A progress report on electronic health records in U.S. hospitals

Impact of Electronic Health Record Use on Cognitive Load and Burnout Among Clinicians: Narrative Review

The cognitive load theory suggests that completing a task relies on the interplay between sensory input, working memory, and long-term memory. Cognitive overload occurs when the working memory's limited capacity is exceeded due to excessive information processing. In health care, clinicians face increasing cognitive load as the complexity of patient care has risen, leading to potential burnout. Electronic health records (EHRs) have become a common feature in modern health care, offering improved access to data and the ability to provide better patient care. They have been added to the electronic ecosystem alongside emails and other resources, such as guidelines and literature searches. Concerns have arisen in recent years that despite many benefits, the use of EHRs may lead to cognitive overload, which can impact the performance and well-being of clinicians. We aimed to review the impact of EHR use on cognitive load and how it correlates with physician burnout. Additionally, we wanted to identify potential strategies recommended in the literature that could be implemented to decrease the cognitive burden associated with the use of EHRs, with the goal of reducing clinician burnout. Using a comprehensive literature review on the topic, we have explored the link between EHR use, cognitive load, and burnout among health care professionals. We have also noted key factors that can help reduce EHR-related cognitive load, which may help reduce clinician burnout. The research findings suggest that inadequate efforts to present large amounts of clinical data to users in a manner that allows the user to control the cognitive burden in the EHR and the complexity of the user interfaces, thus adding more "work" to tasks, can lead to cognitive overload and burnout; this calls for strategies to mitigate these effects. Several factors, such as the presentation of information in the EHR, the specialty, the health care setting, and the time spent completing documentation and navigating systems, can contribute to this excess cognitive load and result in burnout. Potential strategies to mitigate this might include improving user interfaces, streamlining information, and reducing documentation burden requirements for clinicians. New technologies may facilitate these strategies. The review highlights the importance of addressing cognitive overload as one of the unintended consequences of EHR adoption and potential strategies for mitigation, identifying gaps in the current literature that require further exploration.

A Scoping Review on Learning Health Networks Available in Pediatric Surgical Specialties

BACKGROUND

Learning health networks (LHN) are consortia of institutions that collaborate and embrace the elements of the learning health system (LHS), including quality improvement, education, research, and stakeholder involvement. Their ultimate goal is rapid information dissemination in clinical care. Pediatric surgical specialties perform unique yet high-impact procedures that could benefit from LHN, thereby improving surgical outcomes and care through LHS approaches. Consequently, health system leaders should be aware of LHN and their importance in enhancing surgical care and improving outcomes. This scoping review aims to map and characterize the existing LHN applied in pediatric surgical specialties.

METHODS

A systematic literature search was performed on Medline, EMBASE, and Scopus up to June 2022, with an update search conducted in May 2023. Additionally, Google Scholar, ProQuest and inquiry from topic experts were used for cross-referencing relevant review articles to identify grey literature. This scoping review was conducted and reported according to the PRISMA-scoping review extension.

RESULTS

A total of 56 publications for 19 LHN were identified and included in this scoping review. Out of 19 identified LHN in pediatric surgical specialties, 18 were organized in North America. Eight of the networks are related to pediatric general surgery and another eight were related to pediatric transplantation. The 16 out of 19 LHN were initiated after 2001. To date, only eight of the LHNs generated reports of comparative improved outcomes.

CONCLUSION

This scoping review provides an overview of the available LHNs in pediatric surgical specialties. Over the past decade, several pediatric surgical specialties have embraced the principles of learning health systems, forming inter-institutional collaborations that utilize information technology to generate big data on patient-level clinical information, engage in quality improvement cycles, adopt evidence-based practices, and actively involve patients and stakeholders.

LEVEL OF EVIDENCE

IV.

Comparison of guideline concordant antibiotic prophylaxis in Veterans Affairs and non-Veterans Affairs dental settings among those with cardiac conditions or prosthetic joints

BACKGROUND

No research has been conducted to assess whether antibiotic prophylaxis prescribing differs by dental setting. Therefore, the goal of this study was to compare the prescribing of antibiotic prophylaxis in Veterans Affairs (VA) and non-Veterans Affairs settings.

METHODS

This was a retrospective study of veteran and non-veteran dental patients with cardiac conditions or prosthetic joints between 2015-2017. Multivariable log binomial regression analysis was conducted to compare concordant prescribing by setting with a sub-analysis for errors of dosing based on antibiotic duration (i.e., days prescribed).

RESULTS

A total of 61,124 dental visits that received a prophylactic antibiotic were included. Most were male (61.0%), and 55 years of age or older (76.2%). Nearly a third (32.7%) received guideline concordant prophylaxis. VA dental settings had a lower prevalence of guideline concordant prescribing compared to non-VA settings in unadjusted results (unadjusted prevalence ratio [uPR] = 0.92, 95% CI: 0.90-0.95). After adjustment, prevalence of guideline concordant prescribing was higher in those with prosthetic joints in the VA setting (adjusted prevalence ratio [aPR] = 1.73, 95% CI: 1.59-1.88), with no difference identified in those without a prosthetic joint (aPR = 0.99, 95% CI: 0.96-1.01). Concordance of dosing was higher in VA compared to non-VA settings (aPR = 1.11, 95% CI: 1.07-1.15).

CONCLUSIONS

VA has a higher prevalence of guideline concordant prescribing among those with prosthetic joints and when assessing dosing errors. Though the presence of an integrated electronic health record (EHR) may be contributing to these differences, other system or prescriber-related factors may be responsible. Future studies should focus on to what extent the integrated EHR may be responsible for increased guideline concordant prescribing in the VA setting.

The Special Measures for Quality and Challenged Provider Regimes in the English NHS: A Rapid Evaluation of a National Improvement Initiative for Failing Healthcare Organisations

BACKGROUND

There is limited knowledge about interventions used for the improvement of low-performing healthcare organisations and their unintended consequences. Our evaluation sought to understand how healthcare organisations in the National Health Service (NHS) in England responded to a national improvement initiative (the Special Measures for Quality [SMQ] and challenged provider [CP] regimes) and its perceived impact on achieving quality improvements (QIs).

METHODS

Our evaluation included national-level interviews with key stakeholders involved in the delivery of SMQ (n=6); documentary analysis (n=20); and a qualitative study based on interviews (n=60), observations (n=8) and documentary analysis (n=291) in eight NHS case study sites. The analysis was informed by literature on failure, turnaround and QI in organisations in the public sector.

RESULTS

At the policy level, SMQ/CP regimes were intended to be "support" programmes, but perceptions of the interventions at hospital level were mixed. The SMQ/CP regimes tended to consider failure at an organisational level and turnaround was visualised as a linear process. There was a negative emotional impact reported by staff, especially in the short-term. Key drivers of change included: engaged senior leadership teams, strong clinical input and supportive external partnerships within local health systems. Trusts focused efforts to improve across multiple domains with particular investment in improving overall staff engagement, developing an open, listening organisational culture and better governance to ensure clinical safety and reporting.

CONCLUSION

Organisational improvement in healthcare requires substantial time to embed and requires investment in staff to drive change and cultivate QI capabilities at different tiers. The time this takes may be underestimated by external 'turn-around' interventions and performance regimes designed to improve quality in the short-term and which come at an emotional cost for staff. Shifting an improvement focus to the health system or regional level may promote sustainable improvement across multiple organisations over the long-term.

A Retrospective Cohort Study Evaluating the Association Between Implementation of a Digital Care Plan and Hospitalization Rates for Home Care Residents in the United Kingdom

Cera, a homecare provider, uses digital care plans (DCP), to streamline the provision of home care. DCP rollout is part of a larger digitization initiative, including carer visit reports collected through a mobile app and branch actions recorded in a web application supported by a secure central database. This retrospective cohort study aimed to assess the association of a DCP rollout with service user hospitalization rates. his study utilized retrospective data from 2 groups of service users, those for whom their first 30 days of Cera membership occurred prior to DCP rollout (pre-DCP group) versus those whose first 30 days of Cera membership occurred after DCP rollout (post-DCP group). The 30-day hospitalization rate was the primary outcome measure and was determined through a combination of carer reports, reporting from service users or their families, and branch staff follow-up. There were 55 hospitalizations among 392 users in the pre-DCP group in the 30 days after joining Cera (14.0% hospitalization rate), compared to 23 hospitalizations among 297 users in the post-DCP group (7.7% hospitalization rate). This represented a significant reduction in hospitalizations in the post-DCP group (6.3% absolute difference in hospitalization rate; 45% relative reduction; P < .001). This result was robust to multiple sensitivity analyses. The implementation of a DCP was associated with a 45% relative reduction in the 30-day hospitalization rate for new service users when compared to pre-DCP enrollment. These benefits could be further amplified by combining the DCP with additional initiatives aimed at the prediction and prevention of avoidable hospitalizations.

Association of Hospital Interoperable Data Sharing With Alternative Payment Model Participation

Importance

Interoperable patient data exchange across hospitals remains an important policy goal for reducing costs and improving the quality of care. Congress designated 2018 as the goal for nationwide interoperability, and policy makers hoped that aligning financial incentives via alternative payment models (APMs) would help achieve that goal.

Objective

To measure interoperability progress since 2014, assess the association between alternative payment model participation and hospital engagement in interoperable data sharing from 2014 to 2018, and evaluate hospital-reported barriers to interoperability in 2018.

Design Setting and Participants

This cohort study included nonfederal acute care hospitals in the US from January 2014 to December 2018 that responded to the American Hospital Association Annual Survey. Data were analyzed from October 2019 through March 2021.

Exposures

Participation in an APM, including accountable care organizations, bundled payments, or patient-centered medical homes.

Main Outcomes and Measures

Hospital engagement in all 4 domains of interoperability: finding/querying for data, sending data electronically, receiving data electronically, and integrating electronic patient data from external care delivery organizations.

Results

The sample included 3928 hospitals in the US from January 2014 to December 2018. Progress across interoperability domains was uneven, 2430 (88.3%) hospitals sending and 2115 (76.9%) receiving patient data electronically in 2018. However, only 1249 (45.4%) hospitals engaged in all 4 domains of interoperability in 2018, and growth between 2014 and 2018 was slow. There was no evidence that participation in APMs was associated with interoperability, with multivariate models suggesting that participation in an APM was associated with only a non-statistically significant 1-percentage point increase in interoperability engagement (β = 0.01; 95% CI, -0.01 to 0.03). The most commonly cited barrier to interoperability was challenges associated with sharing data across different electronic health record vendors.

Conclusions and Relevance

In this cohort study of hospital interoperability, fewer than half of US hospitals were engaged in interoperable data exchange in 2018. There was no observable evidence that hospital APM participation was associated with interoperability engagement. Many hospitals report technical and governance challenges to data sharing that are unlikely to be addressed by the alignment of financial incentives alone.

A Comparison of Infectious Disease Forecasting Methods across Locations, Diseases, and Time

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate adverse impacts. This study compares the performance of statistical, machine learning (ML), and deep learning (DL) approaches in forecasting infectious disease incidences across different countries and time intervals. We forecasted three diverse diseases: campylobacteriosis, typhoid, and Q-fever, using a wide variety of features (n = 46) from public datasets, e.g., landscape, climate, and socioeconomic factors. We compared autoregressive statistical models to two tree-based ML models (extreme gradient boosted trees [XGB] and random forest [RF]) and two DL models (multi-layer perceptron and encoder–decoder model). The disease models were trained on data from seven different countries at the region-level between 2009–2017. Forecasting performance of all models was assessed using mean absolute error, root mean square error, and Poisson deviance across Australia, Israel, and the United States for the months of January through August of 2018. The overall model results were compared across diseases as well as various data splits, including country, regions with highest and lowest cases, and the forecasted months out (i.e., nowcasting, short-term, and long-term forecasting). Overall, the XGB models performed the best for all diseases and, in general, tree-based ML models performed the best when looking at data splits. There were a few instances where the statistical or DL models had minutely smaller error metrics for specific subsets of typhoid, which is a disease with very low case counts. Feature importance per disease was measured by using four tree-based ML models (i.e., XGB and RF with and without region name as a feature). The most important feature groups included previous case counts, region name, population counts and density, mortality causes of neonatal to under 5 years of age, sanitation factors, and elevation. This study demonstrates the power of ML approaches to incorporate a wide range of factors to forecast various diseases, regardless of location, more accurately than traditional statistical approaches.

Use of Electronic Health Information Technology in a National Sample of Hospitals That Provide Specialty Substance Use Care

OBJECTIVE

Most U.S. acute care hospitals have adopted basic electronic health record (EHR) functionality and health information exchange (HIE) (84% and 88%, respectively, in 2017). This study examined whether rates of EHR and HIE adoption by hospital-based substance use disorder programs are lower than rates by acute care hospitals.

METHODS

Data from the 2017 National Survey on Substance Abuse Treatment Services were analyzed to examine adoption of basic EHR functionality (i.e., assessment, progress monitoring, discharge, labs, and prescription dispensing) and use of HIE by hospital-based programs. Analyses used weighted multivariable models of EHR and HIE outcomes, adjusted for nonresponse.

RESULTS

Of 894 hospital-based substance use disorder programs with EHR information, two-thirds (N=606, 68%) reported use of basic EHR functionality. Psychiatric hospitals were less likely than acute care hospitals to have adopted EHR (odds ratio [OR]=0.49, 95% confidence interval [CI]=0.35-0.71). Compared with nonprofit hospitals, for-profit (OR=0.23, 95% CI=0.16-0.35) and government-owned (OR=0.52, 95% CI=0.33-0.83) hospitals were less likely to use basic EHR functionality. Hospital-based programs providing medications for alcohol or opioid use disorders were more likely than those not providing such medications to use basic EHR (OR=1.95, 95% CI=1.31-2.90). Of 839 hospitals with information on HIE use, 598 (71%) reported using electronic HIE. Adoption of basic EHR functionality was the strongest predictor of HIE use (OR=4.73, 95% CI=3.29-6.79).

CONCLUSIONS

Hospital-based substance use disorder programs trail behind U.S. acute care hospitals in adoption of basic EHR and electronic HIE. Findings raise concerns about missed opportunities to improve hospital-based substance use disorder care quality and performance measurement.

Electronic charting of radiation therapy planning and treatment: Report of Task Group 262

While most Radiation Oncology clinics have adopted electronic charting in one form or another, no consensus document exists that provides guidelines for safe and effective use of the Radiation Oncology electronic medical records (RO-EMR). Task Group 262 was formed to provide these guidelines as well as to provide recommendations to vendors for improving electronic charting functionality in future. Guidelines are provided in the following areas: Implementation and training for the RO-EMR, acceptance testing and quality assurance (QA) of the RO-EMR, use of the RO-EMR as an information repository, use of the RO-EMR as a workflow manager, electronic charting for brachytherapy and nonstandard treatments, and information technology (IT) considerations associated with the RO-EMR. The report was based on a literature search by the task group, an extensive survey of task group members on their respective RO-EMR practices, an AAPM membership survey on electronic charting, as well as group consensus.

Hospital adoption of electronic health record functions to support age-friendly care: results from a national survey

OBJECTIVE

To measure US hospitals' adoption of electronic health record (EHR) functions that support care for older adults, focusing on structured documentation of the 4Ms (What Matters, Medication, Mentation, and Mobility) and electronic health information exchange/communication with patients, caregivers, and long-term care providers.

MATERIALS AND METHODS

In an online survey of a national, random sample of 797 US acute-care hospitals in 2018-2019, 479 (60.1%) responded. We calculated nationally representative measures of the percentages of hospitals with EHRs that include structured documentation of the 4Ms and exchange/communications functions.

RESULTS

Structured EHR documentation of the 4Ms was fully implemented in at least 1 unit in 64.0% of hospitals and across all units in 41.5% of hospitals. Of the 4Ms, structured documentation was the highest for medications (91.3% in at least 1 unit) and the lowest for mentation (70.3% in at least 1 unit). All exchange/communication functions had been implemented in at least 1 unit in 16.2% of facilities and across all units in 7.6% of hospitals. Less than half of the hospitals had an EHR portal for long-term care facilities to access hospital information (45.4% in at least 1 unit), sent information electronically to long-term care facilities (44.6%), and had training for adults/caregivers on the patient portal (32.1%).

DISCUSSION

Despite significant national investment in EHRs, hospital EHRs do not yet include key documentation, exchange, and communication functions needed to support evidence-based care for the older adults who comprise the majority of the inpatient population. Additional policy efforts are likely needed to promote the expansion of EHR capabilities into these high-value domains.

CONCLUSIONS

US acute-care hospital EHRs are lacking key functions that support care for older adults.

Self-Perceptions of Readiness to Use Electronic Health Records Among Medical Students: Survey Study

BACKGROUND

Although several national organizations have declared the ability to work with electronic health records (EHRs) as a core competency of medical education, EHR education and use among medical students vary widely. Previous studies have reported EHR tasks performed by medical students, but students' self-perceived readiness and comfort with EHRs are relatively unknown.

OBJECTIVE

This study aimed to better understand medical students' self-perceived readiness to use EHRs to identify potential curricular gaps and inform future training efforts based on students' perspectives.

METHODS

The authors deployed a survey investigating self-perceived comfort with EHRs at 2 institutions in the United States in May 2019. Descriptive statistics were generated regarding demographics, comfort level with various EHR-related tasks, and cross-institutional comparisons. We also assessed the impact of extracurricular EHR experience on comfort level.

RESULTS

In total, 147 medical students responded, of which 80 (54.4%) were female, with equal distribution across all 4 years of training. Overall confidence was generally higher for students with longer extracurricular EHR experience, even when adjusted for age, gender, year of training, and institution. Students were most comfortable with tasks related to looking up information in the EHR and felt less comfortable with tasks related to entering new information and managing medications. Fourth-year students at both schools reported similar levels of comfort with EHR use, despite differences in preclinical EHR training. Open-ended comments emphasized the value of experiential training over didactic formats.

CONCLUSIONS

Information entry and medication management in the EHR represent areas for future curricular development. Experiential training via extracurricular activities and early clinical exposure may be high-yield approaches to help medical students achieve critical EHR competencies.

Use of electronic medical records in development and validation of risk prediction models of hospital readmission: systematic review

OBJECTIVE

To provide focused evaluation of predictive modeling of electronic medical record (EMR) data to predict 30 day hospital readmission.

DESIGN

Systematic review.

DATA SOURCE

Ovid Medline, Ovid Embase, CINAHL, Web of Science, and Scopus from January 2015 to January 2019.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

All studies of predictive models for 28 day or 30 day hospital readmission that used EMR data.

OUTCOME MEASURES

Characteristics of included studies, methods of prediction, predictive features, and performance of predictive models.

RESULTS

Of 4442 citations reviewed, 41 studies met the inclusion criteria. Seventeen models predicted risk of readmission for all patients and 24 developed predictions for patient specific populations, with 13 of those being developed for patients with heart conditions. Except for two studies from the UK and Israel, all were from the US. The total sample size for each model ranged between 349 and 1 195 640. Twenty five models used a split sample validation technique. Seventeen of 41 studies reported C statistics of 0.75 or greater. Fifteen models used calibration techniques to further refine the model. Using EMR data enabled final predictive models to use a wide variety of clinical measures such as laboratory results and vital signs; however, use of socioeconomic features or functional status was rare. Using natural language processing, three models were able to extract relevant psychosocial features, which substantially improved their predictions. Twenty six studies used logistic or Cox regression models, and the rest used machine learning methods. No statistically significant difference (difference 0.03, 95% confidence interval -0.0 to 0.07) was found between average C statistics of models developed using regression methods (0.71, 0.68 to 0.73) and machine learning (0.74, 0.71 to 0.77).

CONCLUSIONS

On average, prediction models using EMR data have better predictive performance than those using administrative data. However, this improvement remains modest. Most of the studies examined lacked inclusion of socioeconomic features, failed to calibrate the models, neglected to conduct rigorous diagnostic testing, and did not discuss clinical impact.

A randomized study on the usefulness of an electronic outpatient hypoglycemia risk calculator for clinicians of patients with diabetes in a safety-net institution

Objective: Hypoglycemia (HG) occurs in up to 60% of patients with diabetes mellitus (DM) each year. We assessed a HG alert tool in an electronic health record system, and determined its effect on clinical practice and outcomes.Methods: The tool applied a statistical model, yielding patient-specific information about HG risk. We randomized outpatient primary-care providers (PCPs) to see or not see the alerts. Patients were assigned to study group according to the first PCP seen during four months. We assessed prescriptions, testing, and HG. Variables were compared by multinomial, logistic, or linear model. ClinicalTrials.gov ID: NCT04177147 (registered on 22 November 2019).Results: Patients (N = 3350) visited 123 intervention PCPs; 3395 patients visited 220 control PCPs. Intervention PCPs were shown 18,645 alerts (mean of 152 per PCP). Patients' mean age was 55 years, with 61% female, 49% black, and 49% Medicaid recipients. Mean baseline A1c and body mass index were similar between groups. During follow-up, the number of A1c and glucose tests, and number of new, refilled, changed, or discontinued insulin prescriptions, were highest for patients with highest risk. Per 100 patients on average, the intervention group had fewer sulfonylurea refills (6 vs. 8; p < .05) and outpatient encounters (470 vs. 502; p < .05), though the change in encounters was not significant. Frequency of HG events was unchanged.Conclusions: Informing PCPs about risk of HG led to fewer sulfonylurea refills and visits. Longer-term studies are needed to assess potential for long-term benefits.

Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study

BACKGROUND

Electronic health records (EHRs) with embedded clinical decision support systems (CDSSs) have the potential to improve healthcare delivery. This study was conducted to explore merits, features, and desiderata to be considered when planning for, designing, developing, implementing, piloting, evaluating, maintaining, upgrading, and/or using EHRs with CDSSs.

METHODS

A mixed-method combining the Delphi technique and Analytic Hierarchy Process was used. Potentially important items were collected after a thorough search of the literature and from interviews with key contact experts (n = 19). Opinions and views of the 76 panelists on the use of EHRs were also explored. Iterative Delphi rounds were conducted to achieve consensus on 122 potentially important items by a panel of 76 participants. Items on which consensus was achieved were ranked in the order of their importance using the Analytic Hierarchy Process.

RESULTS

Of the 122 potentially important items presented to the panelists in the Delphi rounds, consensus was achieved on 110 (90.2%) items. Of these, 16 (14.5%) items were related to the demographic characteristics of the patient, 16 (14.5%) were related to prescribing medications, 16 (14.5%) were related to checking prescriptions and alerts, 14 (12.7%) items were related to the patient's identity, 13 (11.8%) items were related to patient assessment, 12 (10.9%) items were related to the quality of alerts, 11 (10%) items were related to admission and discharge of the patient, 9 (8.2%) items were general features, and 3 (2.7%) items were related to diseases and making diagnosis.

CONCLUSIONS

In this study, merits, features, and desiderata to be considered when planning for, designing, developing, implementing, piloting, evaluating, maintaining, upgrading, and/or using EHRs with CDSSs were explored. Considering items on which consensus was achieved might promote congruence and safe use of EHRs. Further studies are still needed to determine if these recommendations can improve patient safety and outcomes in Palestinian hospitals.

The Digitization of Patient Care: A Review of the Effects of Electronic Health Records on Health Care Quality and Utilization

Electronic health records (EHRs) adoption has become nearly universal during the past decade. Academic research into the effects of EHRs has examined factors influencing adoption, clinical care benefits, financial and cost implications, and more. We provide an interdisciplinary overview and synthesis of this literature, drawing on work in public and population health, informatics, medicine, management information systems, and economics. We then chart paths forward for policy, practice, and research.

Electronic Health Record-Based Registries: Clinical Research Using Registries in Colon and Rectal Surgery

Electronic health records (EHRs) or electronic medical records (EMRs) contain a vast amount of clinical data that can be useful for multiple purposes including research. Disease registries are collections of data in predefined formats for population management, research, and other purposes. There are differences between EHRs and registries in the data structure, data standards, and protocols. Proprietary EHR systems use different coding systems and data standards, which are usually kept secret. For EHR data to flow seamlessly into registries, there is the need for interoperability between EHR systems and between EHRs and registries. The levels of interoperability required include functional, structural, and semantic interoperability. EHR data can be manually mapped to registry data, but that is a tedious, resource-intensive endeavor. The development of data standards that can be used as building blocks for both EHRs and registries will help overcome the problem of interoperability.

Hospitals' adoption of intra-system information exchange is negatively associated with inter-system information exchange

Introduction

U.S. policy on interoperable HIT has focused on increasing inter-system (ie, between different organizations) health information exchange. However, interoperable HIT also supports the movement of information within the same organization (ie, intra-system exchange).

Methods

We examined the relationship between hospitals' intra- and inter-system information exchange capabilities among health system hospitals included in the 2010-2014 American Hospital Association's Annual Health Information Technology Survey. We described the factors associated with hospitals that adopted more intra-system than inter-system exchange capability, and explored the extent of new capability adoption among hospitals that reported neither intra- or inter-system information capabilities at baseline.

Results

The prevalence of exchange increased over time, but the adoption of inter-system information exchange was slower; when hospitals adopt information exchange, adoption of intra-system exchange was more common. On average during our study period, hospitals could share 4.6 types of information by intra-system exchange, but only 2.7 types of information by inter-system exchange. Controlling for other factors, hospitals exchanged more types of information in an intra-system manner than inter-system when the number of different inpatient EHR vendors in use in health system is larger.

Conclusion

Consistent with the U.S. goals for more widely accessible patient information, hospitals' ability to share information has increased over time. However, hospitals are prioritizing within-organizational information exchange over exchange between different organizations. If increasing inter-system exchanges is a desired goal, current market incentives and government policies may be insufficient to overcome hospitals' motivations for pursuing an intra-system-information-exchange-first strategy.

Electronic Medical Records in Greece and Oman: A Professional's Evaluation of Structure and Value

An Electronic Medical Record (EMR) is a patient’s database record that can be transmitted securely. There are a diversity of EMR systems for different medical units to choose from. The structure and value of these systems is the focus of this qualitative study, from a medical professional’s standpoint, as well as its economic value and whether it should be shared between health organizations. The study took place in the natural setting of the medical units’ environments. A purposive sample of 40 professionals in Greece and Oman, was interviewed. The study suggests that: (1) The demographics of the EMR should be divided in categories, not all of them accessible and/or visible by all; (2) The EMR system should follow an open architecture so that more categories and subcategories can be added as needed and following a possible business plan (ERD is suggested); (3) The EMR should be implemented gradually bearing in mind both medical and financial concerns; (4) Sharing should be a patient’s decision as the owner of the record. Reaching a certain level of maturity of its implementation and utilization, it is useful to seek the professionals’ assessment on the structure and value of such a system.

Assessing Intensity of Nursing Care Needs Using Electronically Available Data

Although previous research has confirmed that nurse staffing affects patient outcomes, some potentially important factors have not been accounted for in tools to assess relationships between staffing and outcomes. The aim of this project was to develop and test a Nursing Intensity of Care Index using electronically available data from 152 072 patient discharges from three hospitals. Initially, 1765 procedure codes were reviewed; 69 were confirmed as directly increasing nursing workload by at least 15 minutes per shift. Two research staff independently reviewed a random sample of 5 patient days to assess interrater reliability with complete scoring agreement. To assess face validity, eight nurse clinician experts reviewed factors included in the Nursing Intensity of Care Index to assess the accuracy of the nursing time estimates in the tool. To examine concurrent validity, Nursing Intensity of Care Index scores for a random sample of 28 patients from four clinical units were compared with assessments made by a unit-based clinical nurse (low/medium/high intensity) for the same patients on the same day with a Spearman correlation of 0.94. In preliminary testing, data for the Nursing Intensity of Care Index, which accurately reflect nursing care intensity, can be obtained electronically in real time. The next steps will be a discrete-event simulation model and large-scale field trials.

Know Your Numbers: Creation and implementation of a novel community health mobile application (app) by student pharmacists

OBJECTIVES

A free mobile application (app), Know Your Numbers (KYN), was developed by student pharmacists to assist underserved community members to track their health numbers. The study objectives included creating a health app, implementing a pilot program, and analyzing the frequency of app use and perceptions of community members toward their health numbers, pharmacists, and health apps.

SETTING

Student pharmacists recruited participants at the community clinics and health fairs organized in underserved communities of the Atlanta metropolitan area.

PRACTICE DESCRIPTION

This study used a pre- and post-survey study design to compare perceptions before and after use of a health app. Eligible participants completed a 22-item pre-survey that assessed understanding of their health numbers, previous health app use, and perceptions of pharmacists.

EVALUATION

Frequency of app use and change in perceptions of community members toward health numbers, pharmacists, and health apps before and after enrolling in KYN were analyzed with the use of descriptive statistics and Wilcoxon signed rank tests for matched pre- and post-surveys.

RESULTS

Thirty-three participants were enrolled for 56 days. African American participants (93.9%) earned less than $25,000 annually (56.7%). On average, participants had 3.98 interactions per week. Before using the mobile health app, 84.8% of users felt comfortable using a health app, but only 9% used one regularly. The post-survey response rate was 27.2% (n = 9). More participants agreed that a health app helped them to meet their health goals after the program (24.4% to 100%; P = 0.0006). More than 90% of participants agreed in both surveys that it is important to check their health numbers regularly and that they trust pharmacists to provide accurate information.

CONCLUSION

KYN is a novel mobile tool that promotes chronic disease self-management and the profession of pharmacy. These findings support the benefits of mobile health app's usability and its ability to assist in achieving personal health goals.

Electronic health record adoption in US hospitals: the emergence of a digital "advanced use" divide

OBJECTIVE

While most hospitals have adopted electronic health records (EHRs), we know little about whether hospitals use EHRs in advanced ways that are critical to improving outcomes, and whether hospitals with fewer resources - small, rural, safety-net - are keeping up.

MATERIALS AND METHODS

Using 2008-2015 American Hospital Association Information Technology Supplement survey data, we measured "basic" and "comprehensive" EHR adoption among hospitals to provide the latest national numbers. We then used new supplement questions to assess advanced use of EHRs and EHR data for performance measurement and patient engagement functions. To assess a digital "advanced use" divide, we ran logistic regression models to identify hospital characteristics associated with high adoption in each advanced use domain.

RESULTS

We found that 80.5% of hospitals adopted at least a basic EHR system, a 5.3 percentage point increase from 2014. Only 37.5% of hospitals adopted at least 8 (of 10) EHR data for performance measurement functions, and 41.7% of hospitals adopted at least 8 (of 10) patient engagement functions. Critical access hospitals were less likely to have adopted at least 8 performance measurement functions (odds ratio [OR] = 0.58; P < .001) and at least 8 patient engagement functions (OR = 0.68; P = 0.02).

DISCUSSION

While the Health Information Technology for Economic and Clinical Health Act resulted in widespread hospital EHR adoption, use of advanced EHR functions lags and a digital divide appears to be emerging, with critical-access hospitals in particular lagging behind. This is concerning, because EHR-enabled performance measurement and patient engagement are key contributors to improving hospital performance.

CONCLUSION

Hospital EHR adoption is widespread and many hospitals are using EHRs to support performance measurement and patient engagement. However, this is not happening across all hospitals.

Designing and Implementing an Electronic Patient Registry to Improve Warfarin Monitoring in the Ambulatory Setting

BACKGROUND

Warfarin requires individualized dosing and monitoring in the ambulatory setting for protection against thromboembolic disease. Yet in multiple settings, patients spend upwards of 30% of time outside the therapeutic range, subjecting them to an increased risk of adverse events. At an urban, publicly funded clinic, the electronic health record (EHR) would not support integration with extant warfarin management software, which led to the creation and implementation of an electronic patient registry and a complementary team-based work flow to provide real-time health-system-level data for warfarin patients.

METHODS

Creation of the registry, which began in August 2014, entailed use of an existing platform, which could interface with the outpatient EHR. The registry was designed to help ensure regular testing and monitoring of patients while enabling identification of patients and subpopulations with suboptimal management. The work flow used for the clinic's warfarin patients was also redesigned. An assessment indicated that the registry identified 341 (96%) of 357 patients actively seen in the clinic.

RESULTS

For the cohort of the 357 patients in the registry, the no-show rate decreased from 31% (preimplementation, August 2014-December 2014) to 21% (postimplementation, January 2015-November 2015). The ratio of visits to no-shows increased from 2.3 to 4.0 visits.

CONCLUSION

Design and implementation of an electronic registry in conjunction with a complementary work flow established an active tracking system that improved treatment monitoring for patients on anticoagulation therapy. Registry creation also facilitated assessment of the quality of care and laid the groundwork for ongoing evaluation and quality improvement efforts.

Key success factors behind electronic medical record adoption in Thailand

Purpose The purpose of this paper is to investigate the elements that health care personnel in Thailand believe are necessary for successful adoption of electronic medical record (EMR) systems. Design/methodology/approach Initial qualitative in-depth interviews with physicians to adapt key elements from the literature to the Thai context. The 12 elements identified included things related to managing the implementation and to IT expertise. The nationwide survey was supported by the Ministry of Public Health and returned 1,069 usable questionnaires (response rate 42 percent) from a range of medical personnel. Findings The key elements clearly separated into a managerial dimension and an IT dimension. All were considered fairly important, but managerial expertise was more critical. In particular, there should be clear EMR project goals and scope, adequate budget allocation, clinical staff must be involved in implementation, and the IT should facilitate good electronic communication. Research limitations/implications Thailand is representative of middle-income developing countries, but there is no guarantee findings can be generalized. National policies differ, as do economic structures of health care industries. The focus is on management at the organizational level, but future research must also examine macro-level issues, as well as gain more depth into thinking of individual health care personnel. Practical implications Technical issues of EMR implementation are certainly important. However, it is clear actual adoption and use of the system also depends very heavily on managerial issues. Originality/value Most research on EMR implementation has been in developed countries, and has often focussed more on technical issues rather than examining managerial issues closely. Health IT is also critical in developing economies, and management of health IT implementation must be well understood.

Hospital Adoption of Health Information Technology to Support Public Health Infrastructure

CONTEXT

Health information technology (IT) has the potential to improve the nation's public health infrastructure. In support of this belief, meaningful use incentives include criteria for hospitals to electronically report to immunization registries, as well as to public health agencies for reportable laboratory results and syndromic surveillance. Electronic reporting can facilitate faster and more appropriate public health response. However, it remains unclear the extent that hospitals have adopted IT for public health efforts.

OBJECTIVE

To examine hospital adoption of IT for public health and to compare hospitals capable of using and not using public health IT.

DESIGN

Cross-sectional design with data from the 2012 American Hospital Association annual survey matched with data from the 2013 American Hospital Association Information Technology Supplement. Multivariate logistic regression was used to compare hospital characteristics. Inverse probability weights were applied to adjust for selection bias because of survey nonresponse.

PARTICIPANTS

All acute care general hospitals in the United States that matched across the surveys and had complete data available were included in the analytic sample.

MAIN OUTCOME MEASURES

Three separate outcome measures were used: whether the hospital could electronically report to immunization registries, whether the hospital could send electronic laboratory results, and whether the hospital can participate in syndromic surveillance.

RESULTS

A total of 2841 hospitals met the inclusion criteria. Weighted results show that of these hospitals, 62.7% can electronically submit to immunization registries, 56.6% can electronically report laboratory results, and 54.4% can electronically report syndromic surveillance. Adjusted and weighted results from the multivariate analyses show that small, rural hospitals and hospitals without electronic health record systems lag in the adoption of public health IT capabilities.

CONCLUSION

While a majority of hospitals are using public health IT, the infrastructure still has significant room for growth. Differences in hospitals' adoption of public health IT may exacerbate existing health disparities.

Support for Sustainable Use of Personal Health Records: Understanding the Needs of Users as a First Step Towards Patient-Driven Mobile Health

Background

The tethering of a personal health record (PHR) to an electronic medical record (EMR) may serve as a catalyst in accelerating the distribution of integrated PHRs. Creating shared health records for patients and their health care professionals using self-administered functions of EMR-tethered PHRs is crucial to support sustainable use of the system.

Objective

This study assesses the factors related to active use of a self-administered function (Health Notes) in an EMR-tethered PHR (Health4U) in a tertiary academic hospital.

Methods

This research is a cross-sectional study conducted in a tertiary academic hospital in South Korea. The enrollees included adults aged 19 years and older with experience accessing Health4U in the 13-month period after June 2013. The primary outcome was the adoption of Health Notes in accordance with the number of chronic diseases. Socio-demographic variables were included as confounding factors.

Results

Subjects 71 years of age and older were less likely to become active users of Health Notes than those 30 years and younger. Moreover, compared with men, women had 44% and 40% lower tendencies to become Health Notes users and active users, respectively. Those who accessed the desktop page and/or mobile page had higher tendencies to become users of Health Notes. We found a consistent increase in the odds ratio as the number of chronic diseases increased in the active users. When considering specific diseases, patients who had cancer or chronic kidney disease had higher tendencies to become users of Health Notes.

Conclusions

Patients with a greater number of chronic diseases tended to use PHR more actively, and used the self-administered function. Women and the elderly may have lower tendencies to actively use PHR. Therefore, items specific to the health of each demographic—women, the elderly, and those with chronic diseases—should be carefully considered to support sustainable use of PHRs.

Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting

BACKGROUND

Data capture is one of the most expensive phases during the conduct of a clinical trial and the increasing use of electronic health records (EHR) offers significant savings to clinical research. To facilitate these secondary uses of routinely collected patient data, it is beneficial to know what data elements are captured in clinical trials. Therefore our aim here is to determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems.

METHODS

Case report forms for 23 clinical trials in differing disease areas were analyzed. Through an iterative and consensus-based process of medical informatics professionals from academia and trial experts from the European pharmaceutical industry, data elements were compiled for all disease areas and with special focus on the reporting of adverse events. Afterwards, data elements were identified and statistics acquired from hospital sites providing data to the EHR4CR project.

RESULTS

The analysis identified 133 unique data elements. Fifty elements were congruent with a published data inventory for patient recruitment and 83 new elements were identified for clinical trial execution, including adverse event reporting. Demographic and laboratory elements lead the list of available elements in hospitals EHR systems. For the reporting of serious adverse events only very few elements could be identified in the patient records.

CONCLUSIONS

Common data elements in clinical trials have been identified and their availability in hospital systems elucidated. Several elements, often those related to reimbursement, are frequently available whereas more specialized elements are ranked at the bottom of the data inventory list. Hospitals that want to obtain the benefits of reusing data for research from their EHR are now able to prioritize their efforts based on this common data element list.

Comparative Effectiveness of Infliximab and Adalimumab in Crohn's Disease and Ulcerative Colitis

BACKGROUND

The availability of monoclonal antibodies to tumor necrosis factor α has revolutionized management of Crohn's disease (CD) and ulcerative colitis. However, limited data exist regarding comparative effectiveness of these agents to inform clinical practice.

METHODS

This study consisted of patients with CD or ulcerative colitis initiation either infliximab (IFX) or adalimumab (ADA) between 1998 and 2010. A validated likelihood of nonresponse classification score using frequency of narrative mentions of relevant symptoms in the electronic health record was applied to assess comparative effectiveness at 1 year. Inflammatory bowel disease-related surgery, hospitalization, and use of steroids were determined during this period.

RESULTS

Our final cohort included 1060 new initiations of IFX (68% for CD) and 391 of ADA (79% for CD). In CD, the likelihood of nonresponse was higher in ADA than IFX (odds ratio, 1.62 and 95% CI, 1.21-2.17). Similar differences favoring efficacy of IFX were observed for the individual symptoms of diarrhea, pain, bleeding, and fatigue. However, there was no difference in inflammatory bowel disease-related surgery, hospitalizations, or prednisone use within 1 year after initiation of IFX or ADA in CD. There was no difference in narrative or codified outcomes between the 2 agents in ulcerative colitis.

CONCLUSIONS

We identified a modestly higher likelihood of symptomatic nonresponse at 1 year for ADA compared with IFX in patients with CD. However, there were no differences in inflammatory bowel disease-related surgery or hospitalizations, suggesting these treatments are broadly comparable in effectiveness in routine clinical practice.

Identification of Nonresponse to Treatment Using Narrative Data in an Electronic Health Record Inflammatory Bowel Disease Cohort

BACKGROUND

Electronic health records, increasingly a part of healthcare, provide a wealth of untapped narrative free text data that have the potential to accurately inform clinical outcomes.

METHODS

From a validated cohort of patients with Crohn's disease or ulcerative colitis, we identified patients with ≥1 coded or narrative mention of monoclonal antibodies to tumor necrosis factor α. Chart review by ascertained true use of therapy, time of initiation, and cessation of treatment, and also clinical response stratified as nonresponse, partial, or complete response at 1 year. Internal consistency was assessed in an independent validation cohort.

RESULTS

A total of 3087 patients had a mention of an antibodies to tumor necrosis factor α. Actual therapy initiation was within 60 days of the first coded mention in 74% of patients. In the derivation cohort, 18% of antibodies to tumor necrosis factor α starts were classified as nonresponse at 1 year, 21% as partial, and 56% as complete response. On multivariate analysis, the number of narrative mentions of diarrhea (odds ratio 1.08; 95% confidence interval, 1.02-1.14) and fatigue (odds ratio 1.16; 95% confidence interval, 1.02-1.32) was independently associated with nonresponse at 1 year (area under the curve 0.82). A likelihood of nonresponse score comprising a weighted sum of both demonstrated a good dose-response relationship across nonresponders (2.18), partial (1.20), and complete (0.50) responders (P < 0.0001) and correlated well with need for surgery or hospitalizations.

CONCLUSIONS

Narrative data in an electronic health record offer considerable potential to define temporally evolving disease outcomes such as nonresponse to treatment.

A Narrative Review of Meaningful Use and Anesthesia Information Management Systems

The US federal government has enacted legislation for a federal incentive program for health care providers and hospitals to implement electronic health records. The primary goal of the Meaningful Use (MU) program is to drive adoption of electronic health records nationwide and set the stage to monitor and guide efforts to improve population health and outcomes. The MU program provides incentives for the adoption and use of electronic health record technology and, in some cases, penalties for hospitals or providers not using the technology. The MU program is administrated by the Department of Health and Human Services and is divided into 3 stages that include specific reporting and compliance metrics. The rationale is that increased use of electronic health records will improve the process of delivering care at the individual level by improving the communication and allow for tracking population health and quality improvement metrics at a national level in the long run. The goal of this narrative review is to describe the MU program as it applies to anesthesiologists in the United States. This narrative review will discuss how anesthesiologists can meet the eligible provider reporting criteria of MU by applying anesthesia information management systems (AIMS) in various contexts in the United States. Subsequently, AIMS will be described in the context of MU criteria. This narrative literature review also will evaluate the evidence supporting the electronic health record technology in the operating room, including AIMS, independent of certification requirements for the electronic health record technology under MU in the United States.

Electronic Health Record Adoption In US Hospitals: Progress Continues, But Challenges Persist

Achieving nationwide adoption of electronic health records (EHRs) remains an important policy priority. While EHR adoption has increased steadily since 2010, it is unclear how providers that have not yet adopted will fare now that federal incentives have converted to penalties. We used 2008-14 national data, which includes the most recently available, to examine hospital EHR trends. We found large gains in adoption, with 75 percent of US hospitals now having adopted at least a basic EHR system--up from 59 percent in 2013. However, small and rural hospitals continue to lag behind. Among hospitals without a basic EHR system, the function most often not yet adopted (in 61 percent of hospitals) was physician notes. We also saw large increases in the ability to meet core stage 2 meaningful-use criteria (40.5 percent of hospitals, up from 5.8 percent in 2013); much of this progress resulted from increased ability to meet criteria related to exchange of health information with patients and with other physicians during care transitions. Finally, hospitals most often reported up-front and ongoing costs, physician cooperation, and complexity of meeting meaningful-use criteria as challenges. Our findings suggest that nationwide hospital EHR adoption is in reach but will require attention to small and rural hospitals and strategies to address financial challenges, particularly now that penalties for lack of adoption have begun.

Implementing Computerized Provider Order Entry in Acute Care Hospitals in the United States Could Generate Substantial Savings to Society

BACKGROUND

Computerized provider order entry (CPOE) with clinical decision support is a basic criterion for hospitals' meaningful use of electronic health record systems. A study was conducted to evaluate from the societal perspective the cost-utility of implementing CPOE in acute care hospitals in the United States.

METHODS

A decision-analytical model compared CPOE with paper ordering among patients admitted to acute care hospitals with >25 beds. Parameters included start-up and maintenance costs, as well as costs for provider time use, medication and laboratory test ordering, and preventable adverse drug events. Probabilistic analyses produced incremental costs, effectiveness, and cost-effectiveness ratios for hospitals in four bed-size categories (25-72, 72-141, 141-267, 267-2,249).

RESULTS

Relative to paper ordering and using typical estimates of implementation costs, CPOE had, on average, >99% probability of yielding savings to society and improving health. Per hospital in each size category, mean life-time savings -in millions-were $11.6 (standard deviation, $9.30), $34.4 ($21.2), $71.8 ($43.8), and $170 ($119) (2012 dollars), respectively, and quality-adjusted life-years (QALYs) gained were 19.9 (16.9), 53.7 (38.7), 109 (79.6), and 249 (205). Incremental effectiveness and costs were less favorable in certain circumstances, such as high implementation costs. Nationwide, anticipated increases in CPOE implementation from 2009 through 2015 could save $133 billion and 201,000 QALYs.

CONCLUSIONS

In addition to improving health, implementing CPOE with clinical decision support could yield substantial long-term savings to society in the United States, although results for individual hospitals are likely to vary.

Lack of impact of electronic health records on quality of care and outcomes for ischemic stroke

BACKGROUND

Electronic 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.

OBJECTIVES

The goal of this study was to determine whether hospitals with EHRs differed on quality or outcome measures for ischemic stroke from those without EHRs.

METHODS

We 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.

RESULTS

A 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).

CONCLUSIONS

In 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.

Analyzing Determinants of Hospitals’ Accountable Care Organizations Participation

Accountable care organizations (ACOs) are rapidly being implemented across the United States, but little is known about what environmental and organizational factors are associated with hospital participation in ACOs. Using resource dependency theory, this study examines external environmental characteristics and organizational characteristics that relate to hospital participation in Medicare ACOs. Results indicate hospitals operating in more munificent environments (as measured by income per capita: β = 0.00002, p < .05) and more competitive environments (as measured by Health Maintenance Organization penetration: β = 1.86, p < .01) are more likely to participate in ACOs. Organizational characteristics including hospital ownership, health care system membership, electronic health records implementation, hospital type, percentage of Medicaid inpatient discharge, and number of nursing home beds per 1,000 population over 65 are also related to ACO participation. Should the anticipated benefits of ACOs be realized, findings from this study can guide strategies to encourage hospitals that have not gotten involved in ACOs.

Inclusion of dynamic clinical data improves the predictive performance of a 30-day readmission risk model in kidney transplantation

BACKGROUND

Thirty-day readmissions (30DRA) are a highly scrutinized measure of healthcare quality and relatively frequent among kidney transplants (KTX). Development of predictive risk models is critical to reducing 30DRA and improving outcomes. Current approaches rely on fixed variables derived from administrative data. These models may not capture clinical evolution that is critical to predicting outcomes.

METHODS

We directed a retrospective analysis toward: (1) developing parsimonious risk models for 30DRA and (2) comparing efficiency of models based on the use of immutable versus dynamic data. Baseline and in-hospital clinical and outcomes data were collected from adult KTX recipients between 2005 and 2012. Risk models were developed using backward logistic regression and compared for predictive efficacy using receiver operating characteristic curves.

RESULTS

Of 1147 KTX patients, 123 had 30DRA. Risk factors for 30DRA included recipient comorbidities, transplant factors, and index hospitalization patient level clinical data. The initial fixed variable model included 9 risk factors and was modestly predictive (area under the curve, 0.64; 95% confidence interval [95% CI], 0.58-0.69). The model was parsimoniously reduced to 6 risks, which remained modestly predictive (area under the curve, 0.63; 95% CI, 0.58-0.69). The initial predictive model using 13 fixed and dynamic variables was significantly predictive (AUC, 0.73; 95% CI, 0.67-0.80), with parsimonious reduction to 9 variables maintaining predictive efficacy (AUC, 0.73; 95% CI, 0.67-0.79). The final model using dynamically evolving clinical data outperformed the model using static variables (P=0.009). Internal validation demonstrated that the final model was stable with minimal bias.

CONCLUSIONS

We demonstrate that modeling dynamic clinical data outperformed models using immutable data in predicting 30DRA.

Insights into temporal patterns of hospital patient safety from routinely collected electronic data

BACKGROUND

The last two decades have seen an unprecedented growth in initiatives aimed to improve patient safety. For the most part, however, evidence of their impact remains controversial. At the same time, the healthcare industry has experienced an also unprecedented growth in the amount and variety of available electronic data.

METHODS

In this paper, we provide a review of the use of routinely collected electronic data in the identification, analysis and surveillance of temporal patterns of patient safety.

RESULTS

Two important temporal patterns of the safety of hospitalised patients were identified and discussed: long-term trends related to changes in clinical practice and healthcare policy; and shorter term patterns related to variations in workforce and resources. We found that consistency in reporting is intrinsically related to availability of large-scale, fit-for-purpose data. Consistent reported trends of patient harms included an increase in the incidence of post-operative sepsis and a decrease in central-line associated bloodstream infections. Improvement in the treatment of specific diseases, such as cardiac conditions, has also been demonstrated. Linkage of hospital data with other datasets provides essential temporal information about errors, as well as information about unsuspected system deficiencies. It has played an important role in the measurement and analysis of the effects of off-hours hospital operation.

CONCLUSIONS

Measuring temporal patterns of patient safety is still inadequate with electronic health records not yet playing an important role. Patient safety interventions should not be implemented without a strategy for continuous monitoring of their effect.

Demonstration of the Weighted-Incidence Syndromic Combination Antibiogram: An Empiric Prescribing Decision Aid

Objective.

Healthcare providers need a better empiric antibiotic prescribing aid than the traditional antibiogram, which supplies no information on the relative frequency of organisms recovered in a given infection and which is uninformative in situations where multiple antimicrobials are used or multiple organisms are anticipated. We aimed to develop and demonstrate a novel empiric prescribing decision aid.

Design/Setting.

This is a demonstration involving more than 9,000 unique encounters for abdominal-biliary infection (ABI) and urinary tract infection (UTI) to a large healthcare system with a fully integrated electronic health record (EHR).

Methods.

We developed a novel method of displaying microbiology data called the weighted-incidence syndromic combination antibiogram (WISCA) for 2 clinical syndromes, ABI and UTI. The WISCA combines simple diagnosis and microbiology data from the EHR to (1) classify patients by syndrome and (2) determine, for each patient with a given syndrome, whether a given regimen (1 or more agents) would have covered all the organisms recovered for their infection. This allows data to be presented such that clinicians can see the probability that a particular regimen will cover a particular infection rather than the probability that a single drug will cover a single organism.

Results.

There were 997 encounters for ABI and 8,232 for UTI. A WISCA was created for each syndrome and compared with a traditional antibiogram for the same period.

Conclusions.

Novel approaches to data compilation and display can overcome limitations to the utility of the traditional antibiogram in helping providers choose empiric antibiotics.

Variants of uncertain significance in BRCA: a harbinger of ethical and policy issues to come?

After two decades of genetic testing and research, the BRCA1 and BRCA2 genes are two of the most well-characterized genes in the human genome. As a result, variants of uncertain significance (VUS; also called variants of unknown significance) are reported less frequently than for genes that have been less thoroughly studied. However, VUS continue to be uncovered, even for BRCA1/2. The increasing use of multi-gene panels and whole-genome and whole-exome sequencing will lead to higher rates of VUS detection because more genes are being tested, and most genomic loci have been far less intensively characterized than BRCA1/2. In this article, we draw attention to ethical and policy-related issues that will emerge. Experience garnered from BRCA1/2 testing is a useful introduction to the challenges of detecting VUS in other genetic testing contexts, while features unique to BRCA1/2 suggest key differences between the BRCA experience and the current challenges of multi-gene panels in clinical care. We propose lines of research and policy development, emphasizing the importance of pooling data into a centralized open-access database for the storage of gene variants to improve VUS interpretation. In addition, establishing ethical norms and regulated practices for sharing and curating data, analytical algorithms, interpretive frameworks and patient re-contact are important policy areas.

A taxonomy of accountable care organizations for policy and practice

OBJECTIVE

To develop an exploratory taxonomy of Accountable Care Organizations (ACOs) to describe and understand early ACO development and to provide a basis for technical assistance and future evaluation of performance.

DATA SOURCES/STUDY SETTING

Data from the National Survey of Accountable Care Organizations, fielded between October 2012 and May 2013, of 173 Medicare, Medicaid, and commercial payer ACOs.

STUDY DESIGN

Drawing on resource dependence and institutional theory, we develop measures of eight attributes of ACOs such as size, scope of services offered, and the use of performance accountability mechanisms. Data are analyzed using a two-step cluster analysis approach that accounts for both continuous and categorical data.

PRINCIPAL FINDINGS

We identified a reliable and internally valid three-cluster solution: larger, integrated systems that offer a broad scope of services and frequently include one or more postacute facilities; smaller, physician-led practices, centered in primary care, and that possess a relatively high degree of physician performance management; and moderately sized, joint hospital-physician and coalition-led groups that offer a moderately broad scope of services with some involvement of postacute facilities.

CONCLUSIONS

ACOs can be characterized into three distinct clusters. The taxonomy provides a framework for assessing performance, for targeting technical assistance, and for diagnosing potential antitrust violations.