3 research outputs found
Distinguishing between types of data and methods of collecting them
No full textThe author examines the role of different data collection methods--including the types of data they produce--in the analysis of social phenomena in developing countries. He points out that one confusing factor in the"quantitative-qualitative"debate is that a distinction is not clearly made between methods of data collection used and types of data generated. He maintains the divide between quantitative and qualitative types of data but analyzes methods according to their"contextuality": the degree to which they try to understand human behavior in the social, cultural, economic, and political environment of a given place. He emphasizes that it is most fruitful to think of both methods and data as lying on a continuum stretching from more to less contextual methodology and from more to less qualitative data output. Using characteristic information needs for health planning derived from data on the use of health services, he shows that each combination of method (more or less contextual) and data (more or less qualitative) is a unique primary source that can fulfill different information requirements. He concludes that: 1) Certain information about health utilization can be obtained only through contextual methods--in which case strict statistical representability must give way to inductive conclusions, assessments of internal validity, and replicability of results. 2) Often contextual methods are needed to design appropriate noncontextual data collection tools. 3) Even where noncontextual data collection methods are needed, contextual methods can play an important role in assessing the validity of the results at the local level. 4) In cases where different data collection methods can be used to probe general results, the methods can--and need to be--formally linked.Early Child and Children's Health,Health Monitoring&Evaluation,Health Systems Development&Reform,Housing&Human Habitats,Public Health Promotion,Health Monitoring&Evaluation,Poverty Assessment,ICT Policy and Strategies,Health Systems Development&Reform,Scientific Research&Science Parks
Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries
No full textBackground: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures. Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge. Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to sideeffects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (β coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and lowand middle-income countries, patient-reported outcomes did not. Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model
No full textOpioids are frequently overprescribed after surgery. We applied a tabular foundation model to predict the risk of post-discharge opioid consumption. The model was trained and internally validated on an 80:20 training/test split of the ‘Opioid PrEscRiptions and usage After Surgery’ (ACTRN12621001451897p) study cohort, including adult patients undergoing general, orthopaedic, gynaecological and urological operations (n = 4267), with external validation in a distinct cohort of patients discharged after general surgical procedures (n = 826). The area under the receiver operator curve was 0.84 (95% confidence interval [CI] 0.81–0.88) at internal testing and 0.77 (95% CI 0.74–0.80) at external validation. Brier scores were 0.13 (95% CI 0.12–0.14) and 0.19 (95% CI 0.17–0.2). Patients with a <50% predicted risk of opioid consumption consumed a median of 0 oral morphine equivalents in the first week after surgery. Applying this model would reduce opioid prescriptions by 4.5% globally, and counterfactual modelling suggests without increasing time in severe pain (−4.3%, 95% CI −17.7 to 8.6)
