Quality of Care Before and After Mergers and Acquisitions of Rural Hospitals.

Importance: Rural hospitals are increasingly merging with other hospitals. The associations of hospital mergers with quality of care need further investigation. Objectives: To examine changes in quality of care for patients at rural hospitals that merged compared with those that remained independent. Design, Setting, and Participants: In this case-control study, mergers at community nonrehabilitation hospitals in Federal Office of Rural Health Policy-eligible zip codes during 2009 to 2016 in 32 states were identified from Irving Levin Associates and the American Hospital Association Annual Survey. Outcomes for inpatient stays for select conditions and elective procedures were derived from the Healthcare Cost and Utilization Project State Inpatient Databases. Difference-in-differences linear probability models were used to assess premerger to postmerger changes in outcomes for patients discharged from merged vs comparison hospitals that remained independent. Data were analyzed from February to December 2020. Exposures: Hospital mergers. Main Outcomes and Measures: The main outcome was in-hospital mortality among patients admitted for acute myocardial infarction (AMI), heart failure, stroke, gastrointestinal hemorrhage, hip fracture, or pneumonia, as well as complications during stays for elective surgeries. Results: A total of 172 merged hospitals and 266 comparison hospitals were analyzed. After matching, baseline patient characteristics were similar for 303 747 medical stays and 175 970 surgical stays at merged hospitals and 461 092 medical stays and 278 070 surgical stays at comparison hospitals. In-hospital mortality among AMI stays decreased from premerger to postmerger at merged hospitals (9.4% to 5.0%) and comparison hospitals (7.9% to 6.3%). Adjusting for patient, hospital, and community characteristics, the decrease in in-hospital mortality among AMI stays 1 year postmerger was 1.755 (95% CI, -2.825 to -0.685) percentage points greater at merged hospitals than at comparison hospitals (P < .001). This finding held up to 4 years postmerger (DID, -2.039 [95% CI, -3.388 to -0.691] percentage points; P = .003). Greater premerger to postmerger decreases in mortality at merged vs comparison hospitals were also observed at 5 years postmerger among stays for heart failure (DID, -0.756 [95% CI, -1.448 to -0.064] percentage points; P = .03), stroke (DID, -1.667 [95% CI, -3.050 to -0.283] percentage points; P = .02), and pneumonia (DID, -0.862 [95% CI, -1.681 to -0.042] percentage points; P = .04). Conclusions and Relevance: These findings suggest that rural hospital mergers were associated with better mortality outcomes for AMI and several other conditions. This finding is important to enhancing rural health care and reducing urban-rural disparities in quality of care.

Characteristics and related factors of emergency department visits, readmission, and hospital transfers of inpatients under a DRG-based payment system: A nationwide cohort study.

OBJECTIVES: Taiwan has implemented the Diagnosis Related Groups (DRGs) since 2010, and the quality of care under the DRG-Based Payment System is concerned. This study aimed to examine the characteristics, related factors, and time distribution of emergency department (ED) visits, readmission, and hospital transfers of inpatients under the DRG-Based Payment System for each Major Diagnostic Category (MDC). METHODS: We conducted a retrospective cohort study using data from the National Health Insurance Research Database (NHIRD) from 2012 to 2013 in Taiwan. Multilevel logistic regression analysis was used to examine the factors related to ED visits, readmissions, and hospital transfers of patients under the DRG-Based Payment System. RESULTS: In this study, 103,779 inpatients were under the DRG-Based Payment System. Among these inpatients, 4.66% visited the ED within 14 days after their discharge. The factors associated with the increased risk of ED visits within 14 days included age, lower monthly salary, urbanization of residence area, comorbidity index, MDCs, and hospital ownership (p < 0.05). In terms of MDCs, Diseases and Disorders of the Kidney and Urinary Tract (MDC11) conferred the highest risk of ED visits within 14 days (OR = 4.95, 95% CI: 2.69-9.10). Of the inpatients, 6.97% were readmitted within 30 days. The factors associated with the increased risk of readmission included gender, age, lower monthly salary, comorbidity index, MDCs, and hospital ownership (p < 0.05). In terms of MDCs, the inpatients with Pregnancy, Childbirth and the Puerperium (MDC14) had the highest risk of readmission within 30 days (OR = 20.43, 95% CI: 13.32-31.34). Among the inpatients readmitted within 30 days, 75.05% of them were readmitted within 14 days. Only 0.16% of the inpatients were transferred to other hospitals. CONCLUSION: The study shows a significant correlation between Major Diagnostic Categories in surgery and ED visits, readmission, and hospital transfers. The results suggested that the main reasons for the high risk may need further investigation for MDCs in ED visits, readmissions, and hospital transfers.

Hospitalization direct cost of adults with community-acquired pneumonia in Portugal from 2000 to 2009.

INTRODUCTION: Hospitalizations due to community-acquired pneumonia (CAP) in mainland Portugal from 2000 to 2009 accounted for 3.7% of all hospital admissions in population with 18 or more years of age. There is no direct-cost data regarding these admissions. METHODS: In this observational descriptive study all adult hospitalizations associated with CAP diagnosis were retrospectively analyzed for the period between 2000 and 2009. Patients under 18 years old, those with pneumonia as secondary diagnosis, patients with tuberculous or obstructive pneumonia, and immunocompromised patients were excluded from the study. The direct cost of hospitalization was calculated according to the diagnosis-related groups (DRG), established for the respective year of hospitalization. RESULTS: There were 294,026 hospital admissions with an average annual direct cost of 80 million Euros, which almost doubled between 2000 and 2009. The average direct hospitalization costs per admission, including wards and Intensive Care Units (ICU), amounted to €2,707, with an increasing trend. The average hospitalization cost was €2,515 for admissions resulting in live discharge, and €3,457 for the deceased. CONCLUSION: The average direct cost of adult hospitalizations associated with CAP amounted to €2,707 in mainland Portugal from 2000 to 2009, showing an increase of 37.5% in hospitalization cost of living and deceased patients. The economic impact of CAP-related hospital admissions justifies the need for better implementation of preventive measures.

Economic evaluation of surgical treatment of obesity. / Evaluación económica del tratamiento quirúrgico de la obesidad.

INTRODUCTION: Obesity surgery is the best treatment for extreme obesity, with demonstrated long-term positive outcomes. The potential cost-savings generated by the improvement of comorbidities after surgery can justify the allocation of more resources in the surgical treatment of obesity. METHODS: This was an observational, descriptive, longitudinal and retrospective study. Eligible patients underwent Roux-en-Y gastric bypass surgery at the Hospital Universitario Central de Asturias between 2003 and 2012. The established minimum follow-up period was two years. We calculated the individualized cost per patient treated (bottom-up) as well as per Diagnosis-Related Group (DRG) codes (top-down). RESULTS: Our study included 307 patients. The average cost per hospitalization calculated by DRG codes was €6,545.90, and the average cost per patient was €10,572.20. DRG 288 represented 91% of the series, with a value of €4,631. The number of medications also decreased during this period, from 2.86 to 0.78 per medically treated patient, representing a cost reduction of €4,433 per patient with all the obesity-related comorbidities analyzed. CONCLUSIONS: Two years after Roux-en-Y gastric bypass conducted at Hospital Universitario Central de Asturias, the savings in drug costs for patients with multiple pathologies would compensate the inherent costs of the surgical treatment itself. Our results showed that DRG-related costs was insufficient to make a correct economic evaluation, so we recommend an individualized cost calculating method.

Clinical Documentation for Intensivists: The Impact of Diagnosis Documentation.

OBJECTIVES: The aim of this review is to describe the interaction of clinical documentation with patient care, measures of patient acuity, quality metrics, research database accuracy, and healthcare reimbursement in order to highlight potential areas of improvement for intensivists. DATA SOURCES: An online search of PubMed was undertaken as well as review of resources published by the American Academy of Pediatrics, the Society of Critical Care Medicine, the American Medical Association, and the Association of Clinical Documentation Improvement Specialists. STUDY SELECTION: Selected publications included those that described coding, medical record documentation, healthcare reimbursement, quality metrics, administrative databases, Clinical Documentation Improvement programs, medical scribe programs, and various payment models. DATA EXTRACTION: Relevant information was extracted to highlight the impact of diagnosis documentation on patient care, perceived patient severity of illness, quality metrics, and healthcare reimbursement. Query data from our hospital's Clinical Documentation Improvement program were reviewed to highlight areas of improvement within our own Division of Critical Care Medicine. Additionally, interventions to improve clinical documentation were incorporated into this review. DATA SYNTHESIS: Available data in the literature indicate that documentation of precise diagnoses in the medical record has a positive impact on quality metrics, accuracy of administrative databases, hospital reimbursement, and perceived patient complexity. However, there is insufficient data to make conclusions regarding documentation of specific diagnoses and effects on patient care. Administrative responsibilities associated with documentation have been increasing, especially with the introduction of electronic medical records. CONCLUSIONS: Documentation of specific diagnoses in the medical record is important in the broad context of our existing medical system but there is an associated burden in doing so. Widespread implementation of electronic medical record systems has inadvertently led to clinician dissatisfaction and burnout. Research is needed to further evaluate the impact of documentation on patient care as well as steps to decrease the associated burden.

Incorporation of expert knowledge in the statistical detection of diagnosis related group misclassification.

BACKGROUND: In activity based funding systems, the misclassification of inpatient episode Diagnostic Related Groups (DRGs) can have significant impacts on the revenue of health care providers. Weakly informative Bayesian models can be used to estimate an episode's probability of DRG misclassification. METHODS: This study proposes a new, Hybrid prior approach which utilises guesses that are elicited from a clinical coding auditor, switching to non-informative priors where this information is inadequate. This model's ability to detect DRG revision is compared to benchmark weakly informative Bayesian models and maximum likelihood estimates. RESULTS: Based on repeated 5-fold cross-validation, classification performance was greatest for the Hybrid prior model, which achieved best classification accuracy in 14 out of 20 trials, significantly outperforming benchmark models. CONCLUSIONS: The incorporation of elicited expert guesses via a Hybrid prior produced a significant improvement in DRG error detection; hence, it has the ability to enhance the efficiency of clinical coding audits when put into practice at a health care provider.

Quality of coding within clinical datasets: A case-study using burn-related hospitalizations.

The quality of clinical data held in administrative databases is crucial for appropriate funding of health care services. As Diagnosis-Related Groups (DRGs) continue to play an important role in hospital payment mechanisms, proper coding of diagnoses and procedures is of most concern. This study used an administrative, nationwide Portuguese inpatient database to characterize and assess coding patterns in burn-related hospitalization data, with a special focus on identifying suspected miscoding practices that could be affecting APR-DRG (All-Patient Refined Diagnosis-Related Groups) classification. Using coded clinical data of 4,182 burn-related admissions occurred between 2011 and 2015, we compared APR-DRG and Severity of Illness (SOI) frequencies between hospitals with a burn unit in Portugal. The frequencies of individual diagnosis and procedure codes among episodes grouped within the same APR-DRG were also compared. Hospitals with a burn unit in Portugal differed significantly in the frequencies of APR-DRGs 842 and 844. Proper coding of extensive third-degree burns might be related with the observed discrepant frequencies of APR-DRGs across the evaluated hospitals. Facilities also differed significantly concerning the proportions of SOI levels in certain APR-DRGs. Significant differences in reporting certain comorbidities and common hospital procedures, especially non-operating room procedures, might have influenced the observed discrepancies in SOI levels. Moreover, there seems to be a lack of standard in coding debridement procedures among the evaluated hospitals. Overall, we found some suspected coding patterns that could potentially be associated with miscoding practices impacting APR-DRG classification. Those findings could not only be relevant for planning future audit processes and improving medical coding practices, but also for discussing quality and desirable features of burn-related clinical data, keeping in mind their use for other purposes beyond DRG grouping, namely clinical and health care services research, as well as health care management.

Back to the Future: Impact of a Paper-Based Admission H&P on Clinical Documentation Improvement at a Level 1 Trauma Center.

The Medicare Severity Diagnosis Related Group (MS-DRG) weight, as derived from the MS-DRG assigned at discharge, is in part determined by the physician-documented diagnoses. However, the terminology associated with MS-DRG determination is often not aligned with typical physician language, leading to inaccurate coding and decreased hospital reimbursements. The goal of this study was to evaluate the impact of a diagnosis picklist within a paper-based history and physical examination (H&P) on the average MS-DRG weight and the Case-mix index (CMI). Our trauma center implemented a paper H&P form for trauma patients featuring picklist diagnoses aligned with the MS-DRG terminology and arranged by the physiologic system. To evaluate its impact, we conducted a cohort study using data from our trauma registry between July 2015 and November 2017. Our cohort included 442 (26.0%) paper and 1,261 (74.0%) dictated H&Ps. Average CMI (2.56 vs 2.15) and expected patients ($25,057 vs $19,825) were higher for the paper group (P < 0.001, P = 0.002). Adjusted regression models demonstrated paper coding to be associated with 0.265 CMI points, translating to an average increase in expected payment of 6.5 per cent per patient. Utilization of a standardized, paper-based H&P template with picklist diagnoses was associated with a higher trauma service CMI and higher expected payments. Preprinted diagnoses that align with the MS-DRG terminology lead to clinical documentation improvement.

[Determinants of time required by medical information technicians for quality control of hospital activity coding, in French medico-administrative system]. / Déterminants du temps nécessaire au contrôle qualité dans le cadre du programme de médicalisation des systèmes d'information (PMSI), dans le champ médecine, chirurgie et obstétrique (MCO) d'un centre hospitalier régional, par les techniciens d'information médicale.

BACKGROUND: Since 2008, in France, hospital funding is determined by the nature of activities provided (activity-based funding). Quality control of hospital activity coding is essential to optimize hospital remuneration. There is a need for reliable tools to allocate human resources wisely in order to improve these controls. METHODS: The main objective of this study was to identify the determinants of time needed by medical information technicians to control hospital activity coding in a Regional Hospital Center. From March 2016 to the beginning of January 2017, medical information technicians reported the time they spent on each quality control, and the time they needed when they had to code the entire stay. Multiple linear regressions were performed to identify the determinants of quality control or coding duration. A split sample validation was used: model was created on one half of the sample and validated on the remaining half. RESULTS: Among the controls, 5431 were included in the analysis of determinants of control duration (2715 kept aside for model validation). Seven determinants have been identified (stay duration, level of complexity, month of control, type of control, medical information technician, rank of classing information, and major diagnostic category). The correlation coefficient between predicted and real control duration was 0.71 (P<10-4); 808 stays were included in the analysis of determinants of coding duration (404 kept aside for model validation). Two determinants have been identified. The correlation coefficient, between predicted and real coding duration, was 0.47 (P<10-3). We performed the same multiple regression, on 2017 activity data, to estimate the weight of each hospital activity pole, regarding quality control of hospital activity coding. CONCLUSION: We succeeded in modeling time needed for quality control of hospital stays. These results helped to estimate human resources required for quality control of each hospital pole. Nevertheless, the second analysis did not give satisfactory results: we failed in modeling time needed to code hospital stays.

Validity of ICD-9 and ICD-10 codes used to identify acute liver injury: A study in three European data sources.

PURPOSE: Validating cases of acute liver injury (ALI) in health care data sources is challenging. Previous validation studies reported low positive predictive values (PPVs). METHODS: Case validation was undertaken in a study conducted from 2009 to 2014 assessing the risk of ALI in antidepressants users in databases in Spain (EpiChron and SIDIAP) and the Danish National Health Registers. Three ALI definitions were evaluated: primary (specific hospital discharge codes), secondary (specific and nonspecific hospital discharge codes), and tertiary (specific and nonspecific hospital and outpatient codes). The validation included review of patient profiles (EpiChron and SIDIAP) and of clinical data from medical records (EpiChron and Denmark). ALI cases were confirmed when liver enzyme values met a definition by an international working group. RESULTS: Overall PPVs (95% CIs) for the study ALI definitions were, for the primary ALI definition, 84% (60%-97%) (EpiChron), 60% (26%-88%) (SIDIAP), and 74% (60%-85%) (Denmark); for the secondary ALI definition, 65% (45%-81%) (EpiChron), 40% (19%-64%) (SIDIAP), and 70% (64%-77%) (Denmark); and for the tertiary ALI definition, 25% (18%-34%) (EpiChron), 8% (7%-9%) (SIDIAP), and 47% (42%-52%) (Denmark). The overall PPVs were higher for specific than for nonspecific codes and for hospital discharge than for outpatient codes. The nonspecific code "unspecified jaundice" had high PPVs in Denmark. CONCLUSIONS: PPVs obtained apply to patients using antidepressants without preexisting liver disease or ALI risk factors. To maximize validity, studies on ALI should prioritize hospital specific discharge codes and should include hospital codes for unspecified jaundice. Case validation is required when ALI outpatient cases are considered.

Challenging cases during clinical clerkships beyond the domain of the "medical expert": an analysis of students' case vignettes.

Background: During clinical clerkships students experience complex and challenging clinical situations related to problems beyond the domain of the "Medical Expert". Workplace routine may leave little opportunity to reflect on these situations. The University of Zurich introduced a mandatory course directly after the clinical clerkship year (CCY) to work up these situations. Prior to the course each student submitted a vignette on a case he or she had perceived challenging during the CCY and which was not related to the domain of the "Medical Expert" role. In this paper we want to characterize these cases in respect to most prominent themes and related CanMEDS roles. The goal was to inform clinical supervisors about potential teaching demands during the CCY. Methods: All case vignettes submitted by a years' cohort were analysed by three researchers in two ways: for the clinical characteristics and the main theme of the underlying problem and the most prominent CanMEDS roles involved. Themes of the underlying problem were aggregated to overarching topics and subsequently to main categories by pragmatic thematic analysis. Results: 254 case vignettes covered the whole spectrum of clinical disciplines. A wide range of underlying themes could be assigned to five main categories: "communication within team" (23.2%), "communication with patients and relatives" (24.8%), "patient behavior and attitudes" (18.5%), "clinical decision making" (24.0%), and "social and legal issues" (9.4%). Most frequent CanMEDS roles were "Communicator" (26.9%) and "Professional" (23.5%). Conclusions: Cases students perceived as challenging beyond the "Medical Expert" were reported from all clinical disciplines. These were mainly related to communicational and professional issues, mirrored by the CanMEDS roles "Communicator" and "Professional". Therefore, supervisors in clinical clerkships should put an additional teaching focus on communication and professionalism.

Identification of gastrointestinal perforation based on ICD-10 code in a Japanese administrative medical information database and associated drug exposure risk factors.

PURPOSE: The purpose of this study is to evaluate the accuracy of gastrointestinal (GI) perforation ICD-10 coding in the Diagnosis Procedure Combination (DPC) database and to examine drug exposure risk factors for GI perforation. METHODS: A total of 100 patients with GI perforation ICD-10 codes were selected randomly from Kagawa University Hospital's DPC database between April 2011 and December 2016. Two experienced specialist physicians independently reviewed the medical records and classified cases as "definite A," "definite B," "probable," or "no GI perforation." The positive predictive values (PPVs) of "definite A/B" cases were calculated after stratification by sex, age, ICD-10 code, and diagnostic information in the DPC data. The number of prescribed drugs with side effects of GI perforation according to historical data was compared between "definite A/B" and "no GI perforation" cases. RESULTS: The overall PPV was 47.0% (95% confidence interval [CI], 36.9-57.2). However, the PPVs for the three categories of diagnostic information in the DPC data ("main diagnosis," "diagnosis causing admission," and "most resource-intensive diagnosis") were each more than 70% after excluding inappropriate patients. Additionally, the PPV focused on these three categories was 76.3% (95% CI, 59.8-88.6). Prescribed drugs with side effects of GI perforation were more frequently detected in "definite A/B" cases (P = .028). CONCLUSIONS: Although the overall PPV for GI perforation based on ICD-10 code was low, our results suggest that the PPV could be improved by appropriate selection of DPC diagnosis category and that use of multiple medications enhances the risk of GI perforation.

Assessment of ICD-10-CM code assignment validity for case finding of outpatient anticoagulant-related bleeding among Medicare beneficiaries.

PURPOSE: To assess performance of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code assignments for identifying bleeding events resulting in emergency department visits and hospitalizations among outpatient Medicare beneficiaries prescribed anticoagulants. METHODS: Performance of 206 ICD-10-CM code assignments indicative of bleeding, five anticoagulant adverse effect/poisoning codes, and five coagulopathy codes (according to Medicare Parts A and B claims) as assessed among Medicare fee-for-service beneficiaries prescribed anticoagulants between October 1, 2015 and September 30, 2016 (according to Part D claims). Structured medical record review was the gold standard for validating the presence of anticoagulant-related bleeding. Sensitivity was adjusted to correct for partial verification bias due to sampling design. RESULTS: Based on the study sample of 1166 records (583 cases, 583 controls), 57 of 206 codes yielded the optimal performance for anticoagulant-related bleeding (diagnostic odds ratio, 51; positive predictive value (PPV), 75.7% [95% CI, 72.0%-79.1%]; adjusted sensitivity, 70.0% [95% CI, 63.2%-77.7%]). Codes for intracranial bleeding demonstrated the highest PPV (85.0%) and adjusted sensitivity (91.0%). Bleeding codes in the primary position demonstrated high PPV (86.9%), but low adjusted sensitivity (36.0%). The adjusted sensitivity improved to 69.5% when codes in a secondary position were added. Only one adverse effect/poisoning code was used, appearing in 7.8% of cases and controls (PPV, 71.4% and adjusted sensitivity, 6.8%). CONCLUSIONS: Performance of ICD-10-CM code assignments for bleeding among patients prescribed anticoagulants varied by bleed type and code position. Adverse effect/poisoning codes were not commonly used and would have missed over 90% of anticoagulant-related bleeding cases.

Sensitivity and Specificity of Administrative Medical Coding for Pediatric Eosinophilic Esophagitis.

OBJECTIVES: Eosinophilic esophagitis (EoE) is a delayed-type hypersensitivity with increasing rates among pediatric populations. Although studies have used International Classification of Diseases (ICD) coding to define local cohorts and report disease epidemiology, the accuracy of the EoE ICD code for pediatric EoE is unknown. METHODS: We searched the Intermountain Healthcare Database for pediatric cases with the EoE ICD code over a 5-year period. We cross-referenced these results with a recently published pediatric EoE cohort from the same region and period, where incident cases were identified via retrospective review of pathology reports and medical records. Using the retrospective review cohort as the reference standard, we evaluated the accuracy of the EoE ICD code. RESULTS: Via retrospective review, we identified 1129 new pediatric EoE cases in the Intermountain Healthcare system over 5 years. Six hundred ten of these had the EoE ICD code associated with their chart. Out of 878,872 unique pediatric records in the Intermountain Healthcare system, 219 had the EoE ICD code incorrectly applied. The specificity of the EoE ICD code in children was 99%, but sensitivity and positive predictive value were 61% and 79%, respectively. CONCLUSIONS: The EoE ICD code has strengths and weaknesses in pediatrics. The EoE ICD code is specific, with few false positives across a large population, but not sensitive. The low sensitivity is likely multifactorial and requires further evaluation. Compared to retrospective chart review, which allows for application of clinicopathologic EoE diagnostic criteria, sole use of ICD codes results in underascertainment of EoE cases and key misclassifications.

Reliability measurement and ICD-10 validation of ICPC-2 for coding/classification of diagnoses/health problems in an African primary care setting.

Background: The routine application of a primary care classification system to patients' medical records in general practice/primary care is rare in the African region. Reliable data are crucial to understanding the domain of primary care in Nigeria, and this may be actualized through the use of a locally validated primary care classification system such as the International Classification of Primary Care, 2nd edition (ICPC-2). Although a few studies from Europe and Australia have reported that ICPC is a reliable and feasible tool for classifying data in primary care, the reliability and validity of the revised version (ICPC-2) is yet to be objectively determined particularly in Africa. Objectives: (i) To determine the convergent validity of ICPC-2 diagnoses codes when correlated with International Statistical Classification of Diseases (ICD)-10 codes, (ii) to determine the inter-coder reliability among local and foreign ICPC-2 experts and (iii) to ascertain the level of accuracy when ICPC-2 is engaged by coders without previous training. Methods: Psychometric analysis was carried out on ICPC-2 and ICD-10 coded data that were generated from physicians' diagnoses, which were randomly selected from general outpatients' clinic attendance registers, using a systematic sampling technique. Participants comprised two groups of coders (ICPC-2 coders and ICD-10 coders) who coded independently a total of 220 diagnoses/health problems with ICPC-2 and/or ICD-10, respectively. Results: Two hundred and twenty diagnoses/health problems were considered and were found to cut across all 17 chapters of the ICPC-2. The dataset revealed a strong positive correlation between selected ICPC-2 codes and ICD-10 codes (r ≈ 0.7) at a sensitivity of 86.8%. Mean percentage agreement among the ICPC-2 coders was 97.9% at the chapter level and 95.6% at the rubric level. Similarly, Cohen's kappa coefficients were very good (κ > 0.81) and were higher at chapter level (0.94-0.97) than rubric level (0.90-0.93) between sets of pairs of ICPC-2 coders. An accuracy of 74.5% was achieved by ICD-10 coders who had no previous experience or prior training on ICPC-2 usage. Conclusion: Findings support the utility of ICPC-2 as a valid and reliable coding tool that may be adopted for routine data collection in the African primary care context. The level of accuracy achieved without training lends credence to the proposition that it is a simple-to-use classification and may be a useful starting point in a setting devoid of any primary care classification system for morbidity and mortality registration at such a critical level of public health importance.

A physician-led initiative to improve clinical documentation results in improved health care documentation, case mix index, and increased contribution margin.

INTRODUCTION: Clinical documentation is the key determinant of inpatient acuity of illness and payer reimbursement. Every inpatient hospitalization is placed into a diagnosis related group with a relative value based on documented procedures, conditions, comorbidities and complications. The Case Mix Index (CMI) is an average of these diagnosis related groups and directly impacts physician profiling, medical center profiling, reimbursement, and quality reporting. We hypothesize that a focused, physician-led initiative to improve clinical documentation of vascular surgery inpatients results in increased CMI and contribution margin. METHODS: A physician-led coding initiative to educate physicians on the documentation of comorbidities and conditions was initiated with concurrent chart review sessions with coding specialists for 3 months, and then as needed, after the creation of a vascular surgery documentation guide. Clinical documentation and billing for all carotid endarterectomy (CEA) and open infrainguinal procedures (OIPs) performed between January 2013 and July 2016 were stratified into precoding and postcoding initiative groups. Age, duration of stay, direct costs, actual reimbursements, contribution margin (CM), CMI, rate of complication or comorbidity, major complication or comorbidity, severity of illness, and risk of mortality assigned to each discharge were abstracted. Data were compared over time by standardizing Centers for Medicare and Medicaid Services (CMS) values for each diagnosis related group and using a CMS base rate reimbursement. RESULTS: Among 458 CEA admissions, postcoding initiative CEA patients (n = 253) had a significantly higher CMI (1.36 vs 1.25; P = .03), CM ($7859 vs $6650; P = .048), and CMS base rate reimbursement ($8955 vs $8258; P = .03) than precoding initiative CEA patients (n = 205). The proportion of admissions with a documented major complication or comorbidity and complication or comorbidity was significantly higher after the coding initiative (43% vs 27%; P < .01). Among 504 OIPs, postcoding initiative patients (n = 227) had a significantly higher CMI (2.23 vs 2.05; P < .01), actual reimbursement ($23,203 vs $19,909; P < .01), CM ($12,165 vs $8840; P < .01), and CMS base rate reimbursement ($14,649 vs $13,496; P < .01) than precoding initiative patients (n = 277). The proportion of admissions with a documented major complication or comorbidity and complication or comorbidity was significantly higher after the coding initiative (61% vs 43%; P < .01). For both CEA and OIPs, there were no differences in age, duration of stay, total direct costs, or primary insurance status between the precoding and postcoding patient groups. CONCLUSIONS: Accurate and detailed clinical documentation is required for key stakeholders to characterize the acuity of inpatient admissions and ensure appropriate reimbursement; it is also a key component of risk-adjustment methods for assessing quality of care. A physician-led documentation initiative significantly increased CMI and CM.

Case-Mix for Performance Management: A Risk Algorithm Based on ICD-10-CM.

BACKGROUND: Accurate risk adjustment is the key to a reliable comparison of cost and quality performance among providers and hospitals. However, the existing case-mix algorithms based on age, sex, and diagnoses can only explain up to 50% of the cost variation. More accurate risk adjustment is desired for provider performance assessment and improvement. OBJECTIVE: To develop a case-mix algorithm that hospitals and payers can use to measure and compare cost and quality performance of their providers. METHODS: All 6,048,895 patients with valid diagnoses and cost recorded in the US Veterans health care system in fiscal year 2016 were included in this study. The dependent variable was total cost at the patient level, and the explanatory variables were age, sex, and comorbidities represented by 762 clinically homogeneous groups, which were created by expanding the 283 categories from Clinical Classifications Software based on ICD-10-CM codes. The split-sample method was used to assess model overfitting and coefficient stability. The predictive power of the algorithms was ascertained by comparing the R, mean absolute percentage error, root mean square error, predictive ratios, and c-statistics. RESULTS: The expansion of the Clinical Classifications Software categories resulted in higher predictive power. The R reached 0.72 and 0.52 for the transformed and raw scale cost, respectively. CONCLUSIONS: The case-mix algorithm we developed based on age, sex, and diagnoses outperformed the existing case-mix models reported in the literature. The method developed in this study can be used by other health systems to produce tailored risk models for their specific purpose.

Identification, Coding, and Reimbursement of Pediatric Malnutrition at an Urban Academic Medical Center.

BACKGROUND: The American Academy of Nutrition and Dietetics and the American Society of Parenteral and Enteral Nutrition released a pediatric malnutrition consensus statement in 2014 recommending the use of z-scores as indicators for identification and documentation of malnutrition. A shift in focus is needed on standardizing pediatric malnutrition language at institutions nationwide to make study data comparable. With this standardized language, establishment of institutional baselines for identification, coding, and reimbursement of pediatric malnutrition is crucial to measure process improvements. OBJECTIVES: The objectives of this study were to determine the prevalence of malnutrition among pediatric patients at an urban academic medical center, the frequency of malnutrition codes used, and the reimbursement impact of coding for malnutrition. METHODS: Electronic medical records of pediatric patients admitted from January 2013 to December 2015 were reviewed. Malnutrition was identified based on registered dietitian identification and z-score. Patients given a malnutrition-related International Classification of Diseases code upon discharge were identified. A reimbursement calculation was performed: the malnutrition-related International Classification of Diseases code was removed to determine the difference in reimbursement with vs without the code. RESULTS: Of the 1,532 admissions included in this study, 464 (30%) were identified as malnourished. A total of 152 (33%) malnourished patients were given a malnutrition-related secondary diagnosis. The calculation revealed that coding for malnutrition resulted in an additional $27,665.70 to the medical center. CONCLUSION: Malnutrition coding may have a significant financial impact and processes improvement efforts can be made to improve malnutrition coding.

Validation of the All Patient Refined Diagnosis Related Group (APR-DRG) Risk of Mortality and Severity of Illness Modifiers as a Measure of Perioperative Risk.

The All Patient Refined Diagnosis Related Group (APR-DRG) is an inpatient visit classification system that assigns a diagnostic related group, a Risk of Mortality (ROM) subclass and a Severity of Illness (SOI) subclass. While extensively used for cost adjustment, no study has compared the APR-DRG subclass modifiers to the popular Charlson Comorbidity Index as a measure of comorbidity severity in models for perioperative in-hospital mortality. In this study we attempt to validate the use of these subclasses to predict mortality in a cohort of surgical patients. We analyzed all adult (age over 18 years) inpatient non-cardiac surgery at our institution between December 2005 and July 2013. After exclusions, we split the cohort into training and validation sets. We created prediction models of inpatient mortality using the Charlson Comorbidity Index, ROM only, SOI only, and ROM with SOI. Models were compared by receiver-operator characteristic (ROC) curve, area under the ROC curve (AUC), and Brier score. After exclusions, we analyzed 63,681 patient-visits. Overall in-hospital mortality was 1.3%. The median number of ICD-9-CM diagnosis codes was 6 (Q1-Q3 4-10). The median Charlson Comorbidity Index was 0 (Q1-Q3 0-2). When the model was applied to the validation set, the c-statistic for Charlson was 0.865, c-statistic for ROM was 0.975, and for ROM and SOI combined the c-statistic was 0.977. The scaled Brier score for Charlson was 0.044, Brier for ROM only was 0.230, and Brier for ROM and SOI was 0.257. The APR-DRG ROM or SOI subclasses are better predictors than the Charlson Comorbidity Index of in-hospital mortality among surgical patients.