Association between practice coding of chronic kidney disease (CKD) in primary care and subsequent hospitalisations and death: a cohort analysis using national audit data

Uncoded chronic kidney disease prevalence in secondary care: a retrospective audit with population health implications

BACKGROUND

One million patients are estimated to have undiagnosed chronic kidney disease (CKD) in England. Clinical coding in CKD is associated with improved management and lower acute kidney injury (AKI), unscheduled care and mortality risk. Primary care's role in coding CKD is well documented. However, there is scant evidence on CKD coding quality in secondary care. Primary aims: to measure total and coded/uncoded CKD prevalence on admission and discharge, and conversion of uncoded to coded CKD in secondary care. Secondary aims: to map coding status to kidney health inequality themes and to measure predictors of coding, death and AKI.

METHODS

Retrospective audit in an acute medical hospital ward in England, April 2022-February 2023. Descriptive statistics include counts/percentages for categorical data, prevalence estimates and rates. Logistic regression measured significant predictors (p = < 0.05) of receiving a diagnostic CKD code on discharge, risk of death, and of AKI.

RESULTS

Uncoded CKD prevalence using discharge estimated GFR (eGFR) was 58.7% (n = 283), equating to 1.1 cases uncoded CKD per bed/month and 13.7 cases uncoded CKD per bed/year. Conversion of uncoded to coded CKD at discharge was only 6.7%. Hypertension and advanced CKD were significant predictors of coding CKD on discharge in uncoded patients. Age, sex, indices of multiple deprivation, and AKI were significant predictors of death during admission. Advanced CKD was a significant predictor of AKI during admission.

CONCLUSIONS

Uncoded CKD is highly prevalent in an acute medical hospital ward highlighting opportunity to improve coding in another part of the health system in addition primary care.

An updated systematic review of the risk factors for unplanned dialysis initiation

Background

Previously, a comprehensive review of the risk factors for unplanned dialysis initiation (UDI) was conducted by Hassan et al. (2019), based on studies published up to the end of 2017. They demonstrated that high-quality data and well-designed studies on the subject are lacking. Thus we updated their review to establish the modifiable factors associated with UDI.

Methods

MEDLINE and Embase were searched from January 2018 to August 2023. Following several rounds of screening, we identified 17 international studies (the majority of which were based in Europe) that met the eligibility criteria.

Results

Many of the included studies were well designed, utilised large datasets and adopted properly adjusted analyses to examine associations between patient characteristics and UDI. Definitions of UDI varied across studies, i.e. timeliness of presentation, vascular access type, initiating dialysis as an inpatient/outpatient or for life-threatening indications. The most common risk factors reported were cardiovascular disease, older age, lower body mass index, cause of kidney disease, cancer, diabetes, lower serum albumin, faster decline in kidney function and fewer number of nephrology visits prior to dialysis start. These were in line with those reported by Hassan et al., however, our updated review revealed several other important predictors of UDI, e.g. worse coding of chronic kidney disease in the general practitioner health record, lower health literacy and having acute kidney injury.

Conclusions

Our review provides new insights into reasons why people start dialysis in an unplanned manner, many of which are modifiable, thus contributing to efforts in reducing the rate of UDI.

Referral, monitoring, and factors associated with non-referral of chronic kidney disease in Germany: a nationwide, retrospective cohort study

Background

Chronic kidney disease (CKD) is one of the most significant drivers of the global burden of disease and an increasing public health issue. Adequate monitoring and referral of high-risk patients to nephrologists are associated with improved management of CKD. We aimed to assess nephrology referral rates, monitoring of kidney function, and factors associated with failure to refer in Germany.

Methods

We retrospectively analyzed ambulatory claims data of 73,675,956 German patients who were covered by statutory health care in 2022, building a cohort of 1,301,122 patients who had at least two diagnoses of CKD stage 3-5 within the calendar year. In our analysis, we focused particularly on patients with CKD stage 4.

Findings

We identified 207,043 patients with CKD stage 4, of which 134,143/207,043 (64.8%) received nephrologist treatment in 2022. The median age of the cohort was 82 years. Failure to quantify proteinuria occurred in 61,991/72,900 (85.0%) non-referred patients compared to 51,382/134,143 (38.3%) referred patients. In a mixed logistic regression model, referral was less likely for women (odds ratio [OR] 0.72, 95% confidence interval [CI] 0.71-0.74), higher age (OR per year 0.97, CI 0.96-0.97), nursing home inhabitants (OR 0.63, CI 0.61-0.65), and those with certain comorbidities. Regional factors (deprivation, population density, nephrologist density) were not associated with referral.

Interpretation

A substantial proportion of patients with late-stage CKD are not receiving guideline-recommended kidney care in the German health care system, with disparities driven primarily by individual patient factors rather than geographical barriers.

Funding

This study was funded by the University Hospital Schleswig-Holstein and the Central Research Institute of Ambulatory Health Care in Germany.

Diagnosis codes underestimate chronic kidney disease incidence compared with eGFR-based evidence: a retrospective observational study of patients with type 2 diabetes in UK primary care

BACKGROUND

Type two diabetes (T2D) is a leading cause of both chronic kidney disease (CKD) and onward progression to end-stage renal disease. Timely diagnosis coding of CKD in patients with T2D could lead to improvements in quality of care and patient outcomes.

AIM

To assess the consistency between estimated glomerular filtration rate (eGFR)-based evidence of CKD and CKD diagnosis coding in UK primary care.

DESIGN & SETTING

A retrospective analysis of electronic health record data in a cohort of people with T2D from 60 primary care centres within England between 2012 and 2022.

METHOD

We estimated the incidence rate of CKD per 100 person-years using eGFR-based CKD and diagnosis codes. Logistic regression was applied to establish which attributes were associated with diagnosis coding. Time from eGFR-based CKD to entry of a diagnosis code was summarised using the median and interquartile range.

RESULTS

The overall incidence of CKD was 2.32 (95% confidence interval [CI] = 2.24 to 2.41) and significantly higher for eGFR-based criteria than diagnosis codes: 1.98 (95% CI = 1.90 to 2.05) versus 1.06 (95% CI = 1.00 to 1.11), respectively; P<0.001. Only 45.4% of CKD incidences identified using eGFR-based criteria had a corresponding diagnosis code. Patients who were younger, had a higher CKD stage (G4), had an observed urine albumin-to-creatinine ratio (A1), or no observed HbA1c in the past year were more likely to have a diagnosis code.

CONCLUSION

Diagnosis coding of patients with eGFR-based evidence of CKD in UK primary care is poor within patients with T2D, despite CKD being a well-known complication of diabetes.