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Consideration of ICD-9 code-derived disease-specific safety indicators in CKD.

ABSTRACT: The Agency for Healthcare and Research Quality patient safety indicators track adverse safety events in hospitalized patients but overlook safety incidents specific to CKD. This study considers candidate CKD-pertinent patient safety indicators and compares them with the Agency for Healthcare and Research Quality patient safety indicators.Using a national Veterans Health Administration database of hospitalized veterans from fiscal year 2005, 247,160 hospitalized veterans with prehospitalization measures of renal function were retrospectively examined for proposed CKD patient safety indicators versus Agency for Healthcare and Research Quality patient safety indicators using International Classification of Diseases, Ninth Revision diagnosis codes. Candidate CKD-pertinent patient safety indicators included in-hospital acute kidney failure; in-hospital congestive heart failure (and related diagnostic codes); electrolyte disturbances; and medication errors, poisoning, and intoxication. Patients with a prehospital estimated GFR<60 ml/min per 1.73 m(2) (CKD group) were compared with a non-CKD group. For CKD patient safety indicators, hospitalizations were excluded if the admitting condition was a potential cause of the secondary condition. Regression methods were used to present adjusted rates in study groups of interest.The CKD patient safety indicators were generally more common than the Agency for Healthcare and Research Quality patient safety indicators in all groups, tended to occur in different patients than those patients who experienced Agency for Healthcare and Research Quality patient safety indicators, and were more common in the CKD group than the non-CKD group, except for hypoglycemia, hypokalemia, and hyponatremia. The adjusted composite CKD patient safety indicators rate (per 1000 patient-hospitalizations) was 398.0 (95% confidence interval, 391.2 to 405.0) for patients in the CKD group and 250.0 (95% confidence interval, 247.4 to 252.7) for patients in the non-CKD group. The prevalence ratio of CKD patient safety indicators to Agency for Healthcare and Research Quality patient safety indicators was 23.4 (95% confidence interval, 21.9 to 25.0).The candidate CKD patient safety indicators that occur in hospitalized patients are distinct from the Agency for Healthcare and Research Quality patient safety indicators and tend to be more common in CKD than non-CKD patients. These measures have the potential to serve as sentinel tools for identifying patients with CKD who warrant examination for disease-pertinent safety events.

SUBMITTER: Hartley IR

PROVIDER: S-EPMC3848413 | biostudies-other | 2013 Dec

REPOSITORIES: biostudies-other

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Consideration of ICD-9 code-derived disease-specific safety indicators in CKD.

Hartley Iris R IR Ginsberg Jennifer S JS Diamantidis Clarissa J CJ Zhan Min M Walker Loreen L Rattinger Gail B GB Fink Jeffrey C JC

Clinical journal of the American Society of Nephrology : CJASN 20130919 12

<h4>Background and objectives</h4>The Agency for Healthcare and Research Quality patient safety indicators track adverse safety events in hospitalized patients but overlook safety incidents specific to CKD. This study considers candidate CKD-pertinent patient safety indicators and compares them with the Agency for Healthcare and Research Quality patient safety indicators.<h4>Design, setting, participants, & measurements</h4>Using a national Veterans Health Administration database of hospitalized ...[more]

PMID: 24052221

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Project description:BACKGROUND:Quantifying the burden of multimorbidity for healthcare research using administrative data has been constrained. Existing measures incompletely capture chronic conditions of relevance and are narrowly focused on risk-adjustment for mortality, healthcare cost or utilization. Moreover, the measures have not undergone a rigorous review for how accurately the components, specifically the International Classification of Diseases, Ninth Revision (ICD-9) codes, represent the chronic conditions that comprise the measures. We performed a comprehensive, structured literature review of research studies on the accuracy of ICD-9 codes validated using external sources across an inventory of 81 chronic conditions. The conditions as a weighted measure set have previously been demonstrated to impact not only mortality but also physical and mental health-related quality of life. METHODS:For each of 81 conditions we performed a structured literature search with the goal to identify 1) studies that externally validate ICD-9 codes mapped to each chronic condition against an external source of data, and 2) the accuracy of ICD-9 codes reported in the identified validation studies. The primary measure of accuracy was the positive predictive value (PPV). We also reported negative predictive value (NPV), sensitivity, specificity, and kappa statistics when available. We searched PubMed and Google Scholar for studies published before June 2019. RESULTS:We identified studies with validation statistics of ICD-9 codes for 51 (64%) of 81 conditions. Most of the studies (47/51 or 92%) used medical chart review as the external reference standard. Of the validated using medical chart review, the median (range) of mean PPVs was 85% (39-100%) and NPVs was 91% (41-100%). Most conditions had at least one validation study reporting PPV ?70%. CONCLUSIONS:To help facilitate the use of patient-centered measures of multimorbidity in administrative data, this review provides the accuracy of ICD-9 codes for chronic conditions that impact a universally valued patient-centered outcome: health-related quality of life. These findings will assist health services studies that measure chronic disease burden and risk-adjust for comorbidity and multimorbidity using patient-centered outcomes in administrative data.

Project description:Electronic health records (EHR) provide a comprehensive resource for discovery, allowing unprecedented exploration of the impact of genetic architecture on health and disease. The data of EHRs also allow for exploration of the complex interactions between health measures across health and disease. The discoveries arising from EHR based research provide important information for the identification of genetic variation for clinical decision-making. Due to the breadth of information collected within the EHR, a challenge for discovery using EHR based data is the development of high-throughput tools that expose important areas of further research, from genetic variants to phenotypes. Phenome-Wide Association studies (PheWAS) provide a way to explore the association between genetic variants and comprehensive phenotypic measurements, generating new hypotheses and also exposing the complex relationships between genetic architecture and outcomes, including pleiotropy. EHR based PheWAS have mainly evaluated associations with case/control status from International Classification of Disease, Ninth Edition (ICD-9) codes. While these studies have highlighted discovery through PheWAS, the rich resource of clinical lab measures collected within the EHR can be better utilized for high-throughput PheWAS analyses and discovery. To better use these resources and enrich PheWAS association results we have developed a sound methodology for extracting a wide range of clinical lab measures from EHR data. We have extracted a first set of 21 clinical lab measures from the de-identified EHR of participants of the Geisinger MyCodeTM biorepository, and calculated the median of these lab measures for 12,039 subjects. Next we evaluated the association between these 21 clinical lab median values and 635,525 genetic variants, performing a genome-wide association study (GWAS) for each of 21 clinical lab measures. We then calculated the association between SNPs from these GWAS passing our Bonferroni defined p-value cutoff and 165 ICD-9 codes. Through the GWAS we found a series of results replicating known associations, and also some potentially novel associations with less studied clinical lab measures. We found the majority of the PheWAS ICD-9 diagnoses highly related to the clinical lab measures associated with same SNPs. Moving forward, we will be evaluating further phenotypes and expanding the methodology for successful extraction of clinical lab measurements for research and PheWAS use. These developments are important for expanding the PheWAS approach for improved EHR based discovery.

Project description:Rationale & Objective:Data from patients in one delivery system have suggested that the prevalence of chronic kidney disease (CKD) awareness differs by how the question is asked. We examined the sensitivity and specificity of different CKD awareness questions among diverse community-dwelling adults who were not necessarily engaged in primary care to determine the generalizability of prior results. Study Design:Cross-sectional study. Setting & Participants:Participants in the Healthy Aging in Neighborhoods of Diversity Across the Life Span (HANDLS) Study. Predictor:CKD awareness, ascertained using 5 different questions. Outcome:Sensitivity and specificity of each awareness question, using laboratory results as the gold standard. Analytic Approach:Logistic regression was used to compare sensitivities of different awareness questions. Results:Among 2,046 participants, mean (SD) age was 56.5 (9.1) years, 41.5% were men, and 61.3% were African American. More than 40% were poor, 35% reported not having health insurance, and 16.9% had low health literacy. More than 20% (n = 424) had CKD. Sensitivities of single CKD awareness questions ranged from 2.2% for "kidney damage" to 5.2% for "kidney problem." Sensitivity of the compound question asking about "weak kidneys, failing kidneys, or kidney disease" was 19.5%. Sensitivity of this compound CKD awareness question was higher among study participants with more advanced CKD and low health literacy, and those who lived below the poverty level. Limitations:Single measures of estimated glomerular filtration rate and albuminuria; study participants may have been more engaged in their health care than the average US adult, potentially limiting the generalizability of results. Conclusions:CKD awareness is low among community-dwelling adults with kidney disease, though data using a sensitive compound question ascertaining awareness suggest that we have met the Healthy People 2020 goal related to CKD awareness of 13.4%. Understanding the phrases about kidney disease that are most understandable to patients with and at risk for CKD is important to further increase CKD awareness.

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Consideration of ICD-9 code-derived disease-specific safety indicators in CKD.

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Consideration of ICD-9 code-derived disease-specific safety indicators in CKD.

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