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BACKGROUND: Previous studies found that documentation of comorbidities differed when Veterans received care within versus outside Veterans Health Administration (VHA). Changes to medical center funding, increased attention to performance reporting, and expansion of Clinical Documentation Improvement programs, however, may have caused coding in VHA to change. METHODS: Using repeated cross-sectional data, we compared Elixhauser-van Walraven scores and Medicare Severity Diagnosis Related Group (DRG) severity levels for Veterans admissions across settings and payers over time, utilizing a linkage of VHA and all-payer discharge data for 2012-2017 in seven US states. To minimize selection bias, we analyzed records for Veterans admitted to both VHA and non-VHA hospitals in the same year. Using generalized linear models, we adjusted for patient and hospital characteristics. RESULTS: Following adjustment, VHA admissions consistently had the lowest predicted mean comorbidity scores (4.44 (95% CI 4.34-4.55)) and lowest probability of using the most severe DRG (22.1% (95% CI 21.4%-22.8%)). In contrast, Medicare-covered admissions had the highest predicted mean comorbidity score (5.71 (95% CI 5.56-5.85)) and highest probability of using the top DRG (35.3% (95% CI 34.2%-36.4%)). CONCLUSIONS: More effective strategies may be needed to improve VHA documentation, and current risk-adjusted comparisons should account for differences in coding intensity.

Abstract Background Universal health visiting has been a cornerstone of preventative healthcare for children in the United Kingdom (UK) for over 100 years. In 2016, Scotland introduced a new Universal Health Visiting Pathway (UHVP), involving a greater number of contacts with a particular emphasis on the first year, visits within the home setting, and rigorous developmental assessment conducted by a qualified Health Visitor. To evaluate the UHVP, an outcome indicator framework was developed using routine administrative data. This paper sets out the development of these indicators. Methods A logic model was produced with stakeholders to define the group of outcomes, before further refining and aligning of the measures through discussions with stakeholders and inspection of data. Power calculations were carried out and initial data described for the chosen indicators. Results Eighteen indicators were selected across eight outcome areas: parental smoking, breastfeeding, immunisations, dental health, developmental concerns, obesity, accidents and injuries, and child protection interventions. Data quality was mixed. Coverage of reviews was high; over 90% of children received key reviews. Individual item completion was more variable: 92.2% had breastfeeding data at 6–8 weeks, whilst 63.2% had BMI recorded at 27–30 months. Prevalence also varied greatly, from 1.3% of children’s names being on the Child Protection register for over six months by age three, to 93.6% having received all immunisations by age two. Conclusions Home visiting services play a key role in ensuring children and families have the right support to enable the best start in life. As these programmes evolve, it is crucial to understand whether changes lead to improvements in child outcomes. This paper describes a set of indicators using routinely-collected data, lessening additional burden on participants, and reducing response bias which may be apparent in other forms of evaluation. Further research is needed to explore the transferability of this indicator framework to other settings.

Abstract Background Previous studies found that documentation of comorbidities differed when Veterans received care within versus outside Veterans Health Administration (VHA). Changes to medical center funding, increased attention to performance reporting, and expansion of Clinical Documentation Improvement programs, however, may have caused coding in VHA to change. Methods Using repeated cross-sectional data, we compared Elixhauser-van Walraven scores and Medicare Severity Diagnosis Related Group (DRG) severity levels for Veterans’ admissions across settings and payers over time, utilizing a linkage of VHA and all-payer discharge data for 2012–2017 in seven US states. To minimize selection bias, we analyzed records for Veterans admitted to both VHA and non-VHA hospitals in the same year. Using generalized linear models, we adjusted for patient and hospital characteristics. Results Following adjustment, VHA admissions consistently had the lowest predicted mean comorbidity scores (4.44 (95% CI 4.34–4.55)) and lowest probability of using the most severe DRG (22.1% (95% CI 21.4%-22.8%)). In contrast, Medicare-covered admissions had the highest predicted mean comorbidity score (5.71 (95% CI 5.56–5.85)) and highest probability of using the top DRG (35.3% (95% CI 34.2%-36.4%)). Conclusions More effective strategies may be needed to improve VHA documentation, and current risk-adjusted comparisons should account for differences in coding intensity.

Abstract Background In-hospital mortality from acute myocardial infarction (AMI) is widely used in international comparisons as an indicator of health system performance. Because of the high risk of early death after AMI, international comparisons may be biased by differences in the recording of early death cases in hospital inpatient data. This study examined whether differences in the recording of early deaths affect international comparisons of AMI in-hospital mortality by using the example of Germany and the United States, and explored approaches to address this issue. Methods The German Diagnosis-Related Groups Statistics (DRG Statistics), the U.S. National Inpatient Sample (NIS) and the U.S. Nationwide Emergency Department Sample (NEDS) were analysed from 2014 to 2019. Cases with treatment for AMI were identified in German and U.S. inpatient data. AMI deaths occurring in the emergency department (ED) without inpatient admission were extracted from NEDS data. 30-day in-hospital mortality figures were calculated according to the OECD indicator definition (unlinked data) and modified by including ED deaths, or excluding all same-day cases. Results German age-and-sex standardized 30-day in-hospital mortality was substantially higher compared to the U.S. (in 2019, 7.3% vs. 4.6%). The ratio of German vs. U.S. mortality was 1.6. After inclusion of ED deaths in U.S. data this ratio declined to 1.4. Exclusion of same-day cases in German and U.S. data led to a similar ratio. Conclusions While short-duration treatments due to early death are generally recorded in German inpatient data, in U.S. inpatient data those cases are partially missing. Excluding cases with short-duration treatment from the calculation of mortality indicators could be a feasible approach to account for differences in the recording of early deaths, that might be existent in other countries as well.

Background: Universal health visiting has been a cornerstone of preventative healthcare for children in the United Kingdom (UK) for over 100 years. In 2016, Scotland introduced a new Universal Health Visiting Pathway (UHVP), involving a greater number of contacts with a particular emphasis on the first year, visits within the home setting, and rigorous developmental assessment conducted by a qualified Health Visitor. To evaluate the UHVP, an outcome indicator framework was developed using routine administrative data. This paper sets out the development of these indicators. Methods: A logic model was produced with stakeholders to define the group of outcomes, before further refining and aligning of the measures through discussions with stakeholders and inspection of data. Power calculations were carried out and initial data described for the chosen indicators. Results: Eighteen indicators were selected across eight outcome areas: parental smoking, breastfeeding, immunisations, dental health, developmental concerns, obesity, accidents and injuries, and child protection interventions. Data quality was mixed. Coverage of reviews was high; over 90% of children received key reviews. Individual item completion was more variable: 92.2% had breastfeeding data at 6–8 weeks, whilst 63.2% had BMI recorded at 27–30 months. Prevalence also varied greatly, from 1.3% of children's names being on the Child Protection register for over six months by age three, to 93.6% having received all immunisations by age two. Conclusions: Home visiting services play a key role in ensuring children and families have the right support to enable the best start in life. As these programmes evolve, it is crucial to understand whether changes lead to improvements in child outcomes. This paper describes a set of indicators using routinely-collected data, lessening additional burden on participants, and reducing response bias which may be apparent in other forms of evaluation. Further research is needed to explore the transferability of this indicator framework to other settings. [ABSTRACT FROM AUTHOR]

Background: In-hospital mortality from acute myocardial infarction (AMI) is widely used in international comparisons as an indicator of health system performance. Because of the high risk of early death after AMI, international comparisons may be biased by differences in the recording of early death cases in hospital inpatient data. This study examined whether differences in the recording of early deaths affect international comparisons of AMI in-hospital mortality by using the example of Germany and the United States, and explored approaches to address this issue. Methods: The German Diagnosis-Related Groups Statistics (DRG Statistics), the U.S. National Inpatient Sample (NIS) and the U.S. Nationwide Emergency Department Sample (NEDS) were analysed from 2014 to 2019. Cases with treatment for AMI were identified in German and U.S. inpatient data. AMI deaths occurring in the emergency department (ED) without inpatient admission were extracted from NEDS data. 30-day in-hospital mortality figures were calculated according to the OECD indicator definition (unlinked data) and modified by including ED deaths, or excluding all same-day cases. Results: German age-and-sex standardized 30-day in-hospital mortality was substantially higher compared to the U.S. (in 2019, 7.3% vs. 4.6%). The ratio of German vs. U.S. mortality was 1.6. After inclusion of ED deaths in U.S. data this ratio declined to 1.4. Exclusion of same-day cases in German and U.S. data led to a similar ratio. Conclusions: While short-duration treatments due to early death are generally recorded in German inpatient data, in U.S. inpatient data those cases are partially missing. Excluding cases with short-duration treatment from the calculation of mortality indicators could be a feasible approach to account for differences in the recording of early deaths, that might be existent in other countries as well. [ABSTRACT FROM AUTHOR]

Abstract Background Data on resource use are frequently required for healthcare assessments. Studies on healthcare utilization (HCU) in individuals with mental disorders have analyzed both self-reports and administrative data. Source of data may affect the quality of analysis and compromise the accuracy of results. We sought to ascertain the degree of agreement between self-reports and statutory health insurance (SHI) fund claims data from patients with mental disorders. Methods Claims data from six German SHI and self-reports were obtained along with a cost-effectiveness analysis performed as a part of a controlled prospective multicenter cohort study conducted in 18 psychiatric hospitals in Germany (PsychCare), including patients with pre-defined psychiatric disorders. Self-reports were collected using the German adaption of the Client Sociodemographic and Service Receipt Inventory (CSSRI) questionnaire with a 6-month recall period. Data linkage was performed using a unique pseudonymized identifier. Missing responses were coded as non-use for all analyses. HCU was calculated for inpatient and outpatient care, day-care services, home treatment, and pharmaceuticals. Concordance was measured using Cohen’s Kappa (κ) and intraclass correlation coefficient (ICC). Regression approaches were used to investigate the effect of independent variables on the agreements. Results In total 274 participants (mean age 47.8 [SD = 14.2] years; 47.08% women) were included in the analysis. No significant differences were observed between the linked and unlinked patients in terms of baseline characteristics. Total agreements values were 63.9% (κ = 0.03; PABAK = 0.28) for outpatient contacts, 69.3% (κ = 0.25; PABAK = 0.39) for medication use, 81.0% (κ = 0.56; PABAK = 0.62) for inpatient days and 86.1% (κ = 0.67; PABAK = 0.72) for day-care services. There was varied quantitative agreement between data sources, with the poorest agreement for outpatient care (ICC [95% CI] = 0.22 [0.10–0.33]) and the best for psychiatric day-care services (ICC [95% CI] = 0.72 [0.66–0.78]). Marital status and time since first treatment positively affected the chance of agreement on utilization of outpatient services. Conclusions Although there were high levels of absolute agreement, the measures of concordance between administrative records and self-reports were generally minimal to moderate. Healthcare investigations should consider using linked or at least different data sources to estimate HCU for specific utilization areas, where unbiased information can be expected. Trial registration This study was part of the multi-center controlled PsychCare trial (German Clinical Trials Register No. DRKS00022535; Date of registration: 2020–10-02).

Background: Data on resource use are frequently required for healthcare assessments. Studies on healthcare utilization (HCU) in individuals with mental disorders have analyzed both self-reports and administrative data. Source of data may affect the quality of analysis and compromise the accuracy of results. We sought to ascertain the degree of agreement between self-reports and statutory health insurance (SHI) fund claims data from patients with mental disorders. Methods: Claims data from six German SHI and self-reports were obtained along with a cost-effectiveness analysis performed as a part of a controlled prospective multicenter cohort study conducted in 18 psychiatric hospitals in Germany (PsychCare), including patients with pre-defined psychiatric disorders. Self-reports were collected using the German adaption of the Client Sociodemographic and Service Receipt Inventory (CSSRI) questionnaire with a 6-month recall period. Data linkage was performed using a unique pseudonymized identifier. Missing responses were coded as non-use for all analyses. HCU was calculated for inpatient and outpatient care, day-care services, home treatment, and pharmaceuticals. Concordance was measured using Cohen's Kappa (κ) and intraclass correlation coefficient (ICC). Regression approaches were used to investigate the effect of independent variables on the agreements. Results: In total 274 participants (mean age 47.8 [SD = 14.2] years; 47.08% women) were included in the analysis. No significant differences were observed between the linked and unlinked patients in terms of baseline characteristics. Total agreements values were 63.9% (κ = 0.03; PABAK = 0.28) for outpatient contacts, 69.3% (κ = 0.25; PABAK = 0.39) for medication use, 81.0% (κ = 0.56; PABAK = 0.62) for inpatient days and 86.1% (κ = 0.67; PABAK = 0.72) for day-care services. There was varied quantitative agreement between data sources, with the poorest agreement for outpatient care (ICC [95% CI] = 0.22 [0.10–0.33]) and the best for psychiatric day-care services (ICC [95% CI] = 0.72 [0.66–0.78]). Marital status and time since first treatment positively affected the chance of agreement on utilization of outpatient services. Conclusions: Although there were high levels of absolute agreement, the measures of concordance between administrative records and self-reports were generally minimal to moderate. Healthcare investigations should consider using linked or at least different data sources to estimate HCU for specific utilization areas, where unbiased information can be expected. Trial registration: This study was part of the multi-center controlled PsychCare trial (German Clinical Trials Register No. DRKS00022535; Date of registration: 2020–10-02). [ABSTRACT FROM AUTHOR]

Abstract Background The period after release from prison can be challenging, especially due to a higher risk of morbidity and mortality despite commonly increased use of healthcare services. However, little is known about the quality of the healthcare offered to this population, which limits the possibility of addressing this important health inequity. This study characterised multimorbidity and investigated the relationship between multimorbidity and quality of primary healthcare in adults within 2 years after release from prison. Methods This was a prospective cohort study of 1046 participants of a service brokerage intervention after release from prison between August 2008 and July 2010 in Queensland, Australia. Participants had their baseline survey and clinical data linked prospectively with their medical, correctional and death records. Multimorbidity was ascertained using the Cumulative Illness Rating Scale and classified into three categories: none, moderate (morbidity in 2–3 domains) and complex (morbidity in 4 or more domains). Outcomes were Usual Provider Continuity Index (UPCI), Continuity of Care (COC) Index, and having at least one extended primary care consultation (> 20 minutes). Descriptive statistics and logistic regression were used in the analyses. Results Multimorbidity was present for 761 (73%) participants, being more prevalent among females (85%) than males (69%), p

Abstract Background and purpose Studies of carotid endarterectomy (CEA) require stratification by symptomatic vs asymptomatic status because of marked differences in benefits and harms. In administrative datasets, this classification has been done using hospital discharge diagnosis codes of uncertain accuracy. This study aims to develop and evaluate algorithms for classifying symptomatic status using hospital discharge and physician claims data. Methods A single center’s administrative database was used to assemble a retrospective cohort of participants with CEA. Symptomatic status was ascertained by chart review prior to linkage with physician claims and hospital discharge data. Accuracy of rule-based classification by discharge diagnosis codes was measured by sensitivity and specificity. Elastic net logistic regression and random forest models combining physician claims and discharge data were generated from the training set and assessed in a test set of final year participants. Models were compared to rule-based classification using sensitivity at fixed specificity. Results We identified 971 participants undergoing CEA at the Vancouver General Hospital (Vancouver, Canada) between January 1, 2008 and December 31, 2016. Of these, 729 met inclusion/exclusion criteria (n = 615 training, n = 114 test). Classification of symptomatic status using hospital discharge diagnosis codes was 32.8% (95% CI 29–37%) sensitive and 98.6% specific (96–100%). At matched 98.6% specificity, models that incorporated physician claims data were significantly more sensitive: elastic net 69.4% (59–82%) and random forest 78.8% (69–88%). Conclusion Discharge diagnoses were specific but insensitive for the classification of CEA symptomatic status. Elastic net and random forest machine learning algorithms that included physician claims data were sensitive and specific, and are likely an improvement over current state of classification by discharge diagnosis alone.

Abstract Background Researchers often use survey data to study the effect of health and social variables on physician use, but how self-reported physician use compares to administrative data, the gold standard, in particular within the context of multimorbidity and functional limitations remains unclear. We examine whether multimorbidity and functional limitations are related to agreement between self-reported and administrative data for physician use. Methods Cross-sectional data from 52,854 Ontario participants of the Canadian Community Health Survey linked to administrative data were used to assess agreement on physician use. The number of general practitioner (GP) and specialist visits in the previous year was assessed using both data sources; multimorbidity and functional limitation were from self-report. Results Fewer participants self-reported GP visits (84.8%) compared to administrative data (89.1%), but more self-reported specialist visits (69.2% vs. 64.9%). Sensitivity was higher for GP visits (≥90% for all multimorbidity levels) compared to specialist visits (approximately 75% for 0 to 90% for 4+ chronic conditions). Specificity started higher for GP than specialist visits but decreased more swiftly with multimorbidity level; in both cases, specificity levels fell below 50%. Functional limitations, age and sex did not impact the patterns of sensitivity and specificity seen across level of multimorbidity. Conclusions Countries around the world collect health surveys to inform health policy and planning, but the extent to which these are linked with administrative, or similar, data are limited. Our study illustrates the potential for misclassification of physician use in self-report data and the need for sensitivity analyses or other corrections.

Background: The period after release from prison can be challenging, especially due to a higher risk of morbidity and mortality despite commonly increased use of healthcare services. However, little is known about the quality of the healthcare offered to this population, which limits the possibility of addressing this important health inequity. This study characterised multimorbidity and investigated the relationship between multimorbidity and quality of primary healthcare in adults within 2 years after release from prison.Methods: This was a prospective cohort study of 1046 participants of a service brokerage intervention after release from prison between August 2008 and July 2010 in Queensland, Australia. Participants had their baseline survey and clinical data linked prospectively with their medical, correctional and death records. Multimorbidity was ascertained using the Cumulative Illness Rating Scale and classified into three categories: none, moderate (morbidity in 2-3 domains) and complex (morbidity in 4 or more domains). Outcomes were Usual Provider Continuity Index (UPCI), Continuity of Care (COC) Index, and having at least one extended primary care consultation (> 20 minutes). Descriptive statistics and logistic regression were used in the analyses.Results: Multimorbidity was present for 761 (73%) participants, being more prevalent among females (85%) than males (69%), p < 0.001. Moderate multimorbidity was not associated with UPCI or COC, but was associated with having at least one long consultation (AOR = 1.64; 95% CI:1.14-2.39), after adjusting for covariates. Complex multimorbidity was positively associated with all outcomes in the adjusted models. Indigenous status was negatively associated with UPCI (AOR = 0.54; 95% CI: 0.37-0.80) and COC (AOR = 0.53; 95% CI: 0.36-0.77), and people younger than 25 years were at 36% lower odds (AOR = 0.64; 95% CI: 0.44-0.93) of having a long consultation than the middle-aged group (25-44 years) in the adjusted models.Conclusion: Moderate multimorbidity was associated with having at least one extended primary care consultation, but not with adequate continuity of care, for adults within 2 years of being released from prison. Nearly half of those with complex multimorbidity did not receive adequate continuity of care. The quality of primary care is inadequate for a large proportion of adults released from prison, constituting an important and actionable health inequity. [ABSTRACT FROM AUTHOR]

Abstract Background Switzerland, with its decentralized health system, has seen the emergence of a variety of care models to meet the complex needs of asylum seekers. A network of public and private providers was designed in the canton Vaud, in which a nurse-led team acts as a first contact point to the health system and provides health checks, preventive care, and health education to this population. In addition, the service plays a case management role for more complex and vulnerable patients. While the network has been examined from a clinical angle, we provide the first descriptive evidence on the care and cost trajectories of asylum seekers in the canton. Methods We used routinely collected administrative, patient-level data in a Swiss region responsible for 10% of the asylum seekers in the country. We extracted data on all asylum seekers aged 18 or older who entered the network between 2012 and 2015. The data covered all healthcare costs during the period until they left the network, either because they were granted residence, they left the country, or until 31 December 2018. We estimated random effects regression models for costs and consultations within and outside the network for each month of stay in the network. We investigated language barriers in access to care by stratifying the analysis between patients who spoke one of the official Swiss languages or English and patients who did not speak any of these languages. Principal findings We found that both overall health care costs and contacts with the nurse-led team were relatively high during the first year of stay. Asylum seekers then progressively integrated into the regular health system. Individuals who did not speak the language generally had more contacts with the network and fewer contacts outside. Conclusions In this exploratory study, we observe a transition from nurse-led specific care with frequent contacts to care in the regular health system. This leads us to generate the hypothesis that a nurse-led, patient-centered care network for asylum seekers can play an important role in providing primary care during the first year after their arrival and can subsequently help them navigate autonomously within the conventional healthcare system.

Background: Research findings on the association between outpatient service use and emergency department (ED) visits for mental and substance use disorders (MSUDs) are mixed and may differ by disorder type.Methods: We used population-based linked administrative data in British Columbia, Canada to examine associations between outpatient primary care and psychiatry service use and ED visits among people ages 15 and older, comparing across people treated for three disorder categories: common mental disorders (MDs) (depressive, anxiety, and/or post-traumatic stress disorders), serious MDs (schizophrenia spectrum and/or bipolar disorders), and substance use disorders (SUDs) in 2016/7. We used hurdle models to examine the association between outpatient service use and odds of any ED visit for MSUDs as well count of ED visits for MSUDs, stratified by cohort in 2017/8.Results: Having had one or more MSUD-related primary care visit was associated with lower odds of any ED visit among people treated for common MDs and SUDs but not people treated for serious MDs. Continuity of primary care was associated with slightly lower ED use in all cohorts. One or more outpatient psychiatrist visits was associated with lower odds of ED visits among people treated for serious MDs and SUDs, but not among people with common MDs.Conclusion: Findings highlight the importance of expanded access to outpatient specialist mental health services, particularly for people with serious MDs and SUDs, and collaborative models that can support primary care providers treating people with MSUDs. [ABSTRACT FROM AUTHOR]

Background and Purpose: Studies of carotid endarterectomy (CEA) require stratification by symptomatic vs asymptomatic status because of marked differences in benefits and harms. In administrative datasets, this classification has been done using hospital discharge diagnosis codes of uncertain accuracy. This study aims to develop and evaluate algorithms for classifying symptomatic status using hospital discharge and physician claims data.Methods: A single center's administrative database was used to assemble a retrospective cohort of participants with CEA. Symptomatic status was ascertained by chart review prior to linkage with physician claims and hospital discharge data. Accuracy of rule-based classification by discharge diagnosis codes was measured by sensitivity and specificity. Elastic net logistic regression and random forest models combining physician claims and discharge data were generated from the training set and assessed in a test set of final year participants. Models were compared to rule-based classification using sensitivity at fixed specificity.Results: We identified 971 participants undergoing CEA at the Vancouver General Hospital (Vancouver, Canada) between January 1, 2008 and December 31, 2016. Of these, 729 met inclusion/exclusion criteria (n = 615 training, n = 114 test). Classification of symptomatic status using hospital discharge diagnosis codes was 32.8% (95% CI 29-37%) sensitive and 98.6% specific (96-100%). At matched 98.6% specificity, models that incorporated physician claims data were significantly more sensitive: elastic net 69.4% (59-82%) and random forest 78.8% (69-88%).Conclusion: Discharge diagnoses were specific but insensitive for the classification of CEA symptomatic status. Elastic net and random forest machine learning algorithms that included physician claims data were sensitive and specific, and are likely an improvement over current state of classification by discharge diagnosis alone. [ABSTRACT FROM AUTHOR]

Background: Researchers often use survey data to study the effect of health and social variables on physician use, but how self-reported physician use compares to administrative data, the gold standard, in particular within the context of multimorbidity and functional limitations remains unclear. We examine whether multimorbidity and functional limitations are related to agreement between self-reported and administrative data for physician use.Methods: Cross-sectional data from 52,854 Ontario participants of the Canadian Community Health Survey linked to administrative data were used to assess agreement on physician use. The number of general practitioner (GP) and specialist visits in the previous year was assessed using both data sources; multimorbidity and functional limitation were from self-report.Results: Fewer participants self-reported GP visits (84.8%) compared to administrative data (89.1%), but more self-reported specialist visits (69.2% vs. 64.9%). Sensitivity was higher for GP visits (≥90% for all multimorbidity levels) compared to specialist visits (approximately 75% for 0 to 90% for 4+ chronic conditions). Specificity started higher for GP than specialist visits but decreased more swiftly with multimorbidity level; in both cases, specificity levels fell below 50%. Functional limitations, age and sex did not impact the patterns of sensitivity and specificity seen across level of multimorbidity.Conclusions: Countries around the world collect health surveys to inform health policy and planning, but the extent to which these are linked with administrative, or similar, data are limited. Our study illustrates the potential for misclassification of physician use in self-report data and the need for sensitivity analyses or other corrections. [ABSTRACT FROM AUTHOR]

Abstract Background The look-back period is needed to define baseline population for estimating incidence. However, short look-back period is known to overestimate incidence of diseases misclassifying prevalent cases to incident cases. The purpose of this study is to evaluate the impact of the various length of look-back period on the observed incidences of uterine leiomyoma, endometriosis and adenomyosis, and to estimate true incidences considering the misclassification errors in the longitudinal administrative data in Korea. Methods A total of 319,608 women between 15 to 54 years of age in 2002 were selected from Korea National Health Insurance Services (KNHIS) cohort database. In order to minimize misclassification bias incurred when applying various length of look-back period, we used 11 years of claim data to estimate the incidence by equally setting the look-back period to 11 years for each year using prediction model. The association between the year of diagnosis and the number of prevalent cases with the misclassification rates by each look-back period was investigated. Based on the findings, prediction models on the proportion of misclassified incident cases were developed using multiple linear regression. Results The proportion of misclassified incident cases of uterine leiomyoma, endometriosis and adenomyosis were 32.8, 10.4 and 13.6% respectively for the one-year look-back period in 2003. These numbers decreased to 6.3% in uterine leiomyoma and − 0.8% in both endometriosis and adenomyosis using all available look-back periods (11 years) in 2013. Conclusion This study demonstrates approaches for estimating incidences considering the different proportion of misclassified cases for various length of look-back period. Although the prediction model used for estimation showed strong R-squared values, follow-up studies are required for validation of the study results.

Abstract Background Most studies on the physician code creep (i.e., changes in case mix record-keeping practices to improve reimbursement) have focused on episodes (inpatient hospitalizations or outpatient procedures). Little is known regarding changes in diagnostic coding practices for better reimbursement among a fixed cohort of patients with chronic diseases. Methods To examine whether physicians in tertiary medical centers changed their coding practices after the initiation of the Outpatient Volume Control Program (OVCP) in Taiwan, we conducted a retrospective observational study of four patient cohorts (two interventions and two controls) from January 2016 to September 2017 in Taiwan. The main outcomes were the number of outpatient visits with four coding practices: 1) OVCP monitoring code recorded as primary diagnosis; 2) OVCP monitoring code recorded as secondary diagnosis; 3) non-OVCP monitoring code recorded as primary diagnosis; 4) non-OVCP monitoring code recorded as secondary diagnosis. Results The percentage change of the number of visits with coding practice 1 between 2016Q1 and 2017Q3 was − 74% for patients with hypertension and − 73% with diabetes in tertiary medical centers and − 23% and − 17% in clinics, respectively. By contrast, the percentage changes of coding practice 3 were + 73% for patients with hypertension and + 46% for patients with diabetes in tertiary medical centers and − 19% and − 2% in clinics, respectively. Conclusions Physician code creep occurred after the initiation of the OVCP. Education regarding appropriate outpatient coding for physicians will be relatively effective when proper coding is related to reimbursement.

Abstract Background The Charlson comorbidity index (CCI) is commonly used to adjust for patient casemix. We reevaluated the CCI in an ischemic stroke (IS) cohort to determine whether the original seventeen comorbidities and their weights are relevant. Methods We identified an IS cohort (N = 6988) from the Ontario Stroke Registry (OSR) who were discharged from acute hospitals (N = 100) between April 1, 2012 and March 31, 2013. We used hospital discharge ICD-10-CA data to identify Charlson comorbidities. We developed a multivariable Cox model to predict one-year mortality retaining statistically significant (P

Abstract Background This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. By definition, we refer to 30-day mortality and 30-day unplanned readmission as the number of deaths and non-programmed hospitalizations for any cause within 30 days after the incident heart failure (HF). In particular, the focus is on the role played by hospital-level factors. Methods A multi-level logistic model that combines patient- and hospital-level covariates has been developed to better disentangle the role played by the two groups of covariates. Later on, hospital outliers in term of better-than-expected/worst-than-expected performers have been identified by comparing expected cases vs. observed cases. Hospitals performance in terms of 30-day mortality and 30-day unplanned readmission rates have been visualized through the creation of funnel plots. Covariates have been selected coherently to past literature. Data comes from the hospital discharge forms for Heart Failure patients in the Lombardy Region (Northern Italy). Considering incident cases for HF in the timespan 2010–2012, 78,907 records for adult patients from 117 hospitals have been collected after quality checks. Results Our results show that 30-day mortality and 30-day unplanned readmissions are explained by hospital-level covariates, paving the way for the design and implementation of evidence-based improvement strategies. While the percentage of surgical DRG (OR = 1.001; CI (1.000–1.002)) and the hospital type of structure (Research hospitals vs. non-research public hospitals (OR = 0.62; CI (0.48–0.80)) and Non-research private hospitals vs. non-research hospitals OR = 0.75; CI (0.63–0.90)) are significant for mortality, the mean length of stay (OR = 0.96; CI (0.95–0.98)) is significant for unplanned readmission, showing that mortality and readmission rates might be improved through different strategies. Conclusion Our results confirm that hospital-level covariates do affect quality of care, and that 30-day mortality and 30-day unplanned readmission are affected by different managerial choices. This confirms that hospitals should be accountable for their “added value” to quality of care.

Background: Switzerland, with its decentralized health system, has seen the emergence of a variety of care models to meet the complex needs of asylum seekers. A network of public and private providers was designed in the canton Vaud, in which a nurse-led team acts as a first contact point to the health system and provides health checks, preventive care, and health education to this population. In addition, the service plays a case management role for more complex and vulnerable patients. While the network has been examined from a clinical angle, we provide the first descriptive evidence on the care and cost trajectories of asylum seekers in the canton.Methods: We used routinely collected administrative, patient-level data in a Swiss region responsible for 10% of the asylum seekers in the country. We extracted data on all asylum seekers aged 18 or older who entered the network between 2012 and 2015. The data covered all healthcare costs during the period until they left the network, either because they were granted residence, they left the country, or until 31 December 2018. We estimated random effects regression models for costs and consultations within and outside the network for each month of stay in the network. We investigated language barriers in access to care by stratifying the analysis between patients who spoke one of the official Swiss languages or English and patients who did not speak any of these languages.Principal Findings: We found that both overall health care costs and contacts with the nurse-led team were relatively high during the first year of stay. Asylum seekers then progressively integrated into the regular health system. Individuals who did not speak the language generally had more contacts with the network and fewer contacts outside.Conclusions: In this exploratory study, we observe a transition from nurse-led specific care with frequent contacts to care in the regular health system. This leads us to generate the hypothesis that a nurse-led, patient-centered care network for asylum seekers can play an important role in providing primary care during the first year after their arrival and can subsequently help them navigate autonomously within the conventional healthcare system. [ABSTRACT FROM AUTHOR]

Abstract Background Faced with growing budget pressure, policymakers worldwide recognize the necessity of strategic disinvestment from ineffective, inefficient or harmful medical practices. However, disinvestment programs face substantial social, political and cultural challenges: mistrust, struggles for clinical autonomy or stakeholders’ reluctance to engage in what can be perceived as ‘rationing’. Academic literature says little about effective strategies to address these challenges. This paper provides insights on this matter. We analyzed the epistemic work of a group of policymakers at the National Health Care Institute on what was initially a disinvestment initiative within the context of the Dutch basic benefits package: the ‘Appropriate Care’ program. The Institute developed a strategy using national administrative data to identify and tackle low-value care covered from public funds as well as potential underuse, and achieve savings through improved organization of efficiency and quality in health care delivery. How did the Institute deal with the socio-political sensitivities associated with disinvestment by means of their epistemic work? Method We conducted ethnographic research into the National Health Care Institute’s epistemic practices. Research entailed document analysis, non-participant observation, in-depth conversations, and interviews with key-informants. Results The Institute dealt with the socio-political sensitivities associated with disinvestment by democratizing the epistemic practices to identify low-value care, by warranting data analysis by clinical experts, by creating an epistemic safe space for health care professionals who were the object of research into low-value care, and by de-emphasizing the economization measure. Ultimately, this epistemic work facilitated a collaborative construction of problems relating to low-value care practices and their solutions. Conclusions This case shows that – apart from the right data and adequate expertise – disinvestment requires clinical leadership and political will on the part of stakeholders. Our analysis of the Institute’s Appropriate Care program shows how the epistemic effort to identify low-value care became a co-construction between policymakers, care providers, patients and insurers of problems of ‘waste’ in Dutch social health insurance. This collective epistemic work gave cognitive, moral and political standing to the idea of ‘waste’ in public health expenditure.

Abstract Background Residence in public housing, a subsidized and managed government program, may affect health and healthcare utilization. We compared healthcare use in the year before individuals moved into public housing with usage during their first year of tenancy. We also described trends in use. Methods We used linked population-based administrative data housed in the Population Research Data Repository at the Manitoba Centre for Health Policy. The cohort consisted of individuals who moved into public housing in 2009 and 2010. We counted the number of hospitalizations, general practitioner (GP) visits, specialist visits, emergency department visits, and prescriptions drugs dispensed in the twelve 30-day intervals (i.e., months) immediately preceding and following the public housing move-in date. Generalized linear models with generalized estimating equations tested for a period (pre/post-move-in) by month interaction. Odds ratios (ORs), incident rate ratios (IRRs), and means are reported along with 95% confidence intervals (95% CIs). Results The cohort included 1942 individuals; the majority were female (73.4%) who lived in low income areas and received government assistance (68.1%). On average, the cohort had more than four health conditions. Over the 24 30-day intervals, the percentage of the cohort that visited a GP, specialist, and an emergency department ranged between 37.0% and 43.0%, 10.0% and 14.0%, and 6.0% and 10.0%, respectively, while the percentage of the cohort hospitalized ranged from 1.0% to 5.0%. Generally, these percentages were highest in the few months before the move-in date and lowest in the few months after the move-in date. The period by month interaction was statistically significant for hospitalizations, GP visits, and prescription drug use. The average change in the odds, rate, or mean was smaller in the post-move-in period than in the pre-move-in period. Conclusions Use of some healthcare services declined after people moved into public housing; however, the decrease was only observed in the first few months and utilization rebounded. Knowledge of healthcare trends before individuals move in are informative for ensuring the appropriate supports are available to new public housing residents. Further study is needed to determine if decreased healthcare utilization following a move is attributable to decreased access.

Abstract Background Few people with limited English proficiency are provided with the services of a healthcare interpreter when admitted to hospital. This retrospective study utilised health administrative data to explore which patients with limited English proficiency were provided with a healthcare interpreter during their hospital admission. Method A retrospective analysis of health administrative data for adult overnight-stay patients admitted to a public hospital in a region of significant cultural and linguistic diversity in Sydney, Australia in 2014–2015. Descriptive analyses were used to explore demographic and diagnostic data. Chi-square and analysis of variance were used to test for association between variables. Results The site hospital provided for 19,627 overnight-stay episodes of care over the one year period. Emergency admissions made up 70.5% (n = 13,845) of all hospital admissions and obstetric patients 11.7% (n = 2291). For 15.7% (n = 3074) of episodes of care a healthcare interpreter was identified at hospital admission as being required. In 3.7% (n = 727) of episodes of care a healthcare interpreter was provided. Patients who received an interpreter were more likely to be female, of a younger age and admitted to hospital for childbirth. Conclusions A minority of patients with limited English proficiency received a healthcare interpreter during their episode of care. The majority of interpreter services were provided to obstetric patients.

Abstract Background The burden of HCV among those living with HIV remains a major public health challenge. We aimed to characterize trends in healthcare-related visits (HRV) of people living with HIV (PLW-HIV) and those living with HIV and HCV (PLW-HIV/HCV), in British Columbia (BC), and to identify risk factors associated with the highest HRV rates over time. Methods Eligible individuals, recruited from the BC Seek and Treat for Optimal Prevention of HIV/AIDS population-based retrospective cohort (N = 3955), were ≥ 18 years old, first started combination antiretroviral therapy (ART) between 01/01/2000–31/12/2013, and were followed for ≥6 months until 31/12/2014. The main outcome was HRV rate. The main exposure was HIV/HCV co-infection status. We built a confounder non-linear mixed effects model, adjusting for several demographic and time-dependent factors. Results HRV rates have decreased since 2000 in both groups. The overall age-sex standardized HRV rate (per person-year) among PLW-HIV and PLW-HIV/HCV was 21.11 (95% CI 20.96–21.25) and 41.69 (95% CI 41.51–41.88), respectively. The excess in HRV in the co-infected group was associated with late presentation for ART, history of injection drug use, sub-optimal ART adherence and a higher number of comorbidities. The adjusted HRV rate ratio for PLW-HIV/HCV in comparison to PLW-HIV was 1.18 (95% CI 1.13–1.24). Conclusions Although HRV rates have decreased over time in both groups, PLW-HIV/HCV had 18% higher HRV than those only living with HIV. Our results highlight several modifiable risk factors that could be targeted as potential means to minimize the disease burden of this population and of the healthcare system.

Abstract Background Post-marketing safety studies of medicines often rely on administrative claims databases to identify adverse outcomes following drug exposure. Valid ascertainment of outcomes is essential for accurate results. We aim to quantify the validity of diagnostic codes for serious hypocalcemia and dermatologic adverse events from insurance claims data among women with postmenopausal osteoporosis (PMO). Methods We identified potential cases of serious hypocalcemia and dermatologic events through ICD-9 diagnosis codes among women with PMO within claims from a large US healthcare insurer (June 2005-May 2010). A physician adjudicated potential hypocalcemic and dermatologic events identified from the primary position on emergency department (ED) or inpatient claims through medical record review. Positive predictive values (PPVs) and 95% confidence intervals (CIs) quantified the fraction of potential cases that were confirmed. Results Among 165,729 patients with PMO, medical charts were obtained for 40 of 55 (73%) potential hypocalcemia cases; 16 were confirmed (PPV 40%, 95% CI 25–57%). The PPV was higher for ED than inpatient claims (82 vs. 24%). Among 265 potential dermatologic events (primarily urticaria or rash), we obtained 184 (69%) charts and confirmed 128 (PPV 70%, 95% CI 62–76%). The PPV was higher for ED than inpatient claims (77 vs. 39%). Conclusion Diagnostic codes for hypocalcemia and dermatologic events may be sufficient to identify events giving rise to emergency care, but are less accurate for identifying events within hospitalizations.

Abstract Background Improved data access and funding for health services research have promoted the application of routine data to measure costs and effects of interventions within the German health care system. Following the trend towards real world evidence, this review aims to evaluate the status and quality of health economic evaluations based on routine data in Germany. Methods To identify relevant economic evaluations, a systematic literature search in the databases PubMed and EMBASE was complemented by a manual search. The included studies had to be full economic evaluations using German routine data to measure either costs, effects, or both. Study characteristics were assessed with a structured template. Additionally, the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) were used to measure quality of reporting. Results In total, 912 records were identified and 35 studies were included in the further analysis. The majority of these studies was published in the past 5 years (n = 27, 77.1%) and used insurance claims data as a source of routine data (n = 30, 85.7%). The most common method used for handling selection bias was propensity score matching. With regard to the reporting quality, 42.9% (n = 15) of the studies satisfied at least 80% of the criteria on the CHEERS checklist. Conclusions This review confirms that routine data has become an increasingly common data source for health economic evaluations in Germany. While most studies addressed the application of routine data, this analysis reveals deficits in considering methodological particularities and in reporting quality of economic evaluations based on routine data. Nevertheless, this review demonstrates the overall potential of routine data for economic evaluations.

Abstract Background Hospital mortality, readmission and length of stay (LOS) are commonly used measures for quality of care. We aimed to disentangle the correlations between these interrelated measures and propose a new way of combining them to evaluate the quality of hospital care. Methods We analyzed administrative data from the Global Comparators Project from 26 hospitals on patients discharged between 2007 and 2012. We correlated standardized and risk-adjusted hospital outcomes on mortality, readmission and long LOS. We constructed a composite measure with 5 levels, based on literature review and expert advice, from survival without readmission and normal LOS (best) to mortality (worst outcome). This composite measure was analyzed using ordinal regression, to obtain a standardized outcome measure to compare hospitals. Results Overall, we observed a 3.1% mortality rate, 7.8% readmission rate (in survivors) and 20.8% long LOS rate among 4,327,105 admissions. Mortality and LOS were correlated at the patient and the hospital level. A patient in the upper quartile LOS had higher odds of mortality (odds ratio = 1.45, 95% confidence interval 1.43–1.47) than those in the lowest quartile. Hospitals with a high standardized mortality had higher proportions of long LOS (r = 0.79, p

Abstract Background To estimate changes in the cost and utilization of Medicare among beneficiaries over age 65 who have been impacted by a natural disaster, we merged publically available county-level Medicare claims for the years 2008–2012 with Federal Emergency Management Agency (FEMA) data related to disasters in each U.S. County from 2007 to 2012. Methods Fixed-effects generalized linear models were used to calculate change in per capita costs standardized by region and utilization per 1000 beneficiaries at the county level. Aggregate county demographic characteristics of Medicare participants were included as predictors of change in county-level utilization and cost. FEMA data was used to determine counties that experienced no, some, high, and extreme hazard exposure. FEMA data was merged with claims data to create a balanced panel dataset from 2008 to 2012. Results In general, both cost and utilization of Medicare services were higher in counties with more hazard exposure. However, utilization of home health services was lower in counties with more hazard exposure. Conclusions Additional research using individual-level data is needed to address limitations and determine the impacts of the substitution of services (e.g., inpatient rehabilitation for home health) that may be occurring in disaster affected areas during the post-disaster period.

Background: The look-back period is needed to define baseline population for estimating incidence. However, short look-back period is known to overestimate incidence of diseases misclassifying prevalent cases to incident cases. The purpose of this study is to evaluate the impact of the various length of look-back period on the observed incidences of uterine leiomyoma, endometriosis and adenomyosis, and to estimate true incidences considering the misclassification errors in the longitudinal administrative data in Korea.Methods: A total of 319,608 women between 15 to 54 years of age in 2002 were selected from Korea National Health Insurance Services (KNHIS) cohort database. In order to minimize misclassification bias incurred when applying various length of look-back period, we used 11 years of claim data to estimate the incidence by equally setting the look-back period to 11 years for each year using prediction model. The association between the year of diagnosis and the number of prevalent cases with the misclassification rates by each look-back period was investigated. Based on the findings, prediction models on the proportion of misclassified incident cases were developed using multiple linear regression.Results: The proportion of misclassified incident cases of uterine leiomyoma, endometriosis and adenomyosis were 32.8, 10.4 and 13.6% respectively for the one-year look-back period in 2003. These numbers decreased to 6.3% in uterine leiomyoma and - 0.8% in both endometriosis and adenomyosis using all available look-back periods (11 years) in 2013.Conclusion: This study demonstrates approaches for estimating incidences considering the different proportion of misclassified cases for various length of look-back period. Although the prediction model used for estimation showed strong R-squared values, follow-up studies are required for validation of the study results. [ABSTRACT FROM AUTHOR]

Background: Most studies on the physician code creep (i.e., changes in case mix record-keeping practices to improve reimbursement) have focused on episodes (inpatient hospitalizations or outpatient procedures). Little is known regarding changes in diagnostic coding practices for better reimbursement among a fixed cohort of patients with chronic diseases.Methods: To examine whether physicians in tertiary medical centers changed their coding practices after the initiation of the Outpatient Volume Control Program (OVCP) in Taiwan, we conducted a retrospective observational study of four patient cohorts (two interventions and two controls) from January 2016 to September 2017 in Taiwan. The main outcomes were the number of outpatient visits with four coding practices: 1) OVCP monitoring code recorded as primary diagnosis; 2) OVCP monitoring code recorded as secondary diagnosis; 3) non-OVCP monitoring code recorded as primary diagnosis; 4) non-OVCP monitoring code recorded as secondary diagnosis.Results: The percentage change of the number of visits with coding practice 1 between 2016Q1 and 2017Q3 was - 74% for patients with hypertension and - 73% with diabetes in tertiary medical centers and - 23% and - 17% in clinics, respectively. By contrast, the percentage changes of coding practice 3 were + 73% for patients with hypertension and + 46% for patients with diabetes in tertiary medical centers and - 19% and - 2% in clinics, respectively.Conclusions: Physician code creep occurred after the initiation of the OVCP. Education regarding appropriate outpatient coding for physicians will be relatively effective when proper coding is related to reimbursement. [ABSTRACT FROM AUTHOR]

Abstract Background Administrative health data are increasingly used for research and surveillance to inform decision-making because of its large sample sizes, geographic coverage, comprehensivity, and possibility for longitudinal follow-up. Within Canadian provinces, individuals are assigned unique personal health numbers that allow for linkage of administrative health records in that jurisdiction. It is therefore necessary to ensure that these data are of high quality, and that chart information is accurately coded to meet this end. Our objective is to explore the potential barriers that exist for high quality data coding through qualitative inquiry into the roles and responsibilities of medical chart coders. Methods We conducted semi-structured interviews with 28 medical chart coders from Alberta, Canada. We used thematic analysis and open-coded each transcript to understand the process of administrative health data generation and identify barriers to its quality. Results The process of generating administrative health data is highly complex and involves a diverse workforce. As such, there are multiple points in this process that introduce challenges for high quality data. For coders, the main barriers to data quality occurred around chart documentation, variability in the interpretation of chart information, and high quota expectations. Conclusions This study illustrates the complex nature of barriers to high quality coding, in the context of administrative data generation. The findings from this study may be of use to data users, researchers, and decision-makers who wish to better understand the limitations of their data or pursue interventions to improve data quality.

Abstract Background Like much of the developed world, healthcare costs in Canada are rising. A small proportion of patients account for a large proportion of healthcare spending and much of this spending occurs in acute care settings. The purpose of our study was to determine potentially modifiable factors related to care processes that contribute to high-cost admissions. Methods Using a mixed-methods study design, factors contributing to high-cost admissions were identified from literature and case review. We defined pre- and post-admission factors contributing to high-cost admissions. Pre-admission factors included reason for admission (e.g. complex medical, elective surgery, trauma, etc.). Post-admission factors included medical complications, disposition delays, clinical services delays, and inefficient clinical decision-making. We selected a random sample of admissions in the top decile of inpatient cost from the Ottawa Hospital between January 1 and December 31, 2010. A single reviewer classified cases based on the pre- and post-admission factors. We combined this information with data derived from the Ottawa Hospital Data Warehouse to describe patient-level clinical and demographic characteristics and costs incurred. Results We reviewed 200 charts which represents ~5% of all high cost admissions within the Ottawa Hospital in 2010. Post-admission factors contributing to high-cost admissions were: complications (60%), disposition delays (53%), clinical service delays (39%), and inefficient clinical decision-making (13%). Further, these factors varied substantially across service delivery lines. The mean (standard deviation (SD)) cost per admission was $49,923 CDN ($45,773). The most common reason for admission was “complex medical” (49%) and the overall median (IQR) length of stay was 27 (18–48) days. Approximately 1 in 3 high cost admissions (29%) included time in the intensive care unit (ICU). Conclusions While high cost admissions often include time in ICU and have long lengths of stay, a substantial proportion of costs were attributable to complications and potentially preventable delays in care processes. These findings suggest opportunities exist to improve outcomes and reduce costs for this diverse patient population.

Background: This study aims at gathering evidence about the relation between 30-day mortality and 30-day unplanned readmission and patient and hospital factors. By definition, we refer to 30-day mortality and 30-day unplanned readmission as the number of deaths and non-programmed hospitalizations for any cause within 30 days after the incident heart failure (HF). In particular, the focus is on the role played by hospital-level factors.Methods: A multi-level logistic model that combines patient- and hospital-level covariates has been developed to better disentangle the role played by the two groups of covariates. Later on, hospital outliers in term of better-than-expected/worst-than-expected performers have been identified by comparing expected cases vs. observed cases. Hospitals performance in terms of 30-day mortality and 30-day unplanned readmission rates have been visualized through the creation of funnel plots. Covariates have been selected coherently to past literature. Data comes from the hospital discharge forms for Heart Failure patients in the Lombardy Region (Northern Italy). Considering incident cases for HF in the timespan 2010-2012, 78,907 records for adult patients from 117 hospitals have been collected after quality checks.Results: Our results show that 30-day mortality and 30-day unplanned readmissions are explained by hospital-level covariates, paving the way for the design and implementation of evidence-based improvement strategies. While the percentage of surgical DRG (OR = 1.001; CI (1.000-1.002)) and the hospital type of structure (Research hospitals vs. non-research public hospitals (OR = 0.62; CI (0.48-0.80)) and Non-research private hospitals vs. non-research hospitals OR = 0.75; CI (0.63-0.90)) are significant for mortality, the mean length of stay (OR = 0.96; CI (0.95-0.98)) is significant for unplanned readmission, showing that mortality and readmission rates might be improved through different strategies.Conclusion: Our results confirm that hospital-level covariates do affect quality of care, and that 30-day mortality and 30-day unplanned readmission are affected by different managerial choices. This confirms that hospitals should be accountable for their "added value" to quality of care. [ABSTRACT FROM AUTHOR]

BackgroundThe Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) provide information on hospital risk-adjusted rates for potentially preventable adverse events. Although designed to work with routine administrative data, it is unknown whether the PSIs can accurately distinguish between complications and pre-existing conditions. The objective of this study is to examine whether the AHRQ PSIs accurately measure hospital complication rates, using the data with present-on-admission (POA) codes to distinguish between complications and pre-existing conditionsMethodsRetrospective cohort study of patients undergoing isolated CABG surgery in California conducted using the 1998–2000 California State Inpatient Database. We calculated the positive predictive value of selected AHRQ PSIs using information from the POA as the gold standard, and the intra-class correlation coefficient to assess the level of agreement between the hospital risk-adjusted PSI rates with and without the information contained in the POA modifier.ResultsThe false positive error rate, defined as one minus the positive predictive value, was greater than or equal to 20% for four of the eight PSIs examined: decubitus ulcer, failure-to-rescue, postoperative physiologic and metabolic derangement, and postoperative pulmonary embolism or deep venous thrombosis. Pairwise comparison of the hospital risk-adjusted PSI rates, with and without POA information, demonstrated almost perfect agreement for five of the eight PSI's. For decubitus ulcer, failure-to-rescue, and postoperative pulmonary embolism or DVT, the intraclass-correlation coefficient ranged between 0.63 to 0.79.ConclusionFor some of the AHRQ Patient Safety Indicators, there are significant differences in the risk-adjusted rates of adverse events depending on whether the POA indicator is used to distinguish between pre-existing conditions and complications. The use of the POA indicator will increase the accuracy of the AHRQ PSIs as measures of adverse outcomes.

Abstract Background Since in an ageing society more long-term care (LTC) facilities are needed, it is important to understand the main determinants of first-time utilization of (LTC) services. Methods The Andersen service model, which distinguishes predisposing, enabling and need factors, was used to develop a model for first-time utilization of LTC services among the general population of the Netherlands. We used data on 214,821 persons registered in a database of general practitioners (NIVEL Primary Care Database). For each person the medical history was known, as well as characteristics such as ethnicity, income, home-ownership, and marital status. Utilization data from the national register on long-term care was linked at a personal level. Generalized Linear Models were used to determine the relative importance of factors of incident LTC-service utilization. Results Top 5 determinants of LTC are need, measured as the presence of chronic diseases, age, household size, household income and homeownership. When controlling for all other determinants, the presence of an additional chronic disease increases the probability of utilizing any LTC service by 45% among the 20+ population (OR = 1.45, 95% CI: 1.41–1.49), and 31% among the 65+ population (OR = 1.31, 95% CI: 1.27–1.36). With respect to the 20+ population, living in social rent (OR = 2.45, 95% CI = 2.25–2.67, ref. = home-owner) had a large impact on utilizing any LTC service. In a lesser degree this was the case for living alone (OR = 1.63, 95% CI = 1.52–1.75, ref. = not living alone). A higher household income was linked with a lower utilization of any LTC service. Conclusions All three factors of the Anderson model, predisposing, enabling, and need determinants influence the likelihood of future LTC service utilization. This implies that none of these factors can be left out of the analysis of what determines this use. New in our analysis is the focus on incident utilization. This provides a better estimate of the effects of predictors than a prevalence based analysis, as there is less confounding by changes in determinants occurring after LTC initiation. Especially the need of care is a strong factor. A policy implication of this relative importance of health status is therefore that LTC reforms should take health aspects into account.

Abstract Background Validation of administrative data case definitions is key for accurate passive surveillance of disease. Transient ischemic attack (TIA) is a condition primarily managed in the emergency department. However, prior validation studies have focused on data after inpatient hospitalization. We aimed to determine the validity of the Canadian 10th International Classification of Diseases (ICD-10-CA) codes for TIA in the national ambulatory administrative database. Methods We performed a diagnostic accuracy study of four ICD-10-CA case definition algorithms for TIA in the emergency department setting. The study population was obtained from two ongoing studies on the diagnosis of TIA and minor stroke versus stroke mimic using serum biomarkers and neuroimaging. Two reference standards were used 1) the emergency department clinical diagnosis determined by chart abstractors and 2) the 90-day final diagnosis, both obtained by stroke neurologists, to calculate the sensitivity, specificity, positive and negative predictive values (PPV and NPV) of the ICD-10-CA algorithms for TIA. Results Among 417 patients, emergency department adjudication showed 163 (39.1%) TIA, 155 (37.2%) ischemic strokes, and 99 (23.7%) stroke mimics. The most restrictive algorithm, defined as a TIA code in the main position had the lowest sensitivity (36.8%), but highest specificity (92.5%) and PPV (76.0%). The most inclusive algorithm, defined as a TIA code in any position with and without query prefix had the highest sensitivity (63.8%), but lowest specificity (81.5%) and PPV (68.9%). Sensitivity, specificity, PPV, and NPV were overall lower when using the 90-day diagnosis as reference standard. Conclusions Emergency department administrative data reflect diagnosis of suspected TIA with high specificity, but underestimate the burden of disease. Future studies are necessary to understand the reasons for the low to moderate sensitivity.

Abstract Background Hysterectomy is among the most common surgeries performed on U.S. women. For benign conditions, minimally invasive hysterectomy is recommended, whenever permitted by clinical indication and previous surgery history. No study has examined whether the use of less invasive hysterectomy spread more slowly for Black women. Methods We used the hysterectomy that occurs in outpatient settings as a proxy for minimally invasive hysterectomy. Using claims-based surgery data and census denominators, we calculated age-standardized rates of all hysterectomies in North Carolina from 2011 to 2013. Study participants were 41,899 women (64.6% non-Hispanic White, 28.3% non-Hispanic Black) who underwent hysterectomy for non-malignant indications. We fit Poisson models to determine whether changes in outpatient hysterectomy rates differed by Black-White race. We employed a difference-in-difference approach to control for racial differences in the severity of clinical indication. Further, we restricted to one state to minimize confounding from geographic differences in where Black and White women live. Results From 2011 to 2013, the overall hysterectomy rate decreased from 42.3 per 10,000 women (n = 14,648) to 37.9 per 10,000 (n = 13,241) (p

Abstract Background A small proportion of patients utilizes a disproportionately large amount of emergency department (ED) resources. Being able to properly identify chronic frequent ED users, i.e. frequent ED users over a multiple-year period, would allow healthcare professionals to intervene before it occurs and, if possible, redirect these patients to more appropriate health services. The objective of this study was to explore the factors associated with chronic frequent ED utilization in a population with diabetes. Methods A population-based retrospective cohort study using administrative data was conducted on 62,316 patients with diabetes living in metropolitan areas of Quebec (Canada), having visited an ED during 2006, and still alive in 31 December 2009. The dependant variable was being a chronic frequent ED user, defined as having at least 3 ED visits per year during three consecutive years (2007–2009). Independent variables, measured during 2006, included age, sex, neighbourhood deprivation, affiliation to a general practitioner, and number of physical and mental health comorbidities. Logistic regression and tree-based method were used to identify factors associated with chronic frequent ED use. Results A total of 2.6% of the cohort (patients with diabetes and at least one ED visit in 2006) was identified as chronic frequent ED users. These patients accounted for 16% of all ED visits made by the cohort during follow-up. The cumulative effect of a high illness burden combined with mental health disorders was associated with an increased risk of chronic frequent ED use. Conclusions Interventions must target the population at higher risk of becoming chronic frequent ED users and should be designed to manage the complex interaction between high illness burden and mental health.

Background: Many studies have investigated the presence of a 'weekend effect' in mortality following hospital admission, and these frequently use diagnostic codes from administrative data for information on comorbidities for risk adjustment. However, it is possible that coding practice differs between week and weekend. We assess patients with a confirmed history of certain long-term health conditions and investigate how well these are recorded in subsequent week and weekend admissions.Methods: We selected six long-term conditions that are commonly assessed when risk-adjusting mortality rates, via the Charlson and Elixhauser indices. Using Hospital Episode Statistics data from England for the period April 2009 to March 2011, we identified patients with the condition recorded at least twice, on separate emergency admissions. Then we assessed how often each condition was recorded on subsequent emergency admissions between April 2011 and March 2013. We then compared coding between week and weekend admissions using the Cochran-Mantel-Haenszel test, stratifying by hospital.Results: We studied 111,457 patients with chronic pulmonary disease, 106,432 with diabetes, 36,447 with congestive heart failure, 30,996 with dementia, 7808 with hemiplegia or paraplegia and 5877 with metastatic cancer. Across the entire week, between April 2011 and March 2013, coding completeness ranged from 89% for diabetes to 43% for hemiplegia/paraplegia. Compared with weekday admissions, congestive heart failure was less likely to be recorded as a secondary diagnosis at the weekend (odds ratio 0.92, 95% CI, 0.88 to 0.97), with smaller but statistically significant differences also detected for chronic pulmonary disease (odds ratio 0.96, 95% CI, 0.93 to 0.99) and diabetes (odds ratio 0.95, 95% CI 0.91 to 0.99). There was no statistically significant difference in recording between week and weekend admissions for dementia (odds ratio 1.04, 95% CI 0.97 to 1.11), hemiplegia/paraplegia (odds ratio 0.99, 95% CI 0.89 to 1.10) or metastatic cancer (odds ratio 1.04, 95% CI 0.90 to 1.20).Conclusions: Long-term conditions are often not recorded on administrative data and the lack of recording may be worse for weekend admissions. Studies of the weekend effect that rely on administrative data might have underestimated the health burden of patients, particularly if admitted at the weekend. [ABSTRACT FROM AUTHOR]

Background: Hospital mortality, readmission and length of stay (LOS) are commonly used measures for quality of care. We aimed to disentangle the correlations between these interrelated measures and propose a new way of combining them to evaluate the quality of hospital care.Methods: We analyzed administrative data from the Global Comparators Project from 26 hospitals on patients discharged between 2007 and 2012. We correlated standardized and risk-adjusted hospital outcomes on mortality, readmission and long LOS. We constructed a composite measure with 5 levels, based on literature review and expert advice, from survival without readmission and normal LOS (best) to mortality (worst outcome). This composite measure was analyzed using ordinal regression, to obtain a standardized outcome measure to compare hospitals.Results: Overall, we observed a 3.1% mortality rate, 7.8% readmission rate (in survivors) and 20.8% long LOS rate among 4,327,105 admissions. Mortality and LOS were correlated at the patient and the hospital level. A patient in the upper quartile LOS had higher odds of mortality (odds ratio = 1.45, 95% confidence interval 1.43-1.47) than those in the lowest quartile. Hospitals with a high standardized mortality had higher proportions of long LOS (r = 0.79, p < 0.01). Readmission rates did not correlate with either mortality or long LOS rates. The interquartile range of the standardized ordinal composite outcome was 74-117. The composite outcome had similar or better reliability in ranking hospitals than individual outcomes.Conclusions: Correlations between different outcome measures are complex and differ between hospital- and patient-level. The proposed composite measure combines three outcomes in an ordinal fashion for a more comprehensive and reliable view of hospital performance than its component indicators. [ABSTRACT FROM AUTHOR]

Background: Like much of the developed world, healthcare costs in Canada are rising. A small proportion of patients account for a large proportion of healthcare spending and much of this spending occurs in acute care settings. The purpose of our study was to determine potentially modifiable factors related to care processes that contribute to high-cost admissions.Methods: Using a mixed-methods study design, factors contributing to high-cost admissions were identified from literature and case review. We defined pre- and post-admission factors contributing to high-cost admissions. Pre-admission factors included reason for admission (e.g. complex medical, elective surgery, trauma, etc.). Post-admission factors included medical complications, disposition delays, clinical services delays, and inefficient clinical decision-making. We selected a random sample of admissions in the top decile of inpatient cost from the Ottawa Hospital between January 1 and December 31, 2010. A single reviewer classified cases based on the pre- and post-admission factors. We combined this information with data derived from the Ottawa Hospital Data Warehouse to describe patient-level clinical and demographic characteristics and costs incurred.Results: We reviewed 200 charts which represents ~5% of all high cost admissions within the Ottawa Hospital in 2010. Post-admission factors contributing to high-cost admissions were: complications (60%), disposition delays (53%), clinical service delays (39%), and inefficient clinical decision-making (13%). Further, these factors varied substantially across service delivery lines. The mean (standard deviation (SD)) cost per admission was $49,923 CDN ($45,773). The most common reason for admission was "complex medical" (49%) and the overall median (IQR) length of stay was 27 (18-48) days. Approximately 1 in 3 high cost admissions (29%) included time in the intensive care unit (ICU).Conclusions: While high cost admissions often include time in ICU and have long lengths of stay, a substantial proportion of costs were attributable to complications and potentially preventable delays in care processes. These findings suggest opportunities exist to improve outcomes and reduce costs for this diverse patient population. [ABSTRACT FROM AUTHOR]

Background: Administrative health data are increasingly used for research and surveillance to inform decision-making because of its large sample sizes, geographic coverage, comprehensivity, and possibility for longitudinal follow-up. Within Canadian provinces, individuals are assigned unique personal health numbers that allow for linkage of administrative health records in that jurisdiction. It is therefore necessary to ensure that these data are of high quality, and that chart information is accurately coded to meet this end. Our objective is to explore the potential barriers that exist for high quality data coding through qualitative inquiry into the roles and responsibilities of medical chart coders.Methods: We conducted semi-structured interviews with 28 medical chart coders from Alberta, Canada. We used thematic analysis and open-coded each transcript to understand the process of administrative health data generation and identify barriers to its quality.Results: The process of generating administrative health data is highly complex and involves a diverse workforce. As such, there are multiple points in this process that introduce challenges for high quality data. For coders, the main barriers to data quality occurred around chart documentation, variability in the interpretation of chart information, and high quota expectations.Conclusions: This study illustrates the complex nature of barriers to high quality coding, in the context of administrative data generation. The findings from this study may be of use to data users, researchers, and decision-makers who wish to better understand the limitations of their data or pursue interventions to improve data quality. [ABSTRACT FROM AUTHOR]

Background: Validation of administrative data case definitions is key for accurate passive surveillance of disease. Transient ischemic attack (TIA) is a condition primarily managed in the emergency department. However, prior validation studies have focused on data after inpatient hospitalization. We aimed to determine the validity of the Canadian 10th International Classification of Diseases (ICD-10-CA) codes for TIA in the national ambulatory administrative database.Methods: We performed a diagnostic accuracy study of four ICD-10-CA case definition algorithms for TIA in the emergency department setting. The study population was obtained from two ongoing studies on the diagnosis of TIA and minor stroke versus stroke mimic using serum biomarkers and neuroimaging. Two reference standards were used 1) the emergency department clinical diagnosis determined by chart abstractors and 2) the 90-day final diagnosis, both obtained by stroke neurologists, to calculate the sensitivity, specificity, positive and negative predictive values (PPV and NPV) of the ICD-10-CA algorithms for TIA.Results: Among 417 patients, emergency department adjudication showed 163 (39.1%) TIA, 155 (37.2%) ischemic strokes, and 99 (23.7%) stroke mimics. The most restrictive algorithm, defined as a TIA code in the main position had the lowest sensitivity (36.8%), but highest specificity (92.5%) and PPV (76.0%). The most inclusive algorithm, defined as a TIA code in any position with and without query prefix had the highest sensitivity (63.8%), but lowest specificity (81.5%) and PPV (68.9%). Sensitivity, specificity, PPV, and NPV were overall lower when using the 90-day diagnosis as reference standard.Conclusions: Emergency department administrative data reflect diagnosis of suspected TIA with high specificity, but underestimate the burden of disease. Future studies are necessary to understand the reasons for the low to moderate sensitivity. [ABSTRACT FROM AUTHOR]

Background: Since in an ageing society more long-term care (LTC) facilities are needed, it is important to understand the main determinants of first-time utilization of (LTC) services.Methods: The Andersen service model, which distinguishes predisposing, enabling and need factors, was used to develop a model for first-time utilization of LTC services among the general population of the Netherlands. We used data on 214,821 persons registered in a database of general practitioners (NIVEL Primary Care Database). For each person the medical history was known, as well as characteristics such as ethnicity, income, home-ownership, and marital status. Utilization data from the national register on long-term care was linked at a personal level. Generalized Linear Models were used to determine the relative importance of factors of incident LTC-service utilization.Results: Top 5 determinants of LTC are need, measured as the presence of chronic diseases, age, household size, household income and homeownership. When controlling for all other determinants, the presence of an additional chronic disease increases the probability of utilizing any LTC service by 45% among the 20+ population (OR = 1.45, 95% CI: 1.41-1.49), and 31% among the 65+ population (OR = 1.31, 95% CI: 1.27-1.36). With respect to the 20+ population, living in social rent (OR = 2.45, 95% CI = 2.25-2.67, ref. = home-owner) had a large impact on utilizing any LTC service. In a lesser degree this was the case for living alone (OR = 1.63, 95% CI = 1.52-1.75, ref. = not living alone). A higher household income was linked with a lower utilization of any LTC service.Conclusions: All three factors of the Anderson model, predisposing, enabling, and need determinants influence the likelihood of future LTC service utilization. This implies that none of these factors can be left out of the analysis of what determines this use. New in our analysis is the focus on incident utilization. This provides a better estimate of the effects of predictors than a prevalence based analysis, as there is less confounding by changes in determinants occurring after LTC initiation. Especially the need of care is a strong factor. A policy implication of this relative importance of health status is therefore that LTC reforms should take health aspects into account. [ABSTRACT FROM AUTHOR]

Background: Hysterectomy is among the most common surgeries performed on U.S. women. For benign conditions, minimally invasive hysterectomy is recommended, whenever permitted by clinical indication and previous surgery history. No study has examined whether the use of less invasive hysterectomy spread more slowly for Black women.Methods: We used the hysterectomy that occurs in outpatient settings as a proxy for minimally invasive hysterectomy. Using claims-based surgery data and census denominators, we calculated age-standardized rates of all hysterectomies in North Carolina from 2011 to 2013. Study participants were 41,899 women (64.6% non-Hispanic White, 28.3% non-Hispanic Black) who underwent hysterectomy for non-malignant indications. We fit Poisson models to determine whether changes in outpatient hysterectomy rates differed by Black-White race. We employed a difference-in-difference approach to control for racial differences in the severity of clinical indication. Further, we restricted to one state to minimize confounding from geographic differences in where Black and White women live.Results: From 2011 to 2013, the overall hysterectomy rate decreased from 42.3 per 10,000 women (n = 14,648) to 37.9 per 10,000 (n = 13,241) (p < 0.0001). Most hysterectomy (67.6%) occurred in outpatient settings. The inpatient rate decreased 35.2% (p < 0.0001), to 10.3 per 10,000, while the outpatient rate increased 4.6% (p < 0.01), to 27.5 per 10,000. From 2011 to 2013, Black women's outpatient rate increased 22% (p < 0.0001): from 25.8 per 10,000 to 31.5. In contrast, among White women, outpatient rates remained stable (p = 0.79): at 28.3 per 10,000 in 2013.Conclusions: Rapid increases in outpatient hysterectomy among Black women compared to stable rates among White women indicate a race-specific catch-up phenomenon in the spread of minimally invasive hysterectomy. These results are consistent with the hypothesis that minimally invasive hysterectomy may have been adopted more slowly for Black women than their White counterparts after its introduction in the early 2000s. The persistently high rates of hysterectomy among young Black women and potentially slower adoption of minimally invasive procedures among these women highlight a potential racial disparity in women's healthcare. [ABSTRACT FROM AUTHOR]

Background: A small proportion of patients utilizes a disproportionately large amount of emergency department (ED) resources. Being able to properly identify chronic frequent ED users, i.e. frequent ED users over a multiple-year period, would allow healthcare professionals to intervene before it occurs and, if possible, redirect these patients to more appropriate health services. The objective of this study was to explore the factors associated with chronic frequent ED utilization in a population with diabetes.Methods: A population-based retrospective cohort study using administrative data was conducted on 62,316 patients with diabetes living in metropolitan areas of Quebec (Canada), having visited an ED during 2006, and still alive in 31 December 2009. The dependant variable was being a chronic frequent ED user, defined as having at least 3 ED visits per year during three consecutive years (2007-2009). Independent variables, measured during 2006, included age, sex, neighbourhood deprivation, affiliation to a general practitioner, and number of physical and mental health comorbidities. Logistic regression and tree-based method were used to identify factors associated with chronic frequent ED use.Results: A total of 2.6% of the cohort (patients with diabetes and at least one ED visit in 2006) was identified as chronic frequent ED users. These patients accounted for 16% of all ED visits made by the cohort during follow-up. The cumulative effect of a high illness burden combined with mental health disorders was associated with an increased risk of chronic frequent ED use.Conclusions: Interventions must target the population at higher risk of becoming chronic frequent ED users and should be designed to manage the complex interaction between high illness burden and mental health. [ABSTRACT FROM AUTHOR]

Background: Although it is well-known that early detection of colorectal cancer (CRC) is important for optimal patient survival, the relationship of patient and health system factors with delayed diagnosis are unclear. The purpose of this study was to identify the demographic, clinical and healthcare factors related to mode of CRC detection and length of the diagnostic interval.Methods: All residents of Alberta, Canada diagnosed with first-ever incident CRC in years 2004-2010 were identified from the Alberta Cancer Registry. Population-based administrative health datasets, including hospital discharge abstract, ambulatory care classification system and physician billing data, were used to identify healthcare services related to CRC diagnosis. The time to diagnosis was defined as the time from the first CRC-related healthcare visit to the date of CRC diagnosis. Mode of CRC detection was classified into three groups: urgent, screen-detected and symptomatic. Quantile regression was performed to assess factors associated with time to diagnosis.Results: 9626 patients were included in the study; 25% of patients presented as urgent, 32% were screen-detected and 43% were symptomatic. The median time to diagnosis for urgent, screen-detected and symptomatic patients were 6 days (interquartile range (IQR) 2-14 days), 74 days (IQR 36-183 days), 84 days (IQR 39-223 days), respectively. Time to diagnosis was greater than 6 months for 27% of non-urgent patients. Healthcare factors had the largest impact on time to diagnosis: 3 or more visits to a GP increased the median by 140 days whereas 2 or more visits to a GI-specialist increased it by 108 days compared to 0-1 visits to a GP or GI-specialist, respectively.Conclusion: A large proportion of CRC patients required urgent work-up or had to wait more than 6 months for diagnosis. Actions are needed to reduce the frequency of urgent presentation as well as improve the timeliness of diagnosis. Findings suggest a need to improve coordination of care across multiple providers. [ABSTRACT FROM AUTHOR]

Background: A small proportion of patients account for the majority of health care spending. The objectives of this study were to explore the clinical characteristics, patterns of health care use, and the proportion of acute care spending deemed potentially preventable among high cost inpatients within a Canadian acute-care hospital.Methods: We identified all individuals within the Ottawa Hospital with one or more inpatient hospitalization between April 1, 2010 and March 31, 2011. Clinical characteristics and frequency of hospital encounters were captured in the information systems of the Ottawa Hospital Data Warehouse. Direct inpatient costs for each encounter were summed using case costing information and those in the upper first and fifth percentiles of the cumulative direct cost distribution were defined as extremely high cost and high cost respectively. We quantified preventable acute care spending as hospitalizations for ambulatory care sensitive conditions (ACSC) and spending attributable to difficulty discharging patients as measured by alternate level of care (ALC) status.Results: During the study period, 36,892 patients had 44,066 hospitalizations. High cost patients (n = 1,844) accounted for 38 % of total inpatient spending ($122 million) and were older, more likely to be male, and had higher levels of co-morbidity compared to non-high cost patients. In over half of the high cost cohort (54 %), costs were accumulated from a single hospitalization. The majority of costs were related to nursing care and intensive care unit spending. High cost patients were more likely to have an encounter deemed to be ambulatory care sensitive compared to non-high cost inpatients (6.0 versus 2.8 %, p < 0.001). A greater proportion of inpatient spending was attributable to ALC days for high cost versus non-high cost patients (9.1 versus 4.9 %, p < 0.001).Conclusions: Within a population of high cost inpatients, the majority of costs are attributed to a single, non-preventable, acute care episode. However, there are likely opportunities to improve hospital efficiency by focusing on different approaches to community based care directed towards specific populations. [ABSTRACT FROM AUTHOR]