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Patient characteristics, resource use and outcomes associated with general internal medicine hospital care: the General Medicine Inpatient Initiative (GEMINI) retrospective cohort study.

ABSTRACT: BACKGROUND:The precise scope of hospital care delivered under general internal medicine services remains poorly quantified. The purpose of this study was to describe the demographic characteristics, medical conditions, health outcomes and resource use of patients admitted to general internal medicine at 7 hospital sites in the Greater Toronto Area. METHODS:This was a retrospective cohort study involving all patients who were admitted to or discharged from general internal medicine at the study sites between Apr. 1, 2010, and Mar. 31, 2015. Clinical data from hospital electronic information systems were linked to administrative data from each hospital. We examined trends in resource use and patient characteristics over the study period. RESULTS:There were 136?208 admissions to general internal medicine involving 88?121 unique patients over the study period. General internal medicine admissions accounted for 38.8% of all admissions from the emergency department and 23.7% of all hospital bed-days. Over the study period, the number of admissions to general internal medicine increased by 32.4%; there was no meaningful change in the median length of stay or cost per hospital stay. The median patient age was 73 (interquartile range [IQR] 57-84) years, and the median number of coexisting conditions was 6 (IQR 3-9). The median acute length of stay was 4.6 (IQR 2.5-8.6) days, and the median total cost per hospital stay was $5850 (IQR $3915-$10?061). Patients received at least 1 computed tomography scan in 52.2% of admissions. The most common primary discharge diagnoses were pneumonia (5.0% of admissions), heart failure (4.7%), chronic obstructive pulmonary disease (4.1%), urinary tract infection (4.0%) and stroke (3.6%). INTERPRETATION:Patients admitted to general internal medicine services represent a large, heterogeneous, resource-intensive and growing population. Understanding and improving general internal medicine care is essential to promote a high-quality, sustainable health care system.

SUBMITTER: Verma AA

PROVIDER: S-EPMC5741428 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Patient characteristics, resource use and outcomes associated with general internal medicine hospital care: the General Medicine Inpatient Initiative (GEMINI) retrospective cohort study.

Verma Amol A AA Guo Yishan Y Kwan Janice L JL Lapointe-Shaw Lauren L Rawal Shail S Tang Terence T Weinerman Adina A Cram Peter P Dhalla Irfan A IA Hwang Stephen W SW Laupacis Andreas A Mamdani Muhammad M MM Shadowitz Steven S Upshur Ross R Reid Robert J RJ Razak Fahad F

CMAJ open 20171213 4

<h4>Background</h4>The precise scope of hospital care delivered under general internal medicine services remains poorly quantified. The purpose of this study was to describe the demographic characteristics, medical conditions, health outcomes and resource use of patients admitted to general internal medicine at 7 hospital sites in the Greater Toronto Area.<h4>Methods</h4>This was a retrospective cohort study involving all patients who were admitted to or discharged from general internal medicine ...[more]

PMID: 29237706

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Project description:BACKGROUND:Short hospital stays may represent opportunities to avert unnecessary admissions or expedite inpatient care. To inform the design of interventions that target patients with potentially avoidable hospital admissions or brief stays, we examined the patient, physician and situational characteristics associated with short stays among patients admitted to general internal medicine wards and describe the use of hospital resources by these patients. METHODS:This was a multicentre cross-sectional study conducted between Apr. 1, 2012, and Mar. 31, 2015, at 5 teaching hospitals in Toronto. We included all general internal medicine admissions through the emergency department. We examined patient, physician and situational predictors of a short hospital stay, which was defined as the patient's being discharged home alive in 2 possible time windows: less than 24 hours, or 72 hours or less. RESULTS:The final study sample included 56 055 admissions and 37 700 unique patients. Patients discharged in less than 24 hours and in 72 hours or less accounted for 4245 (7.6%) and 13 442 (31.6%) admissions, respectively. After we controlled for patient factors, patients of female physicians were less likely than those of male physicians to have stays lasting less than 24 hours (adjusted odds ratio [OR] 0.80, 95% confidence interval [CI] 0.74-0.86) or 72 hours or less (adjusted OR 0.82, 95% CI 0.79-0.86). Patients admitted at night or on a weekday were significantly more likely than those admitted at other times to have stays lasting less than 24 hours (night: adjusted OR 2.73, 95% CI 2.44-3.06; weekday: adjusted OR 1.26, 95% CI 1.17-1.36) or 72 hours or less (night: adjusted OR 1.29, 95% CI 1.22-1.37, weekday: adjusted OR 1.05, 95% CI 1.01-1.10). Among stays lasting less than 24 hours and 24-72 hours, intravenously administered medications were ordered for 2788 (65.7%) and 10 722 (79.8%) patients, respectively, and computed tomography scans were performed for 1561 (36.8%) and 5354 (39.1%) patients, respectively. INTERPRETATION:Short general internal medicine hospital stays were common and were associated with patient, physician and situational factors. Interventions to avert hospital admission or reduce length of stay may be more effective if they are accessible outside typical working hours and provide access to intravenous therapy and radiological investigations.

Project description:BackgroundPrior evaluation at our hospital demonstrated that, compared to White patients, Black and Latinx patients with congestive heart failure (CHF) were less likely to be admitted to the cardiology service rather than the general medicine service (GMS). Patients admitted to GMS (compared to cardiology) had inferior rates of cardiology follow-up and 30-day readmission.ObjectiveTo develop and test the feasibility and impacts of using quality improvement (QI) methods, in combination with the Public Health Critical Race Praxis (PHCRP) framework, to engage stakeholders in developing an intervention for ensuring guideline-concordant inpatient CHF care across all patient groups.MethodsWe compared measures for all patients admitted with CHF to GMS between September 2019 and March 2020 (intervention group) to CHF patients admitted to GMS in the previous year (pre-intervention group) and those admitted to cardiology during the pre-intervention and intervention periods (cardiology group). Our primary measures were 30-day readmissions and 14- and 30-day post-discharge cardiology follow-up.ResultsThere were 79 patients admitted with CHF to GMS during the intervention period, all of whom received the intervention. There were similar rates of Black and Latinx patients across the three groups. Compared to pre-intervention, intervention patients had a significantly lower 30-day readmission rate (18.9% vs. 24.8%; p=0.024), though the cardiology group also had a decrease in 30-day readmissions from the pre-intervention to intervention period. Compared to pre-intervention, intervention patients had significantly higher 14-day and 30-day post-discharge follow-up visits scheduled with cardiology (36.7% vs. 24.8%, p=0.005; 55.7% vs. 42.3%, p=0.0029), but no improvement in appointment attendance.ConclusionThis study provides a first test of applying the PHCRP framework within a stakeholder-engaged QI initiative for improving CHF care across races and ethnicities. Our study design cannot evaluate causation. However, the improvements in 30-day readmission, as well as in processes of care that may affect it, provide optimism that inclusion of a racism-conscious framework in QI initiatives is feasible and may enhance QI measures.

Project description:BackgroundUnderstanding the most common and costly conditions treated by inpatient general medical services is important for implementing quality improvement, developing health policy, conducting research, and designing medical education.ObjectiveTo determine the prevalence and cost of conditions treated on general internal medicine (GIM) inpatient services.DesignRetrospective cross-sectional study involving 7 hospital sites in Toronto, Canada.ParticipantsAll patients discharged between April 1, 2010 and March 31, 2015 who were admitted to or discharged from an inpatient GIM service.Main measuresHospital administrative data were used to identify diagnoses and costs associated with admissions. The primary discharge diagnosis was identified for each admission and categorized into clinically relevant and mutually exclusive categories using the Clinical Classifications Software (CCS) tool.Key resultsAmong 148,442 admissions, the most common primary discharge diagnoses were heart failure (5.1%), pneumonia (5.0%), urinary tract infection (4.6%), chronic obstructive pulmonary disease (4.5%), and stroke (4.4%). The prevalence of the 20 most common conditions was significantly correlated across hospitals (correlation coefficients ranging from 0.55 to 0.95, p???0.01 for all comparisons). No single condition represented more than 5.1% of all admissions or more than 7.9% of admissions at any hospital site. The costliest conditions were stroke (median cost $7122, interquartile range 5587-12,354, total cost $94,199,422, representing 6.0% of all costs) and the group of delirium, dementia, and cognitive disorders (median cost $12,831, IQR 9539-17,509, total cost $77,372,541, representing 4.9% of all costs). The 10 most common conditions accounted for only 36.2% of hospitalizations and 36.8% of total costs. The remaining hospitalizations included 223 different CCS conditions.ConclusionsGIM services care for a markedly heterogeneous population but the most common conditions were similar across 7 hospitals. The diversity of conditions cared for in GIM may be challenging for healthcare delivery and quality improvement. Initiatives that cut across individual diseases to address processes of care, patient experience, and functional outcomes may be more relevant to a greater proportion of the GIM population than disease-specific efforts.

Project description:BACKGROUND:Identifying patients at high risk of hospital preventable readmission is an essential step towards selecting those who might benefit from specific transitional interventions. OBJECTIVE:Derive and validate a predictive risk score for potentially avoidable readmission (PAR) based on analysis of readmissions, with a focus on medication. DESIGN/SETTING/PARTICIPANTS:Retrospective analysis of all hospital admissions to internal medicine wards between 2011 and 2014. Comparison between patients readmitted within 30 days and non-readmitted patients, as identified using a specially designed algorithm. Univariate and multivariate regression analyses of demographic data, clinical diagnoses, laboratory results, and the medication data of patients admitted during the first period (2011-2013), to identify factors associated with PAR. Using these, derive a predictive score with a regression coefficient-based scoring method. Subsequently, validate this score with a second cohort of patients admitted in 2013-2014. Variables were identified at hospital discharge. RESULTS:The derivation cohort included 7,317 hospital stays. Multivariate logistic regressions found significant associations with PAR for: [adjusted OR (95% CI)] hospital length of stay > 4 days [1.3 (1.1-1.7)], admission in previous 6 months [2.3 (1.9-2.8)], heart failure [1.3 (1.0-1.7)], chronic ischemic heart disease [1.7 (1.2-2.3)], diabetes with organ damage [2.2 (1.3-3.8)], cancer [1.4 (1.0-1.9)], metastatic carcinoma [1.9 (1.3-3.0)], anemia [1.2 (1.0-1.5)], hypertension [1.3 (1.1-1.7)], arrhythmia [1.3 (1.0-1.6)], hyperkalemia [1.4 (1.0-1.7)], opioid drug prescription [1.3 (1.1-1.6)], and acute myocardial infarction [0.6 (0.4-0.9)]. The PAR-Risk Score, derived from these results, demonstrated fair discriminatory and calibration power (C-statistic = 0.699; Brier Score = 0.069). The results for the validation cohort's operating characteristics were similar (C-statistic = 0.687; Brier Score = 0.064). CONCLUSION:This study identified routinely-available factors that were significantly associated with PAR. A predictive score was derived and internally validated.

Project description:BackgroundThe eConsultant model of care is an outpatient substitution approach which has been evaluated and implemented extensively internationally. It provides an asynchronous, digital, clinician-to-clinician advice service, giving primary care physicians remote access to specialist support for patient care within 3 business days. Results from initial trials of the eConsultant model in Australia support international evidence of reduced wait times and improved access to specialist input, avoidance of face-to-face hospital outpatient visits, and better integrated care. This study compared the cost of delivery of an eConsultant episode of care with that of a hospital-based outpatient appointment.MethodsA cost-minimisation analysis, using a decision analytic model, was used to compare the two approaches. eConsultant costs were calculated from specialist reported data (minutes spent preparing the response; the number of patients referred subsequently for a hospital-based outpatient appointment) and administration staff data (time spent recording the occasion-of-service). Outpatient costs were calculated using finance data and information from outpatient clinic managers at the hospital-based outpatient clinic. The primary outcome was incremental cost saving per patient from a hospital system perspective. Uncertainty was explored using one-way sensitivity analyses and characterised with probabilistic sensitivity analysis using 10,000 Monte Carlo simulations.ResultsThe traditional referral pathway cost estimate was $587.20/consult compared to $226.13/consult for an eConsultant episode: an efficiency saving of $361.07 per patient. The incremental difference between eConsultant and traditional care was most sensitive to the cost estimate of an outpatient attendance, the time for a specialist to complete an eConsult, and the probability of a patient requiring a face-to-face hospital-based attendance following an eConsult. However, at the upper bounds of each of these estimates, an eConsult remained the most cost-efficient model. In 96.5% of the Monte Carlo simulations eConsult was found to be more cost efficient than the traditional approach.ConclusionsThe eConsultant model of care was associated with a 61.5% efficiency gain, allowing diversion of support to hospital-based outpatient appointments.

Dataset Information

Patient characteristics, resource use and outcomes associated with general internal medicine hospital care: the General Medicine Inpatient Initiative (GEMINI) retrospective cohort study.

Publications

Patient characteristics, resource use and outcomes associated with general internal medicine hospital care: the General Medicine Inpatient Initiative (GEMINI) retrospective cohort study.

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