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Objective: The goal of this study was to assess the validity of the International Classification of Disease, 10th Version (ICD-10) administrative hospital discharge data and to determine whether there were improvements in the validity of coding for clinical conditions compared with ICD-9 Clinical Modification (ICD-9-CM) data., Methods: We reviewed 4,008 randomly selected charts for patients admitted from January 1 to June 30, 2003 at four teaching hospitals in Alberta, Canada to determine the presence or absence of 32 clinical conditions and to assess the agreement between ICD-10 data and chart data. We then re-coded the same charts using ICD-9-CM and determined the agreement between the ICD-9-CM data and chart data for recording those same conditions. The accuracy of ICD-10 data relative to chart data was compared with the accuracy of ICD-9-CM data relative to chart data., Results: Sensitivity values ranged from 9.3 to 83.1 percent for ICD-9-CM and from 12.7 to 80.8 percent for ICD-10 data. Positive predictive values ranged from 23.1 to 100 percent for ICD-9-CM and from 32.0 to 100 percent for ICD-10 data. Specificity and negative predictive values were consistently high for both ICD-9-CM and ICD-10 databases. Of the 32 conditions assessed, ICD-10 data had significantly higher sensitivity for one condition and lower sensitivity for seven conditions relative to ICD-9-CM data. The two databases had similar sensitivity values for the remaining 24 conditions., Conclusions: The validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions was generally similar though validity differed between coding versions for some conditions. The implementation of ICD-10 coding has not significantly improved the quality of administrative data relative to ICD-9-CM. Future assessments like this one are needed because the validity of ICD-10 data may get better as coders gain experience with the new coding system.

The influence of organisational factors on the quality of hospital coding using the International Statistical Classification of Diseases and Health Related Problems, 10th Revision, Australian Modification (ICD-10-AM) was investigated using a mixed quantitative-qualitative approach. The organisational variables studied were: hospital specialty; geographical locality; structural characteristics of the coding unit; education, training and resource supports for Clinical Coders; and quality control mechanisms. Baseline data on the hospitals' coding quality, measured by the Performance Indicators for Coding Quality tool, were used as an independent index measure. No differences were found in error rates between rural and metropolitan hospitals, or general and specialist hospitals. Clinical Coder allocation to "general" rather than "specialist" unit coding resulted in fewer errors. Coding Managers reported that coding quality can be improved by: Coders engaging in a variety of role behaviours; improved Coder career opportunities; higher staffing levels; reduced throughput; fewer time constraints on coding outputs and associated work; and increased Coder interactions with medical staff.

Tracking case outcomes helps improve care and create efficiency. But without universal reporting standards, the workload for hospitals is heavy and the data lacks uniformity.

Asthma is a national health priority area in Australia, and there is significant interest in capturing relevant detail about hospitalisations as a result of asthma. A public submission received by the National Centre for Classification in Health from a large teaching hospital in Victoria suggested that current classification terminology in ICD-10-AM did not adequately reflect the terms recorded in clinical inpatient records, and that patterns and severity of asthma better reflected current clinical terminology in Australian hospitals. The purpose of this study was to determine the validity of the public submission and inform future changes to ICD-10-AM. A representative sample of over 3000 asthma records across Australia and New Zealand were extracted, and the asthma terminology documented and codes assigned were recorded and analysed. The study concluded that there was little support for either pattern terminology or the current classification terminology; however, severity of asthma was commonly used in asthma documentation.

The Hospital In-Patient Enquiry and National Perinatal Reporting System (HIPE & NPRS) Unit of the Economic and Social Research Institute in Ireland requested a review of its coder training programs and data quality initiatives, primarily because of the decision to implement a major change in Ireland's morbidity classification in January 2005. In August 2004, a formative evaluation using qualitative methods was conducted to assess the Unit's programs and initiatives. A number of opportunities for building on the solid frameworks the Unit has implemented were identified. In this paper, we focus on the Unit's coder training programs. The Unit's data quality initiatives will be discussed in a subsequent paper (Bramley & Reid 2005).

An increase in accounts receivable or outstanding days to collect payment could be a sign that you have a shortage of medical coders. Fewer people are choosing the profession because of the growing complexity and heavier workloads. However, experts say hospitals must confront the problem or risk losing millions of dollars in unbilled charges.

To ease staffing burdens, Seton Healthcare Network established a home coding program. DNFB claims pending the health information management department's code assignment consistently decreased, reducing the organization's dollars holding by 25 percent. Decreases in contract and as-needed labor contributed to an operational cost savings of about $200,000 per year. The organization was able to fill all of its coding vacancies.

Is your chargemaster current, compliant, and comprehensive? In the age of APCs, healthcare facilities would do well to answer these questions regularly. Here's how an HIM professional can help.

After examining their charge description master management processes, HIM professionals, in conjunction with clinical and support departments, redesigned and automated several practice aspects. Turnaround times were reduced and end users are happier. Here's how they did it.

If coders, case managers, diagnosis-related group (DRG) coordinators, and physicians work cooperatively, then documentation and coding accuracy can be greatly improved. A five-step process is proving effective toward compliance and appropriate reimbursement in a large acute care setting.

An innovative program has brought physicians and coders together to reduce one facility's complication rates. To overcome physician resistance and improve physician documentation, quality management staff formed an ad hoc group of physicians to work with the coding supervisor to set clinical guidelines for the coding of complications, launched an in-house coding newsletter, and formed a coding subcommittee within the hospital's resource steering committee.

Objective: To evaluate the impact of a programme of training, education and awareness on the quality of the data collected through discharge abstracts., Study Design: Three random samples of hospital discharge abstracts relating to three different periods were studied. Quality control to evaluate the impact of systematic training and education activities was performed by checking the quality of abstracting medical records., Setting: The study was carried out at the Istituto Dermopatico dell'Immacolata, a research hospital in Rome, Italy; it has 335 beds specializing in dermatology and vascular surgery., Measures: Error rates in discharge abstracts were subdivided into six categories: wrong selection of the principal diagnosis (type A); low specificity of the principal diagnosis (type B); incomplete reporting of secondary diagnoses (type C); wrong selection of the principal procedure (type D); low specificity of the principal procedure (type E); incomplete reporting of procedures (type F). A specific rate of errors modifying classification in diagnosis related groups was then estimated., Results: Error types A, B and F dropped from 8.5% to 1.3%, from 15.8% to 1.6% and from 22% to 2.6% respectively. Error type D and E were zero in the third period of analysis (September-October 1997) compared with a rate of 0.7% and 4.1% in the third quarter of 1994. Error type C showed a slight decrease from 31.8% in 1994 to 27.2% in 1997. All differences in error types except incomplete reporting of secondary diagnoses were statistically significant. Five and a half per cent of cases were assigned to a different diagnoses related group after re-abstracting in 1997 as compared to 24.3% in the third quarter of 1994 and 23.8% in the first quarter of 1995., Discussion: Training and continuous monitoring, and feedback of information to departments have proved to be successful in improving the quality of abstracting information at patient level from the medical record. The effort to increase administrative data quality at hospital level will facilitate the use of those data sets for internal quality management activities and for population-based quality of care studies.

Now more than ever, HIM professionals must ensure that documentation of health information is thorough, clear, and accurate. Here are some strategies to solve problems and improve processes.

As compliance becomes an increasingly hot topic, how can a facility ensure its coding quality? Here are some ways that HIM departments can improve the quality of coding on a daily basis.

Auditing and monitoring are two important components of a compliance plan. The author answers the most frequently asked questions about audits. In addition, find out how to get started--and what to do with the results.

The aim of this study was to compare the quality of the reporting and coding of eclampsia in two routine data collections: the Victorian Inpatient Minimum Database (VIMD) and the Perinatal Data Collection Unit (PDCU). The validity of cases in the two data sets was confirmed by reference to the original medical record data. Only 12 cases were the same in both data sets (i.e., 35.3% agreement). There were an additional 51 cases that were reported to either one or the other of the data sets and, of these, only 15 (i.e., 29%) were confirmed as eclampsia. The overall number of cases confirmed for both systems in 1995 was 27, or 0.4 per 1000 confinements. Reasons for these discrepancies were investigated and three basic problems identified: quality of documentation in the medical record, coding errors, and use of data from computer-generated forms. Neither the VIMD nor the PDCU was regarded as having sufficiently accurate data for adequate reporting of maternal morbidity. By combining the information from both databases a better estimate of incidence can be obtained, but improved reporting and coding is essential for accurate assessment of this condition.

Competitive health care systems are improving their clinical and cost efficiency by performing clinical practice analyses. Large numbers of severity-adjusted cases provide the most objective data for making clinical efficiency decisions. The most cost-effective way to perform these analyses is to utilize well-coded, computer-based health information. This requires consistent coding of patients' comorbidities and complications as well as an interactive working relationship between coders and clinicians providing the clinical practice analysis. The article describes one hospital's evolving clinical efficiency information needs, how its health information system met them, the clinical practice analysis procedure, and the outcomes of this clinical practice analysis.

This paper summarises the findings of coding audits in seven hospitals and one re-audit conducted by the Health Department of Western Australia. The accuracy of the coding in the first audits, as measured by differences in AN-DRG assignment, varied from 83% to 93%. The accuracy of the coding in the re-audited hospital increased by 6% to 94.5%. The major coding problems related to incorrect abstraction of information from the medical record, inaccurate code assignment, non-application of the Australian Coding Standards, or poor documentation. On average, these coding problems resulted in a loss of nearly $400,000 per hospital per year in the surveyed hospitals.

This paper provides an overview of health information management practices in Singapore, based on personal observation and interviews with health information managers in five Singaporean hospitals. In Singapore borrowing a medical record often requires a formal request and a permanent tracer is maintained for each record. Medical officers generally have more responsibility than in Australia for coding, which is completed within three days of discharge. A Singapore-wide centralised patient database has been developed which is an important source of information about patient drug allergies. Record design and assembly, release of information and centralised registries are also described.

Preventing GIGO with concurrent, accurate coding. With so much riding on the accuracy of claims data, including outcomes and performance ratings, more should be done to improve the process of gathering this all-important information. That's the case at the University of Washington Medical Center, where coders actually work on the patient care floors, coding concurrently, interacting with physicians, and actually observing patients' treatment. Here's how the program works.

The following paper describes the development and evaluation of a Continuous Quality Improvement Model (CQIM) applied to the coding process of a public metropolitan teaching hospital. The evaluation was carried out by measuring changes to the accuracy, timeliness and quantity of the outputs of the coding process before and after the CQIM was implemented. For all three indicators of quality and productivity, improvements were observed after the CQIM was implemented. Continuous Quality Improvement methods are one strategy which health information managers can use to improve the quality of the coding process to support the provision of accurate coded data in a timely manner.

Encoded data on diagnoses and procedures are put to a broad range of uses. Coding accuracy and speed are imperative. One method that coding experts have recommended to improve coding accuracy and speed is automated encoders. The article describes the effect of automated encoders on coding accuracy and speed when used by trained coding staff. A study involving six Veterans Administration medical centers found that, overall, coding accuracy improved 19.4 percent after implementation of encoding software. The effect on coding speed, however, depended on the system set-up, with some set-ups actually reducing the number of discharges coded per day.