Search

The International Classification of Diseases 10th Revision Procedure Classification System (ICD-10-PCS) has been developed as a replacement for Volume 3 of the International Classification of Diseases 9th Revision. The development of ICD-10-PCS was funded by the U.S. Health Care Financing Administration. ICD-10-PCS has a multi-axial seven character alphanumerical code structure, which provides a unique code for all substantially different procedures and which allows new procedures to be easily incorporated as new codes. ICD-10-PCS was under development for over five years and the initial draft was formally tested and evaluated by an independent contractor. The final version of the ICD-10-PCS was released in the spring of 1998. The design, development and testing of ICD-10-PCS are discussed.

This article applies the concepts of knowledge management to diagnostic and procedural coding performed by health care providers. The process of diagnostic and procedural coding is both an art and a science. In particular, the information stored away in the minds of individuals performing the coding function is ripe for the basis of an effective knowledge Health Information Management (HIM) coding management system. In this article, we explore the issues and processes that HIM professionals can take advantage of in standardizing the coding function.

Knowledge management (KM) is a new management theory embraced by hundreds of writers in multiple countries and industries. Although a single fixed methodology does not exist, several methodological elements are common to most KM writtings. KM has a number of similarities to and differences from quality improvement and reengineering. It can be applied to at least two universes in health care organizations. Applying KM to a case study in health information management (HIM) departments yielded much useful information but also proved unable ultimately to resolve the problem being studied. HIM professionals can embrace elements about KM that are good and useful, while ignoring elements that do not work.

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.

Quality ICD-9-CM coding depends on the selection of the appropriate diagnosis codes and the proper sequencing of the codes. A simple, diagnosis code-sequencing error was selected to evaluate the quality of diagnosis coding within the National Inpatient Sample of the Healthcare Costs and Utilization Project. The source of coding variation originates at the hospital level. Coding error rates were found to vary widely among states, hospitals within states, geographic location, and hospital characteristics. Coding errors were significantly different among patient demographic groups and whether the state used billing versus abstract data.

The health information management (HIM) profession is expanding to new sites and perspectives. The implementation of Medicare managed care has brought changes not only by emphasis on management of the individual's medical care and the cost of that care, but also by creating new uses for coded data. This article examines the evolution of risk adjustment methods in Medicare Managed Care. The current choice for risk adjustment is the Principal Inpatient Diagnostic Cost Groups (PIP-DCG). This article explains the health plan's submission of encounter data and how HIM can play a valuable role in data capture and improvement in data quality and reimbursement.

This article examines how simple descriptive statistical and graphing techniques may be used in compliance efforts. Specifically, we propose the following three-step process: (1) Retrospective review of external data--Where do I stand? (2) Retrospective use of internal data--How can I improve? and (3) Prospective use of external and internal data--How can I avoid future problems? Findings suggest that when examining charges and length of stay (LOS) data, box plots are useful in retrospective analysis in identifying both over and under charges and LOS. Run charts are useful in prospective analysis of data in setting benchmark standards for evaluation.

The Episode Treatment Group (ETG) methodology is a patented case-mix adjustment and episode-building system that uses routinely collected inpatient and ambulatory claims data. The resulting clinically homogenous groups, of which there are approximately 600, adjust for severity by the presence of complicating conditions, comorbidities, and other characteristics of a patient's condition that affect resource utilization.

Developing a comprehensive inpatient clinical documentation and coding improvement program that demonstrates successful outcomes and proves to be sustainable by the health care organization is a difficult process but significant in maintaining accurate coding and reimbursement under the Medicare system. This case study of one health care organization that undertook just such a comprehensive program, chronicles the steps involved, the categories of health care professionals necessary to support ongoing communication and education, and the need for physician partnerships to sustain the program and achieve results. The program had a positive impact with a net increase in reimbursement attributed directly to the case reviews and point of service clinical education. Creating a new position of Coding/Documentation Specialist, working at the point of care as a regulatory interpreter and coding expert, was found to be key to cementing the successful team approach to documentation quality.

Emergency medical transportation services have some different characteristics than other patient services that make billing for the services more difficult than for other providers. Payers have been less than systematic in their definition of medical necessity, a criterion that is required in order to justify reimbursement. As a result, documentation of an ambulance trip and appropriate coding of the activities carried out during the course of the trip are key elements in determining whether or not the service will be reimbursed. This article examines the many dilemmas associated with this issue.

Automated coding is a rapidly growing technology. The implications of this technology for the clinical, business, and research areas of health care today are dramatic. Before a health care organization chooses an automated coding system it is important that the implications of each of the various types as well as the vocabulary to be chosen are understood. This article will discuss three types of automated coding systems that are currently available, but it will not discuss the merits of the various vocabularies available for use in an automated coding system.

Readmissions are a key measurement tool in today's outcomes-focused health care environment. Monitoring the volume of readmissions is a straightforward process in light of the database resources available to care providers. Examining and reporting on the actual reasons for readmissions provides opportunities for improvement specific to the needs of a patient population. The readmission coding tool used at the Medical University of South Carolina demonstrates both the ability to assess the causes for patients returning to our institution within thirty days of discharge and the opportunity to correct problems in specific service areas with regard to discharge planning.

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.

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.

Computerized encoders that assist medical record department coders in making ICD-9-CM disease and operative code selections have been available for approximately 10 years but there have been no studies to evaluate job satisfaction among coders using this technology. The purpose of this study was to determine whether there is a difference in job satisfaction between coders who use computerized encoders and those who do not. The Job Descriptive Index was mailed to hospital medical record departments in Cleveland, Columbus, and Cincinnati, Ohio; the return rate was 93.5 percent. Results indicated that individuals in these three cities coding by the traditional manual method were more satisfied with their jobs than those who used computer technology. The coders in the traditional group were more challenged by their jobs and had more positive interactions with their peers and supervisors. Also traditional coders were satisfied with the pay they received; coders using computerized encoders believed that their pay was inadequate.

A historical-prospective study is being conducted to determine whether there is a relationship between obesity and breast cancer recurrence and survival in African-American women. The primary data sources for the study are the medical record and cancer registry abstract. It has been found that data items such as occupation, menopausal status, height, weight, estrogen receptor and progesterone receptor values, stage, tumor size, number of positive nodes, family history of cancer, and tumor status are not always documented. Suggestions for improving documentation of the primary data sources are provided.

Health care providers are being asked to collect, analyze, and evaluate the results of medical processes or procedures to improve the outcome of health care services. The linkage of process to outcome is not a new science, but it has assumed greater importance in today's health care economic climate. Medical effectiveness and outcomes management studies, once within the purview of health services investigators, are moving to the individual provider setting. This evolution has tremendous impact on health information management professionals. As the guardians of the data that are indispensable for medical effectiveness and outcomes management investigations, health information management professionals play a key role in caregivers' attempts to correlate process and outcome performance measures. The article discusses the historical origins of outcomes management, the prominence of outcomes management in health care reform activities, and the responsibilities of health information management professionals in these strategic initiatives.

The characteristics of health data are diverse and vary by discipline. Health data can be viewed from three perspectives. They can be examined at a basic level of different variable types and database constructions. At an intermediate level, the way data are structured in a facility is a model of how an organization works. A computerized information system is a model of how work is performed. An understanding of facility data architecture and data structure is essential for adapting both manual and computerized systems to the rapid changes occurring in health care today. Lastly from the highest-level perspective, for communication and exchange of health data to be possible across all components of the health care delivery system, standards for data must be adopted by all institutions and individuals involved in the development of health data information systems. To expedite such exchange, the American Medical Informatics Association (AMIA) has recommended standards for patient, provider, and site-of-care identifiers; computerized message exchanges; and medical record content and structure. AMIA has also recommended the use of the universal medical language system as the basis for future developments in a universal medical language.

This article describes how a medical records department responded to relocating, upgrading a departmental computer system, incorporating severity of illness abstracting, and implementing continuous quality improvement techniques by reengineering along department flowlines over a five-year period. Areas of the department that were restructured were storage and retrieval, record completion, and data collection and reporting functions.