A ward-based time study of paper and electronic documentation for recording vital sign observations.
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ABSTRACT:
SUBMITTER: Wong D
PROVIDER: S-EPMC7651906 | biostudies-literature | 2017 Jul
REPOSITORIES: biostudies-literature
Publications
A ward-based time study of paper and electronic documentation for recording vital sign observations.
Wong David D Bonnici Timothy T Knight Julia J Gerry Stephen S Turton James J Watkinson Peter P
Journal of the American Medical Informatics Association : JAMIA 20170701 4
<h4>Objective</h4>To investigate time differences in recording observations and an early warning score using traditional paper charts and a novel e-Obs system in clinical practice.<h4>Methods</h4>Researchers observed the process of recording observations and early warning scores across 3 wards in 2 university teaching hospitals immediately before and after introduction of the e-Obs system. The process of recording observations included both measurement and documentation of vital signs. Interrupt ...[more]
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Project description:BackgroundElectronic recording of vital sign observations (e-Obs) has become increasingly prevalent in hospital care. The evidence of clinical impact for these systems is mixed.ObjectiveThe objective of our study was to assess the effect of e-Obs versus paper documentation (paper) on length of stay (time between trauma unit admission and "fit to discharge") for trauma patients.MethodsA single-center, randomized stepped-wedge study of e-Obs against paper was conducted in two 26-bed trauma wards at a medium-sized UK teaching hospital. Randomization of the phased intervention order to 12 study areas was computer generated. The primary outcome was length of stay.ResultsA total of 1232 patient episodes were randomized (paper: 628, e-Obs: 604). There were 37 deaths in hospital: 21 in the paper arm and 16 in the e-Obs arm. For discharged patients, the median length of stay was 5.4 (range: 0.2-79.0) days on the paper arm and 5.6 (range: 0.1-236.7) days on the e-Obs arm. Competing risks regression analysis for time to discharge showed no difference between the treatment arms (subhazard ratio: 1.05; 95% CI 0.82-1.35; P=.68). A greater proportion of patient episodes contained an Early Warning Score (EWS) ?3 using the e-Obs system than using paper (subhazard ratio: 1.63; 95% CI 1.28-2.09; P<.001). However, there was no difference in the time to the subsequent observation, "escalation time" (hazard ratio 1.05; 95% CI 0.80-1.38; P=.70).ConclusionsThe phased introduction of an e-Obs documentation system was not associated with a change in length of stay. A greater proportion of patient episodes contained an EWS?3 using the e-Obs system, but this was not associated with a change in "escalation time."Trial registrationISRCTN Registry ISRCTN91040762; http://www.isrctn.com/ISRCTN91040762 (Archived by WebCite at http://www.webcitation.org/72prakGTU).
| S-EPMC6236204 | biostudies-literature
Project description:PURPOSE:To assess time requirements for patient encounters and estimate after-hours demands of paper-based clinical workflows in ophthalmology. DESIGN:Time-and-motion study with a structured survey. METHODS:This study was conducted in a single academic ophthalmology department. A convenience sample consisted of 7 attending ophthalmologists from 6 subspecialties observed during 414 patient encounters for the time-motion analysis and 12 attending ophthalmologists for the survey. Outcome measurements consisted of total time spent by attending ophthalmologists per patient and time spent on documentation, examination, and talking with patients. The survey assessed time requirements of documentation-related activities performed outside of scheduled clinic hours. RESULTS:Among the 7 attending ophthalmologists observed (6 men and 1 woman), mean ± SD age 43.9 ± 7.1 years, during encounters with 414 patients (57.8 ± 24.6 years of age), total time spent per patient was 8.1 ± 4.8 minutes, with 2.8 ± 1.4 minutes (38%) for documentation, 1.2 ± 0.9 minutes (17%) for examination, and 3.3 ± 3.1 minutes (37%) for talking with patients. New patient evaluations required significantly more time than routine follow-up visits and postoperative visits. Higher clinical volumes were associated with less time per patient. Survey results indicated that paper-based documentation was associated with minimal after-hours work on weeknights and weekends. CONCLUSIONS:Paper-based documentation takes up a substantial portion of the total time spent for patient care in outpatient ophthalmology clinics but is associated with minimal after-hours work. Understanding paper-based clinical workflows may help inform targeted strategies for improving electronic health record use in ophthalmology.
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Project description:OBJECTIVES:We validate a machine learning-based sepsis-prediction algorithm (InSight) for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate robustness to missing data, customisation to site-specific data using transfer learning and generalisability to new settings. DESIGN:A machine-learning algorithm with gradient tree boosting. Features for prediction were created from combinations of six vital sign measurements and their changes over time. SETTING:A mixed-ward retrospective dataset from the University of California, San Francisco (UCSF) Medical Center (San Francisco, California, USA) as the primary source, an intensive care unit dataset from the Beth Israel Deaconess Medical Center (Boston, Massachusetts, USA) as a transfer-learning source and four additional institutions' datasets to evaluate generalisability. PARTICIPANTS:684?443 total encounters, with 90?353 encounters from June 2011 to March 2016 at UCSF. INTERVENTIONS:None. PRIMARY AND SECONDARY OUTCOME MEASURES:Area under the receiver operating characteristic (AUROC) curve for detection and prediction of sepsis, severe sepsis and septic shock. RESULTS:For detection of sepsis and severe sepsis, InSight achieves an AUROC curve of 0.92 (95% CI 0.90 to 0.93) and 0.87 (95% CI 0.86 to 0.88), respectively. Four hours before onset, InSight predicts septic shock with an AUROC of 0.96 (95% CI 0.94 to 0.98) and severe sepsis with an AUROC of 0.85 (95% CI 0.79 to 0.91). CONCLUSIONS:InSight outperforms existing sepsis scoring systems in identifying and predicting sepsis, severe sepsis and septic shock. This is the first sepsis screening system to exceed an AUROC of 0.90 using only vital sign inputs. InSight is robust to missing data, can be customised to novel hospital data using a small fraction of site data and retains strong discrimination across all institutions.
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Project description:In health care, record keeping of doctor-patient encounters is vital for quality patient care and medico-legal reasons. We audited the documentation of post-acute consultant ward round (PACWR) in our department before and six months after an introduction of a proforma (standard form). The clinical notes of all patients admitted acutely under General Surgery over a period of one week before and one week after the introduction of a proforma were reviewed to note whether time and date, signature, impression and dietary plan were documented after PACWR. The nurses were also surveyed on the day of the PACWR for their certainty regarding the dietary plan of their patients and whether they had to contact the surgical team for clarification. There were 108 and 103 patients eligible for the first and second study periods respectively. After the introduction of the proforma, there was a statistically significant improvement in the documentation of time and date (37% vs. 72%, p-value < 0.01) and impression (40% vs. 61%, p-value < 0.01). Improvement in the documentation of the dietary plan reached statistical significant only when the analysis was restricted to the cases where a proforma was filled out (78 out of 103 patients). Introduction of the proforma had no statistically significant impact on the nurses' certainty regarding their patients' dietary plan and the number of times they had to contact the surgical teams. In conclusion, PACWR proforma improves overall documentation. This will help in avoiding adverse effects on patient care and medico-legal ramifications.
| S-EPMC4652723 | biostudies-literature
Project description:BackgroundThe outbreak of Coronavirus disease (COVID-19) pandemic has become the most serious global health issue. Isolation policy in hospitals is one of the most crucial protocols to prevent nosocomial infection of COVID-19. It is important to monitor and assess the physical conditions of the patients in isolation.MethodsOur institution has installed the novel non-contact wireless sensor for vital sign sensing and body movement monitoring for patients in COVID-19 isolation ward.ResultsWe have collected and compared data between the radar record with the nurse's handover record of two patients, one recorded for 13 days and the other recorded for 5 days. The P value by Fisher's exact test were 0.139 (temperature, P > 0.05) and 0.292 (heart beat rate, P > 0.05) respectively.ConclusionsThis is the first report about the application experience of this equipment. Therefore we attempted to share the experience and try to apply this equipment in COVID-19 patients in future to offer the more reliable and safe policy.
| S-EPMC7447692 | biostudies-literature
Project description:BackgroundAsthma is the most common pediatric chronic disease; thus, clinical guidelines have been developed for its assessment and management, which rely on systematic symptom documentation. Electronic health records (EHR) have the potential to record clinical data systematically; however, variability in documentation persists.ObjectiveTo identify if the use of a structured asthma template is associated with increased guideline-based asthma documentation and clinical outcomes when compared with the use of nonstructured ones.MethodsWe performed a retrospective case-control study comparing the use of nonstructured templates (NSTs) and asthma-structured templates (ASTs) in new patient and first follow-up encounters, evaluated by pediatric pulmonologists between March 2016 and December 2021. Asthma history items were selected following clinical guidelines, summarized in 29 items for new and 22 items for follow-up encounters. Associations with demographic, spirometry, and health care utilization were explored.ResultsA total of 546 initial encounters were included; 450 used structured templates. The use of an AST was associated with higher documentation of asthma items in initial and follow-up encounters. Linear regression analysis showed that the use of ASTs was associated with a 28.2% and 39.65% increase in asthma history completeness (in initial and follow-up encounters, respectively), compared with the use of NSTs. AST use was associated with higher rates of systemic steroid prescriptions within 12 months. No other differences were observed after adjusting for asthma severity.ConclusionsUsing asthma-specific structured templates was associated with increased guideline-based asthma documentation. Leveraging the EHR as a clinical and research tool has the potential to improve clinical practice.
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Project description:Study objectiveRecognition of pediatric sepsis is a key clinical challenge. We evaluate the performance of a sepsis recognition process including an electronic sepsis alert and bedside assessment in a pediatric emergency department (ED).MethodsThis was a cohort study with quality improvement intervention in a pediatric ED. Exposure was a positive electronic sepsis alert, defined as elevated pulse rate or hypotension, concern for infection, and at least one of the following: abnormal capillary refill, abnormal mental status, or high-risk condition. A positive electronic sepsis alert prompted team assessment or huddle to determine need for sepsis protocol. Clinicians could initiate team assessment or huddle according to clinical concern without positive electronic sepsis alert. Severe sepsis outcome defined as activation of the sepsis protocol in the ED or development of severe sepsis requiring ICU admission within 24 hours.ResultsThere were 182,509 ED visits during the study period, with 86,037 before electronic sepsis alert implementation and 96,472 afterward, and 1,112 (1.2%) positive electronic sepsis alerts. Overall, 326 patients (0.3%) were treated for severe sepsis within 24 hours. Test characteristics of the electronic sepsis alert alone to detect severe sepsis were sensitivity 86.2% (95% confidence interval [CI] 82.0% to 89.5%), specificity 99.1% (95% CI 99.0% to 99.2%), positive predictive value 25.4% (95% CI 22.8% to 28.0%), and negative predictive value 100% (95% CI 99.9% to 100%). Inclusion of the clinician screen identified 43 additional electronic sepsis alert-negative children, with severe sepsis sensitivity 99.4% (95% CI 97.8% to 99.8%) and specificity 99.1% (95% CI 99.1% to 99.2%). Electronic sepsis alert implementation increased ED sepsis detection from 83% to 96%.ConclusionElectronic sepsis alert for severe sepsis demonstrated good sensitivity and high specificity. Addition of clinician identification of electronic sepsis alert-negative patients further improved sensitivity. Implementation of the electronic sepsis alert was associated with improved recognition of severe sepsis.
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Project description:ObjectivesClinical deterioration in hospitalized children is associated with increased risk of mortality and morbidity. A prediction model capable of accurate and early identification of pediatric patients at risk of deterioration can facilitate timely assessment and intervention, potentially improving survival and long-term outcomes. The objective of this study was to develop a model utilizing vital signs from electronic health record data for predicting clinical deterioration in pediatric ward patients.DesignObservational cohort study.SettingAn urban, tertiary-care medical center.PatientsPatients less than 18 years admitted to the general ward during years 2009-2018.InterventionsNone.Measurements and main resultsThe primary outcome of clinical deterioration was defined as a direct ward-to-ICU transfer. A discrete-time logistic regression model utilizing six vital signs along with patient characteristics was developed to predict ICU transfers several hours in advance. Among 31,899 pediatric admissions, 1,375 (3.7%) experienced the outcome. Data were split into independent derivation (yr 2009-2014) and prospective validation (yr 2015-2018) cohorts. In the prospective validation cohort, the vital sign model significantly outperformed a modified version of the Bedside Pediatric Early Warning System score in predicting ICU transfers 12 hours prior to the event (C-statistic 0.78 vs 0.72; p < 0.01).ConclusionsWe developed a model utilizing six commonly used vital signs to predict risk of deterioration in hospitalized children. Our model demonstrated greater accuracy in predicting ICU transfers than the modified Bedside Pediatric Early Warning System. Our model may promote opportunities for timelier intervention and risk mitigation, thereby decreasing preventable death and improving long-term health.
| S-EPMC7483876 | biostudies-literature
Project description:ObjectiveTo determine whether a small, wearable multisensor device can discriminate between progressive versus relapsing multiple sclerosis (MS) and capture limb progression over a short interval, using finger and foot tap data.MethodsPatients with MS were followed prospectively during routine clinic visits approximately every 6 months. At each visit, participants performed finger and foot taps wearing the MYO-band, which includes accelerometer, gyroscope, and surface electromyogram sensors. Metrics of within-patient limb progression were created by combining the change in signal waveform features over time. The resulting upper (UE) and lower (LE) extremity metrics' discrimination of progressive versus relapsing MS were evaluated with calculation of AUROC. Comparisons with Expanded Disability Status Scale (EDSS) scores were made with Pearson correlation.ResultsParticipants included 53 relapsing and 15 progressive MS (72% female, baseline mean age 48 years, median disease duration 11 years, median EDSS 2.5, median 10 months follow-up). The final summary metrics differentiated relapsing from secondary progressive MS with AUROC UE 0.93 and LE 0.96. The metrics were associated with baseline EDSS (UE P = 0.0003, LE P = 0.0007). While most had no change in EDSS during the short follow-up, several had evidence of progression by the multisensor metrics.InterpretationWithin a short follow-up interval, this novel multisensor algorithm distinguished progressive from relapsing MS and captured changes in limb function. Inexpensive, noninvasive and easy to use, this novel outcome is readily adaptable to clinical practice and trials as a MS vital sign. This approach also holds promise to monitor limb dysfunction in other neurological diseases.
| S-EPMC7818086 | biostudies-literature
Project description:BACKGROUND:The implementation of an electronic health record (EHR) with structured and standardized recording of patient data can improve data quality and reusability. Whether and how users perceive these advantages may depend on the preimplementation situation. OBJECTIVE:To determine whether the influence of implementing a structured and standardized EHR on perceived EHR use, data quality, and data reuse differed for users working with paper-based records versus a legacy EHR before implementation. METHODS:We used an electronic questionnaire to measure users' perception before implementation (2014), expected change, and perceived change after implementation (2016) on three themes. We included all health care professionals in two university hospitals in the Netherlands. Before jointly implementing the same structured and standardized EHR, one hospital used paper-based records and the other a legacy EHR. We compared perceptions before and after implementation for both centers. Additionally, we compared expected benefit with perceived benefit. RESULTS:We received 7,611 responses (4,537 before and 3,074 after implementation) of which 5,707 (75%) were from professionals reading and recording patient data. A total of 975 (13%) professionals responded to both before and after implementation questionnaires. In the formerly paper-based center staff perceived improvement in all themes after implementation. The legacy EHR center experienced deterioration of perceived EHR use and data reuse, and only one improvement in EHR use. In both centers, for half of the aspects at least 45% of responders experienced results worse than expected preimplementation. CONCLUSION:Our results indicate that the preimplementation recording practice impacts the perceived effect of the implementation of a structured and standardized EHR. For almost half of the respondents the new EHR did not meet their expectations. Especially legacy EHR centers need to investigate the expectations as these might be different and less clear cut than those in paper-based centers. These expectations need to be addressed appropriately to achieve a successful implementation.
| S-EPMC6426723 | biostudies-literature