‘better health - spiral.imperial.ac.uk:8443 · web viewuse this word document for all...

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Analysis and Commentary: Patient segmentation in integrated care:

Theoretical framework and practical applications

ANALYSIS & COMMENTARY

Patient Segmentation Analysis

Offers Significant Benefits

For Integrated Care And Support

Abstract

Integrated care aims to organize care around the patient instead ofrather than

the provider. It is therefore crucial to understand differences acrossbetween

patients and their needs. Segmentation analysis that usesing big data can

help divide a patient population into distinct groups, which can then be

targeted with bespoke care models and intervention programs tailored to their

needs. In this article we explore the potential applications of patient

segmentation in integrated care. We propose a framework for population

strategies in integrated care— – whole populations, subpopulations, and high-

risk populations— – and show how patient segmentation can support these

strategies. Through international case examples, we illustrate practical

considerations such as choosing a segmentation logic, accessing data, and

tailoring care models. Important issues for policy makers to consider are

trade-offs between simplicity and precision, between customized and off-the-

shelf solutions, and the availability of linked data sets. We conclude that

1

JF, 03/02/16,

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lw, 03/07/16,

AU: The title was revised to give the reader a more specific sense of the paper’s findings and main message. Titles for articles of this type can be four lines with no more than 30 characters per line, including spaces. -------OK


segmentation can provide many benefits to integrated care, and we

encourage policy makers to support its use.

INTRODUCTION

Integrated care, which aims to coordinate a patient’s care across

different settings and providers, has taken center stage in most Western

health systems.[1] (1). In England, the drastic reform introduced by the Health

and Social Care Act of 2012 renewed the focus on integrated, patient-

centered care by emphasizing that “care is integrated around the needs of

the patient.”[2] (2). In the United StatesUS, similarly radical changes to the

health care system in the form of the Affordable Care Act focus on integrating

care through the development of new coordination programs and financing

systems.[3] (3).

To truly integrate care around the patientcenter care around the

patient, his or hereach patient’s specific care needs and other characteristics

need tomust be addressed. While it is practically impossible to develop care

models and intervention programs for each individual, they programs can be

created for groups of patients with largely similar characteristics. The creation

of these groups is known as patient segmentation. Segmentation divides a

patient population into distinct groups—, each with specific needs,

characteristics, or behaviors—, to allow care delivery and policies to be

tailored forto these groups.[4,5] (4, 5).

The idea of segmenting patients for integrated care is not new. Already

iIn 1970, Kaiser Permanente co-founder Sidney R. Garfield, Kaiser

2

JF, 03/04/16,

AU: Please reword to clarify whether the meaning is “To truly center care around the patient” or “To truly integrate all of a patient’s care.” -------OK - have replaced the text with option 1


Permanente’s cofounder, described how Kaiser Permanente’stheir integrated

care model distinguishes distinguished between sick, well, worried well, and

early sick patients to tailor medical and preventative services for the different

groups.[6] (6). However, the exponential growth in health care big data,[7,8]

(7, 8), together with the developments in data- mining tools,[9] (9), provides

new opportunities to use data for segmentation analysis.

Data from administrative systems or electronic health records (EHRs)

can be used to allocate patients to segments—based, for example, based on

their long-term conditions—, and analyze costs and outcomes per segment.

There are also exist a range of off-the-shelf tools for patient segmentation

data analysis, which varying in type and sophistication[10-13]10–19] (for more

details, see onlinetechnical aAppendix 2 (10-19) for more details).[1420] The

Johns Hopkins Adjusted Clinical Groups® (ACG) Ssystem uses a granular

system of diagnosis code mapping as the basis for different groupings.[132]

(13). The Community Assessment Risk Screen CARS score provides a

simple method forto allocatinge patients to one of ten risk levels.[103] (10),

Andwhile the 3M™ Clinical Risk Groupsing (CRG) tool system distributes

patients amongover 296 hierarchical Bbase clinical risk groupsCRGs for a

more detailed risk analysis.[110] (11).

In this articlepaper we aim to describe how these types of data-driven

segmentation can be applied in integrated care. We propose a framework that

outlines the potential applications of segmentation in integrated care,

andwhich we illustrate its use through international case examples. We then

explore the practical considerations involved inaround segmentation analysis

through three detailed case studies. Based on thisthe case studies, we

3

JF, 03/04/16,

AU: If the concept of “hierarchical base” must be restored, please add some language to clarify what is hierarchical and what is based on what else. -------OK - no need

JF, 03/04/16,

AU: Reworded for consistency with the item in Note 11. -------OK

JF, 03/04/16,

AU: Each reference to the Appendix in the paper must be accompanied by a callout to a note containing the standard instructions for locating the Appendix. Thus we added a new Note 20 and renumbered subsequent notes. ----- OK see previous note on references

JF, 03/04/16,

AU: We assumed that you wanted to call Notes 10–19 out here. If that is not correct, the notes are not in numerical order, since they would appear in this order: 9, 13, 10, 11, 21… However, below you referred to Notes 10–19 and Note 14 in the same place, which is redundant. Please verify that each note in the paper now cites the correct item in the correct place, or revise the notes in both the text and the notes section as needed. ---- Apologies for the mix up - I misunderstood the endnote reference for the appendix and thought I needed to provide reference ndnotes for the appendix here. Have deleted the ones that did not apply and edited all the endnotes throughout the document.

JF, 03/04/16,

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discuss why and how policy makers may encourage the use of data for

segmentation in practice.

A Framework For The Application Of Patient Segmentation In Integrated

Care

Integrated care can be organized in a variety of ways. The following

three broad levels of integration have been described in the literature: macro-,

meso-, and micro-level integration.[21–2415-18] (20-23). For each level, a

corresponding population strategy can be identified.

Whole Population:

Macro-level integration applies to the whole population. Though the

types of providers included in a macro-levelthe program may vary, these

programsmodels aim to integrate care for all patients. Examples are

integrated care organizations such as Kaiser Permanente in the United

StatesUS, which provide integrated services for their entire covered

population.

Subpopulation:

Meso-level integration provides integrated care services to a specific

subpopulation. Often this subpopulation is based on a long-term condition (for

example,e.g. diabetes, or mental healthdementia) or age (such as e.g.

patients older than seventy-fiveover 75 years of age), which allowsing

specialist services to be included in the integrated care package. An example

is bundled payments in the Netherlands, where care providers receive an

one-off annual payment to manage and deliver care for a group of patients

with a specific conditiondeliver all care required for a specific condition.[2519]

(24).

4

JF, 03/04/16,

AU: Please reword to clarify the meaning—for example, “all care for a subpopulation whose members all have a specific condition”? -------I have edited it, hope it's better.

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AU: Please replace “mental health” with the name of a second condition. -------Done

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AU: Subheadings such as this one need to be relatively short, so we condensed it as shown. -------OK


High-Risk Population:

Micro-level integration focuses on selected individuals deemed to be at

high -risk of certain outcomes, such as an emergency unplanned

hospitalizationadmission. Instead ofRather than integrating care across the

entire care delivery system, this type of integrated care relies on teams or

individuals whothat coordinate services and provide case management. In the

English National Health ServiceNHS, primary care providers are encouraged

to identify patients through risk stratification and proactively manage their

conditions and coordinate their care with other care providers.[2620] (25).

Identifying And Understanding The Target Population

Patient segmentation can support these three population strategies in

the following two ways: it can help to identify a target population, and it can

help [please provide]to understandprovide detailed insights into the target

population (for [please provide], an overview of the framework, see the

onlinetechnical aAppendix 1).[1420]

Understanding The Population

Understanding the population is particularly important for macro-level

integration, where an entire population is included indiscriminately, assince

care needs will vary significantly across the members of the population.

Through patient segmentation, the different needs of the population can be

identified, and tailored policies and budgets can be set for homogeneous

patient groups. The “Better Health for London” report, developed by the

London Health Commission, segments the entire London population of

London into fifteen15 groups, around which cross-settingmulti-stakeholder

5

JF, 03/04/16,

AU: Please briefly explain where requested what the reader will find in the Appendix that’s relevant here (for example, “for a list of possible target populations, see…”). ------- Done

JF, 03/04/16,

AU: Please briefly explain where requested—help who understand the population? -------I have edited it, hope it makes more sense but please feel free to edit

JF, 03/04/16,

AU: Please reword to clarify the meaning—for example, “such as a visit to the emergency department” or “such as an unplanned hospitalization.” ------- I have edited it


population health initiatives are organized[10–19] (14). [21] (for more details,

see technical aAppendix 2 (10-19) for more details).[2014]

Meso-level integrated care models, which focus on a specific

subpopulation, can use segmentation to choose theis subpopulation.

Delaware’s State Health Care Innovation Plan segments the state’s

population and uses this information to select priority subgroups for two

focused interventions,: “‘improved care coordination”’ for patients with multiple

long-term conditions or mental health needs, and overall “‘effective diagnosis

and treatment”’ for people with no long-term care needs.[1522] (15).

For meso-level integratedion care, segmentation can also help health

professionals [please provide]to better understand the targeted subpopulation.

While the care needs of a defined subgroup will not be as diversege as much

as those of for an entire population, there will still be significant variation

across members of the subgroup. Kaiser Permanente’s Senior Segmentation

Algorithm segments the over-65 population over age sixty-five into four

groups, and care priorities are set for each segment.[1623] (16). The segment

assignmentallocation is included in the patient’s EHRelectronic medical

record, and it prompts medical specialists to take certain actions that are

tailored to the segment’s specific needs. The ValCrònic pilot program in Spain

focuses on the subpopulation with long-term conditions, which is segmented

by risk level to adjust the intensity of telemonitoring interventions.[17,1824,25]

(17, 18).

Micro-level integration requires high-risk patients to be identified. The

Counties Manukau Health systemdistrict health board in New Zealand are is

including an automated risk score in theirits e-summary health record, which

6

JF, 03/04/16,

AU: Following up on the comment above, if the official name is Counties Manukau Health, please use that name instead of just “Counties Manukau” throughout your paper. -------the district health board (a type of local authority in NZ that provides healthcare ) is called Counties Manukau, so I suggest keeping it as is.

lw, 03/04/16,

AU: Please confirm accuracy of edit. The information was derived from the following URL: http://www.countiesmanukau.health.nz/ -------edited

JF, 03/04/16,

AU: You refer to it as a pilot below, so we added that word here, where you first mention the program. -------OK

JF, 03/04/16,

AU: This is the term you use everywhere else in your paper. -------OK

JF, 03/04/16,

AU: Please briefly explain where requested—help who understand the subpopulation? -------edited

JF, 03/04/16,

AU: A search through the online item cited in Note 15 did not turn up this quote. Please either omit the quote marks or provide a phrase that does appear in the item in Note 15. -------edited

JF, 03/04/16,

AU: Do you mean to cite all of these notes, or just Note 14, which is the Better Health for London report? ------- see previous comment on refernces for appendix - changed it to just reference Better Health for London

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AU: Please add a brief explanation of “cross-setting” to the text. ----- I have edited the language all together to make it clearer - hope this works


is available to all system care providers across care settings.[1926] Based on

the patient’s risk stratum that the patient is in, different care management

interventions are offered to improve outcomes and reduce emergency

admissionshospitalizations.

In addition to identifying high-risk individuals, segmentation can also

provide insights into the risk strata themselves. Risk stratification only

provides only a one-dimensional view of the population, and segmentation

can help [please provide]integrated care initiatives better understand what the

actual needs are of the identified high-risk patients’ actual needs are. As

described above, the ValCrònic program segments a population by risk and

long-term condition. By segmenting high- and medium- risk patients based on

their long-term conditions, tailoredmore bespoke interventions can be offered,

such as condition-specific education and biometric devices.[17,1824,25] (17,

18).

Practical Applications Of Segmentation In Integrated Care

There are a number of practical issues to consider when applying

segmentation, including data requirements, segmentation logic, and what

practical use should be made of the informationhow the segment information

can be used to deliver care. This section of the article explores these

considerations through three case studies. First, the Better Health for London

initiative provides an example of how an analysis of the segmentation of a

whole population segmentation analysis can provide insights to informsupport

macro-level policy decisions. Second, the ValCrònic pilot program in Spain

focuses on people with long-term conditions, and uses segmentation to tailor

its health service approachinterventions for this subpopulation. Third, the

7

Margaret Saunders, 03/06/16,

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Margaret Saunders, 03/06/16,

Aus: please clarify – practical use of the data on patients? Or information gleaned from segmentation? ---- see above

JF, 03/06/16,

AU: If the edited version has distorted the meaning, please reword to clarify the point. ---- have edited it but please change if it still is unclear..

JF, 03/06/16,

AU: Please briefly explain where requested—help who understand the subpopulation? ----- done

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AU: As above, please reword to clarify the meaning—for example, “visits to the emergency department” or “unplanned hospitalizations.” -------edited

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Counties Manukau Health system example demonstrates how risk-based

patient segmentation can be used as a case-finding tool for high needs

patients.

Part of the information presented below is based on personal

communications with people in the organizations of the case studies.

‘Better Health For London’ (Whole Population Segmentation)

“Better Health for London,” a report developedproduced by the

London Health Commission, applies patient segmentation to develop patient-

centered, needs-based care for everyone.[1421] (14). It divides the whole

London population into 15 patient groups (see exhibit 1), createsing a holistic

view of the population’s needs to support integrated population health

initiatives for integrated care (Exhibit 1).

The segmentation model was adapted from the Whole Systems

Integrated Care (WSIC) project in North West London, which uses a similar

segmentation approach.[27] (26). The development of the segments was

partially data -driven. A purpose- built, one-off database was constructed for

one of the London regions, that linkeding administrative data for nearly

200,000 patients from primary, secondary, mental health, community, and

social care settings for nearly 200,000 patients. This provided a detailed view

of the costs, diagnoses, and other characteristics at the patient level. A

decision- tree analysis was used to determine which characteristics, such as

morbidities or age groups, were significant predictors of total cost and should

be used for the segmentation.

To determine the final segments, Tthe results from the data analysis

were considered in combination with the followinga number of practical

8

JF, 03/06/16,

AU: Or is the point that it “uses” a holistic view? ----- 'creates' works

JF, 03/06/16,

AU: Some condensing to avoid repeating in the text too much information from the exhibit notes, where the segmentation must be explained. -- ok

JF, 03/02/16,

AU: Vancouver and HA require that personal communications appear in the text where relevant, following this format: “(Evan Marks, chief strategy officer, Healthgrades, personal communication, September 16, 2015).” Please add the relevant parenthetical citations to personal communications where needed. We omitted this sentence since you will provide specific information below.

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AU: Please reword to clarify what cases the tool finds (for example, patients with a particular condition?). ---- edited


requirements to determine the final segments:[1421] (14): Patients within a

segment need to have broadly similar needs, considered holistically across

physical, mental, and social needs.; in general, Ppatients need to generally

remain in the same segment over time, to allow for long-term care planning.;

Hhealth care professionals need to be able to assign a patient to a segment.;

and Tthere mustneeds to be the potential to set financial budgets per

segment.

Following the “Better Health for London” report, thirteen

transformation teams programs were organized around the segments to

achievedeliver on the goalsaspirations of the report. The Healthy London

Partnership, was established in May 2015, and broughtbrings together

providers, commissioners, and representatives of public health and other

health organizations into thirteen13 transformation programs.[28] (27). These

programs are intendedaim to integrate and improve care for specific

segments, such as children, cancer patients, people with mental health

conditions, andor the homeless. For people in the healthy segments, there is

a program to encourage healthy behavior and prevent the development of

long-term conditions, while, and for patients with long-term conditions, the

focus is on improving self-management. By bringing together different

stakeholders around a defined group of patients with similar needs, care can

be integrated and tailored.

ValCrònic Program In Valencia (Subpopulation Segmentation)

ValCrònic is a program initiated by the Health Agency of Valencia,

Spain, and Telefónica, with the aim of integrating and improving care for a

subpopulation: patients with long-term conditions.[1825] (18). It was

9

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AU: Are the transformation teams mentioned here are the same as the transformation programs mentioned below? If so, please use one term consistently throughout your paper, to help the reader follow your argument, and move the number “thirteen” up from below. If not, please clarify how the two differ. --- edited


implemented in 2011 as a pilot covering four health centers in Valencia;, with

another two health centers joined the programenrolling later.[29] (28). An

important focuspart of this integrated care model isfocuses on preventing

complications of long-term conditions,ion of [please provide], which is carried

out through telemonitoring and education. These interventions are tailored to

the patient’s needs using a segmentation approach.

The ValCrònic program relies on a shared electronic primary care

record, called Abucasis, which brings together demographic data; information

about vaccinations; and data from primary care and , demographic data,

prescribing providers and on, hospital discharges and other activity, and

vaccinations.[29] (28). It is accessible to primary and secondary care

providers, and theis information exchange between settings is a crucial

enabler for the integration of care. In addition, the care records are used infor

the telemonitoring intervention, to identify patients with long-term conditions,

allocate them to different segments, upload the patient-recorded

measurements, and monitor outcomes.

The pilot program segments patients using the CARS (Community

Assessment Risk Screen) risk score, which predicts a patient’s risk of hospital

admission based on the following three simple criteria: having had a hospital

admission in the previous six6 months, the number of long-term conditions,

and having five5 or more prescriptions.[103] (10). Two benefits of using Tthis

method arehas the benefit that the scoreit can be easily calculated from

routine data in the EHRelectronic health record, and the methodit is free to

use.

10

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In 2015 a new stratification method, Clinical Risk Groups, hwas been

validated for the Valencia region, the Clinical Risk Groups (CRGs). Developed

by the 3M Company, Tthis is a more complex methodology, developed by the

3M Company, which that—as noted above—allocates patients to one of 269

hierarchical base clinical risk groupsCRGs.[1110] (11). Compared to the

Community Assessment Risk Screen, The cost of using the cClinical rRisk

gGroupCRG system costsis much more to usehigher than the Community

Assessment Risk ScreenCARS scale, but itsthe widely used standardized

approach makes multicenter or international studies possible. Nevertheless,

our analysis showed that the two risk scoring methods produce largely similar

results. (Domingo Orozco-Beltran, associate professor, Department of

Medicine, Cathedra of Family Medicine, University Miguel Hernandez,

personal communication, September 9, 2015).

In addition to the patient risk score, segments in the ValCrònic program

are also defined by the presence of the following four long-term conditions:

type 2 diabetes, chronic obstructive pulmonary diseaseCOPD, heart failure,

and hypertension[2418] (see eExhibit 2) (18). These conditions and their

combinations were identified as the most prevalent and costly.[29,30] (28, 29).

Segmenting by condition allows interventions to be developed for a specific

conditiondisease. More importantly, the programs are also get adapted forto

different combinations of conditionsdiseases, which addressesing important

multimorbidity issues.

In practice, the segmentation is used to deliver a highly tailored

telemonitoring and education intervention. The level of risk determines the

intensity of the intervention. Patients allocated to the highest risk stratum

11

JF, 03/06/16,

AU: If the analysis is not yours, please reword as needed and add a citation to the analysis by someone else, renumbering notes in the text and in the notes section as needed. --- done

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AU: Please reword here as needed for consistency with the final wording about these risk groups above (see the comment for you there). ----- ok


receive a tablet personal computerPC for communicating with their primary

care physician, disease-specific biometrical devices, telemonitoring, and

education and support for self-care.[29] (28). Patients atin the lowest risk level

are provided with communication and education through a web portal only.

The segment’s morbidity profile determines the educational program that is

created for patients, as well as which specific biometric devices are made

available. These can include monitors for blood pressure, blood glucose

levels, or heart rate.

The telemonitoring and education initiative is part of ValCrònic’s

integrated care program. The measurements from the biometric devices are

uploaded to the patient’s EHRelectronic health record, where primary and

secondary care providers can access them. If values fall outside

recommended thresholds, an alert is generated for the primary care physician

to allow for proactive intervention and coordination of care.

A study that followeding 200 patients in the program forover one year

in the program showed a 51 percent% reduction in the use of emergency

primary care services, and a 32 percent% reduction in the use of emergency

acute care during that timecompared to the year before.[301] (30). In addition,

patients have reported a high level of satisfaction with the program, with 86

percent% of patients saying that itthe program helped them understand their

disease better.[1724] (17).

At- Risk Individuals In Counties Manukau Health System (High-Risk

Population Segmentation)

Counties Manukau is one of twenty district health boards that fund and

provide public health services in New Zealand. Counties Manukau is in the

12

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AU: If the added wording doesn’t give the correct timeframe for the two reductions, please revise as needed to clarify the point. --- edited


process of an ambitious Ssystem Iintegration Pprogram, which aims to

integrate services across primary, secondary, and community care.[1926]

(19). As part of this effort, they health board hasve introduced a risk

stratification procedure to identifyfind Aat- Rrisk Iindividuals (ARI). The aim of

this program is to allow primary care providers to identify patients at risk of

poor health outcomes, and proactively provide them with patient-centered

care plans and care coordination services.

General Primary care practices within Counties Manukau are starting

to usetilize the Combined Predictive Risk Model (CPRM) to stratify their

enrolled populations. The modelCPRM was developed by the Greater

Auckland Integrated Health Network, and predicts an individual’s risk of an

unplanned hospital admission in the next six months.[312] (31). It is based on

data from a large range of sources, including patient registers, primary care

consultation data, and hospital care data.

To develop this risk algorithm, a one-off, annonymized linked data set

was created.[312] (31). However, implementation of the algorithm in practice

requires primary care providers to have up-to-date access to patient-

identifiable linked data sets in which the patients are identified. The data

governance and information technologyIT requirements related toaround this

identificationdata provision are currently being addressed. Until the risk

algorithmtool becomes universally available, the primary care practices are

using a set of logic rules to identify eligible individuals, based on criteria such

as the number of long-term conditions, diagnostic results indicating unstable

conditions, and indicators of mental health or social risks. (Claire Naumann,

13

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AU: If “general practices” here is the same thing as “primary care practices” below, please use “primary care practices” here for consistency. If they aren’t the same, please briefly explain in the text how they differ. ---- edited


transformation manager integrated care, Counties Manukau Health, personal

communication, September 3, 2015).

The program for at- risk individualsARI program is an example of

micro-level integrated care, in whichwhere a dedicated team or person

integrates all of the care for a high-risk individual. The risk algorithm stratifies

patients into two groups: patients at very high risk patients, and those at risk

individuals.[1926] (19). Very high risk pPatients at very high risk receive

intensive case management, including home visits, care planning and

coordination across care settings, monitoring, and review. Patients identified

as at risk are assigned a named care coordinator from their primary care

practice, who develops a personal care plan with them. Patients’ An e-

sSummary health records, as well as the and personal care plans, can be

viewed by providers across the system.

The program for at- risk individualsARI program was started in 2014,

and as of [please provide date]March 2016 currently has eighty-

seven87ninety-nine participating primary care practices were participating in

the program[33] (32) and over 2014,000 patients were enrolled in it (Claire

Naumann, transformation manager integrated care, Counties Manukau

Health, personal communication, March 5, 2016). The intervention for patients

atthe very high risk patients is a continuation of the VVvery HhHigh IiIntensity

UuUser program, which saw a 45 percent% reduction in the number of

emergency care presentations and a 35 percent% reduction in acute care bed

days, according toin a study that compareding the six- month periods before

and after enrollment in the program.[324] (33).

Policy Implications

14

JF, 03/06/16,

AU: Please verify that the edited version is correct and consistent with the item cited in Note 34, or revise as needed. A search of the item in Note 34 for “six” did not turn up any appropriate hits. ---- changed the source

JF, 03/06/16,

AU: If the item in Note 33 is the source for only the number of practices, please provide the source for the number of patients—renumbering subsequent notes in the text and in the notes section as needed. If the item in Note 33 is the source for both numbers, please move the callout to the end of the sentence. --- edited

JF, 03/06/16,

AU: Please provide the date for these statistics where requested. ---- have inserted this and change them to more recent figures


The framework presented in this articlepaper describes different

population strategies for integrated care, and how segmentation can support

them. The segmentation of a wWhole population segmentation can support

comprehensive population health strategies, by ensuring that the health care

needs of all population groups are considered. In contrast, segmentation of

Ssubpopulations and high-risk populations segmentation on the other hand

can be used to deliver targeted programs of integrated care programs to

patients with high -needs patients.

The Better Health for London initiative shows how thewhole population

segmentation of a whole population can support population health strategies.

By oOrganizing integrated care programs around segments instead ofrather

than by provider or condition, makes it possible for all relevant stakeholders

from across the health system tocan be involved. For some segments this

involvement will go beyond medical care and will include social and

community care, or mental health services. In addition, since the programs

are developed for the differentper segments, they can be fully tailored to

eachthat group’s unique needs and priorities.

Physicians and otherIndividual care providers and physicians can use

segmentation as a case- finding tool to identify patients with a specific

condition or risk, and help them deliver integrated care to defined these

subpopulations or risk groups. Both the ValCrònic program and the program

for Aat-r Risk Iindividuals programs use data from EHRselectronic health

records to identify a target population and allocate patients to segments. This

information is used to deliver interventions tailored to each segment, to

ensure the most effective use of resources.

15

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AU: As asked above, please reword to clarify what cases the tool finds (for example, patients with a particular condition?). ---- done


There isexist a wide range of approaches to segmentation analysis

approaches, ranging from segmenting based on long-term conditions, to

advanced software solutions that use a granular aggregation system or risk

algorithm. Deciding on the right approach involvesis a trade-off between

simplicity and precision. For high-level strategic decisions, segmenting by

condition may suffice, while the calculation of capitated budgets will require

more detailed information. HoweverOn the other hand, a population health

plan would be unmanageable with if the populationit wereas divided into

hundreds of segments.

In addition, there is the option to develop a custom segmentation

analysis can be developed, as was done by the London Health Commission

and Counties Manukau, or to purchase an off-the-shelf solution can be

purchased, such aslike the cClinical rRisk gGroupingCRG system in Valencia.

Developing a segmentation analysis in -house will allows organizations to fully

tailor their segments to their local context and aims, but it requires expertise in

data mining expertise. Software solutions may be more limitedrestrictive in the

segments they create, but they often provide a suite of intuitive analysis tools

to review the segments.

However, Tthe use of all these methods however requires access to

software and technical guidance. Advanced technologies are costly, and

individual providers may not have the required scale to implement them.

Policy makers can encourage uptake by investing in research into

segmentation algorithms and making them available to care providers.[7] (7).

Alternatively, system-wide programs, such as the one that implementedation

of the cClinical rRisk gGrouping CRG system in Valencia, should be

16


considered as a way to provide everyone all health care providers with high-

quality analytics, and standardize the approach across the system.

All of the case studies rely heavily on detailed patient data, often

obtained from different data sets linked at the patient -level. This highlights an

important policy issue, since the availability of linked health care data sets is

still limited in many countries. In Counties Manukau, dData governance

requirements have complicated the implementation of Counties

Manukau’stheir risk tool in practice. Policy makers should consider some of

the levers at their disposal—such as – building support, creating an evidence

base, investing in capabilities, setting anthe example, involving patients, and

legislating— – to facilitate and promote the use of big data in health care.[335]

(34).

Conclusion

Segmentation provides a range of benefits to policy makers and care

providers who aspireing to integrate health care. A segmentation data

analysis can help to select a homogeneous target population, and to tailor

anthe intervention to different patient types within a population. As health care

continues to move towards a patient-centered approach, and big data and

analytics become even more ingrained, policy makers should to consider the

significant benefits of patient segmentation analysis for integrated care and

support its use.

17

JF, 03/06/16,

AU: Please replace “everyone” with more specific wording to clarify the point (for example, “all health care providers”). --- done


NotesReferences

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JF, 03/02/16,

AU: The Notes have been edited to conform to Health Affairs' standards and style. The accuracy of the information in the Notes is the responsibility of the authors. Please verify that all the information in the Notes is correct. Whatever changes you need to make in the Notes must be visible in track change, within our edited Notes. If you need to add or reorder notes and are unable to do so with track change on, please either give clear instructions about the necessary addition or reordering in balloon comments in the manuscript or contact a Health Affairs copy editor, rather than creating a new notes list.


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LUMINA: Page range is “77–110, iv–v.”

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AU: The Appendix will be prepared for posting online after the article’s preparation for publication has been completed. Please be sure that the appendix you have submitted is complete, contains components that correspond to those you have specifically called out in the text, shows no change tracking, and is formatted the way you want it to be. Health Affairs editors do not edit or format appendices. All we do is add a citation to the article and make PDFs for online posting. Any errors or formatting problems are solely the responsibility of the authors. Please verify that you understand this by posting a comment here. OK


http://www.kingsfund.org.uk/sites/files/kf/field/field_publication_file/integrated-

care-summary-chris-ham-sep11.pdf

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from: http://www.londonhealthcommission.org.uk/wp-content/uploads/London-

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JJ. Evaluación de la satisfacción de los pacientes crónicos con los

dispositivos de telemedicina y con el resultado de la atención recibida.

Programa ValCrònic. Atención Primaria. 2014;46(, Supplement 3(0):16–-23.

Spanish.

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1926. Martin G. Introducing the At Risk Individuals Programme. Counties

Manukau Health [blog on the Internet]. 2014 Jul 1. [cited 28 Jan 2016 Mar 2].

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JF, 07/03/16,

AU: The item is identified as a blog post, but the name of the blog is not obvious. If “Counties Manukau Health” is not the name of the blog, please revise the note as needed. ---OK I cannot find a name either so would agree with Counties Manukau Health

JF, 07/03/16,

AU: A Google search failed to locate this item, so we were not able to check any of the information in this note. If you can provide a URL leading directly to the item, please add it and revise the note as needed (using Note 15 as a model). ---- OK, edited

JF, 02/03/16,

CCE: per http://www.sciencedirect.com/science/article/pii/S0212656714700617, the translation of the title (if we need it) is: “Evaluation of satisfaction with telemedicine devices and with the results of the care received among chronic patients. The ValCrònic program.”

JF, 02/03/16,

AU: Please disregard this and any subsequent comments for our formatter. LUMINA: The title is “Evaluación de la satisfacción de los pacientes crónicos con los dispositivos de telemedicina y con el resultado de la atención recibida. Programa ValCrònic.”


Available from: https://cmdhbhome.cwp.govt.nz/blogs/introducing-the-at-risk-

individuals-programme/.

20. To access the Appendix, click on the Appendix link in the box to the

right of the article online.

210. Leutz WN. Five laws for integrating medical and social services:

lessons from the United States and the United Kingdom. Milbank Q.

1999;77(1):77–-110, iv–v.

221. Ham C, Curry N. Integrated care: what is it? Does it work? What does it

mean for the NHS? [Internet]. London: The King’'s Fund;, c 2011; [cited 2016

Mar 2]. Available from:

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care-summary-chris-ham-sep11.pdf

232. Curry N, Ham C. Clinical and service integration— - Tthe route to

improved outcomes [Internet]. London: The King’'s Fund;, c 2010 [cited 2016

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service-integration-Natasha-Curry-Chris-Ham-22-November-2010.pdf

243. Valentijn PP, Schepman SM, Opheij W, Bruijnzeels MA. Understanding

integrated care: a comprehensive conceptual framework based on the

integrative functions of primary care. Int J Integr Care. 2013;13:e13.

23

JF, 02/03/16,

LUMINA: No issue number.

JF, 02/03/16,

LUMINA: Page range is “77–110, iv–v.”

JF, 02/03/16,

AU: The Appendix will be prepared for posting online after the article’s preparation for publication has been completed. Please be sure that the appendix you have submitted is complete, contains components that correspond to those you have specifically called out in the text, shows no change tracking, and is formatted the way you want it to be. Health Affairs editors do not edit or format appendices. All we do is add a citation to the article and make PDFs for online posting. Any errors or formatting problems are solely the responsibility of the authors. Please verify that you understand this by posting a comment here.


254. Busse R, Stahl J. Integrated care experiences and outcomes in

Germany, Tthe Netherlands, Aand England. Health Aff (Millwood).

2014;33(9):1549–-58.

265. NHS England. Enhanced service specification: - A avoiding unplanned

admissions: proactive case finding and patient review for vulnerable people

[Internet]. Leeds (UK): NHS England;, [cited 2016 Mar 2]2014. Available from:

https://www.england.nhs.uk/wp-content/uploads/2014/06/avoid-unpln-admss-

serv-spec.pdf

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prospectus-upd.pdf

24

JF, 02/03/16,

AU: The URL you provided led us not the tool kit but to the home page. Please verify that the item now described in this note is what you want to cite, or provide a new URL leading directly to the correct item and revise the note as needed, using edited notes as models.


298. Beltráan DO, Savorit SC, Garcia JJS, Garcia JLdV. Introducción a los

dos proyectos y a la tecnología de Telefónica que los soporta.

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3010. García JJS. ValCrònic: resultados para la salud y satisfacción general.

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satisfaccion-general/.

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%20prediction%20report%20FINAL%202014.04.28.pdf

25

JF, 07/03/16,

AU: This item appears to be a blog post. Please add the name of the blog where requested. ---- edited

JF, 07/03/16,

AU: A Google search failed to locate this item, so we were not able to check any of the information in this note. If you can provide a URL leading directly to the item, please add it and revise the note as needed (using edited notes as models). ---- I received the presentation slides from Dr Beltran in our communication, on the 9th of September 2015. Should it be quoted as personal communication instead?

JF, 02/03/16,

AU: Per http://www.ascane.org/actividades_cientificas/Programa%20Paciente%20Cronico.pdf (p. 27), “Telemonitorización: realidad o ficción” was the title of a session at this meeting, but “Introducción a los dos proyectos y a la tecnología de Telefónica que los soporta” was the title of the paper presented by the authors you list.


332. Counties Manukau. At Rrisk Iindividuals (ARI) 2014 [Internet]. [Please

provide place of publication]: [Please provide publisher]; [cited 4 September

20165 Mar ??]. Available from: http://www.countiesmanukau.health.nz/about-

us/performance-and-planning/achieving-balance/system-integration/at-risk-

individuals/.

3243. Ko Awatea. The 20,000 Days Campaign: health system improvement

guide VHIU link collaborative 20,000 Ddays Ccampaign: - Ffrom small

revolutions to big change [Internet]. Auckland (New Zealand): Ko Awatea;,

2013[cited 2016 Mar 63]. Available from:

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ko_awatea_-_20000_days_-_how_to_guide_-_vhiu.pdf

http://koawatea.co.nz/wp-content/uploads/2013/08/20000-Book-2-web.pdf

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AS, Darzi A. Developing public policy to advance the use of big data in health

care. Health Aff (Millwood). 2014;33(9):1523–-30.

26

JF, 07/03/16,

AU: The URL you provided no longer works. Please provide a new URL leading directly to the item you want to cite here and revise the note as needed, adding information where requested and using edited notes as models. ---- changed the source as the figures have been updated


Exhibit lList

EXHIBIT 1 (table)

Caption:

Source/Notes:

The London Health Commission segments

Source: Adapted from the London Health Commission, 2014 (12)

EXHIBIT 2 (table)

Caption:

Source/Notes:

ValCrònic segments

Source: Adapted from Mira-Solves et al., 2014 (20)

27

JF, 02/03/16,

AU: We’ll make the information in the Exhibit List match what appears in the Exhibits section once you’ve responded to all of our comments there. Please do not make any changes in the Exhibit List.


ExhibitsTables

EXHIBIT 1: The London Health Commission segmentation of the population

of Londons (14)

Age (years)groupCondition 0–-12 13–-17 18–-64 65 and

older+Conditions

“Mostly” healthy Segment 1

Segment 2 Segment 3 Segmen

t 4One or more long- term physical or mental conditions

Segment 5

Segment 5 Segment 6 Segmen

t 7

Cancer Segment 5

Segment 5 Segment 8 Segme

nt 8Severe, enduring mental illness

Segment 9

Segment 10

Segment 11

Segment 11

Learning disability Segment 9

Segment 10

Segment 12

Segment 12

Severe physical disability

Segment 9

Segment 10

Segment 13

Segment 13

Advanced dementia, Alzheimer’s, and related conditionsetc.

—a —a Segment 14

Segment 14

Socially excluded groups

Segment 15

Segment 15

Segment 15

Segment 15

SOURCEource: Authors’ adaptationed of [please provide] from Starfield B, et

al. Ambulatory care groupsthe London Health Commission, 2014 (Note 12 in

text). NOTE The London Health Commission’s “Better Health for London”

(see Note 14 in text) segmented the population of London into fifteen groups

to target health initiatives at the appropriate people. NOTES The London

Health Commission’s “Better Health for London” (see Note 14 in text)

segmented the population of London into fifteen groups to target health

initiatives at the appropriate people a Not applicable.

28

JF, 07/03/16,

AU: Please verify that the added wording correctly explains why these cells are blank, or revise as needed. --- OK see before

JF, 07/03/16,

AU: If the added exhibit note has distorted the meaning, please reword as needed to clarify the point. --- The note is correct, but the explaination of the segments in in the London Health Commission feels repetitive. If it's HA standard that's fine, but could be left out on my account

JF, 07/03/16,

AU: Please briefly explain where requested what you adapted from the item in Note 12—an exhibit like this table? Or is the point that this exhibit is based on your analysis of data from the item in Note 12? ---- apologies, anothe rmix up with references not updating.. the only reference should be the London Health Commission. I called it an adaptation as the original figure looks different, but the data is the exact same. Have therefore deleted the 'adaptation' comment.

JF, 03/07/16,

AU: If some reference needs to be made to the item in Note 14, please add that reference to the exhibit notes. ---- ok

JF, 03/07/16,

AU: The exhibit table has been edited and extensively revised to meet Health Affairs’ standard formatting requirements. Please check the data carefully to ensure no errors were introduced. Please confirm accuracy by typing a comment to us here or revise if necessary. --- checked


29


EXHIBIT 2: ValCrònic segmentations of the subpopulation of [please

provide]Valencia with long-term conditions (17)

Risk level for hospital admissiona according to Community Assessment Risk Screen

Condition High Moderate LowConditions

Heart failure Segment 1 Segment 2 —b

COPD Segment 3 Segment 4 —b Diabetes —b —b Segment 5 Segment 6Hypertension —b —b Segment 7Heart failure and& COPD Segment 8 —b —b

Heart failure and& Ddiabetes Segment 9 —b —b

Diabetes and& COPD Segment 10 Segment 11 —b

COPD and& Hhypertension Segment 12 Segment 13 —b

Diabetes and& Hhypertension Segment 14 Segment 15 —b

Heart failure, & COPD, and& Ddiabetes

Segment 16 —b —b

SOURCEource: Authors’ adaptationed of [please provide] from Mira-Solves et

al., Evaluación de la satisfacción de los pacientes crónicos con los

dispositivos de telemedicina y con el resultado de la atención recibida (see

Note 2417 in text).2014 (20) NOTES The ValCrònic program in Spain (see

Notes 24 and 25 in text) segmented the subpopulation with long-term

conditions by risk level to provide the appropriate intensity of telemonitoring

interventions. The ValCrònic program in Spain (see Notes 17 and 18 in text)

segmented the subpopulation with long-term conditions by risk level to

provide the appropriate intensity of telemonitoring interventions. COPD is

chronic obstructive pulmonary disease. a Based on the Community

Assessment Risk Screen (see Note 137 in text). b Not applicable.

30

JF, 07/03/16,

AU: Please verify that the added wording correctly explains why these cells are blank, or revise as needed. ---- ok

JF, 03/07/16,

AU: If the added wording has distorted the meaning, please reword as needed to clarify the point. --- see earlier. The information is correct, but could be left out.

JF, 07/03/16,

AU: What was Note 20 (and is now Note 21) cites: “Leutz WN. Five laws for integrating medical and social services: lessons from the United States and the United Kingdom. Milbank Q. 1999;77(1):77–110, iv–v.” The note referring to an item by Mira-Solves is Note 17: “Mira-Solves JJ, Orozco-Beltrán D, Sánchez-Molla M, Sánchez García JJ. Evaluación de la satisfacción de los pacientes crónicos con los dispositivos de telemedicina y con el resultado de la atención recibida. Programa ValCrònic. Atención Primaria. 2014;46(Suppl 3:16–23. Spanish.” If you do not want to refer to Note 17 here, please revise the source information as needed. --- reviewed and edited

JF, 07/03/16,

AU: Please briefly explain where requested what you adapted from the item in Note 12—an exhibit like this table? Or is the point that this exhibit is based on your analysis of data from the item in Note 12? ----- see earlier, deleted

JF, 03/07/16,

AU: If the added wording (based on what you say in the text) doesn’t correctly explain the point, please reword to clarify—risk level for what? --- ok

JF, 03/07/16,

AU: If some reference needs to be made to the item in Note 17 beyond what now appears in table footnote a, please add that reference to the exhibit notes and explain why it is there. ----ok edited

JF, 03/07/16,

AU: Please briefly explain what population this is a subpopulation of (for example, “the subpopulation of Spain with long-term conditions”). ---- edited

JF, 03/07/16,

AU: The exhibit table has been edited and revised to meet Health Affairs’ standard formatting requirements. Please check the data carefully to ensure no errors were introduced. Please confirm accuracy by typing a comment to us here or revise if necessary. --- ok


31


Acknowledgment

Ara Darzi chaired the London Health Commission, and Sabine Vuik consulted

on the Whole Systems Integrated CareWSIC project in North West London.

The authors acknowledge the following individuals for their contributions toon

the case studies: Claire Naumann and David Grayson at Counties Manukau,

Domingo Orozco-Beltran at ValCronic, and Shaun Danielli and Patrice

Donnelly at the Healthy London Partnership.

Bios for 2015-1311_Vuik

Bio 1: Sabine I. Vuik ([email protected]) is a policy fellow at the Institute

of Global Health Innovationin the Centre for Health Policy, Imperial College

London, in the United Kingdom.

Bio 2: Erik K. Mayer is a clinical senior lecturer in surgery and cancer at the

Centre for Health Policy, Imperial College London.

Bio 3: Ara Darzi is executive chair of the World Innovation Summit for Health,

Qatar Foundation, and director of the Institute of Global Health Innovation,

Imperial College London.

32

JF, 07/03/16,

AU: To ensure accuracy, Health Affairs requests that you carefully check all author bio information that will appear on p. 1. The accuracy of this information is the responsibility of the authors. Please verify that all the information is correct and consistent. If revisions are necessary, please provide. ---OKDarzi bio information is what was published in a February 2016 HA article.

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