Dataset Information

The Impact of Electronic Health Records on the Duration of Patients' Visits: Time and Motion Study.

ABSTRACT: BACKGROUND:Despite the many benefits of electronic health records (EHRs), studies have reported that EHR implementation could create unintended changes in the workflow if not studied and designed properly. These changes may impact the time patients spend on the various steps of their visits, such as the time spent in the waiting area and the time spent with a physician. The amount of time patients spend in the waiting area before consultation is often a strong predictor of patient satisfaction, willingness to come back for a return visit, and overall experience. The majority of prior studies that examined the impact of EHR systems on time focused on single aspects of patient visits or user (physicians or nurses) activities. The impact of EHR use on patients' time spent during the different aspects of the visit is rarely investigated. OBJECTIVE:This study aimed to evaluate the impact of EHR systems on the amount of time spent by patients on different tasks during their visit to primary health care (PHC) centers. METHODS:A time and motion observational study was conducted at 4 PHC centers. The PHC centers were selected using stratified randomized sampling. Of the 4 PHC centers, 2 used an EHR system and 2 used a paper-based system. Each group had 1 center in a metropolitan area and another in a rural area. In addition, a longitudinal observation was conducted at one of the PHC centers after 1 year and again after 2 years of implementation. The analysis included descriptive statistics and group comparisons. RESULTS:The results showed no significant difference in the amount of time spent by patients in the reception area (P=.26), in the waiting area (P=.57), consultation time (P=.08), and at the pharmacy (P=.28) between the EHR and paper based groups. However, there was a significant difference (P<.001) in the amount of time spent on all tasks between the PHC centers located in metropolitan and rural areas. The longitudinal observation also showed reduction in the registration time (from 5.5 [SD 3.5] min to 0.9 [SD 0.5] min), which could be attributed to the introduction of a Web-based booking system. CONCLUSIONS:The variation in the time patients spend at PHC centers is more likely to be attributed to the facility location than EHR use. The changes in the introduction of new tools and functions, however, such as the Web-based booking system, can impact the duration of patients' visits.

SUBMITTER: Jabour AM

PROVIDER: S-EPMC7055816 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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The Impact of Electronic Health Records on the Duration of Patients' Visits: Time and Motion Study.

Jabour Abdulrahman Mohammed AM

JMIR medical informatics 20200207 2

<h4>Background</h4>Despite the many benefits of electronic health records (EHRs), studies have reported that EHR implementation could create unintended changes in the workflow if not studied and designed properly. These changes may impact the time patients spend on the various steps of their visits, such as the time spent in the waiting area and the time spent with a physician. The amount of time patients spend in the waiting area before consultation is often a strong predictor of patient satisf ...[more]

PMID: 32031539

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Project description:OBJECTIVE:The authors sought to develop and validate models using electronic health records to predict suicide attempt and suicide death following an outpatient visit. METHOD:Across seven health systems, 2,960,929 patients age 13 or older (mean age, 46 years; 62% female) made 10,275,853 specialty mental health visits and 9,685,206 primary care visits with mental health diagnoses between Jan. 1, 2009, and June 30, 2015. Health system records and state death certificate data identified suicide attempts (N=24,133) and suicide deaths (N=1,240) over 90 days following each visit. Potential predictors included 313 demographic and clinical characteristics extracted from records for up to 5 years before each visit: prior suicide attempts, mental health and substance use diagnoses, medical diagnoses, psychiatric medications dispensed, inpatient or emergency department care, and routinely administered depression questionnaires. Logistic regression models predicting suicide attempt and death were developed using penalized LASSO (least absolute shrinkage and selection operator) variable selection in a random sample of 65% of the visits and validated in the remaining 35%. RESULTS:Mental health specialty visits with risk scores in the top 5% accounted for 43% of subsequent suicide attempts and 48% of suicide deaths. Of patients scoring in the top 5%, 5.4% attempted suicide and 0.26% died by suicide within 90 days. C-statistics (equivalent to area under the curve) for prediction of suicide attempt and suicide death were 0.851 (95% CI=0.848, 0.853) and 0.861 (95% CI=0.848, 0.875), respectively. Primary care visits with scores in the top 5% accounted for 48% of subsequent suicide attempts and 43% of suicide deaths. C-statistics for prediction of suicide attempt and suicide death were 0.853 (95% CI=0.849, 0.857) and 0.833 (95% CI=0.813, 0.853), respectively. CONCLUSIONS:Prediction models incorporating both health record data and responses to self-report questionnaires substantially outperform existing suicide risk prediction tools.

Project description:BackgroundEmbedding patient accommodation need in the electronic health record (EHR) has been proposed as one means to improve health care delivery to patients with disabilities. Accommodation need is not a standard field in commercial EHR software. However, some medical practices ask about accommodation need and store it in the EHR. Little is known about how the information is used, or barriers to its use. This exploratory-descriptive study examines whether and how information about patients' disability-related accommodation needs stored in patient records is used in a primary health care center to plan for care.MethodsFour focus groups (n = 35) were conducted with staff of a Federally Qualified Health Center that asks four accommodation questions at intake for the EHR. Respondents were asked how they learned about patient accommodation need, whether and how they used the information in the EHR, barriers to its use, and recommendations for where accommodation information should reside. A brief semi-structured interview was conducted with patients who had indicated an accommodation need (n = 12) to learn their experience at their most recent appointment. The qualitative data were coded using structural coding and themes extracted.ResultsFive themes were identified from the focus groups: (1) staff often do not know accommodation needs before the patient's arrival; (2) electronic patient information systems offer helpful information, but their structure creates challenges and information gaps; (3) accommodations for a patient's disability occur, but are developed at the time of visit; (4) provider knowledge of a regular patient is often the basis for accommodation preparation; and (5) staff recognize benefits to advance knowledge of accommodation needs and are supportive of methods to enable it. Most patients did not recall indicating accommodation need on the intake form. However, they expected to be accommodated based upon the medical practice's knowledge of them.ConclusionsPatient accommodation information in the EHR can be useful for visit planning. However, the structure must enable transfer of information between scheduling and direct care and be updatable as needs change. Flexibility to record a variety of needs, visibility to differentiate accommodation need from other alerts, and staff education about needs were recommended.

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Project description:Long-term care (LTC) facilities are an important part of the health care industry, providing care to the fastest-growing group of the population. However, the adoption of electronic health records (EHRs) in LTC facilities lags behind other areas of the health care industry. One of the reasons for the lack of widespread adoption in the United States is that LTC facilities are not eligible for incentives under the Meaningful Use program. Implementation of an EHR system in an LTC facility can potentially enhance the quality of care, provided it is appropriately implemented, used, and maintained. Unfortunately, the lag in adoption of the EHR in LTC creates a paucity of literature on the benefits of EHR implementation in LTC facilities.The objective of this systematic review was to identify the potential benefits of implementing an EHR system in LTC facilities. The study also aims to identify the common conditions and EHR features that received favorable remarks from providers and the discrepancies that needed improvement to build up momentum across LTC settings in adopting this technology.The authors conducted a systematic search of PubMed, Cumulative Index of Nursing and Allied Health (CINAHL), and MEDLINE databases. Papers were analyzed by multiple referees to filter out studies not germane to our research objective. A final sample of 28 papers was selected to be included in the systematic review.Results of this systematic review conclude that EHRs show significant improvement in the management of documentation in LTC facilities and enhanced quality outcomes. Approximately 43% (12/28) of the papers reported a mixed impact of EHRs on the management of documentation, and 33% (9/28) of papers reported positive quality outcomes using EHRs. Surprisingly, very few papers demonstrated an impact on patient satisfaction, physician satisfaction, the length of stay, and productivity using EHRs.Overall, implementation of EHRs has been found to be effective in the few LTC facilities that have implemented them. Implementation of EHRs in LTC facilities caused improved management of clinical documentation that enabled better decision making.

Dataset Information

The Impact of Electronic Health Records on the Duration of Patients' Visits: Time and Motion Study.

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The Impact of Electronic Health Records on the Duration of Patients' Visits: Time and Motion Study.

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