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Incidence and Variation of Discrepancies in Recording Chronic Conditions in Australian Hospital Administrative Data.

ABSTRACT: Diagnostic data routinely collected for hospital admitted patients and used for case-mix adjustment in care provider comparisons and reimbursement are prone to biases. We aim to measure discrepancies, variations and associated factors in recorded chronic morbidities for hospital admitted patients in New South Wales (NSW), Australia. Of all admissions between July 2010 and June 2014 in all NSW public and private acute hospitals, admissions with over 24 hours stay and one or more of the chronic conditions of diabetes, smoking, hepatitis, HIV, and hypertension were included. The incidence of a non-recorded chronic condition in an admission occurring after the first admission with a recorded chronic condition (index admission) was considered as a discrepancy. Poisson models were employed to (i) derive adjusted discrepancy incidence rates (IR) and rate ratios (IRR) accounting for patient, admission, comorbidity and hospital characteristics and (ii) quantify variation in rates among hospitals. The discrepancy incidence rate was highest for hypertension (51% of 262,664 admissions), followed by hepatitis (37% of 12,107), smoking (33% of 548,965), HIV (27% of 1500) and diabetes (19% of 228,687). Adjusted rates for all conditions declined over the four-year period; with the sharpest drop of over 80% for diabetes (47.7% in 2010 vs. 7.3% in 2014), and 20% to 55% for the other conditions. Discrepancies were more common in private hospitals and smaller public hospitals. Inter-hospital differences were responsible for 1% (HIV) to 9.4% (smoking) of variation in adjusted discrepancy incidences, with an increasing trend for diabetes and HIV. Chronic conditions are recorded inconsistently in hospital administrative datasets, and hospitals contribute to the discrepancies. Adjustment for patterns and stratification in risk adjustments; and furthermore longitudinal accumulation of clinical data at patient level, refinement of clinical coding systems and standardisation of comorbidity recording across hospitals would enhance accuracy of datasets and validity of case-mix adjustment.

SUBMITTER: Assareh H

PROVIDER: S-EPMC4726608 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Incidence and Variation of Discrepancies in Recording Chronic Conditions in Australian Hospital Administrative Data.

Assareh Hassan H Achat Helen M HM Stubbs Joanne M JM Guevarra Veth M VM Hill Kim K

PloS one 20160125 1

Diagnostic data routinely collected for hospital admitted patients and used for case-mix adjustment in care provider comparisons and reimbursement are prone to biases. We aim to measure discrepancies, variations and associated factors in recorded chronic morbidities for hospital admitted patients in New South Wales (NSW), Australia. Of all admissions between July 2010 and June 2014 in all NSW public and private acute hospitals, admissions with over 24 hours stay and one or more of the chronic co ...[more]

PMID: 26808428

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Project description:IntroductionThe incidence and prevalence of diabetes within a population are important public health metrics. Pharmaceutical administrative data may offer a resource that can contribute to quantifying these measures using the recorded signals derived from the drugs used to treat people with diabetes.ObjectiveTo estimate the longitudinal incidence and prevalence of drug treated (DT) diabetes in Australia utilising an Australian Pharmaceutical Benefits Scheme (PBS) dataset and compare estimates with community survey data for all diabetes reported in the Australian National Health Survey (NHS).MethodsPersons with DT diabetes were identified within the PBS dataset using assigned Anatomic Therapeutic Chemical codes for 'Drugs used in diabetes'. Prevalent persons with DT diabetes were determined by a single annual treatment, and incident cases from the earliest treatment with diabetes medications. Counts were aggregated by age group and utilised Australian national census data as a denominator to calculate diabetes disease frequencies for the period 2004-14. Comparison of PBS prevalence data was made with NHS surveys over equivalent years.ResultsThe age adjusted incidence of DT diabetes was 3.4/1000 in 2006 and increased to 3.8/1000 in 2011 and 5.1/1000 in 2014. Age adjusted prevalence of DT diabetes in Australia also rose from 26.7/1000 in 2006 to 32.1/1000 in 2011 and 42.1/1000 in 2014. DT diabetes prevalence estimates correlated with NHS estimates of self-reported diabetes prevalence across age groups and in 2014 was r = 0.987. However, PBS estimates of DT diabetes prevalence generally underestimated NHS values of self-reported diabetes in older age groups with mean percentage differences of -22% to -3%. In contrast, PBS data captured more younger persons with diabetes in comparison to NHS data. These differences were then used to adjust DT diabetes incidence rates to provide age specific estimates that could potentially reflect diabetes incidence estimates acquired by community survey.ConclusionsPBS data representing dispensed medications prescribed to persons with diabetes offers a perspective for the assessment of diabetes incidence and prevalence. PBS derived DT diabetes prevalence estimates correlate well with community survey estimates of self-reported diabetes, but underestimate NHS data in older age groups. Calibrated DT incidence estimates may potentially reflect community survey derived diabetes incidence estimates and may offer a method for longitudinal monitoring.

Project description:BackgroundChronic diseases are posing an increasing challenge to society, with the associated burden falling disproportionally on more deprived individuals and geographical areas. Although the existence of a socioeconomic health gradient is one of the main concerns of health policy across the world, health information systems commonly do not have reliable data to detect and monitor health inequalities and inequities. The objectives of this study were to measure the level of socioeconomic-related inequality in prevalence of chronic diseases and to investigate the extent and direction of inequities in health care provision.MethodsA dataset linking clinical and administrative information of the entire population living in the Basque Country, Spain (over 2 million individuals) was used to measure the prevalence of 52 chronic conditions and to quantify individual health care costs. We used a concentration-index approach to measure the extent and direction of inequality with respect to the deprivation of the area of residence of each individual.ResultsMost chronic diseases were found to be disproportionally concentrated among individuals living in more deprived areas, but the extent of the imbalance varies by type of disease and sex. Most of the variation in health care utilization was explained by morbidity burden. However, even after accounting for differences in morbidity, pro-poor horizontal inequity was present in specialized outpatient care, emergency department, prescription, and primary health care costs and this fact was more apparent in females than males; inpatient costs exhibited an equitable distribution in both sexes.ConclusionsAnalyses of comprehensive administrative clinical information at the individual level allow the socioeconomic gradient in chronic diseases and health care provision to be measured to a level of detail not possible using other sources. This frequently updated source of information can be exploited to monitor trends and evaluate the impact of policy reforms.

Project description:ContextMany of the publicly available health quality report cards are based on administrative data. ICD-9-CM codes in administrative data are not date stamped to distinguish between medical conditions present at the time of hospital admission and complications, which occur after hospital admission. Treating complications as preexisting conditions gives poor-performing hospitals "credit" for their complications and may cause some hospitals that are delivering low-quality care to be misclassified as average- or high-performing hospitals.ObjectiveTo determine whether hospital quality assessment based on administrative data is impacted by the inclusion of condition present at admission (CPAA) modifiers in administrative data as a date stamp indicator.Design, setting, and patientsRetrospective cohort study based on 648,866 inpatient admissions between 1998 and 2000 for coronary artery bypass graft (CABG) surgery, coronary angioplasty (PTCA), carotid endarterectomy (CEA), abdominal aortic aneurysm (AAA) repair, total hip replacement (THR), acute MI (AMI), and stroke using the California State Inpatient Database which includes CPAA modifiers. Hierarchical logistic regression was used to create separate condition-specific risk adjustment models. For each study population, one model was constructed using only secondary diagnoses present at admission based on the CPAA modifier: "date stamp" model. The second model was constructed using all secondary diagnoses, ignoring the information present in the CPAA modifier: the "no date stamp model." Hospital quality was assessed separately using the "date stamp" and the "no date stamp" risk-adjustment models.ResultsForty percent of the CABG hospitals, 33 percent of the PTCA hospitals, 40 percent of the THR hospitals, and 33 percent of the AMI hospitals identified as low-performance hospitals by the "date stamp" models were not classified as low-performance hospitals by the "no date stamp" models. Fifty percent of the CABG hospitals, 33 percent of the PTCA hospitals, 50 percent of the CEA hospitals, and 36 percent of the AMI hospitals identified as low-performance hospitals by the "no date stamp" models were not identified as low-performance hospitals by the "date stamp" models. The inclusion of the CPAA modifier had a minor impact on hospital quality assessment for AAA repair, stroke, and CEA.ConclusionThis study supports the hypothesis that the use of routine administrative data without date stamp information to construct hospital quality report cards may result in the mis-identification of hospital quality outliers. However, the CPAA modifier will need to be further validated before date stamped administrative data can be used as the basis for health quality report cards.

Project description:Social factors are recognized determinants of morbidity and mortality and also have an impact on use of medical services. The objective of this study was to assess the associations of educational attainment, social and financial resources, and migration factors with length of hospital stays for chronic conditions. In addition, the study investigated the role of comorbidity and discharge destination in mediating these associations. The study made use of nationwide inpatient data that was linked with Swiss census data. The study sample included n = 141,307 records of n = 92,623 inpatients aged 25 to 84 years, hospitalized between 2010 and 2016 for a chronic condition. Cross-classified multilevel models and mediation analysis were performed. Patients with upper secondary and compulsory education stayed longer in hospital compared to those with tertiary education (β 0.24 days, 95% CI 0.14-0.33; β 0.37, 95% CI 0.27-0.47, respectively) when taking into account demographic factors, main diagnosis and clustering on patient and hospital level. However, these effects were almost fully mediated by burden of comorbidity. The effect of living alone on length of stay (β 0.60 days, 95% CI 0.50-0.70) was partially mediated by both burden of comorbidities (33%) and discharge destination (30.4%). (Semi-) private insurance was associated with prolonged stays, but an inverse effect was observed for colon and breast cancer. Allophone patients had also prolonged hospital stays (β 0.34, 95% CI 0.13-0.55). Hospital stays could be a window of opportunity to discern patients who need additional time and support to better cope with everyday life after discharge, reducing the risks of future hospital stays. However, inpatient care in Switzerland seems to take into account rather obvious individual needs due to lack of immediate support at home, but not necessarily more hidden needs of patients with low health literacy and less resources to assert their interests within the health system.

Project description:BackgroundThe goal of regionalized perinatal care, specifically levels of maternal care, is to improve maternal outcomes through risk-appropriate obstetric care. Studies of levels of maternal care are limited by current approaches to identify a hospital's level of care, often relying on hospital self-reported data, which is expensive and challenging to collect and validate. The study objective was to develop an empiric approach to determine a hospital's level of maternal care using administrative data reflective of the patient care provided and apply this approach to describe the levels of maternal care available over time.MethodsRetrospective cohort study of mother-infant dyads who delivered in California, Missouri, and Pennsylvania hospitals from 2000 to 2009. Linked mother-infant administrative records with an infant born at 24-44 weeks' gestation and a birth weight of 400-8000 g were included. Using the American College of Obstetricians and Gynecologists and the Society for Maternal Fetal Medicine descriptions of levels of maternal care, four levels were classified based on the appropriate location of care for patients with specific medical or pregnancy conditions. Individual hospitals were assigned a level of maternal care annually based on the volume of patients who delivered reflective of the four classified levels as determined by International Classification of Diseases and Current Procedural Terminology.ResultsBased on the included 6,895,000 mother-infant dyads, the obstetric hospital levels of maternal care I, II, III and IV were identified. High-risk patients more frequently delivered in hospitals with higher level maternal care, accounting for 8.9, 10.9, 13.8, and 16.9% of deliveries in level I, II, III and IV hospitals, respectively. The total number of obstetric hospitals decreased over the study period, while the proportion of hospitals with high-level (level III or IV) maternal care increased. High-level hospitals were located in more densely populated areas.ConclusionIdentification of the level of maternal care, independent of hospital self-reported variables, is feasible using administrative data. This empiric approach, which accounts for changes in hospitals over time, is a valuable framework for perinatal researchers and other stakeholders to inexpensively identify measurable benefits of levels of maternal care and characterize where specific patient populations receive care.

Project description:ImportanceDespite the large health burden, reliable data on sepsis epidemiology are lacking; studies using International Statistical Classification of Diseases and Related Health Problems (ICD)-coded hospital discharge diagnosis for sepsis identification suffer from limited sensitivity. Also, ICD data do not allow investigation of underlying pathogens and antimicrobial resistance.ObjectivesTo generate reliable epidemiological estimates by linking data from a population-based database to a reference standard of clinical medical record review.Design, setting, and participantsThis was a retrospective, observational cohort study using a population-based administrative database including all acute care hospitals of the Scania region in Sweden in 2019 and 2020 to identify hospital-treated sepsis cases by ICD codes. From this database, clinical medical records were also selected for review within 6 strata defined by ICD discharge diagnosis (both with and without sepsis diagnosis). Data were analyzed from April to October 2022.Main outcomes and measuresHospital and population incidences of sepsis, case fatality, antimicrobial resistance, and temporal dynamics due to COVID-19 were assessed, as well as validity of ICD-10 case identification methods compared with the reference standard of clinical medical record review.ResultsOut of 295 531 hospitalizations in 2019 in the Scania region of Sweden, 997 patient medical records were reviewed, among which 457 had sepsis according to clinical criteria. Of the patients with clinical sepsis, 232 (51%) were female, and 357 (78%) had at least 1 comorbidity. The median (IQR) age of the cohort was 76 (67-85) years. The incidence of sepsis in hospitalized patients according to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria in 2019 was 4.1% (95% CI, 3.6-4.5) by medical record review. This corresponds to an annual incidence rate of 747 (95% CI, 663-832) patients with sepsis per 100 000 population. No significant increase in sepsis during the COVID-19 pandemic nor a decrease in sepsis incidence when excluding COVID-19 sepsis was observed. Few sepsis cases caused by pathogens with antimicrobial resistance were found. The validity of ICD-10-based case identification in administrative data was low.Conclusions and relevanceIn this cohort study of sepsis epidemiology, sepsis was a considerable burden to public health in Sweden. Supplying administrative data with information from clinical medical records can help to generate reliable data on sepsis epidemiology.

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Incidence and Variation of Discrepancies in Recording Chronic Conditions in Australian Hospital Administrative Data.

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Incidence and Variation of Discrepancies in Recording Chronic Conditions in Australian Hospital Administrative Data.

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