toward a population health delivery system first.7 (1)

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76

Toward aPopulation HealthDelivery System:First Steps inPerformance

MeasurementJames Studnicki, Frank V. Murphy,Donna Malvey, Robert A. Costello,Stephen L. Luther, andDennis C. Werner

In spite of the technologicalsophistication and clinical excellenceof the U.S. health care industry and

annual health expenditures in excessof a trillion dollars, the overall healthstatus of the American population iscomparatively poor. The BCHS inwest central Florida sought to improvethe health status of the communitiesthat it serves. Known by the acronymCHAPIR, an information-drivenhealth status decision support systemwas developed, pilot tested, and is now

fully implemented throughout theBCHS. The methodological approach,quantitative indicators, report formatcomponents, and managementimplications of the system aredescribed.

Health Care Manage Rev, 2002, 27(1), 7695 2002 Aspen Publishers, Inc.

Key words: community health status assessment, defined popu-

lations, integrated delivery systems, multihospital systems

James Studnicki, Sc.D., is Professor of Health Policy and Man-agement and Director, Center for Health Outcomes Research,University of South Florida, Health Sciences Center, Tampa andSt. Petersburg, Florida.

Frank V. Murphy, M.H.A., is President and CEO, BayCareHealth System, Clearwater, Florida.

Donna Malvey, Ph.D., is Assistant Professor, Health Policy and Management, University of South Florida, College of PublicHealth, Tampa and St. Petersburg, Florida.

Robert A. Costello, M.B.A., is Director of Quality Planning,BayCare Health System, Clearwater, Florida.

Stephen L. Luther, Ph.D., is Research Assistant Professor, Cen-ter for Health Outcomes Research, University of South Florida,Tampa and St. Petersburg, Florida.

Dennis C. Werner, M.H.A., is Senior Research Coordinator, Cen-ter for Health Outcomes Research, University of South Florida,

Health Sciences Center, Tampa and St. Petersburg, Florida.

Managing health care organizations has never been

more challenging. The continued growth of managedcare, recent changes in Medicare reimbursement, andincreased public access to detailed financial and clini-cal information are making it more difficult for healthcare executives to meet performance expectations re-lated to the quality of service, market share, and prof-itability. An even more difficult challenge, however,may lie ahead for this countrys health care leader-ship: to demonstrate that the health status of commu-nities and populations can be improved. Although theU.S. spends a larger percentage of its wealth for healthexpenditures and has, without question, the mosttechnologically advanced medical care system in the

world, our health status as a nation is persistently sub-par, even when compared to some less economicallydeveloped nations. This gap between our wealth andour health, long a subject of some debate among re-searchers, is now being more widely acknowledged by politicians and the public at large. Increasingly,managers of our health care institutions and agencieswill be expected to close this gap.

Improving the health status of populations repre-sents a new management challenge to a health care

This work was supported in part by grants from the U.S. Department ofCommerce (Telecommunications and Information Infrastructure AssistanceProgram) and the BayCare Health System.


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Toward a Population Health Delivery System 77

system primarily oriented toward providing insur-ance coverage and medical and hospital services tosick people. Our organizational structures, priorities,values, and financial incentives are seemingly incon-gruent with an emphasis on the health of populationsand on coordinated and focused efforts to identifyhealth risks and prevent illness. Especially for privatesector organizations in the U.S., these managementobjectives are unfamiliar territory. This article reviewsthe experience of a hospital-based integrated deliverysystem (IDS) taking its first steps toward managingthe health status of defined communities.

THE AMERICAN DILEMMA

This fundamental, peculiarly American dilemmahas been so well documented over such a long periodof time and with such profound implications for oursociety, it is surprising that it is not widely acknowl-edged as a national disgrace: While our health caresystem consumes the massive amount of resourcesrepresented by the more than one trillion plus dollarsexpended annually, the health status of our nationas characterized by multiple measures is alarminglylow. At least a dozen nations with a populationgreater than one million persons have lower infantmortality rates.1 Immunization rates for measles byage 12 are higher in nearly 60 countries, includingmany that would be considered economically under-developed or distressed.2 Nearly 20 nations have maleand female life expectancy at birth longer than theU.S. The World Bank has cited the United States asthe nation with the worst health outcomes in relationto expenditures.3

MULTIPLE DETERMINANTS OF HEALTH

Since the medical care system consumes such alarge percentage of total U.S. health expenditures,

many investigators expressing a public health per-spective have challenged the extent to which these in-vestments have improved population health status,4,5

generally concluding that medical interventions havea relatively minor impact on population mortality.Explanatory models have emerged that differentiatethe concepts of disease, health, and well being.6 Mul-tiple factors identified as impacting disease, health,and function include the social environment, physicalenvironment, and genetic endowment.7 For example,extensive research evidence exists that higher levels

of socioeconomic status are persistently associatedwith lower mortality and morbidity.8,9 Related factorssuch as employment, income, social support systems,marital status, and race have been found to haveindependent effects on mortality rates.1012 Environ-mental hazards and toxic agents have been deter-mined to have measurable impacts on the health ofpopulations in the form of occupational hazards,food and water contaminants, and components ofcommercial products. Personal behaviors such assmoking habits, diet, exercise, alcohol use, motor ve-hicle use, sexual activity, and violent and abusive be-havior contribute significantly to health outcomes.13

Therefore, since there are multiple determinants of

population health, it is unlikely that even a lavishlyfunded medical care system alone will deliver sub-stantial improvements in health status.

Traditional public health agencies have defined ascore functions the assessment of the health of popula-tions, policy formulation appropriate to the problemsidentified, and assurance that relevant environmental,behavioral, or medical care interventions are appliedand sustained.14 However, most Americans have noexperience with public health agencies, which arechronically handicapped by a paucity of resources, andin many areas, relegated to the role of the health careprovider of last resort to especially vulnerable popula-

tions. Many health policy experts have come to believethat improvements in population health status arelikely to come only from the type of organization de-scribed by Alfred Sommer, Dean of the Johns HopkinsSchool of Hygiene and Public Health as a complex,diverse, integrated, and dynamic enterprise, com-posed of many disciplines, whose primary goal is im-proving and protecting the health of the public.15 (p.657)

No such organization presently exists in the U.S.

NEW ORGANIZATIONAL MODELS, BARRIERS,AND INFORMATION

Currently, our health care system, despite an in-creasing awareness of the importance of both clinicaland population outcomes, is neither organized nor in-centivized to address population health. Considera-tions of profitability and market share continue todominate management decisions in private sectororganizations.16 Public health agencies and organ-izations are largely focused upon designated pop-ulations of interest (e.g., poor mothers and children,patients with AIDS) supported by categorical funding.The challenge of being able to affect both medical and


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78 HEALTH CARE MANAGEMENT REVIEW/WINTER 2002

nonmedical determinants of health through sometype of vertically integrated delivery system has beenaddressed by a few researchers. It has been suggestedthat hospital integrated delivery systems may havethe potential to incrementally develop the verticallyintegrated services (e.g., screening, health education)necessary to address additional determinants of pop-ulation health.17 Barriers to the evolution of hospital- based integrated delivery systems into integratedpopulation health delivery systems are formidable.Implementing appropriate financial incentives isprobably the most essential task in the creation of thenew paradigm. Shortell has described the health pro-motion accountability region (HPAR), a type of inte-

grated delivery system, at the state or regional levelwhose reimbursement would be tied to improve-ments in population health status.18 More recently,Kindig has suggested a financial mechanism that re-wards integrated delivery systems and health plansfor improvements in an index of health adjusted lifeexpectancy (HALE) but also proposes the establish-ment of a Health Outcomes Trust that would have re-sponsibility for coordinating the medical care sectorand other sectors (e.g., social services, education, envi-ronment, public health) in order to maintain and im-prove the health of the public.19 It should be notedthat other European nations have already incorpo-

rated improvements in population health as a meansto evaluate the performance of health care managers.

As exciting as these theoretical concepts and inno-vative organizational schemes may be to some re-searchers and policy analysts, the first few necessarysteps must be taken on the messy turf of the realworld. In the most fundamental terms, there are twopractical requirements necessary for any organizationwishing to impact on community health status: pur-pose and performance measurement. First, an explicitrecognition of improved population health status asan enterprise objective is a prerequisite for success.Second, there must be a valid performance measure-

ment system, which makes the powerful connectionamong the health of the community, information-driven decision support systems, and managementdecisions.20

BAYCARE HEALTH SYSTEM

In the summer of 1997, the signing of a joint operat-ing agreement involving some of the largest and mostinfluential not-for-profit community hospitals in westcentral Florida formed the BayCare Health System

(BCHS). The hospitals forming BCHS collectively rep-resent 2,756 beds, 3,400 medical staff members, and10,989 employees. In fiscal 1999, BCHS hospitals ac-counted for approximately 88,000 admissions, 14,000 births, and 269,000 emergency department visits. Thesystem is moving toward vertical integration of ser-vices and provides a wide range of nonacute services inaddition to hospital care including screening and pre-ventive services, primary care, and postacute services.

The system is organized into a regional structureof three community health alliances (CHAs) that arenamed after the system hospitals located in each ofthe geographically defined population areas (seeFigure 1). BayfrontSt. Anthonys Health Care is lo-

cated in southernmost part of Pinellas County, in thecity of St. Petersburg. (Note: As of December 31,2000, Bayfront Medical Center is no longer a BCHSmember.) Morton Plant Mease Health Care repre-sents the areas of Pinellas County, including the cityof Clearwater, and the western area of Pasco County.St. JosephsBaptist Health Care incorporates all ofHillsborough County, including the city of Tampa,and the eastern area of Pasco County. The total three-county area is home to approximately 2.4 million resi-dents. Each of the three CHAs represents considerablegeographic, demographic, and socioeconomic hetero-geneity. Pinellas County, for example, is the least rural

county in all of Florida, but both Pasco and Hillsbor-ough Counties have expansive rural areas. As is true ofmany Florida places, older and wealthier coastal com-munities lie adjacent to inland pockets of relativepoverty. This diversity represents a formidable chal-lenge to the BCHS management team in assessing theneeds and health status of the communities residinginside their population areas, as well as evaluating theimpact of the services being delivered. All three CHAsshare the same mission of BCHS, to improve thehealth of all we serve through community-ownedhealth care services that set the standard for high qual-ity, compassionate care. Each CHA operationalizes its

commitment to improving the communities healthstatus through their Quality Planning Process, which

The hospitals forming BCHScollectively represent 2,756 beds,3,400 medical staff members, and10,989 employees.


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FIGURE 1

BAYCARE COMMUNITY HEALTH ALLIANCES POPULATION AREAS

BAYCARE HEALTH SYSTEM

COMMUNITY HEALTH ALLIANCES POPULATION AREAS


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defines multiyear Strategic Directions and annualAction Steps and Quality Improvement Goals. Com-munity health priority areas for these benchmarks areselected based on findings from research methodolo-gies discussed in this article. Progress on accomplish-ments (i.e., Quality Reporting) is shared on a quar-terly basis with each CHAs senior and middlemanagement teams, Community Affairs Board Com-mittee, and the health system Board.

PROJECT OBJECTIVES

The rationale for the creation of BCHS was formed inthe competitive hospital service market of the 1990s,

and there was undoubtedly some reaction to the growthof the proprietary Columbia/HCA system in theTampaSt. Petersburg area during that period. Thegoals of the new enterprise reflected the typical antici-pated benefits of service integration: cost efficienciesand economies of scale derived from consolidation ofduplicated administrative services; improvements inthe quality of clinical care by standardizing on bestpractices inside the system; and enhanced attractivenessto managed care organizations by providing a networkof coordinated hospital and physician services througha single signature contract.21 These objectives are con-sistent themes inside the developing literature on the

organization and operation of hospital-based integrateddelivery systems.22,23

However, from the very beginning, the BayCareleadership underscored the systems promise for im-proving the health of the community. A decision wasmade to develop an information-driven, communityhealth status decision support system. With consulta-tion assistance from the Center for Health OutcomesResearch at the University of South Florida HealthSciences Center, the development of this system wasinitiated. Known by the acronym CHAPIR (Commu-nity Health Alliance Performance Impact Report), itwas determined that the community health status

monitoring system would need to meet the followingspecifications:

Comprehensiveness. Following the recommenda-tions of the Institute of Medicine (IOM) of theNational Academy of Sciences, the CHAPIRwould establish and maintain a broad strategicview of the health status of the community andthe various factors that influence it.24

Operational Integratability. The indicators used tomonitor health status of communities inside theCHAs must, at least to some extent, be related to

the programs and services planned or imple-mented by the CHAs.

Feasibility and Continuity. Data elements utilizedin the CHAPIR must be drawn from availableextant public databases, or existing sources ofinternal information. Information requiringoriginal, primary data collection such as surveyswould be less desirable on the assumption of thedecreased likelihood that these special effortswould be sustained over time.

Community-Level Granularity. County- and CHA-specific information, while valuable for compar-ative purposes, is insufficient in identifying thehealth status variability of the communities

inside the CHA service areas. Therefore, theCHAPIR system must aggregate data to the com-munity level as defined by groups of postal zipcodes.

Parsimonious Presentation. Intended primarily forsenior corporate managers, clinical leadership,and board members, the CHAPIR reports mustcapture and present the important and valid in-dicators and findings without resorting tolengthy narrative or complicated statistical treat-ment.

Measurement and Monitoring of Results. TheCHAPIR report must include interim process

indicators to measure progress on recommenda-tions, goals, and action plans initiated to addresspriority problem areas. Process indicators can bereported on a more frequent basis than ultimateoutcome indicators such as morbidity and mor-tality, which are typically updated on an annualbasis.

THE METHODOLOGICAL APPROACH

An existing methodology for assessing the healthstatus of communities, under development for nearly8 years, served as the starting point for CHAPIR.

Known as CATCH (Comprehensive Assessment forTracking Community Health), the method draws 250indicators from multiple sources and uses a compara-tive framework and weighted evaluation criteria toproduce a rank-ordered community problem list. Theindicators are organized into 10 categories: demo-graphic characteristics; socioeconomic characteristics;maternal and child health indicators; infectious diseaseindicators; physical and environmental health in-dicators; health status indicators (mortality andmorbidity); social and mental health indicators; sentinel


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events (immunizable diseases and avoidable hospi-talizations); health resource availability indicators;and, behavioral risk factors.25 Comprehensive CATCHassessments have been completed in 13 Florida coun-ties including all three of the counties composing theBCHSCHA areas. The CHAPIR reports draw muchof their data from the same sources, but the formatspecifies a three-level indicator selection process:

1. Generic Health Status Indicators, which are in-tended to provide a baseline profile of the impor-tant dimensions of community health status.This indicator list will be identical for each ofthe three CHAs, allowing comparison betweenthe CHAs with statewide, regional, and national

norms.2. CHA-Specific Health Status Indicators are in-tended to profile those diseases or conditionsthat can be identified as a priority area of con-cern for each CHA. The assignment of priorityfor any indicator may be the result of eachCHAs internal strategic analysis, a previouscounty-level CATCH assessment, an evaluationof zip code level community cluster analyses, orsome other source of information.

3. Programmatic Indicators are determined largelyby the nature of service programs and monitor-ing systems that have been implemented by the

CHA operating units. These indicators wouldtend to be more operational, focusing on pro-gram utilization or intermediate outcome tar-gets rather than morbidity and mortality indi-cators. Although these indicators are drawnlargely from existing sources of external and in-ternal information, some may require a primarydata collection effort such as a periodic tele-phone survey.

GENERIC HEALTH STATUS INDICATORS

The first level of Generic Health Status Indicatorswas identified through a comprehensive review andstatistical analysis of the unique CATCH database.These indicators are intended to represent majordisease groups and/or leading causes of death, therelevant CATCH category indicators, and a smallersubset of CATCH indicators that would explain mostof the statistical variation in mortality accounted forby all of the CATCH indicators. Researchers refer tothe subset as the parsimonious model, that is, asmaller group of indicators, which accounts for a large

percentage of the total variation represented by all ofthe indicators.

A principal components analysis (PCA) was se-lected as the statistical technique to derive the par-simonious model. The PCA is applied to a set ofvariables where there is interest in discovering whichvariables inside the set or the group of indicators formcoherent subsets that are relatively independent ofone another. Variables that are correlated with one an-other but are largely independent of other subsets arecombined into the principal components. The majorgoal of the PCA is to reduce the number of variablesdown to a few factors. For example, the total numberof variables in the original CATCH socioeconomic

indicators category was reduced to two factors:poverty and education/employment. The 14 factorscreated by the PCA and the individual variables com-prising each are found in Table 1.

CHA-SPECIFIC HEALTH STATUS INDICATORS

Since comprehensive assessments were completedin each of the three counties composing the BCHSservice area, the priority problems or issues identifiedin those projects were an important source of infor-mation in determining CHA priorities. Table 2 is asummary of the major categories and indicators iden-

tifying health challenges in each county.Subsets of the indicators utilized in the comprehen-

sive community assessments are available at thepostal zip code level. This presents the opportunity tofocus down on identified communities inside eachof the CHAs that are composed of groups of zip codes.This capability considerably enhances the process ofdescribing the characteristics and health status ofpopulation groups inside the boundaries of eachCHA. In order to provide these new dimensions to theCHAPIR report, the following analytical steps werecompleted:

Each of the three CHAs was subdivided into

communities based upon groups of zip codes.This process generally attempts to define com-munities that are relatively homogeneous in-ternally, but acknowledged by residents to bedifferent from other communities. While theretends to be some disagreement over the assign-ment of some boundary zip codes to one com-munity versus another, there is usually highagreement regarding the core cluster of zipcodes. Often these communities correspondvery closely to old neighborhood boundaries.


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TABLE 1

PRINCIPAL COMPONENT ANALYSIS OF COMMUNITY HEALTH STATUS: RESULTING FACTORS

Factor Indicators

Poverty % of families below federal poverty level, per capita incomeEducation/Employment % of unemployed persons, % of high school dropoutsDemography % of population15, % of population 65,

% of populations non-whiteRurality % of population living in rural areasCommunity Violence simple assault rate, aggravated assault rate,

domestic violenceMaternal and Child Health birth to mothers15, birth to mothers 1517,

birth to mothers 1819Avoidable Hospitalizations congestive heart failure, pneumonia, asthmaResources physicians/100k population, dentists/100k population,

LPNs/100k populationInfection Morbidity enteric diseasesChronic Morbidity colorectal cancer morbidity, breast cancer morbiditySite-specific Mortality (adult) lung cancer AAM, cardiovascular diseases AAM,

pneumonia AAM, prostate cancer AAM, AIDS AAMUnintentional Injury unintentional injury AAM

Infant Deaths (white) infant mortality (white), neonatal mortality (white)Infant Deaths (non-white) infant mortality (non-white), neonatal mortality (non-white)

AAM - age adjusted mortality

TABLE 2

MAJOR HEALTH PRIORITIES RESULTING FROM THREE COUNTY LEVEL ASSESSMENTS

County Priority Area Indicators

Hillsborough County

Maternal and Child Health infant, neonatal and post neonatal mortalitymortality due to perinatal conditions, birth defects

Community Violence and Safety Issues domestic violence, simple and aggravated assaults,suicide, homicide and unintentional injuries

Preventable Cancers breast, cervical, colorectal; smoking relatedOther stroke, COPD

Pinellas County

Maternal and Child Health infant and child mortality, birth defect mortalitySocial Issues births to mothers 15, repeat births to teenagersLung/Respiratory Diseases smoking related cancers, lung and bronchus cancers,

pneumonia and influenza, chronic obstructive

lung dieseaseOther Years of Productive Life Lost (YPLL)

Pasco County

Maternal and Child Health low and very low birthweight babies, births to mothers 15, perinatal conditions neonatal, post neonataland infant mortality

Lung/Respiratory Diseases pneumonia and influenzaPreventable Cancers breast, cervical; melanoma, lung, and smoking relatedInfectious Diseases syphilis, gonorrhea, meningitisOther stroke


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Figure 2 illustrates the nine communities created by postal zip code aggregation within the St.JosephsBaptist Health Care CHA.

A comprehensive list of indicators from theCATCH database, available at the zip code level,was then aggregated into CHA, county, andcommunity (i.e., zip code groups) mean values.

Finally, eliminating those indicators that re-flected volumes so low that many zip codeswould have three or fewer observations in1 year reduced the list. The remaining indicatorswould then represent a relatively large volumeof cases, and would be suitable for validly iden-tifying indicators which had relatively large dif-

ferences between the CHA mean value and oneor more of the community values.

PROGRAMMATIC INDICATORS

A major source of information that was used toidentify CHA-specific priority issues and problems isthe internal strategic analysis conducted by the CHAsand/or their various operating units. Presumably, aset of organizational objectives serves as the guide forallocating resources and development of programs.Many of these decisions will be based upon the growthof new clinical programs, the strengthening of existing

ones and even, occasionally, the termination of others.In a few instances, those objectives are congruent withimprovement in community health status outcomes.In an effort to include this type of strategic thinking inthe CHA-specific indicators, meetings were scheduledwith key staff and management at each of the threeCHAs. A loosely structured questionnaire was devel-oped that elicited information for three domains: thehealth care needs that have been identified inside eachCHA and its communities; the services or programsimplemented or planned to address these identifiedneeds; and the measures or quantifiable indicatorscurrently utilized or planned that could monitor the

implementation of the programs and anticipated out-comes that would be impacted by these programs. Theresponses were organized in the same categories uti-lized by the CATCH methodology so as to improvethe internal consistency of both the reporting and thepresentation.

BCHS has also implemented a framework for iden-tifying basic quality improvement goals, which weredeveloped by each of the three CHAs and organizedinto three categories: service, outcome, and cost.These measures tend to be operational in nature; that

is, they are typically focused on clinical or administra-tive process improvement. Generally, these indicatorsemphasize improvement in service to key customers,

outcomes (clinical and nonclinical), and cost. These in-dicators may be oriented toward improvements incommunity health status and will be incorporatedinto the CHAPIR report. For example, one CHA hadas an expressed outcome goal the reduction in late-stage breast cancer. This goal could be related tomammography screening or breast self-examinationeducation programs, and ultimately to reductions inbreast cancer mortality.

REPORT FORMAT COMPONENTS

There are two major methods of data presentation

incorporated into the CHAPIR report format: core indi-cator graphs and the total indicator table. The core indi-cator set is composed of each indicator selected foranalysis in each CHA through the process of selectionpreviously described utilizing three levels of indicators(i.e., generic, CHA-specific, and programmatic). Foreach indicator, a graph depicts the CHA value as ahorizontal line and reference symbols placed aboveor below the line. A sample core indicator graph(Figure 3) illustrates morbidity due to psychoses in theSt. JosephsBaptist Health Care CHA and 12 symbolsrepresenting, from left to right, values for: the Floridastate average, the Hillsborough and Pasco County

averages, and the mean values for each of nine zip-code-defined communities within the CHA. Therefore,communities with unfavorable patterns of morbidityand mortality are easily identifiable. The number of coreindicator graphs will vary somewhat between CHAs,and 27 were selected for St. JosephsBaptist HealthCare CHA. Other methods for presenting the core indi-cator data are available such as color-coded mapping.

For a more comprehensive view, all indicatorshaving zip code level data are also displayed in asummary Table 3. The table organizes the indicators

BCHS has also implemented aframework for identifying basicquality improvement goals, whichwere developed by each of the threeCHAs and organized into threecategories: service, outcome, and cost.


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FIGURE 2

ST. JOSEPHSBAPTIST HEALTH CARE COMMUNITY HEALTH ALLIANCE PERFORMANCE IMPACTREPORT (CHAPIR)


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FIGURE 3

CORE INDICATOR GRAPH: MORBIDITY DUE TO PSYCHOSES WITHIN ST. JOSEPHSBAPTIST CHA


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TABLE 3

TOTAL INDICATOR TABLE: ST. JOSEPHSBAPTIST CHA

St. Joseph/ Hillsborough Pasco NE Pasco SE Pasco

Baptist CHA County County Community Community

1,042,571 918,084 310,517 51,260 73,227

CHA Indicators Totl/R per 100K Totl/R per 100K Totl/R per 100K Totl/R per 100K Totl/R per 100K

Socio-Demographic Indicators

Non-White Population 185,764 175,040 14,535 7,812 2,91217.82% 19.07% 4.68% 15.24% 3.98%

Median Household Income $34,405 $35,549 $25,654 $24,006 $27,337Population Over 65 151,197 119,200 104,015 8,767 23,230

14.50% 12.98% 33.50% 17.10% 31.72%Population Under 15 250,549 223,213 55,947 13,792 13,544

24.03% 24.31% 18.02% 26.91% 18.50%

Disease Specific Mortality

Total Mortality 9,190 7,803 4,915 448 939881.47 849.92 1582.84 873.98 1282.31

Cardiovascular Disease 3,548 3,045 1,988 160 343340.31 331.67 640.22 312.13 468.41

Heart Disease 2,709 2,326 1,594 118 265259.84 253.35 513.34 230.20 361.89

Total Cancer 2,261 1,954 1,238 90 217216.87 212.83 398.69 175.58 296.34

Preventable Cancers 1,288 1,093 726 61 134123.54 119.05 233.80 119.00 182.99Smoking Related Cancers 885 749 527 41 95

84.89 81.58 169.72 79.98 129.73Lung Cancer 712 595 433 36 81

68.29 64.81 139.44 70.23 110.61Stroke 612 543 274 19 50

58.70 59.14 88.24 37.07 68.28Chronic Obstructive Lung 491 412 312 20 59

Disease 47.10 44.88 100.48 39.02 80.57Diabetes Mellitus 282 239 101 16 27

27.05 26.03 32.53 31.21 36.87Colorectal Cancer 238 204 113 13 21

22.83 22.22 36.39 25.36 28.68

Pneumonia/Influenza 225 162 159 17 4621.58 17.65 51.20 33.16 62.82Colon Cancer 201 174 94 11 16

19.28 18.95 30.27 21.46 21.85Prostate Cancer 158 141 92 7 10

31.06 31.46 62.18 27.80 28.24Breast Cancer 158 139 67 5 14

29.60 29.58 41.22 19.17 37.02Chronic Liver Disease 112 100 52 6 6

& Cirrhosis 10.74 10.89 16.75 11.71 8.19AIDS 110 99 31 6 5

10.55 10.78 9.98 11.71 6.83


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TABLE 3 (continued)

NW Tampa New Tampa S Tampa E Tampa S Hillsborough Brandon Plant City

Community Community Community Community Community Community Community

95,134 230,650 119,965 192,328 85,973 138,594 55,440

Totl/R per 100K Totl/R per 100K Totl/R per 100K Totl/R per 100K Totl/R per 100K Totl/R per 100K Totl/R per 100K

11,212 37,271 26,179 74,836 7,214 14,007 4,32111.79% 16.16% 21.82% 38.91% 8.39% 10.11% 7.79%

$42,416 $38,110 $34,008 $25,428 $32,689 $44,527 $33,5478,591 21,029 20,614 25,771 23,072 12,373 7,750

9.03% 9.12% 17.18% 13.40% 26.84% 8.93% 13.98%22,768 54,169 24,146 50,416 18,067 38,465 15,182

23.93% 23.49% 20.13% 26.21% 21.02% 27.75% 27.38%

672 1,620 1,240 1,785 1,020 904 562706.37 702.36 1033.63 928.10 1186.42 652.26 1013.71

230 589 523 711 481 316 195241.76 255.37 435.96 369.68 559.48 228.00 351.73

166 416 412 561 369 251 151174.49 180.36 343.43 291.69 429.20 181.10 272.37

195 429 281 401 232 262 154204.97 186.00 234.23 208.50 269.85 189.04 277.78

116 244 153 235 114 148 83121.93 105.79 127.54 122.19 132.60 106.79 149.7177 163 104 167 87 93 58

80.94 70.67 86.69 86.83 101.19 67.10 104.6264 121 80 137 69 79 45

67.27 52.46 66.69 71.23 80.26 57.00 81.1744 137 82 111 78 51 40

46.25 59.40 68.35 57.71 90.73 36.80 72.1538 105 62 77 56 47 27

39.94 45.52 51.68 40.04 65.14 33.91 48.7022 45 32 72 21 30 17

23.13 19.51 26.67 37.44 24.43 21.65 30.6618 43 25 44 21 37 16

18.92 18.64 20.84 22.88 24.43 26.70 28.86

11 28 35 33 16 19 2011.56 12.14 29.18 17.16 18.61 13.71 36.0816 39 18 37 19 33 12

16.82 16.91 15.00 19.24 22.10 23.81 21.655 34 21 36 22 14 9

10.75 30.24 36.42 38.80 50.95 20.41 33.3118 27 20 23 18 20 13

37.02 22.84 32.10 23.11 42.06 28.57 45.745 20 18 39 5 11 2

5.26 8.67 15.00 20.28 5.82 7.94 3.618 22 15 40 3 7 4

8.41 9.54 12.50 20.80 3.49 5.05 7.22


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Rectal Cancer 37 30 19 2 53.55 3.27 6.12 3.90 6.83

Melanoma 35 25 26 2 83.36 2.72 8.37 3.90 10.92

Cervical Cancer 22 21 5 0 14.12 4.47 3.08 0.00 2.64

Tuberculosis 3 3 1 0 00.29 0.33 0.32 0.00 0.00

Other Mortality Indicators

Unintentional Injuries 385 336 124 18 3136.93 36.60 39.93 35.12 42.33

Suicide 132 103 57 11 1812.66 11.22 18.36 21.46 24.58

Homicide 57 51 8 3 35.47 5.56 2.58 5.85 4.10

Drowning 16 10 11 5 11.53 1.09 3.54 9.75 1.37Poison Mortality 2 2 0 0 0

0.19 0.22 0.00 0.00 0.00

Maternal/Child Health Indicators

Had Prenatal Care 10,164 8,901 2,827 440 8231st trimester 661.03 654.05 794.99 518.26 896.51

Teen Births age 1819 1,015 889 273 59 6766.01 65.32 76.77 69.49 72.98

Low Birthweight 957 874 183 40 4362.24 64.22 51.46 47.11 46.84

Teen Births age 1517 669 589 168 44 3643.51 43.28 47.24 51.83 39.22

Repeat Births 424 366 104 30 2827.58 26.89 29.25 35.34 30.50

Had Prenatal Care 187 165 40 15 73rd trimester 12.16 12.12 11.25 17.67 7.63

Very Low Birthweight 179 161 37 11 711.64 11.83 10.40 12.96 7.63

Infant Mortality 90 81 21 4 58.63 8.82 6.76 7.80 6.83

No Prenatal Care 87 80 18 2 55.66 5.88 5.06 2.36 5.45

Neonatal Mortality 55 50 10 1 45.28 5.45 3.22 1.95 5.46

Teen Births under age 15 52 46 8 2 43.38 3.38 2.25 2.36 4.36

Child Mortality 47 36 15 6 518.76 16.13 26.81 43.50 36.92Perinatal Conditions 45 40 9 3 2

4.32 4.36 2.90 5.85 2.73Birth Defects 36 26 19 3 7

3.45 2.83 6.12 5.85 9.56Post Neonatal Mortality 33 31 9 1 1

3.17 3.38 2.90 1.95 1.37

Morbidity Indicators

Psychoses 1,962 1,872 1,189 47 43188.19 203.90 382.91 91.69 58.72

AIDS 395 379 50 6 1137.89 41.23 15.94 11.71 14.34

TABLE 3 (continued)



1,042,571 918,084 310,517 51,260 73,227



14/20

2 4 7 7 2 4 42.10 1.73 5.84 3.64 2.33 2.89 7.22

1 7 4 3 4 2 41.05 3.03 3.33 1.56 4.65 1.44 7.22

2 7 1 4 1 2 44.11 5.92 1.61 4.02 2.34 2.86 14.07

0 0 1 1 0 0 10.00 0.00 0.83 0.52 0.00 0.00 1.80

21 62 35 90 42 54 3222.07 26.88 29.18 46.80 48.85 38.96 57.72

11 22 19 20 12 11 811.56 9.54 15.84 10.40 13.96 7.94 14.43

4 12 7 22 1 2 34.20 5.20 5.84 11.44 1.16 1.44 5.41

2 4 2 1 0 1 02.10 1.73 1.67 0.52 0.00 0.72 0.000 0 1 0 1 0 0

0.00 0.00 0.83 0.00 1.16 0.00 0.00

1,247 2,798 1,343 2,380 163 932 38852.36 805.88 876.06 786.78 136.74 455.52 43.28

77 225 102 383 26 69 752.63 64.80 66.54 126.61 21.81 33.72 7.97

80 225 112 343 25 85 454.68 64.80 73.06 113.39 20.97 41.54 4.56

32 124 74 295 21 36 721.87 35.71 48.27 97.52 17.62 17.60 7.97

21 81 32 188 14 25 514.35 23.33 20.87 62.15 11.74 12.22 5.69

6 44 24 71 6 9 54.10 12.67 15.66 23.47 5.03 4.40 5.69

17 38 20 66 2 16 211.62 10.94 13.05 21.82 1.68 7.82 2.28

10 25 12 30 0 3 110.51 10.84 10.00 15.60 0.00 2.16 1.80

5 15 6 43 3 7 13.42 4.32 3.91 14.21 2.52 3.42 1.14

7 14 7 20 0 1 17.36 6.07 5.84 10.40 0.00 0.72 1.80

2 8 2 25 4 4 11.37 2.30 1.30 8.26 3.36 1.96 1.14

3 11 5 13 0 4 013.18 20.31 20.71 25.79 0.00 10.40 0.005 9 5 21 0 0 0

5.26 3.90 4.17 10.92 0.00 0.00 0.003 12 4 6 0 1 0

3.15 5.20 3.33 3.12 0.00 0.72 0.003 11 5 10 0 2 0

3.15 4.77 4.17 5.20 0.00 1.44 0.00

179 459 411 729 5 80 9188.16 199.00 342.60 379.04 5.82 57.72 16.23

29 80 77 145 11 20 2029.96 34.47 63.77 75.13 12.21 14.07 35.17

TABLE 3 (continued)



95,134 230,650 119,965 192,328 85,973 138,594 55,440



15/20

Lead Poisoning 233 207 53 19 722.35 22.55 17.07 37.07 9.56

Giardiasis 203 168 54 13 2219.47 18.30 17.39 25.36 30.04

Salmonellosis 187 164 25 8 1517.94 17.86 8.05 15.61 20.48

Shigellosis 177 177 0 0 016.98 19.28 0.00 0.00 0.00

Chlamydia 172 0 186 104 6816.50 0.00 59.90 202.89 92.86

Gonorrhea 109 0 116 50 5910.45 0.00 37.36 97.54 80.57

Alcohol Dependency 105 98 34 5 210.07 10.67 10.95 9.75 2.73

Campylobacteriosis 92 74 29 7 118.82 8.06 9.34 13.66 15.02

Depressive Disorder 66 62 10 1 36.33 6.75 3.22 1.95 4.10

Hepatitis A 62 53 10 8 15.95 5.77 3.22 15.61 1.37

Alzheimers Disease 55 43 53 4 85.28 4.68 17.07 7.80 10.92

Hepatitis B 44 42 5 0 24.22 4.57 1.61 0.00 2.73

Drug Dependence 40 40 5 0 03.84 4.36 1.61 0.00 0.00

Rubella, including congenital 18 0 34 4 141.73 0.00 10.95 7.80 19.12

Syphilis, congenital 14 0 27 6 81.29 0.00 8.70 11.71 10.24

Tuberculosis 14 0 27 6 81.29 0.00 8.70 11.71 10.24

Pertussis 14 14 0 0 01.34 1.52 0.00 0.00 0.00

Meningitis (meningococcal) 9 9 0 0 00.86 0.98 0.00 0.00 0.00

Mumps 4 3 1 0 10.38 0.33 0.32 0.00 1.37

Rabies from Animal 1 0 2 1 00.10 0.00 0.64 1.95 0.00

Rabies, Human Bitten 0 0 0 0 00.00 0.00 0.00 0.00 0.00

Measles 0 0 2 0 00.00 0.00 0.64 0.00 0.00

Syphilis, infectious 0 0 0 0 00.00 0.00 0.00 0.00 0.00

Any foodborne disease 0 0 0 0 0outbreak 0.00 0.00 0.00 0.00 0.00

Any waterborne disease 0 0 0 0 0outbreak 0.00 0.00 0.00 0.00 0.00

Avoidable Hospitalizations

Congestive Heart Failure 2,704 2,246 2,239 197 261259.36 244.64 721.06 384.32 356.43

Pneumonia 2,536 2,096 1,449 185 255243.24 228.30 466.64 360.91 348.23

TABLE 3 (continued)



1,042,571 918,084 310,517 51,260 73,227



16/20

1 14 33 138 5 10 61.05 6.07 27.51 71.75 5.82 7.22 10.82

23 46 14 36 12 28 924.18 19.94 11.67 18.72 13.96 20.20 16.23

16 55 20 25 21 25 216.82 23.85 16.67 13.00 24.43 18.04 3.61

4 45 22 71 13 17 54.20 19.51 18.34 36.92 15.12 12.27 9.02

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

21 24 30 19 0 4 022.07 10.41 25.01 9.88 0.00 2.89 0.00

8 18 9 19 4 16 08.41 7.80 7.50 9.88 4.65 11.54 0.00

7 15 16 22 0 2 07.36 6.50 13.34 11.44 0.00 1.44 0.00

4 6 15 13 4 9 24.20 2.60 12.50 6.76 4.65 6.49 3.61

3 16 4 18 0 2 03.15 6.94 3.33 9.36 0.00 1.44 0.00

3 16 5 13 2 3 03.15 6.94 4.17 6.76 2.33 2.16 0.00

3 11 6 17 0 2 13.15 4.77 5.00 8.84 0.00 1.44 1.80

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 3 2 2 0 3 40.00 1.30 1.67 1.04 0.00 2.16 7.22

0 2 1 4 2 0 00.00 0.87 0.83 2.08 2.33 0.00 0.00

0 1 0 0 0 1 10.00 0.43 0.00 0.00 0.00 0.72 1.80

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

0 0 0 0 0 0 00.00 0.00 0.00 0.00 0.00 0.00 0.00

241 512 491 816 13 173 0253.33 221.98 409.29 424.28 15.12 124.83 0.00

224 558 394 726 26 168 0235.46 241.92 328.43 377.48 30.24 121.22 0.00

TABLE 3 (continued)



95,134 230,650 119,965 192,328 85,973 138,594 55,440



17/20

into six color-coded groups or categories: sociodemo-graphic, disease-specific mortality, other mortality,maternal and child health, morbidity, and avoidablehospitalizations. Within categories, the indicators arerank ordered on the basis of the volume of cases or ob-servations, in the St. JosephsBaptist CHA, from thehighest to the lowest. Additionally, those indicatorswhere the community value is unfavorable or worserelative to the CHA average are shaded. This allowsfor easier pattern recognition horizontally for each in-dicator across all communities or, vertically for each

community across all indicators.

DISCUSSION: MANAGING THEINTERVENTIONS

The data produced by the CHAPIR system have been formally integrated into BCHS managementprocess and structure. The Board of Directors of theCHAs define the mission and vision, part of whichremains to improve the health of all we serve. The

system Senior Management Team develops annualaction steps to support the mission and vision and in-cludes the specific action step to assess the commu-nitys health status, develop interventions, and meas-ure results. With the implementation of the CHAPIRsystem, the broad goal statements are now focusedand translated into specific programs and services. AHealth System Community Health Council, com-prised of the manager of community health and keydirectors and department heads who are responsiblefor selected product lines, reviews the CHAPIR find-

ings for each CHA, defines priorities, and develops anintervention plan that outlines annual objectives andmeasurable indicators. These detailed plans are thenreviewed and approved by both the Senior Manage-ment Team and the Community Affairs subcommitteeof the Board of Directors. Individual CHA plans arethen implemented and managed by the communityhealth manager and the relevant product-line depart-ment heads. On a quarterly basis, plan progress andnecessary adjustments are reported to the CommunityHealth Council and the Community Affairs subcom-


Asthma 1,427 1,260 547 90 77136.87 137.24 176.16 175.58 105.15

Cellulitis 757 634 374 54 6972.61 69.06 120.44 105.35 94.23

Perf. or Bleeding Ulcer 453 388 254 21 4443.45 42.26 81.80 40.97 60.09

Diabetes 298 256 122 18 2428.58 27.88 39.29 35.12 32.77

Pyelonephritis 282 235 111 20 2727.05 25.60 35.75 39.02 36.87

Ruptured Appendix 194 164 75 12 1818.61 17.86 24.15 23.41 24.58

Malignant Hypertension 130 92 87 11 2712.47 10.02 28.02 21.46 36.87

Hypokalemia 35 29 32 2 43.36 3.16 10.31 3.90 5.46

Gangrene 15 12 3 2 11.44 1.31 0.97 3.90 1.37

Immunizable Conditions 7 4 3 1 20.67 0.44 0.97 1.95 2.73

TABLE 3 (continued)



1,042,571 918,084 310,517 51,260 73,227



18/20

mittee of the Board. Annual updates of the CHAPIRdata will be utilized to evaluate the impact of theinterventions and to reassess community health statuspriorities.

The CHAPIR system has stimulated a variety of in-terventions in each of the three CHAs. In the largelyAfrican American communities of south Pinellascounty, high rates of late-stage breast cancer and breast cancer mortality were detected. BayfrontSt. Anthony Health Care, with external funding fromthe Susan G. Komen Foundation, developed the

SISTERS FOR BREAST HEALTH program. This pro-gram facilitates mammogram utilization and provides breast health care to African American women over40 years of age in the CHAPIR targeted community.The program utilizes the concept of Sistah Partieswith women coming forward to open up their homesand serve as hostesses for an enjoyable evening wherethe focus is breast health. Barriers to annual screeningmammograms are discussed such as fear, cost, lack oftrust in the system, and fatalistic attitudes toward can-cer. Women without insurance are referred to existing

programs for free or low-cost mammograms. Com-munity partners and organizations supporting theSISTERS program include the American Cancer Soci-ety, Pinellas County, Victorias Secret, and EsteeLauder. The average number of women attending aparty is just over 10 and about 78 parties per monthhave occurred since the start of the program. Prelimi-nary data indicate that about 32 percent of the partyparticipants have never had a mammogram and an-other 40 percent had their most recent mammogrammore than 1 year ago, so that about 72 percent of the

participants are considered eligible for a screeningmammogram.

In some communities in northern Pinellas county,mortality due to stroke was determined to be higherthan the county, peer county, and total state rates. Inneighborhoods identified for screenings by theCHAPIR system, transportation barriers were iden-tified among elderly, minority, and low-incomepopulations. Morton Plant Mease Health Care de-veloped a Mobile Medical Unit, housed in a customdesigned Airstream RV, to deliver primary care and


129 285 205 552 10 79 0135.60 123.56 170.88 287.01 11.63 57.00 0.00

75 150 113 247 4 45 078.84 65.03 94.19 128.43 4.65 32.47 0.00

48 95 83 135 3 24 050.46 41.19 69.19 70.19 3.49 17.32 0.00

34 55 38 119 1 9 035.74 23.85 31.68 61.87 1.16 6.49 0.00

34 61 38 77 2 23 035.74 26.45 31.68 40.04 2.33 16.60 0.00

22 45 30 48 3 16 023.13 19.51 25.01 24.96 3.49 11.54 0.00

17 25 15 29 1 5 017.87 10.84 12.50 15.08 1.16 3.61 0.00

6 7 4 10 0 2 06.31 3.03 3.33 5.20 0.00 1.44 0.00

2 4 2 4 0 0 02.10 1.73 1.67 2.08 0.00 0.00 0.00

1 2 1 0 0 0 01.05 0.87 0.83 0.00 0.00 0.00 0.00



95,134 230,650 119,965 192,328 85,973 138,594 55,440



19/20

prevention and education services directly to the af-fected populations. A color ultrasound unit wasplaced on the mobile unit to assist in stroke screen-ings. A nurse practitioner and nurses from MPMHCprovides services from the unit.

In west Pasco county, unintentional injury mortalityrates were identified as a high priority problem. Unin-tentional deaths from all causes such as motor vehicleaccidents, firearms, and poisonings are included inthis indicator. Further analysis indicated that theunintentional injury problem in these communitieswas found primarily in two subpopulations: childrenand senior citizens. In the absence of injury preven-tion expertise among its own members, St. Josephs-

Baptist Health Care representatives involved existingorganizations from the community. The Safe KidsCoalition and FLIPS (Florida Injury Prevention forSeniors) are now forming chapters in west Pascocounty. Local hospitals are now offering assistance,the Pasco County Health Department is helping tostaff the FLIPS chapter, and 10 other community or-ganizations have volunteered to be sponsors of theSafe Kids Coalition.

Findings of the CHAPIR system, as indicated by theexamples of interventions, are being used to targetscarce resources at the local level and to coordinatethe activities with other health and human services or-

ganizations that may be addressing different compo-nents of the same health status problem.

Community accountability is subsequently pro-moted in two very important ways. Multisectoralinvolvement is stimulated by the broad perspectiverepresented by community health status objectives(e.g., reduction in infant mortality or smoking-relatedcancer morbidity) as opposed to more limited systemoperation objectives (e.g., market share or profitabil-ity). At the same time, consensus on coordinated multi-agency approaches to assessment and integratedinterventions become more easily achievable. From amanagement perspective, the key constraint on this

system is the continuing lack of systematic financialincentives to reward BCHS and other providers foraddressing population health status. Conceivably, theimproved health status of enrolled populations willallow for increased operating margins for managedcare, some of which may be shared with providers.CHAPIR and similarly constructed decision supportsystems, however, will be essential for those healthcare organizations committed to improving the healthstatus of their communities.

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10. Kaplan, G., Pamuk, E., Lynch, J., Cohen, R., and Bal-four, J. Inequality in Income and Mortality in theUnited States: An Analysis of Mortality and PotentialPathways. British Medical Journal 312 (1996): 9991003.

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18. Shortell, S. A Model for State Health Reform.HealthAffairs 11 (Spring 1992): 10827.

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21. Quote from unpublished internal document, A Sum-mary Analysis of the Tampa Bay Area Joint OperatingAgreement.

22. Devers, K.J., Shortell, S.M., Gillies, R.R., Anderson, D.A.,Mitchell, J.B., Erickson, K.L.M. Implementing Orga-nized Delivery Systems: An Integration Scorecard.

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