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The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity.

ABSTRACT: BACKGROUND:Discharge diagnoses are used to track national trends and patterns of maternal morbidity. There are few data regarding the validity of the International Classification of Diseases (ICD) codes used for this purpose. The goal of our study was to try to better understand the validity of administrative data being used to monitor and assess trends in morbidity. METHODS:Hospital stay billing records were queried to identify all delivery admissions at the Massachusetts General Hospital for the time period 2001 to 2011 and the University of Michigan Health System for the time period 2005 to 2011. From this, we identified patients with ICD-9-Clinical Modification (CM) diagnosis and procedure codes indicative of severe maternal morbidity. Each patient was classified with 1 of 18 different medical/obstetric categories (conditions or procedures) based on the ICD-9-CM code that was recorded. Within each category, 20 patients from each institution were selected at random, and the corresponding medical charts were reviewed to determine whether the ICD-9-CM code was assigned correctly. The percentage of correct codes for each of 18 preselected clinical categories was calculated yielding a positive predictive value (PPV) and 99% confidence interval (CI). RESULTS:The overall number of correctly assigned ICD-9-CM codes, or PPV, was 218 of 255 (86%; CI, 79%-90%) and 154 of 188 (82%; CI, 74%-88%) at Massachusetts General Hospital and University of Michigan Health System, respectively (combined PPV, 372/443 [84%; CI, 79-88%]). Codes within 4 categories (Hysterectomy, Pulmonary edema, Disorders of fluid, electrolyte and acid-base balance, and Sepsis) had a 99% lower confidence limit ?75%. Codes within 8 additional categories demonstrated a 99% lower confidence limit between 74% and 50% (Acute respiratory distress, Ventilation, Other complications of obstetric surgery, Disorders of coagulation, Cardiomonitoring, Acute renal failure, Thromboembolism, and Shock). Codes within 6 clinical categories demonstrated a 99% lower confidence limit <50% (Puerperal cerebrovascular disorders, Conversion of cardiac rhythm, Acute heart failure [includes arrest and fibrillation], Eclampsia, Neurotrauma, and Severe anesthesia complications). CONCLUSIONS:ICD-9-CM codes capturing severe maternal morbidity during delivery hospitalization demonstrate a range of PPVs. The PPV was high when objective supportive evidence, such as laboratory values or procedure documentation supported the ICD-9-CM code. The PPV was low when greater judgment, interpretation, and synthesis of the clinical data (signs and symptoms) was required to support a code, such as with the category Severe anesthesia complications. As a result, these codes should be used for administrative research with more caution compared with codes primarily defined by objective data.

SUBMITTER: Sigakis MJ

PROVIDER: S-EPMC7481827 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity.

Sigakis Matthew J G MJ Leffert Lisa R LR Mirzakhani Hooman H Sharawi Nadir N Rajala Baskar B Callaghan William M WM Kuklina Elena V EV Creanga Andreea A AA Mhyre Jill M JM Bateman Brian T BT

Anesthesia and analgesia 20160901 3

<h4>Background</h4>Discharge diagnoses are used to track national trends and patterns of maternal morbidity. There are few data regarding the validity of the International Classification of Diseases (ICD) codes used for this purpose. The goal of our study was to try to better understand the validity of administrative data being used to monitor and assess trends in morbidity.<h4>Methods</h4>Hospital stay billing records were queried to identify all delivery admissions at the Massachusetts General ...[more]

PMID: 27387839

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Project description:ImportancePatients can develop multiple skin cancers, and their medical data can be spread over multiple health care systems. This fragmented care, combined with the lack of skin cancer registries, has limited our ability both to provide accurate estimates of incidence and to study the pathogenesis of multiple skin cancers.ObjectiveTo assess whether standard diagnostic and procedural codes present in the electronic health records at a single health care system are a valid proxy for estimating the number of overall skin cancers.Design, setting, and participantsRetrospective cohort study of patients seen at a single-center tertiary care hospital (ie, Vanderbilt University Medical Center) between July 1, 2008, and June 30, 2018. All patients with at least 1 electronic health record-based diagnostic or procedural code for any skin cancer and at least 1 pathology report of a skin cancer.ExposureThe number of International Classification of Disease (ICD) or Current Procedural Terminology (CPT) codes relating to skin cancer.Main outcomes and measuresPearson correlation coefficient and R2 were calculated for the total number of ICD or CPT codes for skin cancer and histologically verified skin cancers.ResultsIn this cohort study of 35 901 patients, the mean (SD) age was 70.4 (14.4) years, 20 404 (56.8%) were men, and 31 623 (88.1%) were White individuals. Of these patients, 6307 had at least 1 ICD or CPT code or pathology report for a skin cancer, of whom 5688 patients had both a CPT code related to skin malignancy and a histologically verified skin cancer. There was a strong linear correlation between the number of CPT codes and pathology records (r = 0.87). There was a poor correlation between the number of ICD codes and pathology records (r = 0.22).Conclusions and relevanceThis cohort study found that the use of ICD codes was a poor proxy measure for the number of skin cancers per patient. In contrast, CPT codes accounted for more than 75% of the variability in the number of skin cancers (R2 = 0.76) and were a better proxy measure for the total number of skin cancers per patient.

Project description:ObjectiveTo estimate whether severe maternal morbidity is associated with increased risk of psychiatric illness in the year after delivery hospital discharge.MethodsThis retrospective cohort study used International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes within Florida's Healthcare Cost and Utilization Project's databases. The first liveborn singleton delivery from 2005 to 2015 was included; women with ICD-9-CM codes for psychiatric illness or substance use disorder during pregnancy were excluded. The exposure was ICD-9-CM codes during delivery hospitalization of severe maternal morbidity, as per the Centers for Disease Control and Prevention. The primary outcome was ICD-9-CM codes in emergency department encounter or inpatient admission within 1 year of hospital discharge of composite psychiatric morbidity (suicide attempt, depression, anxiety, posttraumatic stress disorder, psychosis, acute stress reaction, or adjustment disorder). The secondary outcome was a composite of ICD-9-CM codes for substance use disorder. We compared women with severe maternal morbidity with those without severe maternal morbidity using multivariable logistic regression adjusting for sociodemographic factors and medical comorbidities. Cox proportional hazard models identified the highest risk period after hospital discharge for the primary outcome.ResultsA total of 15,510 women with severe maternal morbidity and 1,178,458 without severe maternal morbidity were included. Within 1 year of hospital discharge, 2.9% (n=452) of women with severe maternal morbidity had the primary outcome compared with 1.6% (n=19,279) of women without severe maternal morbidity, resulting in an adjusted odds ratio (aOR) 1.74 (95% CI 1.58-1.91). The highest risk interval was within 4 months of discharge (adjusted hazard ratio [adjusted HR] 2.53 [95% CI 2.05-3.12]). Most severe maternal morbidity conditions were associated with higher risk of postpartum psychiatric illness. Women with severe maternal morbidity had nearly twofold higher risk of postpartum substance use disorder (170 [1.1%] vs 6,861 [0.6%]; aOR 1.91 [95% CI 1.64-2.23]).ConclusionThough absolute numbers were modest, severe maternal morbidity was associated with increased risk of severe postpartum psychiatric morbidity and substance use disorder. The highest period of risk extended to 4 months after hospital discharge.

Project description:ImportancePrevious efforts to examine severe maternal morbidity (SMM) in the US have focused on delivery hospitalizations. Little is known about de novo SMM that occurs after delivery discharge.ObjectiveTo investigate the incidence, timing, factors, and maternal characteristics associated with de novo SMM after delivery discharge among women in the US.Design, setting, and participantsIn this retrospective cohort study, data from the IBM MarketScan Multi-State Medicaid database and the IBM MarketScan Commercial Claims and Encounters database were used to construct a sample of women aged 15 to 44 years who delivered between January 1, 2010, and September 30, 2014. Severe maternal morbidity was reported by the timing of diagnosis, and the associated maternal characteristics were examined. Women in the Medicaid and commercial insurance sample were classified into 3 distinct outcome groups: (1) those without any SMM during the delivery hospitalization and the postdelivery period (reference group), (2) those who exhibited at least 1 factor associated with SMM during the delivery hospitalization, and (3) those who exhibited any factor associated with de novo SMM after delivery discharge (defined as SMM that was first diagnosed in the inpatient setting during the 6 weeks [or 42 days] after discharge from the delivery hospitalization, conditional on no factor associated with SMM being identified during delivery). Data were analyzed from February to July 2020.ExposuresTiming of SMM diagnosis.Main outcomes and measuresWomen with SMM were identified using diagnosis and procedure codes from the International Classification of Diseases, Ninth Revision, Clinical Modification for the 21 factors associated with SMM that were developed by the Centers for Disease Control and Prevention.ResultsA total of 2 667 325 women in the US with delivery hospitalizations between 2010 and 2014 were identified; of those, 809 377 women (30.3%) had Medicaid insurance (30.3%; mean [SD] age, 25.6 [5.5] years; 51.1% White), and 1 857 948 women (69.7%; mean [SD] age, 30.6 [5.4] years; 36.4% from the southern region of the US) had commercial insurance. Among those with Medicaid insurance, 17 584 women (2.2%) experienced SMM during the delivery hospitalization, and 3265 women (0.4%) experienced de novo SMM after delivery discharge. Among those with commercial insurance, 32 079 women (1.7%) experienced SMM during the delivery hospitalization, and 5275 women (0.3%) experienced de novo SMM after hospital discharge. A total of 5275 SMM cases (14.1%) and 3265 SMM cases (15.7%) among women with commercial and Medicaid insurance, respectively, developed de novo within 6 weeks after hospital discharge; of those, 3993 cases (75.7%) in the commercial insurance cohort and 2399 cases (73.5%) in the Medicaid cohort were identified in the first 2 weeks after discharge. The most common factors associated with SMM varied based on the timing of diagnosis. In the Medicaid population, non-Hispanic Black women (adjusted odds ratio [aOR], 1.53; 95% CI, 1.48-1.58), Hispanic women (aOR, 1.46; 95% CI, 1.37-1.57), and women of other races or ethnicities (aOR, 1.40; 95% CI, 1.33-1.47) had higher rates of SMM during delivery hospitalization than non-Hispanic White women; however, only the disparity between Black and White women (aOR, 1.69; 95% CI, 1.57-1.81) persisted into the postdischarge period.Conclusions and relevanceIn this study, 15.7% of SMM cases in the Medicaid cohort and 14.1% of SMM cases in the commercial insurance cohort first occurred after the delivery hospitalization, with notable disparities in factors and maternal characteristics associated with the development of SMM. These findings suggest a need to expand the focus of SMM assessment to the postdelivery discharge period.

Project description:Hospital discharge (HD) records contain important information that is used in public health and health care sectors. It is becoming increasingly common to rely mostly or exclusively on HD data to assess and monitor severe maternal morbidity (SMM) overall and by sociodemographic characteristics, including race and ethnicity. Limited studies have validated race and ethnicity in HD or provided estimates on the impact of assessing health differences in maternity populations. This study aims to determine the differences in race and ethnicity reporting between HD and birth certificate (BC) data for maternity hospitals in Florida and to estimate the impact of race and ethnicity misclassification on state- and hospital-specific SMM rates. We conducted a population-based retrospective study of live births using linked BC and HD records from 2016 to 2019 (n = 783,753). BC data were used as the gold standard. Race and ethnicity were categorized as non-Hispanic (NH)-White, NH-Black, Hispanic, NH-Asian Pacific Islander (API), and NH-American Indian or Alaskan Native (AIAN). Overall, race and ethnicity misclassification and its impact on SMM at the state- and hospital levels were estimated. At the state level, NH-AIAN women were the most misclassified (sensitivity: 28.2%; positive predictive value (PPV): 25.2%) and were commonly classified as NH-API (30.3%) in HD records. NH-API women were the next most misclassified (sensitivity: 57.3%; PPV: 85.4%) and were commonly classified as NH-White (5.8%) or NH-other (5.5%). At the hospital level, wide variation in sensitivity and PPV with negative skewing was identified, particularly for NH-White, Hispanic, and NH-API women. Misclassification did not result in large differences in SMM rates at the state level for all race and ethnicity categories except for NH-AIAN women (% difference 78.7). However, at the hospital level, Hispanic women had wide variability of a percent difference in SMM rates and were more likely to have underestimated SMM rates. Reducing race and ethnicity misclassification on HD records is key in assessing and addressing SMM differences and better informing surveillance, research, and quality improvement efforts.

Project description:Community-acquired pneumonia (CAP) remains one of the most common indications for pediatric hospitalization in the United States, and it is frequently the focus of research and quality studies. Use of administrative data is increasingly common for these purposes, although proper validation is required to ensure valid study conclusions.To validate administrative billing data for hospitalizations owing to childhood CAP.Case-control study of 4 tertiary care, freestanding children’s hospitals in the United States.A total of 998 medical records of a 25% random sample of 3646 children discharged in 2010 with at least 1 International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) code representing possible pneumonia were reviewed. Discharges (matched on date of admission) without a pneumonia-related discharge code were also examined to identify potential missed pneumonia cases. Two reference standards, based on provider diagnosis alone (provider confirmed) or in combination with consistent clinical and radiographic evidence of pneumonia (definite), were used to identify CAP.Twelve ICD-9-CM–based coding strategies, each using a combination of primary or secondary codes representing pneumonia or pneumonia-related complications. Six algorithms excluded children with complex chronic conditions.Sensitivity, specificity, and negative and positive predictive values (NPV and PPV, respectively) of the 12 identification strategies.For provider-confirmed CAP (n?=?680), sensitivity ranged from 60.7% to 99.7%; specificity, 75.7% to 96.4%; PPV, 67.9% to 89.6%; and NPV, 82.6% to 99.8%. For definite CAP (n?=?547), sensitivity ranged from 65.6% to 99.6%; specificity, 68.7% to 93.0%; PPV, 54.6% to 77.9%; and NPV, 87.8% to 99.8%. Unrestricted use of the pneumonia-related codes was inaccurate, although several strategies improved specificity to more than 90% with a variable effect on sensitivity. Excluding children with complex chronic conditions demonstrated the most favorable performance characteristics. Performance of the algorithms was similar across institutions.Administrative data are valuable for studying pediatric CAP hospitalizations. The strategies presented here will aid in the accurate identification of relevant and comparable patient populations for research and performance improvement studies.

Dataset Information

The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity.

Publications

The Validity of Discharge Billing Codes Reflecting Severe Maternal Morbidity.

Similar Datasets

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