Comorbidity measures for use with administrative data pdf merge

Ppt calculating measures of comorbidity using administrative data powerpoint presentation free to view id. This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets methods. So if your comorbidity measures rely on the frequency. Studies describing methods to measure comorbidity in epidemiological studies related to. I really do not like the term administrative data, but i use it because it certainly connotes some common understanding of what we mean by data for workload. A comparison of charlson and elixhauser comorbidity measures to predict colorectal cancer survival using administrative health data jessica r. A modification of the elixhauser comorbidity measures into. Performances of comorbidity measures in healthcare related. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in california in 1992 n 1,779,167. These programs are applicable to the medical field for calculating measures of comorbidity using administrative data. The objective of this study was to compare the performance of three comorbidity measures using information from different data periods in predicting short.

We compared 4 previously published comorbidity measures developed for use with administrative data. The charlson index 2 consists of 19 comorbid conditions weighted according to the degree to which they predicted mortality among an inpatient cohort, then summed. Comparison of different comorbidity measures for use with administrative data in predicting short and. Comorbidity administrative data introduction there is increasing interest in the use of administrative databases for studying the outcomes of medical services. Data were obtained from the chronic condition data warehouse. This study investigated predictive performance of five comorbidity measures for populationbased. Data show that persons diagnosed with mood or anxiety disorders are about twice as likely to suffer also from a drug use disorder abuse or dependence compared with respondents in general. International consortium for health outcomes measurement. The development of a stata program to calculate published measures of comorbidity will be of value to researchers working with inpatient discharge data coded in icd9cm or icd10. This study used a large adminis trative data set to develop and test comorbidity measures that can be used to control for a broad array of patients underlying, preexisting condi tions in many types of studies. If data from several mutually exclusive sources eg, inpatient claims, outpatient claims are included in a regression model, this 30item comorbidity measure can quickly multiply to 60 or 90 individual variables and is only practical with a large administrative database. Articles up to march 18, 2011 were searched based on our predefined terms. The complexity of comorbidity data and its potential for creating unwieldy analyses has led to the development of summary comorbidity measures such as the charlson index 8, 9. Performances of comorbidity measures in healthcare related behaviors and outcomes in type 2 diabetes by huang tz ou a dissertation submitted in partial fulfillment of the requirements for the degree of doctor of philosophy social and administrative sciences in the university of michigan 2010 doctoral committee.

Comorbidity coding trends in hospital administrative databases. Pharmacy data provides information about medications, and there are some comorbidity measures and approaches that one could use using information from pharmacy data specifically for medications that might be provided for a specific condition, sort after as a marker. Failure to follow the data dictionary definitions will result in unreliable data. Hcup enables researchers, insurers, policymakers and others to study health care delivery and patient outcomes over time, and at the national, regional, state, and community levels. The use of charlson related expenditures did not result in improved mortality prediction. Organisation of data analyses and measuring of comorbidity. This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets. Developing and validating a novel multisource comorbidity.

Use of comorbidity scores for control of confounding in studies using. Comparison of the elixhauser and charlsondeyo methods of comorbidity measurement in administrative data article in medical care 424. Therefore, comorbidity adjustment based on administrative data with all its limitations is here to stay. Healthcare cost and utilization project hcup agency.

For control of baseline differences in these observational data, one major issue is to find a comorbidity measure with better performance 19. Methods an index of 34 variables measured from inpatient diagnoses and outpatient drug prescriptions within 2 years. A comprehensive set of 30 comorbidity measures was developed. Comparing measures of multimorbidity to predict outcomes in. To develop and validate optimised measures of comorbidity using these data for patients with cancer, to develop, and compare more simplified measures against the optimised measures. Previous studies have found a suboptimal correlation between the comorbidities listed in the clinical record and the comorbidities coded in. Comparison of different comorbidity measures for use with administrative data in predicting short and longterm mortality.

Data on the prevalence of comorbid mental disorders among drug users in european countries are heterogeneous, although prevalence rates are higher in drug users than in. The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Calculating measures of comorbidity using administrative data posted on june 27, 2014 by vicki no comments v the development of a stata program to calculate published measures of comorbidity will be of value to researchers working with inpatient discharge data coded in icd9. Jun 27, 2014 calculating measures of comorbidity using administrative data posted on june 27, 2014 by vicki no comments v the development of a stata program to calculate published measures of comorbidity will be of value to researchers working with inpatient discharge data coded in icd9cm or icd10. We have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The wiki platform enables collective improvements and shared learning. Comorbidity measures for use with administrative data. Comorbidity of substance use and mental disorders in europe 8 mental disorder is detected, a definitive diagnosis and adequate treatment must be arranged. Gridenabled measures gem is a webbased database using a wiki platform that provides researchers and program evaluators with standard measures, tools, and databases. Cci models perform less well in population subgroups with higher underlying mortality risks based on age and chronic conditions.

The adobe flash plugin is needed to view this content. Evaluating comorbidity scores based on health service. New morbidity and comorbidity scores based on the structure of the. Data analysts, researchers and decision makers should always be aware of possible data quality bias, such as completeness, when using administrative databases. An administrative data merging solution for dealing with. The same is true for those diagnosed with an antisocial syndrome. Cancer survival is related to features of the primary malignancy and concurrent presence of. Your input data need to follow the software data elements and coding conventions described in the software documentation sas qi or winqi. Comorbidity measures for use with administrative data meta. Each disease network is generated by merging the individual. Comparing measures of multimorbidity to predict outcomes.

Administrative claims data is coded manually by nonclinical administrative personnel, and thus the legitimacy of administrative claims data has been called into question. Objective to develop and validate a novel comorbidity score multisource comorbidity score mcs predictive of mortality, hospital admissions and healthcare costs using multiple source information from the administrative italian national health system nhs databases. The objective of this study was to compare the use of different comorbidity measures to predict future healthcare utilization and expenditures for diabetic patients. When i use the term administrative data im referring to both va workload data and claims data, which includes a lot of information that can be more than administrative, including some clinical information.

An administrative data merging solution for dealing with missing data in a clinical registry. Obtaining valid inferences from such databases depends in part on being able to stratify or otherwise control for varying levels of disease severity and comorbid illnesses. In the publication comorbidity measures for use with administrative data by elixhauser et al. Comparison of different comorbidity measures for use with administrative data in predicting short and longterm mortality yutseng chu, 1 yeeyung ng, 2, 3 and shiaochi wu 1 1 institute of health and welfare policy, school of medicine, national yangming university, taipei, taiwan. Among the different indexes available to control for comorbid conditions, the most frequently used is the charlson index, which is a weighted score of 17 comorbidities that was initially used to predict inhospital and 1year mortality. The validity of using administratively coded comorbidity and. Here, we describe the process of translating our data merging solution to icd10, and then validating its performance. Ahrq multiple chronic conditions research network data. Administrative databases are increasingly used in health services research, epidemiologic research, and outcome studies. This document describes the software that creates the comorbidity measures reported by elixhauser et al. This study investigated predictive performance of five comorbidity measures for population. Calculating measures of comorbidity using administrative data. Issn 23149264 comorbidity of substance use and mental. Expanding the infrastructure for research deliverable by lix et al.

Each comorbidity category has an associated weight, based on the adjusted risk of. If researchers use the same measures, then eventually they can share data across projects. Comorbidity was associated with poorer survival but the impact varied by. We also developed a new comorbidity index by assigning studyspecific weights to the original charlson comorbidity variables. Some sources of comorbidity information in administrative data.

Pdf comparison of different comorbidity measures for use. Elixhauser comorbidity software assigns variables that identify comorbidities in hospital discharge records using the diagnosis coding of icd9cm international classification of diseases, ninth edition, clinical modifications. Hypertension combine uncomplicated and complicated. The index has since been adapted into several 17item weighted indexes for use with administrative data. The method involves merging registry data to corresponding icd9cm administrative data to fill in missing data holes. Adapting a clinical comorbidity index for use with icd9cm. This was a retrospective study that included 8,704 diabetic patients enrolled continuously for three years in the department of defense tricare program. The charlson comorbidity index is a method for measuring patient comorbidity based on the international classification of diseases icd diagnoses codes of individual patients using administrative data, such as hospital abstracts data. Remember that even if you are using the nationwide inpatient sample nis, you need to format the data for use with the ahrq quality indicators software. Similar comorbidities that, when separate, were weakly related to the outcome measures, but, when merged, had a stronger relationship were combined. Consequently, clinicians, researchers and managers are using different comorbidity concepts when faced with cooccurring chronic diseases. Performance of comorbidity adjustment measures to predict.

The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and. Evidence from different population and datasets are needed for the generalizability of comparative performance 6,10. Comparison of different comorbidity measures for use with. May 27, 2010 it is important to find a comorbidity measure with better performance for use with administrative data. The 2 icd9cm coding adaptations assigned identical charlson comorbidity scores to 90% of cases, and specific comorbidities were largely found in the same cases kappa values of 0. Danielle a southern, colleen m norris4, hude quan, fiona m shrive, p diane galbraith1,3, karin humphries5,6, min gao5,6, merril l knudtson2, william a ghali1,2,3 for the approach investigators. The validity of using administratively coded comorbidity. The simplest comorbidity score is also the most widely used measure of confounding in epidemiology. Keywords icd9cm comorbidity coding and classification administrative data data quality.

Hcup is the nations most comprehensive source of hospital data, including information on inpatient care, ambulatory care, and emergency department visits. Development of a comorbidity index using physician claims data. Introduction this concept identifies and briefly describes the measures of comorbidity investigated in the cancer data linkage in manitoba. In adjusted models, presence of a mental condition was associated with a 0.

Searching for an improved clinical comorbidity index for. Evidence from different population and datasets are needed for the generalizability of comparative performance 6, 10. Developing new comorbidity indices for cancer populations. Mental comorbidity and quality of diabetes care under. Regardless of the data source, the majority of comorbidity measures are summary or aggregate measures. The performance of comorbidity measures for predicting mortality in chronic disease populations and using icd9 diagnosis codes in administrative health data has been investigated in several studies, but less is known about predictive performance with icd10 data and for other health outcomes. The report includes the technical documentation for the comorbidity software and describes three topics. A modification of the elixhauser comorbidity measures into a. Applying comorbidity measures using va and medicare data. D overview of data sources for measures of health care quality for children and adolescents. It is possible to use administrative data to identify new colorectal cancer patients. Outcome measures were those commonly available in administrative data. Comorbidity measures for use with administrative data citeseerx. Comparison of the elixhauser and charlsondeyo methods of.

The various comorbidity instruments can be grouped into three distinct categories according to the source of the comorbid health information. Adapting a clinical comorbidity index for use with icd9. Although summary measures are important in quantifying the effect of an overall disease burden on outcomes, the greatest liability of summary measures is that they do little to advance the science underpinning comorbidities. As our third measure of multimorbidity we used a count of expanded diagnosis clusters edcs. In 2015, a team of hcup researchers and statisticians used a large analysis file built from allpayer hospital administrative data from the hcup state inpatient databases sid from 18 states in 2011 and 2012 to create two indices based on the elixhauser comorbidity measures designed to predict inhospital mortality and 30day readmission in administrative data. A modification of the elixhauser comorbidity measures into a point system for hospital death using administrative data. Because research using administrative datasets often examines re. A comparison of comorbidity measurements to predict. The next three multimorbidity measures were constructed using output from the john hopkins university acg casemix system, which was developed using administrative data in the usa. In search of the perfect comorbidity measure for use with. Searching for an improved clinical comorbidity index for use. Full text utilizing national patientregister data to. Administrative data were found to be adequate for measuring comorbidity in cancer populations.