Showing papers in "Journal of Medical Systems in 2007"

Organizational and Environmental Determinants of Hospital EMR Adoption: A National Study

Abstract: The recent focus on health care quality improvement and cost containment has led some policymakers and practitioners to advocate the adoption of health information technology. One such technology is the Electronic Medical Record (EMR), which is predicted to change and improve health care in the USA. Little is known about factors that influence hospital adoption of this relatively new technology. The purpose of this paper is to determine the national prevalence of EMR adoption in acute care hospitals while examining the organizational and environmental correlates using a Resource Dependence Theoretical Perspective. Significant predictors of hospital EMR use may indicate barriers to use for some hospitals and can be used to guide policy. This study uses a non-experimental cross sectional design to examine hospital EMR use in 2004. A logistic regression approach is used to determine the correlations between hospital EMR use and organizational and environmental characteristics. Hospital EMR use was identified using the HIMSS Analytics data. Organizational and environmental variables were measured using data from the AHA, CMS (financial and case mix) and ARF. Hospital EMR adoption is significantly associated with environmental uncertainty, type of system affiliation, size, and urban-ness. The effects of competition, munificence, ownership, teaching status, public payer mix, and operating margin were not statistically significant. Significant predictors of hospital EMR adoption represent barriers that may prevent certain hospitals from obtaining and using EMRs. These hospitals include those that are smaller, more rural, non-system affiliated, and in areas of low environmental uncertainty. Since EMR adoption may be an organizational survival strategy for hospitals to improve quality and efficiency, hospitals that are at risk of missing the wave of implementation should be offered services and incentives to enable them to implement and maintain EMR systems.

Closing Emergency Operating Rooms Improves Efficiency

Abstract: Long waiting times for emergency operations increase a patient's risk of postoperative complications and morbidity. Reserving Operating Room (OR) capacity is a common technique to maximize the responsiveness of an OR in case of arrival of an emergency patient. This study determines the best way to reserve OR time for emergency surgery. In this study two approaches of reserving capacity were compared: (1) concentrating all reserved OR capacity in dedicated emergency ORs, and (2) evenly reserving capacity in all elective ORs. By using a discrete event simulation model the real situation was modelled. Main outcome measures were: (1) waiting time, (2) staff overtime, and (3) OR utilisation were evaluated for the two approaches. Results indicated that the policy of reserving capacity for emergency surgery in all elective ORs led to an improvement in waiting times for emergency surgery from 74 (±4.4) minutes to 8 (±0.5) min. Working in overtime was reduced by 20%, and overall OR utilisation can increase by around 3%. Emergency patients are operated upon more efficiently on elective Operating Rooms instead of a dedicated Emergency OR. The results of this study led to closing of the Emergency OR in the Erasmus MC (Rotterdam, The Netherlands).

Methods to Evaluate Health information Systems in Healthcare Settings: A Literature Review

Abstract: Although information technology (IT)-based applications in healthcare have existed for more than three decades, methods to evaluate outputs and outcomes of the use of IT-based systems in medical informatics is still a challenge for decision makers, as well as to those who want to measure the effects of ICT in healthcare settings. The aim of this paper is to review published articles in the area evaluations of IT-based systems in order to gain knowledge about methodologies used and findings obtained from the evaluation of IT-based systems applied in healthcare settings. The literature review includes studies of IT-based systems between 2003 and 2005. The findings show that economic and organizational aspects dominate evaluation studies in this area. However, the results focus mostly on positive outputs such as user satisfaction, financial benefits and improved organizational work. This review shows that there is no standard framework for evaluation effects and outputs of implementation and use of IT in the healthcare setting and that until today no studies explore the impact of IT on the healthcare system' productivity and effectiveness.

Wireless Body Sensor Network Using Medical Implant Band

Abstract: A wireless body sensor network hardware has been designed and implemented based on MICS (Medical Implant Communication Service) band. The MICS band offers the advantage of miniaturized electronic devices that can either be used as an implanted node or as an external node. In this work, the prototype system uses temperature and pulse rate sensors on nodes. The sensor node can transmit data over the air to a remote central control unit (CCU) for further processing, monitoring and storage. The developed system offers medical staff to obtain patient's physiological data on demand basis via the Internet. Some preliminary performance data is presented in the paper.

Exploring Physician Adoption of EMRs: A Multi-Case Analysis

Abstract: The adoption of new technology within healthcare has been promoted as a way to reduce costs and increase efficiencies as well as improve quality. The literature has documented a significant number of implementation failures by large groups and hospitals with access to IT skills and resources. Given the low adoption rate among physicians, the challenges facing small practices can be daunting. While financial and technical barriers have been explored at the physician level, the actual implementation challenges facing small groups have not been explored. This paper presents a qualitative three case analysis of physician groups that have employed EMRs and the pre and post adoption insights. Results show that planning was a key common variable missing; the anticipated downtime was longer than expected and the workflow disruption and maintenance costs were underestimated.

Factors Affecting Inpatient Satisfaction: Structural Equation Modeling

Abstract: Objective: Our study aimed to identify factors affecting patient satisfaction. Data: The study was conducted at a training hospital in Turkey. The final sample consisted of 302 inpatients. In this study, patient satisfaction was examined using a survey questionnaire with 22 questions collected under five dimensions. Method: Factor analysis was used to group 22 questions measuring patients' satisfaction questions into certain dimensions. Then, structural equation model (SEM) was performed to determine the influence of patient characteristics on patient satisfaction. Results: Our analysis showed the questionnaire has an appropriate reliability and validity. The structural equation model (SEM) was used to determine those factors which could affect patient satisfaction. The results of SEM analysis showed that 15% of the total variance in patients' satisfaction was explained by the model. The SEM analysis found that variables of education and type of clinic (surgical vs. non-surgical) were significant on patient satisfaction. Persons with a higher level of education were less satisfied when compared to those with a lower level of education. Surgical patients are more satisfied with the care they received when compared to non-surgical patients. Conclusion: The education level of patients and the type of clinics had a significant influence on patient satisfaction.

Effects of a Computer-based Nursing Documentation System on the Quality of Nursing Documentation

Abstract: Nursing documentation is an important part of clinical documentation. However, documentation of the nursing process is frequently lacking quality. There are high expectations that computer support in nursing documentation will help improve documentation quality. This study aimed to examine whether the introduction of a computer based nursing documentation system can improve documentation quality. A prospective intervention study was conducted on 4 wards of the University Medical Center Heidelberg over a period of 18 months. Two wards in the Psychiatric University Medical Center Heidelberg were involved in the research study, as well as a dermatological and a pediatric ward. The results of the study show a significant improvement of documentation quantity and quality on three of the four wards. Positive aspects include completeness of documentation on the nursing process, formal aspects and subjective quality improvement by the nurses. Negative aspects were mainly associated with the contents of the care plans.

Efficiency Measurement for Hospitals Owned by the Iranian Social Security Organisation

Abstract: This study used Data Envelopment Analysis (DEA) to examine the relative efficiency of hospitals owned by the Iranian Social Security Organization, which is the second largest institutional source of hospital care in that country. Using data for the year 2002, 26 of the 53 hospitals were deemed to be efficient. Inefficient hospitals had an average score of 90%, implying a potential reduction in all inputs on average by about 10% with no impact on output levels. In addition to the conventional DEA measurement, efficient hospitals were ranked by calculating super-efficiency scores, by identifying weak efficient hospitals, and by determining the frequency of peers. The study provides useful information for improving hospital management, rationalizing resource allocation, and improving services provided by hospitals.

The Use of Information Technologies Among Rural and Urban Physicians in Florida

Abstract: This study examines rural---urban differences in the use of various information technologies (IT) applications by physicians in the ambulatory setting. Findings suggest that no differences exist between rural and urban physicians with respect to the use of a computer (77.4 vs 81.4; p?=?.144) or with the availability of an Internet connection (95.0 vs 96.5; p?=?.249) in the office. However, rural physicians were significantly less likely than urban doctors to indicate using e-mail with patients (7.9 vs 17.2%; p?

A Norm Utilisation for Scarce Hospital Resources: Evidence from Operating Rooms in a Dutch University Hospital

Abstract: Background Utilisation of operating rooms is high on the agenda of hospital managers and researchers. Many efforts in the area of maximising the utilisation have been focussed on finding the holy grail of 100% utilisation. The utilisation that can be realised, however, depends on the patient mix and the willingness to accept the risk of working in overtime.

The Influence of Job Characteristics on Job Outcomes of Pharmacists in Hospital, Clinic, and Community Pharmacies

Abstract: This study examines the relationship between job characteristics and job outcomes of pharmacists in hospital, clinic, and community pharmacies in Taiwan. The structured questionnaires covered the items of job characteristics, job outcomes, and demographics of pharmacists, and were distributed between Feb 2004 and April 2004. Two hundred and ninety-eight pharmacists responded. Data were analyzed descriptively, and univariate analyses, factor analysis, and multiple regression analyses were used. It found the more enriched the job, the greater the job satisfaction and less intention to leave. And community pharmacists reported greater job enrichment and job satisfaction and less intention to leave than did hospital and clinic pharmacists. It suggests pharmacy managers could recognize the needs of pharmacists to redesign and enrich their work arrangements.

Backpropagation Artificial Neural Network Classifier to Detect Changes in Heart Sound due to Mitral Valve Regurgitation

Abstract: The phonocardiograph (PCG) can provide a non-invasive diagnostic ability to the clinicians and technicians to compare the heart acoustic signal obtained from normal and that of pathological heart (cardiac patient). This instrument was connected to the computer through the analog to digital (A/D) converter. The digital data stored for the normal and diseased (mitral valve regurgitation) heart in the computer were decomposed through the Coifman 4th order wavelet kernel. The decomposed phonocardiographic (PCG) data were tested by backpropagation artificial neural network (ANN). The network was containing 64 nodes in the input layer, weighted from the decomposed components of the PCG in the input layer, 16 nodes in the hidden layer and an output node. The ANN was found effective in differentiating the wavelet components of the PCG from mitral valve regurgitation confirmed person (93%) to normal subjects (98%) with an overall performance of 95.5%. This system can also be used to detect the defects in cardiac valves especially, and other several cardiac disorders in general.

Consent Mechanisms for Electronic Health Record Systems: A Simple Yet Unresolved Issue

Abstract: Electronic health record (EHR) systems are now in widespread use in healthcare institutions worldwide. EHRs include sensitive health information and if they are integrated among healthcare providers, data can be accessible from many different sources. This leads to increased concern regarding invasion of privacy and confidentiality. Incorporating consent mechanisms into EHRs has the potential to enhance confidentiality. However there are both positive and negative effects from employing such mechanisms--they need to balance privacy, safety, consumer and public interest.

Automated Detection of Anesthetic Depth Levels Using Chaotic Features with Artificial Neural Networks

Abstract: Monitoring the depth of anesthesia (DOA) during surgery is very important in order to avoid patients' interoperative awareness. Since the traditional methods of assessing DOA which involve monitoring the heart rate, pupil size, sweating etc, may vary from patient to patient depending on the type of surgery and the type of drug administered, modern methods based on electroencephalogram (EEG) are preferred. EEG being a nonlinear signal, it is appropriate to use nonlinear chaotic parameters to identify the anesthetic depth levels. This paper discusses an automated detection method of anesthetic depth levels based on EEG recordings using non-linear chaotic features and neural network classifiers. Three nonlinear parameters, namely, correlation dimension (CD), Lyapunov exponent (LE) and Hurst exponent (HE) are used as features and two neural network models, namely, multi-layer perceptron network (feed forward model) and Elman network (feedback model) are used for classification. The neural network models are trained and tested with single and multiple features derived from chaotic parameters and the performances are evaluated in terms of sensitivity, specificity and overall accuracy. It is found from the experimental results that the Lyapunov exponent feature with Elman network yields an overall accuracy of 99% in detecting the anesthetic depth levels.

How Can Activity-Based Costing Methodology Be Performed as a Powerful Tool to Calculate Costs and Secure Appropriate Patient Care?

Abstract: Previous studies have shown the advantages of using activity-based costing (ABC) methodology in the health care industry. The potential values of ABC methodology in health care are derived from the more accurate cost calculation compared to the traditional step-down costing, and the potentials to evaluate quality or effectiveness of health care based on health care activities. This project used ABC methodology to profile the cost structure of inpatients with surgical procedures at the Department of Colorectal Surgery in a public teaching hospital, and to identify the missing or inappropriate clinical procedures. We found that ABC methodology was able to accurately calculate costs and to identify several missing pre- and post-surgical nursing education activities in the course of treatment.

Predicting Metastasis in Breast Cancer: Comparing a Decision Tree with Domain Experts

Abstract: Breast malignancy is the second most common cause of cancer death among women in Western countries. Identifying high-risk patients is vital in order to provide them with specialized treatment. In some situations, such as when access to experienced oncologists is not possible, decision support methods can be helpful in predicting the recurrence of cancer. Three thousand six hundred ninety-nine breast cancer patients admitted in south-east Sweden from 1986 to 1995 were studied. A decision tree was trained with all patients except for 100 cases and tested with those 100 cases. Two domain experts were asked for their opinions about the probability of recurrence of a certain outcome for these 100 patients. ROC curves, area under the ROC curves, and calibration for predictions were computed and compared. After comparing the predictions from a model built by data mining with predictions made by two domain experts, no significant differences were noted. In situations where experienced oncologists are not available, predictive models created with data mining techniques can be used to support physicians in decision making with acceptable accuracy.

Regional Health Information Organizations: A Vehicle for Transforming Health Care Delivery?

Abstract: Information technology (IT) has the potential to be a significant enabler in transforming the health care delivery system. New types of organizations are needed to guide the change. Regional Health Information Organizations (RHIOs) hold promise as agents for transformation. This essay discusses the results from a case study on how RHIOs are advancing IT adoption in the health care community. Results indicate that the RHIO model is early in its evolution. To be a catalyst of change, the RHIO must overcome privacy barriers, actively engage purchasers of care, and create compelling incentives for clinicians to adopt the RHIOs' services.

The Role of Simulation and Modeling in Disaster Management

Abstract: The threat of pandemic disaster has motivated many collaborative exercises for the purpose of preparation and evaluation. The nature of these exercises depends upon the status of pre-existing expectations for system behavior and the aims of the exercise stakeholders. The contents of this article argue that these exercises may be developed using the same approach as simulation modeling to advantage. Four levels of maturity are outlined as a guide to understanding reasonable expectations for such activity.

Linear Models of Cumulative Distribution Function for Content-based Medical Image Retrieval

Abstract: We propose an Image matching technique based on Cumulative Distribution Function, which provides a considerable reduction in the retrieval time. The two novel approaches called bit plane histogram and hierarchical bit plane histogram are discussed. Next, the image matching technique based on Cumulative Distribution Function is explained and a comparison of the various techniques is brought out. The CDF of the query and the images in the database are approximated by piecewise linear models with two parameters, slope and intercept at various grayscale intervals. The contiguous set of lines approximating the CDFs enables us to compare the query image and the images in the database with corresponding estimated slopes and intercepts. As the dynamic range of CDF is from 0 to 1, images of different sizes can be compared. Approximation of CDFs with lines further reduces the dimension of the image features and thus improves the speed of matching.

Comparison of the Levels of Accuracy of an Artificial Neural Network Model and a Logistic Regression Model for the Diagnosis of Acute Appendicitis

Abstract: An accurate diagnosis of acute appendicitis in the early stage is often difficult, and decision support tools to improve such a diagnosis might be required. This study compared the levels of accuracy of artificial neural network models and logistic regression models for the diagnosis of acute appendicitis. Data from 169 patients presenting with acute abdomen were used for the analyses. Nine variables were used for the evaluation of the accuracy of the two models. The constructed models were validated by the ".632+ bootstrap method". The levels of accuracy of the two models for diagnosis were compared by error rate and areas under receiver operating characteristic curves. The artificial neural network models provided more accurate results than did the logistic regression models for both indices, especially when categorical variables or normalized variables were used. The most accurate diagnosis was obtained by the artificial neural network model using normalized variables.

E-Nose System for Anesthetic Dose Level Detection using Artificial Neural Network

Abstract: In this study, an E-Nose system was realized for the anesthetic dose level prediction. For this purpose, sevoflurane anesthetic agent was measured using the E-Nose system implemented with sensor array of quartz crystal microbalances (QCM). In surgeries, anesthetic agents are given to the patients with carrier gases of oxygen (O2) and nitrous oxide (N2O). Frequency changes on QCM sensors to the eight sevoflurane anesthetic dose levels were recorded via RS-232 serial port. A multilayer feed forward artificial neural network (MLNN) structure was used to provide the relationship between the frequency change and the anesthetic dose level. The MLNNs were trained with the measured data using Levenberg---Marquardt algorithm. Then, the trained MLNNs were tested with random data. The results have showed that, acceptable anesthetic dose level predictions have been obtained successfully.

Internet Use by Hospice Families and Providers: A Review

Abstract: This literature review explores the current evidence related to use of the Internet by hospice patients or families and palliative care/hospice professionals. The research questions guiding this study pertain to the current Internet-based interventions in hospice and palliative care and the evidence of their effectiveness. Six studies were identified as a result of an extensive literature review. These studies included research about web-based clinical interventions for patients, and patients', caregivers' and hospice/palliative care providers' use of the Internet. The majority of interventions involve accessing information via the Internet. Participants among the studies included patients, caregivers/family members, and health care professionals. Findings overall indicate effectiveness of Internet-based interventions. Both patients and professionals are using the Internet to find answers to healthcare questions, communicate, and/or deliver healthcare interventions.

What Do Young Adults Expect When They Go Online? Lessons for Development of an STD/HIV and Pregnancy Prevention Website

Abstract: We used participatory research to develop a theoretically based online STD/HIV and pregnancy prevention intervention that would be entertaining and captivating for 15---25 year olds while delivering key messages about condom use. We conducted six focus groups with 15---25 year olds attending reproductive health clinics and completed a content analysis with focus group data. Youth had expectations that websites contain features such as graphics and flash technology. They would participate in research online if their confidentiality was assured and if they could receive an instant incentive. Limited access to high-end bandwidth capability requires use of compressed graphics and music to reach diverse audiences. Youth suggested approaches to frame role-model delivered messages about HIV/STD and pregnancy risk, condom attitudes, norms and self-efficacy for negotiation. These data allowed for development of a dynamic, interactive and relatively low bandwidth site that retains fidelity to key theoretical constructs in STD/HIV and pregnancy prevention.

Factors Influencing Community Health Centers' Efficiency: A Latent Growth Curve Modeling Approach

Abstract: The objective of study is to examine factors affecting the variation in technical and cost efficiency of community health centers (CHCs). A panel study design was formulated to examine the relationships among the contextual, organizational structural, and performance variables. Data Envelopment Analysis (DEA) of technical efficiency and latent growth curve modeling of multi-wave technical and cost efficiency were performed. Regardless of the efficiency measures, CHC efficiency was influenced more by contextual factors than organizational structural factors. The study confirms the independent and additive influences of contextual and organizational predictors on efficiency. The change in CHC technical efficiency positively affects the change in CHC cost efficiency. The practical implication of this finding is that healthcare managers can simultaneously optimize both technical and cost efficiency through appropriate use of inputs to generate optimal outputs. An innovative solution is to employ decision support software to prepare an expert system to assist poorly performing CHCs to achieve better cost efficiency through optimizing technical efficiency.

Ultrasound Kidney Image Analysis for Computerized Disorder Identification and Classification Using Content Descriptive Power Spectral Features

Abstract: The objective of this work is to classify few important kidney categories by characterizing the tissues of kidney region using the unique power spectral features with ultrasound as imaging modality. The images are acquired from male and female subjects of age 45?±?15 years. Three kidney categories namely normal, medical renal diseases and cortical cyst are considered for the analysis. The acquired images are initially pre-processed to retain the pixels-of-interest. The proposed features depend on the spatial distribution of spectral components in the kidney region. A set of power spectral features $ {\rm P}^{{W_{1} }}_{T} ,\,{\rm P}^{{W_{2} }}_{T} ,\,{\rm P}^{{R_{1} }}_{{T - W_{{12}} }} ,\,{\rm P}^{{R_{2} }}_{{T - W_{{12}} }} ,\,{\rm P}^{{R_{3} }}_{{T - W_{{1d}} }} $ and $ {\rm P}^{{R_{4} }}_{{T - W_{{1d}} }} $ are estimated at the specific cut-off frequencies ? rc1 and ? rc2 in the spectrum and by considering global mean total power. The results obtained show that the features are highly content descriptive and provide discrete range of values for each kidney category. Such isolated feature values facilitate to identify the kidney categories objectively which may be used as a secondary observer. The proposed method and features also explores the possibility of implementing computer-aided diagnosis system exclusively for US kidney images.

Detection of Obstructive Respiratory Abnormality Using Flow---Volume Spirometry and Radial Basis Function Neural Networks

Abstract: In this work detection of pulmonary abnormalities carried out using flow-volume spirometer and Radial Basis Function Neural Network (RBFNN) is presented. The spirometric data were obtained from adult volunteers (N?=?100) with standard recording protocol. The pressure and resistance parameters were derived using the theoretical approximation of the activation function representing pressure---volume relationship of the lung. The pressure---time and resistance---expiration volume curves were obtained during maximum expiration. The derived values together with spirometric data were used for classification of normal and obstructive abnormality using RBFNN. The results revealed that the proposed method is useful for detecting the pulmonary functions into normal and obstructive conditions. RBFNN was found to be effective in differentiating the pulmonary data and it was confirmed by measuring accuracy, sensitivity, specificity and adjusted accuracy. As spirometry still remains central in the observations of pulmonary function abnormalities these studies seems to be clinically relevant.

Effects of Antenatal Care Services on Birthweight: Importance of Model Specification and Empirical Procedure Used in Estimating the Marginal Productivity of Health Inputs

Abstract: This paper is an attempt to examine the effects of antenatal care (ANC) utilization on birthweight. The analysis is based on the data collected from ever-married women by Turkey Demographic and Health Survey 1998 (TDHS). Cost-effectiveness based health sector reform requires careful estimation of costs and productivity of health interventions as well as the substitution possibility among health inputs. If the parameters of production function are known, policy makers can estimate the health outcome effects of various input-mix. Two-stage least squares (TSLS) and ordinary least squares (OLS) estimation procedures are used in this paper to estimate the effect of health care input, namely antenatal care visits, on birthweight. Since the utilization of medical care itself may be dependent on women's expectation about the pregnancy outcome, the parameters estimated through OLS may underestimate the true productivity of the input. The estimated functions indicate that antenatal care, woman's health status, and birth order are significant determinants in birthweight. The TSLS estimate of marginal productivity of ANC visits was about four times the marginal productivity estimate in the OLS model. The sensitivity of the parameter estimates to model specifications and empirical procedures followed demonstrates the importance of selecting the right model from both theoretical and empirical point of view.

Is the Availability of Hospital IT Applications Associated with a Hospital's Risk Adjusted Incidence Rate for Patient Safety Indicators: Results from 66 Georgia Hospitals

Abstract: This study examines the associations between the availability of IT applications in a hospital and that hospital's risk adjusted incidence rate per 1,000 hospitalizations for Agency for Healthcare Research and Quality's (AHRQ) 15 Patient Safety Indicators (PSIs). The study population consists of a convenience sample of 66 community hospitals in Georgia that completed a Hospital IT survey by December 2003 and provided data to Georgia Hospital Discharge Data Set during 2004. AHRQ's PSI software was used to estimate risk adjusted incidence rates. Differences in means, Pearson correlation coefficients, and multivariate regression analysis were used to determine if the availability of IT applications were associated with better PSI outcomes. This study finds very little statistically significant correlation between the availability of IT applications and risk adjusted PSI incident rate per 1,000 hospitalizations. In the multivariate regression models, the overall availability of IT applications in a hospital was significantly and negatively associated with the risk adjusted incident rate for only postoperative hemorrhage or hematoma. The count of functional applications available was negatively associated with postoperative hemorrhage or hematoma and foreign body left during procedure, while the count of technological devices was only associated with postoperative hemorrhage or hematoma. This study finds that the overall number of functional applications and technological devices available in a hospital is not associated with improved risk adjusted PSI outcomes. Future research is needed to examine if specific IT applications in specific clinical areas of the hospital are associated with improved PSI outcomes.

Electronic Medical Records for a Rural Family Practice: A Case Study In Systems Development

Abstract: In this paper, we describe the planning, development, and overall impact of Electronic Medical Records (EMRs) on Dryden Family Medicine (DFM), a rural family practice in Dryden, New York. The EMR system was installed in July, 2003, and the full conversion to the new system was accomplished in three phases. Significant efficiency gains were achieved in billing, prescription ordering, and other routine processes. Protocols were developed to enhance quality management, preventive medicine, and disease management. Job responsibilities changed and expanded for all members of the practice and coding issues became paramount. Practice revenue increased by about 20 percent and average "case-mix" increased by 10 percent in the second year following the implementation of EMRs due to improved billing documentation. We focus on the implementation process, the lessons learned, the obstacles encountered, and the successes achieved by one rural family practice.

EDI and ERP: A Real-Time Framework for HealthCare Data Exchange

Abstract: A framework is presented for Enterprise Resource Planning (ERP) and Electronic Data Interchange (EDI) in the healthcare industry. As the total cost of healthcare continues to rise and competitive pressures increase, the ability to reduce expenses while at the same time improving overall business characteristics, create an opportunity and necessity for technology usage. The framework addresses current barriers of EDI setup such as cost and flexibility along with ERP communication between entities. A prototype system is created to show feasibility of recent technology improvements and generate a proof of concept for the real-time framework.