Although it may seem self-evident, it is worth stating: health care information is the reason we need health care information systems. No study of information systems in health care would be complete without an examination of the data and information they are designed to support. The focus of this chapter will be on the data and information that are unique to health care, such as the clinical information created during patients’ health care encounters, the administrative information related to those encounters, and the external information used to improve the clinical care and administrative functions associated with those encounters.
We begin the chapter with a brief discussion of some common definitions of health care information. Then we introduce the framework that will be used for exploring various types of health care information. The first major section of the chapter looks at data and information created internally by health care organizations, discussing this information at both the individual client level and the aggregate level. This section also examines some core processes involved in an inpatient and an ambulatory care clinical encounter to further explain how and when internal health care data and information originate and how they are used. The final section examines health care data and information created, at least in part, externally to the health care organization, and addresses both comparative and knowledge-based data and information.
Different texts and articles define health care information, or health information, differently. Often it is the use or setting of the health information that drives the definition. For example, the government or an insurance company may have a certain definition of health care information, and the hospital, nursing home, or physician’s office may have other definitions. In this book we are primarily interested in the information generated or used by health care organizations, such as hospitals, nursing homes, physicians’ offices, and other ambulatory care settings. Of course, this same information may be used by governmental agencies or insurance companies as well.
Different definitions of “health information” and “health care information” have been developed by a variety of agencies and organizations. Some of the most well-known definitions of health information apply to identifiable patient information. These definitions ignore the vast amount of nonidentifiable information that is generated in the delivery of health care. This section examines and compares a few of the most well-known definitions of “health care information.”
The Health Insurance Portability and Accountability Act (HIPAA), the federal legislation that includes provisions to protect patients’ health information from unauthorized disclosure, defines health information as any information, whether oral or recorded in any form or medium, that—
HIPAA refers to this type of information as protected health information, or PHI. To meet the definition of PHI, information must first of all be identifiable, that is, it must have an individual patient perspective and the patient’s identity must be known. HIPAA-defined PHI may exist outside a traditional health care institution and is therefore not an appropriate definition for an organizational view of information such as ours. HIPAA is certainly an important piece of legislation, and it has a direct impact on how health care organizations create and maintain health information (HIPAA is discussed further in Chapter Three). However, not all the information that must be managed in a health care organization is protected health information. Much of the information used by health care providers and executives is neither patient specific nor identifiable in the HIPAA sense.
In an attempt to provide consensus definitions of key health care information terms, the National Alliance for Health Information Technology released a report “On Defining Key Health Information Technology Terms” in April 2008. Although the terms defined in this report are specific to health records, the definitions contain descriptions of the health information that is maintained by each type of record. The following are definitions of electronic medical record, electronic health record, and personal health record. Each of these definitions refers to patient-specific, identifiable health care information that would meet the HIPAA definition of PHI. (Although the alliance ceased to exist in 2009, these definitions continue to be recognized within the health care community.)
The Joint Commission, the major accrediting agency for health care organizations in the United States, has adopted the HIPAA definition of protected health information as the definition of “health information” listed in their accreditation manual glossary of terms (The Joint Commission, 2011). Creating, maintaining, and managing quality health information is a significant factor in a health care organization achieving Joint Commission accreditation. The 2011 accreditation manual contains dozens of standards that are devoted to the creation and management of health information, including two specific chapters, Record of Care, Treatment, and Services (RC) and Information Management (IM). The RC chapter outlines specific standards governing the components of a complete medical record, while the IM chapter outlines standards for managing information as an important organizational resource.
Our framework for looking at data and information created, maintained, manipulated, stored, and used within health care organizations is shown in Figure 1.1. The first level of categorization divides data and information into two categories: internal and external.
Figure 1.1. Types of health care information framework
Within the broad category of data and information created internally by the health care organization, we will focus on clinical and administrative information directly related to the activities surrounding the patient encounter, both the individual encounter and the collective encounters. We break information related to the patient encounter into the subcategories of patient-specific, aggregate, and comparative. Our focus is on the clinical and administrative individual and aggregate health care information that is associated with a patient encounter. Table 1.1 lists the various types of data and information that fall into the patient encounter subcategories of patient-specific and aggregate. Information typically found in a patient medical record is shown in italics. (The comparative data and information subcategory is found in both the internal and external categories; we will discuss it when we discuss external data and information.)
Table 1.1. Examples of types of patient encounter data information
Primary Purpose | ||
Type | Clinical | Administrative |
Patient-specific (items generally included in the patient medical record are in italics) | Identification form or information Problem list Medication record History Physical Progress notes Consultations Physicians’ orders Imaging and X-ray results Lab results Immunization record Operative report Pathology report Discharge summary Diagnoses codes Procedure codes | Identification form Consents Authorizations Preauthorization Scheduling Admission or registration Insurance eligibility Billing Diagnoses codes Procedure codes |
Aggregate | Disease indexes Specialized registers Outcomes data Statistical reports Trend analysis Ad hoc reports | Cost reports Claims denial analysis Staffing analysis Referral analysis Statistical reports Trend analysis Ad hoc reports |
The second major component of internal health care information in our framework is general operations. Data and information needed for the health care organization’s general operations are not a focus of this text. Health care executives do, however, need to be concerned not only with information directly related to the patient encounter but also with information about the organization’s general operations. Health care organizations are, after all, businesses that must have revenues exceeding costs to remain viable. The standard administrative activities of any viable organization also take place in health care settings. Health care executives interact with information and information systems in such areas as general accounting, financial planning, personnel administration, and facility planning on a regular if not daily basis. Our decision to focus on the information that is unique to health care and not a part of general business operations is not intended to diminish the importance of general operations but rather is an acknowledgment that a wealth of resources for general business information and information systems already exists.
In addition to using internally generated patient encounter and general operations data and information, health care organizations use information generated externally (Figure 1.1). Comparative data, as we will explain, combine internal and external data to aid organizations in evaluating their performance. The other major category of external information used in health care organizations is expert or knowledge-based information, which is generally collected or created by experts who are not part of the organization. Health care providers and executives use this type of information in decision making, both clinical and administrative. A classic example of knowledge-based clinical information is the information contained in a professional health care journal. Other examples are regional or national databases and informational web sites related to health or management issues.
The majority of clinical, patient-specific information created and used in health care organizations can be found in or has originated in patients’ medical records. This section will introduce some basic components of the patient medical record. It will also examine an inpatient and an ambulatory care patient encounter to show how the patient medical record is typically created. All types of health care organizations—inpatient, outpatient, long-term care, and so forth—have patient medical records. These records may be in electronic format, paper format, or a combination of both formats but the purpose and basic content are similar regardless of record or organizational type.
Health care organizations maintain medical records for several key purposes. As we move into the discussion of clinical information systems in subsequent chapters, it will be important to remember these purposes. These purposes remain constant regardless of the format or infrastructure supporting the records.
The importance of maintaining complete and accurate patient records cannot be underestimated. They serve not only as a basis for planning patient care but also as the legal record documenting the care that was provided to patients by the organization. Patient medical records provide much of the source data for health care information that is generated within and across health care organizations. The data captured in a patient medical record become a permanent record of that patient’s diagnoses, treatments, and response to treatments.
The American Health Information Management Association (AHIMA) maintains the web site www.myPHR.com, which lists the following components as being common to most patient records, regardless of facility type or medical record system (electronic or paper based) (AHIMA, 2012). Medical record content is determined to a large extent by external requirements, standards, and regulations (discussed in Chapter Three). This is not an exhaustive list, but with our expanded definitions it provides a general overview of this content and of the person or persons responsible for the content. It reveals that the patient record is a repository for a variety of clinical data and information that is produced by many different individuals involved in the care of the patient.
Figures 1.2 through 1.5 display screens from electronic health records. A patient record may contain some or all of the documentation just listed. Depending on the patient’s illness or injury and the type of treatment facility, he or she may need specialized health care services. These services may require specific documentation. For example, long-term care facilities and behavioral health facilities have special documentation requirements. Our list is intended to introduce the common components of patient records, not to provide a comprehensive list of all possible components. As stated before, the patient record components listed here will exist whether the health care organization uses electronic records, paper records, or a combination of both.
Figure 1.2. Sample EHR information screen
Source: Medical University of South Carolina; Epic.
Figure 1.3. Sample EHR problem list
Source: Medical University of South Carolina; Epic.
Figure 1.4. Sample EHR progress notes
Source: Medical University of South Carolina; Epic.
Figure 1.5. Sample EHR lab report
Source: Medical University of South Carolina; Epic.
Information within patient medical records has traditionally been organized in a diary-like, chronological format. The record content is organized by filing like documents together chronologically. In this type of arrangement all nurses notes would be filed in a different section from the physician notes or lab reports, which would be filed in their own sections of the record. Within each record section the notes or reports are organized in chronological order. This type of record arrangement is sometimes referred to as “source-oriented” because the content is organized by the source of the information.
In the late 1960s, Dr. Lawrence Weed challenged the way records were organized. He introduced the concept of patient-oriented medical records (POMR). The POMR is created and organized around the patient’s problems, not the source of the information. The goal of the POMR is to improve patient care through a more systematic way of documentation. Dr. Weed envisioned this system to improve communication and facilitate the continuity of care. The main components of the POMR are:
Although there are few examples of “pure” POMRs in use today, the problem list and the SOAP note are commonplace (Miller & O’Toole, 2003).
Where do medical record data and information come from? How do they originate? In this section we will walk through an inpatient encounter and also take a brief look at a physician’s office patient encounter. Along the way we will point out how medical record information is created and used. Figure 1.6 diagrams a reasonably typical nonsurgical inpatient admission. The middle column represents the basic patient flow in an inpatient episode of care. It shows some of the core activities and processes the patient will undergo during a hospital stay. The left-hand column lists some of the points along the patient flow process where basic medical record information is added to the medical record database or file. The right-hand column lists the hospital personnel who are generally responsible for a patient flow activity or specific medical record documentation or both. Using Figure 1.6 as a guide we will follow a patient, Marcus Low, through his admission to the hospital for radiation treatments.
Figure 1.6. Inpatient encounter flow
Even in this extremely brief outline of a two-day hospital stay, you can see that patient care and the reimbursement for that care involve many individuals who need access to timely and accurate patient information. The coordination of care is essential to quality, and this coordination relies on the availability of information. Other hospital stays are longer; some are emergency admissions; some involve surgery. These stays will need information additional to that discussed in this section. However, the basic components will be essentially the same as those just described.
An ambulatory care encounter is somewhat different from a hospital stay. Let’s follow Mr. Low again. This time we will describe his follow-up office visit with Dr. Good two weeks after his discharge from the hospital. Figure 1.7 is an outline of the process that Mr. Low followed during his office visit and the individuals who were responsible for each step in the process.
Figure 1.7. Physician’s office visit patient flow
One significant difference between an ambulatory care visit, such as a physician’s office visit, and a hospital stay is the scope of the episode of care. During an inpatient stay patients usually receive a course of treatment, with a definite admission point and discharge point. In an ambulatory care setting, particularly primary care physician visits, patients may have multiple problems and treatments that are ongoing. There may not be a definite beginning or end to any one course of treatment. There are likely to be fewer care providers interacting with the patient at any given ambulatory care visit. There may, however, be more consultations over time and a need to coordinate care across organizations. All these characteristics make the clinical information needs of the inpatient setting and the ambulatory care setting somewhat different, but in each setting, this information is equally important to the provision of high-quality care.
Health care information systems and health care processes are closely entwined with one another. Health care processes require the use of data and information and they also produce or create information. Care providers must communicate with one another and often need to share patient information across organizations. The information produced by any one health care process may in turn be used by others. A true web of information sharing is needed.
As we have seen in the previous section, patient-specific clinical information is captured and stored as a part of the patient medical record. However, there is more to the story—health care organizations need to get paid for the care they provide and to plan for the efficient provision of services to ensure that their operations remain viable. In this section we will examine individual patient data and information used specifically for administrative purposes. Health care organizations need data to effectively perform the tasks associated with the patient revenue cycle, tasks such as scheduling, precertification and insurance eligibility determination, billing, and payment verification. To determine what data are needed, we can look, first, at two standard billing documents, the UB-04 (CMS-1450) and the CMS-1500. In addition, we will discuss the concept of a uniform data set and introduce the Uniform Hospital Discharge Data Set, the Uniform Ambulatory Care Data Set, and the Minimum Data Set for long-term care.
Generally, the health care organization’s accounting or billing department is responsible for processing claims, an activity that includes verifying insurance coverage, billing third-party payers (private insurance companies, Medicare, or Medicaid), and processing the payments as they are received. Centers for Medicare and Medicaid Services (CMS) currently requires health care providers to submit claims electronically, unless the provider qualifies for a waiver. Although this section describes forms, the data requirements are the same whether an organization files electronically or with these forms under a waiver from the Administrative Simplification Compliance Act (ASCA) requirement for electronic submission of claims.
Depending on the type of service provided to the patient, one of two standard billing forms or data sets will be submitted to the third-party payer. The UB-04, or CMS-1450, is submitted for inpatient, hospital-based outpatient, home health care, and long-term care services. The CMS-1500 is submitted for health care provider services, such as those provided by a physician’s office. It is also used for billing by some Medicaid state agencies.
In 1975, the American Hospital Association (AHA) formed the National Uniform Billing Committee (NUBC, 1999), bringing the major national provider and payer organizations together for the purpose of developing a single billing form and standard data set that could be used for processing health care claims by institutions nationwide. The first uniform bill was the UB-82. It has since been modified and improved upon, resulting, first, in the UB-92 data set and now in the currently used UB-04 (see Exhibit 1.1). UB-04 is the de facto hospital and other institution claim standard. It is required by the federal government and state governments in their role as third-party payers and has been adopted across the United States by private third-party payers as well. One important change implemented with the transition from the UB-92 to the UB-04 is the requirement that each claim include a valid National Provider Identifier (NPI) (Centers for Medicare and Medicaid [CMS], 2006). The NPI is a unique identification number for each HIPAA-covered health care provider. Covered health care providers and all health plans and health care clearinghouses use NPIs in the administrative and financial transactions adopted under HIPAA. The NPI is a ten-position, “intelligence-free” numeric identifier, meaning that this ten-digit number does not carry any additional information about the health care provider to which it is assigned, such as the state in which the provider works or the provider’s medical specialty (CMS, 2008).
The National Uniform Claim Committee (NUCC, 2012) was created by the American Medical Association (AMA) to develop a standardized data set for the noninstitutional health care community to use in the submission of claims (much as the NUBC has done for institutional providers). Members of this committee represent key provider and payer organizations, with the AMA appointing the committee chair. The standardized claim form developed and overseen by NUCC is the CMS-1500. This claim form has been adopted by the federal government, and like the UB-04 for institutional care, has become the de facto standard for all types of noninstitutional provider claims, such as those for physician services (see Exhibit 1.2).
It is important to recognize that both the UB-04 and the CMS-1500 claim forms incorporate standardized data sets. Regardless of a health care organization’s location or a patient’s insurance coverage, the same data elements are collected. In many states UB-04 data and CMS-1500 data must be reported to a central state agency responsible for aggregating and analyzing the state’s health data. At the federal level the Centers for Medicare and Medicaid Services (CMS) aggregates the data from these claims forms for analyzing national health care reimbursement, clinical, and population trends. Having uniform data sets means that data can be compared not only within organizations but within states and across the country.
Other uniform data sets have been developed for use in the United States. Three examples are the Uniform Hospital Discharge Data Set (UHDDS), the Uniform Ambulatory Care Data Set (ACDS), and the Minimum Data Set (MDS) used for long-term care. These data sets share two purposes:
The UHDDS is the oldest uniform data set used in the United States. The earliest version was developed in 1969 by the National Center for Health Statistics. In 1974, the federal government adopted the UHDDS definitions as the standard for the Medicare and Medicaid programs. The UHDDS has been revised several times. The current version has the following data elements:
The ACDS was approved by the National Committee on Vital and Health Statistics in 1989. The goal of the ACDS is to improve the data collected in ambulatory and outpatient settings. The ACDS has not, however, been incorporated into federal rules or regulations. It remains a recommended rather than a required data set.
The MDS for long-term care is a federally mandated standard assessment tool that is used to collect demographic and clinical information about long-term care facility residents. It is an extensive data set with detailed data elements in twenty major categories. The MDS provides a structured way to organize resident information so that an effective care plan can be developed (LaTour, 2002).
As we have discussed in earlier sections of this chapter, diagnostic and procedural information is captured during the patient encounter to track clinical progress and to document care for reimbursement and other administrative purposes. This diagnostic and procedural information is initially captured in narrative form through physicians’ and other health care providers’ documentation in the patient record. This documentation is subsequently translated into numerical codes. Coding facilitates the classification of diagnoses and procedures not only for reimbursement purposes but also for clinical research and comparative studies.
Two major coding systems are employed by health care providers today:
Use of these systems is required by the federal government for reimbursement, and they are recognized by health care agencies both nationally and internationally.
On January 16, 2009, HHS published a final rule adopting ICD-10-CM (diagnoses codes) and ICD-10-PCS (procedure codes) to replace ICD-9-CM in HIPAA transactions, with the effective implementation date of October 1, 2013. However, the implementation of ICD-10 was delayed from October 1, 2013, to October 1, 2014, by final rule CMS-0040-F, issued on August 24, 2012.
In anticipation of the new system implementation, the discussion in this chapter focuses on the newer ICD-10 coding systems. The primary purpose of the ICD does not change from 9 to 10, but the structure is significantly different.
The U.S. ICD-10 classification system is derived from the International Classification of Diseases, Tenth Revision, which was developed by the World Health Organization to capture disease data. ICD-10-CM, like ICD-9-CM, will be used in the United States to code disease information. Procedure information will be coded using the ICD-10-PCS. Updates to the ICD-10-CM and PCS will be published each year. This publication is considered a federal government document whose contents may be used freely by others. However, multiple companies republish this government document in easier-to-use, annotated, formally copyrighted versions. The precursors to the current ICD system were developed to allow morbidity (illness) and mortality (death) statistics to be compared across nations. ICD-10-CM and PCS coding, like ICD-9-CM, however, has come to play a major role in reimbursement to hospitals. In 1983, ICD-9-CM began being used for determining the diagnosis related group (DRG) into which a patient is assigned. DRGs are the basis for determining appropriate inpatient reimbursements for Medicare, Medicaid, and many other health care insurance beneficiaries. Accurate ICD coding has as a consequence become vital to accurate institutional reimbursement. Exhibits 1.3 and 1.4 are excerpts from the ICD-10-CM and PCS classification systems. They show the system in its text form, but large health care organizations generally use encoders, computer applications that facilitate accurate coding. Whether a book or text file or encoder is used, the classification system is the same.
The conversion from ICD-9-CM to ICD-10-CM and PCS is a tremendous undertaking for health care organizations. ICD-10 includes substantial increases in content and many structural changes. When the U.S. modification is released, all health care providers will be required to adjust their systems to handle the conversion.
The American Medical Association (AMA) publishes an updated Current Procedural Terminology each year. Unlike ICD-9-CM, CPT is copyrighted, with all rights to publication and distribution held by the AMA. CPT was first developed and published in 1966. The stated purpose for developing CPT was to provide a uniform language for describing medical and surgical services. In 1983, however, the government adopted CPT, in its entirety, as the major component (known as Level 1) of the Healthcare Common Procedure Coding System (HCPCS). Since then CPT has become the standard for physician’s office, outpatient, and ambulatory care coding for reimbursement purposes. Exhibit 1.5 is a patient encounter form with examples of HCPCS/CPT codes.
As coding has become intimately linked to reimbursement, directly determining the amount of money a health care organization can receive for a claim from insurers, the government has increased its scrutiny of coding practices. There are official guidelines for accurate coding, and health care facilities that do not adhere to these guidelines are liable to charges of fraudulent coding practices. In addition, the Office of Inspector General of the Department of Health and Human Services (HHS OIG) publishes compliance guidelines to facilitate health care organizations’ adherence to ethical and legal coding practices. The OIG is responsible for (among other duties) investigating fraud involving government health insurance programs. More specific information about compliance guidelines can be found on the OIG web site (www.oig.hhs.gov) (HHS OIG, 2012).
In the previous section we examined different sets of clinical and administrative data that are collected during or in the time closely surrounding the patient encounter. Patient records, uniform billing information, and discharge data sets are the main sources of the data that go into the literally hundreds of aggregate reports or queries that are developed and used by providers and executives in health care organizations. Think of these source data as one or more data repositories, with each data element available to health care providers and executives. What can these data tell you about the organization and the care provided to patients? How can you process these data into meaningful information? The number of aggregate reports that could be developed from patient records or patient accounting information is practically limitless, but there are some common categories of clinical, administrative, and combined reports that the health care executive will likely encounter. We will discuss a few of these in this and the following sections.
On the clinical side, disease indexes and specialized registers are often used.
Health care organization management often wants to know summary information about a particular disease or treatment. Examples of questions that might be asked are: What is the most common diagnosis in the facility? What percentage of diabetes patients are African American? What is the most common procedure performed on patients admitted with gastritis (or heart attack or any other diagnosis)? Traditionally, such questions have been answered by looking in disease and procedure indexes. Prior to the widespread use of databases and computers, disease and procedure indexes were large card catalogues or books that kept track of the numbers of diseases treated and procedures occurring in a facility by disease and procedure ICD codes. Now that databases and computers are common, the disease and procedure index function is generally handled as a component of the patient medical record system or the registration and discharge system. The retrieval of information related to diseases and procedures is still based on ICD and CPT codes, but the queries are limitless. Users can search the disease and procedure database for general frequency statistics for any number of combinations of data. Figure 1.8 is an example of a screen resulting from a query for a list of diabetes patients.
Figure 1.8. Sample diabetes query screen
Source: Partners HealthCare.
Another type of aggregate information that has benefited tremendously from the use of computerized databases is the specialized register. Registers are lists that generally contain the names, and sometimes other identifying information, of patients seen in a particular area of the health care facility. A health facility might want an accounting of patients seen in the emergency department or operating room, for example. In general, a register allows data retrieval in a particular area of the organization. With the increased availability of large databases, many of these registers can be created on an ad hoc basis.
Trauma and tumor registries are specialized registries that often involve data collection beyond that done for the patient medical record and patient billing process. These registries may be found in facilities with high-level trauma or cancer centers. They are used to track information about patients over time and to collect detailed information for research purposes.
Many other types of aggregate clinical reports are used by health care providers and executives. The easy-to-use, ad hoc reporting that is available with databases today gives providers and executives access to any number of summary reports based on the data elements collected during the patient encounter.
Just as with clinical aggregate reports, a limitless number of reports can be created for administrative functions from today’s databases and data repositories. Commonly used administrative aggregate reports include basic health care statistical reports, claims denial reports, and cost reports. (In keeping with our focus on information unique to health care, we will not discuss traditional income statements, cash flow statements, or other general accounting reports.) Two basic types are described in this section: Medicare cost reports and basic health care statistical reports.
Medicare cost reports are filed annually by all hospitals, home health agencies, skilled nursing facilities, and hospices that accept Medicare or Medicaid. These reports must be filed within a specified time after the end of the fiscal year and are subject to scrutiny via compliance audits. The cost report contains such provider information as facility characteristics, utilization data, costs and charges by cost center (in total and for Medicare), Medicare settlement data, and financial statement data. Preparation instructions and the actual forms can be found on the CMS web site (www.cms.gov). Medicare cost reports are used by CMS not only to determine portions of an individual facility’s reimbursement but also to determine Medicare rate adjustments, cost limits, and various wage indexes.
The categories of statistics that are routinely gathered for health care executives or others are
General health care statistics are frequently used to describe the characteristics of the patients within an organization. They may also provide a basis for planning and monitoring patient services.
Health care executives are often interested in aggregate reports that combine clinical and administrative data. Ad hoc statistical reports and trend analyses may draw from both clinical and administrative data sources, for example. These reports may be used for the purpose of improving customer service, quality of patient care, or overall operational efficiency. Examples of aggregate data that relate to customer service are the average time it takes to get an appointment at a clinic and the average referral volume by physician. Quality of care aggregate data take many forms, revealing such things as infection rates and unplanned returns to the operating room. Cost per case, average reimbursement by DRG, and staffing levels by patient acuity are examples of aggregate data that could be used to improve efficiency. These examples represent only a few uses for combined aggregate data. Again, with today’s computerized clinical and administrative databases, any number of ad hoc queries, statistical reports, and trend analyses should be readily available to health care executives. Health care executives need to know what source data are collected and must be able to trust in data accuracy. Executives should be creative in designing aggregate reports to meet their decision-making needs.
Comparative data and information, gathered internally and externally, are used for both clinical and administrative purposes by health care organizations.
Comparative data and information are often aligned with organizations’ quality improvement efforts. For example, an organization might collect data on specific outcome measures and then use this information in a benchmarking process. Outcome measures are the measurable results of a process. This could be a clinical process, such as a particular treatment, or an administrative process, such as a claim filing. Outcome measures can be applied to individuals or groups. An example of a simple clinical outcome measure is the difference in prescribing practices among providers for patients with the same chronic disease. An example of an administrative outcome measure is the percentage of claims denied by Medicare during one month. Implicit in the idea of measuring outcomes is that they can be usefully compared over time or against a set standard. The process of comparing one or more outcome measures against a standard is called benchmarking. Outcome measures and benchmarking may be limited to internally set standards; however, frequently they are involved in comparisons with externally generated benchmarks or standards.
Balanced scorecards are another method for measuring performance in health care organizations. The concept of the balanced scorecard meets executives’ need to design measurement systems aligned with their organization’s strategy goals (Kelly, 2007). Balanced scorecard systems examine multiple measures, rather than the single set of measures common in traditional benchmarking. Suppose a health care organization uses “lowest-cost service in the region” as an outcome measure for benchmarking its performance against that of like facilities in the region. The organization does very well over time on this measure. However, you can see that it may be ignoring some other important performance indicators. What about patient satisfaction? Employee morale? Patient health outcomes? Balanced scorecards employ multiple measures along several dimensions to ensure that the organization is performing well across the board. The clinical value compass is a similar method for measuring clinical process across multiple dimensions (Kelly, 2007).
Organizations may select from many publicly and privately available health care data sets for benchmarking. A few of the more commonly accessed data sets are listed in Exhibit 1.6 (along with web addresses). These data sets are divided into five categories: patient satisfaction, practice patterns, health plans, clinical indicators, and population measures. Many of the listed web sites provide examples of the data sets, along with detailed information about their origins and potential uses.
Patient satisfaction data generally come from survey data. The three organizations listed in Exhibit 1.6, NRC+Picker, Press Ganey, and the health care division of Gallup, provide extensive consulting services to health care organizations across the country. One of these services is to conduct patient satisfaction surveys. There are other private organizations that provide similar services, and some health care organizations undertake patient satisfaction surveys on their own. These private efforts have been significant, but did not facilitate a nationally available system for benchmarking hospital performance. In 2002, CMS partnered with the Agency for Healthcare Research and Quality (AHRQ) to develop the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), “the first national, standardized, publicly reported survey of patient’s perspectives of hospital care” (CMS, 2012). Since 2005, the government has created several financial incentives for hospitals to participate in HCAHPS and it has been widely adopted. Results from HCAHPS are reported through the CMS Hospital Compare program, which is discussed later in this chapter.
The Commonwealth Fund Quality Chartbook series and the Dartmouth Atlas of Health Care allow health care organizations to view practice patterns across the United States. The Dartmouth Atlas provides an online interactive tool that allows organizations to customize comparative reports based primarily on Medicare data (Figure 1.9).
Figure 1.9. Example of Dartmouth Atlas interactive report
Source: Dartmouth Institute for Health Policy & Clinical Practice, 2012.
The mission of the National Committee for Quality Assurance (NCQA) is “to improve the quality of health care.” NCQA’s efforts are organized around two major activities: accreditation and performance measurement. (We will discuss the accreditation activity in Chapter Three.) To facilitate these activities NCQA developed the Health Plan Employer Data and Information Set (HEDIS) in the late 1980s. HEDIS currently consists of seventy-six measures across five domains of care and is used by more than 90 percent of America’s health plans. A few of the health issues measured by HEDIS are (NCQA, 2012a):
The NCQA web site offers an interactive tool for obtaining report cards on specific health plans that have undergone NCQA accreditation. Multiple health plans can be compared to each other and against national averages. The comparison of two South Carolina health plans in Figure 1.10 is an example of an NCQA report card (NCQA, 2012b).
Figure 1.10. Example of NCQA report card
Source: NCQA, 2012b.
Both the Joint Commission and CMS are committed to the improvement of clinical outcomes. The Joint Commission’s Quality Check has evolved since its introduction in 1994 to become a comprehensive guide to health care organizations in the United States. Visitors to www.qualitycheck.org can search for health care organizations by a variety of parameters, identify accreditation status, and download hospital performance measures. In addition, the Joint Commission–accredited organizations can get a summary of their performance measured in terms of the Joint Commission’s National Patient Safety Goals and Quality Improvement Goals (The Joint Commission, 2012).
The CMS quality programs are aimed at hospitals, nursing homes, home care, and physicians’ practices. The Hospital Compare web site (www.hospitalcompare.hhs.gov) and interactive comparison tool were developed in collaboration with other public and private organizational members of the Hospital Quality Alliance. Comparison reports for hospitals can be created based on location and on specific medical conditions or surgical procedures. The resulting reports provide information on process of care measures, outcome of care measures, use of medical imaging, surveys of patients’ hospital experiences from HCAHPS, patient safety measures, and medical payment information (HHS, 2012).
Figure 1.11. Example of hospital compare graphical report
Source: HHS, 2012.
Other comparative data sources that could be useful for the health care manager are those that provide population measures. Most state health departments collect statewide morbidity and mortality data. These data generally come from a variety of sources, including hospital and provider bills. At the national level both the Centers for Disease Control and Prevention (CDC) and the Agency for Healthcare Research and Quality (AHRQ) provide a wealth of population-based health care data.
The Joint Commission accreditation manual (2011, p. GL-9) defines knowledge-based information as “A collection of stored facts, models, and information that can be used for ongoing staff development, for designing and redesigning processes, and for solving problems. … Knowledge-based information is found in the clinical, scientific, and management literature.” Health care executives and health care providers rely on knowledge-based information to maintain their professional competence and to discover the latest techniques and procedures. The content of any professional journal falls into the category of knowledge-based information. Other providers of knowledge-based information are the many online health care and health care management references and resources. With the development of rule-based computer systems, the Internet, and push technologies, health care executives and providers are finding that they often have access to vast quantities of expert or knowledge-based information at the time they need it, even at the patient bedside. Most clinical and administrative professional organizations not only publish print journals but also maintain up-to-date web sites where members or other subscribers can get knowledge-based information. Several organizations also provide daily, weekly, or other periodic e-mail notifications of important events that are pushed onto subscribers’ personal computers.
Knowledge-based information can also be incorporated into electronic medical records or health care organization web sites. Figure 1.12 is a sample of the knowledge-based information resources available through an electronic medical record interface.
Figure 1.12. Sample electronic knowledge-based information resources
Source: Partners HealthCare.
Without health care data and information, there would be no need for health care information systems. Health care information is a valuable asset in health care organizations, and it must be managed like other assets. To manage information effectively, health care executives should have an understanding of the sources and uses of health care data and information. In this chapter we introduced a framework for discussing types of health care information, looked at a wide range of internal data and information whose creation and use must be managed in health care organizations, and also discussed a few associated processes that are typically part of patient encounters. We examined not only patient-specific (individual) internal information but also aggregate information. We addressed both clinical and administrative data and information in our discussions. In addition, we examined several types of external data and information that are available for use by health care organizations, including comparative and knowledge-based data and information. Throughout, our view of data and information was organizational and the focus was on that information that is unique to health care.
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