Data Quality-Driven Improvement in Health Care: Systematic Literature Review.

BACKGROUND: The promise of real-world evidence and the learning health care system primarily depends on access to high-quality data. Despite widespread awareness of the prevalence and potential impacts of poor data quality (DQ), best practices for its assessment and improvement are unknown. OBJECTIVE: This review aims to investigate how existing research studies define, assess, and improve the quality of structured real-world health care data. METHODS: A systematic literature search of studies in the English language was implemented in the Embase and PubMed databases to select studies that specifically aimed to measure and improve the quality of structured real-world data within any clinical setting. The time frame for the analysis was from January 1945 to June 2023. We standardized DQ concepts according to the Data Management Association (DAMA) DQ framework to enable comparison between studies. After screening and filtering by 2 independent authors, we identified 39 relevant articles reporting DQ improvement initiatives. RESULTS: The studies were characterized by considerable heterogeneity in settings and approaches to DQ assessment and improvement. Affiliated institutions were from 18 different countries and 18 different health domains. DQ assessment methods were largely manual and targeted completeness and 1 other DQ dimension. Use of DQ frameworks was limited to the Weiskopf and Weng (3/6, 50%) or Kahn harmonized model (3/6, 50%). Use of standardized methodologies to design and implement quality improvement was lacking, but mainly included plan-do-study-act (PDSA) or define-measure-analyze-improve-control (DMAIC) cycles. Most studies reported DQ improvements using multiple interventions, which included either DQ reporting and personalized feedback (24/39, 61%), IT-related solutions (21/39, 54%), training (17/39, 44%), improvements in workflows (5/39, 13%), or data cleaning (3/39, 8%). Most studies reported improvements in DQ through a combination of these interventions. Statistical methods were used to determine significance of treatment effect (22/39, 56% times), but only 1 study implemented a randomized controlled study design. Variability in study designs, approaches to delivering interventions, and reporting DQ changes hindered a robust meta-analysis of treatment effects. CONCLUSIONS: There is an urgent need for standardized guidelines in DQ improvement research to enable comparison and effective synthesis of lessons learned. Frameworks such as PDSA learning cycles and the DAMA DQ framework can facilitate this unmet need. In addition, DQ improvement studies can also benefit from prioritizing root cause analysis of DQ issues to ensure the most appropriate intervention is implemented, thereby ensuring long-term, sustainable improvement. Despite the rise in DQ improvement studies in the last decade, significant heterogeneity in methodologies and reporting remains a challenge. Adopting standardized frameworks for DQ assessment, analysis, and improvement can enhance the effectiveness, comparability, and generalizability of DQ improvement initiatives.

Primary palliative care in low- and middle-income countries: A systematic review and thematic synthesis of the evidence for models and outcomes.

BACKGROUND: Serious health-related suffering is predicted to double in low- and middle-income countries by 2060. Primary care offers the best opportunity to meet Universal Health Coverage in an equitable way. Primary palliative care growth should be evidence-based to ensure provision is feasible, acceptable and culturally congruent. AIM: To identify the current evidence related to primary palliative care and to describe how primary palliative is defined in this setting, dominant typologies of care and meaningful outcome measures in LMICs. DESIGN: A systematic review and thematic synthesis was conducted. We described the nature, extent and distribution of published literature on primary palliative care in low- and middle-income countries, use thematic synthesis to characterize typologies of primary palliative care and design a process model for care delivery in low- and middle-income countries. DATA SOURCES: Medline, Psychinfo, Global Health, Embase and CINAHL. RESULTS: Thirty-five publications were included. Nearly half took place in Asia (n = 16, 45.7%). We identified five dominant typologies of primary palliative care, including delivery in primary care clinics by multidisciplinary healthcare teams and palliative care specialists, in people's homes by healthcare professionals and volunteers and in tertiary healthcare facilities by generalists. We designed a process model for how these models operate within larger health systems and identified barriers and facilitators to implementing primary palliative care in this context. CONCLUSION: Evidence supporting primary palliative care in low- and middle-income countries is limited, and much of the published literature comes from Asia and southern Africa. Health systems in low- and middle-income countries have unique strengths and needs that affect primary palliative care services that should guide how services evolve to meet future need.