Electronic health record impact on work burden in small, unaffiliated, community-based primary care practices

Benefits, facilitators, and barriers of electronic medical records implementation in outpatient settings: A scoping review

This scoping review examined the breadth and depth of evidence on Electronic Medical Record (EMR) implementation benefits in outpatient settings. Following PRISMA guidelines for scoping reviews, five databases were searched, and 24 studies were retained and reviewed. Benefits, facilitators, and barriers to EMR implementation were extracted. Direct benefits included improved communication/reporting, work efficiency, care process, healthcare outcomes, safety, and patient-centredness of care. Indirect benefits were improved financial performance and increased data accessibility, staff satisfaction, and decision-support usage. Barriers included time and financial constraints; design/technical issues; limited information technology resources, skills, and infrastructure capacity; increased workload and reduced efficiency during implementation; incompatibility of existing systems and local regulations; and resistance from healthcare professionals. Facilitators included training, change management, user-friendliness and alignment with workflow, user experience with EMRs, top management support, and sufficient resources. More rigorous, systematic research is needed, using relevant frameworks to inform healthcare policies and guide EMR projects in outpatient areas.

BIR: Biomedical Information Retrieval System for Cancer Treatment in Electronic Health Record Using Transformers

The rapid growth of electronic health records (EHRs) has led to unprecedented biomedical data. Clinician access to the latest patient information can improve the quality of healthcare. However, clinicians have difficulty finding information quickly and easily due to the sheer data mining volume. Biomedical information retrieval (BIR) systems can help clinicians find the information required by automatically searching EHRs and returning relevant results. However, traditional BIR systems cannot understand the complex relationships between EHR entities. Transformers are a new type of neural network that is very effective for natural language processing (NLP) tasks. As a result, transformers are well suited for tasks such as machine translation and text summarization. In this paper, we propose a new BIR system for EHRs that uses transformers for predicting cancer treatment from EHR. Our system can understand the complex relationships between the different entities in an EHR, which allows it to return more relevant results to clinicians. We evaluated our system on a dataset of EHRs and found that it outperformed state-of-the-art BIR systems on various tasks, including medical question answering and information extraction. Our results show that Transformers are a promising approach for BIR in EHRs, reaching an accuracy and an F1-score of 86.46%, and 0.8157, respectively. We believe that our system can help clinicians find the information they need more quickly and easily, leading to improved patient care.

The Integrated Electronic Health System in Iranian health centers: benefits and challenges

BACKGROUND

Electronic Health Records (EHRs) were introduced to all Iranian medical universities in 2015 with the launch of Integrated Electronic Health System (which is known as SIB: a Persian backronym in Persian meaning apple), and a number of studies were conducted on SIB. However, most of these studies did not consider the benefits and challenges of adopting SIB in Iran. Therefore, the present study aimed to identify the benefits and challenges of SIB in health centers of Khuzestan Province, Iran.

METHODS

This was a qualitative study using qualitative conventional content analysis conducted on 6 experts and 24 users of SIB in six health centers of three cities in Khuzestan province, Iran. The participants were selected using a purposeful sampling method. Maximum variation was considered in selecting the group of users, and snowball sampling was used in the group of experts. Data collection tool was semi-structured interview. Data analysis was performed using thematic analysis.

RESULTS

Overall, 42 components (24 for benefits and 18 for challenges) were extracted from the interviews. Common sub-themes and themes were identified for challenges and benefits. The components formed 12 sub-themes, and they were placed in 3 main themes, namely structure, process and outcome. 1) Structure included four sub-themes of Financial resources, Human resources, Facilities, and Access to the Internet; 2) Process involved three sub-themes of Training, Providing services, and Time and workload; and 3) Outcome incorporated five sub-themes of Quality of health services, Access, Safety and personal distance, Screening and evaluation, and Research.

CONCLUSIONS

In the present study, the benefits and challenges of adopting SIB were examined in three themes: structure, process, and outcome. Most of the identified benefits were related to the theme of outcome, and most of the identified challenges were related to the theme of structure. Based on the identified factors, by strengthening the benefits of SIB and also trying to eliminate or reduce its challenges, it is possible to institutionalize and use it more effectively in order to solve health problems.

Department-focused electronic health record thrive training

A novel approach of department-focused electronic health record (EHR) training was implemented to improve efficiency and time management of EHR use. Based off baseline log data, 5 in-person training sessions were designed, focusing on the common inefficiencies of 6 chosen participants. Log data of 4 key metrics and 2 efficiency scores were analyzed 4 months post-training. A survey was conducted to assess self-reported EHR competence. Individually, several participants had improved efficiency scores. There was a reduced average time spent in the inbox per day, in notes per dictation, and in notes per day. This translated to an average of 8.9 min saved per day (range 0–29.1 min/day) and 37.1 hours saved per year (range 0–116.2 hours/year). From the post-training surveys, all participants felt more efficient in their use of the EHR. This study demonstrates an example of department-focused EHR training and log-based analysis improving time management and efficiency.

This was a pilot study analyzing the use of log-based data to monitor for improvements in electronic health record (EHR) efficiency, after 6 participants completed hands-on, interactive training sessions. These training sessions focused on metrics that were commonly deficient amongst radiation oncology providers at a large academic institution. Four months after the training, a post-training survey demonstrated that all participants felt more efficient in their EHR use. Additionally there was a reduced average time spent on both communication and documentation metrics. This study demonstrates an example of department-focused EHR training and log-based analysis improving time management and efficiency.

Electronic health records, mobile health, and the challenge of improving global health

Technology continues to impact healthcare around the world. This provides great opportunities, but also risks. These risks are compounded in low-resource settings where errors in planning and implementation may be more difficult to overcome. Global Health Informatics provides lessons in both opportunities and risks by building off of general Global Health. Global Health Informatics also requires a thorough understanding of the local environment and the needs of low-resource settings. Forming effective partnerships and following the lead of local experts are necessary for sustainability; it also ensures that the priorities of the local community come first. There is an opportunity for partnerships between low-resource settings and high income areas that can provide learning opportunities to avoid the pitfalls that plague many digital health systems and learn how to properly implement technology that truly improves healthcare.

Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal

BACKGROUND

Research on the integration of artificial intelligence (AI) into community-based primary health care (CBPHC) has highlighted several advantages and disadvantages in practice regarding, for example, facilitating diagnosis and disease management, as well as doubts concerning the unintended harmful effects of this integration. However, there is a lack of evidence about a comprehensive knowledge synthesis that could shed light on AI systems tested or implemented in CBPHC.

OBJECTIVE

We intended to identify and evaluate published studies that have tested or implemented AI in CBPHC settings.

METHODS

We conducted a systematic scoping review informed by an earlier study and the Joanna Briggs Institute (JBI) scoping review framework and reported the findings according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis-Scoping Reviews) reporting guidelines. An information specialist performed a comprehensive search from the date of inception until February 2020, in seven bibliographic databases: Cochrane Library, MEDLINE, EMBASE, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), ScienceDirect, and IEEE Xplore. The selected studies considered all populations who provide and receive care in CBPHC settings, AI interventions that had been implemented, tested, or both, and assessed outcomes related to patients, health care providers, or CBPHC systems. Risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST). Two authors independently screened the titles and abstracts of the identified records, read the selected full texts, and extracted data from the included studies using a validated extraction form. Disagreements were resolved by consensus, and if this was not possible, the opinion of a third reviewer was sought. A third reviewer also validated all the extracted data.

RESULTS

We retrieved 22,113 documents. After the removal of duplicates, 16,870 documents were screened, and 90 peer-reviewed publications met our inclusion criteria. Machine learning (ML) (41/90, 45%), natural language processing (NLP) (24/90, 27%), and expert systems (17/90, 19%) were the most commonly studied AI interventions. These were primarily implemented for diagnosis, detection, or surveillance purposes. Neural networks (ie, convolutional neural networks and abductive networks) demonstrated the highest accuracy, considering the given database for the given clinical task. The risk of bias in diagnosis or prognosis studies was the lowest in the participant category (4/49, 4%) and the highest in the outcome category (22/49, 45%).

CONCLUSIONS

We observed variabilities in reporting the participants, types of AI methods, analyses, and outcomes, and highlighted the large gap in the effective development and implementation of AI in CBPHC. Further studies are needed to efficiently guide the development and implementation of AI interventions in CBPHC settings.

Wound Classification Score Discordance in Pediatric Operations - A Quality Improvement Study

BACKGROUND

Wound classification scores are used to categorize the risk of postoperative infections. It was noted at our academic institution that wound classifications were often inaccurately recorded in the electronic health record. We thus instituted a quality improvement program, hypothesizing that this would improve charting accuracy.

METHODS

On June 1, 2019, we posted the wound classifications in each pediatric operating room (OR), provided OR nurses with teaching, and began including the classification in the postoperative surgeon debriefing. We performed a retrospective chart review of all general pediatric operations from June 19 to December 19 to compare classifications recorded in the electronic health record to the "correct" classification determined by manual review of operating reports. These data were compared with a similar chart review from 2018. To compare the efficacy of nursing versus physician focused changes, we compared our appendectomy data with a nearby community institution where the same group of surgeons practice. Pearson's Chi-squared test was used to report the significance of the differences observed in the concordance proportion, with 95% confidence intervals calculated using the Clopper-Pearson procedure.

RESULTS

Overall, 444 pre- and 179 postpractice change charts were reviewed. There were no significant differences pre or postpractice change. At the community institution, we noted a significant improvement in charting accuracy for appendectomies from 3.33% to 44.83%.

DISCUSSION

Despite implementing nursing and physician focused quality improvement practices, there was not a significant improvement in charting accuracy at the academic institution. However, we did note an improvement at the community facility where our pediatric surgeons also practice. We thus suspect that our nursing focused changes may have been inadequate. Future efforts will focus on providing intensive and sustained OR nurse training to help improve the wound classification charting accuracy.

What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality

PURPOSE

Accurate recording of diagnosis (DX) data in electronic health records (EHRs) is important for clinical practice and learning health care. Previous studies show statistically stable patterns of data entry in EHRs that contribute to inaccurate DX, likely because of a lack of data entry support. We conducted qualitative research to characterize the preferences of oncological care providers on cancer DX data entry in EHRs during clinical practice.

METHODS

We conducted semistructured interviews and focus groups to uncover common themes on DX data entry preferences and barriers to accurate DX recording. Then, we developed a survey questionnaire sent to a cohort of oncologists to verify the generalizability of our initial findings. We constrained our participants to a single specialty and institution to ensure similar clinical backgrounds and clinical experience with a single EHR system.

RESULTS

A total of 12 neuro-oncologists and thoracic oncologists were involved in the interviews and focus groups. The survey developed from these two initial thrusts was distributed to 19 participants yielding a 94.7% survey response rate. Clinicians reported similar user interface experiences, barriers, and dissatisfaction with current DX entry systems including repetitive entry operations, difficulty in finding specific DX options, time-consuming interactions, and the need for workarounds to maintain efficiency. The survey revealed inefficient DX search interfaces and challenging entry processes as core barriers.

CONCLUSION

Oncologists seem to be divided between specific DX data entry and time efficiency because of current interfaces and feel hindered by the burdensome and repetitive nature of EHR data entry. Oncologists' top concern for adopting data entry support interventions is ensuring that it provides significant time-saving benefits and increasing workflow efficiency. Future interventions should account for time efficiency, beyond ensuring data entry effectiveness.

Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review

BACKGROUND

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OBJECTIVE

Electronic health records (EHRs) are linked with documentation burden resulting in clinician burnout. While clear classifications and validated measures of burnout exist, documentation burden remains ill-defined and inconsistently measured. We aim to conduct a scoping review focused on identifying approaches to documentation burden measurement and their characteristics.

MATERIALS AND METHODS

Based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews (ScR) guidelines, we conducted a scoping review assessing MEDLINE, Embase, Web of Science, and CINAHL from inception to April 2020 for studies investigating documentation burden among physicians and nurses in ambulatory or inpatient settings. Two reviewers evaluated each potentially relevant study for inclusion/exclusion criteria.

RESULTS

Of the 3482 articles retrieved, 35 studies met inclusion criteria. We identified 15 measurement characteristics, including 7 effort constructs: EHR usage and workload, clinical documentation/review, EHR work after hours and remotely, administrative tasks, cognitively cumbersome work, fragmentation of workflow, and patient interaction. We uncovered 4 time constructs: average time, proportion of time, timeliness of completion, activity rate, and 11 units of analysis. Only 45.0% of studies assessed the impact of EHRs on clinicians and/or patients and 40.0% mentioned clinician burnout.

DISCUSSION

Standard and validated measures of documentation burden are lacking. While time and effort were the core concepts measured, there appears to be no consensus on the best approach nor degree of rigor to study documentation burden.

CONCLUSION

Further research is needed to reliably operationalize the concept of documentation burden, explore best practices for measurement, and standardize its use.

Remembering Ben-Tzion Karsh's scholarship, impact, and legacy

Dr. Ben-Tzion (Bentzi) Karsh was a mentor, collaborator, colleague, and friend who profoundly impacted the fields of human factors and ergonomics (HFE), medical informatics, patient safety, and primary care, among others. In this paper we honor his contributions by reflecting on his scholarship, impact, and legacy in three ways: first, through an updated simplified bibliometric analysis in 2020, highlighting the breadth of his scholarly impact from the perspective of the number and types of communities and collaborators with which and whom he engaged; second, through targeted reflections on the history and impact of Dr. Karsh's most cited works, commenting on the particular ways they impacted our academic community; and lastly, through quotes from collaborators and mentees, illustrating Dr. Karsh's long-lasting impact on his contemporaries and students.

Time-motion examination of electronic health record utilization and clinician workflows indicate frequent task switching and documentation burden

Clinical documentation burden has been broadly acknowledged, yet few interprofessional measures of burden exist. Using interprofessional time-motion study (TMS) data, we evaluated clinical workflows with a focus on electronic health record (EHR) utilization and fragmentation among 47 clinicians: 34 advanced practice providers (APPs) and 13 registered nurses (RNs) from: an acute care unit (n=15 observations [obs]), intensive care unit (nobs=14), ambulatory clinic (nobs=3), and emergency department (nobs=15). We examined workflow fragmentation, task-switch type, and task involvement. In our study, clinicians on average exhibited 1.4±0.6 switches per minute in their workflow. Eighty-four (19.6%) of the 429 task-switch types presented in the data accounted for 80.1% of all switches. Among those, data viewing- and data entry-related tasks were involved in 48.2% of all switches, indicating documentation burden may play a critical role in workflow disruptions. Therefore, interruption rate evaluated through task switches may serve as a proxy for measuring burden.

Effects of Electronic Health Record Implementation and Barriers to Adoption and Use: A Scoping Review and Qualitative Analysis of the Content

Despite the great advances in the field of electronic health records (EHRs) over the past 25 years, implementation and adoption challenges persist, and the benefits realized remain below expectations. This scoping review aimed to present current knowledge about the effects of EHR implementation and the barriers to EHR adoption and use. A literature search was conducted in PubMed, Web of Science, IEEE Xplore Digital Library and ACM Digital Library for studies published between January 2005 and May 2020. In total, 7641 studies were identified of which 142 met the criteria and attained the consensus of all researchers on inclusion. Most studies (n = 91) were published between 2017 and 2019 and 81 studies had the United States as the country of origin. Both positive and negative effects of EHR implementation were identified, relating to clinical work, data and information, patient care and economic impact. Resource constraints, poor/insufficient training and technical/educational support for users, as well as poor literacy and skills in technology were the identified barriers to adoption and use that occurred frequently. Although this review did not conduct a quality analysis of the included papers, the lack of uniformity in the use of EHR definitions and detailed contextual information concerning the study settings could be observed.

Workflow Differences Affect Data Accuracy in Oncologic EHRs: A First Step Toward Detangling the Diagnosis Data Babel

PURPOSE

Diagnosis (DX) information is key to clinical data reuse, yet accessible structured DX data often lack accuracy. Previous research hints at workflow differences in cancer DX entry, but their link to clinical data quality is unclear. We hypothesized that there is a statistically significant relationship between workflow-describing variables and DX data quality.

METHODS

We extracted DX data from encounter and order tables within our electronic health records (EHRs) for a cohort of patients with confirmed brain neoplasms. We built and optimized logistic regressions to predict the odds of fully accurate (ie, correct neoplasm type and anatomic site), inaccurate, and suboptimal (ie, vague) DX entry across clinical workflows. We selected our variables based on correlation strength of each outcome variable.

RESULTS

Both workflow and personnel variables were predictive of DX data quality. For example, a DX entered in departments other than oncology had up to 2.89 times higher odds of being accurate (P < .0001) compared with an oncology department; an outpatient care location had up to 98% fewer odds of being inaccurate (P < .0001), but had 458 times higher odds of being suboptimal (P < .0001) compared with main campus, including the cancer center; and a DX recoded by a physician assistant had 85% fewer odds of being suboptimal (P = .005) compared with those entered by physicians.

CONCLUSION

These results suggest that differences across clinical workflows and the clinical personnel producing EHR data affect clinical data quality. They also suggest that the need for specific structured DX data recording varies across clinical workflows and may be dependent on clinical information needs. Clinicians and researchers reusing oncologic data should consider such heterogeneity when conducting secondary analyses of EHR data.

Impacts of Operational Failures on Primary Care Physicians' Work: A Critical Interpretive Synthesis of the Literature

PURPOSE

Operational failures are system-level errors in the supply of information, equipment, and materials to health care personnel. We aimed to review and synthesize the research literature to determine how operational failures in primary care affect the work of primary care physicians.

METHODS

We conducted a critical interpretive synthesis. We searched 7 databases for papers published in English from database inception until October 2017 for primary research of any design that addressed problems interfering with primary care physicians' work. All potentially eligible titles/abstracts were screened by 1 reviewer; 30% were subject to second screening. We conducted an iterative critique, analysis, and synthesis of included studies.

RESULTS

Our search retrieved 8,544 unique citations. Though no paper explicitly referred to "operational failures," we identified 95 papers that conformed to our general definition. The included studies show a gap between what physicians perceived they should be doing and what they were doing, which was strongly linked to operational failures-including those relating to technology, information, and coordination-over which physicians often had limited control. Operational failures actively configured physicians' work by requiring significant compensatory labor to deliver the goals of care. This labor was typically unaccounted for in scheduling or reward systems and had adverse consequences for physician and patient experience.

CONCLUSIONS

Primary care physicians' efforts to compensate for suboptimal work systems are often concealed, risking an incomplete picture of the work they do and problems they routinely face. Future research must identify which operational failures are highest impact and tractable to improvement.

Evaluation of a Health Information Technology-Enabled Panel Management Platform to Improve Anticoagulation Control in a Low-Income Patient Population: Protocol for a Quasi-Experimental Design

BACKGROUND

Warfarin is one of the most commonly prescribed medications in the United States, and it causes a significant proportion of adverse drug events. Patients taking warfarin fall outside of the recommended therapeutic range 30% of the time, largely because of inadequate laboratory monitoring and dose adjustment. This leads to an increased risk of blood clots or bleeding events. We propose a comparative effectiveness study to examine whether a technology-enabled anticoagulation management program can improve long-term clinical outcomes compared with usual care.

OBJECTIVE

Our proposed intervention is the implementation of an electronic dashboard (integrated into a preexisting electronic health record) and standardized workflow to track patients' laboratory results, identify patients requiring follow-up, and facilitate the use of a validated nomogram for dose adjustment. The primary outcome of this study is the time in therapeutic range (TTR) at 6 months post intervention (a validated metric of anticoagulation quality among patients receiving warfarin).

METHODS

We will employ a pre-post quasi-experimental design with a nonequivalent usual-care comparison site and a difference-in-differences approach to compare the effectiveness of a technology-enabled anticoagulation management program compared with usual care at a large university-affiliated safety-net clinic.

RESULTS

We used a commercially available health information technology (HIT) platform to host a registry of patients on warfarin therapy and create the electronic dashboard for panel management. We developed the intervention with, and for, frontline clinician users, using principles of human-centered design. This study is funded until September 2020 and is approved by the University of California, San Francisco Institutional Review Board until June 22, 2020. We completed data collection in September 2019 and expect to complete our proposed analyses by February 2020.

CONCLUSIONS

We anticipate that the intervention will increase TTR among patients taking warfarin and that the use of this HIT platform will facilitate tracking and monitoring of patients on warfarin, which could enable outreach to those overdue for visits or laboratory monitoring. We will use these findings to iteratively improve the platform in preparation for a larger, multiple-site, pragmatic clinical trial. If successful, our study will demonstrate the integration of HIT platforms into existing electronic health records to improve patient care in real-world clinical settings.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/13835.

Variation in Physicians' Electronic Health Record Documentation and Potential Patient Harm from That Variation

BACKGROUND

Physician-to-physician variation in electronic health record (EHR) documentation not driven by patients' clinical status could be harmful.

OBJECTIVE

Measure variation in completion of common clinical documentation domains. Identify perceived causes and effects of variation and strategies to mitigate negative effects.

DESIGN

Sequential, explanatory, mixed methods using log data from a commercial EHR vendor and semi-structured interviews with outpatient primary care practices.

PARTICIPANTS

Quantitative: 170,332 encounters led by 809 physicians in 237 practices. Qualitative: 40 interviewees in 10 practices.

MAIN MEASURES

Interquartile range (IQR) of the proportion of encounters in which a physician completed documentation, for each documentation category. Multilevel linear regression measured the proportion of variation at the physician level.

KEY RESULTS

Five clinical documentation categories had substantial and statistically significant (p < 0.001) variation at the physician level after accounting for state, organization, and practice levels: (1) discussing results (IQR = 50.8%, proportion of variation explained by physician level = 78.1%); (2) assessment and diagnosis (IQR = 60.4%, physician-level variation = 76.0%); (3) problem list (IQR = 73.1%, physician-level variation = 70.1%); (4) review of systems (IQR = 62.3%, physician-level variation = 67.7%); and (5) social history (IQR = 53.3%, physician-level variation = 62.2%). Drivers of variation from interviews included user preferences and EHR designs with multiple places to record similar information. Variation was perceived to create documentation inefficiencies and risk patient harm due to missed or misinterpreted information. Mitigation strategies included targeted user training during EHR implementation and practice meetings focused on documentation standardization.

CONCLUSIONS

Physician-to-physician variation in EHR documentation impedes effective and safe use of EHRs, but there are potential strategies to mitigate negative consequences.

Growing Disparities in Patient-Provider Messaging: Trend Analysis Before and After Supportive Policy

BACKGROUND

Public policy introduced since 2011 has supported provider adoption of electronic medical records (EMRs) and patient-provider messaging, primarily through financial incentives. It is unclear how disparities in patients' use of incentivized electronic health (eHealth) tools, like patient-provider messaging, have changed over time relative to disparities in use of eHealth tools that were not directly incentivized.

OBJECTIVE

This study examines trends in eHealth disparities before and after the introduction of US federal financial incentives. We compare rates of patient-provider messaging, which was directly incentivized, with rates of looking for health information on the Web, which was not directly incentivized.

METHODS

We used nationally representative Health Information National Trends Survey data from 2003 to 2018 (N=37,300) to describe disparities in patient-provider messaging and looking for health information on the Web. We first reported the percentage of individuals across education and racial and ethnic groups who reported using these tools in each survey year and compared changes in unadjusted disparities during preincentive (2003-2011) and postincentive (2011-2018) periods. Using multivariable linear probability models, we then examined adjusted effects of education and race and ethnicity in 3 periods-preincentive (2003-2005), early incentive (2011-2013), and postincentive (2017-2018)-controlling for sociodemographic and health factors. In the postincentive period, an additional model tested whether internet adoption, provider access, or providers' use of EMRs explained disparities.

RESULTS

From 2003 to 2018, overall rates of provider messaging increased from 4% to 36%. The gap in provider messaging between the highest and lowest education groups increased by 10 percentage points preincentive (P<.001) and 22 additional points postincentive (P<.001). The gap between Hispanics and non-Hispanic whites increased by 3.2 points preincentive (P=.42) and 11 additional points postincentive (P=.01). Trends for blacks resembled those for Hispanics, whereas trends for Asians resembled those for non-Hispanic whites. In contrast, education-based disparities in looking for health information on the Web (which was not directly incentivized) did not significantly change in preincentive or postincentive periods, whereas racial disparities narrowed by 15 percentage points preincentive (P=.008) and did not significantly change postincentive. After adjusting for other sociodemographic and health factors, observed associations were similar to unadjusted associations, though smaller in magnitude. Including internet adoption, provider access, and providers' use of EMRs in the postincentive model attenuated, but did not eliminate, education-based disparities in provider messaging and looking for health information on the Web. Racial and ethnic disparities were no longer statistically significant in adjusted models.

CONCLUSIONS

Disparities in provider messaging widened over time, particularly following federal financial incentives. Meanwhile, disparities in looking for health information on the Web remained stable or narrowed. Incentives may have disproportionately benefited socioeconomically advantaged groups. Future policy could address disparities by incentivizing providers treating these populations to adopt messaging capabilities and encouraging patients' use of messaging.

A tale of three subspecialties: Diagnosis recording patterns are internally consistent but Specialty-Dependent

BACKGROUND

Structured diagnosis (DX) are crucial for secondary use of electronic health record (EHR) data. However, they are often suboptimally recorded. Our previous work showed initial evidence of variable DX recording patterns in oncology charts even after biopsy records are available.

OBJECTIVE

We verified this finding's internal and external validity. We hypothesized that this recording pattern would be preserved in a larger cohort of patients for the same disease. We also hypothesized that this effect would vary across subspecialties.

METHODS

We extracted DX data from EHRs of patients treated for brain, lung, and pancreatic neoplasms, identified through clinician-led chart reviews. We used statistical methods (i.e., binomial and mixed model regressions) to test our hypotheses.

RESULTS

We found variable recording patterns in brain neoplasm DX (i.e., larger number of distinct DX-OR = 2.2, P < 0.0001, higher descriptive specificity scores-OR = 1.4, P < 0.0001-and much higher entropy after the BX-OR = 3.8 P = 0.004 and OR = 8.0, P < 0.0001), confirming our initial findings. We also found strikingly different patterns for lung and pancreas DX. Although both seemed to have much lower DX sequence entropy after the BX-OR = 0.198, P = 0.015 and OR = 0.099, P = 0.015, respectively compared to OR = 3.8 P = 0.004). We also found statistically significant differences between the brain dataset and both the lung (P < 0.0001) and pancreas (0.009

CONCLUSION

Our results suggest that disease-specific DX entry patterns exist and are established differently by clinical subspecialty. These differences should be accounted for during clinical data reuse and data quality assessments but also during EHR entry system design to maximize accurate, precise and consistent data entry likelihood.

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Key Words

• clinical data management
• data quality
• electronic health records
• learning healthcare system
• secondary use of clinical data

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MESH Headings Collapse

Grants

• K12 GM102773 NIGMS NIH HHS
• UL1 TR001420 NCATS NIH HHS

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Affiliation(s)

Jose-Franck Diaz-Garelli Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Roy Strowd Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Tamjeed Ahmed Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Brian J Wells Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Rebecca Merrill Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Javier Laurini Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Boris Pasche Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA
Umit Topaloglu Wake Forest Baptist Medical Center, Winston Salem, North Carolina, USA

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Incorporating patient-generated contextual data into care: Clinician perspectives using the Consolidated Framework for Implementation Science

Patient contextual data (PCD), defined as patient's values, environment, or behavior influencing health, are essential to the proper care of patients, yet often are missing in the electronic health record (EHR). The current EHR structures and practice demands produce barriers to document PCD systemically. We sought to understand clinicians' perceived facilitators and barriers to use PCD using a consumer informatics technology integrated into the EHR. The PCD components include patient perceived pressures; joys; preferred approach to care; perceived health; health-goals; and visit agenda. We conducted semi-structured interviews of twenty primary care clinicians from an academic health system implementing a PCD initiative. The analysis included an inductive approach and a deductive a priori framework, the Consolidated Framework for Implementation Research (CFIR). Clinicians identified the following facilitators of adoption: reinforcement of patient engagement; a focus on enhancing team-based care; and communication around how the tool can be incorporated for individualized care. Clinicians identified barriers as: challenges incorporating PCD into the time-compressed visit and reviewing the tool involved another click in the EHR. The deductive results spanned four domains and seven constructs of CFIR, principally finding intervention source, relative advantage, organizational needs, and relative priority as facilitators with a need for ongoing leadership for the culture change. Overall, clinicians supported the adoption of a consumer informatics technology, as they reflected on the perceived value of a new data source to enhance patient-centered care and involvement in the development process. User-focused optimization efforts aided in the improved functionality and adoption of the application.

Improved Patient Flow and Provider Efficiency After the Implementation of an Electronic Health Record

Electronic health records are used widely across the nation in many different types of healthcare facilities. Electronic health record systems can provide more accurate and complete information about a patient's health, improve patient safety, and improve patient care. The purpose of this project is to evaluate a provider efficiency and workflow program at a hospital-owned, freestanding urgent care system after implementation of an electronic health record. A retrospective, longitudinal approach was used to evaluate the implementation of an electronic health record system among six freestanding urgent care clinics. The logic model was used as a guiding framework to determine whether provider efficiency and patient flow were improved. Data were collected from participants via an online survey, electronic health record data review, paper chart review, and direct observation of providers. An evaluation of a provider efficiency program using door-to-triage, door-to-provider, door-to-discharge, and average length of stay at each urgent care clinic was collected. The results indicate improvement in all areas after implementation of the electronic health record in all six urgent care settings. The average length of stay decreased from 109 minutes in 2014 to 73 minutes in 2016.

Medication Accuracy in Electronic Health Records for Microbial Keratitis

Importance

Electronic health records (EHRs) contain an abundance of health information. However, researchers need to understand data accuracy to ask appropriate research questions.

Objective

To investigate the concordance of the names of medications for microbial keratitis in the structured, formal EHR medication list and the text of clinicians' progress notes.

Design, Setting, and Participants

This cross-sectional study, conducted in the cornea section of an ophthalmology department in a tertiary care, referral academic medical center, examined the medications of 53 patients with microbial keratitis treated until disease resolution from July 1, 2015, to August 1, 2018. Documentation of medications was compared between the structured medication list extracted from the EHR server and medications written into the clinical progress note and transcribed by the study team.

Exposure

Medication treatment for microbial keratitis.

Main Outcomes and Measures

Medication mismatch frequency.

Results

The study sample included 24 men and 29 women, with a mean (SD) age of 51.8 (19.6) years. Of the 247 medications identified, 57 (23.1%) of prescribed medications differed between the progress notes and the formal EHR-based medication list. Reasons included medications not prescribed via the EHR ordering system (25 [43.9%]), outside medications not reconciled in the internal EHR medication list (23 [40.4%]), and medications prescribed via the EHR ordering system and in the formal list, but not described in the clinical note (9 [15.8%]). Fortified antimicrobials represented the largest category for medication mismatch between modalities (17 of 70 [24.3%]). Nearly one-third of patients (17 [32.1%]) had at least 1 medication mismatch in their record.

Conclusions and Relevance

Almost 1 in 4 medications were mismatched between the progress note and formal medication list in the EHR. These findings suggest that EHR data should be checked for internal consistency before use in research.

Feasibility of a voice-enabled automated platform for medical data collection: CardioCube

AIM

A feasibility study was conducted to evaluate implementation of a voice-enabled automated platform for collection of medical data from patients with cardiovascular disease: CardioCube.

METHODS

The study enrolled 22 individuals (10 males, 45.5%) including 9 patients with cardiovascular disease and 13 healthy participants. Utilizing (1) voice-enabled patient registration software implemented on the Amazon Echo and (2) web-based electronic health record (EHR) system, study participants verbally answered a set of clinical questions. Primary endpoint: accuracy of ​the ​CardioCube system. Secondary endpoints: acceptability, usability and technical performance. The study was performed at the Outpatient Cardiology Clinic, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

RESULTS

The CardioCube system collected 432 data points with a high agreement level between verbally provided data and corresponding EHR information (accuracy 97.51%). The CardioCube was able to automatically generate a summarized medical report, which was instantly available for a doctor in the web-based EHR system. Patients reported CardioCube was "easy to use". Applicability of the system was graded excellent by the medical staff. A single session utilized less than 0.002% of available computational resources.

CONCLUSION

CardioCube can collect, index and document medical data using a voice interface. In this pilot study, CardioCube supported healthcare professionals by performing time-consuming paperwork during patient registration.

Lost in Translation: Diagnosis Records Show More Inaccuracies After Biopsy in Oncology Care EHRs

The use of diagnosis (DX) data is crucial to secondary use of electronic health record (EHR) data, yet accessible structured DX data often lack in accuracy. DX descriptions associated with structured DX codes vary even after recording biopsy results; this may indicate poor data quality. We hypothesized that biopsy reports in cancer care charts do not improve intrinsic DX data quality. We analyzed DX data for a manually well-annotated cohort of patients with brain neoplasms. We built statistical models to predict the number of fully-accurate (i.e., correct neoplasm type and anatomical location) and inaccurate DX (i.e. type or location contradicts cohort data) descriptions. We found some evidence of statistically larger numbers of fully-accurate (RR=3.07, p=0.030) but stronger evidence of much larger numbers of inaccurate DX (RR=12.3, p=0.001 and RR=19.6, p<0.0001) after biopsy result recording. Still, 65.9% of all DX records were neither fully-accurate nor fully-inaccurate. These results suggest EHRs must be modified to support more reliable DX data recording and secondary use of EHR data.

SEWA: A framework for sociotechnical analysis of electronic health record system workarounds

OBJECTIVE

To develop a conceptual framework, SEWA, to address challenges of studying workarounds emerging from Electronic Health Record (EHR) system usage.

MATERIALS AND METHODS

SEWA is based on direct observations and follow-up interviews with physicians, nurses and clerks using their EHR at a large academic hospital. SEWA was developed by an iterative process: each new version was reviewed by experts (case study participants, hospital management, EHR developers) and refined accordingly till deemed final.

RESULTS

SEWA defines the work system and its five components constituting the context in which EHR workarounds are created. It also contains 15 rationales for creating EHR workarounds. Furthermore, four attributes are included that define EHR workarounds: cascadedness, anticipatedness, avoidability, and repetitiveness. Finally, SEWA lists the possible effects of workarounds on outcomes of clinical processes in terms of scope and impact.

DISCUSSION

SEWA provides a grounded foundation for performing sociotechnical analyses of EHR workarounds based on components of the work system. SEWA can likewise be supportive in planning redesign efforts of the work system. Finally, workarounds are subject to gradual change caused by e.g. changes in one's knowledge of the EHR, hospital policies, care directives, and system updates. Snapshots of SEWA can be taken over time and compared to gain insights into the evolution of workarounds.

CONCLUSION

Given the absence of a sociotechnical framework to study EHR workarounds, SEWA could aid researchers and practitioners to identify, analyze and resolve workarounds, and thereby contribute to improved patient safety, effectiveness of care and efficiency of care.

A qualitative framework-based evaluation of radiology clinical decision support initiatives: eliciting key factors to physician adoption in implementation

Objectives

To illustrate key contextual factors that may have effects on clinical decision support (CDS) adoption and, ultimately, success.

Materials and Methods

We conducted a qualitative evaluation of 2 similar radiology CDS innovations for near-term endpoints affecting adoption and present the findings using an evaluation framework. We identified key contextual factors between these 2 innovations and determined important adoption differences between them.

Results

Degree of electronic health record integration, approach to education and training, key drivers of adoption, and tailoring of the CDS to the clinical context were handled differently between the 2 innovations, contributing to variation in their relative degrees of adoption and use. Attention to these factors had impacts on both near and later-term measures of success (eg, patient outcomes).

Discussion

CDS adoption is a well-studied early-term measure of CDS success that directly impacts outcomes. Adoption requires attention throughout the design phases of an intervention especially to key factors directly affecting it, including how implementation across multiple sites and systems complicates adoption, which prior experience with CDS matters, and that practice guidelines invariably require tailoring to the clinical context.

Conclusion

With better planning for the capture of early-term measures of successful CDS implementation, especially adoption, critical adjustments may be made to ensure that the CDS is effectively implemented to be successful.

Primary Care Practices' Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement

Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. To determine whether EHRs produce reports adequate to the task, we examined survey responses from 1,492 practices across twelve states, supplemented with qualitative data. Meaningful-use participation, which requires the use of a federally certified EHR, was associated with the ability to generate reports-but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, such as difficulty manipulating and aligning measurement time frames with quality improvement needs, lack of functionality for generating reports on electronic clinical quality measures at different levels, discordance between clinical guidelines and measures available in reports, questionable data quality, and vendors that were unreceptive to changing EHR configuration beyond federal requirements. The current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.

Burnout Among Physicians, Advanced Practice Clinicians and Staff in Smaller Primary Care Practices

BACKGROUND

Burnout among primary care physicians, advanced practice clinicians (nurse practitioners and physician assistants [APCs]), and staff is common and associated with negative consequences for patient care, but the association of burnout with characteristics of primary care practices is unknown.

OBJECTIVE

To examine the association between physician-, APC- and staff-reported burnout and specific structural, organizational, and contextual characteristics of smaller primary care practices.

DESIGN

Cross-sectional analysis of survey data collected from 9/22/2015-6/19/2017.

SETTING

Sample of smaller primary care practices in the USA participating in a national initiative focused on improving the delivery of cardiovascular preventive services.

PARTICIPANTS

10,284 physicians, APCs and staff from 1380 primary care practices.

MAIN MEASURE

Burnout was assessed with a validated single-item measure.

KEY RESULTS

Burnout was reported by 20.4% of respondents overall. In a multivariable analysis, burnout was slightly more common among physicians and APCs (physician vs. non-clinical staff, adjusted odds ratio [aOR] = 1.26; 95% confidence interval [CI], 1.05-1.49, APC vs. non-clinical staff, aOR = 1.34, 95% CI, 1.10-1.62). Other multivariable correlates of burnout included non-solo practice (2-5 physician/APCs vs. solo practice, aOR = 1.71; 95% CI, 1.35-2.16), health system affiliation (vs. physician/APC-owned practice, aOR = 1.42; 95%CI, 1.16-1.73), and Federally Qualified Health Center status (vs. physician/APC-owned practice, aOR = 1.36; 95%CI, 1.03-1.78). Neither the proportion of patients on Medicare or Medicaid, nor practice-level patient volume (patient visits per physician/APC per day) were significantly associated with burnout. In analyses stratified by professional category, practice size was not associated with burnout for APCs, and participation in an accountable care organization was associated with burnout for clinical and non-clinical staff.

CONCLUSIONS

Burnout is prevalent among physicians, APCs, and staff in smaller primary care practices. Members of solo practices less commonly report burnout, while members of health system-owned practices and Federally Qualified Health Centers more commonly report burnout, suggesting that practice level autonomy may be a critical determinant of burnout.

Designing health information technology tools for behavioral health clinicians integrated within a primary care team

Background

Electronic health records (EHRs) are a key tool for primary care practice. However, the EHR functionality is not keeping pace with the evolving informational and decision-support needs of behavioural health clinicians (BHCs) working on integrated teams.

Objective

Describe the workflows and tasks of integrated BHCs working with adult patients identify their health information technology (health IT) needs and develop EHR tools to address them.

Method

A mixed-methods, comparative case study of six community health centres (CHCs) in Oregon, each with at least one BHC integrated into their primary care team. We observed clinical work and conducted interviews to understand workflows and clinical tasks, aiming to identify how effectively current EHRs supported integrated care delivery, including transitions, documentation, information sharing and decision-making. We analysed these data and employed a user-centred design process to develop EHR tools addressing the identified needs.

Results

BHCs used the primary care EHR for documentation and communication with other team members, but the EHR lacked the functionality to fully support integrated care. Needs include the ability to: (1) automate and track paper-based screening; (2) document behavioural health history; (3) access patient social and medical history relevant to behavioural health issues and (4) rapidly document and track progress on goals. To meet these needs, we engaged users and developed a set of EHR tools called the Behavioural Health e-Suite (BH e-Suite).

Conclusion

US-based integrated primary care teams, and particularly BHCs working with adult populations, have unique information needs, workflows and tasks. These needs can be met and supported by the EHR with a moderate level of modification.

Checking the potential shift to perceived usefulness-The analysis of users' response to the updated electronic health record core features

OBJECTIVE

The primary objective of this paper is to identify the main factors which have an impact on the users' attitude towards the functionalities representing the perceived ease of use and to those representing the perceived usefulness. Another objective is to examine whether there occurred a shift towards the perceived usefulness of users' behavior over a period of time. To support these objectives, two different cases are examined - the case in which users are simultaneously offered basic and updated functionalities, and the one in which users are offered a completely new set of features. The results of this study are expected to exert a significant impact on a further development of new software components, as well as the updates of the existing ones.

MATERIAL AND METHODS

As the starting point, there were employed the user behavior indicators defined in similar researches and conducted in the countries with a similar cultural background or with a comparatively similar national healthcare system. What ensued was an updated set of functionalities offered within the electronic health record based medical information system. Instead of the survey being posted, the effects of implanted updates were measured through the analysis of the collected data. The data collected in the Nis Primary and Ambulatory Care Center during a four-year period represented the material used in the research. The obtained records indicating the usage of the initial and updated visit registration form, as well as the usage of the new types of visits, were examined in relation to the technology acceptance model and integrated behavior model.

RESULTS

The response to the initial functionalities, perceived as easy to use, was high as expected since they kept the users in their "comfort zone". As regards the updated features, the ones corresponding to the perceived usefulness, the initial overall acceptance rate was 60%, while the overall increase of their acceptance was around 20%. The overall usage of the newly introduced features was doubled in some cases throughout the four-year period, while some of them were not accepted as expected.

DISCUSSION

Carefully designed additional functionalities, aimed to improve the most common daily activities, have a significant potential to be accepted by the medical professionals. The shift from the perceived ease of use to the perceived usefulness is not uniform, nor is its use in different departments or by the users of the same department. A higher acceptance rate was observed in the departments with more complex administrative procedures, as well as among the users having contacts with more patients and using the system for a longer period.

CONCLUSION

When accepting new features, medical professionals will initially choose the simpler ones with obvious benefits. If the usage of a feature triggers indirect benefits, the number of examined patients is of a crucial importance for the acceptance of that feature. In the event of the advanced functionality with an extended set of options competing with the simple functionality covering basic requirements, the latter will be used. A feature design, together with a proper training, system stability and ensuring utilization, represent a key point for increasing the positive impact that the information system can have in many application areas, including the healthcare.

Laboratory testing in primary care: A systematic review of health IT impacts

INTRODUCTION

Laboratory testing in primary care is a fundamental process that supports patient management and care. Any breakdown in the process may alter clinical information gathering and decision-making activities and can lead to medical errors and potential adverse outcomes for patients. Various information technologies are being used in primary care with the goal to support the process, maximize patient benefits and reduce medical errors. However, the overall impact of health information technologies on laboratory testing processes has not been evaluated.

OBJECTIVES

To synthesize the positive and negative impacts resulting from the use of health information technology in each phase of the laboratory 'total testing process' in primary care.

METHODS

We conducted a systematic review. Databases including Medline, PubMed, CINAHL, Web of Science and Google Scholar were searched. Studies eligible for inclusion reported empirical data on: 1) the use of a specific IT system, 2) the impacts of the systems to support the laboratory testing process, and were conducted in 3) primary care settings (including ambulatory care and primary care offices). Our final sample consisted of 22 empirical studies which were mapped to a framework that outlines the phases of the laboratory total testing process, focusing on phases where medical errors may occur.

RESULTS

Health information technology systems support several phases of the laboratory testing process, from ordering the test to following-up with patients. This is a growing field of research with most studies focusing on the use of information technology during the final phases of the laboratory total testing process. The findings were largely positive. Positive impacts included easier access to test results by primary care providers, reduced turnaround times, and increased prescribed tests based on best practice guidelines. Negative impacts were reported in several studies: paper-based processes employed in parallel to the electronic process increased the potential for medical errors due to clinicians' cognitive overload; systems deemed not reliable or user-friendly hampered clinicians' performance; and organizational issues arose when results tracking relied on the prescribers' memory.

DISCUSSION

The potential of health information technology lies not only in the exchange of health information, but also in knowledge sharing among clinicians. This review has underscored the important role played by cognitive factors, which are critical in the clinician's decision-making, the selection of the most appropriate tests, correct interpretation of the results and efficient interventions.

CONCLUSIONS

By providing the right information, at the right time to the right clinician, many IT solutions adequately support the laboratory testing process and help primary care clinicians make better decisions. However, several technological and organizational barriers require more attention to fully support the highly fragmented and error-prone process of laboratory testing.

Predictors of physicians' stress related to information systems: a nine-year follow-up survey study

Background

Among the important stress factors for physicians nowadays are poorly functioning, time consuming and inadequate information systems. The present study examined the predictors of physicians’ stress related to information systems (SRIS) among Finnish physicians. The examined predictors were cognitive workload, staffing problems, time pressure, problems in teamwork and job satisfaction, adjusted for baseline levels of SRIS, age, gender and employment sector.

Methods

The study has a follow-up design with two survey data collection waves, one in 2006 and one in 2015, based on a random sample of Finnish physicians was used. The present study used a sample that included 1109 physicians (61.9% women; mean age in 2015 was 54.5; range 34–72) who provided data on the SRIS in both waves. The effects of a) predictor variable levels in 2006 on SRIS in 2015 and b) the change in the predictor variables from 2006 to 2015 on SRIS in 2015 were analysed with linear regression analyses.

Results

Regression analyses showed that the higher level of cognitive workload in 2006 significantly predicted higher level of SRIS in 2015 (β = 0.08). The reciprocity of this association was tested with cross-lagged structural equation model analyses which showed that the direction of the association was from cognitive workload to SRIS, not from SRIS to cognitive workload. Moreover, increases in time pressure (β = 0.16) and problems in teamwork (β = 0.10) were associated with higher levels of SRIS in 2015, whereas job satisfaction increase was associated with lower SRIS (β = − 0.06).

Conclusions

According to our results, physicians’ cognitive workload may have long-lasting negative ramifications in regard to how stressful physicians experience their health information systems to be. Thus, organisations should pay attention to physicians workload if they wish physicians to master all the systems they need to use. It is also important to provide physicians with enough time and collegial support in their system-related problems, and in learning new systems and system updates.

Time utilization and perceived psychosocial work environment among staff in Swedish primary care settings

Background

Over the past decades, reorganizations and structural changes in Swedish primary care have affected time utilization among health care professionals. Consequently, increases in administrative tasks have substantially reduced the time available for face-to-face consultations. This study examined how work-time was utilized and the association between work time utilization and the perceived psychosocial work environment in Swedish primary care settings.

Methods

This descriptive, multicentre, cross-sectional study was performed in 2014–2015. Data collection began with questionnaire. In the first section, respondents were asked to estimate how their workload was distributed between patients (direct and indirect patient work) and other work tasks. The questionnaire also comprised the Copenhagen Psychosocial Questionnaire, which assessed the psychosocial work environment. Next a time study was conducted where the participants reported their work-time based on three main categories: direct patient-related work, indirect patient-related work, and other work tasks. Each main category had a number of subcategories. The participants recorded the time spent (minutes) on each work task per hour, every day, for two separate weeks. Eleven primary care centres located in southeast Sweden participated. All professionals were asked to participate (n = 441), including registered nurses, primary care physicians, care administrators, nurse assistants, and allied professionals. Response rates were 75% and 79% for the questionnaires and the time study, respectively.

Results

All health professionals allocated between 30.9% - 37.2% of their work-time to each main category: direct patient work, indirect patient work, and other work. All professionals estimated a higher proportion of time spent in direct patient work than they reported in the time study. Physicians scored highest on the psychosocial scales of quantitative demands, stress, and role conflicts. Among allied professionals, the proportion of work-time spent on administrative tasks was associated with more role conflicts. Younger staff perceived more adverse working conditions than older staff.

Conclusions

This study indicated that Swedish primary care staff spent a limited proportion of their work time directly with patients. PCPs seemed to perceive their work environment in negative terms to a greater extent than other staff members. This study showed that work task allocations influenced the perceived psychosocial work environment.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-2948-6) contains supplementary material, which is available to authorized users.

Perspectives and Uses of the Electronic Health Record Among US Pediatricians: A National Survey

Little is known about how existing electronic health records (EHRs) influence the practice of pediatric medicine. A total of 808 pediatricians participated in a survey about workflows using the EHR. The EHR was the most commonly used source of initial patient information. Seventy-two percent reported requiring between 2 and 10 minutes to complete an initial review of the EHR. Several moderately severe information barriers were reported regarding the display of information in the EHR. Pediatricians acquire information about new patients from EHRs more often than any other source. EHRs play a critical role in pediatric care but require improved design and efficiency.

Do Years of Experience With Electronic Health Records Matter for Productivity in Community Health Centers?

This study investigated how years of experience with an electronic health record (EHR) related to productivity in community health centers (CHCs). Using data from the 2012 Uniform Data System, we regressed average annual medical visits, weighted for service intensity, as a function of full-time equivalent medical staff controlling for CHC size and location. Physician productivity significantly improved. Although the productivity of all other staff types was not significantly different by years of EHR experience, the trends showed lower productivity among nurses and other medical staff in CHCs with fewer years of EHR experience versus more years of experience.

Two-year longitudinal assessment of physicians' perceptions after replacement of a longstanding homegrown electronic health record: does a J-curve of satisfaction really exist?

This report describes a 2-year prospective, longitudinal survey of attending physicians in 3 clinical areas (family medicine, general pediatrics, internal medicine) who experienced a transition from a homegrown electronic health record (EHR) to a vendor EHR. Participants were already highly familiar with using EHRs. Data were collected 1 month before and 3, 6, 13, and 25 months post implementation. Our primary goal was to determine if perceptions followed a J-curve pattern in which they initially dropped but eventually surpassed baseline measures. A J-curve was not found for any measures, including workflow, safety, communication, and satisfaction. Only the reminders and alerts measure dropped and then returned to baseline (U-curve); a few remained flatlined. Most dropped and remained below baseline (L-curve). The only measure that remained above baseline was documenting in the exam room with the patient. This study adds to the literature about current controversies surrounding EHR adoption and physician satisfaction.

Assessment of SERVQUAL Model in Hospitals Located in Tier II Cities of India

Service quality, being an assessment of services offered to a customer or the extent to which the services offered meets customers’ expectations, plays a significant role in healthcare industry. Patients pay hefty prices for the services they avail from specialty hospitals and they demand quality services. Hospitals have a larger challenge in delivering these services effectively to the patients. The current study helps us understand the role of information systems in service delivery process. Most of the hospitals have adopted healthcare information systems due to the benefit it provides. The study attempts to analyze the impact of information systems on service quality in the hospitals which are located in Tier II cities. The popular SERVQUAL model is adopted for this purpose. Patients who visit the hospitals were part of the respondent group. Gap score is found in order to observe the expected and actual experience of the patients based on five dimensions.

Workarounds Emerging From Electronic Health Record System Usage: Consequences for Patient Safety, Effectiveness of Care, and Efficiency of Care

Background

Health care providers resort to informal temporary practices known as workarounds for handling exceptions to normal workflow unintendedly imposed by electronic health record systems (EHRs). Although workarounds may seem favorable at first sight, they are generally suboptimal and may jeopardize patient safety, effectiveness of care, and efficiency of care.

Objective

Research into the scope and impact of EHR workarounds on patient care processes is scarce. This paper provides insight into the effects of EHR workarounds on organizational workflows and outcomes of care services by identifying EHR workarounds and determining their rationales, scope, and impact on health care providers’ workflows, patient safety, effectiveness of care, and efficiency of care. Knowing the rationale of a workaround provides valuable clues about the source of origin of each workaround and how each workaround could most effectively be resolved. Knowing the scope and impact a workaround has on EHR-related safety, effectiveness, and efficiency provides insight into how to address related concerns.

Methods

Direct observations and follow-up semistructured interviews with 31 physicians, 13 nurses, and 3 clerks and qualitative bottom-up coding techniques was used to identify, analyze, and classify EHR workarounds. The research was conducted within 3 specialties and settings at a large university hospital. Rationales were associated with work system components (persons, technology and tools, tasks, organization, and physical environment) of the Systems Engineering Initiative for Patient Safety (SEIPS) framework to reveal their source of origin as well as to determine the scope and the impact of each EHR workaround from a structure-process-outcome perspective.

Results

A total of 15 rationales for EHR workarounds were identified of which 5 were associated with persons, 4 with technology and tools, 4 with the organization, and 2 with the tasks. Three of these 15 rationales for EHR workarounds have not been identified in prior research: data migration policy, enforced data entry, and task interference.

Conclusions

EHR workaround rationales associated with different SEIPS work system components demand a different approach to be resolved. Persons-related workarounds may most effectively be resolved through personal training, organization-related workarounds through reviewing organizational policy and regulations, tasks-related workarounds through process redesign, and technology- and tools-related workarounds through EHR redesign efforts. Furthermore, insights gained from knowing a workaround’s degree of influence as well as impact on patient safety, effectiveness of care, and efficiency of care can inform design and redesign of EHRs to further align EHR design with work contexts, subsequently leading to better organization and (safe) provision of care. In doing so, a research team in collaboration with all stakeholders could use the SEIPS framework to reflect on the current and potential future configurations of the work system to prevent unfavorable workarounds from occurring and how a redesign of the EHR would impact interactions between the work system components.

Exploring Workarounds Related to Electronic Health Record System Usage: A Study Protocol

Background

Health care providers resort to informal temporary practices known as workarounds for handling exceptions to normal workflow that are unintentionally imposed by electronic health record (EHR) systems. Although workarounds may seem favorable at first sight, they are generally suboptimal and may jeopardize patient safety, effectiveness, and efficiency of care. Identifying workarounds and understanding their motivations, scope, and impact is pivotal to support the design of user-friendly EHRs and achieve closer alignment between EHRs and work contexts.

Objective

We propose a study protocol to identify EHR workarounds and subsequently determine their scope and impact on health care providers’ workflows, patient safety, effectiveness, and efficiency of care. First, knowing whether a workaround solely affects the health care provider who devised it, or whether its effects extends beyond the EHR user to the work context of other health care providers, is key to accurately assessing its degree of influence on the overall patient care workflow. Second, knowing whether the consequence of an EHR workaround is favorable or unfavorable provides insights into how to address EHR-related safety, effectiveness, and efficiency concerns. Knowledge of both perspectives can provide input on optimizing EHR designs.

Methods

In the study, a combination of direct observations, semistructured interviews, and qualitative coding techniques will be used to identify, analyze, and classify EHR workarounds. The research project will be conducted within three distinct pediatric care processes and settings at a large university hospital.

Results

Data was collected using the described approach from January 2016 to March 2017. Data analysis is underway and is expected to be completed in May 2017. We aim to report the results of this study in a follow-up publication.

Conclusions

This study protocol provides a grounded framework to explore EHR workarounds from a holistic and integral perspective. Insights from this study can inform the design and redesign of EHRs to further align with work contexts of healthcare professionals, and subsequently lead to better organization and safer provision of care.

Impact of a scribe program on patient throughput, physician productivity, and patient satisfaction in a community-based emergency department

Previous literature on the impact of scribe programs varies and has mostly been reported from academic institutions or other clinics. We report the implementation of the scribe program in the emergency room of a community hospital and its impact on patient throughput, physician productivity, and patient satisfaction. We performed a quasi-experimental, before-and-after study measuring patient throughput metrics, physician productivity, and patient satisfaction. The intervention measuring the scribe implementation was divided into pre- and post-implementation periods. Patient throughput metrics were (1) door-to-room time, (2) room-to-doc time, (3) door-to-doc time, (4) doc-to-disposition time, and (5) length of stay for discharged/admitted patients. Our secondary outcome was physician productivity, which was calculated by measuring total patients seen per hour and work relative value units per hour. Additionally, we calculated the time-motion analysis in minutes to measure the emergency department physician’s efficiency by recording the following: (1) chart preparation, (2) chart review, (3) doctor–patient interaction, (4) physical examination, and (5) post-visit documentation. Finally, we measured patient satisfaction as provided by Press Ganey surveys. Data analysis was conducted in 12,721 patient encounters in the pre-scribe cohort, and 13,598 patient encounters in the post-scribe cohort. All the patient throughput metrics were statistically significant (p < 0.0001). The patients per hour increased from 2.3 ± 0.3 pre-scribe to 3.2 ± 0.6 post-scribe cohorts (p < 0.001). Total work relative value units per hour increased from 241(3.1 ± 1.5 per hour) pre-scribe cohort to 336 (5.2 ± 1.4 per hour) post-scribe cohort (p < 0.001). The pre-scribe patient satisfaction was high and remained high in the post-scribe cohort. There was a significant increase in the clinician providing satisfactory feedback from the pre-scribe (3.9 ± 0.3) to the post-scribe (4.7 ± 0.1) cohorts (p < 0.01). We describe a prospective trial of medical scribe use in the emergency department setting to improve patient throughput, physician productivity, and patient satisfaction. We illustrate that scribe use in community emergency department is feasible and results in improvement in all three metrics

Impact of a scribe program on patient throughput, physician productivity, and patient satisfaction in a community-based emergency department

Previous literature on the impact of scribe programs varies and has mostly been reported from academic institutions or other clinics. We report the implementation of the scribe program in the emergency room of a community hospital and its impact on patient throughput, physician productivity, and patient satisfaction. We performed a quasi-experimental, before-and-after study measuring patient throughput metrics, physician productivity, and patient satisfaction. The intervention measuring the scribe implementation was divided into pre- and post-implementation periods. Patient throughput metrics were (1) door-to-room time, (2) room-to-doc time, (3) door-to-doc time, (4) doc-to-disposition time, and (5) length of stay for discharged/admitted patients. Our secondary outcome was physician productivity, which was calculated by measuring total patients seen per hour and work relative value units per hour. Additionally, we calculated the time-motion analysis in minutes to measure the emergency department physician's efficiency by recording the following: (1) chart preparation, (2) chart review, (3) doctor-patient interaction, (4) physical examination, and (5) post-visit documentation. Finally, we measured patient satisfaction as provided by Press Ganey surveys. Data analysis was conducted in 12,721 patient encounters in the pre-scribe cohort, and 13,598 patient encounters in the post-scribe cohort. All the patient throughput metrics were statistically significant (p < 0.0001). The patients per hour increased from 2.3 ± 0.3 pre-scribe to 3.2 ± 0.6 post-scribe cohorts (p < 0.001). Total work relative value units per hour increased from 241(3.1 ± 1.5 per hour) pre-scribe cohort to 336 (5.2 ± 1.4 per hour) post-scribe cohort (p < 0.001). The pre-scribe patient satisfaction was high and remained high in the post-scribe cohort. There was a significant increase in the clinician providing satisfactory feedback from the pre-scribe (3.9 ± 0.3) to the post-scribe (4.7 ± 0.1) cohorts (p < 0.01). We describe a prospective trial of medical scribe use in the emergency department setting to improve patient throughput, physician productivity, and patient satisfaction. We illustrate that scribe use in community emergency department is feasible and results in improvement in all three metrics.

Incorporação de Tecnologias de Informação e Comunicação e qualidade na atenção básica em saúde no Brasil

Resumo: As Tecnologias de Informação e Comunicação (TIC) - meios para tratar informação e agilizar comunicação - contribuem para o cuidado. Este artigo descreve a incorporação de TIC na atenção básica e sua associação com a qualidade, utilizando Programa Nacional de Melhoria do Acesso e da Qualidade da Atenção Básica (PMAQ). É um estudo transversal. O universo englobou 17.053 equipes. Criou-se o Índice de Incorporação de Tecnologias de Informação e Comunicação (ITIC) englobando: infraestrutura, sistemas e utilização de informação. Para as associações, realizou-se análise de regressão. Somente 13,5% das equipes possuem grau alto de TIC. É na utilização da informação que se observou a maior força de associação. As TIC contribuem para a melhoria da qualidade da atenção básica.

Overcoming the Challenges of Unstructured Data in Multisite, Electronic Medical Record-based Abstraction

BACKGROUND

Unstructured data encountered during retrospective electronic medical record (EMR) abstraction has routinely been identified as challenging to reliably abstract, as these data are often recorded as free text, without limitations to format or structure. There is increased interest in reliably abstracting this type of data given its prominent role in care coordination and communication, yet limited methodological guidance exists.

OBJECTIVES

As standard abstraction approaches resulted in substandard data reliability for unstructured data elements collected as part of a multisite, retrospective EMR study of hospital discharge communication quality, our goal was to develop, apply and examine the utility of a phase-based approach to reliably abstract unstructured data. This approach is examined using the specific example of discharge communication for warfarin management.

RESEARCH DESIGN

We adopted a "fit-for-use" framework to guide the development and evaluation of abstraction methods using a 4-step, phase-based approach including (1) team building; (2) identification of challenges; (3) adaptation of abstraction methods; and (4) systematic data quality monitoring.

MEASURES

Unstructured data elements were the focus of this study, including elements communicating steps in warfarin management (eg, warfarin initiation) and medical follow-up (eg, timeframe for follow-up).

RESULTS

After implementation of the phase-based approach, interrater reliability for all unstructured data elements demonstrated κ's of ≥0.89-an average increase of +0.25 for each unstructured data element.

CONCLUSIONS

As compared with standard abstraction methodologies, this phase-based approach was more time intensive, but did markedly increase abstraction reliability for unstructured data elements within multisite EMR documentation.

Physician Opinions about EHR Use by EHR Experience and by Whether the Practice had optimized its EHR Use

Optimization and experience with using EHRs may improve physician experiences. Physician opinions about EHR-related impacts, and the extent to which these impacts differ by self-reported optimized EHR use and length of experience are examined through nationally representative physician data of EHR users from the National Electronic Health Records Survey extended survey (n=1,471). Logistic regression models first estimated how physicians’ length of times using an EHR were associated with each EHR-related impact. Additionally, a similar set of models estimated the association of self-reported optimized EHR use with each EHR impact. At least 70% of physicians using EHRs continue to attribute their administrative burdens to their EHR use. Physicians with 4 or more years of EHR experience accounted for 58% of those using EHRs. About 71% of EHR users self-reported using an optimized EHR. Physicians with more EHR experience and those in practices that optimized EHR use had positive opinions about the impacts of using EHRs, compared to their counterparts. These findings suggest that longer experience with EHRs improves perceptions about EHR use; and that perceived EHR use optimization is crucial to identifying EHR-related benefits. Finding ways to reduce EHR-related administrative burden has yet to be addressed.

The Feasibility of Using Electronic Health Records to Describe Demographic and Clinical Indicators of Migrant and Seasonal Farmworkers

Few extensive, national clinical databases exist on the health of migrant and seasonal farmworkers (MSFWs). Electronic health records (EHRs) are increasingly utilized by Federally Qualified Health Centers (FQHCs) and have the potential to improve clinical care and complement current surveillance and epidemiologic studies of underserved working populations, such as MSFWs. The aim of this feasibility study was to describe the demographics and baseline clinical indicators of patients at an FQHC by MSFW status. The authors described 2012 patient demographics, social history, medical indicators, and diagnoses by MSFW status from the de-identified EHR database of a large, multisite Colorado Migrant Health Center (MHC). Included in the study were 41,817 patients from 2012: 553 (1.3%) MSFWs, 20,665 (49.4%) non-MSFWs, and 20,599 (49.3%) who had no information in the MSFW field. MSFWs were more often male, married, employed, Hispanic, and Spanish-speaking compared with non-MSFWs. The most frequent diagnoses for all patients were hypertension, overweight/obesity, lipid disorder, type 2 diabetes, or a back disorder. Although there were significant missing values, this feasibility study was able to analyze medical data in a timely manner and show that Meaningful Use requirements can improve the usability of EHR data for epidemiologic research of MSFWs and other patients at FQHCs. The results of this study were consistent with current literature available for MSFWs. By reaching this vulnerable working population, EHRs may be a key data source for occupational injury and illness surveillance and research.

Electronic Health Record Use a Bitter Pill for Many Physicians

Electronic health record (EHR) adoption among office-based physician practices in the United States has increased significantly in the past decade. However, the challenges of using EHRs have resulted in growing dissatisfaction with the systems among many of these physicians. The purpose of this qualitative multiple-case study was to increase understanding of physician perceptions regarding the value of using EHR technology. Important findings included the belief among physicians that EHR systems need to be more user-friendly and adaptable to individual clinic workflow preferences, physician beliefs that lack of interoperability among EHRs is a major barrier to meaningful use of the systems, and physician beliefs that EHR use does not improve the quality of care provided to patients. These findings suggest that although government initiatives to encourage EHR adoption among office-based physician practices have produced positive results, additional support may be required in the future to maintain this momentum.

A Family Medicine Health Technology Strategy for Achieving the Triple Aim for US Health Care

Health information technology (health IT) and health technology, more broadly, offer tremendous promise for connecting, synthesizing, and sharing information critical to improving health care delivery, reducing health system costs, and achieving personal and community health. While efforts to spur adoption of electronic health records (EHRs) among US practices and hospitals have been highly successful, aspirations for effective data exchanges and translation of data into measureable improvements in health outcomes remain largely unrealized. There are shining examples of health enhancement through new technologies, and the discipline of family medicine is well poised to take advantage of these innovations to improve patient and population health. The Future of Family Medicine led to important family medicine health IT initiatives over the past decade. For example, the American Academy of Family Physicians (AAFP) Center for Health Information Technology and the Robert Graham Center provided important leadership for informing health IT policy and standard-setting, such as the Centers for Medicare and Medicaid Services EHR incentives programs (often referred to as "meaningful use."). As we move forward, there is a need for a new and more comprehensive family medicine strategy for technology. To inform the Family Medicine for America's Health (FMAHealth) initiative, this paper explores strategies and tactics that family medicine could pursue to improve the utility of technology for primary care and to help primary care become a leader in rapid development, testing, and implementation of new technologies. These strategies were also designed with a broader stakeholder audience in mind, intending to reach beyond the work being done by FMAHealth. Specific suggestions include: a shared primary care health IT center, meaningful primary care quality measures and capacity to assess/report them, increased primary care technology research, a national family medicine registry, enhancement of family physicians' technology leadership, and championing patient-centered technology functionality.

Quality measure performance in small practices before and after electronic health record adoption

Introduction:

To date, little research has been published on the impact that the transition from paper-based record keeping to the use of electronic health records (EHR) has on performance on clinical quality measures. This study examines whether small, independent medical practices improved in their performance on nine clinical quality measures soon after adopting EHRs.

Methods:

Data abstracted by manual review of paper and electronic charts for 6,007 patients across 35 small, primary care practices were used to calculate rates of nine clinical quality measures two years before and up to two years after EHR adoption.

Results:

For seven measures, population-level performance rates did not change before EHR adoption. Rates of antithrombotic therapy and smoking status recorded increased soon after EHR adoption; increases in blood pressure control occurred later. Rates of hemoglobin A1c testing, BMI recorded, and cholesterol testing decreased before rebounding; smoking cessation intervention, hemoglobin A1c control and cholesterol control did not significantly change.

Discussion:

The effect of EHR adoption on performance on clinical quality measures is mixed. To improve performance, practices may need to develop new workflows and adapt to different documentation methods after EHR adoption.

Conclusions:

In the short term, EHRs may facilitate documentation of information needed for improving the delivery of clinical preventive services. Policies and incentive programs intended to drive improvement should include in their timelines consideration of the complexity of clinical tasks and documentation needed to capture performance on measures when developing timelines, and should also include assistance with workflow redesign to fully integrate EHRs into medical practice.

Development of an Instrument to Measure the Unintended Consequences of EHRs

This article augments the existing body of literature through examining the creation and design of an instrument measuring unintended consequences (UCs) of electronic health records (EHRs). Data from a previous qualitative study that explored nurses' perceptions of EHR effectiveness as a communication system were analyzed using a theoretical model focused on decision making. The qualitative data, informed by the model, were then organized into an instrument seeking to quantitatively measure nurses' experiences with UCs of EHRs. The model assisted in revealing patterns in nurses' perceptions of the effectiveness of the EHR as a communication system that ultimately strengthened the development of the instrument. Instrumentation from qualitative data has long been considered an acceptable and positive approach to scale development. The process for accomplishing this goal has often been omitted from the literature. We contend that other researchers will find this methods article informative for similar undertakings.

Electronic health records and support for primary care teamwork

Objective Consensus that enhanced teamwork is necessary for efficient and effective primary care delivery is growing. We sought to identify how electronic health records (EHRs) facilitate and pose challenges to primary care teams as well as how practices are overcoming these challenges.

Methods Practices in this qualitative study were selected from those recognized as patient-centered medical homes via the National Committee for Quality Assurance 2011 tool, which included a section on practice teamwork. We interviewed 63 respondents, ranging from physicians to front-desk staff, from 27 primary care practices ranging in size, type, geography, and population size.

Results EHRs were found to facilitate communication and task delegation in primary care teams through instant messaging, task management software, and the ability to create evidence-based templates for symptom-specific data collection from patients by medical assistants and nurses (which can offload work from physicians). Areas where respondents felt that electronic medical record EHR functionalities were weakest and posed challenges to teamwork included the lack of integrated care manager software and care plans in EHRs, poor practice registry functionality and interoperability, and inadequate ease of tracking patient data in the EHR over time.

Discussion Practices developed solutions for some of the challenges they faced when attempting to use EHRs to support teamwork but wanted more permanent vendor and policy solutions for other challenges.

Conclusions EHR vendors in the United States need to work alongside practicing primary care teams to create more clinically useful EHRs that support dynamic care plans, integrated care management software, more functional and interoperable practice registries, and greater ease of data tracking over time.