Validation of the V49.86 Code for Do-Not-Resuscitate Status in Hospitalized Patients at a Single Academic Medical Center.
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ABSTRACT:
SUBMITTER: Fonseca L
PROVIDER: S-EPMC6321991 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveThe pain prevalence of inpatients is not a well-studied medical issue in Asia. We have aimed to evaluate pain prevalence and characterize those patients who have suffered from severe, persistent pain.MethodsWe investigated pain prevalence using a quota sampling from 19 general wards during the year 2018. Using a structured questionnaire, eight interviewers visited patients at an age ≥ 20 years, and who had been staying in general wards for ≥ 3 days. Those patients were excluded if they were unable to respond to the interview questions. If they reported pain during hospitalization, the maximum pain level and the duration of pain suffered in the past 24 hours were assessed. Care-related pain was also surveyed.ResultsA total of 1,034 patients (M/F, 537/497) completed the survey. Amongst them, 719 patients (69.5%) experienced pain, with moderate and severe pain levels being 27.3% and 43%, respectively. Surgery was considered as it related to pain, including significantly severe pain. The top 3 care-related pain causes were needle pain, wound dressing, and change in position/chest percussion. Change in position/chest percussion and rehabilitation were associated with severe, persistent pain.ConclusionsPain is common in approximately 70% of inpatients, with surgery being associated with severe pain. Mobilization and rehabilitation may lead to severe, persistent pain. The periodic study of pain prevalence is essential in order to provide precise pain management.
| S-EPMC7721481 | biostudies-literature
Project description:ImportanceSome patients are avoiding essential care for fear of contracting coronavirus disease 2019 (COVID-19) in hospitals. There are few data, however, on the risk of acquiring COVID-19 in US hospitals.ObjectiveTo assess the incidence of COVID-19 among patients hospitalized at a large US academic medical center in the 12 weeks after the first inpatient case was identified.Design, setting, and participantsThis cohort study included all patients admitted to Brigham and Women's Hospital (Boston, Massachusetts) between March 7 and May 30, 2020. Follow-up occurred through June 17, 2020. Medical records for all patients who first tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse-transcription polymerase chain reaction (RT-PCR) on hospital day 3 or later or within 14 days of discharge were reviewed.ExposuresA comprehensive infection control program was implemented that included dedicated COVID-19 units with airborne infection isolation rooms, personal protective equipment in accordance with US Centers for Disease Control and Prevention recommendations, personal protective equipment donning and doffing monitors, universal masking, restriction of visitors, and liberal RT-PCR testing of symptomatic and asymptomatic patients.Main outcomes and measuresWhether infection was community or hospital acquired based on timing of tests, clinical course, and exposures.ResultsOver the 12-week period, 9149 patients (mean [SD] age, 46.1 [26.4] years; median [IQR] age, 51 years [30-67 years]; 5243 female [57.3%]) were admitted to the hospital, for whom 7394 SARS-CoV-2 RT-PCR tests were performed; 697 COVID-19 cases were confirmed, translating into 8656 days of COVID-19-related care. Twelve of the 697 hospitalized patients with COVID-19 (1.7%) first tested positive on hospital day 3 or later (median, 4 days; range, 3-15 days). Of these, only 1 case was deemed to be hospital acquired, most likely from a presymptomatic spouse who was visiting daily and diagnosed with COVID-19 before visitor restrictions and masking were implemented. Among 8370 patients with non-COVID-19-related hospitalizations discharged through June 17, 11 (0.1%) tested positive within 14 days (median time to diagnosis, 6 days; range, 1-14 days). Only 1 case was deemed likely to be hospital acquired, albeit with no known exposures.Conclusions and relevanceIn this cohort study of patients in a large academic medical center with rigorous infection control measures, nosocomial COVID-19 was rare during the height of the pandemic in the region. These findings may inform practices in other institutions and provide reassurance to patients concerned about contracting COVID-19 in hospitals.
| S-EPMC7489854 | biostudies-literature
Project description:BACKGROUND:Electronic medical records (EMRs) contain a wealth of information that can support data-driven decision making in health care policy design and service planning. Although research using EMRs has become increasingly prevalent, challenges such as coding inconsistency, data validity, and lack of suitable measures in important domains still hinder the progress. OBJECTIVE:The objective of this study was to design a structured way to process records in administrative EMR systems for health services research and assess validity in selected areas. METHODS:On the basis of a local hospital EMR system in Singapore, we developed a structured framework for EMR data processing, including standardization and phenotyping of diagnosis codes, construction of cohort with multilevel views, and generation of variables and proxy measures to supplement primary data. Disease complexity was estimated by Charlson Comorbidity Index (CCI) and Polypharmacy Score (PPS), whereas socioeconomic status (SES) was estimated by housing type. Validity of modified diagnosis codes and derived measures were investigated. RESULTS:Visit-level (N=7,778,761) and patient-level records (n=549,109) were generated. The International Classification of Diseases, Tenth Revision, Australian Modification (ICD-10-AM) codes were standardized to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) with a mapping rate of 87.1%. In all, 97.4% of the ICD-9-CM codes were phenotyped successfully using Clinical Classification Software by Agency for Healthcare Research and Quality. Diagnosis codes that underwent modification (truncation or zero addition) in standardization and phenotyping procedures had the modification validated by physicians, with validity rates of more than 90%. Disease complexity measures (CCI and PPS) and SES were found to be valid and robust after a correlation analysis and a multivariate regression analysis. CCI and PPS were correlated with each other and positively correlated with health care utilization measures. Larger housing type was associated with lower government subsidies received, suggesting association with higher SES. Profile of constructed cohorts showed differences in disease prevalence, disease complexity, and health care utilization in those aged above 65 years and those aged 65 years or younger. CONCLUSIONS:The framework proposed in this study would be useful for other researchers working with EMR data for health services research. Further analyses would be needed to better understand differences observed in the cohorts.
| S-EPMC6320424 | biostudies-other
Project description:BackgroundThere are plenty of studies investigating the disparity of payer status in accessing to care. However, most studies are either disease-specific or cohort-specific. Quantifying the disparity from the level of facility through a large controlled study are rare. This study aims to examine how the payer status affects patient hospitalization from the perspective of a facility.MethodsWe extracted all patients with visiting record in a medical center between 5/1/2009-4/30/2014, and then linked the outpatient and inpatient records three year before target admission time to patients. We conduct a retrospective observational study using a conditional logistic regression methodology. To control the illness of patients with different diseases in training the model, we construct a three-dimension variable with data stratification technology. The model is validated on a dataset distinct from the one used for training.ResultsPatients covered by private insurance or uninsured are less likely to be hospitalized than patients insured by government. For uninsured patients, inequity in access to hospitalization is observed. The value of standardized coefficients indicates that government-sponsored insurance has the greatest impact on improving patients' hospitalization.ConclusionAttention is needed on improving the access to care for uninsured patients. Also, basic preventive care services should be enhanced, especially for people insured by government. The findings can serve as a baseline from which to measure the anticipated effect of measures to reduce disparity of payer status in hospitalization.
| S-EPMC8425077 | biostudies-literature
Project description:ContextThe COVID-19 pandemic has highlighted variability in intensity of care. We aimed to characterize intensity of care among hospitalized patients with COVID-19.ObjectivesExamine the prevalence and predictors of admission code status, palliative care consultation, comfort-measures-only orders, and cardiopulmonary resuscitation (CPR) among patients hospitalized with COVID-19.MethodsThis cross-sectional study examined data from an international registry of hospitalized patients with COVID-19. A proportional odds model evaluated predictors of more aggressive code status (i.e., Full Code) vs. less (i.e., Do Not Resuscitate, DNR). Among decedents, logistic regression was used to identify predictors of palliative care consultation, comfort measures only, and CPR at time of death.ResultsWe included 29,923 patients across 179 sites. Among those with admission code status documented, Full Code was selected by 90% (n = 15,273). Adjusting for site, Full Code was more likely for patients who were of Black or Asian race (ORs 1.82, 95% CIs 1.5-2.19; 1.78, 1.15-3.09 respectively, relative to White race), Hispanic ethnicity (OR 1.89, CI 1.35-2.32), and male sex (OR 1.16, CI 1.0-1.33). Of the 4951 decedents, 29% received palliative care consultation, 59% transitioned to comfort measures only, and 29% received CPR, with non-White racial and ethnic groups less likely to receive comfort measures only and more likely to receive CPR.ConclusionIn this international cohort of patients with COVID-19, Full Code was the initial code status in the majority, and more likely among patients who were Black or Asian race, Hispanic ethnicity or male. These results provide direction for future studies to improve these disparities in care.
| S-EPMC9233554 | biostudies-literature
Project description: Not available
| S-EPMC7979268 | biostudies-literature
Project description:Objectives: To assess the external validity of the Padua and International Medical Prevention Registry on Venous Thromboembolism (IMPROVE-VTE) risk assessment models (RAMs) for predicting venous thromboembolism (VTE) within 90 days of admission among hospitalized medical patients in Japan. Materials and Methods: A university hospital cohort comprising 3876 consecutive patients ages ≥15 years admitted to a general internal medicine department between July 2016 and July 2021 was retrospectively analyzed using data extracted from their medical records. Results: A total of 74 VTE events (1.9%), including six cases with pulmonary embolism (0.2%), were observed. Both RAMs had poor discriminative performance (C-index=0.64 for both) and generally underestimated VTE risks. However, recalibrating the IMPROVE-VTE RAM to update the baseline hazard improved the calibration (calibration slope=1.01). Decision curve analysis showed that a management strategy with no prediction model outperformed a clinical management strategy guided by the originally proposed RAMs. Conclusions: Both RAMs require an update to function in this particular setting. Further studies with a larger-sized cohort, including re-estimation of the individual regression coefficients with additional, more context-specific predictors, are needed to create a useful model that would help advance risk-oriented VTE prevention programs.
| S-EPMC10064295 | biostudies-literature
Project description: Not available
| S-EPMC3193354 | biostudies-literature
Project description:One of the most significant changes in US hospitals over the past decade has been the emergence of hospitalists as key providers of inpatient care. The number of hospitalists in both community and teaching hospitals is growing rapidly, and as the field burgeons, many are questioning where hospitalists should reside within the academic medical center (AMC). Should they be a distinct division or department, or should they be incorporated into existing divisions? We describe hospital medicine's current trajectory and provide recommendations for hospital medicine's place in the AMC. Local social and economic factors are most likely to determine whether hospital medicine programs will become independent divisions at most AMCs. We believe that in many large AMCs, separate divisions of hospital medicine are less likely to form soon, and in our opinion should not form until they are able to fulfill the tripartite mission traditionally carried out by independent specialist divisions. At community hospitals and less research-oriented AMCs, hospital medicine programs may soon be ready to become separate divisions.
| S-EPMC2517972 | biostudies-other
Project description:BackgroundThe International Medical Prevention Registry for Venous Thromboembolism (IMPROVE) Bleeding Risk Score is the recommended risk assessment model (RAM) for predicting bleeding risk in acutely ill medical inpatients in Western countries. However, few studies have assessed its predictive performance in local Asian settings.MethodsWe retrospectively identified acutely ill adolescents and adults (aged ≥ 15 years) who were admitted to our general internal medicine department between July 5, 2016 and July 5, 2021, and extracted data from their electronic medical records. The outcome of interest was the cumulative incidence of major and nonmajor but clinically relevant bleeding 14 days after admission. For the two-risk-group model, we estimated sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively). For the 11-risk-group model, we estimated C statistic, expected and observed event ratio (E/O), calibration-in-the-large (CITL), and calibration slope. In addition, we recalibrated the intercept using local data to update the RAM.ResultsAmong the 3,876 included patients, 998 (26%) were aged ≥ 85 years, while 656 (17%) were hospitalized in the intensive care unit. The median length of hospital stay was 14 days. Clinically relevant bleeding occurred in 58 patients (1.5%), 49 (1.3%) of whom experienced major bleeding. Sensitivity, specificity, NPV, and PPV were 26.1% (95% confidence interval [CI]: 15.8-40.0%), 84.8% (83.6-85.9%), 98.7% (98.2-99.0%), and 2.5% (1.5-4.3%) for any bleeding and 30.9% (95% CI: 18.8-46.3%), 84.9% (83.7-86.0%), 99.0% (98.5-99.3%), and 2.5% (1.5-4.3%) for major bleeding, respectively. The C statistic, E/O, CITL, and calibration slope were 0.64 (95% CI: 0.58-0.71), 1.69 (1.45-2.05), - 0.55 (- 0.81 to - 0.29), and 0.58 (0.29-0.87) for any bleeding and 0.67 (95% CI: 0.60-0.74), 0.76 (0.61-0.87), 0.29 (0.00-0.58), and 0.42 (0.19-0.64) for major bleeding, respectively. Updating the model substantially corrected the poor calibration observed.ConclusionsIn our Japanese cohort, the IMPROVE bleeding RAM retained the reported moderate discriminative performance. Model recalibration substantially improved the poor calibration obtained using the original RAM. Before its introduction into clinical practice, the updated RAM needs further validation studies and an optimized threshold.
| S-EPMC10976666 | biostudies-literature