Challenges and remediation for Patient Safety Indicators in the transition to ICD-10-CM
01 Jan 2015-Journal of the American Medical Informatics Association (Oxford University Press)-Vol. 22, Iss: 1, pp 19-28
TL;DR: This work provides the first report of substantial hospital safety reporting errors with five direct comparisons from the 23 types of PSIs (transfusion and anesthesia related PSIs), and investigates which PSIs would reliably transition between ICD-9-CM and I CDD-10-CM, and those at risk of under-reporting and over-reporting adverse events while the frequency of these adverse events remain unchanged.
About: This article is published in Journal of the American Medical Informatics Association.The article was published on 2015-01-01 and is currently open access. It has received 19 citations till now. The article focuses on the topics: Diagnosis code & Patient safety.
Citations
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12 Apr 2016
TL;DR: It appears that for clinically distinct and homogenous conditions, the recall of FBM is sufficient, and different mapping approaches yield different collections of ICD-10-CM codes.
Abstract: Background: The national mandate for health systems to transition from ICD-9-CM to ICD-10-CM in October 2015 has an impact on research activities. Clinical phenotypes defined by ICD-9-CM codes need to be converted to ICD-10-CM, which has nearly four times more codes and a very different structure than ICD-9-CM. Methods: We used the Centers for Medicare & Medicaid Services (CMS) General Equivalent Maps (GEMs) to translate, using four different methods, condition-specific ICD-9-CM code sets used for pragmatic trials (n=32) into ICD-10-CM. We calculated the recall, precision, and F‑score of each method. We also used the ICD-9-CM and ICD-10-CM value sets defined for electronic quality measure as an additional evaluation of the mapping methods. Results: The forward-backward mapping (FBM) method had higher precision, recall and F‑score metrics than simple forward mapping (SFM). The more aggressive secondary (SM) and tertiary mapping (TM) methods resulted in higher recall but lower precision. For clinical phenotype definition, FBM was the best (F=0.67), but was close to SM (F=0.62) and TM (F=0.60), judging on the F‑scores alone. The overall difference between the four methods was statistically significant (one-way ANOVA, F=5.749, p=0.001). However, pairwise comparisons between FBM, SM, and TM did not reach statistical significance. A similar trend was found for the quality measure value sets. Discussion: The optimal method for using the GEMs depends on the relative importance of recall versus precision for a given use case. It appears that for clinically distinct and homogenous conditions, the recall of FBM is sufficient. The performance of all mapping methods was lower for heterogeneous conditions. Since code sets used for phenotype definition and quality measurement can be very similar, there is a possibility of cross-fertilization between the two activities. Conclusion: Different mapping approaches yield different collections of ICD-10-CM codes. All methods require some level of human validation.
53 citations
Cites result from "Challenges and remediation for Pati..."
...seem to favor an approach similar to SM, but they did not explain why, nor did they compare the various mapping methods quantitatively.(21,25,29) In our study, the different methods are compared quantitatively, and their strengths and weakness are highlighted....
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TL;DR: To describe the consistency in the frequency of 5 health outcomes across the International Classification of Diseases, Ninth Revision, clinical Modification and Tenth Revision, Clinical Modification eras in the US, ICD‐9‐CM is used.
Abstract: Purpose To describe the consistency in the frequency of 5 health outcomes across the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and Tenth Revision, Clinical Modification (ICD-10-CM) eras in the US. Methods We examined the incidence of 3 acute conditions (acute myocardial infarction [AMI], angioedema, ischemic stroke) and the prevalence of 2 chronic conditions (diabetes, hypertension) during the final 5 years of the ICD-9-CM era (January 2010-September 2015) and the first 15 months of the ICD-10-CM era (October 2015-December 2016) in 13 electronic health care databases in the Sentinel System. For each health outcome reviewed during the ICD-10-CM era, we evaluated 4 definitions, including published algorithms derived from other countries, as well as simple-forward, simple-backward, and forward-backward mapping using the General Equivalence Mappings. For acute conditions, we also compared the incidence between April to December 2014 and April to December 2016. Results The analyses included data from approximately 172 million health plan members. While the incidence or prevalence of AMI and hypertension performed similarly across the 2 eras, the other 3 outcomes did not demonstrate consistent trends for some or all the ICD-10-CM definitions assessed. Conclusions When using data from both the ICD-9-CM and ICD-10-CM eras, or when using results from ICD-10-CM data to compare to results from ICD-9-CM data, researchers should test multiple ICD-10-CM outcome definitions as part of sensitivity analysis. Ongoing assessment of the impact of ICD-10-CM transition on identification of health outcomes in US electronic health care databases should occur as more data accrue.
43 citations
Cites methods from "Challenges and remediation for Pati..."
...Thus, it is important to identify how the transition from ICD‐9‐ CM to ICD‐10‐CM in the US may impact the identification of health outcomes commonly assessed in medical product safety studies.(3-5) In this descriptive study, we explore the consistency of the incidence of 3 acute health outcomes (acute myocardial infarction [AMI], angioedema, ischemic stroke) and the prevalence of 2 chronic health outcomes (diabetes, hypertension) across the ICD‐9‐CM and ICD‐10‐CM eras in 13 electronic health care databases in the US, and compare the performance of 4 different approaches used to define each health outcome in the ICD‐10‐CM era....
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TL;DR: It is found that most women do not achieve optimal weight gain during pregnancy, and low weight gain was associated with increased risk of severe adverse birth outcomes, and in particular with maternal death and perinatal death.
Abstract: Background Suboptimal weight gain during pregnancy is a potentially modifiable risk factor. We aimed to investigate the association between suboptimal gestational weight gain and severe adverse birth outcomes by pre-pregnancy body mass index (BMI) categories, including obesity class I to III. Methods and findings We conducted a population-based study of pregnant women with singleton hospital births in Washington State, US, between 2004 and 2013. Optimal, low, and excess weight gain in each BMI category was calculated based on weight gain by gestational age as recommended by the American College of Obstetricians and Gynecologists and the Institute of Medicine. Primary composite outcomes were (1) maternal death and/or severe maternal morbidity (SMM) and (2) perinatal death and/or severe neonatal morbidity. Logistic regression was used to obtain adjusted odds ratios (AORs) and 95% confidence intervals. Overall, 722,839 women with information on pre-pregnancy BMI were included. Of these, 3.1% of women were underweight, 48.1% had normal pre-pregnancy BMI, 25.8% were overweight, and 23.0% were obese. Only 31.5% of women achieved optimal gestational weight gain. Women who had low weight gain were more likely to be African American and have Medicaid health insurance, while women with excess weight gain were more likely to be non-Hispanic white and younger than women with optimal weight gain in each pre-pregnancy BMI category. Compared with women who had optimal weight gain, those with low gestational weight gain had a higher rate of maternal death, 7.97 versus 2.63 per 100,000 (p = 0.027). In addition, low weight gain was associated with the composite adverse maternal outcome (death/SMM) in women with normal pre-pregnancy BMI and in overweight women (AOR 1.12, 95% CI 1.04–1.21, p = 0.004, and AOR 1.17, 95% CI 1.04–1.32, p = 0.009, respectively) compared to women in the same pre-pregnancy BMI category who had optimal weight gain. Similarly, excess gestational weight gain was associated with increased rates of death/SMM among women with normal pre-pregnancy BMI (AOR 1.20, 95% CI 1.12–1.28, p < 0.001) and obese women (AOR 1.12, 95% CI 1.01–1.23, p = 0.019). Low gestational weight gain was associated with perinatal death and severe neonatal morbidity regardless of pre-pregnancy BMI, including obesity classes I, II, and III, while excess weight gain was associated with severe neonatal morbidity only in women who were underweight or had normal BMI prior to pregnancy. Study limitations include the ascertainment of pre-pregnancy BMI using self-report, and lack of data availability for the most recent years. Conclusions In this study, we found that most women do not achieve optimal weight gain during pregnancy. Low weight gain was associated with increased risk of severe adverse birth outcomes, and in particular with maternal death and perinatal death. Excess gestational weight gain was associated with severe adverse birth outcomes, except for women who were overweight prior to pregnancy. Weight gain recommendations for this group may need to be reassessed. It is important to counsel women during pregnancy about specific risks associated with both low and excess weight gain.
35 citations
Cites methods from "Challenges and remediation for Pati..."
...Third, we relied on ICD-9-CM codes to identify severe maternal conditions, which may be under-reported [37,38], resulting in potential underestimation of the associations with suboptimal weight gain....
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TL;DR: To quantify the challenges faced by emergency physicians, a subset of a 2010 Illinois Medicaid database of emergency department I CD-9-CM codes was analyzed, seeking to determine the accuracy of existing mapping tools in order to better prepare emergency physicians for the change to the expanded ICD-10-CM system.
Abstract: Beginning October 2015, the Center for Medicare and Medicaid Services will require medical providers to use the vastly expanded International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) system. Despite wide availability of information and mapping tools for the next generation of the ICD classification system, some of the challenges associated with transition from ICD-9-CM to ICD-10-CM are not well understood. To quantify the challenges faced by emergency physicians, we analyzed a subset of a 2010 Illinois Medicaid database of emergency department ICD-9-CM codes, seeking to determine the accuracy of existing mapping tools in order to better prepare emergency physicians for the change to the expanded ICD-10-CM system. We found that 27% of 1830 codes represented convoluted multidirectional mappings. We then analyzed the convoluted transitions and found that 8% of total visit encounters (23% of the convoluted transitions) were clinically incorrect. The ambiguity and inaccuracy of these mappings may impact the workflow associated with the translation process and affect the potential mapping between ICD codes and Current Procedural Codes, which determine physician reimbursement.
34 citations
Cites background from "Challenges and remediation for Pati..."
...Because ICD codes are used for adverse effects reporting by hospitals, Patient Safety Indicators compiled by the Agency for Healthcare Research and Quality might suffer from similar challenges [13]....
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02 Jan 2012
TL;DR: In this paper, the authors examine the benefits and challenges of the US healthcare system's upcoming conversion to use of the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) and review the cost implications of the transition.
Abstract: This article will examine the benefits and challenges of the US healthcare system's upcoming conversion to use of the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) and will review the cost implications of the transition. Benefits including improved quality of care, potential cost savings from increased accuracy of payments and reduction of unpaid claims, and improved tracking of healthcare data related to public health and bioterrorism events are discussed. Challenges are noted in the areas of planning and implementation, the financial cost of the transition, a shortage of qualified coders, the need for further training and education of the healthcare workforce, and the loss of productivity during the transition. Although the transition will require substantial implementation and conversion costs, potential benefits can be achieved in the areas of data integrity, fraud detection, enhanced cost analysis capabilities, and improved monitoring of patients' health outcomes that will yield greater cost savings over time. The discussion concludes with recommendations to healthcare organizations of ways in which technological advances and workforce training and development opportunities can ease the transition to the new coding system.
33 citations
References
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TL;DR: This paper brings together some of the common themes which have been described, including: vocabulary content, concept orientation, concept Orientation, concept permanence, nonsemantic concept identifiers, polyhierarchy, formal definitions, rejection of "not elsewhere classified" terms, multiple granularities, multiple consistent views, context representation, graceful evolution, and recognized redundancy.
Abstract: Builders of medical informatics applications need controlled medical vocabularies to support their applications and it is to their advantage to use available standards. In order to do so, however, these standards need to address the requirements of their intended users. Over the past decade, medical informatics researchers have begun to articulate some of these requirements. This paper brings together some of the common themes which have been described, including: vocabulary content, concept orientation, concept permanence, nonsemantic concept identifiers, polyhierarchy, formal definitions, rejection of "not elsewhere classified" terms, multiple granularities, multiple consistent views, context representation, graceful evolution, and recognized redundancy. Standards developers are beginning to recognize and address these desiderata and adapt their offerings to meet them.
610 citations
Journal Article•
TL;DR: The PSIs provide an efficient and user-friendly tool to identify potential inhospital patient safety problems for targeted institution-level quality improvement efforts and can serve to shed light on the problem of medical errors not limited solely to mortality because of errors.
Abstract: OBJECTIVE: To develop Patient Safety Indicators (PSI) to identify potential in-hospital patient safety problems for the purpose of quality improvement. DATA SOURCE/STUDY DESIGN: The data source was 2,400,000 discharge records in the 1997 New York State Inpatient Database. PSI algorithms were developed using systematic literature reviews of indicators and hand searches of the ICD-9-CM code book. The prevalence of PSI events and associations between PSI events and patient-level and hospital-level characteristics, length of stay, in-hospital mortality, and hospital charges were examined. PRINCIPAL FINDINGS: PSIs were developed for 12 distinct clinical situations and an overall summary measure. The 1997 event rates per 10,000 discharges varied from 1.1 for foreign bodies left during procedure to 84.7 for birth traumas. Discharge records with PSI events had twofold to threefold longer hospital stays, twofold to 20-fold higher rates of in-hospital mortality, and twofold to eightfold higher total charges than records without PSI events. Multivariate logistic regression revealed that PSI events were primarily associated with increasing age (p < .001), hospitals performing more inpatient surgery (p < .001), and hospitals with higher percentage of beds in intensive care units (p < .001). CONCLUSIONS: The PSIs provide an efficient and user-friendly tool to identify potential inhospital patient safety problems for targeted institution-level quality improvement efforts. Until better error-reporting systems are developed the PSIs can serve to shed light on the problem of medical errors not limited solely to mortality because of errors.
168 citations
TL;DR: The prevention of pressure ulcers is a key intervention that is not new, not expensive, and has the potential to save thousands of patients from unnecessary harm.
96 citations
01 Jan 2012
TL;DR: Research conducted at one medical practice in Florida indicated that in spite of the patients' relatively low education level, the majority indicated a broad acceptance of personal health record (PHR) technology.
Abstract: Health literacy is a concept that describes a patient's ability to understand materials provided by physicians or other providers. Several factors, including education level, income, and age, can influence health literacy. Research conducted at one medical practice in Florida indicated that in spite of the patients’ relatively low education level, the majority indicated a broad acceptance of personal health record (PHR) technology. The key variable explaining patient willingness to adopt a PHR was the patient's health literacy as measured by the eHealth Literacy Scale (eHEALS). Adoption and use rates may also depend on the availability of office staff for hands-on training as well as assistance with interpretation of medical information. It is hoped that technology barriers will disappear over time, and usefulness of the information will promote increased utilization of PHRs. Patient understanding of the information remains a challenge that must be overcome to realize the full potential of PHRs.
95 citations
01 Apr 2013
TL;DR: The quality of the most frequently cited scientific evidence that underpins the recent debates focusing on two major issues: ICD-10-CM implementation costs and revenue gains and the projected clinical data quality improvement is analyzed.
Abstract: The International Statistical Classification of Diseases and Related Health Problems (ICD) has undergone a long evolution from its initial inception in the late 18th century. Today, ICD is the internationally recognized classification that helps clinicians, policy makers, and patients to navigate, understand, and compare healthcare systems and services. Currently in the United States, hot debates surround the transition from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM). This article presents an analysis of the views of the proponents and opponents of the upcoming change. We also briefly present and analyze the quality of the most frequently cited scientific evidence that underpins the recent debates focusing on two major issues: ICD-10-CM implementation costs and revenue gains and the projected clinical data quality improvement. We conclude with policy and research suggestions for healthcare stakeholders.
77 citations