DEFINING HEALTH CARE

One of the first challenges in addressing safety in U.S. health care is that there may not be a uniform way to define “U.S. health care.” The Dartmouth Atlas, published by the Dartmouth Institute for Health Policy and Clinical Practice, found U.S. health care is “remarkably uneven,” with wide variations in the frequency of primary care, visits to medical specialists, hospitalization rates, and other characteristics (Wennenberg et al, 2008). These variations challenge popular assumptions about health care. At first glance, one is tempted to make a lot of assumptions that the Dartmouth Atlas subsequently refutes. For instance, facilities that spend more on care do not necessarily deliver better care. Conversely, some of the best care in the United States is provided by lower-cost providers. It might seem reasonable to assume that different severities of illness are reflected in different spending levels, but that is also not the case. Therein lies the heart of the issue: high costs are more indicative of quality and safety issues than higher levels of care (Wennenberg et al, 2008).

HEALTH CARE COSTS

In discussing why care costs much more at certain institutions, the Dartmouth Atlas attributes such variations to supply-sensitive care, in which the supply of a specific resource (such as number of specialists or hospital beds per capita) influences use rates. Although supply sensitivity influences health care spending, it does not necessarily deliver better care. Whether viewed from the patient’s perspective (outcomes, technical quality, satisfaction with care provided) or the physician’s viewpoint (quality of communication among physicians, continuity of care), higher spending is not associated with better care either for Medicare beneficiaries (in isolation) or for all patients who have serious illnesses cared for at major U.S. academic medical centers.

The relationship between cost and safety in U.S. health care is complex. Medical errors carry a huge price tag for institutions, payers, and patients and their families. Yet the current U.S. health care system is not set up for payers to exercise much control over the quality of care delivered.

CURRENT HEALTH CARE SYSTEMS

Congress has called for fundamental reforms of the Centers for Medicare & Medicaid Services (CMS), moving it to a more proactive role from its previous role as “passive payer” that provides incentives for health care consumption with no links back to quality or appropriateness. The original Medicare program was designed to pay for care, as ordered, and to treat as inconsequential the quality of care. Medicare had no incentives (or even passive penalties) for such commonsense tactics as preventive medicine, withholding excessive care, or thorough patient education (Valuck, 2009). Under the Deficit Reduction Act of 2005, Section 5001(b), CMS was authorized to develop a pay-for-performance or value-based purchasing (VBP) program for hospitals that would tie reimbursement to achievement of certain benchmarks or goals in quality and efficiency. VBP is considered a major paradigm shift in U.S. health care. Although financial reform is no doubt needed, it is perhaps even more important to consider the role VBP could play in improving patient safety.

GOVERNMENT INITIATIVES

The hospital VBP plan, launched in 2009, uses measures, data infrastructure and validation steps, incentive structure, and public reporting. In setting up this program, CMS identified that care ought to be safe, effective, efficient, patient centered, timely, and equitable. The goal is first to quantify where hospitals are and then establish ways to measure improvement. Hospitals will be awarded a Total Performance Score, an aggregate of scores based on attaining certain benchmark levels and based on their own improvement over the preceding year. This Total Performance Score translates into an incentive payment plan. The hospital VBP plan has elevated patient safety to a key element of the Total Performance Score. Although safety is now tied to financial incentives, it may be of even more value that hospitals have been given ways to measure their levels of safety, to report safety data, to compare their data against established benchmarks, and to use safety scores as a way to identify specific areas for improvement. Of course, tying financial incentives to performance in a field fraught with uncontrollable variables can be a difficult leap of faith for hospital administration. Every health care provider knows that there are times when a clinical team can do everything right and still get a poor outcome.

The American Hospital Association (AHA) supports VBP but advocates moving forward carefully and with deliberation to avoid the creation of convoluted or counterproductive incentive-based payment plans. The AHA has set forth guidelines to create a workable incentive program that includes focusing on improving quality (rather than cutting costs), incremental implementation, and using measures that are evidence based, tested, feasible, and statistically sound and that recognize differences in patient populations (AHA, 2009b). VBP initiatives are some of the most fundamental changes in American health care in recent times, but other initiatives already have been used successfully to help address the safety issues in U.S. hospitals.

In 1996 the Institute of Medicine (IOM) of the National Academies in the United States launched a phased, multiyear initiative aimed at the large but important goal of improving the quality of health care in the United States. The first phase (1996-1999) reviewed medical literature to capture the scope of the problem, which can be summed up as the overuse, underuse, and misuse of available health care resources. In the second phase (1999-2001), the Committee on Quality of Health Care in America formulated metrics and a road map to help “cross the quality chasm” from what medical consensus determines to be sound health care practice versus what U.S. patients actually receive. Now in its third phase, this initiative seeks to put its vision into practice by creating a “more patient-responsive health system” (IOM, 2009).

Initiatives to improve patient safety may seem fairly straightforward on the surface, but crafting them can be complicated. Such measures, both public and private, have been successful in accomplishing the goals they set for themselves and finding resonance with the clinical community. The result has been a wave of initiatives that has created its own confusion. In 2006 the AHA launched the AHA Quality Center to help hospital leaders keep abreast of the many new and effective measures to improve quality and patient safety (AHA, 2009a).

An effective initiative must involve two distinct entities—health care services and health care systems—and help restructure their interaction (Clancy, 2007). The Agency for Healthcare Research and Quality (AHRQ) of the U.S. Department of Health and Human Services formulated Ten Patient Safety Tips for Hospitals. The tips may be grouped into setting up quality programs at the hospital (continuous improvement, reporting systems, proper decision-making tools), creating an efficient working environment for clinicians (teamwork, limiting shifts, using appropriate-level staff, minimizing interruptions), and fundamental medical safety tips (such as infection prevention and proper use of chest tubes and urinary catheters) (AHRQ, 2009).

Part of AHRQ’s role is to provide data necessary to formulate initiatives and assess quality levels. One such successful effort is the creation of the Consumer Assessment of Healthcare Providers and Systems (CAHPS), a program that develops patient surveys to evaluate the patient’s perception of his or her care. Data pose a unique problem in patient safety initiatives. As the U.S. health care market increasingly asks consumers to make important decisions about their own health care, the need for comprehensible patient safety data becomes urgent. Hospitals now follow no uniform national standards regarding what data they collect, how they collect data, and how these data are transmitted. Apples-to-apples comparisons can be impossible across systems. Variations in which data are collected and how they are collected can occur even among hospitals in the same system. For this reason the National Voluntary Hospital Reporting Initiative, a public-private collaborative, launched a three-state pilot program in 2003 to standardize hospital data across all systems. The goal is to collect similar data in similar ways so that meaningful comparisons can be made across the continuum of care and among facilities (American Health Quality Association, 2003).

Even today, the degree to which health care in the United States is consistent with basic quality standards is largely unknown, in part because quality studies tend to be highly focused and not indicative of overall care received by the average consumer (McGlynn and Brook, 2001). Thus it may be possible to obtain safety statistics for a specific procedure done in a specific time period at certain hospitals, but not broad safety statistics. This paucity of information contributes to the persistent belief in the United States that quality is not a serious national health care issue. In a comprehensive study, phone interviews with a random sampling of adults (n = 6712) in 12 U.S. metropolitan areas evaluated performance on 439 indicators of quality of care for 30 acute and chronic conditions and for preventive care. Aggregate scores found that only about half (54.9%) of patients received recommended care (McGlynn et al, 2003). What remains unknown is the real price tag for those patients who did not receive recommended care—in financial terms and in human suffering and even loss of life.

Institute for Healthcare Improvement Initiatives

The Institute for Healthcare Improvement (IHI) (2009b) launched a groundbreaking initiative in 2004 with its aptly named 100,000 Lives Campaign, aimed at reducing deaths attributable to preventable medical errors. More than 3000 hospitals came together for an initial program credited with saving 122,000 lives in its first 18 months. Encouraged by national and grassroots-level resonance, IHI launched its 5 Million Lives Campaign in 2006, aimed at preventing 5 million cases of medical harm over a 2-year period (IHI, 2009b). More than 3800 facilities enrolled in 5 Million Lives, including more than 1500 rural hospitals (which have a special rural affinity group to address their unique needs). Building on the first six proven interventions of the 100,000 Lives Campaign, the 5 Million Lives Campaign added six more (Box 2-1).

BOX 2-1 IHI Proven Interventions

The 5 Million Lives Campaign challenges U.S. hospitals to adopt 12 changes in care that save lives and reduce patient injuries:

THE SIX INTERVENTIONS FROM THE 100,000 LIVES CAMPAIGN

• Deploy Rapid Response Teams… at the first sign of patient decline

• Deliver Reliable, Evidence-Based Care for Acute Myocardial Infarction… to prevent deaths from heart attack

• Prevent Adverse Drug Events (ADEs)… by implementing medication reconciliation

• Prevent Central Line Infections… by implementing a series of interdependent, scientifically grounded steps

• Prevent Surgical Site Infections… by reliably delivering the correct perioperative antibiotics at the proper time

• Prevent Ventilator-Associated Pneumonia… by implementing a series of interdependent, scientifically grounded steps

NEW INTERVENTIONS TARGETED AT HARM

• Prevent Harm From High-Alert Medications… starting with a focus on anticoagulants, sedatives, narcotics, and insulin

• Reduce Surgical Complications… by reliably implementing all of the changes recommended by SCIP, the Surgical Care Improvement Project (www.medqic.org/scip)

• Prevent Pressure Ulcers… by reliably using science-based guidelines for their prevention

• Reduce Methicillin-Resistant Staphylococcus aureus (MRSA) infection… by reliably implementing scientifically proven infection control practices

• Deliver Reliable, Evidence-Based Care for Congestive Heart Failure… to avoid readmissions

• Get Boards on Board… by defining and spreading the best known leveraged processes for hospital boards of directors, so that they can become far more effective in accelerating organizational progress toward safe care

IHI, Institute for Healthcare Improvement.

From Institute for Healthcare Improvement: Protecting 5 million lives from harm, available at http://www.ihi.org/NR/rdonlyres/EB78B6DB-0955-4C9C-A9B8-599E1E53DF6D/0/5MillionLivesCampaignBrochure0207.pdf. Accessed on August 18, 2009.

Participating hospitals picked at least one of the interventions to address and were encouraged to implement several. The 100,000 Lives and 5 Million Lives initiatives demonstrate the role that a single hospital, acting independently, can play in improving patient safety. Although sweeping national programs are important, this sort of well-promoted initiative of individual facilities also has been effective.

The eighth intervention of the 5 Million Lives campaign refers to the Surgical Care Improvement Project (SCIP), a well-known program for surgical safety. SCIP’s genesis was in 2002, when CMS and the Centers for Disease Control and Prevention (CDC) launched the Surgical Infection Prevention Project. Findings from this project on preventable surgical site infections and inappropriate use of antibiotics resulted in the creation of SCIP, a suite of national initiatives to improve the care of Medicare patients receiving surgery. The original goal of SCIP was to reduce preventable surgical morbidity and mortality by 25% by 2010. Using outcome, process, and test measures, SCIP periodically identifies, measurable outcomes of preventable complications specific to the surgical setting (Table 2-1).

TABLE 2-1 Surgical Care Improvement Project National Hospital Inpatient Quality Measures

Set Measure ID #	Measure Short Name
INFECTION
SCIP Inf-1	Prophylactic antibiotic received within one hour prior to surgical incision.
SCIP Inf-2	Appropriate antibiotic received.
SCIP Inf-3	Prophylactic antibiotic discontinued within 24 hours after surgery end (48 hours for cardiac surgery).
SCIP Inf-4	Cardiac surgery patients with controlled 6 am postoperative blood glucose.
SCIP inf-6	Appropriate hair removal for surgery patients.
SCIP Inf-9	Urinary catheter removed on postoperative (POD) Day 1 or POD Day 2
SCIP Inf-10	Surgery patients with perioperative temperature management.
VENOUS THROMBOEMBOLISM
SCIP VTE-1	Recommended VTE prophylaxis ordered.
SCIP VTE-2	Appropriate VTE prophylaxis received within 24 hours prior to surgery to 24 hours after surgery.
CARDIAC
SCIP Card-2	Surgery patients on beta-blocker therapy prior to arrival who receive a beta-blocker during perioperative period.

The Specifications Manual for National Hospital Inpatient Quality Measures (Version 3.0c, November 06, 2009) is the collaborative work of the Centers for Medicare & Medicaid Services and The Joint Commission. The Specifications Manual is periodically updated by the Centers for Medicare & Medicaid Services and The Joint Commission.

Modified from Centers for Medicare and Medicaid Services (CMS), The Joint Commission (TJC): Specifications manual for national hospital inpatient quality measures (specifications manual), version 3.0c, 2009, available at: http://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2Fpage%2FQnetTier4&cid=1228695698425. Accessed December 14, 2009.

At the beginning of 2009 IHI launched a new campaign called the IHI Improvement Map, which retains the 12 patient safety interventions from the 5 Million Lives campaign and adds 3 more: (1) the World Health Organization (WHO) Surgical Safety Checklist, (2) prevention of catheter-associated urinary tract infections, and (3) ability to link quality and financial management—engage the chief financial officer and provide value for patients (IHI, 2009a). The WHO Surgical Safety Checklist (Figure 2-1) gained recognition following a study describing how its use significantly reduced patient morbidity and complications (Haynes et al, 2009). In hospitals where the checklist was used, postoperative complication rates fell by 36% on average, and death rates fell by a similar amount (Haynes et al, 2009).