Impact of Electronic versus Paper-Based Recording before EHR Implementation on Health Care Professionals' Perceptions of EHR Use, Data Quality, and Data Reuse.

BACKGROUND: The implementation of an electronic health record (EHR) with structured and standardized recording of patient data can improve data quality and reusability. Whether and how users perceive these advantages may depend on the preimplementation situation. OBJECTIVE: To determine whether the influence of implementing a structured and standardized EHR on perceived EHR use, data quality, and data reuse differed for users working with paper-based records versus a legacy EHR before implementation. METHODS: We used an electronic questionnaire to measure users' perception before implementation (2014), expected change, and perceived change after implementation (2016) on three themes. We included all health care professionals in two university hospitals in the Netherlands. Before jointly implementing the same structured and standardized EHR, one hospital used paper-based records and the other a legacy EHR. We compared perceptions before and after implementation for both centers. Additionally, we compared expected benefit with perceived benefit. RESULTS: We received 7,611 responses (4,537 before and 3,074 after implementation) of which 5,707 (75%) were from professionals reading and recording patient data. A total of 975 (13%) professionals responded to both before and after implementation questionnaires. In the formerly paper-based center staff perceived improvement in all themes after implementation. The legacy EHR center experienced deterioration of perceived EHR use and data reuse, and only one improvement in EHR use. In both centers, for half of the aspects at least 45% of responders experienced results worse than expected preimplementation. CONCLUSION: Our results indicate that the preimplementation recording practice impacts the perceived effect of the implementation of a structured and standardized EHR. For almost half of the respondents the new EHR did not meet their expectations. Especially legacy EHR centers need to investigate the expectations as these might be different and less clear cut than those in paper-based centers. These expectations need to be addressed appropriately to achieve a successful implementation.

Development and validation of a model for the adoption of structured and standardised data recording among healthcare professionals.

BACKGROUND: Healthcare professionals provide care to patients and during that process, record large quantities of data in patient records. Data in an Electronic Health Record should ideally be recorded once and be reusable within the care process as well as for secondary purposes. A common approach to realise this is to let healthcare providers record data in a standardised and structured way at the point of care. Currently, it is not clear to what extent this structured and standardised recording has been adopted by healthcare professionals and what barriers to their adoption exist. Therefore, we developed and validated a multivariable model to capture the concepts underlying the adoption of structured and standardised recording among healthcare professionals. METHODS: Based on separate models from the literature we developed a new theoretical model describing the underlying concepts of the adoption of structured and standardised recording. Using a questionnaire built upon this model we gathered data to perform a summative validation of our model. Validation was done through partial least squares structural equation modelling (PLS-SEM). The quality of both levels defined in PLS-SEM analysis, i.e., the measurement model and the structural model, were assessed on performance measures defined in literature. RESULTS: The theoretical model we developed consists of 29 concepts related to information systems as well as organisational factors and personal beliefs. Based on these concepts, 59 statements with a 5 point Likert-scale (fully disagree to fully agree) were specified in the questionnaire. We received 3584 responses. The validation shows our model is supported to a large extent by the questionnaire data. Intention to record in a structured and standardised way emerged as a significant factor of reported behaviour (ß = 0.305, p < 0.001). This intention is influenced most by attitude (ß = 0.512, p < 0.001). CONCLUSIONS: This model can be used to measure the perceived level of adoption of structured and standardised recording among healthcare professionals and further improve knowledge on the barriers and facilitators of this adoption.

Time Spent on Dedicated Patient Care and Documentation Tasks Before and After the Introduction of a Structured and Standardized Electronic Health Record.

BACKGROUND: Physicians spend around 35% of their time documenting patient data. They are concerned that adopting a structured and standardized electronic health record (EHR) will lead to more time documenting and less time for patient care, especially during consultations. OBJECTIVE: This study measures the effect of the introduction of a structured and standardized EHR on documentation time and time for dedicated patient care during outpatient consultations. METHODS: We measured physicians' time spent on four task categories during outpatient consultations: documentation, patient care, peer communication, and other activities. Physicians covered various specialties from two university hospitals that jointly implemented a structured and standardized EHR. Preimplementation, one hospital used a legacy-EHR, and one primarily paper-based records. The same physicians were observed 2 to 6 months before and 6 to 8 months after implementation.We analyzed consultation duration, and percentage of time spent on each task category. Differences in time distribution before and after implementation were tested using multilevel linear regression. RESULTS: We observed 24 physicians (162 hours, 439 consultations). We found no significant difference in consultation duration or number of consultations per hour. In the legacy-EHR center, we found the implementation associated with a significant decrease in time spent on dedicated patient care (-8.5%). In contrast, in the previously paper-based center, we found a significant increase in dedicated time spent on documentation (8.3%) and decrease in time on combined patient care and documentation (-4.6%). The effect on dedicated documentation time significantly differed between centers. CONCLUSION: Implementation of a structured and standardized EHR was associated with 8.5% decrease in time for dedicated patient care during consultations in one center and 8.3% increase in dedicated documentation time in another center. These results are in line with physicians' concerns that the introduction of a structured and standardized EHR might lead to more documentation burden and less time for dedicated patient care.

What is needed to implement a web-based audit and feedback intervention with outreach visits to improve care quality: A concept mapping study among cardiac rehabilitation teams.

INTRODUCTION: Evidence on successful quality improvement (QI) in health care requires quantitative information from randomized clinical trials (RCTs) on the effectiveness of QI interventions, but also qualitative information from professionals to understand factors influencing QI implementation. OBJECTIVE: Using a structured qualitative approach, concept mapping, this study determines factors identified by cardiac rehabilitation (CR) teams on what is needed to successfully implement a web-based audit and feedback (A&F) intervention with outreach visits to improve the quality of CR care. METHODS: Participants included 49 CR professionals from 18 Dutch CR centres who had worked with the A&F system during a RCT. In three focus group sessions participants formulated statements on factors needed to implement QI successfully. Subsequently, participants rated all statements for importance and feasibility and grouped them thematically. Multi dimensional scaling was used to produce a final concept map. RESULTS: Forty-two unique statements were formulated and grouped into five thematic clusters in the concept map. The cluster with the highest importance was QI team commitment, followed by organisational readiness, presence of an adequate A&F system, access to an external quality assessor, and future use and functionalities of the A&F system. CONCLUSION: Concept mapping appeared efficient and useful to understand contextual factors influencing QI implementation as perceived by healthcare teams. While presence of a web-based A&F system and external quality assessor were seen as instrumental for gaining insight into performance and formulating QI actions, QI team commitment and organisational readiness were perceived as essential to actually implement and carry out these actions. These two sociotechnical factors should be taken into account when implementing and evaluating the success of QI implementations in future research.

Collect Once, Use Many Times: End-Users Don't Practice What They Preach.

Data in an Electronic Health Record must be recorded once, in a standardized and structured way at the point of care to be reusable within the care process as well as for secondary purposes ('collect once, use many times' (COUMT) paradigm). COUMT has not yet been fully adopted by staff in every organization. Our study intends to identify concepts that underlie its adoption and describe its current status in Dutch academic hospitals. Based on literature we have constructed a model that describes these concepts and that guided the development of a questionnaire investigating COUMT adoption. The questionnaire was sent to staff working with patient data or records in seven out of eight Dutch university hospitals. Results show high willingness of end-users to comply to COUMT in the care process. End-users agree that COUMT is important, and that they want to work in a structured and standardized way. However, end-users indicate to not actually use terminology or information standards, but often register diagnoses and procedures in free text, and experience repeated recording of data. In conclusion, we found that COUMT is currently well adopted in mind, but not yet in practice.

Eliciting end-user expectations to guide the implementation process of a new electronic health record: A case study using concept mapping.

OBJECTIVE: To evaluate the usability of concept mapping to elicit the expectations of healthcare professionals regarding the implementation of a new electronic health record (EHR). These expectations need to be taken into account during the implementation process to maximize the chance of success of the EHR. SETTING: Two university hospitals in Amsterdam, The Netherlands, in the preparation phase of jointly implementing a new EHR. During this study the hospitals had different methods of documenting patient information (legacy EHR vs. paper-based records). METHOD: Concept mapping was used to determine and classify the expectations of healthcare professionals regarding the implementation of a new EHR. A multidisciplinary group of 46 healthcare professionals from both university hospitals participated in this study. Expectations were elicited in focus groups, their relevance and feasibility were assessed through a web-questionnaire. Nonmetric multidimensional scaling and clustering methods were used to identify clusters of expectations. RESULTS: We found nine clusters of expectations, each covering an important topic to enable the healthcare professionals to work properly with the new EHR once implemented: usability, data use and reuse, facility conditions, data registration, support, training, internal communication, patients, and collaboration. Average importance and feasibility of each of the clusters was high. CONCLUSION: Concept mapping is an effective method to find topics that, according to healthcare professionals, are important to consider during the implementation of a new EHR. The method helps to combine the input of a large group of stakeholders at limited efforts.

End-User Experiences and Expectations Regarding Data Registration and Reuse Before the Implementation of a (New) Electronic Health Record: A Case Study in Two University Hospitals.

Patient data stored in Electronic Health Records (EHRs) are used during care provision but are also potentially usefully reused for other purposes. Data (re)use requires good data quality, which necessitates efforts by healthcare professionals for proper data registration. However, their commitment depends on their perception of the reuse benefits. We developed a questionnaire to investigate the perception and expectations of end-users on data registration and reuse in two university hospitals starting a joint EHR implementation. Especially personnel in direct patient care reports to spend much time (40%) on data registration and this group is not willing to spend more time with the new EHR. Additionally, approximately one third of the personnel did not yet have a clear view on future developments regarding data registration and reuse. We found only small differences between hospitals.

End-user expectations during an electronic health record implementation: a case study in two academic hospitals.

Implementing an Electronic Health Record (EHR) is a sociotechnical process. End-users' expectations and attitudes need to be monitored during the implementation of a new EHR. It is not clear what end-users consider the most important determinants (both barriers and enablers for a successful EHR implementation) during this process. Based on the concept mapping method and a literature search we developed a questionnaire to investigate which determinants (future) end-users of an EHR consider important. Additionally we analysed whether there are differences between a centre working with a legacy EHR and one with paper-based patient records before implementation. We identified the following determinants: usability of EHR, availability of facilities, alignment with work processes, support during implementation, training on new EHR, support after implementation, practice with new EHR, internal communication, learning from other centres, reuse of patient data, general IT skills, and patient involvement in decision making. All determinants were perceived important by end-users to successfully work with an EHR directly after its go-live. The only two significant differences between centres were knowledge about the effect of the EHR on work processes, and importance of patient involvement in decision making.

Composite quality of care scores, electronic health record maturity models, and their associations; preliminary literature review results.

To accurately assess the association between the use of EHR systems and the quality of healthcare we need (composite) measures for quality of healthcare, and a model to measure the maturity of the EHR. This Medline-based literature study therefore focussed on three topics; (1) methods to compose a measure for quality of care based on individual quality indicators (QI), (2) models to measure EHR maturity, and (3) the association between the former two. Composite quality is most often measured using opportunity-based scores, maturity is measured in functionalities or levels. EHR maturity measures are not used extensively in biomedical literature. Most studies found a positive association between EHR use and the quality of care but almost none of them differentiate in maturity of EHR which hampers firm conclusions about this relation.