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Relationship network at a mobile urgent care service unit: analysis of a work team.

ABSTRACT: Introduction:Professionals at the Mobile Urgent Care Service (Serviço de Atendimento Móvel de Urgência - SAMU) face extreme situations which pose high psychological demands. Objective:To investigate networks of relationships among employees of SAMU-Ceará, in Northeastern Brazil. Methods:Case study of qualitative nature in which we conducted semi-structured interviews with SAMU-Ceará staff. To draw the relationship network, we first interviewed three professionals including physicians and nurses. Based on their narratives, we interviewed two further employees named by the former. We used program Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires (iRaMuTeQ) for textual analysis of the narratives obtained. Structural network characteristics, such as size and density, were analyzed with software UCINET 6.123 and NetDraw 2.38. Results:The interviewees had worked at the service for one year at least. The connections identified based on the interviews evidenced interrelationship between networks involving the interviewees. The links found were weak and unarticulated, even though two interviewees worked in the same department. Discourse analysis yielded three classes: 1) teamwork characteristics and peculiar ways to execute work; 2) relational and subjective aspects centered on management; and 3) nature of the service delivered. Conclusions:The social networks at SAMU-Ceará represent a set of workers who establish mutual relationships to satisfy the demands and needs of service users in an integrated manner while attempting to respect the knowledge and autonomy of each member. Nevertheless, the networks evidenced conflict which is a cause of mental suffering at work.

SUBMITTER: Cavalcante JB

PROVIDER: S-EPMC7104832 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Relationship network at a mobile urgent care service unit: analysis of a work team.

Cavalcante Juliana Brito JB da-Silva-Junior Geraldo Bezerra GB Bastos Maria Luiza Almeida MLA Costa Mateus Estevam Medeiros MEM Santos Alexandre de Lima AL Maciel Regina Heloísa Mattei de Oliveira RHMO

Revista brasileira de medicina do trabalho : publicacao oficial da Associacao Nacional de Medicina do Trabalho-ANAMT 20180601 2

<h4>Introduction</h4>Professionals at the Mobile Urgent Care Service (Serviço de Atendimento Móvel de Urgência - SAMU) face extreme situations which pose high psychological demands.<h4>Objective</h4>To investigate networks of relationships among employees of SAMU-Ceará, in Northeastern Brazil.<h4>Methods</h4>Case study of qualitative nature in which we conducted semi-structured interviews with SAMU-Ceará staff. To draw the relationship network, we first interviewed three professionals including ...[more]

PMID: 32270080

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Project description:BACKGROUND:?In the neonatal intensive care unit (NICU), predefined acuity-based team care models are restricted to core roles and neglect interactions with providers outside of the team, such as interactions that transpire via electronic health record (EHR) systems. These unaccounted interactions may be related to the efficiency of resource allocation, information flow, communication, and thus impact patient outcomes. This study applied network analysis methods to EHR audit logs to model the interactions of providers beyond their core roles to better understand the interaction network patterns of acuity-based teams and relationships of the network structures with postsurgical length of stay (PSLOS). METHODS:?The study used the EHR log data of surgical neonates from a large academic medical center. The study included 104 surgical neonates, for whom 9,206 unique actions were performed by 457 providers in their EHRs. We applied network analysis methods to model EHR provider interaction networks of acuity-based teams in NICU postoperative care. We partitioned each EHR network into three subnetworks based on interaction types: (1) interactions between known core providers who were documented in scheduling records (core subnetwork); (2) interactions between core and noncore providers (extended subnetwork); and (3) interactions between noncore providers (extended subnetwork). For each core subnetwork, we assessed its capability to replicate predefined core-provider relations as documented in scheduling records. We further compared each EHR network, as well as its subnetworks, using standard network measures to determine its differences in network topologies. We conducted a case study to learn provider interaction networks taking care of 15 neonates who underwent gastrostomy tube placement surgery from EHR log data and measure the effectiveness of the interaction networks on PSLOS by the proportional-odds model. RESULTS:?The provider networks of four acuity-based teams (two high and two low acuity), along with their subnetworks, were discovered. We found that beyond capturing the predefined core-provider relations, EHR audit logs can also learn a large number of relations between core and noncore providers or among noncore providers. Providers in the core subnetwork exhibited a greater number of connections with each other than with providers in the extended subnetworks. Many more providers in the core subnetwork serve as a hub than those in the other types of subnetworks. We also found that high-acuity teams exhibited more complex network structures than low-acuity teams, with high-acuity team generating 6,416 interactions between 407 providers compared with 931 interactions between 124 providers, respectively. In addition, we discovered that high-acuity and low-acuity teams shared more than 33 and 25% of providers with each other, respectively, but exhibited different collaborative structures demonstrating that NICU providers shift across different acuity teams and exhibit different network characteristics. Results of case study show that providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those who treated higher PSLOS patients (p?=?0.03). CONCLUSION:?Network analysis can be applied to EHR log data to model acuity-based NICU teams capturing interactions between providers within the predesigned core team as well as those outside of the core team. In the NICU, dissemination of information may be linked to reduced PSLOS. EHR log data provide an efficient, accessible, and research-friendly way to study provider interaction networks. Findings should guide improvements in the EHR system design to facilitate effective interactions between providers.

Project description:BackgroundDuring the COVID-19 pandemic, new intensive care units (ICUs) were created and clinicians were assigned or volunteered to work in these ICUs. These new ICU teams were newly formed and may have had varying practice styles which could affect team dynamics. The purpose of our qualitative descriptive study was to explore clinician perceptions of team dynamics in this newly formed ICU and specifically understand the challenges and potential improvements in this environment to guide future planning and preparedness in ICUs.MethodsWe conducted 14 semistructured one-on-one interviews with six nurses and eight physicians from a newly formed 36- to 50-bed medical ICU designed for COVID-19 patients in a teaching hospital. We purposively sampled and recruited ICU nurses, medical/surgical nurses, fellows, and attending physicians (with pulmonary/critical care and anaesthesia training) to participate. Participants were asked about team dynamics in the ICU, its challenges, and potential solutions. We then used a rapid analytic approach by first deductively categorising interview data into themes, based on our interview guide, to create a unique data summary for each interview. Then, these data were transferred to a matrix to compare data across all interviews and inductively analysed these data to provide deeper insights into team dynamics in ICUs.ResultsWe identified two themes that impacted team dynamics positively (facilitator) and negatively (barrier): interpersonal factors (individual character traits and interactions among clinicians) and structural factors (unit-level factors affecting workflow, organisation, and administration). Clinicians had several suggestions to improve team dynamics (e.g., scheduling to ensure clinicians familiar with one another worked together, standardisation of care processes across teams, and disciplines).ConclusionsIn a newly formed COVID ICU, interpersonal factors and structural factors impacted the team's ability to work together. Considering team dynamics during ICU reorganisation is crucial and requires thoughtful attention to interpersonal and structural factors.

Project description:Introduction:Pain is the most common complaint for an emergency department (ED) visit, but ED pain management is poor. Reasons for poor pain management include providers' concerns for drug-seeking behaviors and perceptions of patients' complaints. Patients who had objective findings of long bone fractures were more likely to receive pain medication than those who did not, despite pain complaints. We hypothesized that patients who were interhospital-transferred from an ED to an intensive care unit (ICU) for urgent surgical interventions would display objective pathology for pain and thus receive adequate pain management at ED departure. Methods:This was a retrospective study at a single, quaternary referral, academic medical center. We included non-trauma adult ED patients who were interhospital-transferred and underwent operative interventions within 12 hours of ICU arrival between July 2013 and June 2014. Patients who had incomplete ED records, required invasive mechanical ventilation, or had no pain throughout their ED stay were excluded. Primary outcome was the percentage of patients at ED departure achieving adequate pain control of ? 50% of triage level. We performed multivariable logistic regression to assess association between demographic and clinical variables with inadequate pain control. Results:We included 112 patients from 39 different EDs who met inclusion criteria. Mean pain score at triage and ED departure was 8 (standard deviation 8 and 5 [3]), respectively. Median of total morphine equivalent unit (MEU) was 7.5 [5-13] and MEU/kg total body weight (TBW) was 0.09 [0.05-0.16] MEU/kg, with median number of pain medication administration of 2 [1-3] doses. Time interval from triage to first narcotic dose was 61 (35-177) minutes. Overall, only 38% of patients achieved adequate pain control. Among different variables, only total MEU/kg was associated with significant lower risk of inadequate pain control at ED departure (adjusted odds ratio = 0.22; 95% confidence interval = 0.05-0.92, p = 0.037). Conclusion:Pain control among a group of interhospital-transferred patients requiring urgent operative interventions, was inadequate. Neither demographic nor clinical factors, except MEU/kg TBW, were shown to associate with poor pain management at ED departure. Emergency providers should consider more effective strategies, such as multimodal analgesia, to improve pain management in this group of patients.

Project description:ImportanceUrgent Care (UC) encounters result in more inappropriate antibiotic prescriptions than other outpatient setting. Few stewardship interventions have focused on UC.ObjectiveTo evaluate the effectiveness of an antibiotic stewardship initiative to reduce antibiotic prescribing for respiratory conditions in a UC network.Design, setting, and participantsThis quality improvement study conducted in a UC network with 38 UC clinics and 1 telemedicine clinic included 493 724 total UC encounters. The study compared the antibiotic prescribing rates of all UC clinicians who encountered respiratory conditions for a 12-month baseline period (July 1, 2018, through June 30, 2019) with an intervention period (July 1, 2019, through June 30, 2020). A sustainability period (July 1, 2020, through June 30, 2021) was added post hoc.InterventionsStewardship interventions included (1) education for clinicians and patients, (2) electronic health record (EHR) tools, (3) a transparent clinician benchmarking dashboard, and (4) media. Occurring independently but concurrent with the interventions, a stewardship measure was introduced by UC leadership into the quality measures, including a financial incentive.Main outcomes and measuresThe primary outcome was the percentage of UC encounters with an antibiotic prescription for a respiratory condition. Secondary outcomes included antibiotic prescribing when antibiotics were not indicated (tier 3 encounters) and first-line antibiotics for acute otitis media, sinusitis, and pharyngitis. Interrupted time series with binomial generalized estimating equations were used to compare periods.ResultsThe baseline period included 207 047 UC encounters for respiratory conditions (56.8% female; mean [SD] age, 30.0 [21.4] years; 92.0% White race); the intervention period included 183 893 UC encounters (56.4% female; mean [SD] age, 30.7 [20.8] years; 91.2% White race). Antibiotic prescribing for respiratory conditions decreased from 47.8% (baseline) to 33.3% (intervention). During the initial intervention month, a 22% reduction in antibiotic prescribing occurred (odds ratio [OR], 0.78; 95% CI, 0.71-0.86). Antibiotic prescriptions decreased by 5% monthly during the intervention (OR, 0.95; 95% CI, 0.94-0.96). Antibiotic prescribing for tier 3 encounters decreased by 47% (OR, 0.53; 95% CI, 0.44-63), and first-line antibiotic prescriptions increased by 18% (OR, 1.18; 95% CI, 1.09-1.29) during the initial intervention month. Antibiotic prescriptions for tier 3 encounters decreased by an additional 4% each month (OR, 0.96; 95% CI, 0.94-0.98), whereas first-line antibiotic prescriptions did not change (OR, 1.00; 95% CI, 0.99-1.01). Antibiotic prescribing for respiratory conditions remained stable in the sustainability period.Conclusions and relevanceThe findings of this quality improvement study indicated that a UC antibiotic stewardship initiative was associated with decreased antibiotic prescribing for respiratory conditions. This study provides a model for UC antibiotic stewardship.

Dataset Information

Relationship network at a mobile urgent care service unit: analysis of a work team.

Publications

Relationship network at a mobile urgent care service unit: analysis of a work team.

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