Hospital electronic medical record use and cost of inpatient pediatric care

Rebooting the Electronic Health Record

Justifications for the widespread adoption and integration of an electronic health record (EHR) have long leaned on the purported benefits of the technology. However, the performance of the EHR has been underwhelming relative to the promises of immediate access to relevant patient information, clinical decision supports, computerized ordering, and transferable patient data. In this narrative review, we provide an overview of the historical problems and limitations of the EHR, detail the core principles that define agile processes that may overcome the barriers faced by the current EHR, and re-imagine what an integrated, seamless EHR that serves its users and patients might look like. Moving forward, the EHR should be redesigned using a middle-out framework and empowering dual-type champions to maintain the sustainable diffusion of future innovations.

Higher Electronic Health Record Functionality Is Associated with Lower Operating Costs in Urban—but Not Rural—Hospitals

Objectives  The aim of the study is to examine the relationship between electronic health record (EHR) use/functionality and hospital operating costs (divided into five subcategories), and to compare the results across rural and urban facilities.

Methods  We match hospital-level data on EHR use/functionality with operating costs and facility characteristics to perform linear regressions with hospital- and time-fixed effects on a panel of 1,596 U.S. hospitals observed annually from 2016 to 2019. Our dependent variables are the logs of the various hospital operating cost categories, and alternative metrics for EHR use/functionality serve as the primary independent variables of interest. Data on EHR use/functionality are retrieved from the American Hospital Association's (AHA) Annual Survey of Hospitals Information Technology (IT) Supplement, and hospital operating cost and characteristic data are retrieved from the American Hospital Directory. We include only hospitals classified as “general medical and surgical,” removing specialty hospitals.

Results  Our results suggest, first, that increasing levels of EHR functionality are associated with hospital operating cost reductions. Second, that these significant cost reductions are exclusively seen in urban hospitals, with the associated coefficient suggesting cost savings of 0.14% for each additional EHR function. Third, that urban EHR-related cost reductions are driven by general/ancillary and outpatient costs. Finally, that a wide variety of EHR functions are associated with cost reductions for urban facilities, while no EHR function is associated with significant cost reductions in rural locations.

Conclusion  Increasing EHR functionality is associated with significant hospital operating cost reductions in urban locations. These results do not hold across geographies, and policies to promote greater EHR functionality in rural hospitals will likely not lead to short-term cost reductions.

Value of the Electronic Medical Record for Hospital Care: Update From the Literature

Background

Electronic records could improve quality and efficiency of health care. National and international bodies propagate this belief worldwide. However, the evidence base concerning the effects and advantages of electronic records is questionable. The outcome of health care systems is influenced by many components, making assertions about specific types of interventions difficult. Moreover, electronic records itself constitute a complex intervention offering several functions with possibly positive as well as negative effects on the outcome of health care systems.

Objective

The aim of this review is to summarize empirical studies about the value of electronic medical records (EMRs) for hospital care published between 2010 and spring 2019.

Methods

The authors adopted their method from a series of literature reviews. The literature search was performed on MEDLINE with “Medical Record System, Computerized” as the essential keyword. The selection process comprised 2 phases looking for a consent of both authors. Starting with 1345 references, 23 were finally included in the review. The evaluation combined a scoring of the studies’ quality, a description of data sources in case of secondary data analyses, and a qualitative assessment of the publications’ conclusions concerning the medical record’s impact on quality and efficiency of health care.

Results

The majority of the studies stemmed from the United States (19/23, 83%). Mostly, the studies used publicly available data (“secondary data studies”; 17/23, 74%). A total of 18 studies analyzed the effect of an EMR on the quality of health care (78%), 16 the effect on the efficiency of health care (70%). The primary data studies achieved a mean score of 4.3 (SD 1.37; theoretical maximum 10); the secondary data studies a mean score of 7.1 (SD 1.26; theoretical maximum 9). From the primary data studies, 2 demonstrated a reduction of costs. There was not one study that failed to demonstrate a positive effect on the quality of health care. Overall, 9/16 respective studies showed a reduction of costs (56%); 14/18 studies showed an increase of health care quality (78%); the remaining 4 studies missed explicit information about the proposed positive effect.

Conclusions

This review revealed a clear evidence about the value of EMRs. In addition to an awesome majority of economic advantages, the review also showed improvements in quality of care by all respective studies. The use of secondary data studies has prevailed over primary data studies in the meantime. Future work could focus on specific aspects of electronic records to guide their implementation and operation.

The effect of different classification of hospitals on medical expenditure from perspective of classification of hospitals framework: evidence from China

Background

Different classification of hospitals (COH) have an important impact on medical expenditures in China. The objective of this study is to examine the impact of COH on medical expenditures with the hope of providing insights into appropriate care and resource allocation.

Methods

From the perspective of COH framework, using the Urban Employee Basic Medical Insurance (UEBMI) data of Chengdu City from 2011 to 2015, with sample size of 488,623 hospitalized patients, our study empirically analyzed the effect of COH on medical expenditure by multivariate regression modeling.

Results

The average medical expenditure was 5468.86 Yuan (CNY), the average expenditure of drug, diagnostic testing, medical consumables, nursing care, bed, surgery and blood expenditures were 1980.06 Yuan (CNY), 1536.27 Yuan (CNY), 500.01 Yuan (CNY), 166.23 Yuan (CNY), 221.98 Yuan (CNY), 983.18 Yuan (CNY) and 1733.21 Yuan (CNY) respectively. Patients included in the analysis were mainly elderly, with an average age of 86.65 years old. Female and male gender were split evenly. The influence of COH on total medical expenditures was significantly negative (p < 0.001). The reimbursement ratio of UEBMI had a significantly positive (p < 0.001) effect on various types of medical expenditures, indicating that the higher the reimbursement ratio was, the higher the medical expenditures would be.

Conclusions

COH influenced medical expenditures significantly. In consideration of reducing medical expenditures, the government should not only start from the supply side of healthcare services, but also focus on addressing the demand side.

Physician Use of Electronic Health Records: Survey Study Assessing Factors Associated With Provider Reported Satisfaction and Perceived Patient Impact

BACKGROUND

The effect electronic health record (EHR) implementation has on physician satisfaction and patient care remains unclear. A better understanding of physician perceptions of EHRs and factors that influence those perceptions is needed to improve the physician and patient experience when using EHRs.

OBJECTIVE

The objective of this study was to determine provider and clinical practice factors associated with physician EHR satisfaction and perception of patient impact.

METHODS

We surveyed a random sample of physicians, including residents and fellows, at a US quaternary care academic hospital from February to March 2016. The survey assessed provider demographics, clinical practice factors (ie, attending, fellow, or resident), and overall EHR experience. The primary outcomes assessed were provider satisfaction and provider perceptions of impact to patient care. Responses on the satisfaction and patient impact questions were recorded on a continuous scale initially anchored at neutral (scale range 0 to 100: 0 defined as "extremely negatively" and 100 as "extremely positively"). Independent variables assessed included demographic and clinical practice factors, including perceived efficiency in using the EHR. One-way analysis of variance or the Kruskal-Wallis test was used for bivariate comparisons, and linear regression was used for multivariable modeling.

RESULTS

Of 157 physicians, 111 (70.7%) completed the survey; 51.4% (57/111) of the respondents were attending physicians, and of those, 71.9% (41/57) reported a >50% clinical full-time-equivalency and half reported supervising residents >50% of the time. A total of 50.5% (56/111) of the respondents were primary care practitioners, previous EHR experience was evenly distributed, and 12.6% (14/111) of the total sample were EHR super-users. Responses to how our current EHR affects satisfaction were rated above the neutral survey anchor point (mean 58 [SD 22]), as were their perceptions as to how the EHR impacts the patient (mean 61 [SD 18]). In bivariate comparisons, only physician age, clinical role (resident, fellow, or attending), and perceived efficiency were associated with EHR satisfaction. In the linear regression models, physicians with higher reported perceived efficiency reported higher overall satisfaction and patient impact after controlling for other variables in the model.

CONCLUSIONS

Physician satisfaction with EHRs and their perception of its impact on clinical care were generally positive, but physician characteristics, greater age, and attending level were associated with worse EHR satisfaction. Perceived efficiency is the factor most associated with physician satisfaction with EHRs when controlling for other factors. Understanding physician perceptions of EHRs may allow targeting of technology resources to ensure efficiency and satisfaction with EHR system use during clinical care.

The Effect of Implementation of Standardized, Evidence-Based Order Sets on Efficiency and Quality Measures for Pediatric Respiratory Illnesses in a Community Hospital

OBJECTIVE

Standardization of evidence-based care, resource utilization, and cost efficiency are commonly used metrics to measure inpatient clinical care delivery. The aim of our project was to evaluate the effect of pediatric respiratory order sets and an asthma pathway on the efficiency and quality measures of pediatric patients treated with respiratory illnesses in an adult community hospital setting.

METHODS

We used a pre-post study to review pediatric patients admitted to the inpatient setting with the primary diagnoses of asthma, bronchiolitis, or pneumonia. Patients with concomitant chronic respiratory illnesses were excluded. After implementation of order sets and asthma pathway, we examined changes in respiratory medication use, hospital utilization cost, length of stay (LOS), and 30-day readmission rate. Statistical significance was measured via 2-tailed t-test and Fisher test.

RESULTS

After implementation of evidence-based order sets and asthma pathway, utilization of bronchodilators decreased and the hospital utilization cost of patients with asthma was reduced from $2010 per patient in 2009 to $1174 per patient in 2011 (P < .05). Asthma LOS decreased from 1.90 days to 1.45 days (P < .05), bronchiolitis LOS decreased from 2.37 days to 2.04 days (P < .05), and pneumonia LOS decreased from 2.3 days to 2.1 days (P = .083). Readmission rates were unchanged.

CONCLUSION

The use of order sets and an asthma pathway was associated with a reduction in respiratory treatment use as well as hospitalization utilization costs. Statistically significant decrease in LOS was achieved within the asthma and bronchiolitis populations but not in the pneumonia population. No statistically significant effect was found on the 30-day readmission rates.

Paediatric models in motion: requirements for model-based decision support at the bedside

Optimal paediatric pharmacotherapy is reliant on a detailed understanding of the individual patient including their developmental status and disease state as well as the pharmaceutical agents he/she is receiving for treatment or management of side effects. Our appreciation for size and maturation effects on the pharmacokinetic/pharmacodynamic (PK/PD) phenomenon has improved to the point that we can develop predictive models that permit us to individualize therapy, especially in the situation where we are monitoring drug effects or therapeutic concentrations. The growth of efforts to guide paediatric pharmacotherapy via model-based decision support necessitates a coordinated and systematic approach to ensuring reliable and robust output to caregivers that represents the current standard of care and adheres to governance imposed by the host institution or coalition responsible. Model-based systems which guide caregivers on dosing paediatric patients in a more comprehensive manner are in development at several institutions. Care must be taken that these systems provide robust guidance with the current best practice. These systems must evolve as new information becomes available and ultimately are best constructed from diverse data representing global input on demographics, ethnic / racial diversity, diet and other lifestyle factors. Multidisciplinary involvement at the project team level is key to the ultimate clinical valuation. Likewise, early engagement of clinical champions is also critical for the success of model-based tools. Adherence to regulatory requirements as well as best practices with respect to software development and testing are essential if these tools are to be used as part of the routine standard of care.

Pediatric aspects of inpatient health information technology systems

In the past 3 years, the Health Information Technology for Economic and Clinical Health Act accelerated the adoption of electronic health records (EHRs) with providers and hospitals, who can claim incentive monies related to meaningful use. Despite the increase in adoption of commercial EHRs in pediatric settings, there has been little support for EHR tools and functionalities that promote pediatric quality improvement and patient safety, and children remain at higher risk than adults for medical errors in inpatient environments. Health information technology (HIT) tailored to the needs of pediatric health care providers can improve care by reducing the likelihood of errors through information assurance and minimizing the harm that results from errors. This technical report outlines pediatric-specific concepts, child health needs and their data elements, and required functionalities in inpatient clinical information systems that may be missing in adult-oriented HIT systems with negative consequences for pediatric inpatient care. It is imperative that inpatient (and outpatient) HIT systems be adapted to improve their ability to properly support safe health care delivery for children.

Use of Electronic Health-Related Datasets in Nursing and Health-Related Research

Datasets of gigabyte size are common in medical sciences. There is increasing consensus that significant untapped knowledge lies hidden in these large datasets. This review article aims to discuss Electronic Health-Related Datasets (EHRDs) in terms of types, features, advantages, limitations, and possible use in nursing and health-related research. Major scientific databases, MEDLINE, ScienceDirect, and Scopus, were searched for studies or review articles regarding using EHRDs in research. A total number of 442 articles were located. After application of study inclusion criteria, 113 articles were included in the final review. EHRDs were categorized into Electronic Administrative Health-Related Datasets and Electronic Clinical Health-Related Datasets. Subcategories of each major category were identified. EHRDs are invaluable assets for nursing the health-related research. Advanced research skills such as using analytical softwares, advanced statistical procedures, dealing with missing data and missing variables will maximize the efficient utilization of EHRDs in research.

Lower rates of EMR use in rural hospitals represent a previously unexplored child health disparity

OBJECTIVES

Rural hospitals face significant barriers to adoption of advanced-stage electronic medical records (EMRs), which may translate to an unexplored disparity for children in rural hospitals. Our objective was to determine whether children hospitalized in rural settings are less likely to be cared for using advanced-stage EMRs.

METHODS

We merged the 2009 Healthcare Cost and Utilization Project Kids Inpatient Dataset with the 2009 Healthcare Information and Management Systems Society database. Logistic regression determined the independent relationship between receiving care in a rural hospital and advanced-stage EMRs.

RESULTS

A total of 430 055 (9.3%) of the 4 605 454 pediatric discharges were rural. Logistic regression analysis determined that even when an extensive list of various patient and hospital characteristics are accounted for, rurality continues to be a strong predictor of a child's care without advanced-stage EMRs (odds ratio 0.3; 95% confidence interval, 0.2-0.5).

CONCLUSIONS

Children hospitalized in a rural hospital are less than half as likely to be treated using advanced-stage EMRs. A focus of government and hospital policies to expand the use of EMRs among rural hospitals may reduce this child health care disparity.

Computerized decision support in adult and pediatric critical care

Computerized decision support (CDS) is the most advanced form of clinical decision support available and has evolved with innovative technologies to provide meaningful assistance to medical professionals. Critical care clinicians are in unique environments where vast amounts of data are collected on individual patients, and where expedient and accurate decisions are paramount to the delivery of quality healthcare. Many CDS tools are in use today among adult and pediatric intensive care units as diagnostic aides, safety alerts, computerized protocols, and automated recommendations for management. Some CDS use have significantly decreased adverse events and improved costs when carefully implemented and properly operated. CDS tools integrated into electronic health records are also valuable to researchers providing rapid identification of eligible patients, streamlining data-gathering and analysis, and providing cohorts for study of rare and chronic diseases through data-warehousing. Although the need for human judgment in the daily care of critically ill patients has limited the study and realization of meaningful improvements in overall patient outcomes, CDS tools continue to evolve and integrate into the daily workflow of clinicians, and will likely provide advancements over time. Through novel technologies, CDS tools have vast potential for progression and will significantly impact the field of critical care and clinical research in the future.

Electronic health record use and preventive counseling for US children and adolescents

The objective was to assess whether rates of preventive counseling delivered at well child visits (WCVs) differ for practices with basic, fully functional, or no electronic health record (EHR). Cross-sectional analyses of WCVs included in the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey Electronic Medical Records Supplement, 2007-2010 were performed. Practices with fully functional EHRs documented delivery of 34% more counseling topics than those without an EHR. WCVs with a fully functional EHR lasted 3.5 more minutes than those with a basic EHR. Overall, for each additional 10 min, 12% more topics were covered, regardless of EHR functionality. Further studies should assess the impact of such systems on the quality of patient care during preventive care visits and on health outcomes.