An important component of the informatics infrastructure is

Chapter 20 Patient Safety and Quality Initiatives in Informatics

Patricia C. Dykes

Kumiko Ohashi

Because of the complexity of the errors in healthcare, multifaceted strategies including health information technology tools are needed to realize improvement in clinical processes and patient outcomes when striving to improve quality and safety.

Objectives

At the completion of this chapter the reader will be prepared to:

1.Define patient safety and quality of care and describe the role of health IT in advancing the quality and safety of healthcare in the United States

2.Review three national initiatives driving adoption and use of health IT in the United States

3.Review two national initiatives related to promoting quality data standards in the United States

4.Discuss the components of the Framework for Patient Safety and Quality Research Design and describe how this framework can be used to evaluate quality and patient safety interventions and research.

Key Terms

Adverse event, 328

Health information technology (health IT), 323

Meaningful Use, 323

Patient safety, 324

Pay for performance, 329

Quality of care, 324

Abstract

The chapter begins by defining quality of care and patient safety and by discussing key regulatory initiatives that drive a focus on quality and safety in the United States. The Framework for Patient Safety and Quality Research Design is then introduced as a means to classify and to evaluate adverse patient safety and quality events with a focus on medication safety, chronic illness screening and management, and nursing sensitive quality outcomes. The chapter ends with a discussion of success factors, lessons learned, and future directions for using the Framework for Patient Safety and Quality Research Design as a guide for both informatics research and practice.

Introduction

For more than a decade a series of Institute of Medicine (IOM) reports on the quality of healthcare have led to widespread recognition that errors occur far too often and that the quality of patient care is variable across the U.S. healthcare system.1–5 Evidence suggests that the use of health information technology (health IT) supports better communication and error reduction.6,7 Widespread adoption of health IT is a recommended strategy to facilitate effective, high-quality, and safe patient care.8

The passage of the American Recovery and Reinvestment Act (ARRA) of 2009 is expected to improve the quality of care by promoting adoption and supporting Meaningful Use of electronic health records (EHRs)9 and through widespread improvement in the ability to detect and reduce clinical errors.10 ARRA requires that hospitals demonstrate Meaningful Use of EHRs through the following mechanisms:

1.Use of a certified EHR

2.Facilitation of care coordination and quality by participating in the exchange of electronic health information

3.Submission of data for quality reporting

In this chapter the use of health IT to improve quality of care and patient safety is examined. First, the concepts “quality of care” and “patient safety” are defined and some of the key regulatory initiatives that are driving a focus on quality of care and patient safety in the U.S. are discussed. Next, the Framework for Patient Safety and Quality Research Design11 is introduced and used to classify adverse patient safety and quality events, discuss key success factors and lessons learned, and then make recommendations for implementation and future research.

Definitions

Inconsistent use of language is a barrier to understanding quality and patient safety and to benchmarking beyond the organizational level.12 To provide a foundation, the definitions of quality of care and patient safety put forth by the IOM and the World Health Organization (WHO) World Alliance for Patient Safety are presented.

Quality of Care

In its 1990 report titled Medicare: A Strategy for Quality Assurance the IOM defined quality of care as “the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge.”4(p21) In 2001, in its report titled Crossing the Quality Chasm, the IOM proposed six aims as a means to narrow the quality chasm that exists in the U.S. healthcare system.2 It proposed that healthcare should be:

•Safe: prevents injury or other adverse outcomes

•Effective: ensures that evidence-based interventions are used, with patients always receiving the treatments most likely to be beneficial

•Patient-centered: ensures that patient preferences, needs, and values are front and center in the process of clinical decision making

•Timely: delivered when needed and without harmful delays

•Efficient: prevents the waste of valuable human and material resources

•Equitable: provided to all individuals without regard for ethnic, racial, socioeconomic, or other personal characteristics

The WHO World Alliance for Patient Safety adopted the IOM definition of quality of care in its International Classification for Patient Safety (ICPS) released in 2009.12

Patient Safety

The IOM defined patient safety as “freedom from accidental injury due to medical care, or medical errors” where error is defined as “the failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim.”3(p4)

The ICPS defined safety as “the reduction of risk and unnecessary harm to an acceptable minimum” and patient safety as “the reduction of risk of unnecessary harm associated with healthcare to an acceptable minimum.”12(p21) The ICPS defined error as “failure to carry out a planned action as intended or application of an incorrect plan” and healthcare-associated harm as “harm arising from or associated with plans or actions taken during the provision of healthcare, rather than an underlying disease or injury.”12(pp19,21)

These definitions highlight the multifaceted nature of quality and safety and the notion that failures of both omission (e.g., failure to provide evidence-based care) and commission (e.g., providing care incorrectly) can compromise the quality and safety of healthcare.

National Initiatives Driving Adoption and Use of Health IT

A key lesson learned from the IOM's Quality Chasm Series is that achievement of higher quality and safer care in the U.S. requires systemic redesign of established clinical processes and that health IT is needed to support and maintain the transition to best practices.1–3,5,8,13 Several initiatives on the national level have maintained a steady focus on quality and patient safety. Recent U.S. policy is aligning incentives with the goal of adoption and widespread use of health IT to ensure a healthcare system characterized by uniform high quality and safe patient care.14 In 2011 the Office of the National Coordinator for Health Information Technology (ONC) published a report titled Federal Health Information Technology Strategic Plan: 2011–2015.15 This report defines the ONC's plan for working with the private and public sectors to achieve the nation's health IT agenda. Specific examples of accreditation and policy efforts designed to achieve the six quality aims defined by the IOM through a focus on redesign of clinical processes and adoption and Meaningful Use of health IT are included in Table 20-1.

Key areas of focus for ongoing accreditation and policy efforts include improving the quality of care and preventing adverse events. Evidence suggests that the U.S. may be making progress in the quest for higher quality and safer care but there is much room for improvement. Downey, Hernandez-Boussard, Banka, and Morton evaluated national trends in patient safety indicators (PSI) such as postoperative pulmonary embolism, deep vein thrombosis, and pressure ulcers. They found significant PSI trends for the decade 1998 to 2007. PSIs with the greatest levels of improvement during that period included birth trauma injury to neonates, postoperative physiologic and metabolic derangements, and iatrogenic pneumothorax. The PSIs with the greatest increase in incidence included pressure ulcers, postoperative sepsis, and infections due to medical care. Downey and colleagues noted that health IT holds potential for decreasing PSIs through standard reporting requirements and by supporting evidence-based practices through decision support and the use of order sets.16

National Efforts Related to Quality Data Standards

As mentioned in the previous section, the Meaningful Use initiative aims to improve the quality of care in the U.S. through routine exchange of electronic health information for care delivery and quality reporting purposes. However, much work is needed to build the informatics infrastructure required to support the interoperability of systems and routine data exchange. An important component of the informatics infrastructure is the establishment and adoption of standards at multiple levels to support semantic interoperability. Semantic interoperability means that data are exchanged without a loss of context or meaning. Semantic interoperability is only possible when all organizations adopt the same standards for quality measurement and reporting and use those standards in their electronic systems. The ultimate goal is to capture data for quality reporting in the context of existing documentation workflows. This requires that standard clinical content is adopted and used in electronic systems, standard taxonomies or vocabularies are used to encode that content, and messaging standards are used to transfer information from one healthcare organization to another.

TABLE 20-1 Accreditation and Policy Initiatives Focusing on Improving Quality of Care and Patient Safety through Health Information Technology (Health IT)

INITIATIVE

DESCRIPTION

The Joint Commission National Patient Safety Goals (NSPG)17

Program established in 2002 by The Joint Commission to assist accredited organizations in addressing patient safety concerns.17

Examples of 2012 NPSG facilitated by health IT include the following:

• Reduce the likelihood of patient harm associated with the use of anticoagulant therapy (NPSG.03.05.01). (1) EMR-based clinical decision support to alert and manage potential food and drug interactions, (2) use of “smart pumps” to provide consistent and accurate dosing, and (3) use of MedlinePlus to educate patients about the importance of follow-up monitoring, compliance, drug–food interactions, and the potential for adverse drug reactions and interactions.

• Maintain and communicate accurate patient medication information (NPSG.03.06.01). (1) Use of an electronic medication reconciliation system to obtain information on the medications the patient is currently taking at all care transitions and (2) use of MedlinePlus to provide the patient (or family) with written information about the medications prescribed.

The Leapfrog Group18

Initiative led by healthcare purchasers designed to improve the quality, safety, and affordability of healthcare by reducing preventable medical mistakes.18

Examples of 2012 Leapfrog goals facilitated by health IT include the following:

• Prevent medication errors: Use of CPOE

• Steps to avoid harm: Use of clinical decision support in EMR decision support to prevent medical mistakes

• Reduce pressure ulcers: Electronic assessment and plan of care application to link areas of risk with tailored interventions to prevent pressure ulcers from occurring

• Reduce in-hospital injuries: Electronic assessment and plan of care application to link areas of risk with tailored interventions to prevent falls and related injury

CMS Hospital-Acquired Conditions9

In response to the Deficit Reduction Act of 2006, CMS identified a list of preventable hospital-acquired conditions for which hospitals would no longer receive additional payment.9

Examples of hospital-acquired conditions that could be prevented through use of health IT include the following:

• Pressure ulcers: Electronic assessment and plan of care application to link areas of risk with tailored interventions to prevent pressure ulcers from occurring

• Patient falls with injury: Electronic assessment and plan of care application to link areas of risk with tailored interventions to prevent falls and related injury

• Manifestations of poor glycemic control: Use of clinical decision support in EMR for postoperative insulin dosing

Pay for Performance (P4P)19

Medicare initiative designed to improve quality of care in all healthcare settings through collaboration with providers and other stakeholders, to ensure that valid reliable measures of quality determine levels of reimbursement for care provided.19

Examples of P4P measures facilitated by health IT include the following:

• Cholesterol management–LDL control <100: Patient use of self-management tools through patient portal

• HbA1c control <7.0%: Patient use of self-management tools through patient portal

• Implement drug–drug and drug–allergy interaction checks: Use of clinical decision support in EMR for automated interaction checking

Meaningful Use20

American Recovery and Reinvestment Act (ARRA) of 2009 initiative designed to provide incentives for providers and healthcare organizations to improve quality of care through Meaningful Use of EHRs.

Examples of Meaningful Use of health IT performance measures include the following:

• Use CPOE

• Use eMAR

• Provide online access to health information to patients20

National Committee for Quality Assurance (NCQA)

A nonprofit organization established in 1990 by the Robert Wood Johnson Foundation to improve the consumer's ability to evaluate health plans through voluntary public reporting.21 The Healthcare Effectiveness Data and Information Set (HEDIS) was developed and is maintained by NCQA.

Utilization Review Accreditation Commission (URAC)

An independent, nonprofit organization that aims to promote continuous improvement in the quality and efficiency of healthcare management through processes of accreditation and education.22

CMS, Centers for Medicare & Medicaid Services; CPOE, computerized provider order entry; EHR, electronic health record; eMAR, Electronic Medication Administration Record; EMR, electronic medical record; LDL, low-density lipoprotein.

To automatically track the quality of care, standard quality measures are needed to ensure that all organizations are using consistent metrics for benchmarking and that organizations are using the same types of data to populate the quality metrics. For data to be collected as a by-product of documentation, the standard quality metrics must define standard value sets (allowed values), taxonomies (standard terminologies), concept codes (codes assigned by the terminology developer), attributes (characteristics that provide context), and data structures and these same standards must also be used to encode the content in the electronic record.

TABLE 20-2 Categories and Types of Data Elements Common to High-Priority Measures and Adopted Terminologies

DATA CATEGORIES

DATA TYPES

ADOPTED VOCABULARY STANDARDS TO SUPPORT MEANINGFUL USE STAGE 1/STAGE 2

Adverse drug event

Allergy

Intolerance

NA/Unique Ingredient Identifier (UNII)

Communication

Provider–provider

Provider–patient

Diagnostic study

Order

Result

ICD-9 CM, CPT 4/ICD-10 CM, CPT 4

Diagnosis

Outpatient (billing)

Outpatient (problem list)

Inpatient

ICD-9 CM, SNOMED CT/ICD-10 CM, SNOMED CT

History

Behavioral (smoking)

Birth

Care classification

Death

Enrollment trial

Ethnicity/race

Language

Payment source

Primary care provider

Sex

Symptoms

Laboratory

Order

Result

LOINC

Location

Source/current/target

Transfer type

Medication

Discontinue order

Inpatient administered

Inpatient ordered

Outpatient duration

Outpatient order

Outpatient filled

RxNorm

Opt out

Other reason

Physical exam

Vitals

Procedure

Inpatient end

Inpatient start

Order

Outpatient

Past history

Consult results

ICD-9 CM, CPT 4/ICD-10 CM, CPT 4

Adapted with permission from American Medical Informatics Association and based on Dykes PC, Caligtan C, Novack A, et al. Development of automated quality reporting: aligning local efforts with national standards. AMIA Annu Symp Proc. 2010; 2010:187-191.

CPT, Current Procedural Terminology; ICD, International Classification of Diseases; LOINC, Logical Observation Identifier Names and Codes; SNOMED, Systematized Nomenclature of Medicine.

Currently, work aimed at mapping (linking) specific quality concepts to recommended terminologies is ongoing for 16 Center for Medicare & Medicaid Services (CMS) and The Joint Commission (TJC) inpatient measures in the domains of Stroke, Venous Thromboembolism, and Emergency Department as part of a quality measure retooling effort. The resulting work is published in the Healthcare Information Technology Standards Panel (HITSP) Quality Measures Technical Note (version 1.2), providing a detailed use case for applying existing standards to specify measures electronically.

Defined standards to support Meaningful Use are included in Table 20-2.23 As mentioned above, representation of the complete data element set (e.g., the entire question-answer pair) by standardized terminologies and codes within an EHR system is required for full automation of quality reporting. Adoption and use of the same standards by all organizations are required for quality reporting and benchmarking beyond the organizational level. Many of these standards are included in the Stage 2 Meaningful Use initiative that aims to provide incentives for their use in EHR systems and subsequently to provide the informatics infrastructure needed across the U.S. to collect and report quality data as a by-product of documentation.

Evaluating Quality and Patient Safety

The foundation for the approach used to evaluate quality and patient safety in healthcare organizations in the U.S. is based on the work of Avedis Donabedian, who developed a framework for measuring quality based on organizational structure, processes, and their linkages to patient outcomes.24 Donabedian's model provides the underpinnings for the framework for patient safety and quality research design (PSQRD) (Fig. 20-1).11

•Structure: The setting and its attributes (e.g., the physical structure of buildings, staffing ratios, the equipment available within an organization, and the budget to support care provision) are all part of its structure. Exogenous factors that may not be completely under the local control of a hospital or healthcare organization are also part of the structure. Examples include TJC accreditation standards, Meaningful Use requirements, and other accreditation, licensing, and payment directives.

•Process: The managerial (human resource policies, training practices, management practices) and clinical (use of evidence-based interventions to promote quality and safety, communication practices at the bedside) processes in place to support the provision of care are all included under the process component. Managerial processes have a latent effect on outcomes, as they influence communication and care practices that aim to affect patient care

C:\Users\chanda\AppData\Local\Temp\978-0-323-10095-3_0080.jpg

FIG 20-1 A framework for patient safety and quality research design. EHR, Electronic health record.

(Modified from Brown C, Hofer T, Johal A, et al. An epistemology of patient safety research: a framework for study design and interpretation. Part 1. Conceptualising and developing interventions. Qual Saf Health Care. 2008;17[3]:160.)

delivery. Interventions aimed at clinical processes may have an immediate effect on patient outcomes.

•Outcomes: The outcomes or end result of the structures and processes in place. These may include both clinical outcomes (e.g., improved health status, decreased mortality) and throughput (i.e., the number of patients treated). The outcomes are often the aim of health IT and other interventions implemented to improve patient status.

Conceptual Framework for Patient Safety and Quality

The framework for PSQRD builds on Donabedian's structure-process-outcome model to support evaluation of an intervention from the preimplementation testing phase through implementation and evaluation.11 In the case of a health IT intervention, the expanded framework supports understanding where the health IT intervention is most likely to have an effect, within the organizational causal chain of quality and safety events (see Fig. 20-1). The PSQRD framework provides a means to categorize interventions according to areas of the causal chain targeted (e.g., the structure, the management or clinical processes, and the patient outcomes or throughput targeted by the intervention or that drive adoption and use of the intervention in clinical practice).

The PSQRD framework is pertinent to evaluating the effect of health IT interventions on quality and patient safety, as it provides a means to better explain why a health IT intervention was successful (or not). There are many reasons why health IT interventions are not adopted in practice.25,26 Health IT tools not widely adopted and used will have a limited effect on patient outcomes. In the sections below we use the PSQRD framework to first evaluate health IT interventions designed to improve quality and patient safety. We then use it to make some recommendations to improve the implementation and evaluation of health IT interventions aimed at enhancing quality and patient safety.

Within the PSQRD framework, quality and safety issues are not mutually exclusive entities but exist on a “vector of egregiousness” (Fig. 20-2). Quality is at one end of the vector, representing frequent events with lower levels of immediacy. Causality and patient safety are at the opposite end of the vector, encompassing more immediate events with high levels of causality. Errors or events that do not fall on or close to the vector are included within the quality–safety continuum and classified as having components of both. The PSQRD framework defines causality as “the confidence with which a bad outcome, if it occurs, can be attributed to an error” and defines immediacy as “immediate or rapid.”11(pp158-159) For example, there is good evidence on the population level that screening mammography decreases breast cancer mortality in women.27 When an unscreened woman develops end-stage breast cancer, the adverse outcome was preventable. However, the causal link is low and the time over which breast cancer occurs is typically not immediate or rapid.

Using this model as a framework, a hospital-acquired infection from poor handwashing practices has a high degree of causality and a low to moderate degree of immediacy. Patient falls and pressure ulcers are located midway up the vector of egregiousness with lack of tailored interventions to mitigate risk, placing patients at risk for injury with moderate degrees of causality and immediacy. Serious medication errors are higher on the vector, as they may occur due to

C:\Users\chanda\AppData\Local\Temp\978-0-323-10095-3_0081.jpg

FIG 20-2 The quality–safety continuum.

(Modified from Brown C, Hofer T, Johal A, et al. An epistemology of patient safety research: a framework for study design and interpretation. Part 1. Conceptualising and developing interventions. Qual Saf Health Care. 2008;17(3):159.)

inadequate adherence to the “5 rights” for medication safety (right patient, right time, right drug, right dose, and right route). Medication errors are the most common adverse event (an unintended and unfavorable effect of medical care or treatment) in hospital settings and are largely preventable through use of health IT systems with decision support at the bedside (i.e., closed loop bar-coding, medication administration, and smart pumps).28 Medication errors are high on the vector of egregiousness toward safety because these types of errors are preventable through adherence to the “5 rights” and, when they occur, have the potential to cause immediate and significant patient harm.

Medication Safety

Health IT systems hold promise for improving the quality and safety of care, particularly in the area of medication safety. To date, computerized provider order entry (CPOE) and clinical decision support (CDS) systems have been used successfully in clinical practice to reduce errors during the process of ordering medications.7,29 In addition, Bar Code Medication Administration (BCMA) and Electronic Medication Administration Record (eMAR) systems have been adopted in a number of hospitals to improve patient safety and streamline clinical workflow, focusing in particular on improving administration processes at the point of care.30–32 These systems leverage bar-coding applications, with bar code labels placed on patient wristbands and on medications. The systems can ensure adherence to the “5 rights” to reduce medication errors and to document administration of drugs in real time. BCMA and eMAR systems are effective when implemented and used properly.33–35 For example, after BCMA system implementation, the scanning compliance rate is often suboptimal for scanning both drugs and patient IDs.36,37 One study found that compliance with scanning medications was only 55.3%.36 Another study revealed that nurses may bypass scanning processes and create workarounds to reduce workloads or prevent delay of medication administrations.35 Workarounds are defined as any use of an operating system outside its designed protocol.35 This problem occurs most often in the system implementation stage and may create potential new paths to medical errors or other negative effects, such as inefficiency.34,38

The IOM reports, the TJC Standards, and the National Patient Safety Goals (NPSG) represent structural incentives for use of health IT to improve medication safety.8,17 TJC is an international nonprofit organization that aims to inspire healthcare organizations to excel in providing safe and effective care of the highest quality and value. The NPSG and TJC Standards relevant to medication administrations (Table 20-3) are requirements for institutions in the U.S. and other countries that seek TJC accreditation.

Published studies suggest that successful implementation of BCMA and eMAR systems that improve patient safety depends on several factors, including the following:

1.A positive workplace culture (leadership, teamwork, and clinician ownership)

2.Training and support

TABLE 20-3 The Joint Commission Standards and National Patient Safety Goals

REQUIREMENTS

ELEMENTS OF PERFORMANCE

National Patient Safety Goals (NPSG): NPSG.01.01.01

Use at least two patient identifiers when providing care, treatment, and services

Use at least two patient identifiers when administering medications, blood, or blood components; when collecting blood samples and other specimens for clinical testing; and when providing treatments or procedures. The patient's room number or physical location is not used as an identifier.

NPSG.03.04.01

Label all medications, medication containers, and other solutions on and off the sterile field in perioperative and other procedural settings*

All medications and solutions both on and off the sterile field and their labels are reviewed by entering and exiting staff responsible for the management of medications.

Medication Management: MM.06.01.01

The hospital safely administers medications

Before administration, the individual administering the medication does the following:

•Verifies that the medication selected matches the medication order and product label

•Verifies that the medication has not expired

•Verifies that no contraindications exist

•Verifies that the medication is being administered at the proper time, in the prescribed dose, and by the correct route

Data from The Joint Commission (TJC). Facts about Joint Commission accreditation standards. TJC. http://www.jointcommission.org/assets/1/18/Standards1.PDF. 2011. Accessed April 12, 2012; TJC. Facts about the National Patient Safety Goals. TJC. http://www.jointcommission.org/assets/1/18/National_Patient_Safety_Goals_6_3_111.PDF. 2012. Accessed April 12, 2012.

*Medication containers include syringes, medicine cups, and basins.

3.Acceptance of the major impact of work practices by all team staff

4.A usable system with adequate decision support30–32

Systems implemented using these principles can meet TJC Standards and NPSG and are likely to improve patient safety.

Chronic Illness Screening and Management

Health IT has demonstrated potential in improving the quality of care with regard to chronic illness screening and management.39–46 As noted in Figure 20-2, health IT interventions that target chronic illness screening and management fall on the quality end of the vector of egregiousness, with lower levels of causality and immediacy.

Examples of structural incentives for use of health IT to improve clinical processes include practice guidelines such as the U.S. Preventive Services Task Force (USPSTF) recommendations on screening for breast cancer47 and depression,48 pay for performance measures,49 and CMS core measures.50 Analysis of these types of external programs on process improvement and patients' outcomes suggests that the long-term effect is limited and that tailoring quality improvement programs (e.g., the management and clinical processes) based on organization-specific situations is recommended.49

One strategy that is successful in improving quality outcomes is the use of health IT interventions that target patients to improve access to treatment,44 adherence with medication, diet and exercise regimens,42 adherence with recommended screening guidelines,41 and engagement in symptom management.40 Involvement of patients using health IT is a successful strategy for improving adherence with screening and best practices management of chronic illness and improved quality outcomes.

Nursing Sensitive Quality Outcomes: Patient Falls and Pressure Ulcers

Health IT interventions are also effective for improving quality of care and patient safety related to fall and pressure ulcer prevention.51–55 The patient characteristics and factors related to risks for falls and pressure ulcers are multifaceted. For example, the patient's risks increase or decrease when skin surveillance is inadequate or when fall prevention interventions are not ordered and taught to the patient and family. As noted previously and in Figure 20-2, patient falls and pressure ulcers are located midway on the vector of egregiousness between quality and safety, with moderate levels of causality (failure to consistently implement tailored interventions) and immediacy (time to patient fall or development of pressure ulcer). An important structural component present for hospitals in the U.S. was the Deficit Reduction Act of 2006, through which CMS identified a list of preventable, hospital-acquired conditions for which hospitals would no longer receive additional payment.9 The regulations regarding nonpayment for hospital-acquired conditions included both patient falls and pressure ulcers.9 The regulations provided an external directive (e.g., structure) that created a sense of urgency within organizations to eliminate preventable patient falls and pressure ulcers.

Management processes including an administrative focus on fall and pressure ulcer prevention are key factors in improving the quality of care related to fall and pressure ulcer prevention. At the organizational level interventions such as training, the use of health IT systems for decision support, and involvement of peer champions in identifying and implementing interventions that are both feasible and effective, provide an environment conducive to fall and pressure ulcer prevention.53,55 The use of clinical experts to improve the knowledge base of nurses and other healthcare providers51 and the use of a peer champion model51,53,55 support fidelity of both management processes (e.g., communication, importance of behavior change, advocacy for fall and pressure ulcer prevention initiatives) and clinical processes (e.g., end-user training, support, modeling the intervention set on patient care units).

When implementing complex practice change, as required for fall and pressure ulcer prevention, health IT is often a single component of a multifaceted performance improvement intervention and leadership support for the practice change is essential. Health IT interventions are most effective when both clinical and management processes are addressed and where organizational leadership demonstrates strong support for improvement strategies.51,53,55

Success Factors and Lessons Learned

The effects of health IT interventions aimed at improving quality and patient safety using the PSQRD framework have been evaluated to identify key success factors and to provide a foundation for making recommendations for health IT implementation and future research. The PSQRD framework is useful for exploring the relationships between the organization's structural forces (e.g., setting attributes, exogenous factors) that support organizational change, including adoption and use of health IT as a tool to improve clinical processes and patient outcomes. External accreditation or regulatory requirements provide structural incentives for the changes in clinical processes that are supported by health IT interventions. The PSQRD framework expands the process component of the Donabedian model to include both management and clinical processes. The expanded process components underscore the relationship between managerial interventions, improved clinical processes, and patient outcomes. Management interventions are effective in maximizing stakeholder support for a project. An example of a management intervention is the appointment of a task force to address poor adherence with best practice guidelines. The task force is charged by management with identifying and overcoming barriers to best practice. These types of interventions improve overall adherence to practice changes and improve fidelity with health IT interventions. In addition, the PSQRD framework includes a focus on intervening variables that improve staff commitment to process changes such as incentive payments and morale.56 Additional examples of management strategies to improve fidelity with the intervention include the use of peer champion support networks51,57,58 and end-user education.55,56,58