Health Care Quality Measures Research Articles

622. Risk Factors for 30-Day Unplanned Readmissions in Patients Discharged with Outpatient Parenteral Antimicrobial Therapy

BackgroundOutpatient parenteral antimicrobial therapy (OPAT) programs have shown to reduce hospital readmissions; however, 20-25% of OPAT patients are readmitted. As 30-day readmissions is a healthcare quality measure, it is important to recognize predictors for readmissions in OPAT patients in an effort to minimize risk factors and optimize patient outcomes. The aim of this study was to identify modifiable and non-modifiable risk factors for 30-day unplanned readmission in patients discharged with OPAT.MethodsThis was a retrospective cohort study of patients admitted to University of Virginia (UVA) Health System between March 2019 and December 2019 who were discharged home with intravenous antimicrobials followed by the UVA OPAT program. Data collected included patient demographics, comorbidities, infection diagnosis, source control, and antimicrobial class. Variables were compared between patients with a 30-day unplanned readmission and those without a readmission. Mann-Whitney U, Pearson chi-squared, and Fisher’s exact tests were utilized, as appropriate. A multiple logistic regression analysis was performed to determine predictors of 30-day unplanned readmission.ResultsThere were 334 OPAT patients who met inclusion criteria. Median age was 58 years, 58% were male, and the most common infection diagnoses were bone/joint (49%), bloodstream (22%), and endovascular (13%). There were 64 (19%) patients who had an unplanned 30-day readmission. The most common reasons for readmission included non-infection related (45%), worsening infection (28%), and antimicrobial-related complication (17%). Readmitted patients were more likely to have a higher Charlson Comorbidity Index (CCI); prior admissions; bloodstream, endovascular, or pulmonary infection; no source control; and an infection caused by a multi-drug resistant organism. CCI was found to be an independent predictor of readmission (OR 1.096, 95% CI 1.001-1.200).ConclusionUnplanned readmissions were common in patients discharged with OPAT. There should be an emphasis on interventions to prevent readmissions in OPAT patients, particularly those with high-risk clinical characteristics.Disclosures All Authors: No reported disclosures

Behavioral Health Care Quality Among Marketplace Insurers in 2019.

Using 2019 Centers for Medicare and Medicaid Services data, the authors analyzed performance on behavioral health care quality measures among 168 marketplace insurers offering 185 products and investigated whether performance differed by insurer attributes. The authors considered four quality measures: antidepressant medication management, follow-up care for children prescribed attention-deficit hyperactivity disorder medication, follow-up care within 7 days after hospitalization for mental illness, and initiation and engagement of alcohol and other drug dependence treatment. Multivariate regression was used to determine whether performance varied by insurers' nonprofit ownership, Blue Cross-Blue Shield affiliation, Medicaid-managed care participation, and preferred provider organization status. Performance levels were highest for management with antidepressant medication and lowest for initiation and engagement of drug dependence treatment. Systematic differ-ences were observed by ownership status and Medicaid-managed care plan status. Increasing the transparency of health plan quality information is important for aiding enrollee decision making and encouraging quality improvement among providers and insurers.

ADAPTED SERVQUAL: A Health Service Quality Scale Incorporating Indicators of Sanitation and Hygiene.

Many scales have been developed to measure health care quality over the years, but no scale available today incorporates all important indicators of sanitation and hygiene in health care. This study therefore assessed the psychometric properties of an adapted scale, hereby called ADAPTED SERVQUAL, in an attempt to provide a scale that includes relevant indicators of hospital hygiene and sanitation. The setting of the study was low- and medium-capacity hospitals in the Greater Accra Region of Ghana. Patients in wards and outpatient departments in the hospitals participated in the study. We used relevant statistical tools to estimate the psychometric properties of ADAPTED SERVQUAL. To understand the relative importance of the new scale, we compared and related it to a recent scale, HEALTHQUAL. Principal component analysis yielded 6 factors: "tangibles," "reliability," "responsiveness," "assurance," "empathy," and "sanitation and hygiene," which explained 84% of the total variance. ADAPTED SERVQUAL has a good internal consistency (Cronbach α = 0.96). Confirmatory factor analysis confirmed the 6-factor solution and produced satisfactory discriminant validity and convergent validity indicators. The adapted scale was highly correlated with all dimensions of HEALTHQUAL, including continuous quality improvement (r ≥0.75, P < .001). In multiple linear regression, the 5 domains of HEALTHQUAL explained 59% of the variance in ADAPTED SERVQUAL (P < .001). The study concluded that 8 items that make up a single factor (ie, sanitation and hygiene) and contribute most of the total variance satisfactorily fit into the SERVQUAL scale as additional indicators of health care quality.

Development of An All-Payer Quality Program for the Pennsylvania Rural Health Model.

Measuring rural health care quality is challenging, and payer and government reporting requirements are frequently misaligned. The Pennsylvania Rural Health Model, a multipayer global budget demonstration for rural hospitals, initially required the proposal of an All-Payer Quality (APQ) Program in which participating payers would have held participating hospitals accountable for performance on a common set of quality measures. We sought to identify quality measures appropriate for use in APQ measurement and reporting programs for globally budgeted rural hospitals. A method was devised to identify, assess, and select quality measures from an environmental scan of core measure sets. An initial screen identified measures that were relevant, valid, and reliable. Four reviewers then independently assessed measures that passed the initial screen on a Likert scale of 1-5 for relevance, validity, reliability, responsiveness, alignment, and feasibility, and they selected a proposed measure set guided by prespecified measure set criteria. The 4 reviewers selected 10 quality measures from a list of 344 measures drawn from 8 core measure sets. One hundred twenty-five measures satisfied screening criteria and were assessed. The mean total score was 21.5/30 (95% CI: 17.0-26.0). Inter-rater reliability was moderate (intraclass correlation coefficient range 0.544-0.656). A formal performance measure selection methodology can generate a set of rural-appropriate health care quality measures for a multipayer rural hospital global budget program. This methodology could be replicated to select quality measures for inclusion in rural multipayer quality measurement and reporting programs.

Linking Patient Safety Culture to Quality Ratings in the Nursing Home Setting.

There is limited evidence on the associations between patient safety culture and measures of health care quality in nursing homes. This study examines the relationship between scores on the Agency for Healthcare Research and Quality (AHRQ) Surveys on Patient Safety Culture™ (SOPS®) Nursing Home Survey (NH SOPS) and Centers for Medicare and Medicaid Services Nursing Home Five-Star Quality Ratings. Using data from 186 nursing homes, we conducted multiple regression analyses predicting the Five-Star Quality Ratings from the NH SOPS survey measures. Five NH SOPS measures were related to the Overall, Health Inspections, and Quality Five-Star Ratings. Four NH SOPS measures were related to at least two of the four Five-Star Quality Ratings and three SOPS measures were related to one Five-Star Rating. None of the NH SOPS measures were significantly associated with the Staffing Five-Star Rating. Findings generally indicated that stronger patient safety culture is associated with higher quality ratings.

Measuring health care quality: Implications, threats, and opportunities for clinical pharmacists

AbstractThe Patient Protection and Affordable Care Act of 2010 has helped usher in an era of focus on health care quality and quality improvement. Since then, a variety of programs has driven quality improvement throughout the health care system using a combination of incentives and penalties. Many studies have demonstrated the value of integrating clinical pharmacist services into interdisciplinary models of care for the purpose of moving the needle on performance measures. The implementation of quality‐linked reimbursement programs has the greatest potential to meaningfully improve quality of care and reduce costs. However, the benefits of quality measures are dependent on their implementation into measurement systems and their application into clinical practice. Common threats to quality measurement in pharmacy practice may arise due to misapplication of health plan‐related measures to evaluate pharmacy services. Additionally, the core concepts related to novel reimbursement models have not adequately percolated into the formal education of practicing pharmacists. Therefore, the goal of this article is to help educate and raise awareness about the current quality landscape and present opportunities and directions for pharmacists to demonstrate their value in interdisciplinary health care teams. This article is broadly divided into four sections—first, we provide an introduction to quality measurement and its application to clinical pharmacists. Second, we elaborate on the development and endorsement of quality measures and measurement systems. Third, we present clinical scenarios of patient care—set in inpatient, ambulatory care, and community practice settings—that engage pharmacists in the context of quality measurement and evaluate the implications, threats, and opportunities for clinical pharmacists in each of these scenarios. Finally, we present recommendations for future advocacy, measurement, and leadership for pharmacist involvement in the quality landscape.

ECO Experts’ consensus on establishing renal cancer healthcare quality measures in Spain.

220 Background: The ECO Foundation (Excellence and Quality in Oncology) proposes to establish a set of healthcare quality measures (including indicators and standards) for the diagnosis, treatment and follow-up of renal cancer in Spain which all healthcare professionals involved can assume, being suitable for implementation in the continuous improvement process of our healthcare system. Methods: a) International literature review on the quality of healthcare in renal cancer; b) multidisciplinary driving group (9 oncologists with expertise in renal cancer plus 2 methodologists) to identify and choose possible quality measures to be applied in Spain; c) global evaluation of the relevance of these measures through experts’ consensus (Delphi modified by a stratified state panel, n = 55 oncologists specialized in renal cancer); d) selection of definitive measures, according to their feasibility and efficiency (information provided/effort in obtaining it) using a quantitative online priority grid; e) standard wording of the chosen measures: definition, indicator, sources of information, exclusions, clarifications, categorization and acceptable standard. Results: The nominal group proposed 43 quality measures for the Delphi panel. Consensus agreement rate = 84.5% (47/55). The professional consensus was reached on 40 measures (4 structural, 33 in healthcare procedures and 3 in clinical results). Therefore, there is a high level of consensus (93%) among Spanish oncologists who specialize in renal cancer on the content of the healthcare quality measures in the management of renal cancer. The final measures were chosen using a high confidence level (95%) in the unanimity of the experts (oncologists in the driving group) for prioritization depending on the feasibility and efficiency in the healthcare system. Finally, 25 measures were chosen (2 structural, 20 in procedures and 3 in results). Conclusions: The level of consensus and prioritization of measures achieved, will most likely translate in a widespread acceptance and viability for implementation in the National Health System. This could provide a valuable tool for quality assessment and equality in the care of renal cancer patients in Spain.

Development and Evaluation of a Structured Tool to Assess the Preventability of Hospital-Onset Bacteremia and Fungemia

Background: Hospital-onset bacteremia and fungemia (HOB) may be a preventable hospital-acquired condition and a potential healthcare quality measure. We developed and evaluated a tool to assess the preventability of HOB and compared it to a more traditional consensus panel approach. Methods: A 10-member healthcare epidemiology expert panel independently rated the preventability of 82 hypothetical HOB case scenarios using a 6-point Likert scale (range, 1= “Definitively or Almost Certainly Preventable” to 6= “Definitely or Almost Certainly Not Preventable”). Ratings on the 6-point scale were collapsed into 3 categories: Preventable (1–2), Uncertain (3–4), or Not preventable (5–6). Consensus was defined as concurrence on the same category among ≥70% expert raters. Cases without consensus were deliberated via teleconference, web-based discussion, and a second round of rating. The proportion meeting consensus, overall and by predefined HOB source attribution, was calculated. A structured HOB preventability rating tool was developed to explicitly account for patient intrinsic and extrinsic healthcare-related risks (Fig. 1). Two additional physician reviewers independently applied this tool to adjudicate the same 82 case scenarios. The tool was iteratively revised based on reviewer feedback followed by repeat independent tool-based adjudication. Interrater reliability was evaluated using the Kappa statistic. Proportion of cases where tool-based preventability category matched expert consensus was calculated. Results: After expert panel round 1, consensus criteria were met for 29 cases (35%), which increased to 52 (63%) after round 2. Expert consensus was achieved more frequently for respiratory or surgical site infections than urinary tract and central-line–associated bloodstream infections (Fig. 2a). Most likely to be rated preventable were vascular catheter infections (64%) and contaminants (100%). For tool-based adjudication, following 2 rounds of rating with interim tool revisions, agreement between the 2 reviewers was 84% for cases overall (κ, 0.76; 95% CI, 0.64–0.88]), and 87% for the 52 cases with expert consensus (κ, 0.79; 95% CI, 0.65–0.94). Among cases with expert consensus, tool-based rating matched expert consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewer 1 and reviewer 2, respectively. The proportion of cases rated “uncertain“ was lower among tool-based adjudicated cases with reviewer agreement (15 of 69) than among cases with expert consensus (23 of 52) (Fig. 2b). Conclusions: Healthcare epidemiology experts hold varying perspectives on HOB preventability. Structured tool-based preventability rating had high interreviewer reliability, matched expert consensus in most cases, and rated fewer cases with uncertain preventability compared to expert consensus. This tool is a step toward standardized assessment of preventability in future HOB evaluations.Funding: NoneDisclosures: None

Unmet social needs among low-income adults in the United States: Associations with health care access and quality.

ObjectiveTo describe social needs among low‐income adults and estimate the relationship between level of unmet social needs and key indicators of health care access and quality.Data SourceNational survey data from 12 states from the 2017 Behavioral Risk Factor Surveillance System, which added a “Social Determinants of Health” Module in 2017.Study DesignWe examined differences in eight measures of health care access and quality (eg, check‐up in last 12 months, inability to see doctor due to cost, receipt of eye examination for diabetics) for low‐income adults with 0, 1, 2‐3, and 4+ unmet social needs based on 7 social needs measures. We used adjusted logistic regression models to estimate the association between level of unmet need and each outcome.Principal FindingsMost common unmet social needs included not having enough money for balanced meals (33 percent) or food (32 percent). After adjusting for observable characteristics, higher levels of unmet social need were associated with poorer access and quality. Compared to those with no reported unmet needs, having 4+ unmet needs was significantly associated with reduced probability of having a yearly check‐up (65 percent vs 78 percent, adjusted difference = −7.1 percentage points (PP)), receiving a flu vaccine (33 percent vs 42 percent, adjusted difference = −5.4 PP), having a personal doctor (74 percent vs 80 percent, adjusted difference = −3.1 PP), and having a foot (63 percent vs 80 percent, adjusted difference = −12.8 PP) or eye examination (61 percent vs 73 percent, adjusted difference = −12.6 PP) for diabetic patients, and increased probability of being unable to see a doctor due to cost (44 percent vs 9 percent, adjusted difference = 27.9 PP) and having diabetes affect the eyes (22 percent vs 19 percent, adjusted difference = 8.0 PP) at α = 0.05.ConclusionsHigher levels of unmet social needs were associated with poorer access to and quality of care among low‐income adults. Addressing social needs both inside and outside of health care settings may help mitigate these negative effects. Additional research on if and how to effectively do so is critical.

Audit on in-hospital mortality of trauma patients: EMS Management and Mismanagement

Background: The investigation of trauma-related mortality is one of the key components in trauma studies and it is used as a performance index and measure of health care quality. Objective: The present study aimed to evaluate the performance of pre-hospital interventions and identify possible mismanagements in dealing with trauma patients transferred by emergency medical services (EMS) to the hospital and died. Methods: This study was conducted in 2019, in Tehran, Iran. All trauma patients who were transferred to the emergency department (ED) of three main referral hospitals, by Tehran EMS and died at the hospital within 24 hours of admission, were studied retrospectively. The required information was collected from the EMS and the hospital records. A panel of experts was asked to identify possible errors based on standards for each patient. Results: During the one-year study period, almost 14000 trauma patients were transported by Tehran EMS to the studied hospitals. Of them, a total of 197 deaths were recorded. The most and least provided services were breathing management (87.3%) and intravenous (IV) fluid therapy (12.2%), respectively. Needle thoracostomy, IV fluids therapy, life supports (basic and advanced cardiac), and airway management had the highest percentage of mismanagement among provided services. Bleeding control and resuscitation were consistent with the recommended standard. Conclusion: In the current study, bleeding control and immobilization was performed appropriately. Needle tracheostomy was not performed at all. Airway management and life supports of the victims were not performed properly.

Variability in Health Care Quality Measurement among Studies Using Service Provision Assessment Data from Low- and Middle-Income Countries: A Systematic Review.

Quality of care is essential for improving health outcomes, but heterogeneity in theoretical frameworks and metrics can limit studies' generalizability and comparability. This research aimed to compare definitions of care quality across research articles that incorporate data from Service Provision Assessment (SPA) surveys. Following Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines, we used a keyword search in PubMed. Each author reviewed abstracts, then full texts, for inclusion criteria, and peer-reviewed publications of empirical analysis using SPA data. The search yielded 3,250 unique abstracts, and 34 publications were included in the final analysis. We extracted details on the SPA dataset(s) used, theoretical framework applied, and how care quality was operationalized. The 34 included articles used SPA data from 14 surveys in nine countries (all in sub-Saharan Africa plus Haiti). One-third of these articles (n = 13) included no theoretical or conceptual framework for care quality. Among those articles referencing a framework, the most common was the Donabedian model (n = 7). Studies operationalized quality constructs in extremely different ways. Few articles included outcomes as a quality construct, and the operationalization of structure varied widely. A key asset of SPA surveys, owing to the standardized structure and use of harmonized data collection instruments, is the potential for cross-survey comparisons. However, this is limited by the lack of a common framework for measuring and reporting quality in the existing literature using SPA data. Service Provision Assessment surveys offer unique and valuable insights, and a common framework and approach would substantially strengthen the body of knowledge on quality of care in low-resource settings.

Dutch oral health care quality measures: a modified Delphi study

Objectives: Quality measures offer opportunities for evaluation and improvement of the quality of oral health care. This study describes the development of a core set of oral health care quality measures for adults in the Netherlands, which can be used in dental practice. Materials and methods: A comprehensive two-stage approach was used, consisting of: (1) identification of an initial set of measures based on appraised literature; and (2) a four-round modified RAND/UCLA Appropriateness Method to establish measures that are relevant, appropriate and important to oral health care. Measures were rated anonymously on a nine-point Likert scale, ranging from 1 (lowest rating) to 9 (highest rating), followed by a group discussion to reach consensus. Multiple key stakeholder groups in the Dutch oral health care field were involved in the Delphi rounds, including dental professionals, scientists and representatives from Dutch oral health care organisations. Results: The study resulted in a core set of 13 oral health care quality measures. The measures cover domains related to oral disease outcomes, oral treatment and preventive services, patient experiences, patient safety, and organisational aspects of oral health care. In addition, the study led to the identification of 49 structural aspects of oral health care that are important to measure. Discussion: To our knowledge, this is the first study combining appraised literature from a systematic review and a rigorous multi-stage procedure with extensive stakeholder involvement to develop a core set of oral health care quality measures. In the next phase, the measures will be tested on feasibility, reliability, and will be piloted and implemented in practice.

How COVID has Illuminated the Pitfalls of a Single-Payer System in the US

Health care quality measures are impacted by resources invested into outcomes. COVID-19 has had a direct impact upon quality outcomes, the same illuminating just some of the problems with the concept of a single-payer health care system. The US government's inefficiencies in attempting to run the single-payer system known as IHS in context with its repeated failures in managing the COVID-19 crises along with the economic impact of the same, is but one call for strong leadership to dispel the myth that a single-payer system is a panacea for America.

Reducing Unnecessary Chest X-Ray Films After Thoracic Surgery: A Quality Improvement Initiative

Previous work has identified that inpatient post-thoracic surgery chest x-ray films (CXR) are overutilized. A three-phase rapid cycle quality improvement initiative was performed to reduce empiric post-thoracic surgery CXR use by 25% over 1 year. We adapted evidence-based guidelines and implemented "plan-do-study-act" (PDSA) cycle methodology. The PDSA cycles included (1) education with literature and preintervention statistics; (2) electronic medical record order-set modification; and (3) audit and feedback with monthly status reports. Each cycle lasted 3 months. Use of CXR was tracked in the post-anesthesia care unit and as a daily rate of non-post-anesthesia care unit CXRs. Cost data were estimated from Centers for Medicare & Medicaid Services fees. During the initiative, 292 thoracic surgery inpatients were monitored. Before intervention, 99% of patients (69 of 70) received a post-anesthesia care unit CXR, and the daily rate of other CXRs was 1.6. Overall, there was a significant reduction in CXR utilization (P< .001). Post-anesthesia care unit CXRs decreased by 42%, lowering to 89% (68 of 76) to 68% (50 of 74) to 57% (41 of 72) in PDSA cycles 1 through 3, respectively. The daily rate of other CXRs decreased by 38%, lowering to 1.4 to 1.3 to 1.0. Patient perioperative characteristics and health care quality measures were not different between cycles. After quality improvement implementation, cost savings were estimated to be at least $73,292 per year. Implementation of our quality improvement initiative safely and systematically reduced empiric CXR use after inpatient thoracic surgery. Results will be used in future quality improvement initiatives to reduce unnecessary postoperative testing.

What Do Patients Want? A Qualitative Analysis of Patient, Provider, and Administrative Perceptions and Expectations About Patients' Hospital Stays.

Patient experience is increasingly recognized as a measure of health care quality and patient-centered care and is currently measured through the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). The HCAHPS survey may miss key factors important to patients, and in particular, to underserved patient populations. We performed a qualitative study utilizing semi-structured interviews with 45 hospitalized English- and Spanish-speaking patients and 6 focus groups with physicians, nurses, and administrators at a large, urban safety-net hospital. Four main themes were important to patients: (1) the hospital environment including cleanliness and how hospital policies and procedures impact patients’ perceived autonomy, (2) whole-person care, (3) communication with and between care teams and utilizing words that patients can understand, and (4) responsiveness and attentiveness to needs. We found that several key themes that were important to patients are not fully addressed in the HCAHPS survey and there is a disconnect between what patients and care teams believe patients want and what hospital policies drive in the care environment.

The terminology of social emergency medicine: Measuring social determinants of health, social risk, and social need.

Emergency medicine has increasingly focused on addressing social determinants of health (SDoH) in emergency medicine. However, efforts to standardize and evaluate measurement tools and compare results across studies have been limited by the plethora of terms (eg, SDoH, health‐related social needs, social risk) and a lack of consensus regarding definitions. Specifically, the social risks of an individual may not align with the social needs of an individual, and this has ramifications for policy, research, risk stratification, and payment and for the measurement of health care quality. With the rise of social emergency medicine (SEM) as a field, there is a need for a simplified and consistent set of definitions. These definitions are important for clinicians screening in the emergency department, for health systems to understand service needs, for epidemiological tracking, and for research data sharing and harmonization. In this article, we propose a conceptual model for considering SDoH measurement and provide clear, actionable, definitions of key terms to increase consistency among clinicians, researchers, and policy makers.

Relationship of Press Ganey Satisfaction and PROMIS Function and Pain in Foot and Ankle Patients.

Patient satisfaction has garnered interest as a tool to measure health care quality. However, orthopedic studies in total joint arthroplasty, spine, and hand patients have offered conflicting relationships between Press Ganey (PG) satisfaction metrics and patient-reported outcome (PRO) measures. No prior study has assessed the relationship between PG and PROs in foot and ankle patients. Whether satisfaction and outcomes instruments, though, measure similar or differing aspects of the patient experience is unclear. Here, we tested if there was an association between Patient-Reported Outcomes Measurement Information System (PROMIS) outcomes and PG satisfaction scores. PG and PROMIS outcomes data for new patient visits to an orthopedic foot and ankle clinic between 2015 and 2017 were retrospectively analyzed. Patients that completed PG satisfaction surveys were included for study. All patients who completed PG surveys and completed one or both PROMIS physical function (PF) or pain interference (PI) metrics administered by computerized adaptive testing were included. Negative binomial regressions were used to compare PRO scores to PG overall satisfaction and PG satisfaction with care provider, adjusting for patient characteristics. Results were reported as dissatisfaction score ratios, which represented the amount of PG dissatisfaction associated with a 10-point increase in PROMIS PF or PI. Of the 3984 new patient visits, only 441 completed the PG survey (11.3% response rate). Ceiling effects were seen with PG data: 64% of patients reported perfect satisfaction with care provider and 27% had perfect overall satisfaction. Higher function on the PROMIS PF was weakly associated with increased overall satisfaction (ratio = 0.82, 95% CI: 0.68-0.99, P = .039) and increased satisfaction with care provider (ratio = 0.60, 95% CI: 0.40-0.92, P = .019). However, pain (PROMIS PI) was not associated with overall satisfaction or with satisfaction with care provider. Based on our data here, patient satisfaction was weakly related to patient-reported function but not pain interference among this subset of new patients presenting to a foot and ankle clinic. Given our essentially negative findings, further study is needed to determine which aspects of the PG satisfaction and PROMIS scores track similarly. Further, our findings add to the growing literature showcasing limitations of the PG tool, including low response rates and notable ceiling effects. If satisfaction metrics and patient-reported outcomes capture differing aspects of the patient experience, we need to better understand how that influences the measurement of health care quality and value. Level III, comparative study.

Translating international guidelines for use in routine maternal and neonatal healthcare quality measurement

ABSTRACT Background Improving facility-based quality for maternal and neonatal care is the key to reducing morbidity and mortality rates in low- and middle-income countries. Recent guidance from WHO and others has produced a large number of indicators to choose from to track quality. Objective To explore how to translate complex global maternal and neonatal health standards into actionable application at the facility level. Methods We applied a two-step process as an example of how the 352 indicators in WHO’s 2016 Standards for Improving Quality of Maternal and Newborn Care in Health Facilities might be reduced to only those with the strongest evidence base, associated with outcomes, and actionable by facility managers. We applied Hill criteria and assessed whether indicators were within the control of facility managers. We next conducted a rapid review of supporting literature and applied GRADE analysis, retaining those with scores of ‘moderate’ or ‘high’. To understand the utility and barriers to measuring this limited set of indicators in practice, we undertook a case study of hypothetical measurement application in two districts in Bangladesh, interviewing 25 clinicians, managers, and other stakeholders. Results From the initial 352 indicators, 56 were retained. The 56 indicators were used as a base for interviews. Respondents emphasized the practical challenges to the use of complex guides and the need for parsimonious and actionable sets of quality indicators. Conclusions This work offers one way to move towards a reduced quality indicator set, beginning from current WHO guidance. Despite study limitations, this work provides evidence of the need for reduced and evidence-based sets of quality indicators if guides are to be used to improve quality in practice. We hope that future research will build on and refine our efforts. Measuring quality effectively so that evidence guides and improves practice is the first step to assuring safe maternal and neonatal care.

The State of Health Care Quality Measurement in the Era of COVID-19

The State of Health Care Quality Measurement in the Era of COVID-19

Assessing the impact of social determinants of health on predictive models for potentially avoidable 30-day readmission or death.

ObjectivesEarly hospital readmissions or deaths are key healthcare quality measures in pay-for-performance programs. Predictive models could identify patients at higher risk of readmission or death and target interventions. However, existing models usually do not incorporate social determinants of health (SDH) information, although this information is of great importance to address health disparities related to social risk factors. The objective of this study is to examine the impact of social determinants of health on predictive models for potentially avoidable 30-day readmission.MethodsWe extracted electronic health record data for 19,941 hospital admissions between January 2015 and November 2017 at an academic medical center in New York City. We applied the Simplified HOSPITAL score model to predict potentially avoidable 30-day readmission or death and examined if incorporating individual- and community-level SDH could improve the prediction using cross-validation. We calculated the C-statistic for discrimination, Brier score for accuracy, and Hosmer–Lemeshow test for calibration for each model using logistic regression. Analysis was conducted for all patients and three subgroups that may be disproportionately affected by social risk factors, namely Medicaid patients, patients who are 65 or older, and obese patients.ResultsThe Simplified HOSPITAL score model achieved similar performance in our sample compared to previous studies. Adding SDH did not improve the prediction among all patients. However, adding individual- and community-level SDH at the US census tract level significantly improved the prediction for all three subgroups. Specifically, C-statistics improved from 0.70 to 0.73 for Medicaid patients, from 0.66 to 0.68 for patients 65 or older, and from 0.70 to 0.73 for obese patients.ConclusionsPatients from certain subgroups may be more likely to be affected by social risk factors. Incorporating SDH into predictive models may be helpful to identify these patients and reduce health disparities associated with vulnerable social conditions.