Impact Of Electronic Health Record Research Articles

Comprehensive methodology to monitor longitudinal change patterns during EHR implementations: a case study at a large health care delivery network

ObjectiveTo test a systematic methodology to monitor longitudinal change patterns on quality, productivity, and safety outcomes during a large-scale commercial Electronic Health Record (EHR) implementation. Materials and MethodsOur method combines an interrupted time-series design with control sites and 41 consensus outcomes including quality (11 measures), productivity (20 measures), and safety (10 measures). The intervention consisted of a phased commercial EHR implementation at a large health care delivery network. Four medium-size hospitals and 39 clinics from 5 geographic regions implementing the new EHR were compared against a parallel control consisting of one medium-size and one large hospital and 10 clinics that had not implemented the new EHR at the time of this study. We collected monthly data from February 2013 to July 2017. ResultsThe proposed methodology was successfully implemented and significant changes were observed in most measured variables. A significant change attributable to the intervention was observed in 12 (29%) measures in three or more regions; in 32 (78%) measures in two or more regions; and in 40 (98%) measures in at least one region. A similar pattern (i.e., same impact in three or more regions) was detected for nine (22%) measures, a mixed pattern (i.e., same impact in two regions, and different impact in other regions) was detected for nine (22%) measures, and an inconsistent pattern (i.e., did not detect the same impact across regions) was detected for 23 (56%) measures. DiscussionUsing a formal methodology to assess changes in a set of consensus measures, we detected various patterns of impact and mixed time-sensitive effects. With an increasing adoption of EHR systems, it is critical for health care organizations to systematically monitor their EHR implementations. The proposed method provides a robust and consistent approach to monitor EHR implementations longitudinally allowing for continuous monitoring after the system becomes stable in order to avoid unexpected effects. ConclusionOur results and methodology can guide the broader medical and informatics communities by informing what and how to continuously monitor EHR impact on quality, productivity, and safety.

Changes in hospital bond ratings after the transition to a new electronic health record

To assess the impact of electronic health record (EHR) implementation on hospital finances. We analyzed the impact of EHR implementation on bond ratings and net income from service to patients (NISP) at 32 hospitals that recently implemented a new EHR and a set of controls. After implementing an EHR, 7 hospitals had a bond downgrade, 7 had a bond upgrade, and 18 had no changes. There was no difference in the likelihood of bond rating changes or in changes to NISP following EHR go-live when compared to control hospitals. Most hospitals in our analysis saw no change in bond ratings following EHR go-live, with no significant differences observed between EHR implementation and control hospitals. There was also no apparent difference in NISP. Implementation of an EHR did not appear to have an impact on bond ratings at the hospitals in our analysis.

Impact of Electronic Health Records on Long-Term Care Facilities: Systematic Review.

BackgroundLong-term care (LTC) facilities are an important part of the health care industry, providing care to the fastest-growing group of the population. However, the adoption of electronic health records (EHRs) in LTC facilities lags behind other areas of the health care industry. One of the reasons for the lack of widespread adoption in the United States is that LTC facilities are not eligible for incentives under the Meaningful Use program. Implementation of an EHR system in an LTC facility can potentially enhance the quality of care, provided it is appropriately implemented, used, and maintained. Unfortunately, the lag in adoption of the EHR in LTC creates a paucity of literature on the benefits of EHR implementation in LTC facilities.ObjectiveThe objective of this systematic review was to identify the potential benefits of implementing an EHR system in LTC facilities. The study also aims to identify the common conditions and EHR features that received favorable remarks from providers and the discrepancies that needed improvement to build up momentum across LTC settings in adopting this technology.MethodsThe authors conducted a systematic search of PubMed, Cumulative Index of Nursing and Allied Health (CINAHL), and MEDLINE databases. Papers were analyzed by multiple referees to filter out studies not germane to our research objective. A final sample of 28 papers was selected to be included in the systematic review.ResultsResults of this systematic review conclude that EHRs show significant improvement in the management of documentation in LTC facilities and enhanced quality outcomes. Approximately 43% (12/28) of the papers reported a mixed impact of EHRs on the management of documentation, and 33% (9/28) of papers reported positive quality outcomes using EHRs. Surprisingly, very few papers demonstrated an impact on patient satisfaction, physician satisfaction, the length of stay, and productivity using EHRs.ConclusionsOverall, implementation of EHRs has been found to be effective in the few LTC facilities that have implemented them. Implementation of EHRs in LTC facilities caused improved management of clinical documentation that enabled better decision making.

Electronic Immunization Alerts and Spillover Effects on Other Preventive Care.

The impact of electronic health record (EHR) immunization clinical alert systems on the delivery of other preventive services remains unknown. We assessed for spillover effects of an EHR immunization alert on delivery of 6 other preventive services, in children 18 to 30 months of age needing immunizations. We conducted a secondary data analysis, with additional primary data collection, of a randomized, historically controlled trial to improve immunization rates with EHR alerts, in an urban, primary care clinic. No significant differences were found in screening for anemia, lead, development, nutrition, and injury prevention counseling in children prompting EHR immunization alerts (n = 129), compared with controls (n = 135). Significant increases in oral health screening in patients prompting EHR alerts (odds ratio = 4.8, 95% CI = 1.8-13.0) were likely due to practice changes over time. An EHR clinical alert system targeting immunizations did not have a spillover effect on the delivery of other preventive services.

Medication Safety in Two Intensive Care Units of a Community Teaching Hospital After Electronic Health Record Implementation: Sociotechnical and Human Factors Engineering Considerations.

The aim of the study was to assess the impact of Electronic Health Record (EHR) implementation on medication safety in two intensive care units (ICUs). Using a prospective pre-post design, we assessed 1254 consecutive admissions to two ICUs before and after an EHR implementation. Each medication event was evaluated with regard to medication error (error type, medication-management stage) and impact on patient (severity of potential or actual harm). We identified 4063 medication-related events either pre-implementation (2074 events) or post-implementation (1989 events). Although the overall potential for harm due to medication errors decreased post-implementation only 2 of the 3 error rates were significantly lower post-implementation. After EHR implementation, we observed reductions in rates of medication errors per admission at the stages of transcription (0.13-0, P < 0.001), dispensing (0.49-0.16, P < 0.001), and administration (0.83-0.56, P = 0.011). Within the ordering stage, 4 error types decreased post-implementation (orders with omitted information, error-prone abbreviations, illegible orders, failure to renew orders) and 4 error types increased post-implementation (orders of wrong drug, orders containing a wrong start or stop time, duplicate orders, orders with inappropriate or wrong information). Within the administration stage, we observed a reduction of late administrations and increases in omitted administrations and incorrect documentation. Electronic Health Record implementation in two ICUs was associated with both improvement and worsening in rates of specific error types. Further safety improvements require a nuanced understanding of how various error types are influenced by the technology and the sociotechnical work system of the technology implementation. Recommendations based on human factors engineering principles are provided for reducing medication errors.

The impact of electronic health record (EHR) interoperability on immunization information system (IIS) data quality.

Objectives: To evaluate the impact of electronic health record (EHR) interoperability on the quality of immunization data in the North Dakota Immunization Information System (NDIIS). Methods: NDIIS doses administered data was evaluated for completeness of the patient and dose-level core data elements for records that belong to interoperable and non-interoperable providers. Data was compared at three months prior to electronic health record (EHR) interoperability enhancement to data at three, six, nine and twelve months post-enhancement following the interoperability go live date. Doses administered per month and by age group, timeliness of vaccine entry and the number of duplicate clients added to the NDIIS was also compared, in addition to, immunization rates for children 19 – 35 months of age and adolescents 11 – 18 years of age. Results: Doses administered by both interoperable and non-interoperable providers remained fairly consistent from pre-enhancement through twelve months post-enhancement. Comparing immunization rates for infants and adolescents, interoperable providers had higher rates both pre- and post-enhancement than non-interoperable providers for all vaccines and vaccine series assessed. The overall percentage of doses entered into the NDIIS within one month of administration varied slightly between interoperable and non-interoperable providers; however, there were significant changes between the percentage of doses entered within one day and within one week with the percentage entered within one day increasing and within one week decreasing with interoperability. The number of duplicate client records created by interoperable providers increased from 94 duplicates pre-enhancement to 10,552 at twelve months post-enhancement, while the duplicates from non-interoperable providers only increased from 300 to 637 over the same period. Of the 40 core data elements in the NDIIS, there was some difference in completeness between the interoperable versus non-interoperable providers. Only middle name, sex, county, phone number, mother’s maiden name, vaccine manufacturer, lot number and expiration date were significantly (>=5%) different between the two provider groups. Conclusions: Interoperability with provider EHRs has had an impact on NDIIS data quality. Timeliness of data entry has improved and overall doses administered have remained fairly consistent, as have the immunization rates for the providers assessed. There are more technical and non-technical interventions that will need to be accomplished by NDIIS staff and vendor to help reduce the negative impact of duplicate record creation, as well as, data completeness.

The Impact of Electronic Health Records on Risk Management of Information Systems in Australian Residential Aged Care Homes.

To obtain indications of the influence of electronic health records (EHR) in managing risks and meeting information system accreditation standard in Australian residential aged care (RAC) homes. The hypothesis to be tested is that the RAC homes using EHR have better performance in meeting information system standards in aged care accreditation than their counterparts only using paper records for information management. Content analysis of aged care accreditation reports from the Aged Care Standards and Accreditation Agency produced between April 2011 and December 2013. Items identified included types of information systems, compliance with accreditation standards, and indicators of failure to meet an expected outcome for information systems. The Chi-square test was used to identify difference between the RAC homes that used EHR systems and those that used paper records in not meeting aged care accreditation standards. 1,031 (37.4%) of 2,754 RAC homes had adopted EHR systems. Although the proportion of homes that met all accreditation standards was significantly higher for those with EHR than for homes with paper records, only 13 RAC homes did not meet one or more expected outcomes. 12 used paper records and nine of these failed the expected outcome for information systems. The overall contribution of EHR to meeting aged care accreditation standard in Australia was very small. Risk indicators for not meeting information system standard were no access to accurate and appropriate information, failure in monitoring mechanisms, not reporting clinical incidents, insufficient recording of residents' clinical changes, not providing accurate care plans, and communication processes failure. The study has provided indications that use of EHR provides small, yet significant advantages for RAC homes in Australia in managing risks for information management and in meeting accreditation requirements. The implication of the study for introducing technology innovation in RAC in Australia is discussed.

Measuring the Impact of Electronic Health Record Adoption on Charge Capture

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.

Does electronic health record use improve hospital financial performance? Evidence from panel data.

The aim of this study was to examine the impact of electronic health record (EHR) adoption on hospital financial performance. We constructed a longitudinal panel using data from the three secondary sources: (a) the 2007-2010 American Hospital Association (AHA) Annual Survey, (b) the 2007-2010 AHA Annual Survey Information Technology Supplement, and (c) the 2007-2011 Medicare Cost Reports from Centers for Medicare and Medicaid Services. Because potential financial benefits attributable to EHR adoption may take some time to accrue, we ran regressions with lags of 1 and 2 years that included hospital and year fixed effects to examine the relationship between the level of EHR adoption and three hospital financial performance measures. A change in the level of EHR adoption was not associated with changes in operating margin or return on assets within hospitals. However, total margin was significantly improved, after 2 years, in hospitals that moved from no EHR to having a comprehensive EHR in all areas of their hospital (β = 0.030, p < .034). On the other hand, hospitals that increased their level of EHR adoption but did not achieve hospital-wide comprehensive adoption did not experience changes in any financial performance measures examined. The improvements in total margin, as opposed to operating margin, are likely due to hospital incentive payments under the Health Information Technology for Economic and Clinical Health Act that are reflected in nonpatient revenues and therefore show up in total margin calculations. Thus, after 2 years of EHR adoption, hospital financial performance is observed to improve based only on meaningful use incentive payments. More research will be needed to determine whether EHR adoption impacts financial performance on a longer time horizon.

Mapping communication spaces: The development and use of a tool for analyzing the impact of EHRs on interprofessional collaborative practice

IntroductionMembers of the healthcare team must access and share patient information to coordinate interprofessional collaborative practice (ICP). Although some evidence suggests that electronic health records (EHRs) contribute to in-team communication breakdowns, EHRs are still widely hailed as tools that support ICP. If EHRs are expected to promote ICP, researchers must be able to longitudinally study the impact of EHRs on ICP across communication types, users, and physical locations. ObjectiveThis paper presents a data collection and analysis tool, named the Map of the Clinical Interprofessional Communication Spaces (MCICS), which supports examining how EHRs impact ICP over time, and across communication types, users, and physical locations. MethodsThe tool’s development evolved during a large prospective longitudinal study conducted at a Canadian pediatric academic tertiary-care hospital. This two-phased study [i.e., pre-implementation (phase 1) and post implementation (phase 2)] of an EHR employed a constructivist grounded theory approach and triangulated data collection strategies (i.e., non-participant observations, interviews, think-alouds, and document analysis). The MCICS was created through a five-step process: (i) preliminary structural development based on the use of the paper-based chart (phase 1); (ii) confirmatory review and modification process (phase 1); (iii) ongoing data collection and analysis facilitated by the map (phase 1); (iv) data collection and modification of map based on impact of EHR (phase 2); and (v) confirmatory review and modification process (phase 2). ResultsCreating and using the MCICS enabled our research team to locate, observe, and analyze the impact of the EHR on ICP, (a) across oral, electronic, and paper communications, (b) through a patient’s passage across different units in the hospital, (c) across the duration of the patient’s stay in hospital, and (d) across multiple healthcare providers. By using the MCICS, we captured a comprehensive, detailed picture of the clinical milieu in which the EHR was implemented, and of the intended and unintended consequences of the EHR’s deployment. The map supported our observations and analysis of ICP communication spaces, and of the role of the patient chart in these spaces. ConclusionsIf EHRs are expected to help resolve ICP challenges, it is important that researchers be able to longitudinally assess the impact of EHRs on ICP across multiple modes of communication, users, and physical locations. Mapping the clinical communication spaces can help EHR designers, clinicians, educators and researchers understand these spaces, appreciate their complexity, and navigate their way towards effective use of EHRs as means for supporting ICP. We propose that the MCICS can be used “as is” in other academic tertiary-care pediatric hospitals, and can be tailored for use in other healthcare institutions.

Electronic Health Record Availability and Anxiety Treatment in Office-Based Practices.

This study compared the probability of receiving anxiety treatment during a physician visit to primary care practices with and without an electronic health record (EHR). The 2007-2010 National Ambulatory Medical Care Survey was used to identify visits for anxiety (N=290). The outcome was receipt of anxiety treatment. The independent variable was the presence of a fully functioning EHR. Logistic regression was used to conduct the analysis. Patients who were seen in practices with a fully functioning EHR had lower odds of being offered antianxiety medication (adjusted odds ratio [AOR]=.37, 95% confidence interval [CI]=.15-.90, p=.028), mental health counseling (AOR=.43, CI=.18-1.04, p=.061), and any anxiety treatment (AOR=.40, CI=.15-1.05, p=.062) compared with patients at practices without a fully functioning EHR. EHRs may have a negative impact on the delivery of care for anxiety during primary care visits. Future studies should monitor the impact of EHRs on delivery and quality of care.

Impact of Electronic Health Records on the Hospital Bed Occupancy Rates in Surgical Units in France: Results from the E-SI (PREPS-SIPS) Study

Impact of Electronic Health Records on the Hospital Bed Occupancy Rates in Surgical Units in France: Results from the E-SI (PREPS-SIPS) Study

The Growing Gap in Electronic Medical Record Satisfaction Between Clinicians and Information Technology Professionals: Issues of Most Concern and Suggested Remediations.

With the alarming statistics concerning the quality of national health care, it is hoped that electronic health records (EHRs) will reduce inefficiencies associated with medical delivery and improve patient safety. This study reports the results of a survey that demonstrates a pattern in EHR system implementation that indicates that health-care information technology decisions are based more on the preferences of information technology professionals (ITPs) and hospital administrators than clinicians. We present survey data highlighting the growing discrepancy in EHR-related satisfaction between clinicians and ITPs. We conducted a literature search to identify major barriers that must be overcome to achieve optimal EHR benefits. We summarize our recommendations in order to maximize the favorable impact of EHRs on the health-care system. The existing gap in postimplementation EHR satisfaction ratings between ITPs and clinicians reveals an underlying systematic problem. Electronic medical record vendors perceive administrators and ITPs as the "buyers" for many EHR systems, and their needs are given higher priority than those of clinicians. This possibly may lead to the lack of clinically optimized EHRs, with systems often presenting as rigid and standardized with a limited exchange of health information. EHRs have the potential to become a powerful tool that may improve many processes related to health care, including quality, safety, and economical aspects. The involvement of physicians in every step of the process, from electronic medical record selection to acquisition, implementation, and ongoing optimization, is crucial for enabling the achievement of the medical organization's mission.

Trends in ICU Quality After Implementation of an Electronic Health Record

Trends in ICU Quality After Implementation of an Electronic Health Record

Up to Speed: A Role for Trainees in Advancing Health Information Technology.

* Abbreviations: EHR — : electronic health record HIT — : health information technology The six-year old wheezed for two days before the steroids took full effect. As his airways relaxed and his retractions calmed, we prepared to send him home. When rounds finished, I ran to a computer and started the tedious process of discharge paperwork. As a last step, I leafed through a 14-page instructional binder and clicked through the dozen checkboxes required to create his asthma action plan. When I started residency, I expected that asthma care would be a “bread and butter” component of my learning. I did not anticipate, however, the time I would spend mastering the multi-click process for generating asthma action plans, among many other daily computer tasks. I certainly did not expect to spend more time working with clunky software than I spent interacting with my patients and their families. The goal of utilizing electronic health records (EHRs) in medicine is to deliver high-quality care more safely and effectively. Too often, we fall short of that goal. Whether completing asthma action plans, reconciling medications, or simply dealing with a frozen computer, many of the current digital tools in medicine fail to achieve their potential. As a result, trainees (like many other providers) are becoming increasingly frustrated. The Institute of Medicine’s 2011 report1 pointed out the quality and safety deficiencies inherent in EHR workflow and highlighted the need to examine and address the impact of EHRs in these areas. The Joint Commission has also published two “Sentinel Event Alerts,”2,3 cautioning providers about the surprisingly high incidence of … Address correspondence to James Xie, MD, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA 02115. E-mail: james.xie{at}childrens.harvard.edu

The impact of electronic health records on healthcare quality: a systematic review and meta-analysis.

To assess the impact of electronic health record (EHR) on healthcare quality, we hence carried out a systematic review and meta-analysis of published studies on this topic. PubMed, Web of Knowledge, Scopus and Cochrane Library databases were searched to identify studies that investigated the association between the EHR implementation and process or outcome indicators. Two reviewers screened identified citations and extracted data according to the PRISMA guidelines. Meta-analysis was performed using the random effects model for each indicator. Heterogeneity was quantified using the Cochran Q test and I2 statistics, and publication bias was assessed using the Egger's test. Of the 23 398 citations identified, 47 articles were included in the analysis. Meta-analysis showed an association between EHR use and a reduced documentation time with a difference in mean of -22.4% [95% confidence interval (CI) = -38.8 to -6.0%; P < 0.007]. EHR resulted also associated with a higher guideline adherence with a risk ratio (RR) of 1.33 (95% CI = 1.01 to 1.76; P = 0.049) and a lower number of medication errors with an overall RR of 0.46 (95% CI = 0.38 to 0.55; P < 0.001), and adverse drug effects (ADEs) with an overall RR of 0.66 (95% CI = 0.44 to 0.99; P = 0.045). No association with mortality was evident (P = 0.936). High heterogeneity among the studies was evident. Publication bias was not evident. EHR system, when properly implemented, can improve the quality of healthcare, increasing time efficiency and guideline adherence and reducing medication errors and ADEs. Strategies for EHR implementation should be therefore recommended and promoted.

The Practice Impact of Electronic Health Record System Implementation Within a Large Multispecialty Ophthalmic Practice.

Given the lack of previous reports examining the impact of electronic health record (EHR) system migration in ophthalmology, a study evaluating the practice and economic effect of implementing an EHR into an ophthalmic practice is warranted. To examine the clinical and economic impact of EHR system implementation into a large multispecialty ophthalmic practice. A retrospective case-control study was conducted comparing the pre-EHR and post-EHR time periods at the Cole Eye Institute, Cleveland, Ohio. Eight months were spent prior to implementation personalizing and customizing the system to enable advanced charting functions (July 1, 2011, to March 1, 2012). The periods were compared regarding total revenue, total visit volume, revenue per visit, coding volumes, and the number of diagnostic tests and procedures performed. In addition, the total costs of the EHR implementation and the expected return in EHR incentive payments were evaluated. Data analysis was performed from April 1, 2011, through April 5, 2013. Net revenue, patient volume, revenue to volume ratio, diagnostic and procedure volume, capital and implementation costs, EHR incentive payments received, and coding volumes (including eye and evaluation and management [E/M] codes). A total of 28,161 patient encounters were identified (13,969 in the pre-EHR period and 14,191 in the post-EHR period). No significant change was identified with total net fiscal revenue between the periods (median, -$44,372 per month; 25th to 75th interquartile range [IQR], -$103,850 to $83,126; P = .42). No significant change in patient volume (median, +217.0; IQR, -511.5 to 812.0; P = .57) or revenue per visit volume (median, -$7; IQR, -$9 to -$1; P = .20) was identified. The volume of diagnostic tests and procedures billed was unchanged after conversion (median, +93; IQR, -20 to 235; P = .13). Overall use of eye codes declined (-15.7%) and use of E/M codes increased (14.7%) following EHR implementation (P < .001). The composition of eye codes showed a 2% change toward comprehensive codes over intermediate codes after implementation, but only the composition of new E/M codes increased (42.6%) (P < .001 for both values). Total capital costs amounted to $1,571,864, and personnel costs amounted to $1,514,334. A cumulative amount of $983,103 from meaningful use attestation is expected by 2016. The analyses conducted in this study did not identify significant differences in revenue or productivity following EHR conversion in this clinical setting. The EHR incentive payments did not offset costs of implementation.

Lack of Impact of Electronic Health Records on Quality of Care and Outcomes for Ischemic Stroke

BackgroundElectronic health records (EHRs) may be key tools for improving the quality of health care, particularly for conditions for which guidelines are rapidly evolving and timely care is critical, such as ischemic stroke. ObjectivesThe goal of this study was to determine whether hospitals with EHRs differed on quality or outcome measures for ischemic stroke from those without EHRs. MethodsWe studied 626,473 patients from 1,236 U.S. hospitals in Get With the Guidelines-Stroke (GWTG-Stroke) from 2007 through 2010, linked with the American Hospital Association annual survey to determine the presence of EHRs. We conducted patient-level logistic regression analyses for each of the outcomes of interest. ResultsA total of 511 hospitals had EHRs by the end of the study period. Hospitals with EHRs were larger and were more often teaching hospitals and stroke centers. After controlling for patient and hospital characteristics, patients admitted to hospitals with EHRs had similar odds of receiving “all-or-none” care (odds ratio [OR]: 1.03; 95% CI: 0.99 to 1.06; p = 0.12), of discharge home (OR: 1.02; 95% CI: 0.99 to 1.04; p = 0.15), and of in-hospital mortality (OR: 1.01; 95% CI: 0.96 to 1.05; p = 0.82). The odds of having a length of stay >4 days was slightly lower at hospitals with EHRs (OR: 0.97; 95% CI: 0.95 to 0.99; p = 0.01). ConclusionsIn our sample of GWTG-Stroke hospitals, EHRs were not associated with higher-quality care or better clinical outcomes for stroke care. Although EHRs may be necessary for an increasingly high-tech, transparent healthcare system, as currently implemented, they do not appear to be sufficient to improve outcomes for this important disease.

EHealth 2015 Special Issue: Impact of Electronic Health Records on the Completeness of Clinical Documentation Generated during Diabetic Retinopathy Consultations

SummaryBackground: Two years ago, the Diabetic Retinopathy (DRP) and Traumatology clinic of the Department of Ophthalmology and Optometrics at the Medical University of Vienna, Austria switched from paper-based to electronic health records. A customized electronic health record system (EHR-S) was implemented.Objectives: To assess the completeness of information documented electronically compared with manually during patient visits.Methods: The Preferred Practice Pattern for Diabetic Retinopathy published by the American Academy of Ophthalmology was distilled into a list of medical features grouped into categories to be assessed and documented during the management of patients with DRP. The last seventy paper-based records and all electronic records generated since the switch were analyzed and graded for the presence of features on the list and the resulting scores compared.Results: In all categories, clinical documentation was more complete in the EHR group.Conclusions: In our setting, the implementation of an EHR-S showed a statistically significant positive impact on documentation completeness.Citation: Mitsch C, Huber P, Kriechbaum K, Scholda C, Duftschmid G, Wrba T, Schmidt-Erfurth U. Impact of Electronic Health Records on the Completeness of Clinical Documentation Generated during Diabetic Retinopathy Consultations. Appl Clin Inform 2015; 6: 478–487http://dx.doi.org/10.4338/ACI-2015-03-RA-0028

Quality Outcomes in the Surgical Intensive Care Unit after Electronic Health Record Implementation

The electronic health record (EHR) is increasingly viewed as a means to provide more coordinated, patient-centered care. Few studies consider the impact of EHRs on quality of care in the intensive care unit (ICU) setting. To evaluate key quality measures of a surgical intensive care unit (SICU) following implementation of the Epic EHR system in a tertiary hospital. A retrospective chart review was undertaken to record quality indicators for all patients admitted to the SICU two years before and two years after EHR implementation. Data from the twelve-month period of transition to EHR was excluded. We collected length of stay, mortality, central line associated blood stream infection (CLABSI) rates, Clostridium difficile (C. diff.) colitis rates, readmission rates, and number of coded diagnoses. To control for variation in the patient population over time, the case mix indexes (CMIs) and APACHE II scores were also analyzed. There was no significant difference in length of stay, C. diff. colitis, readmission rates, or case mix index before and after EHR. After EHR implementation, the rate of central line blood stream infection (CLABSI) per 1 000 catheter days was 85% lower (2.16 vs 0.39; RR, 0.18; 95% CI, 0.05 to 0.61, p < .005), and SICU mortality was 28% lower (12.2 vs 8.8; RR, 1.35; 95% CI, 1.06 to 1.71, p < .01). Moreover, after EHR there was a significant increase in the average number of coded diagnoses from 17.8 to 20.8 (p < .000). EHR implementation was statistically associated with reductions in CLABSI rates and SICU mortality. The EHR had an integral role in ongoing quality improvement endeavors which may explain the changes in CLABSI and mortality, and this invites further study of the impact of EHRs on quality of care in the ICU.