Advanced Electronic Medical Record Research Articles

Specific patterns and potential risk factors to predict 3-year risk of death among non-cancer patients with advanced chronic kidney disease by machine learning.

Chronic kidney disease (CKD) is a major public health concern. But there are limited machine learning studies on non-cancer patients with advanced CKD, and the results of machine learning studies on cancer patients with CKD may not apply directly on non-cancer patients. We aimed to conduct a comprehensive investigation of risk factors for a 3-year risk of death among non-cancer advanced CKD patients with an estimated glomerular filtration rate < 60.0 mL/min/1.73m2 by several machine learning algorithms. In this retrospective cohort study, we collected data from in-hospital and emergency care patients from 2 hospitals in Taiwan from 2009 to 2019, including their international classification of disease at admission and laboratory data from the hospital's electronic medical records (EMRs). Several machine learning algorithms were used to analyze the potential impact and degree of influence of each factor on mortality and survival. Data from 2 hospitals in northern Taiwan were collected with 6565 enrolled patients. After data cleaning, 26 risk factors and approximately 3887 advanced CKD patients from Shuang Ho Hospital were used as the training set. The validation set contained 2299 patients from Taipei Medical University Hospital. Predictive variables, such as albumin, PT-INR, and age, were the top 3 significant risk factors with paramount influence on mortality prediction. In the receiver operating characteristic curve, the random forest had the highest values for accuracy above 0.80. MLP, and Adaboost had better performance on sensitivity and F1-score compared to other methods. Additionally, SVM with linear kernel function had the highest specificity of 0.9983, while its sensitivity and F1-score were poor. Logistic regression had the best performance, with an area under the curve of 0.8527. Evaluating Taiwanese advanced CKD patients' EMRs could provide physicians with a good approximation of the patients' 3-year risk of death by machine learning algorithms.

EGFR slope as a surrogate endpoint for end-stage kidney disease in patients with diabetes and eGFR > 30 mL/min/1.73 m2 in the J-DREAMS cohort

BackgroundAn analysis of European and American individuals revealed that a reduction in estimated glomerular filtration rate (eGFR) slope by 0.5 to 1.0 mL/min/1.73 m2 per year is a surrogate endpoint for end-stage kidney disease (ESKD) in patients with early chronic kidney disease. However, it remains unclear whether this can be extrapolated to Japanese patients.MethodsUsing data from the Japan diabetes comprehensive database project based on an advanced electronic medical record system (J-DREAMS) cohort of 51,483 Japanese patients with diabetes and a baseline eGFR ≥ 30 mL/min/1.73 m2, we examined whether the eGFR slope could be a surrogate indicator for ESKD. The eGFR slope was calculated at 1, 2, and 3 years, and the relationship between each eGFR slope and ESKD risk was estimated using a Cox proportional hazards model to obtain adjusted hazard ratios (aHRs).ResultsSlower eGFR decline by 0.75 mL/min/1.73 m2/year reduction in 1-, 2-, and 3-year slopes was associated with lower risk of ESKD (aHR 0.93 (95% confidence interval (CI) 0.92–0.95), 0.84 (95% CI 0.82–0.86), and 0.77 (95% CI 0.73–0.82), respectively); this relationship became more apparent as the slope calculation period increased. Similar results were obtained in subgroup analyses divided by baseline eGFR or baseline urine albumin-creatinine ratio (UACR), with a stronger correlation with ESKD in the baseline eGFR < 60 mL/min/1.73 m2 group and in the baseline UACR < 30 mg/gCre group.ConclusionWe found that changes in the eGFR slope were associated with ESKD risk in this population.

An online intelligent electronic medical record system via speech recognition

Traditional electronic medical record systems in hospitals rely on healthcare workers to manually enter patient information, resulting in healthcare workers having to spend a significant amount of time each day filling out electronic medical records. This inefficient interaction seriously affects the communication between doctors and patients and reduces the speed at which doctors can diagnose patients’ conditions. The rapid development of deep learning–based speech recognition technology promises to improve this situation. In this work, we build an online electronic medical record system based on speech interaction. The system integrates a medical linguistic knowledge base, a specialized language model, a personalized acoustic model, and a fault-tolerance mechanism. Hence, we propose and develop an advanced electronic medical record system approach with multi-accent adaptive technology for avoiding the mistakes caused by accents, and it improves the accuracy of speech recognition obviously. For testing the proposed speech recognition electronic medical record system, we construct medical speech recognition data sets using audio and electronic medical records from real medical environments. On the data sets from real clinical scenarios, our proposed algorithm significantly outperforms other machine learning algorithms. Furthermore, compared to traditional electronic medical record systems that rely on keyboard inputs, our system is much more efficient, and its accuracy rate increases with the increasing online time of the proposed system. Our results show that the proposed electronic medical record system is expected to revolutionize the traditional working approach of clinical departments, and it serves more efficient in clinics with low time consumption compared with traditional electronic medical record systems depending on keyboard inputs, which has less recording mistakes and lows down the time consumption in modification of medical recordings; due to the proposed speech recognition electronic medical record system is built on knowledge database of medical terms, so it has a good generalized application and adaption in the clinical scenarios for hospitals.

Evolving competencies to align electronic medical records - adynamic resource-based perspective on hospitals' co-evolutionary information systems alignment capability.

Advanced Electronic Medical Records (EMR) provide many potential benefits to hospitals. However, because of their broad scope, many stakeholders deal with the EMR and a continuous effort has to be made to keep up with internal and external change. Therefore, hospitals need to deliberately shape their organizational competencies considering the pursuit of alignment, i.e. making sure that the EMR remains optimally aligned with strategies, goals and needs of the hospital and its stakeholders. This paper aims to investigate the evolutionary paths of these alignment competencies and their drivers, from a theoretical perspective of co-evolutionary information systems alignment (COISA). This paper reports on a longitudinal multiple case study of three Dutch hospitals which each recently implemented an advanced EMR system. The authors conducted 35 in-depth interviews in 2 phases (before and after go-live of the EMR), and studied documentation related to the EMR implementations. The findings show that each hospital's COISA capability shows a different evolutionary path. However, two of the three case hospitals ended up coordinating part of their COISA capability to an ecosystem level, i.e. they incorporated other hospitals using the same EMR system to coordinate their alignment efforts, either from an operational perspective, or in terms of orchestration and strategy. The found evolutionary paths' key drivers include "stakeholder initiative", "accumulating experience", "driving events" and "emerging issues". The findings help healthcare practitioners to deliberately shape their organization's COISA capability in pursuit of EMR alignment. Furthermore, the authors add to the knowledge base on co-evolutionary approaches to alignment through the longitudinal approach.

A mixed-methods study of pharmacy instructors' early experiences with a teaching electronic medical record

IntroductionAs use of electronic medical records (EMRs) increases in healthcare, multiple accreditation organizations recommend training future clinicians on EMRs as part of the academic curriculum. Therefore, some pharmacy programs now utilize an academic EMR. Our objective was to examine pharmacy instructors' early experiences with a commercially available teaching EMR (tEMR) in order to identify current and future priorities along with benefits and barriers to academic EMR use in pharmacy education. MethodsWe conducted semi-structured interviews and a web-based survey with pharmacy instructors. Interview and survey data analyses consisted of hybrid inductive/deductive approaches to coding data and descriptive statistics, respectively. We mapped themes to the Pharmacists' Patient Care Process (PPCP). ResultsSeven instructors participated in interviews, and 10 completed the survey. We identified 25 interview themes that were generally congruent with survey responses. A noted benefit of the tEMR was providing a large repository of real-life patient data. Instructors' current priorities for tEMR activities primarily aligned with “collect,” “assess,” and “plan” steps of the PPCP. One reported barrier was insufficient training regarding the tEMR capabilities. Instructors offered innovative ideas for future academic EMR use, including pharmacokinetics, incident reporting, and longitudinal cases. ConclusionsStudy findings are most applicable to pharmacy programs in the early stages of academic EMR adoption. We identified opportunities for pharmacy programs to facilitate innovative, future use of academic EMRs, including curriculum planning, so pharmacy students gain experience using EMR functions for each PPCP step and develop more advanced EMR skills.

Comorbidities and complications in Japanese patients with type 2 diabetes mellitus: Retrospective analyses of J-DREAMS, an advanced electronic medical records database

AimsTo investigate the prevalence of comorbid conditions/complications among Japanese patients with type 2 diabetes mellitus (T2DM) in a real-world setting. MethodsWe performed retrospective analyses of a large-scale database directly linked to electronic medical records, J-DREAMS (Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System), to determine the prevalence of clinically significant comorbid conditions/complications among Japanese patients with T2DM aged ≥ 20 years with ≥ 1 clinical encounter at a referral center between April 1, 2017 and March 31, 2019. ResultsData were available for 10,151 patients (39.2% female). The mean age and T2DM duration were 66.0 years and 16.1 years, respectively. Only 0.5% had isolated T2DM, 6.6% had one comorbid condition/complication, and the remainder had multiple comorbid conditions/complications. Dyslipidemia (84.7%) and hypertension (75.1%) were the most common, followed by chronic kidney disease (35.4%), retinopathy (23.1%), and cardiovascular diseases (22.1%). Overall, 36.0% of patients were overweight/obese (body mass index ≥ 25 kg/m2) and 18.6% had a history of neoplasms. The prevalence of comorbid conditions/complications tended to increase with advancing age and duration of T2DM. ConclusionsWe revealed a high prevalence of comorbid conditions/complications, including chronic kidney and cardiovascular diseases, in Japanese patients with T2DM.

Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review

BackgroundDespite a substantial increase in the adoption of electronic medical records (EMRs) in primary health care settings, the use of advanced EMR features is limited. Several studies have identified both barriers and facilitating factors that influence primary care physicians’ (PCPs) use of advanced EMR features and the maturation of their EMR use. The purpose of this study is to explore and identify the factors that impact PCPs’ mature use of EMRs.MethodsA systematic review was conducted in accordance with the Cochrane Handbook. The MEDLINE, Embase, and PsycINFO electronic databases were searched from 1946 to June 13, 2019. Two independent reviewers screened the studies for eligibility; to be included, studies had to address factors influencing PCPs’ mature use of EMRs. A narrative synthesis was conducted to collate study findings and to report on patterns identified across studies. The quality of the studies was also appraised.ResultsOf the 1893 studies identified, 14 were included in this study. Reported factors that influenced PCPs’ mature use of EMRs fell into one of the following 5 categories: technology, people, organization, resources, and policy. Concerns about the EMR system’s functionality, lack of physician awareness of EMR functionality, limited physician availability to learn more about EMRs, the habitual use of successfully completing clinical tasks using only basic EMR features, business-oriented organizational objectives, lack of vendor training, limited resource availability, and lack of physician readiness were reported as barriers to PCPs’ mature use of EMRs. The motivation of physicians, user satisfaction, coaching and peer mentoring, EMR experience, gender, physician perception, transition planning for changes in roles and work processes, team-based care, adequate technical support and training, sharing resources, practices affiliated with an integrated delivery system, financial incentives, and policies to increase EMR use all had a favorable impact on PCPs’ use of advanced EMR features.ConclusionsBy using a narrative synthesis to synthesize the evidence, we identified interrelated factors influencing the mature use of EMRs by PCPs. The findings underline the need to provide adequate training and policies that facilitate the mature use of EMRs by PCPs.Trial registration: PROSPERO CRD42019137526.

110. IMPROVING E-CIGARETTE AND VAPING USE SCREENING AMONG ADOLESCENTS

Background Recent data suggests that 27.5% of high school students reported using electronic cigarettes (e-cigarettes) in the past 30 days, a rise from 1.5% in 2011. Only 37% of adolescents recognized nicotine presence in these products. Screening, educating and providing cessation counseling for adolescents using e-cigarettes is fundamental. It has been documented that physicians infrequently screen or counsel their adolescent patients about e-cigarette use. According to a recent study, physicians using advanced electronic medical record (EMR) systems were more likely to record smoking status, and counsel patients on smoking cessation than those using less sophisticated technology, hence the idea to encourage the use of the e-cigarette/vaping screening tab in the EMR during adolescent visits. Aim Statement To improve e-cigarette/vaping use screening among adolescents attending school-based clinics to a minimum of 80% in six months by encouraging the use of a specific tab embedded in the EMR. Interventions This quality improvement project included a baseline retrospective chart review of 100 health maintenance and sports physical visits in four school-based clinics associated to a major Academic Medical Center in Miami, Florida. The first Plan-Do-Study-Act (PDSA) cycle consisted of an email sent to health care providers encouraging them to utilize the e-cigarette tab in the EMR. Measures 100 charts were reviewed one month after the intervention to assess whether e-cigarette use or vaping was assessed at health maintenance and sports physical visits in the same four school-based clinics. Results At baseline (September-October 2019) 23% of adolescent patients were screened for e-cigarette/vaping use. This varied by school location, ranging from 12-36%. In the first PDSA cycle (November-December 2019) 55% of adolescents were screened. This varied by school location, ranging from 16-88%. Conclusions and Next Steps Encouraging health care providers to use a designated e-cigarette screening tab embedded in the EMR through an email alert increased the number of patients screened during their health maintenance or sports physical visit. One of the four school-based clinics exceeded the goal of screening at least 80% of adolescents. Because locating the e-cigarette tab was identified as a barrier by some health care providers, a second intervention that included step-by-step information about where to access the tab was implemented. Results for the second PDSA cycle will be available February 2020.

Elicitation and prioritization of requirements for electronic health records for oncology in low resource settings: A concept mapping study

BackgroundUnderstanding functional and non-functional requirements is essential to successfully implement electronic medical record (EMR) systems. Actual requirements will be different for different contexts. ObjectiveTo elicit and prioritize requirements for implementing EMRs in oncology in low and middle income countries (LMICs), and to relate these to requirements from high-income countries. Participants and settingCancer care stakeholders including oncologists, general doctors, nurses, biostatisticians, information technologists, from different LMICs, were involved. MethodsConcept mapping was used. Statements of requirements were obtained during focus group discussions (FGDs) and interviews. Using surveys, the requirements were clustered and ranked on importance and feasibility. Data were analyzed in SPSS using agglomerative hierarchical clustering and multidimensional scaling, to create cluster maps and go-zone maps reflecting the relationships between the requirements and their prioritization. ResultsFour FGD sessions, with twenty participants, were conducted. In addition, six participants were interviewed. Twenty-two participants clustered the requirements and sixty-three participants ranked them on importance and feasibility.One hundred and sixty requirement statements were generated which were reduced to sixty-four after de-duplication and merging. Nine clusters were obtained encompassing the following domains, in order of importance: Security, Conducive organization, Management/Governance, General EMR functionalities, Computer infrastructure, Data management, Usability, Oncology decision support, and Ancillary requirements. On ranking, the requirements scored between 3.74 and 4.80 on importance, and between 3.55 and 4.46 on feasibility, on a 5-point Likert scale. We generated concept maps for use when communicating with stakeholders. ConclusionFor oncology EMRs in LMICs, requirements overlap those from high-income countries, but generic EMR functionalities, Infrastructural and organizational requirements are still considered priority in LMICs compared to oncology-specific requirements or advanced EMR features e.g. computerized decision support or interoperability. Concept mapping is a fast and cost-effective method for eliciting and prioritizing EMR requirements in a user-centered manner.

Primary Care Physicians' Experience Using Advanced Electronic Medical Record Features to Support Chronic Disease Prevention and Management: Qualitative Study.

BackgroundChronic diseases are the leading cause of death worldwide. In Canada, more than half of all health care spending is used for managing chronic diseases. Although studies have shown that the use of advanced features of electronic medical record (EMR) systems improves the quality of chronic disease prevention and management (CDPM), a 2012 international survey found that Canadian physicians were the least likely to use 2 or more EMR system functions. Some studies show that maturity vis-à-vis clinicians’ EMR use is an important factor when evaluating the use of advanced features of health information systems. The Clinical Adoption Framework (CAF), a common evaluation framework used to assess the success of EMR adoption, does not incorporate the process of maturing. Nevertheless, the CAF and studies that discuss the barriers to and facilitators of the adoption of EMR systems can be the basis for exploring the use of advanced EMR features.ObjectiveThis study aimed to explore the factors that primary care physicians in Ontario identified as influencing their use of advanced EMR features to support CDPM and to extend the CAF to include primary care physicians’ perceptions of how their use of EMRs for performing clinical tasks has matured.MethodsGuided by the CAF, directed content analysis was used to explore the barriers and facilitating factors encountered by primary care physicians when using EMR features. Participants were primary care physicians in Ontario, Canada, who use EMRs. Data were coded using categories from the CAF.ResultsA total of 9 face-to-face interviews were conducted from January 2017 to July 2017. Dimensions from the CAF emerged from the data, and one new dimension was derived: physicians’ perception of their maturity of EMR use. Primary care physicians identified the following key factors that impacted their use of advanced EMR features: performance of EMR features, information quality of EMR features, training and technical support, user satisfaction, provider’s productivity, personal characteristics and roles, cost benefits of EMR features, EMR systems infrastructure, funding, and government leadership.ConclusionsThe CAF was extended to include physicians’ perceptions of how their use of EMR systems had matured. Most participants agreed that their use of EMR systems for performing clinical tasks had evolved since their adoption of the system and that certain system features facilitated their care for patients with chronic diseases. However, several barriers were identified and should be addressed to further enhance primary care physicians’ use of advanced EMR features to support CDPM.

Development of Patient State Model to Overview Clinical Registry Database.

By applying the Bayesian network method to the clinical registry database J-DREAMS (Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System), we have developed a reference model that summarizes the exploration of the patient group's state and facilitates a bird's-eye view. This visualization method would help registry researchers to screen the registry database.

Electronic medical records and medical procedure choice: Evidence from cesarean sections.

This paper examines how hospital adoption of electronic medical records (EMRs) impacts medical procedure choice in the context of cesarean section deliveries. It provides a unique contribution by tying the literature on EMR diffusion to the literature on the utilization of expensive medical technology and provider practice style. Exploiting within-hospital variation in three types of EMR adoption, we find that computerized physician order entry, an advanced EMR system that typically incorporates decision support, reduces C-section rates for low-risk mothers by 2.5%. Obstetric-specific EMR systems and physician documentation have no statistically significant effect on C-section rates. In addition, we find that the computerized practitioner order entry effect occurs predominantly in hospitals that were already performing fewer C-sections and does not change the behavior of already high-intensity providers.

Influence of Patient Setting and Dedicated Limb Salvage Efforts on Outcomes in Charcot-Related Foot Ulcer.

Charcot neuroarthropathy is a devastating consequence of diabetes mellitus and peripheral neuropathy. Because of its rarity, the condition is often misdiagnosed or poorly managed. When misadventure occurs, patients with Charcot neuroarthropathy can suffer ulceration, infection, amputation, and death. When patients have Charcot-related foot ulcers, the risks are amplified. Utilizing advanced electronic medical record analysis, a 30-month investigation was undertaken to determine if patients with diabetes mellitus and a concomitant diagnosis of Charcot-related foot ulcer were at greater risk of complications because of location setting of initial treatment for their condition. Charcot foot-related ulcers that are diagnosed in the outpatient setting had established foot specialist care. The outpatient management of the condition lead to a significant reduction in the amount of admissions to a higher acuity setting. However, patient outcomes did not vary once established and dedicated limb salvage efforts were employed. In this large contemporary population managed in a tertiary health system, patients with Charcot-related foot ulcer had negative outcomes when they were initially treated in an inpatient setting and had a significantly greater likelihood of readmission as compared with individuals who had established focused limb salvage care.

Educational approaches for improving physicians' use of health information technology.

The benefits of Health Information Technology (HIT) depend on the way they are being used. Education and training are often needed to move from basic to advanced, value-adding, use. In this article, we describe three educational approaches that can help in achieving this goal: "productive failure," video tutorials, and simulation. We describe the rationale behind these approaches, their strengths, and limitations and illustrate their application, respectively, to three problems associated with the use of HIT in clinical practice: improving data quality within Electronic Medical Records (EMRs) at the point of data entry, use of advanced EMR features for chronic disease management, and impact of the EMR on patient-clinician communication. We conclude that, while these approaches are promising, there is a need for innovation and diversity of educational approaches to address use of advanced HIT features, identified challenges with HIT, and usage in context-as well as for rigorous evaluation.

Impact of a tailored training on advanced electronic medical records use for providers in a Veterans Health Administration Medical System.

This quality improvement project evaluated the impact of a tailored, evidence-based training strategy on advanced electronic medical record (EMR) use for Veterans Administration (VA) clinicians experienced in using the EMR. After developing the curriculum, an online needs assessment tool evaluated 20 clinicians' competency gaps. Responses were used to prioritize clinicians' training needs. Clinician informaticists then provided 2-4 h of tailored training to groups of 1-5 clinicians. Compared with baseline scores (M = 3.59), scores on EMR Task Comfort showed a large improvement in the week following training (M = 4.60; t = 5.41; P <.000, r = 0.58) regardless of baseline level of computer anxiety. Assessment and tailored training methods can help maximize the benefits of resources for EMR training. This formative evaluation suggests that tailored, hands-on training led by clinician informaticists effectively improved clinicians' EMR comfort and confidence in only 2-4 h.

Hospital Ownership Type and Innovation: The Case of Electronic Medical Records Adoption

Nonprofit and for-profit firms coexist in many industries, with the hospital sector being one of the most predominant examples. This article explores whether nonprofit hospitals are more likely to make expensive investments with uncertain returns and potential public good value. Specifically, we estimate differences in the adoption of electronic medical records (EMRs) by ownership structure. We find that nonprofit hospitals are 11 to 18 percentage points more likely to have installed advanced EMR systems than for-profit hospitals by 2012. Although we find little difference in the likelihood of meeting initial government requirements for the “meaningful use” of EMRs, we find that nonprofits are 12 percentage points more likely to reach more stringent meaningful use standards that began in 2014. That being said, nonprofit adoption rates decrease as for-profit market penetration rates increase, suggesting nonprofits are less likely to adopt an uncertain technology when facing more direct competition from for-profit hospitals.

Towards optimal electronic medical record use: perspectives of advanced users.

While primary health care electronic medical record (EMR) adoption has increased in Canada, the use of advanced EMR features is limited. Realizing the potential benefits of primary health care EMR use is dependent not only on EMR acquisition, but also on its comprehensive use and integration into practice; yet, little is known about the advanced use of EMRs in primary health care. To explore the views of advanced primary health care EMR users practising in a team-based environment. A descriptive qualitative approach was used to explore the views of primary health care practitioners who were identified as advanced EMR users. Twelve individual semi-structured interviews were held with primary health care practitioners in Southwestern Ontario, Canada. Field notes were created after each interview. Interviews were audio recorded and transcribed verbatim. Researchers independently coded the transcripts and then met to discuss the results of the coding. We used a thematic approach to data analysis. Three themes emerged from the data analysis: advanced EMR users as individuals with signature characteristics, advanced EMR users as visionaries and advanced EMR users as agents of change. In any one participant, these elements could overlap, illuminating the important interplay between these themes. Taken together, these themes defined advanced use among this group of primary health care practitioners. To realize the potential benefits of EMR use in improved patient care and outcomes, we need to understand how to support EMR use. This study provides a necessary building block in furthering this understanding.

Design of and rationale for the Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System (J-DREAMS).

The "Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System" is a registry of patients with diabetes in Japan. The characteristics of this registry include a clinical information input process using the template function of an electronic medical record (EMR) system [the standard diabetes management template (SDMT)], a standardized exchangeable information storage format [the Standardized Structured Medical Information eXchange 2(SS-MIX2)], and a secure and efficient information extraction process [Multipurpose Clinical Data Repository System(MCDRS)]. Together, these characteristics enable efficient data input during routine patient consultations, efficient and exact data extraction from each facility, and the integration of data across different facilities even though these data were generated by EMR systems from different vendors. The SDMT collects clinical information including the type of diabetes, body height and weight, blood pressure, lifestyle, and comorbidities. Completing this template triggers the automatic collection of other information such as fundamental information (sex, year and month of birth, and facility), prescription information, and laboratory examination results. As the information from every routine consultation is saved with an anonymized patient ID, linked data can be used as panel data allowing longitudinal investigations. The data obtained from the registry will allow analyses, for exmaple, mortality and morbidity risk, by various characteristics or drug types and may reveal unmet needs that inform future diabetes care.

Ceiling effect in EMR system assimilation: a multiple case study in primary care family practices

BackgroundThere has been indisputable growth in adoption of electronic medical record (EMR) systems in the recent years. However, physicians’ progress in using these systems has stagnated when measured with maturity scales. While this so-called ceiling effect has been observed and its consequences described in previous studies, there is a paucity of research on the elements that could explain such an outcome. We first suggest that in the context of EMR systems we are in presence of a “tiered ceiling effect” and then we show why such phenomenon occurs.MethodsWe conducted in-depth case studies in three primary care medical practices in Canada where physicians had been using EMR systems for 3 years or more. A total of 37 semi-structured interviews were conducted with key informants: family physicians (about half of the interviews), nurses, secretaries, and administrative managers. Additional information was obtained through notes taken during observations of users interacting with their EMR systems and consultation of relevant documents at each site. We used abductive reasoning to infer explanations of the observed phenomenon by going back and forth between the case data and conceptual insights.ResultsOur analysis shows that a ceiling effect has taken place in the three clinics. We identified a set of conditions preventing the users from overcoming the ceiling. In adopting an EMR system, all three clinics essentially sought improved operational efficiency. This had an influence on the criteria used to assess the systems available on the market and eventually led to the adoption of a system that met the specified criteria without being optimal. Later, training sessions focussed on basic functionalities that minimally disturbed physicians’ habits while helping their medical practices become more efficient. Satisfied with the outcome of their system use, physicians were likely to ignore more advanced EMR system functionalities. This was because their knowledge about EMR systems came almost exclusively from a single source of information: their EMR system vendors. This knowledge took the form of interpretations of what the innovation was (know-what), with little consideration of the rationales for innovation adoption (know-why) or hands-on strategies for adopting, implementing and assimilating the innovation in the organization (know-how).ConclusionsThis paper provides a holistic view of the technological innovation process in primary care and contends that limited learning, satisficing behaviours and organizational inertia are important factors leading to the ceiling effect frequently experienced in the EMR system assimilation phase.

Level of Digitization in Dutch Hospitals and the Lengths of Stay of Patients with Colorectal Cancer

A substantial amount of research has been published on the association between the use of electronic medical records (EMRs) and quality outcomes in U.S. hospitals, while limited research has focused on the Western European experience. The purpose of this study is to explore the association between the use of EMR technologies in Dutch hospitals and length of stay after colorectal cancer surgery. Two data sets were leveraged for this study; the HIMSS Analytics Electronic Medical Record Adoption Model (EMRAMSM) and the Dutch surgical colorectal audit (DSCA). The HIMSS Analytics EMRAM score was used to define a Dutch hospital’s electronic medical records (EMR) capabilities while the DSCA was used to profile colorectal surgery quality outcomes (specifically total length of stay (LOS) in the hospital and the LOS in ICU). A total of 73 hospitals with a valid EMRAM score and associated DSCA patients (n = 30.358) during the study period (2012–2014) were included in the comparative set. A multivariate regression method was used to test differences adjusted for case mix, year of surgery, surgical technique and for complications, as well as stratifying for academic affiliated hospitals and general hospitals. A significant negative association was observed to exist between the total LOS (relative median LOS 0,974, CI 95% 0.959–0,989) of patients treated in advanced EMR hospitals (high EMRAM score cohort) versus patients treated at less advanced EMR care settings, once the data was adjusted for the case mix, year of surgery and type of surgery (laparoscopy or laparotomy). Adjusting for complications in a subgroup of general hospitals (n = 39) yielded essentially the same results (relative median LOS 0,934, CI 95% 0,915–0,954). No consistent significant associations were found with respect to LOS on the ICU. The findings of this study suggest advanced EMR capabilities support a healthcare provider’s efforts to achieve desired quality outcomes and efficiency in Western European hospitals.