Database software claims

Our platform enables businesses to redu HawkSoft CMS. HawkSoft is an insurance management solution designed for independent agencies. HawkSoft offers workflows for commercial and personal lines and an auto-documentation process that builds a trail of every client interaction. EZLynx is an insurance agency management software that streamlines all agency workflows.

It provides back-office management features, CRM, and marketing automation tools that help agents strengthen relationships with customers and A1 Tracker. A1 Tracker's features include contract approval workflow, documents, vendors, audits, reminder notifications, templates, certi With more than 25 years in the industry, Commence CRM is a customizable and modular system to help small and midsized organizations convert leads into sales, with functions to nurture prospects throughout the sales cycle Applied Rater.

Applied Rater is a cloud-based insurance rating and quoting solution that helps businesses to present insurance rates to their clients. It integrates into agency websites and management systems, providing users with a single point Eclipse is an insurance agency management system for independent insurance agents with both on-premise or cloud-based deployment.

It provides features for single agencies as well as multi-agency locations of all sizes. The sy Commission Tracker. Commission Tracker is an on-premise and cloud-based solution that enables insurance agencies to manage policies and calculate agents' commissions. Administrators can sort existing policies based on agents, carriers or clients and Virtual Claims Adjuster.

Virtual Claims Adjuster is a web-based claims management solution designed to help small to large businesses in the insurance industry create automated workflows to manage claims and identify different development trends. FileTrac is a web-based claims management solution for independent adjusters and insurance businesses of all sizes.

Commissionly is an intelligent, fully automated compensation management platform that streamlines sales commission processes for medical sales, insurance sales, IT sales, recruitment, and more. Users can manage sales territory, sa Bitrix24 vs Indio. Jenesis Software vs PhoneBurner. NowCerts vs Applied Epic. EZLynx vs A1 Tracker. Despite a slew of challenges in recent years—government regulations being constantly in flux , homeownership rates declining —insurance companies continue to survive in an increasingly competitive and complex industry.

In some cases, they're even thriving: The global insurance industry is expected to grow 4. Does that mean it's time to be complacent if you're an insurance carrier, agency or brokerage? No way. Your business won't last long in this day and age without being able to manage a growing policy volume, while still meeting the increasing demands of digital-savvy customers.

Building new distribution channels and working closely with existing distribution partners to enhance the customer experience is a strategic imperative. This is why you should consider investing in insurance software—systems designed with the specific needs of insurance carriers, agencies and brokerages in mind. In this Buyer's Guide, we'll explain what insurance software is, what common functionality to look out for, how much it costs and everything else your insurance business needs to know before making a purchase decision.

It develops full-st Recent recommendations: 2 recommendations. Jenesis Software. Jenesis is a cloud-based solution that helps insurance agents manage personal and commercial lines and obtain new potential customers.

Key features include claims management, rating engine, policy processing and reinstatement trac NowCerts is a cloud-based insurance solution designed for insurance agencies of all sizes. Key functionalities include commission tracking, task management, claims management, reporting, self-service certificates, reminders, calen It is built for businesses of all sizes.

Our platform enables businesses to redu HawkSoft CMS. HawkSoft is an insurance management solution designed for independent agencies. HawkSoft offers workflows for commercial and personal lines and an auto-documentation process that builds a trail of every client interaction. Eclipse is an insurance agency management system for independent insurance agents with both on-premise or cloud-based deployment.

It provides features for single agencies as well as multi-agency locations of all sizes. The sy Virtual Claims Adjuster. Virtual Claims Adjuster is a web-based claims management solution designed to help small to large businesses in the insurance industry create automated workflows to manage claims and identify different development trends. The software is designed for life and health agencies, but is easy to customize for your agency.

Anagram, formerly Patch, is a cloud-based insurance management solution, which assists health centers and medical practitioners with claim submission and out-of-network benefits management. Key features include ROI tracking, treat Insly is a cloud-based accounting solution that is designed for brokers, agents and accounting professionals. Key features include accounting and billing management, debt management and reporting.

Insly helps in managing sale Velocity is a cloud-based agency management system for property and casualty insurance carriers. It helps users handle the needs of general agents, program administrators, wholesalers, carriers, reinsurers and retailers.

The core Xanatek Connect. IMS 4 is an on-premise and cloud-based solution that helps insurance agencies manage various administrative operations such as document storage, drip marketing, receipt generation and more. FileHandler Enterprise.

FileHandler Enterprise is a claims administration software designed to help public entities, third-party administrators and self-insured organizations streamline workflow automation and risk management.

Key features include case m ISI Enterprise. ISI Enterprise is a cloud-based insurance solution that assists businesses in policy administration, billing, claims and other related services. Key features include reinsurance management, a policy rating engine, document managem Vertafore Agency Platform. Vertafore Agency Platform is a cloud-based insurance management solution designed for insurance companies of all sizes.

It offers accounting, customer management, document management, policy management and reporting within a suite Partner XE. Built for the agency that cares about community values and is tired of the s The software automates the whole insurance policy lifecycle, from policy issuance to ca Thus, HDO information might be applied in retrospective profiling of provider-related information as a means of identifying providers that might be brought into or kept out of selective contracting arrangements; it can also be employed to monitor performance over time.

One of the chief aims of HDOs emerging today is, in fact, to aid payer or other groups in this process by enabling them to develop or acquire analyses of practice patterns, outcomes, costs, and similar variables that will permit them to make decisions about the providers their systems will include or exclude. Nearly three-quarters of employers with 1, or more employees manage self-insured health plans Foster Higgins, , in IOM, e.

These firms can, for all practical purposes, be regarded as conducting or being responsible for the same tasks as insurers, as discussed above. For example, employers may want to create case-management plans that are increasingly directive and oriented toward exclusive provider organization EPO arrangements, like those that are common today for high-technology therapies such as transplantation and cardiac surgery.

Employers might also wish to use the information in some databases for personnel actions—promotions, relocations, dismissals, and the like. Nevertheless, the connections between workplace wellness and personnel actions are clear. Those studying and having responsibility for public health efforts can be expected to use HDO databases for a broad set of applications. These include analyses of the incidence of injury and disease and studies of the prevalence of trauma-related health problems and chronic illness.

Today, disease and injury registries provide information on traumatic events, episodes of illness, and the processes and outcomes of care that exemplify what might be done with HDO data in the future. For instance, cancer registry data from two states, Illinois and Washington, have been used to address a range of questions Hand et al.

One study focused analyses on the percentage of early-stage breast cancer patients who do not receive indicated auxillary lymph node dissection or assays for hormone receptors; in another, the study question was the percentage of women receiving breast-conserving surgery who did not receive indicated radiation therapy. In commenting on these studies, Chassin notes that they suggest problems "in the extent to which physicians fail to communicate options and outcomes data objectively" p.

With respect to injury, the American College of Surgeons National Trauma Registry is another example of a database that provides information on patterns of injury and their outcomes see Table ; for those concerned with emergency medical services, such sources of epidemiologic and clinical information are critical IOM, d. Other public health applications of HDO databases relate to preventive care and health behaviors.

For some industries, for instance, epidemiologic information from large databases may enable analysts to identify potential safety or health-related problems in workplace environments and to suggest corrective steps. Immunization tracking systems, currently under development regionally and nationally, might be incorporated into HDO databases to simplify monitoring and recording of children's immunization status both in aggregate and individually.

HDOs might also maintain information about blood type, organ donors, and tissue matching in their databases, as a means of fostering improved blood banking and organ procurement and transplant services. When HDO databases are statewide, or sponsored by state health departments, the potential uses by states and all subordinate levels of government for health planning, health care delivery, public health, and administrative responsibilities become quite extensive; they can involve the health departments and social services agencies of states, counties, and municipalities in many overlapping efforts.

Planning and educational activities that could employ HDO data might be focused on improving access to, reducing costs of, and enhancing quality of care; on organizing provider systems of care; or on investigating epidemiologic patterns of injury or illness.

For example, community-specific studies conducted using HDO data might examine the kinds of cases treated by local hospital emergency departments, whether use differs by hospital or patient characteristics, and whether patient outcomes differ accordingly.

Such information might enable public agencies to target public funds or other resources in new ways to meet previously undetected problems or needs. Integrating data on vital statistics, epidemiologic surveillance, and local and regional public health programs with those in the personal-health-care files of HDOs raises the possibility of more effective public health activities for monitoring health, attaining public health objectives at a population level, and targeting efforts for hard-to-reach individuals.

For example, researchers in Boston have developed and operationalized a distributed health record system for a homeless population seen at many sites by many different providers Chueh and Barnett, In addition to whatever public-sector agencies might do to monitor the public health of communities, community and consumer organizations may wish also to carry out population-based studies as a means of learning where significant health problems exist and of making elected officials and others more accountable for solving those problems.

Another significant way that information held by HDOs may contribute to the work of community, voluntary, and consumer groups is in their public education and outreach programs. Here the data may suggest emerging problems that warrant increased attention or waning problems that need reduced effort ; data may also indicate where in geographic areas or population subgroups education initiatives might best be targeted.

For example, recognition that bicycle accidents are a major source of children's head injuries could lead to community education programs in schools and neighborhood associations.

Public-sector agencies, academic centers, or consumer groups might pursue such public health efforts by analyzing HDO data and developing community-specific informational materials e. Charitable groups and voluntary organizations concerned with particular diseases and conditions have many roles: providing information to and support for patients with particular illnesses and for their families; sponsoring research; and lobbying for more policy attention, social acceptance, and research support for the problem.

Because they are likely to be private organizations that secure their funds through donations from individuals and corporations, most must engage in aggressive fund-raising campaigns. Information from health data banks might enable them to increase their efficiency in amassing epidemiologic information and perhaps in targeting fund-raising efforts. The IOM committee identified a great many other potential users and uses of HDO databases, including agencies engaged in law enforcement at the federal, state, and local levels; law firms and attorneys; and various commercial entities.

The more plausible are briefly described here. Law enforcement officials can be expected to find many uses for the information held in HDO files. They may wish to trace individuals for instance, to locate parents not paying child support. They may also need to investigate alleged illegal acts; in the health context, this might extend to abuse of illegal substances or cases of possible child abuse.

Conceivably, law enforcement agencies might want genetic information to assist them in identification of a suspect. Finally, such agencies may be expected to monitor providers and patients for possible fraud. Arguably attorneys and law firms might identify many uses for HDO data, including malpractice litigation. Plaintiffs' lawyers, for instance, might try to access information from HDOs concerning previous quality-of-care deficiencies of a physician or hospital; defendants' counsel might seek to demonstrate, through analysis of HDO data, that the provider acted well within community standards.

One important application occurs in cases where the past or current health condition of the patient is relevant to the case or is at issue in the case. Product safety litigation may also call forth requests for data from the network, especially when a medical device is in question.

Finally, attorneys representing health plans, insurers, medical groups, hospitals, and other providers in their business e. A wide array of other kinds of companies, organizations, and services might well have an interest in the information available through HDOs. Among them are direct marketing firms, financial and credit institutions, and bill collection agencies. Such entities especially the last named might wish to have person-identified information, but in general many applications of the information might not be directed at patients but rather at providers or at groupings such as zip codes.

Financial and credit institutions might be interested in health plan and hospital data to determine market share or estimate solvency for a given group practice or facility. In general, this committee takes an extremely negative view toward giving these groups access to HDO files, particularly any data that might conceivably identify individual persons, and thus these uses are not explored further here.

The committee emphasizes that its roster of users includes examples of current as well as potential HDO database users; 16 it does not believe that HDOs necessarily ought to satisfy all such claimants.

It does acknowledge, however, that the mere existence of a database creates new demands for access and new users and uses. Consequently, those who establish health databases and HDOs may be creating something for which the end uses cannot always be anticipated. Because this study took place at a time of change in both health care infrastructure and information systems, the committee tried to anticipate the probable sources of the tension that will exist between those who create databases and wish to protect the information and those who might argue for access to those databases on grounds of anticipated benefits.

Historically, the creation of large databases, such as those to administer the Social Security program and the National Crime Information Network, has been followed by modifications in the databases themselves and in the policies and legislation that regulate access to them—which results more often than not in relaxing prohibitions or barriers to access. Realism dictates that large databases such as those maintained by HDOs will be dynamic.

In the committee's view, policies regarding access to these databases should, therefore, be based on firm principles but flexible enough to accommodate unavoidable changes and unanticipated uses. The benefits of electronic patient records should not be overlooked, however. These benefits include the availability of much more powerful databases, elimination of the need for repeated requests to record subjects for the same information, and assurance that information is available when needed.

Despite the privacy concerns described, it should be possible to improve privacy protection and safeguard the confidentiality of health information in HDOs through a variety of methods described in later chapters. Moreover, information must be acted on by individuals in a position to change their own, and others', behaviors and performance. Most experts agree that getting information to people and organizations is just the first, and perhaps not the most important, step in the change process.

Although this committee in Chapter 3 places great store on information dissemination efforts by HDOs, HDOs will not be well placed to follow up the actions taken or not taken by recipients of that information. Many of the challenges faced by the health care sector are essentially exogenous—for instance, the changing demographics of the U. No amount of radical change in health care, let alone tinkering, will demonstrably affect those problems, and HDOs similarly cannot influence them.

Further, despite the promise that HDOs hold for addressing certain health policy issues, this committee emphasizes that information derived from the files of HDOs and similar entities will not be the solution to all the ills of the health care system. Information may be incomplete or untimely, lack critical variables such as health status, or otherwise be imperfect. In addition, such data may be observational, meaning that they lend themselves more to description than to causal or inferential analysis, and more to retrospective commentary than to prediction.

In the terminology used earlier, HDOs and their constituent databases may be neither acceptably comprehensive nor inclusive. Commentary on a related information activity is instructive. The survey is described as having the following objective: "to produce annual data on the use of health care and the outcomes of care for the major sectors of the health care delivery system.

Often they do not cover the universe of providers and sites of health care [or] patients or potential users of health care. They lack sufficient information on exactly what services are provided and what the outcomes of those services are.

These faults may well affect the data repositories and networks considered by this IOM committee; they are discussed in greater detail below. The above discussion has outlined the many potential users, uses, and benefits of HDOs. Ultimately, however, the real rewards of developing and operating HDOs will depend heavily on the quality of the data that they acquire and maintain.

The committee considers this subject of sufficient importance that it elected to comment on it directly. The absolute prerequisites to successful implementation of any type of database or HDO with the expansive goals implied by the foregoing discussion are reliable and valid data.

Developers must ensure that the data in their systems are of high enough quality that the descriptive compilations, the effectiveness research, and the comparative analyses envisioned can be done in a credible, defensible manner.

McNeil et al. Mistakes, qualifications and caveats, retractions, and similar problems must be minimized, and precision about what data are actually being sought must be maximized.

All this must be done from the outset so that the long-term integrity and believability of the database and work based on its information will not be undermined irretrievably. The committee did not wish to prescribe methods that HDOs might employ for ensuring data quality, judging that approaches might differ by type of database and HDO.

It did, however, consider that success in meeting this responsibility will call for attention on several fronts. First, the committee held the view that information becomes more useful when it is used. Although the characteristic of comprehensiveness is clearly of primary importance in considering the value of a database, HDOs need to avoid the trap of collecting everything that it is possible to collect, regardless of its reliability and completeness, and thereby end up with data elements that will be used only rarely and, worse, be of questionable value when they are used.

Part of the problem is that analysts will have little experience with such data elements and may make incorrect assumptions about their reliability or about how to interpret values correctly.

Another part of the problem is that some data, although currently collected routinely because an entry must be made in a box on a form, are not used for anything by anyone.

Such data will likely have a very low level of accuracy. A commonly cited example relates to information on hospital diagnoses in the Medicare program; diagnoses were often doubtful before the advent of the DRG-based PPS see Gardner, When diagnostic data began to figure in decisions about reimbursement, studies of quality of care, choices in clinical care, or analyses about productivity, the situation changed.

After hospitals came to be paid on the basis of DRGs which obviously are diagnosis based , and diagnostic information improved markedly, although some problems persist. Similar problems of suspicious missing, wrong, or even fraudulent information on insurance claims forms for outpatient care exist to this day; the underlying problem is that payment mechanisms do not depend so heavily on outpatient diagnostic data—that is, the information is not used in the same way as inpatient data—so little incentive exists to record diagnoses accurately.

Second, data must be accurate and analyzable. Sometimes these points are couched in terms of reliability and validity of data. Among the problems one must guard against are the following: missing data; out-of-range values for quantitative data e. Analysts must also be cautious about their interpretation of patient care events—for example, not misconstruing the reasons for or timing of a particular diagnostic procedure when interpreting events in the course of treatment of a life-threatening emergency.

Third, the committee also believes that structural aspects of health databases should be emphasized as conducive to high-quality data and information.

Databases should be built around a core of uniformly reported or translatable data that is relevant and can be shown to be accurate and valid for the HDO's intended analyses in keeping with the comments just above. In addition, HDO should have an easily implemented capacity to supplement core data elements.

The committee and other experts agree on the significant tension that exists between the desire for comprehensive databases and the consequently broad uses to which HDO data might be put and the wisdom of a certain parsimony in the actual gathering of person-identifiable information.

Although the committee realizes that the federal government may have to take the lead in standards development and improved coding systems, the committee urges HDOs to foster, encourage, and work toward national standards for coding and definitions for at least core data elements. The reason is that the costs of momentous or frequent changes in terms of money, loss of comparability of data, potential incompatibility of clinical and payment coding, and incentives for fragmentation and upcoding of services can be significant; consultation between the public and private sectors can help avert excessive or unnecessary costs of these types.

Fourth, the committee takes the position that the basic structure and content of these databases ought to be carefully designed from the beginning, but they must have sufficient capacity for expansion and change as health care reform, effectiveness and outcomes research, and other dynamic aspects of the health care sector evolve in coming years.

This requirement implies that due attention will be paid to the quality of new categories of data that may become available for HDOs in the future.

To address these issues, the committee recommends that health database organizations take responsibility for assuring data quality on an ongoing basis and, in particular, take affirmative steps to ensure: 1 the completeness and accuracy of the data in the databases for which they are responsible and 2 the validity of data for analytic purposes for which they are used.

Part 2 of this recommendation applies to analyses that HDOs con duct. They cannot, of course, police the validity of data when used by others for purposes over which the HDOs have no a priori control. Until HDOs can demonstrate the quality of their data, the committee cautions that their proponents must guard against promising too much in the early years, particularly in the area of improving quality of care and conducting research on the appropriateness and effectiveness of health services.

The committee returns to this point in Chapter 4 in a discussion of data protection and data integrity. As many investigators have pointed out, the absence of sufficient clinical information in most databases today and likely for tomorrow is a critical limitation Roos et al. Efforts to acquire such information through manual abstraction of relevant information in hospital records, which is the basis of various patient classification programs e.

Some means of obtaining such information more directly from patient records will be needed. Clinical data should be obtained, whenever practical, to validate analyses. The committee does not regard the clinical data found in medical records, whether computerized or not, as always sufficiently comprehensive, accurate, or legible to characterize them as a "gold standard," but they are a valuable, and sometimes indispensable, touchstone against which to judge the less rich administrative data on which many types of health policy and health services research are and must be based.

The validity of elements in a database must be matched with the kinds of inferences that can be drawn. The committee believes that the best method of enhancing the comprehensiveness of HDO databases and the accuracy and completeness of data elements is to move toward CPRs in which the desired variables themselves, rather than high-level abstraction and proxy coding systems, could be accessed.

This committee does not wish to convey the impression that the transition to CPR systems is anything but an extraordinarily difficult task. In addition, planning efforts by the Computer Science and Telecommunications Board a unit of the Commission on Physical Sciences, Mathematics, and Applications of the National Research Council on the national information infrastructure and its role in health care and health care reform make clear that both the health care and the computer and information sciences communities have a considerable way to go even in agreeing on details about the directions that policies and technical advances should take in addressing major issues in this critical area.

It also called on the American National Standards Institute Healthcare Information Standards Planning Panel to coordinate the development, adoption, and use of national information standards for patient data definitions, codes and terminology, intersystem communication, and uniform patient, provider, and payer identifiers. Accordingly, the committee recommends that health database organizations support and contribute to regional and national efforts to create computer-based patient records.

The committee acknowledges the importance of computer-based patient records with uniform standards for connectivity, terminology, and data sharing if the creation and maintenance of pooled health databases is to be efficient and their information accurate and complete. The committee urges HDOs to anticipate the development of CPRs and to contribute to the development and adoption of these standards.

HDOs should take a proactive stance, by joining efforts by the CPR Institute and other organizations working to facilitate implementation of CPRs, helping in standards-setting efforts, and otherwise becoming full participants in the multidisciplinary effort that is now under way. Much of the thrust of this report concerns how to maximize the benefits that this committee believes can be realized from the construction and operation of inclusive and comprehensive health databases.

In examining these questions, the committee has focused on what it calls health database organizations. HDOs are emerging entities of many different characteristics in states and other geographic regions of the country; the committee made two key assumptions about them: 1 HDOs have access to and possibly control considerable amounts of person-identifiable health data outside the care settings in which those data were originally generated and 2 the chief mission of HDOs is public release of data and results of studies about health care providers or other health-related topics.

The broad-based value of HDOs and their databases might be said to be the provision of reliable and valid information in a reasonably timely manner to address all the major questions in health care delivery—access, costs, quality, financing and organization, health resources and personnel, and research—facing the nation today and in the coming years.

The chapter also details the narrower benefits that might accrue to a variety of potential users, including patients and their families, health care providers, purchasers and payers, employers, and many other possible clients in the public and private sectors. In assembling the data that will go into products for all such users and uses, the committee had sobering concerns about the quality of those data.

Thus, it recommends that HDOs take responsibility for assuring data quality on an ongoing basis, and in particular take affirmative steps to ensure: 1 the completeness and accuracy of the data in the databases for which they are responsible and 2 the validity of data for analytic purposes for which they are used [by HOOs] Recommendation 2. Initially, HDOs will attempt to provide data for particular users and uses to answer particular kinds of questions. Nevertheless, advances in the creation and operation of computer-based databases, whether centralized or far-flung, can be expected in the coming years.

The committee believes that thoughtful appreciation of their potential and anticipation of their potential limitations will hasten that progress. The development of HDOs—their structure, governance, and policies on disclosure as well as on protection of data—must be designed for the achievement of these long-term goals. The next chapter takes up the major responsibilities of HDOs in carrying out a critical mission: furnishing information to the public on costs, quality, and other features of health care providers in a given region or community.

The committee adopted two strong assumptions as it began to consider this topic. The first is that considerable benefits will accrue to interested consumers and to the public at large from having access to accurate and timely information on these aspects of the health care delivery system with which they deal; this has been the thrust of the present chapter. The other assumption is that HDOs supported by public funds ought to have a stated mission of making such information available, and this will be a core element of several committee recommendations.

The committee also assumes, however, that harms can arise from some uses of the information in such databases. For this reason, in the next chapter the committee considers administrative and other protections that it believes HDOs should put in place.

The Clinton administration's proposed Health Security Act HSA, gives appreciable attention to information systems and related matters. It calls for the establishment of a National Health Board to oversee the creation of an electronic data network consisting of regional centers that collect, compile, and transmit information Sec.

The board will, among other duties, provide technical assistance on 1 the promotion of community-based health information systems and 2 the promotion of patient care information systems that collect data at the point of care or as a by-product of the delivery of care Sec. The types of information collected would include: enrollment and disenrollment in health plans; clinical encounters and other items and services provided by health care providers; administrative and financial transactions and activities of participating states, regional alliances, corporate alliances, health plans, health care providers, employers, and individuals; number and demographic characteristics of eligible individuals residing in each alliance area; payment of benefits; utilization management; quality management; grievances, and fraud or misrepresentation in claims or benefits Sec.

The HSA further specifies the use of 1 uniform paper forms containing standard data elements, definitions, and instructions for completion; 2 requirements for use of uniform health data sets with common definitions to standardize the collection and transmission of data in electronic form; 3 uniform presentation requirements for data in electronic form; and 4 electronic data interchange requirements for the exchange of data among automated health information systems Sec.

It also calls for a national health security card that will permit access to information about health coverage although it will contain only a minimum amount of information Sec. Title V. Quality and Consumer Protection. Part 1. Health Information Systems. According to the IOM a, p. A secondary patient record is derived from the primary record and contains selected data elements to aid nonclinical users i. General Accounting Office provides the following startling figures on the equivalent volume of paper: "We estimate that the 34 million annual U.

One major hurdle to the development of CPRs involves standards for vocabulary, structure and content, messaging, and security, according to GAO reports , a ; without standards for uniform electronic recording and transmission of medical data, effective automated medical record systems will be delayed.

This committee did not examine these technical issues, although they pertain as well to large-scale regional HDOs; arguably, the government and the private sector will need to move more forcefully on development of such standards—perhaps moving beyond near-total reliance on voluntary efforts—if CPRs, CPR systems, and regional health databases and networks are to succeed.

The discussion of comprehensiveness and inclusiveness of databases is couched in terms of what might be regarded as the traditional domain of medical care, including mental health care.

Clearly, more advanced databases could include information on dental care and care provided by health professionals that practice independently, such as nurse-practitioners and nurse-midwives, acupuncturists, or alternative healers of various sorts. Even more far-reaching databases might contain information on sociomedical services provided through, for instance, day care and home care for adults or children. This is illustrative only because Medicare files also include younger but disabled beneficiaries and persons with end-stage renal disease.

In its annual report, PPRC described an "all-patient database" [emphasis in the original], conceptualized as a "network of local or regional data processing centers The report goes on to posit "parallel organizing entities The commissioners also envisioned the network evolving into a "means to link and assimilate more detailed clinical information. In defining an all-patient database, the commissioners appear to have in mind what this committee terms inclusiveness; what the PPRC report lays out as "core data elements'' in that database approaches what the IOM report calls comprehensiveness.

Benton International is a consulting firm for the financial services industry, with expertise in credit card and ATM automatic teller machine transaction processing. Hartford Foundation nor BI retains proprietary claims on this information. In a recent report, the Institute of Medicine IOM, c outlined the critical elements of health care reform that it believed sound reform proposals ought to address. The five main topics were access, containing costs, ensuring quality, financing care, and enhancing the infrastructure of health care.

At the time this study was conducted, the Hartford Foundation sponsored a separate study from researchers at the Harvard School of Public Health to examine questions related to the establishment of an ''Institute for Health Care Assessment," which would have as a major goal the advancement of quality measurement and improvement.

Services that such an institute might provide to HDOs might include project formulation, technical assistance in quality measurement, data collection and management, and analysis , report design and profiling e.

A clearinghouse effort and dissemination might also be contemplated. For further information, see McNeil et al. The literature in this area is extensive. Well-known articles—beginning about a decade ago on small-area-variations analysis—include McPherson et al.

For a recent review of this literature and a new interpretation of this body of empirical work that suggests that physician enthusiasm for particular services explains much of the geographic variation in utilization, see Chassin, a. The first major release of hospital-specific mortality rates dates to publications from HCFA e. Other illustrative research efforts include those reported by Chassin et al. Technology assessment overlaps with these research efforts in so far as it extends beyond reviews of the published literature or operations of expert panels to actual collection and analysis of data.

Often, however, technology assessment is directed more at emerging technologies—for example, new drugs, devices, or less often procedures—than at established ones. To the extent this is true, databases of the sort described in this report, particularly those derived from financial transactions in health care, will not contain much relevant or useable data on those newer technologies.

They will, however, contain valuable information for the comparison of these new technologies with existing approaches which always include watchful waiting.

When the focus of technology assessment is on established technologies, databases are useful not only for such evaluation activities, but also for setting priorities for assessment IOM, b. The term "benefits," as used in this report, has two distinct meanings, depending on the context. One reflects the general notion of positive advantages, gains, and useful aids in the conduct of some activity.

The other is the narrower insurance-related concept of a benefit package or contract, in which a set of services typically characterized as "medically necessary" is specified as covered and in which other services may be specifically identified as not covered.