Dataset Information

How organizational escalation prevention potential affects success of implementation of innovations: electronic medical records in hospitals.

ABSTRACT: Escalation of commitment is the tendency that (innovation) projects continue, even if it is clear that they will not be successful and/or become extremely costly. Escalation prevention potential (EPP), the capability of an organization to stop or steer implementation processes that do not meet their expectations, may prevent an organization of losing time and money on unsuccessful projects. EPP consists of a set of checks and balances incorporated in managerial practices that safeguard management against irrational (but very human) decisions and may limit the escalation of implementation projects. We study whether successful implementation of electronic medical records (EMRs) relates to EPP and investigate the organizational factors accounting for this relationship.Structural equation modelling (SEM), using questionnaire data of 427 doctors and 631 nurses who had experience with implementation and use of EMRs in hospitals, was applied to study whether formal governance and organizational culture mediate the relationship between EPP and the perceived added value of EMRs.Doctors and nurses in hospitals with more EPP report more successful implementation of EMR (in terms of perceived added value of the EMR). Formal governance mediates the relation between EPP and implementation success. We found no evidence that open or innovative culture explains the relationship between EPP and implementation success.There is a positive relationship between the level of EPP and perceived added value of EMRs. This relationship is explained by formal governance mechanisms of organizations. This means that management has a set of tangible tools to positively affect the success of innovation processes. However, it also means that management needs to be able to critically reflect on its (previous) actions and decisions and is willing to change plans if elements of EPP signal that the implementation process is hampered.

SUBMITTER: Lambooij MS

PROVIDER: S-EPMC4875635 | biostudies-other | 2016

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundDespite the rapid adoption of electronic health records (EHRs) resulting from the reimbursement program of the US government, EHR adoption in behavioral hospitals is still slow, and there remains a lack of evidence regarding barriers and facilitators to the implementation of mental health care EHRs.ObjectiveThe aim of this study is to analyze the experience of mental health professionals to explore the perceived barriers, facilitators, and critical ideas influencing the implementation and usability of a mental health care EHR.MethodsIn this phenomenological qualitative study, we interviewed physicians, nurses, pharmacists, mental health clinicians, and administrative professionals separately at 4 behavioral hospitals in the United States. We conducted semistructured interviews (N=43) from behavioral hospitals involved in the adoption of the mental health care EHR. Purposeful sampling was used to maximize the diversity. Transcripts were coded and analyzed for emergent domains. An exploratory data analysis was conducted.ResultsContent analyses revealed 7 barriers and 4 facilitators. The most important barriers to implementing the mental health care EHR were the low levels of computer proficiency among nurses, complexity of the system, alert fatigue, and resistance because of legacy systems. This led to poor usability, low acceptability, and distrust toward the system. The major facilitators to implementing the mental health care EHR were well-executed training programs, improved productivity, better quality of care, and the good usability of the mental health care EHR.ConclusionsHealth care professionals expected to enhance their work productivity and interprofessional collaboration by introducing the mental health care EHR. Routine education for end users is an essential starting point for the successful implementation of mental health care EHR electronic decision support. When adopting the mental health care EHR, managers need to focus on common practices in behavioral hospitals, such as documenting structured data in their organizations and adopting a seamless workflow of mental health care into the system.

Project description:BackgroundIn resources constrained settings, effectively implemented Electronic Medical Record systems have numerous benefits over paper-based record keeping. This system was implemented in the 2009 Gregorian Calendar in the two Ethiopian territory hospitals, Ayder and St. Paul's. The pilot implementation and similar re-deployment efforts done in 2014 and 2017 Gregorian Calendar failed at St. Paul's. This study aimed to assess the current status, identify challenges, success factors and perception of health care providers to the system to inform on future roll-outs and scale-up plans.MethodsA cross sectional study design with quantitative and qualitative methods was employed. A survey was administered October to December 2019 using a structured questionnaire. A total of 240 health care providers participated in the study based on a stratified random sampling technique. An interview was conducted with a total of 10 persons that include IT experts and higher managements of the hospital. Descriptive statistics were employed to summarize the survey data using SPSS V.21. Qualitative data were thematically presented.ResultsSt. Paul's hospital predominantly practiced the manual medical recording system. The majority of respondents (30.6%) declared that a lack of training and follow up, lack of management commitment, poor network infrastructure and hardware/software-related issues were challenges and contributed to EMR system failure at St. Paul's. Results from the qualitative data attested to the above results. The system is found well-functioning at Ayder, and the majority of respondents (38%) noted that lack of training and follow-up was the most piercing challenge. As per the qualitative findings, ICT infrastructure, availability of equipment, incentive mechanisms, and management commitment are mentioned as supportive for successful implementation. At both hospitals, 70 to 95% of participants hold favorable perceptions and are willing to use the system.ConclusionAssessing the readiness of the hospital, selecting and acquiring standard and certified EMR systems, provision of adequate logistic requirements including equipment and supplies, and upgrading the hospital ICT infrastructure will allow sustainable deployment of an EMR system.

Project description:AIMS: To investigate the perceptions and reported practices of mental health hospital staff using national hospital electronic health records (EHRs) in order to inform future implementations, particularly in acute mental health settings. METHODS: Thematic analysis of interviews with a wide range of clinical, information technology (IT), managerial and other staff at two early adopter mental health National Health Service (NHS) hospitals in London, UK, implementing national EHRs. RESULTS: We analysed 33 interviews. We first sought out examples of workarounds, such as delayed data entry, entering data in wrong places and individuals using the EHR while logged in as a colleague, then identified possible reasons for the reported workarounds. Our analysis identified four main categories of factors contributing to workarounds (i.e., operational, cultural, organisational and technical). Operational factors included poor system integration with existing workflows and the system not meeting users' perceived needs. Cultural factors involved users' competence with IT and resistance to change. Organisational factors referred to insufficient organisational resources and training, while technical factors included inadequate local technical infrastructure. Many of these factors, such as integrating the EHR system with day-to-day operational processes, staff training and adequate local IT infrastructure, were likely to apply to system implementations in various settings, but we also identified factors that related particularly to implementing EHRs in mental health hospitals, for example: EHR system incompatibility with IT systems used by mental health-related sectors, notably social services; the EHR system lacking specific, mental health functionalities and options; and clinicians feeling unable to use computers while attending to distressed psychiatric patients. CONCLUSIONS: A better conceptual model of reasons for workarounds should help with designing, and supporting the implementation and adoption of, EHRs for use in hospital mental health settings.

Project description:IntroductionElectronic health records (EHRs) have the potential to offer real-time, inexpensive standardized health data about chronic health conditions. Despite rapid expansion, EHR data evaluations for chronic disease surveillance have been limited. We present design and methods for the New York City (NYC) Macroscope, an EHR-based chronic disease surveillance system. This methods report is the first in a three part series describing the development and validation of the NYC Macroscope. This report describes in detail the infrastructure underlying the NYC Macroscope; indicator definitions; design decisions that were made to maximize data quality; characteristics of the population sampled; completeness of data collected; and lessons learned from doing this work. The second report describes the methods used to evaluate the validity and robustness of NYC Macroscope prevalence estimates; presents validation results for estimates of obesity, smoking, depression and influenza vaccination; and discusses the implications of our findings for NYC and for other jurisdictions embarking on similar work. The third report applies the same validation methods to metabolic outcomes, including the prevalence, treatment and control of diabetes, hypertension and hyperlipidemia.MethodsWe designed the NYC Macroscope for comparison to a local "gold standard," the 2013-14 NYC Health and Nutrition Examination Survey, and the telephonic 2013 Community Health Survey. NYC Macroscope indicators covered prevalence, treatment, and control of diabetes, hypertension, and hyperlipidemia; and prevalence of influenza vaccination, obesity, depression and smoking. Indicators were stratified by age, sex, and neighborhood poverty, and weighted to the in-care NYC population and limited to primary care patients. Indicator queries were distributed to a virtual network of primary care practices; 392 practices and 716,076 adult patients were retained in the final sample.FindingsThe NYC Macroscope covered 10% of primary care providers and 15% of all adult patients in NYC in 2013 (8-47% of patients by neighborhood). Data completeness varied by domain from 98% for blood pressure among patients with hypertension to 33% for depression screening.DiscussionDesign and validation efforts undertaken by NYC are described here to provide one potential blueprint for leveraging EHRs for population health monitoring. To replicate a model like NYC Macroscope, jurisdictions should establish buy-in; build informatics capacity; use standard, simple case defnitions; establish documentation quality thresholds; restrict to primary care providers; and weight the sample to a target population.

Project description:Models of healthcare organizations (HCOs) are often defined up front by a select few administrative officials and managers. However, given the size and complexity of modern healthcare systems, this practice does not scale easily. The goal of this work is to investigate the extent to which organizational relationships can be automatically learned from utilization patterns of electronic health record (EHR) systems.We designed an online survey to solicit the perspectives of employees of a large academic medical center. We surveyed employees from two administrative areas: (1) Coding & Charge Entry and (2) Medical Information Services and two clinical areas: (3) Anesthesiology and (4) Psychiatry. To test our hypotheses we selected two administrative units that have work-related responsibilities with electronic records; however, for the clinical areas we selected two disciplines with very different patient responsibilities and whose accesses and people who accessed were similar. We provided each group of employees with questions regarding the chance of interaction between areas in the medical center in the form of association rules (e.g., Given someone from Coding & Charge Entry accessed a patient's record, what is the chance that someone from Medical Information Services access the same record?). We compared the respondent predictions with the rules learned from actual EHR utilization using linear-mixed effects regression models.The findings from our survey confirm that medical center employees can distinguish between association rules of high and non-high likelihood when their own area is involved. Moreover, they can make such distinctions between for any HCO area in this survey. It was further observed that, with respect to highly likely interactions, respondents from certain areas were significantly better than other respondents at making such distinctions and certain areas' associations were more distinguishable than others.These results illustrate that EHR utilization patterns may be consistent with the expectations of HCO employees. Our findings show that certain areas in the HCO are easier than others for employees to assess, which suggests that automated learning strategies may yield more accurate models of healthcare organizations than those based on the perspectives of a select few individuals.

Project description:BackgroundTwo of the current methodological barriers to implementation science efforts are the lack of agreement regarding constructs hypothesized to affect implementation success and identifiable measures of these constructs. In order to address these gaps, the main goals of this paper were to identify a multi-level framework that captures the predominant factors that impact implementation outcomes, conduct a systematic review of available measures assessing constructs subsumed within these primary factors, and determine the criterion validity of these measures in the search articles.MethodWe conducted a systematic literature review to identify articles reporting the use or development of measures designed to assess constructs that predict the implementation of evidence-based health innovations. Articles published through 12 August 2012 were identified through MEDLINE, CINAHL, PsycINFO and the journal Implementation Science. We then utilized a modified five-factor framework in order to code whether each measure contained items that assess constructs representing structural, organizational, provider, patient, and innovation level factors. Further, we coded the criterion validity of each measure within the search articles obtained.ResultsOur review identified 62 measures. Results indicate that organization, provider, and innovation-level constructs have the greatest number of measures available for use, whereas structural and patient-level constructs have the least. Additionally, relatively few measures demonstrated criterion validity, or reliable association with an implementation outcome (e.g., fidelity).DiscussionIn light of these findings, our discussion centers on strategies that researchers can utilize in order to identify, adapt, and improve extant measures for use in their own implementation research. In total, our literature review and resulting measures compendium increases the capacity of researchers to conceptualize and measure implementation-related constructs in their ongoing and future research.

Dataset Information

How organizational escalation prevention potential affects success of implementation of innovations: electronic medical records in hospitals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets