Han-I Wang

Risk-adjusted cesarean section rates for the assessment of physician performance in Taiwan: a population-based study

BackgroundOver the past decade, about one-third of all births nationwide in Taiwan were delivered by cesarean section (CS). Previous studies in the US and Europe have documented the need for risk adjustment for fairer comparisons among providers. In this study, we set out to determine the impact that adjustment for patient-specific risk factors has on CS among different physicians in Taiwan.MethodsThere were 172,511 live births which occurred in either hospitals or obstetrics/gynecology clinics between 1 January and 31 December 2003, and for whom birth certificate data could be linked with National Health Insurance (NHI) claims data, available as the sample for this study. Physicians were divided into four equivalent groups based upon the quartile distribution of their crude (actual) CS rates. Stepwise logistic regressions were conducted to develop a predictive model and to determine the expected (risk-adjusted) CS rate and 95% confidence interval (CI) for each physician. The actual rates were then compared with the expected CS rates to see the proportion of physicians whose actual rates were below, within, or above the predicted CI in each quartile.ResultsThe proportion of physicians whose CS rates were above the predicted CI increased as the quartile moved to the higher level. However, more than half of the physicians whose actual rates were higher than the predicted CI were not in the highest quartile. Conversely, there were some physicians (40 of 258 physicians) in the highest quartile who were actually providing obstetric care that was appropriate to the risk. When a stricter standard was applied to the assessment of physician performance by excluding physicians in quartile 4 for predicting CS rates, as many as 60% of physicians were found to have higher CS rates than the predicted CI, and indeed, the CS rates of no physicians in either quartile 3 or quartile 4 were below the predicted CI.ConclusionOverall, our study found that the comparison of unadjusted CS rates might not provide a valid reflection of the quality of obstetric care delivered by physicians, and may ultimately lead to biased judgments by purchasers. Our study has also shown that when we changed the standard of quality assessment, the evaluation results also changed.

Variations in specialist palliative care referrals: findings from a population-based patient cohort of acute myeloid leukaemia, diffuse large B-cell lymphoma and myeloma

Objective To develop and implement a methodology for capturing complete haematological malignancy pathway data and use it to identify variations in specialist palliative care (SPC) referrals. Methods In our established UK population-based patient cohort, 323 patients were diagnosed with acute myeloid leukaemia, diffuse large B-cell lymphoma or myeloma between May 2005 and April 2008, and died before April 2010. A day-by-day calendar approach was devised to collect pathway data, including SPC referrals, to supplement routinely collected information on clinical presentation, diagnosis, treatment, response, and date and place of death. Results 155 (47.9%) of the 323 patients had at least one SPC referral. The likelihood of referral increased with survival (OR 6.58, 95% CIs 3.32 to 13.03 for patients surviving ≥1 year compared to ≤1 month from diagnosis), and varied with diagnosis (OR 1.96, CIs 1.15 to 3.35 for myeloma compared to acute myeloid leukaemia). Compared to patients dying in hospital, those who died at home or in a hospice were also more likely to have had an SPC referral (OR 3.07, CIs 1.59 to 5.93 and 4.74, CIs 1.51 to 14.81, respectively). No associations were found for age and sex. Conclusions Our novel approach efficiently captured pathway data and SPC referrals, revealing evidence of greater integration between haematology and SPC services than previously reported. The likelihood of referral was much higher among those dying outside hospital, and variations in practice were observed by diagnosis, emphasising the importance of examining diseases individually.

Long-Term Medical Costs and Life Expectancy of Acute Myeloid Leukemia: A Probabilistic Decision Model

BACKGROUND Acute myeloid leukemia (AML) can be diagnosed at any age and treatment, which can be given with supportive and/or curative intent, is considered expensive compared with that for other cancers. Despite this, no long-term predictive models have been developed for AML, mainly because of the complexities associated with this disease. OBJECTIVE The objective of the current study was to develop a model (based on a UK cohort) to predict cost and life expectancy at a population level. METHODS The model developed in this study combined a decision tree with several Markov models to reflect the complexity of the prognostic factors and treatments of AML. The model was simulated with a cycle length of 1 month for a time period of 5 years and further simulated until age 100 years or death. Results were compared for two age groups and five different initial treatment intents and responses. Transition probabilities, life expectancies, and costs were derived from a UK population-based specialist registry-the Haematological Malignancy Research Network (www.hmrn.org). RESULTS Overall, expected 5-year medical costs and life expectancy ranged from £8,170 to £81,636 and 3.03 to 34.74 months, respectively. The economic and health outcomes varied with initial treatment intent, age at diagnosis, trial participation, and study time horizon. The model was validated by using face, internal, and external validation methods. The results show that the model captured more than 90% of the empirical costs, and it demonstrated good fit with the empirical overall survival. CONCLUSIONS Costs and life expectancy of AML varied with patient characteristics and initial treatment intent. The robust AML model developed in this study could be used to evaluate new diagnostic tools/treatments, as well as enable policy makers to make informed decisions.

Preferred and actual place of death in haematological malignancy

Objectives Home is considered the preferred place of death for many, but patients with haematological malignancies (leukaemias, lymphomas and myeloma) die in hospital more often than those with other cancers and the reasons for this are not wholly understood. We examined preferred and actual place of death among people with these diseases. Methods The study is embedded within an established population-based cohort of patients with haematological malignancies. All patients diagnosed at two of the largest hospitals in the study area between May 2005 and April 2008 with acute myeloid leukaemia, diffuse large B-cell lymphoma or myeloma, who died before May 2010 were included. Data were obtained from medical records and routine linkage to national death records. Results 323 deceased patients were included. A total of 142 (44%) had discussed their preferred place of death; 45.8% wanted to die at home, 28.2% in hospital, 16.9% in a hospice, 5.6% in a nursing home and 3.5% were undecided; 63.4% of these died in their preferred place. Compared to patients with evidence of a discussion, those without were twice as likely to have died within a month of diagnosis (14.8% vs 29.8%). Overall, 240 patients died in hospital; those without a discussion were significantly more likely to die in hospital than those who had (p≤0.0001). Of those dying in hospital, 90% and 75.8% received haematology clinical input in the 30 and 7 days before death, respectively, and 40.8% died in haematology areas. Conclusions Many patients discussed their preferred place of death, but a substantial proportion did not and hospital deaths were common in this latter group. There is scope to improve practice, particularly among those dying soon after diagnosis. We found evidence that some people opted to die in hospital; the extent to which this compares with other cancers is of interest.

A Generic Model for Follicular Lymphoma: Predicting Cost, Life Expectancy, and Quality-Adjusted-Life-Year Using UK Population–Based Observational Data

Objectives To use real-world data to develop a flexible generic decision model to predict cost, life expectancy, and quality-adjusted life-years (QALYs) for follicular lymphoma (FL) in the general patient population. Methods All patients newly diagnosed with FL in the UK’s population-based Haematological Malignancy Research Network (www.hmrn.org) between 2004 and 2011 were followed until 2015 (N = 740). Treatment pathways, QALYs, and costs were incorporated into a discrete event simulation to reflect patient heterogeneity, including age and disease management. Two scenario analyses, based on the latest National Institute for Health and Clinical Excellence (NICE) guidelines (rituximab induction therapy for newly diagnosed asymptomatic patients and rituximab maintenance therapy for patients between treatments), were conducted and their economic impacts were compared to current practice. Results Incidence-based analysis revealed expected average lifetime costs ranging from £6,165 [US

Cohort Profile: The Haematological Malignancy Research Network (HMRN): a UK population-based patient cohort

7,709] to £63,864 [US

Place of death in haematological malignancy: variations by disease sub-type and time from diagnosis to death

79,862] per patient, and average life expectancy from 75 days to 17.56 years. Prevalence-based analysis estimated average annual treatment costs of £60–65 million [US

Costs of cervical cancer and precancerous lesions treatment in a publicly financed health care system

75-80 million], accounting for approximately 10% of the United Kingdom’s annual National Health Service budget for hematological cancers as a whole. Assuming that treatment effects reported in trials are applicable to all patient groups, scenario analyses for two recent NICE guidelines demonstrated potential annual cost savings for the United Kingdom that ranged with uptake frequency from £0.6 million to £11 million [US

Treatment cost and life expectancy of diffuse large B-cell lymphoma (DLBCL): a discrete event simulation model on a UK population-based observational cohort

0.75-2.75 million]. Conclusions Costs, survival, and QALYs associated with FL vary markedly with patient characteristics and disease management. Allowing the production of more realistic outcomes across the patient population as a whole, our model addresses this heterogeneity and is a useful tool with which to evaluate new technologies/treatments to support healthcare decision makers.

Risk factors for poor outcomes of children with acute acalculous cholecystitis

Cohort Profile: The Haematological Malignancy Research Network (HMRN): a UK populationbased patient cohort Alexandra Smith, Debra Howell, Simon Crouch, Dan Painter, John Blase, Han-I Wang, Ann Hewison, Timothy Bagguley, Simon Appleton, Sally Kinsey, Cathy Burton, Russell Patmore and Eve Roman* Department of Health Sciences, University of York, York, UK, Paediatric Haematology and Oncology Unit, Leeds General Infirmary, St James’s Institute of Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK and Queens Centre for Oncology, Castle Hill Hospital, Cottingham, UK