Regional differences in the validity of self-reported use of health care in Belgium: selection versus reporting bias

Linking health survey data with health insurance data: methodology, challenges, opportunities and recommendations for public health research. An experience from the HISlink project in Belgium

In recent years, the linkage of survey data to health administrative data has increased. This offers new opportunities for research into the use of health services and public health. Building on the HISlink use case, the linkage of Belgian Health Interview Survey (BHIS) data and Belgian Compulsory Health Insurance (BCHI) data, this paper provides an overview of the practical implementation of linking data, the outcomes in terms of a linked dataset and of the studies conducted as well as the lessons learned and recommendations for future links.Individual BHIS 2013 and 2018 data was linked to BCHI data using the national register number. The overall linkage rate was 92.3% and 94.2% for HISlink 2013 and HISlink 2018, respectively. Linked BHIS-BCHI data were used in validation studies (e.g. self-reported breast cancer screening; chronic diseases, polypharmacy), in policy-driven research (e.g., mediation effect of health literacy in the relationship between socioeconomic status and health related outcomes, and in longitudinal study (e.g. identifying predictors of nursing home admission among older BHIS participants). The linkage of both data sources combines their strengths but does not overcome all weaknesses.The availability of a national register number was an asset for HISlink. Policy-makers and researchers must take initiatives to find a better balance between the right to privacy of respondents and society's right to evidence-based information to improve health. Researchers should be aware that the procedures necessary to implement a link may have an impact on the timeliness of their research. Although some aspects of HISlink are specific to the Belgian context, we believe that some lessons learned are useful in an international context, especially for other European Union member states that collect similar data.

Agreement between self-reports and statutory health insurance claims data on healthcare utilization in patients with mental disorders

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).

A multisource approach to health care use: concordance between register and self-reported physician visits in the foreign-born population in Finland

BACKGROUND

Reliable information on the use of health services is important for health care planning, monitoring and policy. It is critical to assess the validity of the sources used for this purpose, including register and survey-based data. Studies on foreign-born populations' health care use have usually implemented either survey or register data. The concordance of such data among groups of different cultural background remains largely unknown. In this study, we presented an approach to examine routinely how survey and register-related characteristics may explain disagreement found between the two information sources.

METHODS

We linked register- and survey-based data pertaining to the Finnish Register of Primary Health Care general physician visits and the Survey on Well-Being among Foreign Born Population (FinMonik, 2018-2019), a nationally representative survey. The sample comprised n = 5,800 informants for whom registered general physician visits were tracked in the 12-month period preceding their participation in the survey. Cohen's kappa was used as measure of multisource concordance, hierarchical loglinear models for the association between single predictors and multisource discrepancy, and a logistic regression model for examining source-related predictors of source discrepancy. Survey weights were used in all sample analyses.

RESULTS

Source concordance was poor. When dichotomizing general physician visits (zero vs one or more), 35% of informants had reported one or more visits while none were found from register. Both register- and informant-related predictors were associated to this discrepancy (i.e. catchment area, private health care use, inability to work, region of origin and reason for migration).

CONCLUSIONS

We found high discrepancy between the reported and the registered physician visits among the foreign-born population in Finland, with a particularly high number of reported physician visits when none were found in the register. There was a strong association between the specific catchment area and mismatch, indicating that both register under-coverage and survey over-report are plausible and may coexist behind the discrepancy. However, associations of informant's characteristics and mismatch were less pronounced. Implications on the validity of medical information sources are discussed.

Validity of self-reported mammography uptake in the Belgian health interview survey: selection and reporting bias

BACKGROUND

The validity of self-reported mammography uptake is often questioned. We assessed the related selection and reporting biases among women aged 50-69 years in the Belgian Health Interview Survey (BHIS) using reimbursement data for mammography stemming from the Belgian Compulsory Health Insurance organizations (BCHI).

METHODS

Individual BHIS 2013 data (n = 1040) were linked to BCHI data 2010-13 (BHIS-BCHI sample). Being reimbursed for mammography within the last 2-years was used as the gold standard. Selection bias was assessed by comparing BHIS estimates reimbursement rates in BHIS-BCHI with similar estimates from the Echantillon Permanent/Permanente Steekproef (EPS), a random sample of BCHI data, while reporting bias was investigated by comparing self-reported versus reimbursement information in the BHIS-BCHI. Reporting bias was further explored through measures of agreement and logistic regression.

RESULTS

Mammography uptake rates based on self-reported information and reimbursement from the BHIS-BCHI were 75.5% and 69.8%, respectively. In the EPS, it was 64.1%. The validity is significantly affected by both selection bias {relative size = 8.93% [95% confidence interval (CI): 3.21-14.64]} and reporting bias [relative size = 8.22% (95% CI: 0.76-15.68)]. Sensitivity was excellent (93.7%), while the specificity was fair (66.4%). The agreement was moderate (kappa = 0.63). Women born in non-EU countries (OR = 2.81, 95% CI: 1.54-5.13), with high household income (OR = 1.27, 95% CI: 1.02-1.60) and those reporting poor perceived health (OR = 1.41, 95% CI: 1.14-1.73) were more likely to inaccurately report their mammography uptake.

CONCLUSIONS

The validity of self-reported mammography uptake in women aged 50-69 years is affected by both selection and reporting bias. Both administrative and survey data are complementary when assessing mammography uptake.

Ambulatory and stationary healthcare use in survivors of ARDS during the first year after discharge from ICU: findings from the DACAPO cohort

Background

For many survivors of acute respiratory distress syndrome (ARDS), the process from discharge from intensive care unit (ICU) to recovery is long and difficult. However, healthcare use after discharge from ICU has received only little attention by research. This study sets out to investigate the extent of ambulatory and stationary healthcare use among survivors of ARDS in Germany (multicenter DACAPO cohort) and to analyze predictors of stationary healthcare use.

Results

A total of 396 survivors of ARDS provided data at 1 year after discharge from ICU. Fifty percent of 1-year survivors were hospitalized for 48 days or longer after discharge from ICU, with 10% spending more than six out of 12 months in stationary care. The duration of hospitalization increased significantly by the length of the initial ICU stay. All participants reported at least one outpatient visit (including visits to general practitioners), and 50% contacted four or more different medical specialties within the first year after discharge from ICU.

Conclusions

For most of the patients, the first year after ARDS is characterized by an extensive amount of healthcare utilization, especially with regard to stationary health care. These findings shed light on the substantial morbidity of patients after ARDS and contribute to a better understanding of the situation of patients following discharge from ICU.

Effects of perceptions of care, medical advice, and hospital quality on patient satisfaction after primary total knee replacement: A cross-sectional study

Introduction

The increase in the number of patients presenting with osteoarthritis in the past decade has led to a 32% increase in knee replacement surgeries designed to reduce restrictions on patient movement and improve their quality of life. Patient satisfaction is becoming an increasingly important indicator of quality of care. This study was designed to identify predictors of various service components in the treatment process and hospital key performance indicators significantly associated with patient satisfaction.

Materials and methods

A multicenter cross-sectional study was conducted with 856 patients having their primary total knee replacements at 41 hospitals. Patient satisfaction was queried via a validated, multidimensional questionnaire mainly using a six-point scale. In addition to bivariate calculations, patient satisfaction was the dependent variable in a binary logistic regression model.

Results

The bivariate analysis showed a strong association between satisfaction and sex (male or female), the patients’ health before admission, and the length of stay. The number of cases treated at each hospital did not reveal any impact on satisfaction. The multivariate analysis identified three predictors associated with overall satisfaction. The strongest factor was the treatment outcome and the weakest was the quality of food. It became apparent that the statutory procedure minimums were not being met.

Conclusions

The relevant factors influencing patient satisfaction were partially the same as previous study results and allowed more detailed conclusions. The results provide suggestions across hospitals that could help health care providers better meet needs of patients after knee arthroplasties.