While much research has been done regarding \"palliative care\" using retrospective cohort studies of large datasets, the data sources may not be capturing specialty palliative care services. This article aims to clarify what source data are used in such studies, how specialty palliative care services are determined to have been provided or not, and mismatches between the nature of the data and the interpretation of researchers. Major US data sources that are examined include cancer registries such as the National Cancer Database; health systems\' internal data; state and nation-level hospital admissions data; and claims data from Medicare and commercial payers. Problematic studies are common. Many used cancer registry data and mischaracterized palliative intent for a given cancer treatment as \"palliative care services.\" Dozens relied on the diagnosis code for \"encounter for palliative care\" which lacks adequate validity for use in research. Researchers, peer-reviewers, and research consumers are cautioned about these potential pitfalls that lead to meaningless or misleading research papers. Suggestions are made regarding more rigorous methods and trustworthy data sources and additional research that can lead to consensus among researchers on these issues.

Background: Traumatic compartment syndrome is a critical condition that can lead to severe, lifelong disability. Methods: This retrospective study analyzed hospital billing data from 2015 to 2022, provided by the Federal Statistical Office of Germany, to examine the demographics and trends of traumatic compartment syndrome in Germany. The analysis included cases coded with ICD-10 codes T79.60 to T79.69 and any therapeutic OPS code starting with 5-79, focusing on diagnosis year, gender, ICD-10 code, and patient age. Results: The results showed that out of 13,305 cases, the majority were in the lower leg (44.4%), with males having a significantly higher incidence than females (2.3:1 ratio). A bimodal age distribution was observed, with peaks at 22-23 and 55 years. A notable annual decline of 43.87 cases in compartment syndrome was observed, with significant decreases across different genders and age groups, particularly in males under 40 (23.68 cases per year) and in the \"foot\" and \"lower leg\" categories (16.67 and 32.87 cases per year, respectively). Conclusions: The study highlights a declining trend in traumatic CS cases in Germany, with distinct demographic patterns. Through these findings, hospitals can adjust their therapeutic regimens, and it could increase awareness among healthcare professionals about this disease.

Asymptomatic bacteriuria and urinary tract infection in renal transplant are important antimicrobial stewardship targets but are difficult to identify within electronic medical records. We validated an \"electronic phenotype\" of antibacterials prescribed for these indications. This may be more useful than billing data in assessing antibiotic indication in this outpatient setting.

OBJECTIVE: To evaluate common surgical procedures and admission causes in inpatient cases with diabetes in Germany between 2015 and 2019 and compare them to inpatient cases without diabetes.
METHODS: Based on the German diagnosis-related groups (G-DRG) statistics, regression models stratified by age groups and gender were used to calculate hospital admissions/100,000 individuals, hospital days as well as the proportion of complications and mortality in inpatient cases ≥ 40 years with or without a documented diagnosis of diabetes (type 1 or type 2).
RESULTS: A total of 14,222,326 (21%) of all inpatient cases aged ≥ 40 years had a diagnosis of diabetes. More middle-aged females with vs. without diabetes/100,000 individuals [95% CI] were observed, most pronounced in cases aged 40-< 50 years with myocardial infarction (305 [293-319] vs. 36 [36-37], p < 0.001). Higher proportions of complications and longer hospital stays were found for all procedures and morbidities in cases with diabetes.
CONCLUSIONS: Earlier hospitalizations, longer hospital stays and more complications in inpatient cases with diabetes together with the predicted future increase in diabetes prevalence depict huge challenges for the German healthcare system. There is an urgent need for developing strategies to adequately care for patients with diabetes in hospital.

We validated  different coronavirus disease 2019 (COVID-19) International Classification of Diseases, Tenth Edition (ICD-10) encounter definitions across 2 urgent care clinics. Sensitivity of definitions varied throughout the pandemic. Inclusion of COVID-19 and COVID-19-like illness (CLI) ICD-10s rendered highest sensitivity but lowest specificity. Antibiotic prescribing rates were low for COVID-19 ICD-10 encounters, increasing with CLI ICD-10 encounters.

(1) Background: Administrative data allows for time- and cost-efficient acquisition of large volumes of individual patient data invaluable for evaluation of the prevalence of diseases and clinical outcomes. The aim of the study was to evaluate the accuracy of data collected from the Polish National Health Fund (NHF), from a researcher\'s perspective, in regard to a cohort of atrial fibrillation patients. (2) Methods: NHF data regarding atrial fibrillation and common cardiovascular comorbidities was compared with the data collected manually from the individual patients\' health records (IHR) collected in the retrospective CRAFT registry (NCT02987062). (3) Results: Data from the NHF underestimated the proportion of patients with AF (NHF = 83% vs. IHR = 100%) while overestimating the proportion of patients with other cardiovascular comorbidities in the cohort. Significantly higher CHA2DS2VASc (Median, [Q1-Q3]) (NHF: 1, [0-2]; vs. IHR: 1, [0-1]; p < 0.001) and HAS-BLED (Median, [Q1-Q3]) (NHF: 4, [2-6] vs. IHR: 3, [2-5]; p < 0.001) scores were calculated according to NHF in comparison to IHR data, respectively. (4) Conclusions: Clinical researchers should be aware that significant differences between IHR and billing data in cardiovascular research can be observed which should be acknowledged while drawing conclusions from administrative data-based cohorts. Natural Language Processing of IHR could further increase administrative data quality in the future.

Improved understanding of the pre- and postoperative trends in costs and healthcare resource utilization (HCRU) is needed to better inform patient expectations and aid in the development of strategies to minimize the significant healthcare burden associated with lumbar spine surgery.
Examine the time course of costs and HCRU in the 2 years preceding and following elective lumbar spine surgery for stenosis in a large national claims cohort.
Retrospective analysis of an administrative claims database (IBM® Marketscan® Research Databases 2007-2015).
Adult patients undergoing elective primary single-level lumbar surgery for stenosis with at least 2 years of continuous health plan enrollment pre- and postoperatively.
Functional measures, including monthly rates of HCRU (15 categories), monthly gross covered payments (including payments made by the health plan and deductibles and coinsurance paid by the patient) overall, by HCRU category, and by spine versus non-spine-related.
All available patients were utilized for analysis of HCRU. For analysis of payments, only patients on noncapitated health plans providing accurate financial information were analyzed. Payments were converted to 2015 United States dollars using the medical care component of the consumer price index. Trends in payments and HCRU were plotted on a monthly basis pre- and post-surgery and assessed with regression models. Relationships with demographics, surgical factors, and comorbidities were assessed with multivariable repeated measures generalized estimating equations.
Median monthly healthcare payments 2 years prior to surgery were $275 ($22, $868). Baseline HCRU at 2 years preoperatively was stable or only gradually rising (office visits, prescription drug use), but began an increasingly steep rise in many categories 6 to 12 months prior to surgery. Monthly payments began an increasingly steep rise 6 months prior to surgery, reaching a peak of $1,402 ($634, $2,827) in the month prior to surgery. This was driven by an increase in radiology, office visits, PT, injections, prescription medications, ER encounters, and inpatient admissions. Payments dropped dramatically immediately following surgery. Over the remainder of the 2 years, the median total payments declined only slightly, as a continued decline in spine-related payments was offset by gradually increased non-spine related payments as patients aged. By 2 years postoperatively, the percentage of patients using PT and injections returned to within 1% of the baseline levels observed 2 years preoperatively; however, spine-related prescription medication use remained elevated, as did other categories of HCRU (radiology, office visits, lab/diagnostic services, and also rare events such as inpatient admissions, ER encounters, and SNF/IRF). Patients with a fusion component to their surgeries had higher payments and HCRU preoperatively, and this did not resolve postoperatively. Variations in payments and HCRU were also evident among plan types, with patients on comprehensive medical plans-predominantly employer-sponsored supplemental Medicare coverage-utilizing more inpatient, ER, and inpatient rehabilitation & skilled nursing facilities. Patients on high-deductible plans had fewer payments and HCRU across all categories; however, we are unable to distinguish whether this is because they used fewer of these services or if they were paying for these services out of pocket without submitting to the payer. By 2 years postoperatively, 51% of patients had no spine-related monthly payments, while 33% had higher and 16% had lower monthly payments relative to 2 years preoperatively.
This is the first study to characterize time trends in direct healthcare payments and HCRU over an extended period preceding and following spine surgery. Differences among plan types potentially highlight disparities in access to care and plan-related financial mediators of patients\' healthcare resource utilization.

The collection of data on SARS-CoV‑2 tests is central to the assessment of the infection rate in the context of the COVID-19 pandemic. At the Robert Koch Institute (RKI), data collected from various laboratory data recording systems are consolidated. First, this article aims to exemplify significant aspects regarding test procedures. Subsequently the different systems for recording laboratory tests are described and test numbers from the RKI test laboratory query and the laboratory-based SARS-CoV‑2 surveillance as well as accounting data from the Association of Statutory Health Insurance Physicians for SARS-CoV‑2 laboratory tests are shown.Early in the pandemic, the RKI test laboratory query and the laboratory-based SARS-CoV‑2 surveillance became available and able to evaluate data on performed tests and test capacities. By recording the positive and negative test results, statements about the total number of tests and the proportion of positive test rates can be made. While the aggregate test numbers are largely representative nationwide, they are not always representative at the state and district level. The billing data of the Association of Statutory Health Insurance Physicians can complement the laboratory data afterwards. In addition, it can provide a retrospective assessment of the total number of SARS-CoV‑2 numbers in Germany, because the services provided by statutory health insurers (around 85% of the population in Germany) are included. The various laboratory data recording systems complement one another and the evaluations flow into the recommended measures for the pandemic response.
UNASSIGNED: Die Erfassung von Daten zu SARS-CoV-2-Testungen in Deutschland sind für die Einschätzung des Infektionsgeschehens im Rahmen der COVID-19-Pandemie von zentraler Bedeutung. Am Robert Koch-Institut (RKI) werden dazu die Daten aus verschiedenen Systemen zur Erfassung von Labortestungen zusammengeführt. In diesem Beitrag werden zunächst bedeutsame Aspekte der Testverfahren erläutert. Nachfolgend werden die unterschiedlichen Systeme zur Erfassung von Labortestungen erläutert und Testzahlen aus der RKI-Testlaborabfrage und der laborbasierten Surveillance SARS-CoV‑2 sowie die Abrechnungsdaten der kassenärztlichen Vereinigungen zu SARS-CoV-2-Labortestungen dargestellt.Mit der RKI-Testlaborabfrage und der laborbasierten Surveillance SARS-CoV‑2 stand früh in der Pandemie eine Surveillance zur Verfügung, mit der unter den teilnehmenden Laboren Daten zu durchgeführten Testungen und Testkapazitäten ausgewertet werden können. Durch die Erfassung von positiven und negativen Testergebnissen sind Aussagen zur Gesamtzahl der durchgeführten Testungen sowie dem Anteil der positiven Testergebnisse möglich. Während die aggregierten Testzahlen bundesweit weitestgehend repräsentativ sind, ist die Repräsentativität auf Bundesland- und Landkreisebene aber nicht immer gegeben. Die Abrechnungsdaten der Kassenärztlichen Vereinigungen können die Labordaten im Nachhinein ergänzen. Sie erlauben eine retrospektive Einschätzung der Gesamtzahl von SARS-CoV-2-Tests in Deutschland, da die Leistungen der vertragsärztlichen Versorgung aller gesetzlich Krankenversicherten (ca. 85 % der Bevölkerung) enthalten sind.Die verschiedenen Systeme zur Erfassung von Labortestungen ergänzen sich gegenseitig. Die Auswertungen fließen in die Maßnahmenempfehlungen zur Pandemiebewältigung ein.

BACKGROUND: The objective of the research consortium PROCLAIR was to gain population level knowledge on the treatment of patients with rheumatoid arthritis (RA), axial spondylarthritis (axSpA) and osteoarthritis (OA) in Germany.
OBJECTIVE: A main question of the consortium was whether it is possible to identify groups of people who were exposed to a particular risk of undersupply or oversupply of treatment. In addition, the study investigated the validity of claims data for these diseases as a basis for further studies.
METHODS: Cross-sectional surveys were carried out among insurees of the BARMER statutory health insurance fund whose claims data included RA, axSpA and OA diagnoses. The questionnaire data were linked with the claims data of the insured persons if they agreed.
RESULTS: In all three diseases risk groups for care deficits could be identified. Persons with RA who are not treated by a specialist have less access to drug treatment. Physical therapy is prescribed for all three diagnoses at a low level, even for people undergoing joint replacement surgery. A connection between depressive symptoms and disease activity or function in axSpA was shown. In addition to the results relevant to care, the PROCLAIR network has also made contributions to critically assess the quality of health insurance data.
CONCLUSIONS: The combination of billing data with survey data enables a comprehensive description of the treatment of musculoskeletal diseases. Particularly relevant factors are the specialization of the physician, sociodemographic parameters of the patients and the region of residence. In particular, access to treatment cannot be investigated in randomized clinical trials.

BACKGROUND: The objective of the research consortium PROCLAIR was to gain population level knowledge on the treatment of patients with rheumatoid arthritis (RA), axial spondylarthritis (axSpA) and osteoarthritis (OA) in Germany.
OBJECTIVE: A main question of the consortium was whether it is possible to identify groups of people who were exposed to a particular risk of undersupply or oversupply of treatment. In addition, the study investigated the validity of claims data for these diseases as a basis for further studies.
METHODS: Cross-sectional surveys were carried out among insurees of the BARMER statutory health insurance fund whose claims data included RA, axSpA and OA diagnoses. The questionnaire data were linked with the claims data of the insured persons if they agreed.
RESULTS: In all three diseases risk groups for care deficits could be identified. Persons with RA who are not treated by a specialist have less access to drug treatment. Physical therapy is prescribed for all three diagnoses at a low level, even for people undergoing joint replacement surgery. A connection between depressive symptoms and disease activity or function in axSpA was shown. In addition to the results relevant to care, the PROCLAIR network has also made contributions to critically assess the quality of health insurance data.
CONCLUSIONS: The combination of billing data with survey data enables a comprehensive description of the treatment of musculoskeletal diseases. Particularly relevant factors are the specialization of the physician, sociodemographic parameters of the patients and the region of residence. In particular, access to treatment cannot be investigated in randomized clinical trials.