WHERE DO WE GO FROM HERE?

Dr. Simone concluded the workshop by asking each participant to consider the day's proceedings and to assess what policy and research actions were warranted.

Many workshop participants noted that volume may be the best available proxy indicator of quality for certain conditions, but efforts should be made to accompany volume information with other quality indicators and with explanatory information. Furthermore, several participants suggested that when research confirms a volume–outcome link, this information should be disclosed to the public to support health care decision-making. In making such disclosures, however, the limitations of the data and how the information should be interpreted must be clear for its intended audience. Public release of data on volume may motivate providers to report process and outcome data, thereby laying the ground for the next generation of health care quality measures. When better measures of quality of care than volume are developed, they should replace the volume measures

Many people could eventually be affected by policies that concentrate care in higher-volume settings (or that avoid low-volume settings) because many procedures for which a volume–outcome relationship has been established are conducted by low-volume providers. Many barriers to implementing volume-based policies were recognized, and implementation was viewed as especially challenging in rural areas. Residents of rural areas, for example, may not want to travel great distances for care and may not be able to afford to do so. Consequently, some workshop participants suggested that initial implementation efforts be focused in urban areas with dense concentrations of hospitals, where success is more likely.

Purchasers were recognized as having taken the lead in applying the evidence regarding volume. The Leapfrog Group, for example, is exploring an evidence-based referral program within the health plans with which it contracts. For conditions or procedures for which the research evidence strongly points to a volume–outcome relationship, a next step for action might be achieving consensus, perhaps with the help of representatives of specialty providers, on acceptable volume thresholds for selected procedures. To apply the volume–outcome findings more broadly, further research is needed on many conditions and on many health care outcomes for which data are now insufficient.

Workshop participants suggested a wide-ranging set of research topics —from policy research and demonstration programs to basic methodological research—to better understand why the relationship between volume and outcome exists and how best to implement policies to improve care.

Policy Research and Demonstration Programs
  • Make the “business case” for implementing a volume standard when assessing quality of care, and examine the implications of policies that would effectively stop certain procedures from being performed in low-volume hospitals.

  • Evaluate current efforts to implement the volume–outcome finding (e.g., the Leapfrog Group's evidence-based referral program).

  • Plan demonstrations with quasi-experimental designs to evaluate the impact of applying different quality-of-care measures to quality improvement programs (e.g., volume versus riskadjusted administrative data plus mortality data).



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OCR for page 17
Interpreting the Volume–Outcome Relationship in the Context of Health Care Quality: Workshop Summary WHERE DO WE GO FROM HERE? Dr. Simone concluded the workshop by asking each participant to consider the day's proceedings and to assess what policy and research actions were warranted. Many workshop participants noted that volume may be the best available proxy indicator of quality for certain conditions, but efforts should be made to accompany volume information with other quality indicators and with explanatory information. Furthermore, several participants suggested that when research confirms a volume–outcome link, this information should be disclosed to the public to support health care decision-making. In making such disclosures, however, the limitations of the data and how the information should be interpreted must be clear for its intended audience. Public release of data on volume may motivate providers to report process and outcome data, thereby laying the ground for the next generation of health care quality measures. When better measures of quality of care than volume are developed, they should replace the volume measures Many people could eventually be affected by policies that concentrate care in higher-volume settings (or that avoid low-volume settings) because many procedures for which a volume–outcome relationship has been established are conducted by low-volume providers. Many barriers to implementing volume-based policies were recognized, and implementation was viewed as especially challenging in rural areas. Residents of rural areas, for example, may not want to travel great distances for care and may not be able to afford to do so. Consequently, some workshop participants suggested that initial implementation efforts be focused in urban areas with dense concentrations of hospitals, where success is more likely. Purchasers were recognized as having taken the lead in applying the evidence regarding volume. The Leapfrog Group, for example, is exploring an evidence-based referral program within the health plans with which it contracts. For conditions or procedures for which the research evidence strongly points to a volume–outcome relationship, a next step for action might be achieving consensus, perhaps with the help of representatives of specialty providers, on acceptable volume thresholds for selected procedures. To apply the volume–outcome findings more broadly, further research is needed on many conditions and on many health care outcomes for which data are now insufficient. Workshop participants suggested a wide-ranging set of research topics —from policy research and demonstration programs to basic methodological research—to better understand why the relationship between volume and outcome exists and how best to implement policies to improve care. Policy Research and Demonstration Programs Make the “business case” for implementing a volume standard when assessing quality of care, and examine the implications of policies that would effectively stop certain procedures from being performed in low-volume hospitals. Evaluate current efforts to implement the volume–outcome finding (e.g., the Leapfrog Group's evidence-based referral program). Plan demonstrations with quasi-experimental designs to evaluate the impact of applying different quality-of-care measures to quality improvement programs (e.g., volume versus riskadjusted administrative data plus mortality data).

OCR for page 17
Interpreting the Volume–Outcome Relationship in the Context of Health Care Quality: Workshop Summary Consumer-Focused Research Examine consumer interest in, and interpretation of, volume as an indicator of health care quality relative to other measures. Evaluate the relationship between exposure to volume quality indicators and consumer health care decision-making. Examine dissemination strategies to maximize consumer access to and use of quality information (e.g., determine which sources of information are trusted). Implementation Related Research Determine thresholds with which to define high volume for each condition or procedure (e.g., using focus groups of members from specialty societies, syntheses of extant literature). New Areas of Research Examine the volume–outcome relationship for chronic conditions and nonsurgical procedures. Examine factors that mediate volume–outcome relationships when found. Methodological Development Examine outcomes other than mortality (e.g., functional status, quality of life), including longer-term outcomes. Include potential intervening variables (e.g., processes and systems of care) in volume– outcome studies. Integrate social science methods (e.g., sociology, medical anthropology, systems analysis) into volume–outcome research. In studies with mortality as an end point, examine the time of death to help explain the cause of death. Develop procedure-condition-specific risk-adjustment tools. Health Services Research Data Infrastructure Develop condition-procedure-specific, prospective, population-based clinical databases and registries (e.g., New York's cardiovascular surgery database). Develop chronic disease databases that cover both hospital and outpatient care. When clinical databases are available to serve as a “gold standard,” evaluate the sensitivity and specificity of volume as a quality indicator. Selectively add key clinical risk factors and process data into administrative databases. Include more reliable identifiers of physicians in federal and state administrative databases. Workshop participants cited several potential sources of research support including AHRQ, health care purchasers, health plans, and provider groups, and suggested that public–private research partnerships might greatly facilitate meaningful research efforts.