Key points

Introduction

Attention to quality, safety, and value in health care has undergone significant evolution over the past 25 years. Traditionally, patients, payers, and hospitals have approached the relationship from a relatively siloed perspective. More recently, efforts have been made to reframe the conversation toward a patient-centric, complex adaptive system. The adoption of the Affordable Care Act has served to accelerate this trend, including focus on patient safety, hospital-acquired conditions (HACs), and outcomes. These efforts have caused institutions to reevaluate what, when, and how they use metrics and analytics in order to improve health care delivery. Increasingly, leaders in health care are becoming fluent in quality management science, often referencing other industries for inspiration/guidance in the health care space. Many recognize the Donabedian framework of structure, process, and outcome, in conjunction with various process improvement tools (plan, do, study, act [PDSA], Lean) to drive organizational change efforts.

Externally, institutions face an evolving competitive landscape, with an increased appetite from patients, families, and insurers demanding data transparency on institutional performance. Health systems, payers, and patients find themselves increasingly aligned toward a goal of high-value (defined as outcomes/cost) health care. In addition to competitive market forces, payment incentives by the Centers for Medicare and Medicaid Services in the area of electronic health records (EHRs) and evolving regulatory standards from The Joint Commission (TJC) have provided a strong impetus for health systems to accelerate learning cultures and best-practice adoption.

This article begins with a brief review of the history of measurement, standards, and benchmarking, with a particular focus on pediatric-specific work led by the Agency on Healthcare Research and Quality (AHRQ). The author then discusses the success of the Ohio Collaborative (now known as Solutions for Patient Safety [SPS]), with remarks on critical success factors, including infrastructure in data/analytics and institutional cultural preparedness to ensure the highest yield from a benchmarking exercise.

Finally, the author uses the Children’s Hospital of Pittsburgh of University of Pittsburgh Medical Center’s (UPMC) (CHP) experience with SPS as a case study in peer-peer benchmarking, beginning with the history of the collaborative and the CHP’s decision to participate. Furthermore, the author discusses the initial process of engagement and the effect of participation on the CHP’s quality and safety process improvement efforts, people, and institutional culture.

Introduction

Attention to quality, safety, and value in health care has undergone significant evolution over the past 25 years. Traditionally, patients, payers, and hospitals have approached the relationship from a relatively siloed perspective. More recently, efforts have been made to reframe the conversation toward a patient-centric, complex adaptive system. The adoption of the Affordable Care Act has served to accelerate this trend, including focus on patient safety, hospital-acquired conditions (HACs), and outcomes. These efforts have caused institutions to reevaluate what, when, and how they use metrics and analytics in order to improve health care delivery. Increasingly, leaders in health care are becoming fluent in quality management science, often referencing other industries for inspiration/guidance in the health care space. Many recognize the Donabedian framework of structure, process, and outcome, in conjunction with various process improvement tools (plan, do, study, act [PDSA], Lean) to drive organizational change efforts.

Externally, institutions face an evolving competitive landscape, with an increased appetite from patients, families, and insurers demanding data transparency on institutional performance. Health systems, payers, and patients find themselves increasingly aligned toward a goal of high-value (defined as outcomes/cost) health care. In addition to competitive market forces, payment incentives by the Centers for Medicare and Medicaid Services in the area of electronic health records (EHRs) and evolving regulatory standards from The Joint Commission (TJC) have provided a strong impetus for health systems to accelerate learning cultures and best-practice adoption.

This article begins with a brief review of the history of measurement, standards, and benchmarking, with a particular focus on pediatric-specific work led by the Agency on Healthcare Research and Quality (AHRQ). The author then discusses the success of the Ohio Collaborative (now known as Solutions for Patient Safety [SPS]), with remarks on critical success factors, including infrastructure in data/analytics and institutional cultural preparedness to ensure the highest yield from a benchmarking exercise.

Finally, the author uses the Children’s Hospital of Pittsburgh of University of Pittsburgh Medical Center’s (UPMC) (CHP) experience with SPS as a case study in peer-peer benchmarking, beginning with the history of the collaborative and the CHP’s decision to participate. Furthermore, the author discusses the initial process of engagement and the effect of participation on the CHP’s quality and safety process improvement efforts, people, and institutional culture.

History of measurement, standards, and benchmarking in pediatrics

For more than 20 years, the AHRQ of the US Department of Health and Human Services has been leading the charge for health care quality improvement and patient safety efforts. Beginning in the late 1990s, AHRQ-funded projects began to specifically focus on pediatric patients and processes related to patient safety. Length of stay, hospital mortality, and increased hospital expenditures were the variables examined relative to their association to patient safety events.

In following suit to their adult counterparts, the development of quality indicators raises unique challenges in pediatric institutions. The AHRQ recognizes such considerations:

These challenges include the need to carefully define indicators using administrative data, establish validity and reliability, detect bias and design appropriate risk adjustment, and overcome challenges of implementation and use. However, the special population of children invokes additional, special challenges. Four factors—differential epidemiology of child healthcare relative to adult healthcare, dependency, demographics, and development—can pervade all aspects of children’s healthcare; simply applying adult indicators to younger age ranges is insufficient.

Background on Pediatric Quality Indicators is provided in Box 1 .

From the AHRQ, In conjunction with the AHRQ, the Child Health Corporatio of America (CHCA), the National Perinatal Information Center, and TJC serve to identify, define, and validate Pediatric Quality Indicators derived from hospital administrative data. The current Pediatric Quality Indicators are noted in Box 2 .

The AHRQ’s work on pediatric-specific quality indicators (PQIs) served to provide a platform for institutions to benchmark against a valid, national standard. Beginning in 2012, the AHRQ began to provide benchmark data tables, enabling easier comparisons of nationwide comparative rates for the PQIs; data presented include observed rate and both numerator and denominator data for each indicator overall and stratified by sex, age group, and insurance status. An example of the overview benchmark data table for March 2015 is provided in Table 1 , with greater detail in provider-level data table for neonatal iatrogenic pneumothorax in Table 2 .

Table 1

March 2015 AHRQ benchmark data

Indicator	Label	Numerator	Denominator	Observed Rate per 1000 (=Observed Rate × 1000)
	Provider-Level Indicators
NQI #1	Neonatal iatrogenic pneumothorax rate	33	186,270	0.18
NQI #2	Neonatal mortality rate	6851	3,041,508	2.25
NQI #3	Neonatal blood stream infection rate	1596	63,379	25.18
PDI #1	Accidental puncture or laceration rate	1067	2,297,161	0.46
PDI #2	Pressure ulcer rate	62	226,690	0.27
PDI #3	Retained surgical item or unretrieved device fragment count	29	—	—
PDI #5	Iatrogenic pneumothorax rate	234	2,071,756	0.11
PDI #6	RACHS-1 pediatric heart surgery mortality rate	447	14,168	31.55
PDI #7	RACHS-1 pediatric heart surgery volume	16,857	—	—
PDI #8	Perioperative hemorrhage or hematoma rate	408	78,531	5.2
PDI #9	Postoperative respiratory failure rate	877	60,392	14.52
PDI #10	Postoperative sepsis rate	938	65,478	14.33
PDI #11	Postoperative wound dehiscence rate	48	42,923	1.12
PDI #12	Central venous catheter–related blood stream infection rate	1387	1,813,113	0.76
PDI #13	Transfusion reaction count	—	—	—
PSI #17	Birth trauma rate: injury to neonate	5636	2,974,363	1.89

Only gold members can continue reading. Log In or Register to continue

Share this:

• X
• Facebook

Related

Related posts:

1. Quality of Care and Information Technology
2. The Intersection of Safety, Quality, and Informatics: Solving Problems in Pediatrics
3. Advanced Technology in Pediatric Intensive Care Units
4. ABCs of Safety and Quality for the Pediatric Resident and Fellow

Stay updated, free articles. Join our Telegram channel

Join