Practical Applications and Observational Implications of Time-Based Coding for Workers' Compensation Clinical Encounters-A Follow-up to Best Practices in Documenting and Coding High-Value Care in Workers' Compensation Encounters-ACOEM Guidance Statement.

ABSTRACT: Clinical practices that provide workers' compensation care and other services related to managing work-related illnesses and injuries have long been challenged in receiving appropriate payment for their professional work. The American College of Occupational and Environmental Medicine (ACOEM) has provided excellent guidelines for coding and billing via its various documents that have been provided over the years. However, despite these guidelines, payors have been slow to adopt occupational specific coding guidelines to justify higher professional payment. With the move to a Centers for Medicare & Medicaid Services (CMS)-sponsored time-based coding option in 2011, the occupational and environmental medicine (OEM) clinics have been able to finally not only document but recoup the value of those services that go beyond the simple patient interface, being able to capture those activities that truly provide high value in the management of workers' medical issues.

Cause of death coding in asthma.

BACKGROUND: While clinical coding is intended to be an objective and standardized practice, it is important to recognize that it is not entirely the case. The clinical and bureaucratic practices from event of death to a case being entered into a research dataset are important context for analysing and interpreting this data. Variation in practices can influence the accuracy of the final coded record in two different stages: the reporting of the death certificate, and the International Classification of Diseases (Version 10; ICD-10) coding of that certificate. METHODS: This study investigated 91,022 deaths recorded in the Scottish Asthma Learning Healthcare System dataset between 2000 and 2017. Asthma-related deaths were identified by the presence of any of ICD-10 codes J45 or J46, in any position. These codes were categorized either as relating to asthma attacks specifically (status asthmatic; J46) or generally to asthma diagnosis (J45). RESULTS: We found that one in every 200 deaths in this were coded as being asthma related. Less than 1% of asthma-related mortality records used both J45 and J46 ICD-10 codes as causes. Infection (predominantly pneumonia) was more commonly reported as a contributing cause of death when J45 was the primary coded cause, compared to J46, which specifically denotes asthma attacks. CONCLUSION: Further inspection of patient history can be essential to validate deaths recorded as caused by asthma, and to identify potentially mis-recorded non-asthma deaths, particularly in those with complex comorbidities.

Undercounting diagnoses in Australian general practice: a data quality study with implications for population health reporting.

BACKGROUND: Diagnosis can often be recorded in electronic medical records (EMRs) as free-text or using a term with a diagnosis code. Researchers, governments, and agencies, including organisations that deliver incentivised primary care quality improvement programs, frequently utilise coded data only and often ignore free-text entries. Diagnosis data are reported for population healthcare planning including resource allocation for patient care. This study sought to determine if diagnosis counts based on coded diagnosis data only, led to under-reporting of disease prevalence and if so, to what extent for six common or important chronic diseases. METHODS: This cross-sectional data quality study used de-identified EMR data from 84 general practices in Victoria, Australia. Data represented 456,125 patients who attended one of the general practices three or more times in two years between January 2021 and December 2022. We reviewed the percentage and proportional difference between patient counts of coded diagnosis entries alone and patient counts of clinically validated free-text entries for asthma, chronic kidney disease, chronic obstructive pulmonary disease, dementia, type 1 diabetes and type 2 diabetes. RESULTS: Undercounts were evident in all six diagnoses when using coded diagnoses alone (2.57-36.72% undercount), of these, five were statistically significant. Overall, 26.4% of all patient diagnoses had not been coded. There was high variation between practices in recording of coded diagnoses, but coding for type 2 diabetes was well captured by most practices. CONCLUSION: In Australia clinical decision support and the reporting of aggregated patient diagnosis data to government that relies on coded diagnoses can lead to significant underreporting of diagnoses compared to counts that also incorporate clinically validated free-text diagnoses. Diagnosis underreporting can impact on population health, healthcare planning, resource allocation, and patient care. We propose the use of phenotypes derived from clinically validated text entries to enhance the accuracy of diagnosis and disease reporting. There are existing technologies and collaborations from which to build trusted mechanisms to provide greater reliability of general practice EMR data used for secondary purposes.

Observational Behavioral Coding in the Pediatric Emergency Department: Development of the Emergency Department Child Behavior Coding System.

BACKGROUND: Despite improvements over the past decade, children continue to experience significant pain and distress surrounding invasive procedures in the emergency department (ED). To assess the impact of newly developed interventions, we must create more reliable and valid behavioral assessment tools that have been validated for the unique settings of pediatric EDs. OBJECTIVE: This study aimed to create and test the Emergency Department Child Behavior Coding System (ED-CBCS) for the assessment of child distress and nondistress behaviors surrounding pediatric ED procedures. METHODS: Via an iterative process, a multidisciplinary expert panel developed the ED-CBCS, an advanced time-based behavioral coding measure. Inter-rater reliability and concurrent validity were examined using 38 videos of children aged from 2 to 12 years undergoing laceration procedures. Face, Legs, Activity, Cry, Consolability (FLACC) scale scores were used to examine concurrent validity. RESULTS: The final ED-CBCS included 27 child distress and nondistress behaviors. Time-unit κ values from 0.64 to 0.98 and event alignment κ values from 0.62 to 1.00 indicated good to excellent inter-rater reliability for all but one of the individual codes. ED-CBCS distress (B = 1.26; p < 0.001) and nondistress behaviors (B = -0.69, p = 0.025) were independently significantly associated with FLACC scores, indicating concurrent validity. CONCLUSIONS: We developed a psychometrically sound tool tailored for pediatric ED procedures. Future work could use this measure to better identify behavioral targets and test the effects of interventions to relieve pediatric ED pain and distress.

Best Practices in Documenting and Coding High-Value Care in Workers' Compensation Encounters-ACOEM Guidance Statement.

ABSTRACT: Workers' compensation outpatient care requires attention to causation, functional assessment, work disability prevention, and return-to-work planning, elements not usually addressed in other types of outpatient encounters. Because these elements of care deviate from the usual pattern of ambulatory services, providers of workers' compensation care have faced challenges in billing and auditing practices resulting in underpayment when providing high-value care based on evidence-based guidelines. Recent changes in Centers for Medicare & Medicaid Services rules on documentation requirements for coding outpatient evaluation and management encounters offer an opportunity for occupational health clinicians to be paid appropriately for care that follows occupational medicine practice guidelines. There remains a need to define the elements of documentation that should be expected in delivering high-value workers' compensation care. This article provides guidance for documenting high-value workers' compensation care.

Combining deep neural networks, a rule-based expert system and targeted manual coding for ICD-10 coding causes of death of French death certificates from 2018 to 2019.

OBJECTIVE: For ICD-10 coding causes of death in France in 2018 and 2019, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team focused on certificates with a special public health interest and those for which DNNs have a low confidence index. METHODS: Supervised seq-to-seq DNNs are trained on previously coded data to ICD-10 code multiple causes and underlying causes of death. The DNNs are then used to target death certificates to be sent to the coding team and to predict multiple causes and underlying causes of death for part of the certificates. Hence, the coding campaign for 2018 and 2019 combines three modes of coding and a loop of interaction between the three. FINDINGS: In this campaign, 62% of the certificates are automatically batch coded by the expert system, 3% by the coding team, and the remainder by DNNs. Compared to a traditional campaign that would have relied on automatic batch coding and manual coding, the present campaign reaches an accuracy of 93.4% for ICD-10 coding of the underlying cause (95.6% at the European shortlist level). Some limitations (risks of under- or overestimation) appear for certain ICD categories, with the advantage of being quantifiable. CONCLUSION: The combination of the three coding methods illustrates how artificial intelligence, automated and human codings are mutually enriching. Quantified limitations on some chapters of ICD codes encourage an increase in the volume of certificates sent for manual coding from 2021 onward.

Validating use of diagnostic codes in Canadian administrative data for identification of adverse drug events.

AIMS: While diagnostic codes from administrative health data might be a valuable source to identify adverse drug events (ADEs), their ability to identify unintended harms remains unclear. We validated claims-based diagnosis codes for ADEs based on events identified in a prospective cohort study and assessed whether key attributes predicted their documentation in administrative data. METHODS: This was a retrospective analysis of 3 prospective cohorts in British Columbia, from 2008 to 2015 (n = 13 969). We linked prospectively identified ADEs to administrative insurance data to examine the sensitivity and specificity of different diagnostic code schemes. We used logistic regression to assess which key attributes (e.g., type of event, symptoms and culprit medications) were associated with better documentation of ADEs in administrative data. RESULTS: Among 1178 diagnosed events, the sensitivity of the diagnostic codes in administrative data ranged from 3.4 to 52.6%, depending on the database and codes used. We found that documentation was worse for certain types of ADEs (dose-related: odds ratio [OR]: 0.32, 95% confidence interval [CI]: 0.15, 0.69; nonadherence events (OR: 0.35, 95% CI: 0.20, 0.62), and better for those experiencing arrhythmias (OR: 4.19, 95% CI: 0.96, 18.28). CONCLUSION: ADEs were not well documented in administrative data. Alternative methods should be explored to capture ADEs for health research.

Accuracy of routinely collected hospital administrative discharge data and death certificate ICD-10 diagnostic coding in progressive supranuclear palsy and corticobasal syndrome: a systematic review and validation study.

BACKGROUND: We conducted a systematic review to identify existing ICD-10 coding validation studies in progressive supranuclear palsy and corticobasal syndrome [PSP/CBS]) and, in a new study, evaluated the accuracy of ICD-10 diagnostic codes for PSP/CBS in Scottish hospital inpatient and death certificate data. METHODS: Original studies that assessed the accuracy of specific ICD-10 diagnostic codes in PSP/CBS were sought. Separately, we estimated the positive predictive value (PPV) of specific codes for PSP/CBS in inpatient hospital data (SMR01, SMR04) compared to clinical diagnosis in four regions. Sensitivity was assessed in one region due to a concurrent prevalence study. For PSP, the consistency of the G23.1 code in inpatient and death certificate coding was evaluated across Scotland. RESULTS: No previous ICD-10 validation studies were identified. 14,767 records (SMR01) and 1497 records (SMR04) were assigned the candidate ICD-10 diagnostic codes between February 2011 and July 2019. The best PPV was achieved with G23.1 (1.00, 95% CI 0.93-1.00) in PSP and G23.9 in CBS (0.20, 95% CI 0.04-0.62). The sensitivity of G23.1 for PSP was 0.52 (95% CI 0.33-0.70) and G31.8 for CBS was 0.17 (95% CI 0.05-0.45). Only 38.1% of deceased G23.1 hospital-coded cases also had this coding on their death certificate: the majority (49.0%) erroneously assigned the G12.2 code. DISCUSSION: The high G23.1 PPV in inpatient data shows it is a useful tool for PSP case ascertainment, but death certificate coding is inaccurate. The PPV and sensitivity of existing ICD-10 codes for CBS are poor due to a lack of a specific code.

Society of Urologic Prosthetic Surgeons' Coding and Billing Position Statement on Ancillary/Adjunct Penile Prosthesis Surgical Procedures: Part I.

OBJECTIVE: To create a society position statement on common adjunct penile prosthesis (PP) procedures. While the Medicare Current Procedural Terminology code book lists descriptions of procedures, it is very brief and lacks detail in the small subspecialty of prosthetic urology. At educational/research meetings, wide variation was found in how experts in prosthetic urology code the same procedures, and need for a standardized format in billing common ancillary surgery was voiced. METHODS: A subcommittee within the Society of Urologic Prosthetic Surgeons developed a survey assessing coding options for several procedures commonly adjunct to PP placement, which was distributed in the fall of 2022. The results of the survey were used to develop consensus statements on coding adjunct PP procedures; statements were distributed among society membership and meetings for approval. RESULTS: Thirty members replied to the survey; demographics were obtained as follows: 73% were trained in a fellowship, 50% identified as university/academic practitioners, and 50% in community/private practice; and 63% respondents place more than 50 implants annually. Only 1 of the 30 respondents stated confidence in coding for these ancillary procedures. Specifically, differences in how to code curvature correction procedures were observed throughout the survey results. CONCLUSION: Only 1 in 30 prosthetic urologists expressed confidence in coding and billing of adjunct PP procedures, further confirming the need for a society position statement. Therefore, we generated a consensus society position statement on common surgeries that are adjunct to PP placement.

Capture, Coding, and Reporting of Health Care and Medicine Information in Australian Workers' Compensation Systems.

OBJECTIVE: This study aims to characterize the approaches to collecting, coding, and reporting health care and medicines data within Australian workers' compensation schemes. METHODS: We conducted a cross-sectional survey of data and information professionals in major Australian workers' compensation jurisdictions. Questionnaires were developed with input from key informants and a review of existing documentation. RESULTS: Twenty-five participants representing regulators (40%) and insurers (60%) with representation from all Australian jurisdictions were included. Health care and medicines data sources, depth, coding standards, and reporting practices exhibited significant variability across the Australian workers' compensation schemes. CONCLUSIONS: Substantial variability exists in the capture, coding, and reporting of health care and medicine data in Australian workers' compensation jurisdictions. There are opportunities to advance understanding of medicines and health service delivery in these schemes through greater harmonization of data collection, data coding, and reporting.

[Evaluation of a coding guide on social determinants of health in primary care consultations: A mixed study]. / Evaluación de una guía de codificación de determinantes sociales de la salud en las consultas de atención primaria: Estudio mixto.

OBJECTIVE: To evaluate a coding guide for social determinants of health in primary care consultations as an effective tool in the professional's daily workflow. DESIGN: Mixed sequential explanatory study. Formed by a quantitative part (experimental) and a qualitative part (descriptive-evaluative). LOCATION: All the primary care teams of the Central Catalonia Management (32 teams). PARTICIPANTS AND SETTING: All nursing, social work and medical professionals working in the 32 primary care teams of the Catalan Institute of Health in Central Catalonia from February 2023 to July 2023. METHODS: A social determinants of health coding guide was developed. This guide was created in a multidisciplinary and multicenter manner. Purposive sampling. Quantitatively, the number of diagnoses recorded by the experimental group versus the control group was counted. Qualitatively, a thematic analysis was carried out from a socio-constructivist perspective. RESULTS: The results were significant and satisfactory. Using a quantitative methodology, the effectiveness of the use of the guide was assessed. A significant increase in the use of the social determinants was observed in the intervention group vs. the control group, with a percentage of post-intervention use of 19.53% in the control group and 32.26% in the intervention group (P < .001). The number of diagnoses recorded increased from 312 to 1322 in the intervention group, while it remained the same in the control group. The main factors identified through qualitative methodology that may explain the effectiveness of the guideline were: 1) the effectiveness of the guideline among primary care professionals, 2) the appropriateness of the guideline by assessing its usefulness and practicality, 3) feasibility and 4) specific contributions to the improvement of the guideline. CONCLUSIONS: The social determinants of health coding guide is effective, appropriate and can be implemented in the workflow of primary health care professionals for good recording of the social determinants of health.

Can the electronic medical record provide reliable indicators of primary care behavioral health fidelity? Comparison of accessibility and productivity indicators assessed through observational coding.

INTRODUCTION: The primary care behavioral health (PCBH) model is one of the most widely implemented integrated care approaches. However, research on the model has been limited by inconsistent measurement and reporting of model fidelity. One way of making measurement of PCBH model fidelity more routine is to incorporate fidelity indicators into the electronic medical record (EMR), though research regarding the accuracy of EMR data is mixed. In this study, we aimed to assess the reliability of EMR data as a PCBH fidelity measurement tool by comparing key EMR indicators of PCBH fidelity to those recorded by an observational coder. METHOD: Over an 8-month period (October 2021-May 2022), 12 behavioral health consultants (BHCs; 92% White, 75% female) across five primary care clinics recorded indicators of PCBH fidelity in the EMR as part of their routine charting of behavioral health visits. During that same period, one observational coder completed seven 4-hr visits per clinic to obtain multiple samples of data from each over time and recorded the same variables (i.e., percentage of visits prompted by warm handoffs, number of warm handoffs, and number of patient visits). We used bivariate correlations to test the associations between the EMR variables and the observer-coded variables. RESULTS: Correlations between EMR and observer-coded variables were moderate to strong, ranging from r = .46 to r = .97. DISCUSSION: Leveraging EMR data appears to be a fairly reliable approach to capturing indicators of PCBH model fidelity in the key domains of accessibility and high productivity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Abortion Miscoding-Legal Risks for Clinicians and Hospital Systems.

This Viewpoint discusses the legal risks physicians and health care facilities may incur by miscoding a surgical or chemical abortion as a miscarriage to conceal an abortion procedure.

Comparing reliability of ICD-10-based COVID-19 comorbidity data to manual chart review, a retrospective cross-sectional study.

International Statistical Classification of Disease and Related Health Problems, 10th Revision codes (ICD-10) are used to characterize cohort comorbidities. Recent literature does not demonstrate standardized extraction methods. OBJECTIVE: Compare COVID-19 cohort manual-chart-review and ICD-10-based comorbidity data; characterize the accuracy of different methods of extracting ICD-10-code-based comorbidity, including the temporal accuracy with respect to critical time points such as day of admission. DESIGN: Retrospective cross-sectional study. MEASUREMENTS: ICD-10-based-data performance characteristics relative to manual-chart-review. RESULTS: Discharge billing diagnoses had a sensitivity of 0.82 (95% confidence interval [CI]: 0.79-0.85; comorbidity range: 0.35-0.96). The past medical history table had a sensitivity of 0.72 (95% CI: 0.69-0.76; range: 0.44-0.87). The active problem list had a sensitivity of 0.67 (95% CI: 0.63-0.71; range: 0.47-0.71). On day of admission, the active problem list had a sensitivity of 0.58 (95% CI: 0.54-0.63; range: 0.30-0.68)and past medical history table had a sensitivity of 0.48 (95% CI: 0.43-0.53; range: 0.30-0.56). CONCLUSIONS AND RELEVANCE: ICD-10-based comorbidity data performance varies depending on comorbidity, data source, and time of retrieval; there are notable opportunities for improvement. Future researchers should clearly outline comorbidity data source and validate against manual-chart-review.

Advancements in the National Vital Statistics System to Meet the Real-Time Data Needs of a Pandemic.

The National Center for Health Statistics' (NCHS's) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133-2140. https://doi.org/10.2105/AJPH.2021.306519).

Out-of-Hospital COVID-19 Deaths: Consequences for Quality of Medical Care and Accuracy of Cause of Death Coding.

Objectives. To examine age and temporal trends in the proportion of COVID-19 deaths occurring out of hospital or in the emergency department and the proportion of all noninjury deaths assigned ill-defined causes in 2020. Methods. We analyzed newly released (March 2021) provisional COVID-19 death tabulations for the entire United States. Results. Children (younger than 18 years) were most likely (30.5%) and elders aged 64 to 74 years were least likely (10.4%) to die out of hospital or in the emergency department. In parallel, among all noninjury deaths, younger people had the highest proportions coded to symptoms, signs, and ill-defined conditions, and percentage symptoms, signs, and ill-defined conditions increased from 2019 to 2020 in all age-race/ethnicity groups. The majority of young COVID-19 decedents were racial/ethnic minorities. Conclusions. The high proportions of all noninjury deaths among children, adolescents, and young adults that were coded to ill-defined causes in 2020 suggest that some COVID-19 deaths were missed because of systemic failures in timely access to medical care for vulnerable young people. Public Health Implications. Increasing both availability of and access to the best hospital care for young people severely ill with COVID-19 will save lives and improve case fatality rates.

Examining the reliability of ICD-10 discharge coding in Red Cross War Memorial Children's Hospital administrative database.

BACKGROUND: Discharge diagnostic data from hospital administrative databases are often used to inform decisions relating to a variety of vital applications. These may include the allocation of resources, quality-of-care assessments, clinical research and formulation of healthcare policy. Accurately coded and reliably captured patient discharge data are of paramount importance for any hospital and health system to function efficiently. OBJECTIVES: To retrospectively examine the reliability of the International Classification of Diseases version 10 (ICD-10) discharge coding in Red Cross War Memorial Children's Hospital (RCWMCH)'s administrative database for primary and secondary discharge diagnoses, and to formulate recommendations for improvement to the current system. METHODS: This study was a retrospective folder review of 450 patient admissions to the short-stay and general paediatric wards at RCWMCH between 1 August 2013 and 1 September 2014. The principal investigator (PI) completed ICD-10 discharge coding for each admission and compared it with the corresponding admission data captured for each patient in the Clinicom (Siemens Medical Solutions, Germany) health information system. Agreement comparison was done to 4- and 3-character ICD-10 code specificity. RESULTS: Of the initial 450 randomly selected folders, 396 (88%) were analysed during the folder review process. The median number of total diagnoses (primary diagnosis plus secondary diagnoses) coded by the PI folder review was 3, with a distribution of 1 - 10 (interquartile range (IQR) 2 - 4). The median number of total diagnoses coded in Clinicom was 1, with a distribution of 1 - 3 (IQR 1 - 1). Agreement of primary diagnosis coding to 4 characters was 26.3%, with slight improvement to 34.3% when assessed to 3 characters. Agreement of secondary diagnoses to 4 characters was 14.9%, and 27.7% when assessed to 3 characters. CONCLUSIONS: Reliability of administrative ICD-10 discharge data from RCWMCH is poor. Inadequacies regarding the employment of dedicated and/or adequately trained coding personnel may significantly contribute to the problem and should be addressed.

Making the call in the field: Validating emergency medical services identification of anatomic trauma triage criteria.

BACKGROUND: The National Field Triage Guidelines were created to inform triage decisions by emergency medical services (EMS) providers and include eight anatomic injuries that prompt transportation to a Level I/II trauma center. It is unclear how accurately EMS providers recognize these injuries. Our objective was to compare EMS-identified anatomic triage criteria with International Classification of Diseases-10th revision (ICD-10) coding of these criteria, as well as their association with trauma center need (TCN). METHODS: Scene patients 16 years and older in the NTDB during 2017 were included. National Field Triage Guidelines anatomic criteria were classified based on EMS documentation and ICD-10 diagnosis codes. The primary outcome was TCN, a composite of Injury Severity Score greater than 15, intensive care unit admission, urgent surgery, or emergency department death. Prevalence of anatomic criteria and their association with TCN was compared in EMS-identified versus ICD-10-coded criteria. Diagnostic performance to predict TCN was compared. RESULTS: There were 669,795 patients analyzed. The ICD-10 coding demonstrated a greater prevalence of injury detection. Emergency medical service-identified versus ICD-10-coded anatomic criteria were less sensitive (31% vs. 59%), but more specific (91% vs. 73%) and accurate (71% vs. 68%) for predicting TCN. Emergency medical service providers demonstrated a marked reduction in false positives (9% vs. 27%) but higher rates of false negatives (69% vs. 42%) in predicting TCN from anatomic criteria. Odds of TCN were significantly greater for EMS-identified criteria (adjusted odds ratio, 4.5; 95% confidence interval, 4.46-4.58) versus ICD-10 coding (adjusted odds ratio 3.7; 95% confidence interval, 3.71-3.79). Of EMS-identified injuries, penetrating injury, flail chest, and two or more proximal long bone fractures were associated with greater TCN than ICD-10 coding. CONCLUSION: When evaluating the anatomic criteria, EMS demonstrate greater specificity and accuracy in predicting TCN, as well as reduced false positives compared with ICD-10 coding. Emergency medical services identification is less sensitive for anatomic criteria; however, EMS identify the most clinically significant injuries. Further study is warranted to identify the most clinically important anatomic triage criteria to improve our triage protocols. LEVEL OF EVIDENCE: Care management, Level IV; Prognostic, Level III.

Improved efficiency of coding systems with health information technology.

This study aimed to investigate the impact of health information technology (IT) on the Case Mix Index (CMI). This study was a retrospective cohort study using hospital financial data from the Office of Statewide Health Planning and Development (OSHPD) in California. A total of 309 unique hospitals were included in the study for 7 years, from 2009 to 2015, resulting in 2,135 hospital observations. The effects of health information technology (IT) on the Case Mix Index (CMI) was evaluated using dynamic panel data analysis to control endogeneity issues. This study found that more health IT adoption could lead to a lower CMI by improving coding systems. Policy makers, researchers, and healthcare providers must be cautious when interpreting the effect of health IT on the CMI. To encourage the adoption of health IT, the cost savings and reimbursement reductions resulting from health IT adoption should be compared. If any profit loss occurs (i.e., the cost savings is less than reimbursement reduction), more incentives should be provided to healthcare providers.