Development and validation of a knowledge-based score to predict Fried's frailty phenotype across multiple settings using one-year hospital discharge data: The electronic frailty score

We aimed to assess the prevalence of hospitalization for endometriosis in the general population in France and in each French region and to describe temporal trends, rehospitalization rates, and prevalence of the different types of endometriosis. The analyses were carried out on French hospital discharge data and covered the period 2008–2012 and a population of 14,239,197 women of childbearing age. In this population, the prevalence of hospitalization for endometriosis was 0.9%, ranging from 0.4% to 1.6% between regions. Endometriosis affected 1.5% of hospitalized women of childbearing age, ranging from 1.0% to 2.4% between regions. The number of patients hospitalized for endometriosis significantly increased over the study period (p<0.01). Of these, 4.2% were rehospitalized at least once at one year: ranging from 2.7% to 6.3% between regions. The cumulative rehospitalization rate at 3 years was 6.9%. The types of endometriosis according to the procedures performed were as follows: ovarian (40–50%), peritoneal (20–30%), intestinal (10–20%), and ureteral or bladder (<10%), with significant differences between regions. This is the first detailed epidemiological study of endometriosis in France. Further studies are needed to assess the reasons for the increasing prevalence of endometriosis and for the significant differences in regional prevalence of this disease.

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Development of a frailty score based on hospital discharge data linked to cohort data

International Journal for Population Data Science ◽

10.23889/ijpds.v3i4.801 ◽

2018 ◽

Vol 3 (4) ◽

Cited By ~ 1

Author(s):

Marie Annick Le Pogam ◽

Bastien Trächsel ◽

Laurence Seematter ◽

Valentin Rousson ◽

Bernard Burnand ◽

...

Keyword(s):

Logistic Regression ◽

World War Ii ◽

Predictive Model ◽

Hospital Discharge ◽

University Hospital ◽

Hospital Discharge Data ◽

Receiver Operating Curve ◽

Frailty Phenotype ◽

Discharge Data ◽

Procedure Codes

IntroductionFrailty is strongly associated with adverse health outcomes and health care costs in elders. However, we have almost no idea of the prevalence of frail older inpatients in Swiss hospitals. Hospital discharge data could contribute to predicting frailty in these patients, and eventually improving SwissDRGs system or casemix-adjustment. Objectives and ApproachThe HFrailty project aimed to develop a predictive model of Fried’s Frailty Phenotype (FFP) based on hospital discharge data. We linked Lausanne University Hospital (CHUV) discharge data to clinical data from the Lausanne cohort study (Lc65+) over the period 2004-2015. The Lc65+ is a longitudinal population-based cohort comprising three random samples of approximately 1500 Lausanne residents aged 65 to 70, born respectively before, during and after World War II. With stepwise and lasso penalized logistic regression, random forest and neural networks, we identified the best-performing model for predicting FFP using CHUV’s data recorded within 12 months prior to frailty assessments. ResultsAmong Lc65+ participants, 1649 were assessed for frailty and hospitalized at least once during the follow-up period, resulting in 3499 FFP assessments of which 544 were preceded by at least one hospitalization within 12 months. In total, 45.7% of the participants were men and 9.4% were frail (FFP score ≥ 3). As expected, prevalence of frailty increased with age from 4.1% in the 66-70 age group, to 5.3% and 10.5% in the 71-75 and 76-80 groups, respectively. Logistic regression with lasso penalty was finally the best model regarding both performance and complexity. It had an area under receiver operating curve of 0.67 to predict FFP based on detailed diagnosis and procedure codes. Conclusion/ImplicationsHospital discharge data may be used to identify frail and non-frail individuals and estimate their prevalence in the Swiss non-institutionalized population. Our predictive model showed limited performance and could be improved. We are currently testing groups of diagnosis and procedure codes, as predictors, instead of detailed ones.

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Comorbidities and Health Outcomes of African American Men With Prostate Cancer: Analysis of Outpatient Claims and Hospital Discharge Data

10.21236/ada398461 ◽

1999 ◽

Author(s):

Gerald P. Hoke

Keyword(s):

Prostate Cancer ◽

African American ◽

Health Outcomes ◽

Hospital Discharge ◽

African American Men ◽

Hospital Discharge Data ◽

Discharge Data

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Characterizing Firearm Assault Injury Among Young Black Men Using Arkansas Hospital Discharge Data

Journal of Interpersonal Violence ◽

10.1177/0886260521997947 ◽

2021 ◽

pp. 088626052199794

Author(s):

Nakita N. Lovelady ◽

Nickolas D. Zaller ◽

Mary Kate Stewart ◽

Ann M. Cheney ◽

Austin Porter III ◽

...

Keyword(s):

Hospital Discharge ◽

Black Men ◽

Hospital Discharge Data ◽

Hospital Charges ◽

Health Care Information ◽

Discharge Data ◽

Patient Demographics ◽

Predicting Factors ◽

Drug Use Disorders ◽

Care Information

Using statewide hospital discharge data from 2005 to 2014, this study aimed to describe and identify predictors of firearm assault among young Black men ages 18 to 44 in Arkansas. Descriptive analyses of data were performed for patient demographics (age, marital status, residential location, etc.), injury, and health care information (hospital charges, length of stay, mortality, time, day and season of injury, etc.). Logistic regression analysis was performed to identify significant predicting factors for firearm assault among this population. Most of the sample survived firearm assault injury, were ages 18–35, were not married, resided in Central Arkansas, and were admitted to a Central Arkansas hospital during night hours on weekends. The majority had a short hospital stay, and total charges exceeded $34 million during the study observation years. Most patients had no diagnosis of a mental disorder, and a little less than half had drug use disorders. Being ages 18–25, living in the Central region of Arkansas, and being married were all significant predictors of firearm assault for this population. Death was also significantly associated with firearm assault. Our findings lay the groundwork for understanding firearm assault injury among young Black men in Arkansas. Research should be expanded to examine other important data sources for firearm assault and to further explore the context of predicting factors, in order to provide a more comprehensive understanding of firearm assault and to better inform future prevention efforts.

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The Incidence, Characteristics, and Outcomes of Community and Hospital-Associated S. aureus Disease in Fulton County, Georgia

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2020.573 ◽

2020 ◽

Vol 41 (S1) ◽

pp. s81-s82

Author(s):

Andrew Webster ◽

Scott Fridkin ◽

Susan Ray

Keyword(s):

Hospital Discharge ◽

Population Based ◽

Incidence Rates ◽

Outcome Data ◽

Hospital Discharge Data ◽

Invasive Infection ◽

Emerging Infections ◽

Inpatient Hospitalization ◽

Discharge Data ◽

Total Treatment

Background: Due to reliance on hospital discharge data for case identification, the burden of noninvasive and community-acquired S. aureus disease is often underestimated. To determine the full burden of S. aureus infections, we utilized population-based surveillance in a large urban county. Methods: The Georgia Emerging Infections Program (GA EIP) conducted CDC-funded, population-based surveillance by finding cases of S. aureus infections in 8 counties around Atlanta in 2017. Cases were residents with S. aureus isolated from either a normally sterile site in a 30-day period (invasive cases) or another site in a 14-day period (noninvasive cases). Medical records (all invasive and 1:4 sample of noninvasive cases) among Fulton County residents were abstracted for clinical, treatment, and outcome data. Cases treated were mapped to standard therapeutic site codes. Noninvasive specimens were reviewed and attributed to an invasive case if both occurred within 2 weeks. Incidence rates were calculated using 2017 census population and using a weight-adjusted cohort to account for sampling. Results: In total, 1,186 noninvasive (1:4 sample) and 529 invasive cases of S. aureus in Fulton county were reviewed. Only 35 of 1,186 (2.9%) noninvasive cases were temporally linked to invasive cases, resulting in 5,133 cases after extrapolation (529 invasive, 4,604 noninvasive). All invasive cases and 3,776 of 4,604 noninvasive cases (82%) were treated (4,305 total). Treatment was highest in skin (90%) and abscess (97%), lowest in urine (62%) and sputum (60%), and consisted of antibacterial agents alone (65%) or in addition to drainage procedures (35%). Overall, 41% of all cases were hospitalized, 12% required ICU admission, and 2.7% died, almost exclusively with bloodstream and pulmonary infections. Attribution of noninvasive infection was most often outside healthcare settings (87%); only 341 (7.9%) were hospital-onset cases; however, 34% of cases had had healthcare exposure in the preceding year, most often inpatient hospitalization (75%) or recent surgery (35%). Estimated countywide incidence was 414 per 100,000 (130 for MRSA and 284 for MSSA), invasive infection was 50 per 100,000. Among treated cases, 57% were SSTI, and the proportion of cases caused by MRSA was ~33% but varied slightly by therapeutic site (Fig. 1). Conclusions: The incidence of treated S. aureus infection in our large urban county is estimated to be 414 per 100,000 persons, which exceeds previously estimated rates based on hospital discharge data. Only 12% of treated infections were invasive, and <1 in 10 were hospital onset. Also, two-thirds of treated disease cases were MSSA; most were SSTIs.Funding: Proprietary Organization: Pfizer.Disclosures: Scott Fridkin, consulting fee - vaccine industry (spouse).

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