IJPDS International Journal of Population Data Science

https://doi.org/10.23889/ijpds.v8i1.1751.review.r1.reviewa

Timely provision of interventions is important for management of patients with ACS (sub-types include STEMI, NSTEMI and unstable angina). The authors discuss STEMI only but do not discuss the other ACS sub-types. Could the authors justify why the selected STEMI and not the other ACS sub-types?

Line 48: NSW is the most populous jurisdiction in Australia but not the largest (by size) jurisdiction which is WA. The same goes for Line 356.

Line 127: The dataset may include inter-state visitors who were hospitalised in NSW while on holidays. How was NSW resident determined from the dataset? Using birth jurisdiction may not be adequate as a person may have been born in one state but then moved to another state.

Lines 130 to 144: Were the same patients given the same de-identified ID across the 4 jurisdictions and by the AIHW? If this was done, could the authors please describe how this was achieved working across different jurisdictions where privacy issues may prevent sharing of personal information across borders. This is important especially for a data linkage journal where many of its readers face this challenge in cross-jurisdictional linkages.

Line 157: Geographic Remoteness – please describe briefly the 5 categories of remoteness.

Line 240: In Table 1 the difference is between “NSW Hospitals” and “All Hospitals + MBS”. Why did the authors select this combination as they have different exclusion criteria? Better pairings would have been “NSW Hospitals” vs “All Hospitals” or “NSW Hospitals+MBS” vs “All Hospitals+MBS”.

Please also check if “Aboriginality” is the correct term to use or if there is a more recent recommendation.

For completeness, please add “in years” for age in Table 1 and other Tables.

Line 242: In Table 2 the authors use the term “Interstate border” and this repeated across several other tables. Could the authors define “Interstate border”, are these located close to the border?

Line 274: The difference (%) in Table 4 probably represent percentage points rather than % difference (as they are differences between % rather than counts).

Line 323: The authors state “Incorporating non-NSW hospital records and MBS data increased enumeration of STEMI hospitalisations…” – how does inclusion of MBS data increase enumeration? MBS data indicates whether a coronary artery procedure was performed but does not indicate the diagnosis.

Supplementary material

Line 14: For completeness, please define ICD-10AM

https://doi.org/10.23889/ijpds.v8i1.1751.review.r1.dec

Dear Branislav Igic, Rachel Farber, Maria Alfaro-Ramirez, Michael Nelson , Lee Taylor :

Resent with reviewer comments now attached

We have reached a decision regarding your submission to International Journal of Population Data Science, "The impact of cross-jurisdictional patient flows on ascertainment of hospitalisations and cardiac procedures for ST-segment-elevation myocardial infarction in an Australian population.".

Please address the attached reviewers' comments and return to us: one clean and one tracked changes version of your revised manuscript, plus a point by point letter of response/rebuttal, by 25 August 2022.

Please also attend to minor typographical errors in Lines 59 (due ischemic), 68 (of management of) and 143 (Health Welfare).

Our decision is to: Resubmit for Review

Kind Regards

Merran

Merran Smith

22 August 2022

Dear Dr Smith,

Thank you for the opportunity to revise and resubmit our manuscript. We are grateful for the feedback given by the reviewer and yourself.

We have revised the manuscript in line with all the recommendations. Please find below an explanation of changes we’ve made (plain text) in response to the feedback (bold text).

We again confirm that this manuscript has not been published elsewhere and is not under consideration by another journal. All authors have approved the manuscript and agree with its submission to the International Journal of Population Data Science.

Please address all correspondence to Rachel Farber (Rachel.Farber@health.nsw.gov.au).

We thank you for your time and we look forward to hearing from you.

Yours sincerely,

Rachel Farber et al.

Editor comments:

Please also attend to minor typographical errors in Lines 59 (due ischemic), 68 (of management of) and 143 (Health Welfare).

Response: We have fixed all these typographical errors.

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Reviewer A comments:

Main document

Timely provision of interventions is important for management of patients with ACS (sub-types include STEMI, NSTEMI and unstable angina). The authors discuss STEMI only but do not discuss the other ACS sub-types. Could the authors justify why the selected STEMI and not the other ACS sub-types?

Response: We agree that there is value in examining similar benefits of cross-jurisdictional linkage for other ACS sub-types. For our study, we have focussed on STEMI because of the clear clinical pathway directed by the NSW state reperfusion strategy. Since STEMI is the most severe type of ACS, requiring urgent assessment and treatment at a cardiac catheterisation laboratory, which may require transport across a jurisdictional border. NSTEMI and unstable angina are also of interest from a health policy perspective, however, the models of care for these conditions are different to that of STEMI and should be looked at separately.

We have added the following text to the discussion:

Lines 391-397: “Our study focussed on STEMI because of the clear clinical pathway directed by the NSW state reperfusion strategy. Since STEMI is the most severe type of ACS, and recommendations include urgent assessment and treatment at a cardiac catheterisation laboratory, which may require transport across a jurisdictional border. Future work should examine cross-border flows and treatment pathways for other types of ACS, such as non-ST-elevation myocardial infarction and unstable angina”.

Line 48: NSW is the most populous jurisdiction in Australia but not the largest (by size) jurisdiction which is WA. The same goes for Line 356.

Response: We have rephrased these sentences to:

Lines 50: “New South Wales (NSW) is the most populous jurisdiction in Australia and is home to one third of the Australian population (Figure 1)”

Lines 382: “The strength of this study is that it is a large population-based study.”

Line 127: The dataset may include inter-state visitors who were hospitalised in NSW while on holidays. How was NSW resident determined from the dataset? Using birth jurisdiction may not be adequate as a person may have been born in one state but then moved to another state.

Response: NSW residence status was derived from the geocoded address information reported on the first hospital record with complete information. We have added the following definition to the Methods section.

Lines 176-178: “NSW resident: Person with a Statistical Local Area or Statistical Area of residence in NSW as defined by the Australian Bureau of Statistics [25], derived from residential address information on the first hospital record for a STEMI Hospitalisation”.

Lines 512-514: [25] Australian Bureau of Statistics. Australian Statistical Geography Standard (ASGS) [Available from: https://www.abs.gov.au/websitedbs/D3310114.nsf/Home/Geography; Accessed: 08 Aug 2022].

Lines 130 to 144: Were the same patients given the same de-identified ID across the 4 jurisdictions and by the AIHW? If this was done, could the authors please describe how this was achieved working across different jurisdictions where privacy issues may prevent sharing of personal information across borders. This is important especially for a data linkage journal where many of its readers face this challenge in cross-jurisdictional linkages.

Response: Yes, all records for a patient were given the same Project Person Number by the AIHWDLU for all datasets in the study. We have added the following explanation to the data linkage section of the Methods:

Lines 146-154: “In summary, jurisdictional data linkage units carried out linkage of their respective datasets and assigned a jurisdictional Project Person Number (PPN) to groups of records for the same person in the Study Population within the jurisdiction. Jurisdictions provided jurisdictional PPNs and personal identifiers to the AIHWDLU, which linked the jurisdictional datasets, MBS and NDI records and assigned a national PPN. The AIHWDLU supplied the national PPNs to the respective jurisdictions, which supplied the jurisdictional content data with national PPNs to the investigators. AIHWDLU supplied MBS and NDI data with national PPNs directly to the investigators. The investigators compiled the contributed datasets into a single dataset for analysis.”

Line 157: Geographic Remoteness – please describe briefly the 5 categories of remoteness.

Response: We have added the following description of the 3 categories of remoteness used in the study:

Lines 168-174: “ARIA+ is a continuous score based on the road distance to service towns of different sizes. We categorised geographic remoteness into three categories of accessibility: Major Cities defined as areas with relatively unrestricted accessibility (score less than or equal to 0.20); Inner Regional areas defined as those with some restrictions to accessibility (score 0.20 to 2.40); and Outer Regional & Remote areas defined as those with significantly restricted accessibility to goods (score greater than 2.40)”.

Line 240: In Table 1 the difference is between “NSW Hospitals” and “All Hospitals + MBS”. Why did the authors select this combination as they have different exclusion criteria? Better pairings would have been “NSW Hospitals” vs “All Hospitals” or “NSW Hospitals+MBS” vs “All Hospitals+MBS”.

Response: Our main study aim was to investigate the benefits of a cross-jurisdiction linkage project against a single jurisdiction linkage project to enumerate STEMI and STEMI treatments for NSW residents. As such, we highlight the comparisons between the “NSW Hospitals” and “All Hospitals + MBS” cohorts in the tables and text as these represent a comparison of single and cross-jurisdiction linkage projects.

We have provided four comparisons, so readers that are more interested in specific benefits of including hospital data from other jurisdictions versus inclusion of MBS data may make those comparisons. We discuss the individual benefits of including cross-jurisdiction hospital data and MBS data in lines 361-369.

We have added the following clarifications to the Methods:

Lines 212-214: “The NSW Hospitals and All Hospitals + MBS cohorts provide a comparison of single jurisdiction and cross-jurisdiction linkage projects to enumerate STEMI and STEMI treatments for NSW residents.”

We have also amended the following statements in the Results:

Lines 267-268 “The addition of cross-jurisdictional data increased the enumeration of STEMI Hospitalisations for NSW residents by 8%”.

Lines 292-293: “Cross-jurisdictional data slightly increased angiography and PCI rates for all NSW, and the increases were greatest for residents of regional and remote areas (Table 4 & 5).”

Lines 309-310: “Cross-jurisdictional data dramatically increased angiography and PCI rates for border LHD residents.”

Lines 323-324: “In contrast to angiography and PCI, the addition of cross-jurisdictional data resulted in a small increase in CABG rates for all LHDs.”

Please also check if “Aboriginality” is the correct term to use or if there is a more recent recommendation.

Response: Aboriginality is a culturally appropriate term for describing the Aboriginal status of individuals (https://www1.health.nsw.gov.au/pds/ActivePDSDocuments/GL2019_008.pdf). We have not made any changes to the text.

For completeness, please add “in years” for age in Table 1 and other Tables.

Response: Changed as requested.

Line 242: In Table 2 the authors use the term “Interstate border” and this repeated across several other tables. Could the authors define “Interstate border”, are these located close to the border?

Response: Correct, these Local Health Districts have a border with another Australian jurisdiction.

To make this meaning clearer in Tables 2, 3, 7, 8, & 9, we have changed the labels from “No interstate border” and “Interstate border” to “No border with another Australian jurisdiction” and “Border with another Australian jurisdiction” respectively.

Line 274: The difference (%) in Table 4 probably represent percentage points rather than % difference (as they are differences between % rather than counts).

Response: Correct. To make this clearer, we have changed the label to “Percentage point change” in Tables 4, 5, 6, 7, 8, 9.

We also now explicitly refer to these as percentage points in the text when referenced.

E.g.,

Lines 291-292 “For total NSW, the additional data increased the angiography rate by 2.5 percentage points (Table 4) and PCI rate by 2.3 percentage points (Table 5)”.

See also lines 33-34, 294, 309-311, 320-321, 352, 355.

Line 323: The authors state “Incorporating non-NSW hospital records and MBS data increased enumeration of STEMI hospitalisations…” – how does inclusion of MBS data increase enumeration? MBS data indicates whether a coronary artery procedure was performed but does not indicate the diagnosis.

Response: We have rephrased this sentence to the following:

Lines 349-352: “Incorporating non-NSW hospital records increased enumeration of STEMI hospitalisations by 8%, and together with MBS data, the percentage of STEMI hospitalisations where procedures were undertaken within 7 days of admission by 2.5 percentage points.”

Supplementary material

Line 14: For completeness, please define ICD-10AM

Response: We have included “International Statistical Classification of Diseases and Related Health Problems, Australian Modification” and “Australian Classification of Health Interventions” as table footnotes (lines 13,14,16) and the following reference to the supplementary materials:

[1] Independent Hospital Pricing Authority. 2022. ICD-10-AM/ACHI/ACS Tenth Edition [Available from: https://www.ihpa.gov.au/publications/icd-10-amachiacs-twelfth-edition; Accessed: 08/08/2022].

https://doi.org/10.23889/ijpds.v8i1.1751.review.r2.reviewa

The penultimate sentence in the discussion justifies why the authors looked at STEMI and not the other ACS sub-types. This might be better in the introduction to provide context, especially to those not familiar with ACS management.

Otherwise, happy for this paper to be accepted. There is no need for this paper to be reviewed again

https://doi.org/10.23889/ijpds.v8i1.1751.review.r2.dec

Dear Branislav Igic, Rachel Farber, Maria Alfaro-Ramirez, Michael Nelson , Lee Taylor :

We have reached a decision regarding your submission to International Journal of Population Data Science, "The impact of cross-jurisdictional patient flows on ascertainment of hospitalisations and cardiac procedures for ST-segment-elevation myocardial infarction in an Australian population.", and are delighted to inform you that our decision is to: Accept Submission.

We look forward to working with you through the next stages towards final publication.

Please get in touch if you have any queries going forward. Thank you.

Kind regards

Merran Smith

IJPDS, Section Editor