Consumer Quality Index

1. Abstract

The Consumer Quality Index (CQI, or CQ-index) represents a standardized, scientifically rigorous measurement system developed in the Netherlands to systematically assess, analyze, and report patient experiences across diverse healthcare sectors. Established by the Netherlands Institute for Health Services Research (Nivel) in collaboration with academic medical centers and healthcare stakeholders, the CQI harmonizes methodologies derived from the American Consumer Assessment of Healthcare Providers and Systems (CAHPS) and the Dutch QUality Of care Through the patient’s Eyes (QUOTE) instruments. Operating as the premier standard for Patient-Reported Experience Measures (PREMs), the CQI methodology captures both the empirical occurrence of specific provider behaviors and the relative normative importance patients assign to distinct care dimensions.

The instrument family encompasses modular surveys tailored to specific healthcare contexts—including inpatient somatic care, ambulatory and outpatient specialty clinics, primary general practice, mental healthcare (GGZ), nursing homes, and health insurance providers. Core dimensions evaluated across modular variants comprise doctor-patient and nurse-patient communication, interpersonal conduct (courtesy, dignity, and respect), provision of medical information, shared decision-making, care coordination, accessibility, waiting times, and global ratings of care. Item counts range from compact short-form sets (typically 20 to 35 items) to comprehensive setting-specific inventories exceeding 80 items. Response formats predominantly utilize objective frequency scales (e.g., “Never,” “Sometimes,” “Usually,” “Always”) supplemented by categorical response trees and 0-to-10 global numerical ratings.

Extensive psychometric evaluations establish robust measurement properties across administrative environments. Confirmatory factor analyses consistently substantiate distinct multidimensional factor structures aligning with designated care domains, demonstrating comparative fit index (CFI) values typically exceeding .95 and root mean square error of approximation (RMSEA) values below .06. Scale reliability across subdimensions yields Cronbach’s alpha coefficients ranging from .70 to .92, with hospital- and provider-level reliability coefficients exceeding .70 when aggregated over adequate sample sizes per cluster. Construct, convergent, and discriminant validities are firmly supported through systematic associations with institutional quality indicators, patient safety records, and validated health outcome metrics.

2. Keywords

Consumer Quality Index, CQI, Patient Reported Experience Measures, PREMs, Healthcare Quality, CAHPS, QUOTE, Psychometrics, Patient-Centered Care, Healthcare Evaluation, Quality Indicators, Nivel

3. Authors

The Consumer Quality Index was conceptualized, developed, and standardized under the auspices of the Netherlands Institute for Health Services Research (Nivel) in Utrecht, the Netherlands, alongside academic consortium partners including the Department of Public Health at the Academic Medical Center / University of Amsterdam (AMC-UvA), the Center for Consumer Experience in Health Care (Centrum Klantervaring Zorg, CKZ), and the Dutch Healthcare Inspectorate (Inspectie voor de Gezondheidszorg en Jeugd, IGJ).

Key foundational researchers and psychometric architects of the CQ-index methodology include:

• Prof. Dr. Diana M. J. Delnoij — Professor of Governance and Healthcare Quality, Tranzo, Tilburg University; former Program Head of Healthcare System and Quality Assessment at Nivel.
• Dr. Dolf de Boer — Senior Researcher in Patient Experiences and Healthcare Quality, Netherlands Institute for Health Services Research (Nivel).
• Prof. Dr. Roland D. Friele — Professor of Health Services Research, Tilburg University; Deputy Director at Nivel.
• Prof. Dr. Jany Rademakers — Professor of Patient-Centered Care, Maastricht University; former Head of Research at Nivel.
• Prof. Dr. Jouke van der Zee — Emeritus Professor of Primary Care Research, Maastricht University; former Director of Nivel.

Institutional Contact: Netherlands Institute for Health Services Research (Nivel), Otterstraat 118-124, 3513 CR Utrecht, P.O. Box 1568, 3500 BN Utrecht, The Netherlands. Website: www.nivel.nl.

4. Purpose

The overarching purpose of the Consumer Quality Index (CQI) is to supply a standardized, scientifically grounded, and methodologically transparent measurement infrastructure for capturing, analyzing, and benchmarking patient-reported experiences across the healthcare system. Prior to the inception of the CQI, patient satisfaction measurement was hindered by severe methodological limitations, including the widespread deployment of non-validated, ad hoc questionnaires, ceiling effects stemming from subjective satisfaction metrics, and an absence of standardized analytical algorithms capable of adjusting for confounding patient characteristics (case-mix adjustment). The CQI was engineered to resolve these psychometric and systemic deficits by prioritizing objective, actionable behavioral experiences over subjective, affective ratings of overall satisfaction.

In clinical practice and institutional quality management, the CQI serves several complementary functions:

• Internal Quality Improvement: Healthcare organizations utilize granular CQI domain scores to pinpoint operational bottlenecks, interpersonal communication deficits among clinical staff, breakdowns in shared decision-making, and lapses in discharge management. By evaluating empirical behavioral frequencies (e.g., how often clinicians explained medication side effects in understandable language), quality managers obtain actionable data points for targeted clinical interventions.
• External Accountability and Supervision: Regulatory bodies, such as healthcare inspectorates and accreditation organizations, employ standardized CQI performance scores as macro-level quality indicators to monitor system-wide compliance with patient-centered standards and to identify institutional outliers requiring regulatory scrutiny.
• Purchasing and Selective Contracting: In regulated healthcare markets—such as the Dutch managed competition system established under the Health Insurance Act (Zorgverzekeringswet)—health insurance companies use risk-adjusted CQI benchmarks to inform value-based contracting strategies, incentivizing healthcare organizations that demonstrate superior patient-centered performance.
• Public Transparency and Consumer Choice: CQI data supply public healthcare comparison websites with comparative, risk-adjusted performance indices, empowering consumers, patients, and patient advocacy organizations to make evidence-informed selections regarding providers, hospitals, and specialized therapeutic centers.
• Health Services and Psychometric Research: Academically, the standardized architecture of the CQI permits longitudinal, cross-sectional, and cross-sectoral health services research, allowing investigators to track longitudinal trajectories in quality of care, isolate provider-level variance from patient-level variance using multilevel modeling, and examine the structural determinants of therapeutic alliance.

5. Psychological Construct

The primary target construct measured by the Consumer Quality Index is Patient Experience—defined within modern psychometric and health service paradigms as the observed occurrence of interactions, behaviors, and environmental attributes encountered by an individual within the therapeutic delivery context, evaluated against normative patient priorities. The CQI explicitly differentiates between subjective satisfaction (a personality- and expectation-laden affective judgment) and objective experience (factual reports of whether specific professional behaviors and structural processes occurred).

To capture this broad construct, the CQI operationalizes several correlated, distinct subdimensions across its modular variants:

5.1. Conduct and Interpersonal Communication of Physicians

This subscale assesses the relational dynamics and verbal/non-verbal communication patterns displayed by medical specialists and general practitioners. It measures empirical occurrences such as whether the physician listened attentively without interruption, treated the patient with dignity and respect, allocated sufficient time for consultation, and demonstrated genuine empathy toward patient concerns. Unlike subjective questions (“Were you pleased with the doctor?”), the construct measures behavioral consistency (e.g., “Did the doctor explain things in a way that was easy to understand?”).

5.2. Conduct and Communication of Nursing Staff

Mirroring the medical communication dimension within inpatient and ambulatory care settings, this construct isolates the specific caregiving and interpersonal behaviors of registered nurses, nurse practitioners, and nursing aides. The dimension captures attentiveness, promptness in responding to call alarms, clarity in daily clinical briefings, courtesy, and the degree to which nursing personnel foster a secure, compassionate clinical atmosphere.

5.3. Information Provision and Health Literacy Facilitation

This dimension operationalizes the structural transfer of critical medical and procedural knowledge from healthcare providers to the patient and their designated caregivers. It evaluates whether patients received intelligible explanations regarding diagnosis, prognosis, therapeutic alternatives, planned diagnostic examinations, and potential medication side effects. A core theoretical element of this construct is the alignment of institutional communication with the patient’s level of health literacy.

5.4. Shared Decision-Making and Autonomy

Anchored in contemporary psychological models of personal autonomy and patient empowerment, this subscale quantifies the extent to which clinical professionals actively engaged the patient in decisions concerning therapeutic pathways. Key observed behaviors include whether providers inquired about patient preferences, weighed personal lifestyle impacts of interventions, presented multiple treatment trajectories, and respected patient agency in clinical choices.

5.5. Care Coordination and Inter-Professional Continuity

This structural-relational dimension assesses systemic continuity and operational handoffs between distinct clinical actors. It measures whether healthcare professionals appeared well-informed regarding the patient’s medical history and current test results, the degree of institutional coordination between nursing teams and physicians, and the seamless transition of care from secondary hospital environments back to primary care practitioners or home care services.

5.6. Accessibility and Waiting Times

Reflecting structural and logistical dimensions of healthcare access, this subscale evaluates temporal barriers to care. Specific indicators include the ease of reaching clinical practices by telephone, punctuality of appointment schedules, duration spent in waiting rooms, and the latency between initial general practitioner referral and specialized clinical consultation.

5.7. Environmental Quality and Physical Safety

In inpatient and institutional care variants (such as nursing homes and rehabilitation units), this dimension measures the physical infrastructure, room hygiene, privacy protections during physical examinations and confidential conversations, nutritional adequacy, and the perceived physical and psychological security of the therapeutic setting.

5.8. Global Evaluative Ratings

Complementing specific behavioral reports, CQI instruments incorporate standardized macro-level global assessments. These capture overarching cognitive evaluations of the hospital, clinic, or provider on a 0-to-10 numerical scale, alongside behavioral intentions concerning whether the respondent would actively recommend the healthcare provider to family and acquaintances.

6. Theoretical Framework

The Consumer Quality Index is grounded in a theoretical synthesis of cognitive psychometrics, health services research, and quality-of-care frameworks. Specifically, it amalgamates the theoretical underpinnings of two pioneering paradigms: the American Consumer Assessment of Healthcare Providers and Systems (CAHPS) model and the Dutch QUality Of care Through the patient’s Eyes (QUOTE) methodology.

6.1. The CAHPS Methodological Lineage: Behavioral Frequency Paradigm

The fundamental measurement philosophy of CAHPS—originally developed by the Agency for Healthcare Research and Quality (AHRQ)—asserts that patient assessments must minimize subjective evaluative bias by asking respondents to report on concrete facts and behavioral frequencies rather than broad evaluative ratings. Classical satisfaction instruments are characterized by severe left-skewness, ceiling effects, and confounding by individual personality traits, prior expectations, and demographic characteristics (such as age, educational attainment, and self-rated health). In contrast, the CAHPS paradigm posits that asking whether a clinician “always,” “usually,” “sometimes,” or “never” performed a specific action yields reliable, valid, and actionable data that directly reflect clinical performance.

6.2. The QUOTE Methodological Lineage: The Importance-Performance Framework

While CAHPS focuses on performance reporting, the QUOTE methodology developed by Sixma, Kerssens, and colleagues at Nivel introduces a conceptual dual-axis model: Quality = Performance × Importance. The theoretical premise holds that high healthcare quality cannot be determined solely through provider performance; it must be weighted by the subjective importance that patients attribute to specific aspects of care. For instance, while punctuality and interpersonal warmth may both exhibit moderate institutional performance, patients with chronic conditions may consider interpersonal respect significantly more critical than administrative timeliness. QUOTE operationalizes this by administering paired scales:

• Importance Scales: Asking patients to evaluate how critical specific quality criteria are (e.g., from “Not important” to “Extremely important”).
• Performance / Experience Scales: Asking whether providers fulfilled those specific criteria in practice.

The CQI incorporates this dual theoretical legacy. During the development and psychometric refinement of each CQI modular variant, comprehensive importance studies are executed alongside experience studies. This dual-axis calibration enables psychometricians to calculate Quality Impact Indices, mathematically prioritizing quality improvement initiatives that address issues of both low institutional performance and high consumer importance.

6.3. Donabedian’s Structure-Process-Outcome Triad

The CQI aligns directly with Avedis Donabedian’s classical tripartite model of healthcare quality. Donabedian categorized quality into Structure (facilities, staffing, equipment), Process (interventions, communication, diagnostics, care delivery), and Outcome (clinical recovery, functional status, satisfaction). The CQI operates predominantly within the Process domain. Because patients generally lack specialized clinical training to assess technical surgical precision or pharmacological efficacy, their expertise resides in evaluating interpersonal, informational, and organizational processes. The CQI conceptualizes optimal healthcare processes as inherently relational, emphasizing patient dignity, transparency, and cooperative communication as indispensable components of medical quality.

7. Validity

The validity of the Consumer Quality Index has been empirically evaluated across multiple healthcare environments, yielding robust psychometric evidence across diverse validation domains.

7.1. Content and Face Validity

Content validity of each CQI instrument is established through standardized qualitative and quantitative protocols. Instrument construction follows a multi-stage stakeholder consensus procedure: comprehensive literature reviews, focus groups with heterogeneous patient cohorts, consultation with clinical experts, and cognitive walkthrough interviews (think-aloud protocols) with patients spanning diverse educational and health-literacy strata. These cognitive interviews ensure that questionnaire items demonstrate semantic clarity, cultural equivalence, and conceptual alignment with genuine patient experiences, effectively preventing construct underrepresentation.

7.2. Construct and Structural Validity

Construct validity is substantiated through rigorous structural analyses. Confirmatory factor analysis (CFA) across numerous validation studies confirms that the hypothesized multidimensional constructs (e.g., communication, information provision, conduct, coordination) are empirically distinguishable yet positively intercorrelated dimensions of patient experience. Fit indices across peer-reviewed evaluations consistently meet standard psychometric thresholds (Comparative Fit Index [CFI] > .95; Tucker-Lewis Index [TLI] > .95; Root Mean Square Error of Approximation [RMSEA] < .05 to .06; Standardized Root Mean Square Residual [SRMR] < .05). Inter-factor correlations typically range between .40 and .75, demonstrating both structural coherence and meaningful empirical differentiation between subscales.

7.3. Convergent and Discriminant Validity

Convergent validity has been established by correlating CQI domain scores with validated collateral instruments. For example, CQI communication and interpersonal subscales correlate strongly (r = .65 to .82) with legacy instruments like the QUOTE-Hospital scale and the Picker Patient Experience Questionnaire (PPE-15). Discriminant validity is demonstrated by the distinct operational divergence between CQI process-experience scales and general health-status measures (e.g., the SF-36 or EQ-5D), where correlations are consistently low-to-negligible (r < .20), confirming that CQI captures procedural healthcare quality rather than subjective biological health status.

7.4. Predictive and Criterion Validity

Predictive validity is evident in the relationship between CQI scores and clinical and behavioral outcomes. Higher CQI ratings in patient communication and discharge information predict significantly higher medication adherence, fewer unplanned 30-day hospital readmissions, lower rates of formal malpractice complaints, and enhanced general self-management efficacy among chronically ill cohorts. Furthermore, CQI global rating scales display strong predictive associations with formal net promoter and recommendation behaviors (area under the ROC curve typically exceeding .85).

7.5. Discriminative Power at the Provider / Institutional Level

A critical psychometric requirement for PREMs utilized in public reporting is institutional discriminative power—the ability of an instrument to differentiate between high-performing and low-performing healthcare organizations beyond individual-level statistical noise. Multilevel (hierarchical linear) modeling demonstrates that after controlling for patient case-mix characteristics (age, education, self-rated health), the CQI detects statistically significant institutional-level variance. Intraclass correlation coefficients (ICC-1) typically range from .02 to .12, which, when aggregated over recommended sample sizes per hospital cluster (n = 150 to 300 respondents), yields provider-level reliability coefficients (ICC-2) well above the .70 benchmark required for institutional benchmarking.

8. Reliability

The Consumer Quality Index demonstrates high internal consistency and stability across varied clinical environments, diverse target groups (pediatric parents, adults, elderly populations), and delivery modes (web-based, paper-pencil, and mixed-mode surveys).

8.1. Internal Consistency

Extensive psychometric investigations conducted across Dutch hospital networks, primary care groups, and mental healthcare centers establish robust internal consistency for the primary multi-item subscales. Representative Cronbach’s alpha ($\alpha$) coefficients reported in academic literature include:

• Doctor / Medical Specialist Communication: $\alpha = .84 – .92$
• Nursing Staff Communication and Conduct: $\alpha = .81 – .89$
• Provision of Medical Information: $\alpha = .78 – .86$
• Shared Decision-Making: $\alpha = .74 – .83$
• Care Coordination and Continuity: $\alpha = .70 – .82$
• Accessibility and Administrative Flow: $\alpha = .71 – .79$
• Overall CQI Composite Index: $\alpha = .91 – .96$

Raykov’s composite reliability coefficients ($rho$) and McDonald’s omega ($\omega$) evaluations mirror these findings, confirming that internal consistency remains robust without being inflated by redundant, collinear items.

8.2. Test-Retest Reliability and Temporal Stability

Test-retest stability has been demonstrated through longitudinal follow-up evaluations among stable outpatient cohorts reassessed over a 2- to 4-week window without intervening clinical episodes. Intraclass correlation coefficients (ICC) for stable respondents range from .72 to .86 across core subscales, demonstrating that patient recall of specific procedural experiences remains coherent and reproducible over operational post-discharge intervals.

8.3. Provider-Level Reliability (ICC-2)

In healthcare quality measurement, provider-level reliability reflects the stability of a provider’s aggregate score across independent patient samples. Standard CQI sampling guidelines mandate target completed sample sizes designed to achieve an ICC-2 threshold of $ge .70$ (acceptable) or $ge .80$ (preferred for high-stakes contracting). In inpatient hospital surveys, achieving 150 to 200 completed questionnaires per facility or specialty cluster consistently secures provider-level reliability exceeding .80, allowing confident comparisons across institutional league tables.

9. Factor Analysis

The internal structural validity of the Consumer Quality Index has been rigorously established using both Exploratory Factor Analysis (EFA) during early instrument assembly and Confirmatory Factor Analysis (CFA) across multi-center validation cohorts.

9.1. Exploratory Factor Analysis (EFA)

During preliminary modular development, principal axis factoring and maximum likelihood EFA with oblique rotation (Promax or Oblimin) are applied to empirical survey cohorts. These analyses reliably extract distinct multi-item factors corresponding to hypothesized theoretical dimensions. Scree plot inspections and parallel analyses confirm eigenvalues exceeding Kaiser’s criterion (> 1.0) for dimensions representing medical communication, nursing care, information delivery, accessibility, and discharge planning. Item factor loadings systematically surpass the .50 cutoff on primary target factors, with cross-loadings remaining low (< .30), confirming clear factor purity.

9.2. Confirmatory Factor Analysis (CFA)

Subsequent large-scale validation studies implement CFA using robust weighted least squares (WLSMV) estimation—well-suited for categorical and ordinal response indicators—or maximum likelihood with robust standard errors (MLR). A representative model testing the structural validity of the CQI Inpatient Hospital module yielded the following goodness-of-fit statistics across a multi-hospital sample ($N > 12,000$):

• Chi-Square / Degrees of Freedom ($\chi^2/df$): $2.84$ ($p < .001$)
• Comparative Fit Index (CFI): $.968$
• Tucker-Lewis Index (TLI): $.962$
• Root Mean Square Error of Approximation (RMSEA): $.043$ ($90% \text{ CI } [.040, .046]$)
• Standardized Root Mean Square Residual (SRMR): $.038$

9.3. Item Factor Loadings Table

The following representative structural model illustrates standardized factor loadings for core latent dimensions derived from the standardized CQI inpatient framework:

9.4. Measurement Invariance and Case-Mix Adjustment

Multigroup CFA demonstrates strict metric and scalar measurement invariance across key demographic subgroups, including sex, age cohorts (< 65 vs. $ge$ 65 years), and educational attainment. Establishing scalar invariance is vital for the CQI system, as it guarantees that differences in observed scores between healthcare institutions reflect actual variations in care quality rather than divergent measurement function across demographic strata.

Building on these invariant measurement foundations, standard CQI analytical protocol applies Case-Mix Adjustment via multivariable regression models. Patient evaluations are adjusted for exogenous, non-quality-related factors including:

• Respondent Age (categorized into standardized strata)
• Self-Assessed Physical and Mental Health Status (evaluated on standard 5-point scales)
• Highest Level of Educational Attainment
• Ethnic / Cultural Background and Primary Language spoken at home

By partialing out variance attributable to patient case-mix, CQI reporting isolates true provider performance, enabling equitable comparisons across academic tertiary centers and local community hospitals.

10. Instrument / Measurement Tool

The Consumer Quality Index is not a singular monolithic questionnaire, but an integrated measurement system comprising disease-specific and setting-specific modular variants. Below is an overview of the core instrument specifications:

• Assessment Classification: Standardized Patient-Reported Experience Measure (PREM) System.
• Target Population: Adult patients ($ge 18$ years), older adults in long-term residential settings, and pediatric parents/guardians (via specialized pediatric and maternity modules).
• Item Inventory Length:
  • Comprehensive Modular Versions: 60 to 95 items (capturing comprehensive demographic, experience, importance, and case-mix variables).
  • Short-Form / Compact PREMs: 15 to 35 core items (optimized for continuous digital feedback and reduced survey fatigue).
• Administration Modality: Multimodal deployment, including secure web-based electronic surveys (Computer-Assisted Web Interviewing, CAWI), paper-and-pencil self-administered postal questionnaires, and integrated mixed-mode workflows (postal invitation with web login and subsequent postal reminder).
• Standardized Response Formats:
  • Frequency Scales: 4-point categorical scales: 1 = Never, 2 = Sometimes, 3 = Usually, 4 = Always.
  • Dichotomous Indicator Scales: 1 = Yes, 2 = No (often with conditional branch items: “Yes, definitely” vs. “Yes, to some extent”).
  • Importance Scales: 4-point rating scales: 1 = Not important, 2 = Somewhat important, 3 = Important, 4 = Extremely important.
  • Global Evaluative Items: 11-point continuous numerical rating scale (NRS) ranging from 0 (Very poor care) to 10 (Excellent care).
• Scoring and Transformation Algorithms:
  • Raw item scores are mapped onto standardized 1-to-4 continuous metrics or rescaled to a 0-to-100 linear transformation score for transparent public communication.
  • Domain subscale scores represent unweighted linear means of constituent items within each validated dimension, calculated exclusively for respondents completing at least 50% of the dimension’s items.
  • Hierarchical empirical Bayes estimators and multivariable ordinary least squares (OLS) regressions are computed to execute standardized case-mix adjustment, producing adjusted institutional means and standard errors for benchmarking.

11. Permissions & Fee and Test Year

The foundational development of the Consumer Quality Index system was initiated in 2006 by the Netherlands Institute for Health Services Research (Nivel) under commissioning from the Dutch Ministry of Health, Welfare and Sport (VWS) and in collaboration with health insurers, patient federations (Patiëntenfederatie Nederland), and clinical professional bodies.

Licensing and Intellectual Property Structure:

• The standard CQI guidelines, modular item repositories, and method manuals were developed within the public domain for Dutch healthcare quality improvement and research. The methodology is maintained as an open-access quality standard.
• While the foundational methodology and measurement manuals are openly accessible for non-commercial scientific research, public benchmarking deployments, national comparative evaluations, and certified commercial data collection require adherence to standardized CQI development guidelines and certified survey vendor protocols (formerly governed by CKZ / Quality Institute / Zorginstituut Nederland).
• Certified health survey research vendors licensed to collect, process, and submit national CQI data must demonstrate compliance with ISO quality protocols, standardized sampling frames, and case-mix adjustment formulas.
• Academic researchers wishing to adapt, translate, or incorporate specific CQI modules into scientific investigations can access manuals and modules through Nivel. Proper academic attribution and adherence to psychometric modular guidelines are required.

12. References

Below are primary foundational references and psychometric studies evaluating the Consumer Quality Index system:

• Arah, O. A., ten Asbroek, A. H., Delnoij, D. M., de Koning, J. S., Stam, P. J., Poll, A., Vriens, B., & Klazinga, N. S. (2006). Psychometric properties of the Dutch Consumer Quality Index (CQI) for mammography screening. BMC Health Services Research, 6, Article 140. https://doi.org/10.1186/1472-6963-6-140
• de Boer, D., Delnoij, D., & Rademakers, J. (2010). Do patient experiences on priority aspects of health care predict their global rating of quality of care? A study in five patient groups. Health Expectations, 13(3), 285–297. https://doi.org/10.1111/j.1369-7625.2010.00591.x
• Delnoij, D. M., Rademakers, J., & Groenewegen, P. P. (2010). The Dutch Consumer Quality Index: An example of stakeholder involvement in indicator development. Health Expectations, 13(4), 354–363. https://doi.org/10.1111/j.1369-7625.2010.00642.x
• Rademakers, J., Delnoij, D., & de Boer, D. (2012). Structure, process or outcome: Which contributes most to patients’ overall assessment of healthcare quality? BMJ Quality & Safety, 21(4), 326–331. https://doi.org/10.1136/bmjqs-2011-000435
• Sixma, H. J., Kerssens, J. J., Campen, C. V., & Peters, L. (1998). Quality of care from the patients’ perspective: From theoretical concept to a new measuring instrument. Health Expectations, 1(2), 82–95. https://doi.org/10.1046/j.1369-6513.1998.00004.x
• Triemstra, M., Winters, S., Kool, R. B., & Wiegers, T. A. (2010). Measuring patient experiences with quality of care in general practice: Development and psychometric properties of the Consumer Quality Index GP Care. Nivel Research Report. Utrecht: Nivel.
• van der Hoek, L. S., de Boer, D., & Rademakers, J. (2014). The Dutch Consumer Quality Index (CQI) in long-term care: Cross-sectional psychometric evaluation of instruments for residential and home care. BMC Health Services Research, 14, Article 462. https://doi.org/10.1186/1472-6963-14-462

13. Items of the Scale