Health service research definition builder: An R Shiny application for exploring diagnosis codes associated with services reported in routinely collected health data.

Many administrative health data-based studies define patient cohorts using procedure and diagnosis codes. The impact these criteria have on a study's final cohort is not always transparent to co-investigators or other audiences if access to the research data is restricted. We developed a SAS and R Shiny interactive research support tool which generates and displays the diagnosis code summaries associated with a selected medical service or procedure. This allows non-analyst users to interrogate claims data and groupings of reported diagnosis codes. The SAS program uses a tree classifier to find associated diagnosis codes with the service claims compared against a matched, random sample of claims without the service. Claims are grouped based on the overlap of these associated diagnosis codes. The Health Services Research (HSR) Definition Builder Shiny application uses this input to create interactive table and graphics, which updates estimated claim counts of the selected service as users select inclusion and exclusion criteria. This tool can help researchers develop preliminary and shareable definitions for cohorts for administrative health data research. It allows an additional validation step of examining frequency of all diagnosis codes associated with a service, reducing the risk of incorrect included or omitted codes from the final definition. In our results, we explore use of the application on three example services in 2016 US Medicare claims for patients aged over 65: knee arthroscopy, spinal fusion procedures and urinalysis. Readers can access the application at https://kelsey209.shinyapps.io/hsrdefbuilder/ and the code at https://github.com/kelsey209/hsrdefbuilder.

Patterns of specialist out-of-pocket costs for Australian Medicare services: implications for price transparency.

Objective To explore out-of-pocket (OOP) costs within specialties and individual specialists, and use of Medicare Benefits Schedule (MBS) data for potential price transparency initiatives. Methods We conducted a cross-sectional descriptive study of claims for a 10% random sample of Medicare enrolees for out-of-hospital MBS-billed subsequent and initial consultations between 1 January 2014 and 31 December 2014, specific to cardiologist, oncologist and ophthalmologists (with at least 10 patient visits in 2014). Our main outcomes were the number of locations per provider, number of unique OOP consultation costs per provider and provider-location, and the proportion of bulk-billed visits for these visits. Results We studied 970 cardiologists, 913 ophthalmologists and 376 oncologists. At least 67% of specialists across each specialty had at least two practice locations: cardiologists had a median of three (interquartile range [IQR]: 2-4) and ophthalmologists and oncologists both had a median of two (IQR: 1-3). For subsequent consultations, cardiologists had a median of three unique costs per location (IQR: 2-3), whereas ophthalmologists had a median of four unique costs per location (IQR: 3-5). In contrast, oncologists had a median of one unique cost per location (IQR: 1-2) (57.6% of oncologists' provider-locations charged only the bulk-billing amount). Conclusions Specialists have distinct fee lists that can vary based on location. Summary statistics on price transparency websites based on a single amount (like a median or mean OOP charge) might mask substantial variation in costs and lead to bill shock for individual patients.

Utilization Rates of Pancreatectomy, Radical Prostatectomy, and Nephrectomy in New York, Ontario, and New South Wales, 2011 to 2018.

Importance: Few studies have compared surgical utilization between countries or how rates may differ according to patients' socioeconomic status. Objective: To compare population-level utilization of 3 common nonemergent surgical procedures in New York State (US), Ontario (Canada), and New South Wales (Australia) and how utilization differs for residents of lower- and higher-income neighborhoods. Design, Setting, and Participants: This cohort study included all adults aged 18 years and older who were hospitalized for pancreatectomy, radical prostatectomy, or nephrectomy between 2011 and 2016 in New York, between 2011 and 2018 in Ontario, and between 2013 and 2018 in New South Wales. Each patient's address of residence was linked to 2016 census data to ascertain neighborhood income. Data were analyzed from August 2019 to November 2020. Main Outcomes and Measures: Primary outcomes were (1) each jurisdiction's per capita age- and sex-standardized utilization rates (procedures per 100 000 residents per year) for each surgery and (2) utilization rates among residents of lower- and higher-income neighborhoods. Results: This study included 115 428 surgical patients (25 780 [22.3%] women); 5717, 21 752, and 24 617 patients in New York were hospitalized for pancreatectomy, radical prostatectomy, and nephrectomy, respectively; 4929, 19 125, and 16 916 patients in Ontario, respectively; and 2069, 13 499, and 6804 patients in New South Wales, respectively. Patients in New South Wales were older for all procedures (eg, radical prostatectomy, mean [SD] age in New South Wales, 64.8 [7.3] years; in New York, 62.7 [8.4] years; in Ontario, 62.8 [6.7] years; P < .001); patients in New York were more likely than those in other locations to be women for pancreatectomy (New York: 2926 [51.2%]; Ontario: 2372 [48.1%]; New South Wales, 1003 [48.5%]; P = .004) and nephrectomy (New York: 10 645 [43.2%]; Ontario: 6529 [38.6%]; 2605 [38.3%]; P < .001). With the exception of nephrectomy in Ontario, there was a higher annual utilization rate for all procedures in all jurisdictions among patients residing in affluent neighborhoods (quintile 5) compared with poorer neighborhoods (quintile 1). This difference was largest in New South Wales for pancreatectomy (4.65 additional procedures per 100 000 residents [SE, 0.28]; P < .001) and radical prostatectomy (73.46 additional procedures per 100 000 residents [SE, 1.20]; P < .001); largest in New York for nephrectomy (8.43 additional procedures per 100 000 residents [SE, 0.85]; P < .001) and smallest in New York for radical prostatectomy (19.70 additional procedures per 100 000 residents [SE, 2.63]; P < .001); and smallest in Ontario for pancreatectomy (1.15 additional procedures per 100 000 residents [SE, 0.28]; P < .001) and nephrectomy (-1.10 additional procedures per 100 000 residents [SE, 0.52]; P < .001). New York had the highest utilization of nephrectomy (28.93 procedures per 100 000 residents per year [SE, 0.18]) and New South Wales for had the highest utilization of pancreatectomy and radical prostatectomy (6.94 procedures per 100 000 residents per year [SE, 0.15] and 94.37 procedures per 100 000 residents per year [SE, 0.81], respectively; all P < .001). Utilization was lowest in Ontario for all procedures (pancreatectomy, 6.18 procedures per 100 000 residents per year [SE, 0.09]; radical prostatectomy, 49.24 procedures per 100 000 residents per year [SE, 0.36]; nephrectomy, 21.40 procedures per 100 000 residents per year [SE, 0.16]; all P < .001). Conclusions and Relevance: In this study, New York and New South Wales had higher per capita surgical utilization and larger neighborhood income-utilization gradients than Ontario. These findings suggest that income-based disparities are larger in the United States and Australia and smaller in Canada and highlight trade-offs inherent in the health care systems of different countries.

Assessment of Overuse of Medical Tests and Treatments at US Hospitals Using Medicare Claims.

Importance: Overuse of health care services exposes patients to unnecessary risk of harm and costs. Distinguishing patterns of overuse among hospitals requires hospital-level measures across multiple services. Objective: To describe characteristics of hospitals associated with overuse of health care services in the US. Design, Setting, and Participants: This retrospective cross-sectional analysis used Medicare fee-for-service claims data for beneficiaries older than 65 years from January 1, 2015, to December 31, 2017, with a lookback of 1 year. Inpatient and outpatient services were included, and services offered at specialty and federal hospitals were excluded. Patients were from hospitals with the capacity (based on a claims filter developed for this study) to perform at least 7 of 12 investigated services. Statistical analyses were performed from July 1, 2020, to December 20, 2020. Main Outcomes and Measures: Outcomes of interest were a composite overuse score ranging from 0 (no overuse of services) to 1 (relatively high overuse of services) and characteristics of hospitals clustered by overuse rates. Twelve published low-value service algorithms were applied to the data to find overuse rates for each hospital, normalized and aggregated to a composite score and then compared across 6 hospital characteristics using multivariable regression. A k-means cluster analysis was used on normalized overuse rates to identify hospital clusters. Results: The primary analysis was performed on 2415 cohort A hospitals (ie, hospitals with capacity for 7 or more services), which included 1 263 592 patients (mean [SD] age, 72.4 [14] years; 678 549 women [53.7%]; 101 017 191 White patients [80.5%]). Head imaging for syncope was the highest-volume low-value service (377 745 patients [29.9%]), followed by coronary artery stenting for stable coronary disease (199 579 [15.8%]). The mean (SD) composite overuse score was 0.40 (0.10) points. Southern hospitals had a higher mean score than midwestern (difference in means: 0.06 [95% CI, 0.05-0.07] points; P < .001), northeast (0.08 [95% CI, 0.06-0.09] points; P < .001), and western hospitals (0.08 [95% CI, 0.07-0.10] points; P < .001). Nonprofit hospitals had a lower adjusted mean score than for-profit hospitals (-0.03 [95% CI, -0.04 to -0.02] points; P < .001). Major teaching hospitals had significantly lower adjusted mean overuse scores vs minor teaching hospitals (difference in means, -0.07 [95% CI, -0.08 to -0.06] points; P < .001) and nonteaching hospitals (-0.10 [95% CI, -0.12 to -0.09] points; P < .001). Of the 4 clusters identified, 1 was characterized by its low counts of overuse in all services except for spinal fusion; the majority of major teaching hospitals were in this cluster (164 of 223 major teaching hospitals [73.5%]). Conclusions and Relevance: This cross-sectional study used a novel measurement of hospital-associated overuse; results showed that the highest scores in this Medicare population were associated with nonteaching and for-profit hospitals, particularly in the South.

Adverse Events and Hospital-Acquired Conditions Associated With Potential Low-Value Care in Medicare Beneficiaries.

Importance: There has been insufficient research on the patient harms and costs associated with potential low-value procedures in the US Medicare population. Objective: To report the prevalence of adverse events associated with potential low-value procedures and the additional hospital length of stay (LOS) and costs. Design Setting and Participants: This is a retrospective cohort study using Medicare fee-for-service claims between January 2016 to December 2018. Participants were aged 65 years or older. Procedures were selected if they had previously published indicators of low-value care, including knee arthroscopy, spinal fusion, vertebroplasty, percutaneous coronary intervention (PCI), carotid endarterectomy, renal stenting, and hysterectomy for benign conditions. Analysis was conducted from July to December, 2020. Main Outcomes and Measures: For inpatient procedures, the number and rate of admissions with a hospital-acquired condition (HAC) or patient safety indicator event (PSIs), as well as the unadjusted and adjusted difference in mean LOS and Medicare costs between admissions with and without a HAC/PSI. For outpatient procedures, we report the number of claims where the beneficiary had an unplanned hospital admission within seven days and the number of these admissions with a HAC/PSI. Results: There were 573 351 patients included in the study, with 617 264 procedures; the mean (SD) age was 74.2 (6.7) years, with 320 637 women (55.9%), and mostly White patients (520 735; 90.8%). Among the 197 755 claims for the inpatient procedures, 231 had an HAC and 1764 had a PSI. Spinal fusion was associated with the most HACs (123 admissions) and PSIs (1015 admissions). Overall, HACs during a PCI admission were associated with the highest adjusted additional mean LOS (17.5 days; 95% CI, 10.3-23.6), with also the highest adjusted additional mean cost ($22 000; 95% CI, $9100-$32 600). There were 419 509 included outpatient procedures, and 7514 (1.8%) had an unplanned admission within 7 days. A total of 17 HACs and PSIs occurred in these admissions. Conclusions and Relevance: In this cross-sectional cohort study of Medicare fee-for-service claims, patients receiving potential low-value care were exposed to risk of unnecessary harm associated with higher cost and LOS.

First steps towards price transparency: comparability of online out-of-pocket tools from Australian private health funds.

Objective The aims of this study were to compare and contrast the information three Australian private health insurance funds (HCF, Bupa and Medibank) have provided on their online out-of-pocket cost tools and to consider the implications this has for price transparency in Australia. Methods Website data were downloaded from HCF, Bupa and Medibank on 18 February 2019. The information and statistics provided on these pages were reviewed, and the procedures compared across funds if their pages had referred to the same Medicare Benefits Schedule (MBS) item(s). Information was extracted regarding descriptions of the claims data used, the types of statistics provided, the out-of-pocket estimates, the total procedure cost, the MBS items referenced and the assumptions the funds described on their pages. Results HCF specified the MBS items used to select the claims data for their estimates, whereas Bupa and Medibank only referred to common MBS items associated with the procedures. On average, HCF had 1.44 more MBS items listed than Bupa and 2.08 more than Medibank. The funds organised procedures differently, such as HCF providing separate cost estimates for vaginal, abdominal and keyhole hysterectomy compared with Medibank's single estimate for hysterectomy costs. Conclusions These funds have started to address the need for transparent out-of-pocket cost information, but the differences across these pages demonstrate complexities and the potential obfuscation of cost data. What is known about the topic? Out-of-pocket costs are highly variable and patient 'bill shock' is an increasing concern in Australia. Private insurance funds have created online tools to share procedure cost estimates based on their claims data. What does this paper add? This is the first review of Australian insurance funds' price transparency tools. The cost information is difficult to interpret both within funds (for members) and across funds (for the system). What are the implications for practitioners? Policy makers will need to consider the complexities and presentation options for cost estimates within the health system if they move ahead with a public price transparency tool. There is still a requirement for cost information that can facilitate price shopping across providers and funders.

Measuring 21 low-value hospital procedures: claims analysis of Australian private health insurance data (2010-2014).

OBJECTIVE: To examine the prevalence, costs and trends (2010-2014) for 21 low-value inpatient procedures in a privately insured Australian patient cohort. DESIGN: We developed indicators for 21 low-value procedures from evidence-based lists such as Choosing Wisely, and applied them to a claims data set of hospital admissions. We used narrow and broad indicators where multiple low-value procedure definitions exist. SETTING AND PARTICIPANTS: A cohort of 376 354 patients who claimed for an inpatient service from any of 13 insurance funds in calendar years 2010-2014; approximately 7% of the privately insured Australian population. MAIN OUTCOME MEASURES: Counts and proportions of low-value procedures in 2014, and relative change between 2010 and 2014. We also report both the Medicare (Australian government) and the private insurance financial contributions to these low-value admissions. RESULTS: Of the 14 662 patients with admissions for at least 1 of the 21 procedures in 2014, 20.8%-32.0% were low-value using the narrow and broad indicators, respectively. Of the 21 procedures, admissions for knee arthroscopy were highest in both the volume and the proportion that were low-value (1607-2956; 44.4%-81.7%).Seven low-value procedures decreased in use between 2010 and 2014, while admissions for low-value percutaneous coronary interventions and inpatient intravitreal injections increased (51% and 8%, respectively).For this sample, we estimated 2014 Medicare contributions for admissions with low-value procedures to be between $A1.8 and $A2.9 million, and total charges between $A12.4 and $A22.7 million. CONCLUSIONS: The Australian federal government is currently reviewing low-value healthcare covered by Medicare and private health insurers. Estimates from this study can provide crucial baseline data and inform design and assessment of policy strategies within the Australian private healthcare sector aimed at curtailing the high volume and/or proportions of low-value procedures.

Low-value care in Australian public hospitals: prevalence and trends over time.

OBJECTIVE: To examine 27 low-value procedures, as defined by international recommendations, in New South Wales public hospitals. DESIGN: Analysis of admitted patient data for financial years 2010-2011 to 2016-2017. MAIN OUTCOME MEASURES: Number and proportion of episodes identified as low value by two definitions (narrower and broader), associated costs and bed-days, and variation between hospitals in financial year 2016-2017; trends in numbers of low-value episodes from 2010-2011 to 2016-2017. RESULTS: For 27 procedures in 2016-2017, we identified 5079 (narrower definition) to 8855 (broader definition) episodes involving low-value care (11.00%-19.18% of all 46 169 episodes involving these services). These episodes were associated with total inpatient costs of $A49.9 million (narrower) to $A99.3 million (broader), which was 7.4% (narrower) to 14.7% (broader) of the total $A674.6 million costs for all episodes involving these procedures in 2016-2017, and involved 14 348 (narrower) to 29 705 (broader) bed-days. Half the procedures accounted for less than 2% of all low-value episodes identified; three of these had no low-value episodes in 2016-2017. The proportion of low-value care varied widely between hospitals. Of the 14 procedures accounting for most low-value care, seven showed decreasing trends from 2010-2011 to 2016-2017, while three (colonoscopy for constipation, endoscopy for dyspepsia, sentinel lymph node biopsy for melanoma in situ) showed increasing trends. CONCLUSIONS: Low-value care in this Australian public hospital setting is not common for most of the measured procedures, but colonoscopy for constipation, endoscopy for dyspepsia and sentinel lymph node biopys for melanoma in situ require further investigation and action to reverse increasing trends. The variation between procedures and hospitals may imply different drivers and potential remedies.

Developing indicators for measuring low-value care: mapping Choosing Wisely recommendations to hospital data.

OBJECTIVE: Low-value health care refers to interventions where the risk of harm or costs exceeds the likely benefit for a patient. We aimed to develop indicators of low-value care, based on selected Choosing Wisely (CW) recommendations, applicable to routinely collected, hospital claims data. RESULTS: We assessed 824 recommendations from the United States, Canada, Australia and the United Kingdom CW lists regarding their capacity to be measured in administrative hospital admissions datasets. We selected recommendations if they met the following criteria: the service occurred in the hospital setting (observable in setting); a claim recorded the use of the service (record of service); the appropriate/inappropriate use of the service could be mapped to information within the hospital claim (indication); and the service is consistently recorded in the claims (consistent documentation). We identified 17 recommendations (15 services) as measurable. We then developed low-value care indicators for two hospital datasets based on the selected recommendations, previously published indicators, and clinical input.

A methodological protocol for selecting and quantifying low-value prescribing practices in routinely collected data: an Australian case study.

BACKGROUND: Growing imperatives for safety, quality and responsible resource allocation have prompted renewed efforts to identify and quantify harmful or wasteful (low-value) medical practices such as test ordering, procedures and prescribing. Quantifying these practices at a population level using routinely collected health data allows us to understand the scale of low-value medical practices, measure practice change following specific interventions and prioritise policy decisions. To date, almost all research examining health care through the low-value lens has focused on medical services (tests and procedures) rather than on prescribing. The protocol described herein outlines a program of research funded by Australia's National Health and Medical Research Council to select and quantify low-value prescribing practices within Australian routinely collected health data. METHODS: We start by describing our process for identifying and cataloguing international low-value prescribing practices. We then outline our approach to translate these prescribing practices into indicators that can be applied to Australian routinely collected health data. Next, we detail methods of using Australian health data to quantify these prescribing practices (e.g. prevalence of low-value prescribing and related costs) and their downstream health consequences. We have approval from the necessary Australian state and commonwealth human research ethics and data access committees to undertake this work. DISCUSSION: The lack of systematic and transparent approaches to quantification of low-value practices in routinely collected data has been noted in recent reviews. Here, we present a methodology applied in the Australian context with the aim of demonstrating principles that can be applied across jurisdictions in order to harmonise international efforts to measure low-value prescribing. The outcomes of this research will be submitted to international peer-reviewed journals. Results will also be presented at national and international pharmacoepidemiology and health policy forums such that other jurisdictions have guidance to adapt this methodology.

Evidence for overuse of medical services around the world.

Overuse, which is defined as the provision of medical services that are more likely to cause harm than good, is a pervasive problem. Direct measurement of overuse through documentation of delivery of inappropriate services is challenging given the difficulty of defining appropriate care for patients with individual preferences and needs; overuse can also be measured indirectly through examination of unwarranted geographical variations in prevalence of procedures and care intensity. Despite the challenges, the high prevalence of overuse is well documented in high-income countries across a wide range of services and is increasingly recognised in low-income countries. Overuse of unneeded services can harm patients physically and psychologically, and can harm health systems by wasting resources and deflecting investments in both public health and social spending, which is known to contribute to health. Although harms from overuse have not been well quantified and trends have not been well described, overuse is likely to be increasing worldwide.

Quantitative Analysis of Axonal Branch Dynamics in the Developing Nervous System.

Branching is an important mechanism by which axons navigate to their targets during neural development. For instance, in the developing zebrafish retinotectal system, selective branching plays a critical role during both initial pathfinding and subsequent arborisation once the target zone has been reached. Here we show how quantitative methods can help extract new information from time-lapse imaging about the nature of the underlying branch dynamics. First, we introduce Dynamic Time Warping to this domain as a method for automatically matching branches between frames, replacing the effort required for manual matching. Second, we model branch dynamics as a birth-death process, i.e. a special case of a continuous-time Markov process. This reveals that the birth rate for branches from zebrafish retinotectal axons, as they navigate across the tectum, increased over time. We observed no significant change in the death rate for branches over this time period. However, blocking neuronal activity with TTX slightly increased the death rate, without a detectable change in the birth rate. Third, we show how the extraction of these rates allows computational simulations of branch dynamics whose statistics closely match the data. Together these results reveal new aspects of the biology of retinotectal pathfinding, and introduce computational techniques which are applicable to the study of axon branching more generally.