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Including Oncology Outcomes of Care in the Computer-Based Patient Record

Including Oncology Outcomes of Care in the Computer-Based Patient Record

ABSTRACT: Changes in the health care system have caused a shift in research to outcomes of care, effectiveness, efficiencies, clinical practice guidelines, and costs. The greater use of computer systems, including decision support systems, quality assurance systems, effectiveness systems, cost containment systems, and networks, will be required to integrate administrative and patient care data for use in determining outcomes and resource management. This article describes developments to look forward to in the decade ahead, including the integration of outcomes data and clinical practice guidelines as content into computer-based patient records; the development of review criteria from clinical practice guidelines to be used in translating guidelines into critical paths; and feedback systems to monitor performance measures and benchmarks of care, and ultimately cost out cancer care. [ONCOLOGY 9(Suppl):161-167, 1995]

Introduction

In the 1990s, the focus of health care research began to shift
toward outcomes, effectiveness, and efficiencies. The Agency for
Health Care Policy and Research (AHCPR) was legislatively charged
with initiating programs and research to provide a more rational
basis for decisions about which treatments to offer and which
technologies to purchase. Dr. Clifton Gaus, the agency administrator,
represents the mission of AHCPR in terms of a quality-accountability
continuum (Figure 1) [1]. Basic science and biomedical research
precede this continuum or provide a basis for the type of health
services research that AHCPR sponsors. Outcomes and effectiveness
research, clinical practice guidelines, technology assessments,
and the science of quality measurement are the necessary ingredients
to yield outcomes management (the assessment of clinical practice)
and institutional or individual accountability.

The computer-based patient record is the most useful tool to manage
the data from outcomes, effectiveness, and efficiencies research.
In the outcomes initiative, we define "effectiveness"
as outcomes experienced by, or observed in, patients in routine
clinical practice. This is distinct from "efficacy,"
which refers to the potential benefit of clinical interventions
provided under ideal circumstances to patients who meet specific
criteria. "Cost effectiveness" summarizes the cost and
effect of treatment in terms of specified outcomes measured in
nonmonetary units; it indicates value obtained for resources expended.
In the past, the concept that "knowledge is power" held
sway, but this has shifted in a market-driven system to the concept
that "knowledge is money" [2].

Outcomes data are an integration of administration and patient
care data for determining outcomes and resource management. Outcomes
are only one part of the assessment of a health system's performance.
Other components include access, utilization, cost, resources,
and patient satisfaction.

The focus of outcomes is also moving toward transaction-information-based
patterns of care and quality of care measurement. This type of
focus emphasizes the use of clinical practice guidelines. Recently,
attention has centered on the possibility of using clinical practice
guidelines developed by AHCPR as content driving the computerized
patient record [3]. Others have described the placement of clinical
practice guidelines on the physician workstation to provide access
to up-to-date information [4].

Guidelines can be useful in managing care, since they define the
appropriate diagnostic and treatment interventions/procedures
to achieve outcomes while reducing variability in practice. The
computer programmed with clinical practice guideline content can
lead to improved collection of data and act as a decision platform
upon which to guide practice [3]. Practice guidelines include
recommendations for diagnostic and treatment procedures that might
be overlooked in the routine delivery of care, but they still
require clinician decision making, since many options are provided.

This manuscript describes the need for integration of the concepts
of outcomes data management, clinical practice guidelines, and
the development of review criteria to provide feedback systems
to monitor critical paths (clinical pathways) and performance
measures (benchmarks of care), and ultimately cost out care through
the computer-based patient record. The examples given in this
manuscript relate to oncology care, but other conditions could
be substituted.

Outcomes Data Management

One definition of outcomes is the end result of a treatment or
intervention. While this definition looks and sounds simple, in
actual practice establishing realistic and measurable outcomes
is more difficult. Many types of outcomes are being used in a
variety of types of health services research. Outcomes management
examines the treatment of clinical conditions rather than individual
procedures or treatments. It is the systematic assessment of clinical
practice, encompassing outcomes that are relevant to patients--mortality,
morbidity, complications, symptom reduction, functional improvement--as
well as physiologic and biologic indicators. It involves all reasonably
held theories and alternative clinical practice interventions
[5].

Many of the concepts of outcome management are wrapped up in the
terms health status and health-related quality of life (HRQOL).
Health status measures a patient's clinical, biological, and physiological
status such as morbidity, mortality, blood pressure, hemoglobin,
and temperature. Health-related quality of life measures physical
function such as activities of daily living (ADLs), instrumental
ADLs (eg, medication administration), emotional and psychological
functioning and well-being, social functioning and support, role
functioning, general health perceptions, pain, vitality (energy/fatigue),
and cognitive functioning.

One method of monitoring outcomes in the computerized patient
record is the use of disease-specific health status and health-related
quality of life measurements. The tools to measure health status
and quality of life, however, have been described for only a few
diseases and conditions.

Once the health status or health-related quality of life indicators
are chosen for specific diseases or conditions, patient trends
for groups of patients with the same condition can be monitored.
These types of systems help to define episodes of care, ie, when
a patient's problem began and when it "ended," and also
which procedures were attached to which episode or patient condition.

The socioeconomic and sociodemographic characteristics of patients
are often forgotten in defining content in databases to monitor
outcomes. Unless the computer database is built interrelating
patient outcomes with patient demographics, it is difficult to
determine if the outcomes of the condition are a result of practitioner
interventions or the patient's environmental, demographic, social,
or economic conditions. For example, it is difficult to determine
patients' responses to chemotherapy when they are also taking
megadoses of vitamins, changing diet, and consuming enormous volumes
of shark cartilage. Similarly, it is more challenging to manage
patients who are homeless than those who have a residence.

Demographic data are also needed to relate the role and influence
of comorbidities, eg, history of substance abuse, age of patient,
obesity, or failure of previous treatment interventions. Different
outcomes can be expected after breast cancer surgery for a 65-year-old
patient with no comorbidities and a 65-year-old patient who also
has insulin-dependent diabetes, a history of congestive heart
failure, and hypertension.

Two other forgotten areas to monitor for outcomes are safety and
claims databases. The safety database includes error reports,
falls, and other patient liabilities. The claims database includes
not only patient liabilities but also personnel or employee claims
for back injuries, falls, and workmen's compensation claims.

Table 1 is a composite list of data requirements in the patient
record for better integration of outcomes with patient care [6-8].

AHCPR Oncology-Related Projects

The activities of the AHCPR include research efforts, the development
of clinical guidelines, and technology assessments. The Medical
Treatment Effectiveness Program (MEDTEP) research portfolio includes
studies designed to describe breast cancer screening policies
and practice; evaluate practice variations and costs of cancer;
study hysterectomy outcomes (a community-based study); identify
treatment choices and outcomes in prostate cancer, ie, TURP versus
open prostatectomy or nonoperative treatments; examine regional
variations in cancer treatment and mortality; study the impact
of a physician's insurer on early cancer detection; evaluate breast
and colon screening by cancer mortality; study cancer prevention
for minority women in a Medicaid HMO; and perform a retrospective
survival analysis for prostate cancer.

Large PORT (patient outcomes research team) studies in oncology
include the assessment of therapies for benign prostatic hypertrophy
and localized prostate cancer (Dr. Wennberg, Dartmouth) and a
new PORT II project concerning the care, costs, and outcomes of
localized breast cancer (Dr. Hadley, Georgetown University) and
prostatic disease (Dr. Barry, Boston).

The AHCPR also funds a number of Research Centers on Minority
Populations. Those that focus on cancer include the University
of California-San Francisco, Henry Ford Hospital in Detroit, Pacific
Health Research Institute in Honolulu, and the University of New
Mexico, Albuquerque.

Clinical practice guidelines developed by the AHCPR that are useful
to the oncologist include those on acute pain management; depression
detection, diagnosis, and treatment; benign prostatic hyperplasia;
quality determinants of mammography; and the management of cancer
pain.

The AHCPR technology assessment program has conducted assessments
of the selection criteria for hyperthermia in conjunction with
cancer chemotherapy and the use of autologous peripheral stem
cell transplantation. In addition, health technology reviews have
been published on lymphedema pumps, pneumatic compression devices,
external and implantable infusion pumps, and hematopoietic stem
cell transplantation for multiple myeloma.

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