Ball, J.K., A. Elixhauser, and M. Johantgen. HCUP-3 Quality Indicators: Methods, Version 1.1: Outcome, Utilization, and Access Measures for Quality Improvement. Healthcare Cost and Utilization Project (HCUP-3) Research Note. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 98-0035, 1998).
The value of information on health care quality has never been so widely recognized, yet many organizations lack the resources and/or expertise to build a quality information program from the ground up. Recognizing this, the Healthcare Cost and Utilization Project Quality Indicators (HCUP QIs) were initiated specifically to meet the short-term needs for information on health care quality using standardized, user-friendly methods and existing sources of data.
The indicators were designed to capitalize on the availability of administrative data on inpatient stays to produce information about: avoidable adverse outcomes (e.g., in-hospital pneumonia); utilization of specific inpatient procedures thought to be over-, under-, or misused (e.g., hysterectomy) and access to care in the community, as reflected in the hospitalizations for ambulatory-care-sensitive conditions (conditions amenable to management in an ambulatory setting, e.g. pediatric asthma).
This report provides an overview of the HCUP QI methodology and comprehensive specifications for each measure. It also illustrates a variety of potential uses of the HCUP QIs and a guide for interpreting results, using illustrations generated from the Colorado component of the HCUP State Inpatient Database and focusing on valuable information that can be derived without identifying "good" or "bad" hospitals.
By developing these tools, illustrating their use, and making them available and accessible, the authors hope to assist others in producing information on health care quality more cost effectively.
Ball, J.K., et al. HCUP-3 Quality Indicators: Software User's Guide, Version 1.1: Outcome, Utilization, and Access Measures for Quality Improvement. Healthcare Cost and Utilization Project (HCUP-3) Research Note. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 98-0036, 1998).
This report is the user's guide for the HCUP QI software Version 1.1 (see above), which is provided on companion diskettes. The diskettes include software developed in two languages, SAS and SPSS, for two platforms, mainframe and personal computers. By making these tools available, we hope to assist others in producing information on health care quality more cost effectively.
Brooks, J.M., A. Dor, and H.S. Wong. "Hospital-Insurer Bargaining: An empirical Investigation of Appendectomy Pricing." Journal of Health Economics 16, no. 4 (1996): 417-34.
Employers' increased sensitivity to health care costs has forced insurers to seek ways to lower costs through effective bargaining with providers. What factors determine the prices negotiated between hospitals and insurers? The hospital-insurer interaction is captured in the context of a bargaining model, in which the gains from bargaining are explicitly defined. Appendectomy was chosen because it is a well-defined procedure with little clinical variation. The results show that certain hospital institutional arrangements (e.g., hospital affiliations), health maintenance organization penetration, and greater hospital concentration improve hospitals' bargaining position. Furthermore, hospitals' bargaining effectiveness has diminished over time and varies across States.
Brooks, J.M., A. Dor, and H.S. Wong. "The Impact of Physician Payments on Hospital-Insurer Bargaining in the U.S." In Governments and Health Care Systems, edited by D. Chinitz and J. Cohen. London: John Wiley and Sons, Ltd., 1998.
In this paper, the researchers extend their earlier work on hospital pricing, in which the bargaining between the hospital and the insurer is modeled as a Nash-bargaining process. In particular, they bring to light the relationship between the hospital-insurer bargaining process and the physician payments. The previous results indicate that competition in hospital markets leads to diminished hospital bargaining power, and that the bargaining position of hospitals has been eroding over time. Although physician payments seem to influence bargaining, these results are essentially unaffected. In addition, the payment to the attending surgeon has a negative effect on hospital bargaining power whereas the portion of the payment dedicated to ancillary physicians has a positive effect on hospital bargaining power.
Coffey, R.M., et al. "The Case for National Health Data Standards." Health Affairs 16, no. 5 (1997): 58-72.
The Health Insurance Portability and Accountability Act of 1996 (HIPAA) contains groundbreaking provisions to encourage the development of a national health information system through the establishment of standards. This paper compares statewide inpatient data systems to one standard—the Uniform Bill (UB)—to understand how standards have been used and how they can be improved. The authors recommend changes to the Uniform Bill, note the need for better compliance, and suggest new standards for common, derived elements.
Daley, W.R., and R.G. Kaczmarek. "The Epidemiology of Cardiac Pacemakers in the Older U.S. Population." Journal of American Geriatric Society 46, no. 8 (1998): 1016-19.
This study estimates the age distribution of older patients (>64 years) receiving implantable cardiac pacemakers in non-Federal US hospitals and determines major characteristics of this group using a massive, nationally representative sample of inpatient discharge records. Discharge records were obtained from the 1992 Nationwide Inpatient Sample. Correlation with census data from 1992 was used to determine age and gender specific rates. The Nationwide Inpatient Sample is a 20 percent stratified probability sample of non-Federal US hospitals. Records of all recipients (26,425) of an initial or replacement pacemaker were selected
Results: Individuals 65 years of age and older received an estimated 131,361 initial and replacement pacemaker pulse generators (87 percent of the total) in non-Federal US hospitals in 1992. Pacemaker implantation was performed in urban teaching hospitals (28.9 percent), non-teaching urban hospitals (57.8 percent), and rural hospitals (13.3 percent). The age-specific implantation rates per 100,000 population were 226.5 (age, 65-74 years), 585.9 (age, 75-84 years), 874.9 (age, 85-94 years), and 540.4 (more than 94 years). The age-adjusted rate for men was 70 percent greater than the corresponding rate for women. Major diagnoses of implant recipients included atrioventricular block (37.8 percent) and atrial fibrillation (28.5 percent). Two percent of pacemaker recipients died before discharge.
The rate of pacemaker implantation increases sharply up to age 95. As the number of older people in the US population grows, particularly those in the age ranges greater than 75 and 85 years, a sharply increased number of pacemakers will be implanted unless other factors decrease the need for these devices. The data also demonstrate diffusion of this technology from academic centers.
Duffy, S.Q., A. Elixhauser, and J.P. Sommers. Diagnosis and Procedure Combinations in Hospital Inpatient Data. Healthcare Cost and Utilization Project (HCUP-3) Research Note 3. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 96-0047, 1996).
This Research Note contains information on the most frequent combinations of diagnoses and procedures for hospital inpatients. It helps to answer the questions "What is this procedure used for?" and "How is this diagnosis managed?" The analysis is based on data from the 1992 Nationwide Inpatient Sample, a component of AHCPR's Healthcare Cost and Utilization Project. For each of the 100 most frequently performed principal procedures, the study lists the 5 principal diagnoses most commonly recorded on discharge abstracts of patients who had that procedures during the hospitalization. In addition, for each of the 100 most frequent diagnoses, the 5 principal procedures most commonly performed are listed. Median charges and length of stay for each diagnosis-procedure combination are also provided, along with estimates of standard errors.
Examples of findings from this Research Note include:
This information can be used as a starting point for many purposes. Medical professionals can compare their own practices with a nationwide sample. Third-party payers and managed care organizations can use this information as a starting point for examining the impact of payment policies on practice patterns. Health services researchers can use this information to generate hypotheses for future research on the treatment of specific conditions.
Elixhauser, A., and C.A. Steiner. Clinical Classifications for Health Policy Research, Version 2: Software and User's Guide. Healthcare Cost and Utilization Project (HCUP-3) Research Note 2. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 96-0046, 1996).
Clinical Classifications for Health Policy Research (CCHPR) Version 2 provides a way to classify diagnoses and procedures into a limited number of categories. CCHPR aggregates individual hospital stays into larger diagnosis and procedure groups for statistical analysis and reporting. This product provides information required to use CCHPR:
CCHPR Version 2 is based on ICD-9-CM codes that are valid for January 1980 through September 1996. There is one classification scheme for diagnoses (260 categories) and one classification scheme for procedures (231 categories).
Elixhauser, A., S.Q. Duffy, and J.P. Sommers. Most Frequent Diagnoses and Procedures for DRGs, by Insurance Status. Healthcare Cost and Utilization Project (HCUP-3) Research Note 4. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 97-0006, 1997).
This Research Note contains information on the most frequent diagnoses and procedures for the top 50 diagnosis-related groups (DRGs) in the U.S. community hospitals. The analysis is based on data from the 1992 Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project (HCUP-3). For each of the 50 most frequent DRGs, the document lists the 5 most common principal diagnoses and the 5 most commonly performed principal procedures. Mean and median charges and length of stay for each DRG-diagnosis combination and each DRG-procedure combination are provided for all patients combined and for three patient groups defined by their insurance status: the privately insured, Medicaid, and self-pay patients.
Examples of findings from this Research Note include:
This information can be used for many purposes. Medical professionals can compare their own practices to a nationwide sample. Third-party payers and managed care organizations can use this information as a starting point for examining the impact of payment policies and insurance status on practice patterns. Health services researchers can use this information to generate hypotheses for future research on the treatment of specific conditions; the variation in resource use within DRGs; and differences in morbidity, use of services, and patterns of care by payer groups.
Elixhauser, A., M. Johantgen, and R. Andrews. Descriptive Statistics by Insurance Status for Most Frequent Hospital Diagnoses and Procedures. Healthcare Cost and Utilization Project (HCUP-3) Research Note 5. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 97-0009, 1997).
A number of studies have demonstrated differences in access to care, hospitalization rates, the process of care, and outcome of treatment among patients by insurance status. For example, patients with Medicaid as the primary payer or patients who are uninsured tend to:
Descriptive statistics are presented by insurance status for the top 50 diagnoses and top 50 procedures in U.S. hospitals, based on a nationwide administrative database from 1993. Results are presented for privately insured, Medicare, Medicaid, and self-pay patients; all other patients; and all patients combined. This information can be used as a starting point for more in-depth analyses aimed at assessing differences in the process of care and outcomes by insurance status.
This study employs data form the Nationwide Inpatient Sample Release 2, a component of the Agency for Health Care Policy and Research's Healthcare Cost and Utilization Project (HCUP-3). This study sample consists of 6,538,976 discharges from 913 hospitals in 17 States.
This Research Note examines differences by insurance status for a wide range of conditions from a nationwide sample of inpatients. Statistics are presented for the following measures of interest:
This publication describes Version 2 of the Clinical Classifications for Health Policy Research (CCHPR), a diagnosis and procedure categorization scheme, and provides descriptive statistics for 1992 hospital inpatient stays illustrating the use of the CCHPR categories. Diagnoses and procedures for hospital stays are coded using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), an uniform and standardized coding system. ICD-9-CM consists of over 12,000 diagnosis codes and 3,500 procedure codes. Although it is possible to present descriptive statistics for individual ICD-9-CM codes, it is often helpful to aggregate codes into clinically meaningful categories that comprise similar conditions or procedures.
CCHPR Version 1 was the initial endeavor to construct such clinically meaningful categories. CCHPR Version 2 is based on the Version 1 summary diagnosis and procedure categories. The original categories were modified on the basis of clinical homogeneity, the number of discharges, and ICD-9-CM coding changes.
CCHPR categories can be employed in many types of projects analyzing data on diagnoses and procedures, such as identifying populations for disease- or procedure-specific studies; providing statistical information (such as charges and length of stay) about relatively specific conditions; defining comorbidities; and cross-classifying procedures by diagnoses to provide insight into the variety of procedures performed for particular diagnoses.
Electronic versions of CCHPR classification schemes will be available in a future HCUP-3 Research Note and can be obtained now by contacting the lead author.
Elixhauser, A., and C.A. Steiner. Hospital Inpatient Statistics, 1996. Healthcare Cost and Utilization Project, HCUP Research Note. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Pub. No. 99-0034, 1999).
This publication provides descriptive statistics for U.S. hospital inpatient stays in 1996 using the Healthcare Cost and Utilization Project Nationwide Inpatient Sample. National estimates are provided for all discharges by principal diagnosis and by principal procedure. Statistics are presented on the number of discharges, mean length of stay, mean charges, charges in quartiles (25th, 50th, and 75th percentiles), percent who died in the hospital, percent male, and mean age. The statistics in this publication can be used to assess the processes and outcomes of care for diagnoses and procedures in U.S. hospitals. For example, among the most frequent conditions are coronary atherosclerosis with over 1.4 million stays and pneumonia with over 1.2 million stays. Among the longest mean lengths of stay were those for short gestational age, low birth weight, and fetal growth retardation (23 days), infant respiratory distress syndrome (22 days), late effects of cerebrovascular disease (15 days) and paralysis (16 days) while the highest mean total charges were seen for organ transplantation ($191,000) and tracheostomy ($148,000). Diagnoses and procedures are categorized using the Clinical Classifications Software (CCS), a system for collapsing diagnosis and procedure codes into clinically meaningful categories. Electronic versions and definitions of CCS can be obtained online at: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
Elixhauser, A., and C.A. Steiner. Most Common Diagnoses and Procedures in U.S. Community Hospitals, 1996. Healthcare Cost and Utilization Project, HCUP Research Note. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Pub. No. 99-0046, 1999).
This publication provides information on the most frequent diagnoses and procedures for hospital inpatients. It helps to answer questions such as "What are the most common reasons for hospitalization in the United States?" "Which procedures are most frequently performed?" "For what conditions is this procedure used?" and "How is this condition treated?" The analysis is based on data for U.S. hospital inpatient stays in 1996 using the Healthcare Cost and Utilization Project Nationwide Inpatient Sample. For each of the 100 most frequently performed principal procedures, we list the 5 principal diagnoses most commonly recorded on the discharge abstract. Similarly, for each of the 100 most frequent principal diagnoses treated in hospitals, we list the 5 principal procedures most commonly performed. For each diagnosis-procedure combination, information on in-hospital mortality and mean and median length of stay and total charges is provided.
This publication can be used to evaluate the variety of diagnoses associated with a given procedure and the variations in treatment for particular diagnoses. In addition, it provides information on variations in length of stay, total charges, and in-hospital mortality among diagnosis-procedure combinations. Examples of findings from this publication include:
There are wide variations in length of stay and total charges for some conditions depending on what specific treatments are provided. Hospital charges for coronary atherosclerosis treated without an invasive procedure are, on average, $5,000, compared with $19,000 for hospitalizations during which percutaneous transluminal coronary angioplasty is performed, and $44,000 for a hospitalization during which coronary artery bypass graft is performed.
Most procedures are performed for a wide range of conditions. One third of all hysterectomies are used to treat benign neoplasm of the uterus, while prolapse of female genital organs accounts for 15 percent, endometriosis accounts for 12 percent, and menstrual disorders account for 11 percent of all hysterectomies.
The major cause of amputation of the lower extremity is diabetes mellitus, accounting for 35 percent of the reasons for amputation. Gangrene is the next most common principal diagnoses (30 percent) followed by infective arthritis and osteomyelitis (6 percent). This information can be used as a starting point for many analyses. Medical professionals can compare their own practices with a nationwide sample. Health plans and insurers can use the information as a starting point for examining the impact of payment policies on practice patterns. Health services researchers can use the information to generate hypotheses for future research on the treatment of specific conditions.
Elixhauser, A., et al. Clinical Classifications for Health Policy Research: Hospital Inpatient Statistics, 1995. Healthcare Cost and Utilization Project (HCUP-3) Research Note. Rockville, MD: Agency for Health Care Policy and Research. (AHCPR Publication No. 98-0049, 1998).
This publication provides descriptive statistics for U.S. hospital inpatient stays in 1995 using the Healthcare Cost and Utilization Project Nationwide Inpatient Sample. National estimates are provided for all discharges by principal diagnosis and by principal procedure. Statistics are presented on the number of discharges, mean length of stay, mean charges, charges in quartiles (25th, 50th, and 75th percentiles), percent who died in the hospital, percent male, and mean age. Diagnoses and procedures are categorized using the Clinical Classifications for Health Policy Research (CCHPR), a system for collapsing diagnosis and procedure codes into clinically meaningful categories. This update of the CCHPR incorporates International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) coding changes through September 1998.
CCHPR categories can be employed in many types of projects analyzing data on diagnoses and procedures, such as identifying populations for disease- or procedure-specific studies; providing statistical information (such as charges and length of stay) about relatively specific conditions; defining comorbidities; and cross-classifying procedures by diagnoses to provide insight into the variety of procedures performed for particular diagnoses.
Elixhauser, A., et al. "Comorbidity Measures for Use with Administrative Data." Medical Care 36, no. 1 (1998): 8-27.This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets. The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other aspects of the patient's patient groups. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in California in 1992 (n = 1,779,167). Outcome measures were those commonly available in administrative data: length of stay, hospital charges, and in-hospital mortality were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Several comorbidities are described that are important predictors of outcomes, yet commonly are not measured. These include mental disorders, drug and alcohol abuse, obesity, coagulopathy, weight loss, and fluid and electrolyte disorders.
The comorbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently among different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive approach to identifying comorbidities and separates them from the primary reason for hospitalization, resulting in an expanded set of comorbidities that easily is applied without further refinement to administrative data for a wide range of diseases.