Health records as the basis of clinical coding: Is the quality adequate? A qualitative study of medical coders' perceptions

Recommendations for Improving Surveillance of Congenital Anomalies in Europe Using Healthcare Databases

BACKGROUND

Although accessing administrative data in healthcare databases may be a more time-efficient and cost-effective method of conducting surveillance, there is evidence suggesting that administrative data alone are not sufficient for population-based surveillance of congenital anomalies.

OBJECTIVE

To propose recommendations to maximise the potential use of healthcare databases for surveillance of congenital anomalies based on our data linkage experiences and results from the EUROlinkCAT study.

METHODS

EUROlinkCAT is a population-based cohort study of 99,416 children with anomalies born between 1995 and 2014. The congenital anomaly case records of children in 11 European congenital anomaly (EUROCAT) registries (eight countries) were linked to standardised administrative healthcare data (birth records, death records and hospital discharge records) to evaluate mortality and morbidity outcomes in these children. Overall, 97% of children with anomalies were successfully matched to their records in their national or regional administrative databases. Recommendations to improve surveillance of anomalies when using healthcare data were developed through establishing and analysing data from this cohort.

RESULTS

The primary recommendation is to develop systems to report anomalies diagnosed in foetuses who undergo a termination and link these data to their mothers. Each liveborn baby must be assigned a permanent unique identification number at birth to enable accurate linkage across healthcare databases. Implementing and improving existing algorithms to discriminate between major anomalies and suspected or minor anomalies will improve accuracy in coding. Heterogeneity in coding anomalies will improve by avoiding the use of 'unspecified' or 'other specified' codes in hospital databases. Relaxation of country-specific regulations concerning the suppression of small numbers are necessary to enable data to be combined across European countries.

CONCLUSION

Implementation of these recommendations will enable the information in electronic healthcare databases, in conjunction with Congenital Anomaly registries, to be fully exploited and hence will improve the surveillance of anomalies in children.

Prevalence and impact of comorbid mental disorders in hospitalized patients with obstructive sleep apnea (OSA): a nationwide study using administrative data

This study aimed to compare the prevalence of mental comorbidities between hospitalization episodes with and without obstructive sleep apnea (OSA), and to analyze the association of those mental comorbidities with modifiable risk factors that may potentiate OSA. An observational retrospective analysis was conducted using an administrative database of discharges from all Portuguese mainland public hospitals. All-cause adult hospitalizations occurring between 2008-2015 were dichotomized according to the existence of an OSA code (ICD-9-CM 327.23). Mental disorders were clustered into categories 650-670 of Clinical Classifications Software. Within the OSA group, binary logistic regressions were performed to analyze associations between mental comorbidities and modifiable OSA risk factors. Of 6 072 538 admissions, 36 385 had a primary or secondary diagnosis of OSA, which was associated with greater odds of comorbid anxiety disorders (adjusted odds ratio [aOR] = 1.84), bipolar disorders (aOR = 2.68), depressive disorders (aOR = 2.38), alcohol abuse (aOR = 1.29) and suicidal behaviors (aOR = 1.52) compared to those without OSA (all p < 0.05). Each of these mental comorbidities was associated with significantly greater odds of at least two of the four studied risk factors that may potentiate OSA (namely obesity, smoking, alcohol abuse and opioid/sedative abuse). These findings emphasize the complex interplay between OSA and mental disorders, suggesting relevant bidirectional relationships, and highlight the importance of comprehensive assessment and management of mental health in individuals with OSA.

Validation of the rates of adverse event incidence in administrative healthcare data through patient chart review: A scoping review protocol

Background

Patient safety is a key issue for health systems and a growing global public health challenge. Administrative healthcare data provide a coded summary of a patient and their encounter with the healthcare system. These aggregated datasets are often used to inform research and decisions relating to health service planning and therefore it is vital that they are accurate and reliable. Given the reported inaccuracy of these datasets for detecting and recording adverse events, there have been calls for validation studies to explore their reliability and investigate further their potential to inform research and health policy. Researchers have since carried out validation studies on the rates of adverse events in administrative data through chart reviews therefore, it seems appropriate to identify and chart the evidence and results of these studies within a scoping review.

Methods

The scoping review will be conducted in accordance with the Joanna Briggs Institute (JBI) methodology for scoping reviews. A search of databases such as PubMed, CINAHL, ScienceDirect and Scopus will be conducted in addition to a search of the reference lists of sourced publications and a search for grey literature. Following this, Covidence will be used to screen the sourced publications and subsequently extract data from the included sources. A numerical summary of the literature will be presented in addition to a charting based on the qualitative content analysis of the studies included.

Conclusions

This protocol provides the structure for the conduct of a review to identify and chart the evidence on validation studies on rates of adverse events in administrative healthcare data. This review will aim to identify research gaps, chart the evidence of and highlight any flaws within administrative datasets to improve extraction and coding practices and enable researchers and policy makers to use these data to their full potential.

Unsupervised algorithms to identify potential under-coding of secondary diagnoses in hospitalisations databases in Portugal

BACKGROUND

Quantifying and dealing with lack of consistency in administrative databases (namely, under-coding) requires tracking patients longitudinally without compromising anonymity, which is often a challenging task.

OBJECTIVE

This study aimed to (i) assess and compare different hierarchical clustering methods on the identification of individual patients in an administrative database that does not easily allow tracking of episodes from the same patient; (ii) quantify the frequency of potential under-coding; and (iii) identify factors associated with such phenomena.

METHOD

We analysed the Portuguese National Hospital Morbidity Dataset, an administrative database registering all hospitalisations occurring in Mainland Portugal between 2011-2015. We applied different approaches of hierarchical clustering methods (either isolated or combined with partitional clustering methods), to identify potential individual patients based on demographic variables and comorbidities. Diagnoses codes were grouped into the Charlson an Elixhauser comorbidity defined groups. The algorithm displaying the best performance was used to quantify potential under-coding. A generalised mixed model (GML) of binomial regression was applied to assess factors associated with such potential under-coding.

RESULTS

We observed that the hierarchical cluster analysis (HCA) + k-means clustering method with comorbidities grouped according to the Charlson defined groups was the algorithm displaying the best performance (with a Rand Index of 0.99997). We identified potential under-coding in all Charlson comorbidity groups, ranging from 3.5% (overall diabetes) to 27.7% (asthma). Overall, being male, having medical admission, dying during hospitalisation or being admitted at more specific and complex hospitals were associated with increased odds of potential under-coding.

DISCUSSION

We assessed several approaches to identify individual patients in an administrative database and, subsequently, by applying HCA + k-means algorithm, we tracked coding inconsistency and potentially improved data quality. We reported consistent potential under-coding in all defined groups of comorbidities and potential factors associated with such lack of completeness.

CONCLUSION

Our proposed methodological framework could both enhance data quality and act as a reference for other studies relying on databases with similar problems.

Perceptions of Portuguese medical coders on the transition to ICD-10-CM/PCS: A national survey

BACKGROUND

In Portugal, trained physicians undertake the clinical coding process, which serves as the basis for hospital reimbursement systems. In 2017, the classification version used for coding of diagnoses and procedures for hospital morbidity changed from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS).

OBJECTIVE

To assess the perceptions of medical coders on the transition of the clinical coding process from ICD-9-CM to ICD-10-CM/PCS in terms of its impact on data quality, as well as the major differences, advantages, and problems they faced.

METHOD

We conducted an observational study using a web-based survey submitted to medical coders in Portugal. Survey questions were based on a literature review and from previous focus group studies.

RESULTS

A total of 103 responses were obtained from medical coders with experience in the two versions of the classification system (i.e. ICD-9-CM and ICD-10-CM/PCS). Of these, 82 (79.6%) medical coders preferred the latest version and 76 (73.8%) considered that ICD-10-CM/PCS guaranteed higher quality of the coded data. However, more than half of the respondents (N = 61; 59.2%) believed that more time for the coding process for each episode was needed.

CONCLUSION

Quality of clinical coded data is one of the major priorities that must be ensured. According to the medical coders, the use of ICD-10-CM/PCS appeared to achieve higher quality coded data, but also increased the effort.

IMPLICATIONS

According to medical coders, the change off classification systems should improve the quality of coded data. Nevertheless, the extra time invested in this process might also pose a problem in the future.

The importance of SNOMED CT concept specificity in healthcare analytics

BACKGROUND

Healthcare data frequently lack the specificity level needed to achieve clinical and operational objectives such as optimising bed management. Pneumonia is a disease of importance as it accounts for more bed days than any other lung disease and has a varied aetiology. The condition has a range of SNOMED CT concepts with different levels of specificity.

OBJECTIVE

This study aimed to quantify the importance of the specificity of an SNOMED CT concept, against well-established predictors, for forecasting length of stay for pneumonia patients.

METHOD

A retrospective data analysis was conducted of pneumonia admissions to a tertiary hospital between 2011 and 2021. For inclusion, the primary diagnosis was a subtype of bacterial or viral pneumonia, as identified by SNOMED CT concepts. Three linear mixed models were constructed. Model One included known predictors of length of stay. Model Two included the predictors in Model One and SNOMED CT concepts of lower specificity. Model Three included the Model Two predictors and the concepts with higher specificity. Model performances were compared.

RESULTS

Sex, ethnicity, deprivation rank and Charlson Comorbidity Index scores (age-adjusted) were meaningful predictors of length of stay in all models. Inclusion of lower specificity SNOMED CT concepts did not significantly improve performance (ΔR2 = 0.41%, p = .058). SNOMED CT concepts with higher specificity explained more variance than each of the individual predictors (ΔR2 = 4.31%, p < .001).

CONCLUSION

SNOMED CT concepts with higher specificity explained more variance in length of stay than a range of well-studied predictors.

IMPLICATIONS

Accurate and specific clinical documentation using SNOMED CT can improve predictive modelling and the generation of actionable insights. Resources should be dedicated to optimising and assuring clinical documentation quality at the point of recording.

Assessment of clinical miscoding errors and potential financial their implications on healthcare management - A case of local hospital in Najran, Saudi Arabia

Background

Healthcare systems can potentially improve their safety, quality of service, and performance efficiency with a cost reduction, through the introduction and implementation of healthcare information management systems. This study aims to examine the frequency of miscoding errors in principal and secondary diagnoses, exploring demographic and coder-related factors contributing to these errors through the use of the QuadraMed system. The study also investigates the association of coding errors with patient safety and service quality to estimate the potential financial implications resulting from these inaccuracies in the healthcare system.

Methods

This analytical cross-sectional retrospective study was conducted at a local hospital in Najran, Saudi Arabia, from July 2021 to February 2022 using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) coding system. The costing and financial data were collected from the reimbursement department for eligible 750 patient cases in terms of payment mode, services availed, and length of stay. The financial claims were evaluated to estimate the impact on the quality of service and patient safety. The reimbursement amount was calculated based on codes. The data were analyzed using SPSS and the odds ratio was calculated to estimate the risk of major coding errors in different departments.

Results

Primary codes 240 (32%) and 40 (5.3) secondary codes were reviewed and percentages and inaccuracies were calculated after recording. The percentage of inaccurate medical codes in principal diagnosis was 57(26.8%) and the percentage of inaccurate medical codes in secondary diagnosis was 21 (9.9%). The primary diagnostic codes have more coding errors with a total number of 240 (32%) coding errors with a moderate level of agreement between the original coder and independent coder with a kappa value of 0.462. The identified recording was done by the independent coder, and the secondary diagnostic code showed 40 (5.3%) cases, with a poor kappa value of 0.128. The results showed the highest number of primary diagnostic codes was among surgery clinics 79 (63.2%). The highest number of secondary diagnostic codes were reported among consultant clinics 12 (9.6%).

Conclusions

The study concludes that the identification of miscoding in the healthy population has a financial impact on the healthcare organization's infrastructure.

Effect of Repeated Intravitreal Injections in Glaucoma Spectrum Diseases

Purpose

To evaluate whether repeated intravitreal injections (IVI) with an anti-vascular endothelial growth factor (anti-VEGF) agent are associated with glaucomatous progression in eyes with glaucoma spectrum diseases (GSD).

Methods

Single-center, retrospective, longitudinal study of patients with bilateral and similar GSD who: (1) received ≥8 IVI in only one eye during the study period; (2) had ≥2 retinal nerve fiber layer thickness (RNFL) measurements obtained by spectral-domain optical coherence tomography (SD-OCT) at least 12 months apart. The primary outcome was the absolute RNFL thickness change, comparing injected and fellow uninjected eyes. Linear mixed effects models were constructed, including a multivariable model.

Results

Sixty-eight eyes from 34 patients were included, 34 injected and 34 fellow uninjected eyes. Average baseline age was 67.68±21.77 years with a follow-up of 3.66±1.89 years and 25.12±14.49 IVI. RNFL thickness decreased significantly from 80.92±15.78 to 77.20±17.35 μm (p<0.001; -1.18±1.93 μm/year) in injected eyes and from 79.95±17.91 to 76.61±17.97 μm (p<0.001; -1.07±0.98 μm/year) in uninjected eyes. In a multivariable linear mixed model of injected eyes, only higher baseline RNFL thickness (p < 0.001) significantly predicted higher absolute RNFL thickness loss. Neither absolute RNFL thickness variation (p=0.716) nor RNFL rate (p=0.779) was significantly different between paired injected and uninjected eyes. Absolute IOP variation was not significantly different between groups (16.62±4.77 to 15.09±4.34 mmHg in injected eyes and 17.68±5.01 to 14.50±3.39 mmHg in fellow uninjected eyes; p=0.248). The proportion of eyes receiving glaucoma medical treatment increased significantly in both groups (55.9% to 76.5% in injected eyes; p=0.039; 58.8% to 76.5% in uninjected eyes; p = 0.031). The number of glaucoma medications also increased significantly in both groups (1.03±1.11 to 1.59±1.18 glaucoma medications in injected eyes; p=0.003; 1.09±1.11 to 1.56±1.19 glaucoma medications in uninjected eyes; p=0.003).

Conclusion

Repeated IVI do not seem to accelerate glaucomatous progression. Future studies with a longer follow-up are needed.

Development of a New Knee Arthroscopy Operative Proforma Saving Thousands of British Pounds

Coding inaccuracies in documentation of surgical procedures misrepresent the productivity of departments, with harmful fiscal consequences and detract from effective clinical governance. We aimed to assess the extent of this within our centres.  We retrospectively analysed the operative records of 34 patients from two centres over a period of a month, undergoing varying arthroscopic knee operations. We found that 50% of cases had incorrect coding for procedures performed. On review of the clinical coding, the loss of payment summed up to £29,325.  The flawed coding practices stemmed from the heterogeneity and convolution in documentation of procedures. Our intervention was the development of a multi-faceted arthroscopic operation note proforma, centred on concise documentation for appropriate codes to be gleaned. We re-audited our new proforma, retrospectively collating data on 37 patients over a period of five months undergoing arthroscopic knee procedures. We found only 5% of cases were coded incorrectly, summing to a loss in tariff payment of £2654.  In conclusion, poor quality of documentation and written communication between surgical and coding departments can have drastic ramifications for funding. An active refinement of this process can ultimately help to provide more resources for improved patient care.

Surfacing undiagnosed disease: consideration, counting and coding

The diagnostic odyssey for people living with rare diseases (PLWRD) is often prolonged for myriad reasons including an initial failure to consider rare disease and challenges to systemically and systematically identifying and tracking undiagnosed diseases across the diagnostic journey. This often results in isolation, uncertainty, a delay to targeted treatments and increase in risk of complications with significant consequences for patient and family wellbeing. This article aims to highlight key time points to consider a rare disease diagnosis along with elements to consider in the potential operational classification for undiagnosed rare diseases during the diagnostic odyssey. We discuss the need to create a coding framework that traverses all stages of the diagnostic odyssey for PLWRD along with the potential benefits this will have to PLWRD and the wider community.

Identification of root causes of clinical coding problems in Iranian hospitals

BACKGROUND

Improving the quality of coded data requires the identification and evaluation of the root causes of clinical coding problems to inform appropriate solutions.

OBJECTIVE

The objective of this study was to identify the root causes of clinical coding problems.

METHOD

Twenty-one clinical coders from three cities in Iran were interviewed. The five formal categories in Ishikawa's cause-and-effect diagram were applied as pre-determined themes for the data analysis.

RESULTS

The study indicated 16 root causes of clinical coding problems in the five main themes: (i) policies, protocols, and processes (lack of clinical documentation guidelines; lack of audit of clinical coding and feedback to clinical coders; the long interval between documentation and clinical coding; and not using coded data for reimbursement; (ii) individual factors (shortage of clinical coders; low-skilled clinical coders; clinical coders' insufficient communication with physicians; and the lack of continuing education; (iii) equipment and materials (incomplete medical records; lack of access to electronic medical records and electronic coding support tools; (iv) working environment (lack of an appropriate, dynamic, and motivational workspace; and (v) management factors (mangers' inattention to the importance of coding and clinical documentation; and to providing the required staff support.

CONCLUSION

The study identified 16 root causes of clinical coding problems that stand in the way of clinical coding quality improvement.

IMPLICATIONS

The quality of clinical coding could be improved by hospital managers and health policymakers taking these problems into account to develop strategies and implement solutions that target the root causes of clinical coding problems.

Dementia-related agitation: a 6-year nationwide characterization and analysis of hospitalization outcomes

OBJECTIVES

To characterize all hospitalizations held in mainland Portugal (2010-2015) with dementia-related agitation based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding, and to investigate whether there is a relationship between agitation and hospitalization outcomes.

METHODS

A retrospective observational study was conducted using an administrative dataset containing data from all mainland Portuguese public hospitals. Only hospitalization episodes for patients aged over 65 years who have received a dementia diagnosis ascertained by an ICD-9-CM code of dementia with behavioral disturbance (294.11 and 294.21) and dementia without behavioral disturbance (294.10 and 294.20) were selected. Episodes were further grouped according to the presence of an agitation code. For each episode, demographic data and hospitalization outcomes, including length of stay (LoS), in-hospital mortality, discharge destination and all-cause hospital readmissions, were sourced from the dataset. Comparative analyses were performed and multivariable logistic methods were used to estimate the adjusted associations between agitation (exposure) and outcomes.

RESULTS

Overall, 53,156 episodes were selected, of which 6,586 had an agitation code. These were mostly related to male, younger inpatients (mean 81.19 vs. 83.29 years, p < 0.001), had a higher comorbidity burden, stayed longer at the hospital (median 9.00 vs. 8.00 days, p < 0.001) and frequently ended being transferred to another facility with inpatient care. Agitation was shown to independently increase LoS (aOR = 1.385; 95%CI:1.314-1.461), but not the risk of a fatal outcome (aOR = 0.648; 95%CI:0.600-0.700).

CONCLUSION

These results support the importance of detecting and managing agitation early on admission, since its prompt management may prevent lengthy disruptive hospitalizations.

Performance assessment of medical service for organ transplant department based on diagnosis-related groups: A programme incorporating ischemia-free liver transplantation in China

Background

In July 2017, the first affiliated hospital of Sun Yat-sen university carried out the world's first case of ischemia-free liver transplantation (IFLT). This study aimed to evaluate the performance of medical services pre- and post-IFLT implementation in the organ transplant department of this hospital based on diagnosis-related groups, so as to provide a data basis for the clinical practice of the organ transplant specialty.

Methods

The first pages of medical records of inpatients in the organ transplant department from 2016 to 2019 were collected. The China version Diagnosis-related groups (DRGs) were used as a risk adjustment tool to compare the income structure, service availability, service efficiency and service safety of the organ transplant department between the pre- and post-IFLT implementation periods.

Results

Income structure of the organ transplant department was more optimized in the post-IFLT period compared with that in the pre-IFLT period. Medical service performance parameters of the organ transplant department in the post-IFLT period were better than those in the pre-IFLT period. Specifically, case mix index values were 2.65 and 2.89 in the pre- and post-IFLT periods, respectively (p = 0.173). Proportions of organ transplantation cases were 14.16 and 18.27%, respectively (p < 0.001). Compared with that in the pre-IFLT period, the average postoperative hospital stay of liver transplants decreased by 11.40% (30.17 vs. 26.73 days, p = 0.006), and the average postoperative hospital stay of renal transplants decreased by 7.61% (25.23 vs.23.31 days, p = 0.092). Cost efficiency index decreased significantly compared with that in the pre-IFLT period (p < 0.001), while time efficiency index fluctuated around 0.83 in the pre- and post-IFLT periods (p = 0.725). Moreover, the average postoperative hospital stay of IFLT cases was significantly shorter than that of conventional liver transplant cases (p = 0.001).

Conclusion

The application of IFLT technology could contribute to improving the medical service performance of the organ transplant department. Meanwhile, the DRGs tool may help transplant departments to coordinate the future delivery planning of medical service.

Attitudes and perceptions of traditional health practitioners towards documentation of patient health information in their practice in eThekwini Municipality, KwaZulu-Natal, Natal Province, South Africa

BACKGROUND

Documentation of patient health information in the form of patient medical records (PMRs) is an essential, ethical and regulatory requirement in any healthcare system. African traditional medicine (ATM) exists parallel to biomedicine and continues to play a significant role in primary healthcare of the majority of South Africans. The World Health Organization (WHO) has promoted the integration of ATM into the national health system of South Africa. Patient health information documentation can facilitate this integration, and PMRs promote communication between the two health systems through referrals. Documentation in biomedicine is a clear, compulsory, routine activity, but does not occur regularly or routinely in ATM.

OBJECTIVE

To examine the attitudes and perceptions of traditional health practitioners (THPs) towards documentation of patient health information in their practice.

METHODS

This quantitative cross-sectional survey involved snowball sampling to recruit THPs in Umlazi Township and rural parts surrounding the township, in Durban, South Africa. A semi-structured questionnaire was used. Quantitative data were analysed using SPSS 25 and the Relative Importance Index (RII) and qualitative data were analysed using Excel for themes.

RESULTS

Sampling resulted in 248 THPs of whom 178 (72%) were females. The RII ranked the factors that negatively influenced the participants' attitudes towards documentation of patient health information. Of the 178 females who participated in the study, 129 (72.5%) showed their willingness to introduce documentation in their practice. Of the 127 participants with less than 10 years of practice experience, 126 (99.2%) agreed to the importance of introducing PMRs in their practice. The majority of participants perceived documentation of patient health information as vital to improve their practice. A prominent theme was that the THPs regarded documenting patient health information as important and effective in their practice.

CONCLUSION

More than half of participants showed positive attitudes and perceptions towards documenting of patient health information in ATM. The majority of the participants in this study acknowledged the importance of introducing documentation of patient health information in their practice even though they lacked experience and more knowledge. This reflects a need for essential intervention in developing specialised tools to begin promoting documentation of patient health information in ATM.

Quality analysis of a breast thermal images database

The study and early detection of breast cancer are key for its treatment. We carry out an exhaustive analysis of the most used database for mastology research with infrared images, analyzing the anomalies according to five quality dimensions: completeness, correctness, concordance, plausibility, and currency. We established control queries that looked for these anomalies and that can be used to ensure the quality of the database. Finally, we briefly review the more than 40 papers that use this database and that do not mention any of these anomalies. When analyzing the database, we found 365 anomalies related to personal and clinical data, and thermal images. The errors found in our research may lead to a modification of the results and conclusions made in the articles found in the literature, serve as a basis for improvements in the quality of the database, and help future researchers to work with it.

Multidimensional analysis of job advertisements for medical record information managers

Objective

The rapid growth of the medical industry has resulted in a tremendous increase in medical record data, which can be utilized for hospital management, aiding in diagnosis and treatment, medical research, and other purposes. For data management and analysis, medical institutions require more qualified medical record information managers. In light of this, we conducted an analysis of the qualifications, abilities, and job emphasis of medical record information managers in order to propose training recommendations.

Materials and methods

From online job posting sites, a sample of 241 job advertisements for medical record information management positions posted by Chinese healthcare institutions were collected. We conducted word frequency and keyword co-occurrence analysis to uncover overall demands at the macro level, and job analysis to investigate job-specific disparities at the micro level. Based on content analysis and job analysis, a competency framework was designed for medical record information managers.

Results

The most frequent keywords were "code," "job experience," and "coding certification," according to the word frequency analysis. The competency framework for managers of medical record information is comprised of seven domains: essential knowledge, medical knowledge, computer expertise, problem-solving skills, leadership, innovation, and attitude and literacy. One of the fundamental skills required of medical record information managers is coordination and communication. Similarly, knowledge and skill requirements emphasize theoretical knowledge, managerial techniques, performance enhancement, and innovation development.

Conclusion

According to organization type and job differences, the most crucial feature of the job duties of medical record information managers is cross-fertilization. The findings can be utilized by various healthcare organizations for strategic talent planning, by the field of education for medical record information managers for qualification and education emphasis adjustment, and by job seekers to enhance their grasp of the profession and self-evaluation.

Demystifying the role of anaesthetists in clinical coding in the Australian healthcare system

Despite the self-evident importance of hospital funding, many anaesthetists remain unsure of exactly how their daily work relates to hospital reimbursement. A lack of awareness of the nuances of the Australian hospital activity-based funding system has the potential to affect anaesthetic department reimbursement and thus resourcing. Activity-based funding relies on clinical coders reviewing clinical documentation and quantifying the care given to a patient during an admission. Errors in funding allocation may arise when there is a disconnect between the work performed and the information coded. In anaesthesia, there are several factors impeding this process, including clinical understanding of coding, system setup and coders' understanding of anaesthesia. This article explores these factors from the clinical anaesthetist's point of view and suggests solutions, such as awareness and education, clinician-coder cooperation and redesign of documentation systems at a systems level that anaesthetic departments can incorporate.

Clinical Coders' Perspectives on Pressure Injury Coding in Acute Care Services in Victoria, Australia

Pressure injuries (PIs) substantively impact quality of care during hospital stays, although only when they are severe or acquired as a result of the hospital stay are they reported as quality indicators. Globally, researchers have repeatedly highlighted the need to invest more in quality improvement, risk assessment, prevention, early detection, and care for PI to avoid the higher costs associated with treatment of PI. Coders' perspectives on quality assurance of the clinical coded PI data have never been investigated. This study aimed to explore challenges that hospital coders face in accurately coding and reporting PI data and subsequently, explore reasons why data sources may vary in their reporting of PI data. This article is based upon data collected as part of a multi-phase collaborative project to build capacity for optimizing PI prevention across Monash Partners health services. We have conducted 16 semi-structured phone interviews with clinical coders recruited from four participating health services located in Melbourne, Australia. One of the main findings was that hospital coders often lacked vital information in clinicians' records needed to code PI and report quality indicators accurately and highlighted the need for quality improvement processes for PI clinical documentation. Nursing documentation improvement is a vital component of the complex capacity building programs on PI prevention in acute care services and is relied on by coders. Coders reported the benefit of inter-professional collaborative workshops, where nurses and coders shared their perspectives. Collaborative workshops had the potential to improve coders' knowledge of PI classification and clinicians' understanding of what information should be included when documenting PI in the medical notes. Our findings identified three methods of quality assurance were important to coders to ensure accuracy of PI reporting: (1) training prior to initiation of coding activity and (2) continued education, and (3) audit and feedback communication about how to handle specific complex cases and complex documentation. From a behavioral perspective, most of the coders reported confidence in their own abilities and were open to changes in coding standards. Transitioning from paper-based to electronic records highlighted the need to improve training of both clinicians and coders.

All Patient Refined-Diagnosis Related Groups' (APR-DRGs) Severity of Illness and Risk of Mortality as predictors of in-hospital mortality

The aims of this study were to assess All-Patient Refined Diagnosis-Related Groups' (APR-DRG) Severity of Illness (SOI) and Risk of Mortality (ROM) as predictors of in-hospital mortality, comparing with Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) scores. We performed a retrospective observational study using mainland Portuguese public hospitalizations of adult patients from 2011 to 2016. Model discrimination (C-statistic/ area under the curve) and goodness-of-fit (R-squared) were calculated. Our results comprised 4,176,142 hospitalizations with 5.9% in-hospital deaths. Compared to the CCI and ECI models, the model considering SOI, age and sex showed a statistically significantly higher discrimination in 49.6% (132 out of 266) of APR-DRGs, while in the model with ROM that happened in 33.5% of APR-DRGs. Between these two models, SOI was the best performer for nearly 20% of APR-DRGs. Some particular APR-DRGs have showed good discrimination (e.g. related to burns, viral meningitis or specific transplants). In conclusion, SOI or ROM, combined with age and sex, perform better than more widely used comorbidity indices. Despite ROM being the only score specifically designed for in-hospital mortality prediction, SOI performed better. These findings can be helpful for hospital or organizational models benchmarking or epidemiological analysis.

Developing a Feasible and Credible Method for Analyzing Healthcare Documents as Written Data

Healthcare provides a rich, and constantly increasing, number of written documents, which are underutilized in research data for health and nursing sciences, but previous literature has only provided limited guidance on the process of document analysis. The aim of this paper is to provide a methodological framework for analyzing health care documents as written data, based on a systematic methodological review and the research team’s experience of the method. Based on the results, the methods consist of seven phases: (i) identify the purpose, (ii) determine the document selection strategy, (iii) select or design an extraction matrix, (iv) carry out pilot testing, (v) collect and analyze the data, (vi) consider the credibility, and (vii) ethics of the study. The framework that has been developed can be used to carry out document analysis studies that are both feasible and credible.

COVID-19 surveillance data quality issues: a national consecutive case series

OBJECTIVES

High-quality data are crucial for guiding decision-making and practising evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese epidemiological surveillance dataset, our study aims to assess COVID-19 data quality issues and suggest possible solutions.

SETTINGS

On 27 April 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On 4 August, an updated dataset (DGSAugust) was also obtained.

PARTICIPANTS

All COVID-19-confirmed cases notified through the medical component of National System for Epidemiological Surveillance until end of June.

PRIMARY AND SECONDARY OUTCOME MEASURES

Data completeness and consistency.

RESULTS

DGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (eg, 4075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (eg, the variable 'underlying conditions' had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily.

CONCLUSIONS

Important quality issues of the Portuguese COVID-19 surveillance datasets were described. These issues can limit surveillance data usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed-for example, simplification of data entry processes, constant monitoring of data, and increased training and awareness of healthcare providers-as low data quality may lead to a deficient pandemic control.

Time-trends and predictors of interhospital transfers and 30-day rehospitalizations after acute coronary syndrome from 2000-2015

Aims

Assess trends and factors associated with interhospital transfers (IHT) and 30-day acute coronary syndrome (ACS) rehospitalizations in a national administrative database of patients admitted with an ACS between 2000–2015.

Methods and results

Cohort study of patients hospitalized with ACS from 2000 to 2015, using a validated linkage algorithm to identify and link patient-level sequential hospitalizations occurring within 30 days from first admission (considering all hospitalizations within the 30-day timeframe as belonging to the same ACS episode of care-ACS-EC). From 212,481 ACS-EC, 42,670 (20.1%) had more than one hospitalization. ACS-EC hospitalization rates decreased throughout the study period (2000: 207.7/100.000 person-years to 2015: 185,8/100,000 person-years, p for trend <0.05). Proportion of IHT increased from 10.5% in 2000 to 20.1% in 2015 compared to a reduction in both planned and unplanned 30-day ACS rehospitalization from 9.0% in 2000 to 2.7% in 2015. After adjusting for patient and first admission hospital’s characteristics, compared to 2000–2003, in 2012–2015 the odds of IHT increased by 3.81 (95%CI: 3.65–3.98); the odds of unplanned and planned 30-day ACS rehospitalization decreased by 0.36 (95%CI: 0.33; 0.39) and 0.47 (95%CI: 0.43; 0.53), respectively. Female sex, older age and the presence and severity of comorbidities were associated with lower likelihood of being transferred or having a planned 30-day ACS rehospitalization. Unplanned 30-day ACS rehospitalization was more likely in patients with higher comorbidity burden.

Conclusion

IHT and 30-day ACS rehospitalization reflect coronary referral network efficiency and access to specialized treatment. Identifying factors associated with higher likelihood of IHT and 30-day ACS rehospitalization may allow heightened surveillance and interventions to reduce rehospitalizations and inequities in access to specialized treatment.

Factors affecting the quality of diagnosis coding data with a triangulation view: A qualitative study

OBJECTIVE

The most important challenge in utilizing medical record codes is the quality of coding data. The present study aims to investigate factors affecting the quality of diagnosis coding from different aspects covering different stakeholders in a multi-dimensional approach.

METHODS

First, we used Conventional Content Analysis to maximally gather all effective factors. As such, semi-structured interviews were conducted with medical record coders (N = 32) at the referral hospitals in Mashhad, Iran. Second, 86 hospital staff members from 25 provinces were surveyed using a web-based questionnaire. Finally, a focus group discussion was conducted among coders (N = 18) in different hospitals across the country.

RESULTS

In general, the barriers to quality of inpatient record coding can be classified into three categories: (I) physician-related, (II) coder-related, and (III) managerial, financial and administrative factors.

CONCLUSION

A triangulation view (related to coders, physicians as well as managerial, financial and administrative dimensions) could be used to identify the barriers affecting the quality of diagnosis coding data. The results of this study may help policymakers in development and implementation of appropriate strategies and effective interventions to improve the quality of clinical coding.

Spatial Patterns in Hospital-Acquired Infections in Portugal (2014-2017)

BACKGROUND

Hospital-Acquired Infections (HAIs) represent the most frequent adverse event associated with healthcare delivery and result in prolonged hospital stays and deaths worldwide.

AIM

To analyze the spatial patterns of HAI incidence from 2014 to 2017 in Portugal.

METHODS

Data from the Portuguese Discharge Hospital Register were used. We selected episodes of patients with no infection on admission and with any of the following HAI diagnoses: catheter-related bloodstream infections, intestinal infections by Clostridium difficile, nosocomial pneumonia, surgical site infections, and urinary tract infections. We calculated age-standardized hospitalization rates (ASHR) by place of patient residence. We used empirical Bayes estimators to smooth the ASHR. The Moran Index and Local Index of Spatial Autocorrelation (LISA) were calculated to identify spatial clusters.

RESULTS

A total of 318,218 HAIs were registered, with men accounting for 49.8% cases. The median length of stay (LOS) was 9.0 days, and 15.7% of patients died during the hospitalization. The peak of HAIs (n = 81,690) occurred in 2015, representing 9.4% of the total hospital admissions. Substantial spatial inequalities were observed, with the center region presenting three times the ASHR of the north. A slight decrease in ASHR was observed after 2015. Pneumonia was the most frequent HAI in all age groups.

CONCLUSION

The incidence of HAI is not randomly distributed in the space; clusters of high risk in the central region were seen over the entire study period. These findings may be useful to support healthcare policymakers and to promote a revision of infection control policies, providing insights for improved implementation.

Classification performance of administrative coding data for detection of invasive fungal infection in paediatric cancer patients

BACKGROUND

Invasive fungal infection (IFI) detection requires application of complex case definitions by trained staff. Administrative coding data (ICD-10-AM) may provide a simplified method for IFI surveillance, but accuracy of case ascertainment in children with cancer is unknown.

OBJECTIVE

To determine the classification performance of ICD-10-AM codes for detecting IFI using a gold-standard dataset (r-TERIFIC) of confirmed IFIs in paediatric cancer patients at a quaternary referral centre (Royal Children's Hospital) in Victoria, Australia from 1st April 2004 to 31st December 2013.

METHODS

ICD-10-AM codes denoting IFI in paediatric patients (<18-years) with haematologic or solid tumour malignancies were extracted from the Victorian Admitted Episodes Dataset and linked to the r-TERIFIC dataset. Sensitivity, positive predictive value (PPV) and the F1 scores of the ICD-10-AM codes were calculated.

RESULTS

Of 1,671 evaluable patients, 113 (6.76%) had confirmed IFI diagnoses according to gold-standard criteria, while 114 (6.82%) cases were identified using the codes. Of the clinical IFI cases, 68 were in receipt of ≥1 ICD-10-AM code(s) for IFI, corresponding to an overall sensitivity, PPV and F1 score of 60%, respectively. Sensitivity was highest for proven IFI (77% [95% CI: 58-90]; F1 = 47%) and invasive candidiasis (83% [95% CI: 61-95]; F1 = 76%) and lowest for other/unspecified IFI (20% [95% CI: 5.05-72%]; F1 = 5.00%). The most frequent misclassification was coding of invasive aspergillosis as invasive candidiasis.

CONCLUSION

ICD-10-AM codes demonstrate moderate sensitivity and PPV to detect IFI in children with cancer. However, specific subsets of proven IFI and invasive candidiasis (codes B37.x) are more accurately coded.

Findings from the Health Information Management Section of the 2020 International Medical Informatics Association Yearbook

Objectives : To summarize the recent literature and research and present a selection of the best papers published in 2019 in the field of Health Information Management (HIM) and Health Informatics.

Methods : A systematic review of the literature was performed by the two section editors with the help of a medical librarian. The search through bibliographic databases for HIM-related papers was achieved using both MeSH headings and keywords in titles and abstracts. A shortlist of 15 candidate best papers was first selected by section editors before being peer-reviewed by independent external reviewers.

Results : Over half of the 15 papers addressed the issue of data quality in the electronic health record (EHR). In addition to the focus on data quality, there were papers on other topics of long-standing interest to the field of HIM. These topics include privacy, security, and confidentiality of health information, comparability of different coding vocabularies, classifications and terminologies, and the HIM workforce. Finally, there were papers on newer topics for the HIM field, including mobile Health (mHealth), EHR use by public health departments, and usability of different strategies for displaying information in the EHR.

Conclusions : Traditional HIM concerns about HIM practice and workforce as well as issues about data in the EHR including data quality, coding, and privacy and confidentiality continue to be a large part of the HIM research literature. However, newer topics which reflect innovative and emerging technologies, usability assessments, and the application of the EHR outside the traditional clinical setting are starting to appear and more research is needed on these newer areas.

Problems and Barriers during the Process of Clinical Coding: a Focus Group Study of Coders' Perceptions

Coded data are the basis of information systems in all countries that rely on Diagnosis Related Groups in order to reimburse/finance hospitals, including both administrative and clinical data. To identify the problems and barriers that affect the quality of the coded data is paramount to improve data quality as well as to enhance its usability and outcomes. This study aims to explore problems and possible solutions associated with the clinical coding process. Problems were identified according to the perspective of ten medical coders, as the result of four focus groups sessions. This convenience sample was sourced from four public hospitals in Portugal. Questions relating to problems with the coding process were developed from the literature and authors' expertise. Focus groups sessions were taped, transcribed and analyzed to elicit themes. Variability in the documents used for coding, illegibility of hand writing when coding on paper, increase of errors due to an extra actor in the coding process when transcribed from paper, difficulties in the diagnoses' coding, coding delay and unavailability of resources and tools designed to help coders, were some of the problems identified. Some problems were identified and solutions such as the standardization of the documents used for coding an episode, the adoption of the electronic coding, the development of tools to help coding and audits, and the recognition of the importance of coding by the management were described as relevant factors for the improvement of the quality of data.