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1.
Med Care ; 55(7): 698-705, 2017 07.
Artigo em Inglês | MEDLINE | ID: mdl-28498196

RESUMO

OBJECTIVE: We extend the literature on comorbidity measurement by developing 2 indices, based on the Elixhauser Comorbidity measures, designed to predict 2 frequently reported health outcomes: in-hospital mortality and 30-day readmission in administrative data. The Elixhauser measures are commonly used in research as an adjustment factor to control for severity of illness. DATA SOURCES: We used a large analysis file built from all-payer hospital administrative data in the Healthcare Cost and Utilization Project State Inpatient Databases from 18 states in 2011 and 2012. METHODS: The final models were derived with bootstrapped replications of backward stepwise logistic regressions on each outcome. Odds ratios and index weights were generated for each Elixhauser comorbidity to create a single index score per record for mortality and readmissions. Model validation was conducted with c-statistics. RESULTS: Our index scores performed as well as using all 29 Elixhauser comorbidity variables separately. The c-statistic for our index scores without inclusion of other covariates was 0.777 (95% confidence interval, 0.776-0.778) for the mortality index and 0.634 (95% confidence interval, 0.633-0.634) for the readmissions index. The indices were stable across multiple subsamples defined by demographic characteristics or clinical condition. The addition of other commonly used covariates (age, sex, expected payer) improved discrimination modestly. CONCLUSIONS: These indices are effective methods to incorporate the influence of comorbid conditions in models designed to assess the risk of in-hospital mortality and readmission using administrative data with limited clinical information, especially when small samples sizes are an issue.


Assuntos
Mortalidade Hospitalar/tendências , Readmissão do Paciente/tendências , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Comorbidade , Bases de Dados Factuais , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Medição de Risco/métodos , Adulto Jovem
2.
Med Care ; 55(11): 918-923, 2017 11.
Artigo em Inglês | MEDLINE | ID: mdl-28930890

RESUMO

BACKGROUND: Trend analyses of opioid-related inpatient stays depend on the availability of comparable data over time. In October 2015, the US transitioned diagnosis coding from International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to ICD-10-CM, increasing from ∼14,000 to 68,000 codes. This study examines how trend analyses of inpatient stays involving opioid diagnoses were affected by the transition to ICD-10-CM. SUBJECTS: Data are from Healthcare Cost and Utilization Project State Inpatient Databases for 14 states in 2015-2016, representing 26% of acute care inpatient discharges in the US. STUDY DESIGN: We examined changes in the number of opioid-related stays before, during, and after the transition to ICD-10-CM using quarterly ICD-9-CM data from 2015 and quarterly ICD-10-CM data from the fourth quarter of 2015 and the first 3 quarters of 2016. RESULTS: Overall, stays involving any opioid-related diagnosis increased by 14.1% during the ICD transition-which was preceded by a much lower 5.0% average quarterly increase before the transition and followed by a 3.5% average increase after the transition. In stratified analysis, stays involving adverse effects of opioids in therapeutic use showed the largest increase (63.2%) during the transition, whereas stays involving abuse and poisoning diagnoses decreased by 21.1% and 12.4%, respectively. CONCLUSIONS: The sharp increase in opioid-related stays overall during the transition to ICD-10-CM may indicate that the new classification system is capturing stays that were missed by ICD-9-CM data. Estimates of stays involving other diagnoses may also be affected, and analysts should assess potential discontinuities in trends across the ICD transition.


Assuntos
Cuidados Críticos/tendências , Classificação Internacional de Doenças/estatística & dados numéricos , Tempo de Internação/tendências , Transtornos Relacionados ao Uso de Opioides/diagnóstico , Bases de Dados Factuais , Humanos , Tempo de Internação/estatística & dados numéricos , Estados Unidos
3.
Am J Emerg Med ; 34(1): 83-7, 2016 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-26603268

RESUMO

STUDY OBJECTIVE: Duration of a stay in an emergency department (ED) is considered a measure of quality, but current measures average lengths of stay across all conditions. Previous research on ED length of stay has been limited to a single condition or a few hospitals. We use a census of one state's data to measure length of ED stays by patients' conditions and dispositions and explore differences between means and medians as quality metrics. METHODS: The data source was the Healthcare Cost and Utilization Project 2011 State Emergency Department Databases and State Inpatient Databases for Florida. Florida is unique in collecting ED length of stay for both released and admitted patients. Clinical Classifications Software was used to group visits based on first-listed International Classification of Disease, Ninth Edition, Clinical Modification, diagnoses. RESULTS: For the 10 most common diagnoses, patients with relatively minor injuries typically required the shortest mean stay (3 hours or less); conditions resulting in admission or transfer tended to be more serious, resulting in longer stays. Patients requiring the longest stays, by disposition, had discharge diagnoses of nonspecific chest pain (mean 7.4 hours among discharged patients), urinary tract infections (4.8 hours among admissions), and schizophrenia (9.6 hours among transfers) among the top 10 diagnoses. CONCLUSION: Emergency department length of stay as a measure of ED quality should take into account the considerable variation by condition and disposition of the patient. Emergency department length of stay measurement could be improved in the United States by standardizing its definition; distinguishing visits involving treatment, observation, and boarding; and incorporating more distributional information.


Assuntos
Serviço Hospitalar de Emergência/normas , Classificação Internacional de Doenças , Tempo de Internação , Qualidade da Assistência à Saúde , Fatores Etários , Bases de Dados Factuais , Florida , Humanos , Admissão do Paciente , Alta do Paciente , Transferência de Pacientes , Estudos Retrospectivos , Fatores de Tempo
5.
Health Serv Res ; 52(1): 220-243, 2017 02.
Artigo em Inglês | MEDLINE | ID: mdl-26969578

RESUMO

OBJECTIVE: To examine the role of patient, hospital, and community characteristics on racial and ethnic disparities in in-hospital postsurgical complications. DATA SOURCES: Healthcare Cost and Utilization Project, 2011 State Inpatient Databases; American Hospital Association Annual Survey of Hospitals; Area Health Resources Files; Centers for Medicare & Medicaid Services Hospital Compare database. METHODS: Nonlinear hierarchical modeling was conducted to examine the odds of patients experiencing any in-hospital postsurgical complication, as defined by Agency for Healthcare Research and Quality Patient Safety Indicators. PRINCIPAL FINDINGS: A total of 5,474,067 inpatient surgical discharges were assessed using multivariable logistic regression. Clinical risk, payer coverage, and community-level characteristics (especially income) completely attenuated the effect of race on the odds of postsurgical complications. Patients without private insurance were 30 to 50 percent more likely to have a complication; patients from low-income communities were nearly 12 percent more likely to experience a complication. Private, not-for-profit hospitals in small metropolitan or micropolitan areas and higher nurse-to-patient ratios led to fewer postsurgical complications. CONCLUSIONS: Race does not appear to be an important determinant of in-hospital postsurgical complications, but insurance and community characteristics have an effect. A population-based approach that includes improving the socioeconomic context may help reduce disparities in these outcomes.


Assuntos
Etnicidade/estatística & dados numéricos , Disparidades em Assistência à Saúde/estatística & dados numéricos , Complicações Pós-Operatórias/epidemiologia , Grupos Raciais/estatística & dados numéricos , Negro ou Afro-Americano/estatística & dados numéricos , Disparidades em Assistência à Saúde/etnologia , Hispânico ou Latino/estatística & dados numéricos , Hospitais/normas , Hospitais/estatística & dados numéricos , Humanos , Seguro Saúde/estatística & dados numéricos , Modelos Logísticos , Complicações Pós-Operatórias/etnologia , Pobreza/estatística & dados numéricos , Fatores de Risco , Estados Unidos/epidemiologia , População Branca/estatística & dados numéricos
6.
Prev Med Rep ; 7: 86-90, 2017 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-28626625

RESUMO

Increasingly, corporate health promotion programs are implementing wellness programs integrating principles of behavioral economics. Employees of a large firm were provided a customized online incentive program to design their own commitments to meet health goals. This study examines patterns of program participation and engagement in health promotion activities. Subjects were US-based employees of a large, nondurable goods manufacturing firm who were enrolled in corporate health benefits in 2010 and 2011. We assessed measures of engagement with the workplace health promotion program (e.g., incentive points earned, weight loss). To further examine behaviors indicating engagement in health promotion activities, we constructed an aggregate, employee-level engagement index. Regression models were employed to assess the association between employee characteristics and the engagement index, and the engagement index and spending. 4220 employees utilized the online program and made 25,716 commitments. Male employees age 18-34 had the highest level of engagement, and male employees age 55-64 had the lowest level of engagement overall. Prior year health status and prior year spending did not show a significant association with the level of engagement with the program (p > 0.05). Flexible, incentive-based behavioral health and lifestyle programs may reach the broader workforce including those with chronic conditions and higher levels of health spending.

7.
Diagnosis (Berl) ; 3(3): 103-113, 2016 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-29536895

RESUMO

BACKGROUND: Often patients who present to the emergency department (ED) with chest symptoms return to the hospital within 30 days with the same or closely related symptoms and are admitted, raising questions about quality of care, timeliness of diagnosis, and patient safety. This study examined the frequency of and patient characteristics associated with subsequent inpatient admissions for related symptoms after discharge from an ED for chest symptoms. METHODS: We used data from the 2012 and 2013 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) and State Emergency Department Databases (SEDD) from eight states to identify over 1.8 million ED discharges for chest symptoms. RESULTS: Approximately 3% of ED discharges experienced potentially related subsequent admissions within 30 days - 0.2% for acute myocardial infarction (AMI), 1.7% for other cardiovascular conditions, 0.5% for respiratory conditions, and 0.6% for mental disorders. Logistic regression results showed higher odds of subsequent admission for older patients and those residing in low-income areas, and lower odds for females and non White racial/ethnic groups. Privately insured patients had lower odds of subsequent admission than did those who were uninsured or covered by other programs. CONCLUSIONS: Because we included multiple diagnostic categories of subsequent admissions, our results show a more complete picture of patients presenting to the ED with chest symptoms compared with previous studies. In particular, we show a lower rate of subsequent admission for AMI versus other diagnoses. ED physicians and administrators can use the results to identify characteristics associated with increased odds of subsequent admission to target at-risk populations.

9.
J Ther Ultrasound ; 2: 7, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25512868

RESUMO

BACKGROUND: To compare one-year all-cause and uterine fibroid (UF)-related direct costs in patients treated with one of the following three uterine-sparing procedures: magnetic resonance-guided focused ultrasound (MRgFUS), uterine artery embolization (UAE) and myomectomy. METHODS: This retrospective observational cohort study used healthcare claims for several million individuals with healthcare coverage from employers in the MarketScan Database for the period 2003-2010. UF patients aged 25-54 on their first UF procedure (index) date with 366-day baseline experience, 366-day follow-up period, continuous health plan enrollment during baseline and follow-up, and absence of any baseline UF procedures were included in the final sample. Cost outcomes were measured by allowed charges (sum of insurer-paid and patient-paid amounts). UF-related cost was defined as difference in mean cost between study cohorts and propensity-score-matched control cohorts without UF. Multivariate adjustment of cost outcomes was conducted using generalized linear models. RESULTS: The study sample comprised 14,426 patients (MRgFUS = 14; UAE = 4,092; myomectomy = 10,320) with a higher percent of older patients in MRgFUS cohort (71% vs. 50% vs. 12% in age-group 45-54, P < 0.001). Adjusted all-cause mean cost was lowest for MRgFUS ($19,763; 95% CI: $10,425-$38,694) followed by myomectomy ($20,407; 95% CI: $19,483-$21,381) and UAE ($25,019; 95% CI: $23,738-$26,376) but without statistical significance. Adjusted UF-related costs were also not significantly different between the three procedures. CONCLUSIONS: Adjusted all-cause and UF-related costs at one year were not significantly different between patients undergoing MRgFUS, myomectomy and UAE.

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