How can the research potential of the clinical quality databases be maximized? The Danish experience

Inhaled corticosteroid treatment and pneumonia in patients with chronic obstructive pulmonary disease - nationwide development from 1998 to 2018

Background

A decreasing use of inhaled corticosteroids (ICS) in patients with a hospital-registered diagnosis of chronic obstructive pulmonary disease (COPD) has recently been documented in Denmark. ICS treatment is not recommended in patients with high pneumonia risk, and we aimed to assess the development of ICS treatment in relation to pneumonia occurrence.

Methods

Annual nationwide register-based cross-sectional studies from 1998 to 2018 including all patients ≥40 years of age with a hospital-registered ICD-10 diagnosis of COPD on the 31st of December each year. We calculated the annual proportion of patients with at least one outpatient pneumonia (redeemed prescription of relevant antibiotics) or pneumonia hospitalization (hospitalization or ER visit), and stratified by ICS dose (No ICS, low dose, medium dose, or high dose).

Results

The study population increased from 35,656 patients in 1998 to 99,057 patients in 2018. The annual proportion of patients experiencing a pneumonia decreased from 69.4% to 55.2%. The proportion of patients with at least one outpatient pneumonia, but no hospitalization, decreased (59.2% to 46.2%). The overall proportion of patients with at least one pneumonia hospitalization remained unchanged (10.2% to 9.0%), but this proportion increased in patients in high dose ICS (9.9% to 14.6%). The overall proportion of patients in high dose treatment decreased (12.7% to 5.7%), but not in patients with pneumonia hospitalization (16.5% to 15.1).

Conclusions

Our study demonstrates a nationwide decrease from 1998 to 2018 in the proportion of patients who redeemed a prescription for antibiotics used mainly for respiratory tract infections, which may reflect a decrease in the number of outpatient pneumonias. This decrease was largely caused by an increase in the number of patients without pneumonia. No differences over time were seen regarding hospitalization-requiring pneumonia. High dose ICS treatment was unchanged in patients with hospitalization-requiring pneumonia.

From electronic health records to clinical management systems: how the digital transformation can support healthcare services

Healthcare systems worldwide are currently undergoing significant transformations in response to increasing costs, a shortage of healthcare professionals and the growing complexity of medical needs among the population. Value-based healthcare reimbursement systems are emerging as an attempt to incentivize patient-centricity and cost containment. From a technological perspective, the transition to digitalized services is intended to support these transformations. A Health Information System (HIS) is a technological solution designed to govern the data flow generated and consumed by healthcare professionals and administrative staff during the delivery of healthcare services. However, the exponential growth of digital capabilities and applied advanced analytics has expanded their traditional functionalities and brought the promise of automating administrative procedures and simple repetitive tasks, while enhancing the efficiency and outcomes of healthcare services by incorporating decision support tools for clinical management. The future of HIS is headed towards modular architectures that can facilitate implementation and adaptation to different environments and systems, as well as the integration of various tools, such as artificial intelligence (AI) models, in a seamless way. As an example, we present the experience and future developments of the European Clinical Database (EuCliD®). EuCliD is a multilingual HIS used by 20 000 nurses and physicians on a daily basis to manage 105 000 patients treated in 1100 clinics in 43 different countries. EuCliD encompasses patients' follow-up, automatic reporting and mobile applications while enabling efficient management of clinical processes. It is also designed to incorporate multiagent systems to automate repetitive tasks, AI modules and advanced dynamic dashboards.

Data source profile reporting by studies that use routinely collected health data to explore the effects of drug treatment

BACKGROUND

Routinely collected health data (RCD) are important resource for exploring drug treatment effects. Adequate reporting of data source profiles may increase the credibility of evidence generated from these data. This study conducted a systematic literature review to evaluate the reporting characteristics of databases used by RCD studies to explore the effects of drug treatment.

METHODS

Observational studies published in 2018 that used RCD to explore the effects of drug treatment were identified by searching PubMed. We categorized eligible reports into two groups by journal impact factor (IF), including the top 5 general medical journals (NEJM, Lancet, JAMA, BMJ and JAMA Internal Medicine) and the other journals. The reporting characteristics of the databases used were described and compared between the two groups and between studies citing and not citing database references.

RESULTS

A total of 222 studies were included, of which 53 (23.9%) reported that they applied data linkage, 202 (91.0%) reported the type of database, and 211 (95.0%) reported the coverage of the data source. Only 81 (36.5%) studies reported the timeframe of the database. Studies in high-impact journals were more likely to report that they applied data linkage (65.1% vs. 20.2%) and used electronic medical records (EMR) (73.7% vs. 30.0%) and national data sources (77.8% vs. 51.3%) than those published in other medical journals. There were 137/222 (61.7%) cited database references. Studies with database-specific citations had better reporting of the data sources and were more likely to publish in high-impact journals than those without (mean IF, 6.08 vs. 4.09).

CONCLUSIONS

Some deficits were found in the reporting quality of databases in studies that used RCD to explore the effects of drug treatment. Studies citing database-specific references may provide detailed information regarding data source characteristics. The adoption of reporting guidelines and education on their use is urgently needed to promote transparency by research groups.

A Validated Algorithm for Register-Based Identification of Patients with Relapse of Clinical Stage I Testicular Cancer

Purpose

The Danish Testicular Cancer (DaTeCa) database aims to monitor and improve quality of care for testicular cancer patients. Relapse data registered in the DaTeCa database rely on manual registration. Currently, some safeguarding against missing registrations is attempted by a non-validated register-based algorithm. However, this algorithm is inaccurate and entails time-consuming medical record reviews. We aimed (1) to validate relapse data as registered in the DaTeCa database, and (2) to develop and validate an improved register-based algorithm identifying patients diagnosed with relapse of clinical stage I testicular cancer.

Patients and Methods

Patients registered in the DaTeCa database with clinical stage I testicular cancer from 2013 to 2018 were included. Medical record information on relapse data served as a gold standard. A pre-specified algorithm to identify relapse was tested and optimized on a random sample of 250 patients. Indicators of relapse were obtained from pathology codes in the Danish National Pathology Register and from diagnosis and procedure codes in the Danish National Patient Register. We applied the final algorithm to the remaining study population to validate its performance.

Results

Of the 1377 included patients, 284 patients relapsed according to the gold standard during a median follow-up time of 5.9 years. The completeness of relapse data registered in the DaTeCa database was 97.2% (95% confidence interval (CI): 95.2-99.1). The algorithm achieved a sensitivity of 99.6% (95% CI: 98.7-100), a specificity of 98.9% (95% CI: 98.2-99.6), and a positive predictive value of 95.9% (95% CI: 93.4-98.4) in the validation cohort (n = 1127, 233 relapses).

Conclusion

The registration of relapse data in the DaTeCa database is accurate, confirming the database as a reliable source for ongoing clinical quality assessments. Applying the provided algorithm to the DaTeCa database will optimize the accuracy of relapse data further, decrease time-consuming medical record review and contribute to important future clinical research.

Impact of time-varying exposure on estimated effects in observational studies using routinely collected data: protocol for a cross-sectional study

INTRODUCTION

Time-varying exposure is an important issue that should be addressed in longitudinal observational studies using routinely collected data (RCD) for drug treatment effects. How well investigators designed, analysed and reported time-varying exposure, and to what extent the divergence that can be observed between different methods used for handling time-varying exposure in these studies remains uncertain. We will conduct a cross-sectional study to comprehensively address this question.

METHODS AND ANALYSIS

We have developed a comprehensive search strategy to identify all studies exploring drug treatment effects including both effectiveness and safety that used RCD and were published in core journals between 2018 and 2020. We will collect information regarding general study characteristics, data source profile, methods for handling time-varying exposure, results and the interpretation of findings from each eligibility. Paired reviewers will screen and extract data, resolving disagreements through discussion. We will describe the characteristics of included studies, and summarise the method used for handling time-varying exposure in primary analysis and sensitivity analysis. We will also compare the divergence between different approaches for handling time-varying exposure using ratio of risk ratios.

ETHICS AND DISSEMINATION

No ethical approval is required because the data we will use do not include individual patient data. Findings will be disseminated through peer-reviewed publications.

Classifying outcomes in secondary and tertiary care clinical quality registries-an organizational case study with the COMET taxonomy

BACKGROUND

The choice of what patient outcomes are included in clinical quality registries is crucial for comparable and relevant data collection. Ideally, a uniform outcome framework could be used to classify the outcomes included in registries, steer the development of outcome measurement, and ultimately enable better patient care through benchmarking and registry research. The aim of this study was to compare clinical quality registry outcomes against the COMET taxonomy to assess its suitability in the registry context.

METHODS

We conducted an organizational case study that included outcomes from 63 somatic clinical quality registries in use at HUS Helsinki University Hospital, Finland. Outcomes were extracted and classified according to the COMET taxonomy and the suitability of the taxonomy was assessed.

RESULTS

HUS clinical quality registries showed great variation in outcome domains and in number of measures. Physiological outcomes were present in 98%, resource use in all, and functioning domains in 62% of the registries. Patient-reported outcome measures were found in 48% of the registries.

CONCLUSIONS

The COMET taxonomy was found to be mostly suitable for classifying the choice of outcomes in clinical quality registries, but improvements are suggested. HUS Helsinki University Hospital clinical quality registries exist at different maturity levels, showing room for improvement in life impact outcomes and in outcome prioritization. This article offers an example of classifying the choice of outcomes included in clinical quality registries and a comparison point for other registry evaluators.

The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records

Background

The Danish Myelodysplastic Syndromes Database (DMDSD) comprises nearly all patients diagnosed with myelodysplastic syndromes (MDS) in Denmark since 2010. The DMDSD has not yet been used for epidemiological research and the quality of registered variables remains to be investigated.

Objective

To describe characteristics of the patients registered in the DMDSD and to calculate predictive values and the proportion of missing values of registered data records.

Methods

We performed a nationwide cross-sectional validation study of recorded disease and treatment data on MDS patients during 2010-2019. Patient characteristics and the proportion of missing values were tabulated. A random sample of 12% was drawn to calculate predictive values with 95% confidence intervals (CIs) of 48 variables using information from medical records as a reference standard.

Results

Overall, 2284 patients were identified (median age: 76 years, men 62%). Of these, 10% had therapy-related MDS, and 6% had an antecedent hematological disease. Hemoglobin level was less than 6.2 mmol/L for 59% of patients. Within the first two years of treatment, 59% received transfusions, 35% received erythropoiesis-stimulating agents, and 15% were treated with a hypomethylating agent. For the majority of variables (around 80%), there were no missing data. A total of 260 medical records were available for validation. The positive predictive value of the MDS diagnosis was 92% (95% CI: 88-95). Predictive values ranged from 64% to 100% and exceeded 90% for 36 out of 48 variables. Stratification by year of diagnosis suggested that the positive predictive value of the MDS diagnosis improved from 88% before 2015 to 95% after.

Conclusion

In this study, there was a high accuracy of recorded data and a low proportion of missing data. Thus, the DMDSD serves as a valuable data source for future epidemiological studies on MDS.

Registrations of Patients with Renal Cell Carcinoma in the Nationwide Danish Renal Cancer Database versus the Danish Cancer Registry: Data Quality, Completeness and Survival (DaRenCa Study-3)

Background

The Danish multidisciplinary renal cancer group (DaRenCa) established the nationwide database DaRenCaData in 2010. The Danish Cancer Registry (DCR) has been considered the golden standard. In contrast to DCR, DaRenCaData required the diagnosis to be histologically or cytologically verified. DaRenCaData and DCR have not previously been compared.

Patients and Methods

We included patients with renal cell carcinoma registered in DaRenCaData and/or DCR from August 1st 2010 to December 31st 2015. We computed completeness and positive predictive value (PPV) of a diagnosis in DaRenCaData compared with DCR, 1-year, 3-year and 5-year mortality rate ratios, and relative survival.

Results

We identified 4890 patients in the two registries. Of these, 4326 were registered in DaRenCaData and 4714 in DCR. Completeness of DaRenCaData was 88% [95% CI, 87–89%] and increased during the period from 82% to 94%. The PPV was 96% [95% CI, 95–97%]. A total of 4150 patients (85%) were found in both registries, 4% (176 patients) in DaRenCaData only, and 12% (564 patients) in DCR only. The relative survival was higher for patients in DaRenCaData vs DCR; the 1-year and 5-year relative survival was 85% vs 81% and 65% vs 59%, respectively. Compared with patients registered in both registries, the mortality rates were higher in patients registered in DaRenCaData only (1-year hazard ratio (HR)=2.84 [95% CI, 2.20–3.68]) or DCR only (1-year HR=4.29 [95% CI, 3.72–4.93]). Observed in both registries, survival improved over time with a 7% yearly reduction in death based on estimations of 1-year mortality rate ratios.

Conclusion

DaRenCaData had high and increasing completeness and high PPV, establishing it as a high-quality research database. Observed in both registries, renal cell carcinoma mortality declined over time; patients only registered in DCR or DaRenCaData had poorer outcomes. This study points to the importance of assessing the inclusion criteria when interpreting registry-based studies.

Depression and cognitive sequelae registered within the first year among young Danish TBI survivors

The aim of the study was to determine the proportion of depression and cognitive sequelae among young (15-30 years) Danish TBI survivors referred to interdisciplinary evaluation through a nationwide government-initiated health initiative. The cross-sectional study is based on data from the "Danish register for young adults with acquired brain injury" on TBI survivors included from October 2013 to December 2016. The main measures were Major depression inventory, Trail making test A and B, Fluency, Word learning with selective reminding, Matrix reasoning, Coding and Glasgow outcome scale - extended (GOS-E). During the study period, 131 young TBI survivors were referred to one of five national outpatient clinics. Ninety-six had complete data and of these 14.6% fulfilled the ICD-10 diagnostic criteria for depression and 34.4% had cognitive sequelae. An association was found between depression and cognitive sequelae (p = 0.004). Patients with both depression and cognitive sequelae (n = 10) had a significantly lower mean score on GOS-E (p = 0.0001). Depression and cognitive sequelae were frequent and associated with a poorer global functional outcome among young TBI survivors referred within a year after trauma. This finding and the notion that only 20% of the expected TBI population was referred to this nationwide health initiative indicate an unacknowledged need for interdisciplinary follow-up.

Association between process performance measures and 1-year mortality among patients with incident heart failure: a Danish nationwide study

Aims

To examine the association between fulfilment of performance measures supported by clinical guidelines recommendations and 1-year mortality among patients with incident heart failure (HF) in Denmark.

Methods and results

A nationwide population-based follow-up study based on the Danish Heart Failure Registry. All Danish hospital departments caring for patients with HF. We identified 24 308 in- and outpatients diagnosed with HF from 2003 to 2010. Quality of care was defined as receiving the guideline recommended processes of care: use of echocardiography, New York Heart Association classification, treatment with angiotensin-converting-enzyme inhibitors/angiotensin-II-receptor blocker, beta blockers, physical training, and patient education. Main outcome measure is 1-year mortality. We used multiple imputation and multivariable Cox proportional hazard regression to compute hazard ratios (HRs) for 1-year mortality adjusted for potential confounding factors. Within 1 year, 17.1% of the patients died and the adjusted HRs ranged from 0.61 [95% confidence interval (CI) 0.55-0.67] for patient education to 0.99 (95% CI 0.90-1.10) for beta blocker therapy. The association between meeting more performance measures and 1-year mortality appeared to follow a dose-response pattern: using 0-25% of fulfilled measures as reference, patients who fulfilled 76-100% of the performance measures had an adjusted HR of 0.43 (95% CI 0.38-0.48), while the adjusted HR was 0.96 (95% CI 0.86-1.07) for patients who fulfilled between 26% and 50% of the performance measures.

Conclusion

Meeting process performance measures, which reflect care in concordance with clinical guideline recommendations, was associated with substantially lower 1-year mortality among patients with incident HF.

Prevalence and severity of fatigue in adolescents and young adults with acquired brain injury: A nationwide study

Objective: To investigate the prevalence and severity of fatigue in adolescents and young adults with acquired brain injury (ABI) compared with healthy controls (HCs) and to examine associations between fatigue and gender, age and level of education. Methods: This cross-sectional study included 15-30 year old patients with ABI and a convenience sample of 15-30 year old HCs. All participants completed the 20-item Multidimensional Fatigue Inventory (MFI-20). Pathological fatigue was defined as "General Fatigue" ≥12. Adjusted mean differences between groups were calculated using multivariate analysis of covariance (MANCOVA). The adjusted prevalence proportion ratio (PPR_adj) of pathological fatigue was calculated using Poisson regression. Results: The patients (n = 334) had higher scores than the HCs (n = 168) on all MFI-20 subscales with adjusted mean differences ranging from 1.7 to 4.7 and a higher prevalence of pathological fatigue (73% versus 29%), PPR_adj 2.7 (95% confidence interval 2.1-3.5). Female patients experienced more fatigue than males on the "General Fatigue" and "Reduced Activity" subscales, while no gender differences were found in the HC group. Patients and HCs with elementary education had elevated scores on the "Reduced Activity" and "Mental Fatigue" subscales. Age was not associated with any of the subscale scores. Conclusion: Young patients with ABI had markedly higher prevalence and severity of fatigue than HCs. Age (15-30 years) was not associated with fatigue. No clear patterns of associations were evident with gender and level of education. Abbreviations: ABI: acquired brain injury; CI: confidence interval; GF: general fatigue; GOSE: Glasgow Outcome Scale Extended; HC: healthy control; MANCOVA: multivariate analysis of covariance; MF: mental fatigue; MFI-20: Multidimensional Fatigue Inventory-20; PF: physical fatigue; RA: reduced activity; RM: reduced motivation; TBI: traumatic brain injury.

Reducing socioeconomic inequalities in COPD care in the hospital outpatient setting - A nationwide initiative

OBJECTIVE

Socioeconomic differences in quality of care have been suggested to contribute to inequality in clinical prognosis of COPD. We examined socioeconomic differences in the quality of COPD outpatient care and the potential of a systematic quality improvement initiative in reducing potential socioeconomic differences.

METHODS

A mandatory national quality improvement initiative has since 2008 monitored the quality of COPD care at all national pulmonary specialized outpatient clinics in Denmark using six evidence-based process performance measures. We followed patients aged ≥30 years with a first-ever outpatient contact for COPD during 2008-2012 (N = 23,741). Adjusted year-specific relative risks (RR) of fulfilling all relevant process performance measures was compared according to ethnicity, education, income, employment, and cohabitation using Poisson regression.

RESULTS

Quality of care improved following the implementation of the clinical improvement initiative with 11% of COPD patients receiving optimal care in 2008 compared to 57% in 2012. Substantial socioeconomic differences were observed the first year: immigrants (RR 0.41, 95% CI 0.21-0.82), the unemployed (RR 0.37, 95% CI 0.18-0.74), disability pensioners (RR 0.63, 95% CI 0.46-0.87) and patients living alone (RR 0.80, 95% CI 0.60-0.97) were less likely to receive all relevant care processes, whereas those with highest education (RR 1.22, 95% CI 0.92-1.63) were more likely to receive these processes. These differences were eliminated during the study period.

CONCLUSION

A systematic quality improvement initiative including regular audits, knowledge sharing, and detailed disease-specific recommendations for care improvement may increase the overall quality of care and considerably modify the substantial socioeconomic inequalities in COPD management.

The Danish Neuro-Oncology Registry: establishment, completeness and validity

Background

The Danish Neuro-Oncology Registry (DNOR) is a nationwide clinical cancer database that has prospectively registered data on patients with gliomas since January 2009. The purpose of this study was to describe the establishment of the DNOR and further to evaluate the database completeness of patient registration and validity of data.

Methods

The completeness of the number of patients registered in the database was evaluated in the study period from January 2009 through December 2014 by comparing cases reported to the DNOR with the Danish National Patient Registry and the Danish Pathology Registry. The data validity of important clinical variables was evaluated by a random sample of 100 patients from the DNOR using the medical records as reference.

Results

A total of 2241 patients were registered in the DNOR by December 2014 with an overall patient completeness of 92 %, which increased during the study period (from 78 % in 2009 to 96 % in 2014). Medical records were available for all patients in the validity analyses. Most variables showed a high agreement proportion (56–100 %), with a fair to good chance-corrected agreement (k = 0.43–1.0).

Conclusions

The completeness of patient registration was very high (92 %) and the validity of the most important patient data was good. The DNOR is a newly established national database, which is a reliable source for future scientific studies and clinical quality assessments among patients with gliomas.

The evolution of healthcare quality measurement in the United States

Quality measurement is fundamental to systematic improvement of the healthcare system. Whilst the United States has made significant investments in healthcare quality measurement and improvement, progress has been somewhat limited. Public and private payers in the United States increasingly mandate measurement and reporting as part of pay-for-performance programmes. Numerous issues have limited improvement, including lack of alignment in the use of measures and improvement strategies, the fragmentation of the U.S. healthcare system, and the lack of national electronic systems for measurement, reporting, benchmarking and improvement. Here, we provide an overview of the evolution of U.S. quality measurement efforts, including the role of the National Quality Forum. Important contextual changes such as the growing shift towards electronic data sources and clinical registries are discussed together with international comparisons. In future, the U.S. healthcare system needs to focus greater attention on the development and use of measures that matter. The three-part aim of effective care, affordable care and healthy communities in the U.S. National Quality Strategy focuses attention on population health and reduction in healthcare disparities. To make significant improvements in U.S. health care, a closer connection between measurement and both evolving national data systems and evidence-based improvement strategies is needed.