword(s):  
Primary Care ◽  
Electronic Health Record ◽  
Fixed Effects ◽  
Pediatric Primary Care ◽  
Health Record ◽  
Care Network ◽  
Collection Data ◽  
Ehr Adoption ◽  
Electronic Health ◽  
The Impact

We examine the impact of electronic health record (EHR) adoption on charge capture—the ability of providers to properly ensure that billable services are accurately recorded and reported for payment. Drawing on billing and practice management data from a large, integrated pediatric primary care network that was previously a paper-based organization, monthly encounter, charge, and collection data were collected from 2008 through 2013. Two-level fixed effects models were built to test the impact of EHR adoption on charge capture. The introduction of the EHR to the pediatric primary care network was independently associated with an $11.09 increase in average per patient charges, an $11.49 increase in average per patient collections, and an improvement in physicians’ charge-to-collection ratios. Despite high initial outlays and operating costs related to EHR adoption, these results suggest organizations may recoup many of these costs over the long term.

scholarly journals A systematic review of the use of the electronic health record for patient identification, communication, and clinical support in palliative care

JAMIA Open ◽  
2018 ◽  
Vol 1 (2) ◽  
pp. 294-303 ◽  
Author(s):  
Ruth A Bush ◽  
Alexa Pérez ◽  
Tanja Baum ◽  
Caroline Etland ◽  
Cynthia D Connelly
Keyword(s):  
Systematic Review ◽  
Palliative Care ◽  
Electronic Health Record ◽  
Original Research ◽  
Health Record ◽  
Clinical Workflow ◽  
Patient Identification ◽  
Patient Reported ◽  
Electronic Health ◽  
Prospective Longitudinal

Abstract Objectives Globally, healthcare systems are using the electronic health record (EHR) and elements of clinical decision support (CDS) to facilitate palliative care (PC). Examination of published results is needed to determine if the EHR is successfully supporting the multidisciplinary nature and complexity of PC by identifying applications, methodology, outcomes, and barriers of active incorporation of the EHR in PC clinical workflow. Methods A systematic review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The data sources PubMed, CINAL, EBSCOhost, and Academic Search Premier were used to identify literature published 1999–2017 of human subject peer-reviewed articles in English containing original research about the EHR and PC. Results The search returned 433 articles, 30 of which met inclusion criteria. Most studies were feasibility studies or retrospective cohort analyses; one study incorporated prospective longitudinal mixed methods. Twenty-three of 30 (77%) were published after 2014. The review identified five major areas in which the EHR is used to support PC. Studies focused on CDS to: identify individuals who could benefit from PC; electronic advanced care planning (ACP) documentation; patient-reported outcome measures (PROMs) such as rapid, real-time pain feedback; to augment EHR PC data capture capabilities; and to enhance interdisciplinary communication and care. Discussion Beginning in 2015, there was a proliferation of articles about PC and EHRs, suggesting increasing incorporation of and research about the EHR with PC. This review indicates the EHR is underutilized for PC CDS, facilitating PROMs, and capturing ACPs.

Sign in / Sign up

Export Citation Format

Share Document