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Exploring Proxy Measures of Mutuality for Strategic Partnership Development: A Case Study.
Mayo-Gamble TL, Barnes PA, Sherwood-Laughlin CM, Reece M, DeWeese S, Kennedy CW, Valenta MA
(2017) Health Promot Pract 18: 598-606
MeSH Terms: Capacity Building, Cooperative Behavior, Education, Public Health Professional, Hospital Administration, Humans, Interinstitutional Relations, Organizational Case Studies, Organizational Objectives, Policy
Show Abstract · Added April 26, 2017
Partnerships between academic and clinical-based health organizations are becoming increasingly important in improving health outcomes. Mutuality is recognized as a vital component of these partnerships. If partnerships are to achieve mutuality, there is a need to define what it means to partnering organizations. Few studies have described the elements contributing to mutuality, particularly in new relationships between academic and clinical partners. This study seeks to identify how mutuality is expressed and to explore potential proxy measures of mutuality for an alliance consisting of a hospital system and a School of Public Health. Key informant interviews were conducted with faculty and hospital representatives serving on the partnership steering committee. Key informants were asked about perceived events that led to the development of the Alliance; perceived goals, expectations, and outcomes; and current/future roles with the Alliance. Four proxy measures of mutuality for an academic-clinical partnership were identified: policy directives, community beneficence, procurement of human capital, and partnership longevity. Findings can inform the development of tools for assisting in strengthening relationships and ensuring stakeholders' interests align with the mission and goal of the partnership by operationalizing elements necessary to evaluate the progress of the partnership.
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9 MeSH Terms
Global, regional, and national levels and causes of maternal mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.
Kassebaum NJ, Bertozzi-Villa A, Coggeshall MS, Shackelford KA, Steiner C, Heuton KR, Gonzalez-Medina D, Barber R, Huynh C, Dicker D, Templin T, Wolock TM, Ozgoren AA, Abd-Allah F, Abera SF, Abubakar I, Achoki T, Adelekan A, Ademi Z, Adou AK, Adsuar JC, Agardh EE, Akena D, Alasfoor D, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Al Kahbouri MJ, Alla F, Allen PJ, AlMazroa MA, Alsharif U, Alvarez E, Alvis-Guzmán N, Amankwaa AA, Amare AT, Amini H, Ammar W, Antonio CA, Anwari P, Arnlöv J, Arsenijevic VS, Artaman A, Asad MM, Asghar RJ, Assadi R, Atkins LS, Badawi A, Balakrishnan K, Basu A, Basu S, Beardsley J, Bedi N, Bekele T, Bell ML, Bernabe E, Beyene TJ, Bhutta Z, Bin Abdulhak A, Blore JD, Basara BB, Bose D, Breitborde N, Cárdenas R, Castañeda-Orjuela CA, Castro RE, Catalá-López F, Cavlin A, Chang JC, Che X, Christophi CA, Chugh SS, Cirillo M, Colquhoun SM, Cooper LT, Cooper C, da Costa Leite I, Dandona L, Dandona R, Davis A, Dayama A, Degenhardt L, De Leo D, del Pozo-Cruz B, Deribe K, Dessalegn M, deVeber GA, Dharmaratne SD, Dilmen U, Ding EL, Dorrington RE, Driscoll TR, Ermakov SP, Esteghamati A, Faraon EJ, Farzadfar F, Felicio MM, Fereshtehnejad SM, de Lima GM, Forouzanfar MH, França EB, Gaffikin L, Gambashidze K, Gankpé FG, Garcia AC, Geleijnse JM, Gibney KB, Giroud M, Glaser EL, Goginashvili K, Gona P, González-Castell D, Goto A, Gouda HN, Gugnani HC, Gupta R, Gupta R, Hafezi-Nejad N, Hamadeh RR, Hammami M, Hankey GJ, Harb HL, Havmoeller R, Hay SI, Pi IB, Hoek HW, Hosgood HD, Hoy DG, Husseini A, Idrisov BT, Innos K, Inoue M, Jacobsen KH, Jahangir E, Jee SH, Jensen PN, Jha V, Jiang G, Jonas JB, Juel K, Kabagambe EK, Kan H, Karam NE, Karch A, Karema CK, Kaul A, Kawakami N, Kazanjan K, Kazi DS, Kemp AH, Kengne AP, Kereselidze M, Khader YS, Khalifa SE, Khan EA, Khang YH, Knibbs L, Kokubo Y, Kosen S, Defo BK, Kulkarni C, Kulkarni VS, Kumar GA, Kumar K, Kumar RB, Kwan G, Lai T, Lalloo R, Lam H, Lansingh VC, Larsson A, Lee JT, Leigh J, Leinsalu M, Leung R, Li X, Li Y, Li Y, Liang J, Liang X, Lim SS, Lin HH, Lipshultz SE, Liu S, Liu Y, Lloyd BK, London SJ, Lotufo PA, Ma J, Ma S, Machado VM, Mainoo NK, Majdan M, Mapoma CC, Marcenes W, Marzan MB, Mason-Jones AJ, Mehndiratta MM, Mejia-Rodriguez F, Memish ZA, Mendoza W, Miller TR, Mills EJ, Mokdad AH, Mola GL, Monasta L, de la Cruz Monis J, Hernandez JC, Moore AR, Moradi-Lakeh M, Mori R, Mueller UO, Mukaigawara M, Naheed A, Naidoo KS, Nand D, Nangia V, Nash D, Nejjari C, Nelson RG, Neupane SP, Newton CR, Ng M, Nieuwenhuijsen MJ, Nisar MI, Nolte S, Norheim OF, Nyakarahuka L, Oh IH, Ohkubo T, Olusanya BO, Omer SB, Opio JN, Orisakwe OE, Pandian JD, Papachristou C, Park JH, Caicedo AJ, Patten SB, Paul VK, Pavlin BI, Pearce N, Pereira DM, Pesudovs K, Petzold M, Poenaru D, Polanczyk GV, Polinder S, Pope D, Pourmalek F, Qato D, Quistberg DA, Rafay A, Rahimi K, Rahimi-Movaghar V, ur Rahman S, Raju M, Rana SM, Refaat A, Ronfani L, Roy N, Pimienta TG, Sahraian MA, Salomon JA, Sampson U, Santos IS, Sawhney M, Sayinzoga F, Schneider IJ, Schumacher A, Schwebel DC, Seedat S, Sepanlou SG, Servan-Mori EE, Shakh-Nazarova M, Sheikhbahaei S, Shibuya K, Shin HH, Shiue I, Sigfusdottir ID, Silberberg DH, Silva AP, Singh JA, Skirbekk V, Sliwa K, Soshnikov SS, Sposato LA, Sreeramareddy CT, Stroumpoulis K, Sturua L, Sykes BL, Tabb KM, Talongwa RT, Tan F, Teixeira CM, Tenkorang EY, Terkawi AS, Thorne-Lyman AL, Tirschwell DL, Towbin JA, Tran BX, Tsilimbaris M, Uchendu US, Ukwaja KN, Undurraga EA, Uzun SB, Vallely AJ, van Gool CH, Vasankari TJ, Vavilala MS, Venketasubramanian N, Villalpando S, Violante FS, Vlassov VV, Vos T, Waller S, Wang H, Wang L, Wang X, Wang Y, Weichenthal S, Weiderpass E, Weintraub RG, Westerman R, Wilkinson JD, Woldeyohannes SM, Wong JQ, Wordofa MA, Xu G, Yang YC, Yano Y, Yentur GK, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Jin KY, El Sayed Zaki M, Zhao Y, Zheng Y, Zhou M, Zhu J, Zou XN, Lopez AD, Naghavi M, Murray CJ, Lozano R
(2014) Lancet 384: 980-1004
MeSH Terms: Age Distribution, Cause of Death, Female, Global Health, HIV Infections, Humans, Maternal Mortality, Models, Statistical, Organizational Objectives, Pregnancy, Pregnancy Complications, Infectious, Risk Factors, Socioeconomic Factors, Time Factors
Show Abstract · Added May 19, 2014
BACKGROUND - The fifth Millennium Development Goal (MDG 5) established the goal of a 75% reduction in the maternal mortality ratio (MMR; number of maternal deaths per 100,000 livebirths) between 1990 and 2015. We aimed to measure levels and track trends in maternal mortality, the key causes contributing to maternal death, and timing of maternal death with respect to delivery.
METHODS - We used robust statistical methods including the Cause of Death Ensemble model (CODEm) to analyse a database of data for 7065 site-years and estimate the number of maternal deaths from all causes in 188 countries between 1990 and 2013. We estimated the number of pregnancy-related deaths caused by HIV on the basis of a systematic review of the relative risk of dying during pregnancy for HIV-positive women compared with HIV-negative women. We also estimated the fraction of these deaths aggravated by pregnancy on the basis of a systematic review. To estimate the numbers of maternal deaths due to nine different causes, we identified 61 sources from a systematic review and 943 site-years of vital registration data. We also did a systematic review of reports about the timing of maternal death, identifying 142 sources to use in our analysis. We developed estimates for each country for 1990-2013 using Bayesian meta-regression. We estimated 95% uncertainty intervals (UIs) for all values.
FINDINGS - 292,982 (95% UI 261,017-327,792) maternal deaths occurred in 2013, compared with 376,034 (343,483-407,574) in 1990. The global annual rate of change in the MMR was -0·3% (-1·1 to 0·6) from 1990 to 2003, and -2·7% (-3·9 to -1·5) from 2003 to 2013, with evidence of continued acceleration. MMRs reduced consistently in south, east, and southeast Asia between 1990 and 2013, but maternal deaths increased in much of sub-Saharan Africa during the 1990s. 2070 (1290-2866) maternal deaths were related to HIV in 2013, 0·4% (0·2-0·6) of the global total. MMR was highest in the oldest age groups in both 1990 and 2013. In 2013, most deaths occurred intrapartum or postpartum. Causes varied by region and between 1990 and 2013. We recorded substantial variation in the MMR by country in 2013, from 956·8 (685·1-1262·8) in South Sudan to 2·4 (1·6-3·6) in Iceland.
INTERPRETATION - Global rates of change suggest that only 16 countries will achieve the MDG 5 target by 2015. Accelerated reductions since the Millennium Declaration in 2000 coincide with increased development assistance for maternal, newborn, and child health. Setting of targets and associated interventions for after 2015 will need careful consideration of regions that are making slow progress, such as west and central Africa.
FUNDING - Bill & Melinda Gates Foundation.
Copyright © 2014 Elsevier Ltd. All rights reserved.
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14 MeSH Terms
Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.
Wang H, Liddell CA, Coates MM, Mooney MD, Levitz CE, Schumacher AE, Apfel H, Iannarone M, Phillips B, Lofgren KT, Sandar L, Dorrington RE, Rakovac I, Jacobs TA, Liang X, Zhou M, Zhu J, Yang G, Wang Y, Liu S, Li Y, Ozgoren AA, Abera SF, Abubakar I, Achoki T, Adelekan A, Ademi Z, Alemu ZA, Allen PJ, AlMazroa MA, Alvarez E, Amankwaa AA, Amare AT, Ammar W, Anwari P, Cunningham SA, Asad MM, Assadi R, Banerjee A, Basu S, Bedi N, Bekele T, Bell ML, Bhutta Z, Blore JD, Basara BB, Boufous S, Breitborde N, Bruce NG, Bui LN, Carapetis JR, Cárdenas R, Carpenter DO, Caso V, Castro RE, Catalá-Lopéz F, Cavlin A, Che X, Chiang PP, Chowdhury R, Christophi CA, Chuang TW, Cirillo M, da Costa Leite I, Courville KJ, Dandona L, Dandona R, Davis A, Dayama A, Deribe K, Dharmaratne SD, Dherani MK, Dilmen U, Ding EL, Edmond KM, Ermakov SP, Farzadfar F, Fereshtehnejad SM, Fijabi DO, Foigt N, Forouzanfar MH, Garcia AC, Geleijnse JM, Gessner BD, Goginashvili K, Gona P, Goto A, Gouda HN, Green MA, Greenwell KF, Gugnani HC, Gupta R, Hamadeh RR, Hammami M, Harb HL, Hay S, Hedayati MT, Hosgood HD, Hoy DG, Idrisov BT, Islami F, Ismayilova S, Jha V, Jiang G, Jonas JB, Juel K, Kabagambe EK, Kazi DS, Kengne AP, Kereselidze M, Khader YS, Khalifa SE, Khang YH, Kim D, Kinfu Y, Kinge JM, Kokubo Y, Kosen S, Defo BK, Kumar GA, Kumar K, Kumar RB, Lai T, Lan Q, Larsson A, Lee JT, Leinsalu M, Lim SS, Lipshultz SE, Logroscino G, Lotufo PA, Lunevicius R, Lyons RA, Ma S, Mahdi AA, Marzan MB, Mashal MT, Mazorodze TT, McGrath JJ, Memish ZA, Mendoza W, Mensah GA, Meretoja A, Miller TR, Mills EJ, Mohammad KA, Mokdad AH, Monasta L, Montico M, Moore AR, Moschandreas J, Msemburi WT, Mueller UO, Muszynska MM, Naghavi M, Naidoo KS, Narayan KM, Nejjari C, Ng M, de Dieu Ngirabega J, Nieuwenhuijsen MJ, Nyakarahuka L, Ohkubo T, Omer SB, Caicedo AJ, Pillay-van Wyk V, Pope D, Pourmalek F, Prabhakaran D, Rahman SU, Rana SM, Reilly RQ, Rojas-Rueda D, Ronfani L, Rushton L, Saeedi MY, Salomon JA, Sampson U, Santos IS, Sawhney M, Schmidt JC, Shakh-Nazarova M, She J, Sheikhbahaei S, Shibuya K, Shin HH, Shishani K, Shiue I, Sigfusdottir ID, Singh JA, Skirbekk V, Sliwa K, Soshnikov SS, Sposato LA, Stathopoulou VK, Stroumpoulis K, Tabb KM, Talongwa RT, Teixeira CM, Terkawi AS, Thomson AJ, Thorne-Lyman AL, Toyoshima H, Dimbuene ZT, Uwaliraye P, Uzun SB, Vasankari TJ, Vasconcelos AM, Vlassov VV, Vollset SE, Waller S, Wan X, Weichenthal S, Weiderpass E, Weintraub RG, Westerman R, Wilkinson JD, Williams HC, Yang YC, Yentur GK, Yip P, Yonemoto N, Younis M, Yu C, Jin KY, El Sayed Zaki M, Zhu S, Vos T, Lopez AD, Murray CJ
(2014) Lancet 384: 957-79
MeSH Terms: Child Mortality, Child, Preschool, Global Health, Humans, Infant, Infant Mortality, Infant, Newborn, Organizational Objectives, Risk Factors, Socioeconomic Factors
Show Abstract · Added May 19, 2014
BACKGROUND - Remarkable financial and political efforts have been focused on the reduction of child mortality during the past few decades. Timely measurements of levels and trends in under-5 mortality are important to assess progress towards the Millennium Development Goal 4 (MDG 4) target of reduction of child mortality by two thirds from 1990 to 2015, and to identify models of success.
METHODS - We generated updated estimates of child mortality in early neonatal (age 0-6 days), late neonatal (7-28 days), postneonatal (29-364 days), childhood (1-4 years), and under-5 (0-4 years) age groups for 188 countries from 1970 to 2013, with more than 29,000 survey, census, vital registration, and sample registration datapoints. We used Gaussian process regression with adjustments for bias and non-sampling error to synthesise the data for under-5 mortality for each country, and a separate model to estimate mortality for more detailed age groups. We used explanatory mixed effects regression models to assess the association between under-5 mortality and income per person, maternal education, HIV child death rates, secular shifts, and other factors. To quantify the contribution of these different factors and birth numbers to the change in numbers of deaths in under-5 age groups from 1990 to 2013, we used Shapley decomposition. We used estimated rates of change between 2000 and 2013 to construct under-5 mortality rate scenarios out to 2030.
FINDINGS - We estimated that 6·3 million (95% UI 6·0-6·6) children under-5 died in 2013, a 64% reduction from 17·6 million (17·1-18·1) in 1970. In 2013, child mortality rates ranged from 152·5 per 1000 livebirths (130·6-177·4) in Guinea-Bissau to 2·3 (1·8-2·9) per 1000 in Singapore. The annualised rates of change from 1990 to 2013 ranged from -6·8% to 0·1%. 99 of 188 countries, including 43 of 48 countries in sub-Saharan Africa, had faster decreases in child mortality during 2000-13 than during 1990-2000. In 2013, neonatal deaths accounted for 41·6% of under-5 deaths compared with 37·4% in 1990. Compared with 1990, in 2013, rising numbers of births, especially in sub-Saharan Africa, led to 1·4 million more child deaths, and rising income per person and maternal education led to 0·9 million and 2·2 million fewer deaths, respectively. Changes in secular trends led to 4·2 million fewer deaths. Unexplained factors accounted for only -1% of the change in child deaths. In 30 developing countries, decreases since 2000 have been faster than predicted attributable to income, education, and secular shift alone.
INTERPRETATION - Only 27 developing countries are expected to achieve MDG 4. Decreases since 2000 in under-5 mortality rates are accelerating in many developing countries, especially in sub-Saharan Africa. The Millennium Declaration and increased development assistance for health might have been a factor in faster decreases in some developing countries. Without further accelerated progress, many countries in west and central Africa will still have high levels of under-5 mortality in 2030.
FUNDING - Bill & Melinda Gates Foundation, US Agency for International Development.
Copyright © 2014 Elsevier Ltd. All rights reserved.
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10 MeSH Terms
Barrett's Esophagus Translational Research Network (BETRNet): the pivotal role of multi-institutional collaboration in esophageal adenocarcinoma research.
Abrams JA, Appelman HD, Beer DG, Berry LD, Chak A, Falk GW, Fitzgerald RC, Ginsberg GG, Grady WM, Joshi BP, Lynch JP, Markowitz S, Richmond ES, Rustgi AK, Seibel EJ, Shaheen NJ, Shyr Y, Umar A, Wang KK, Wang TC, Wang TD, Yassin R
(2014) Gastroenterology 146: 1586-90
MeSH Terms: Adenocarcinoma, Animals, Barrett Esophagus, Cooperative Behavior, Databases, Factual, Esophageal Neoplasms, Humans, Interinstitutional Relations, Organizational Objectives, Prognosis, Risk Factors, Tissue Banks, Translational Medical Research
Added February 19, 2015
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13 MeSH Terms
The dormant National Health Care Workforce Commission needs congressional funding to fulfill its promise.
Buerhaus PI, Retchin SM
(2013) Health Aff (Millwood) 32: 2021-4
MeSH Terms: Advisory Committees, Financing, Government, Health Policy, Health Services Research, Health Workforce, Humans, Organizational Objectives, Patient Protection and Affordable Care Act, United States
Show Abstract · Added March 7, 2014
Congress established the National Health Care Workforce Commission under section 5101 of the Affordable Care Act to provide data on the health care workforce and policy advice to both Congress and the administration. Although members of the Workforce Commission were appointed September 30, 2010, Congress has been unable to appropriate the $3 million requested by the administration to fund the commission. Consequently, the commission has never met and is not operational. As a new era of insurance coverage, care delivery, and payment reforms unfolds, the commission is needed to recommend policies that would help the nation achieve the goals of increased access to high-quality care and better preparation, configuration, and distribution of the nation's health workforce. In a climate where fiscal policy is dominated by spending on health care, the commission can also stimulate innovations aimed at reducing the cost of health care and achieving greater value and transparency.
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9 MeSH Terms
Levels of data: the whys and hows of selection and analysis.
Minnick A
(2000) Outcomes Manag Nurs Pract 4: 106-9
MeSH Terms: Benchmarking, Data Collection, Data Interpretation, Statistical, Health Services Research, Humans, Organizational Objectives, Outcome Assessment (Health Care), Reproducibility of Results, Selection Bias, Total Quality Management
Show Abstract · Added January 20, 2015
There are many challenges in selecting the level of a variable for data collection and analysis. Meeting these challenges is labor intensive and requires considerable skill; however, if a performance improvement project is to produce sound results, shortcuts cannot be taken. Studies that purport to show the impact of important variables on care influence the allocation of resources. The choice of a working unit level of analysis may be highly useful in meeting project goals and statistical requirements, but familiarity with multilevel techniques remains essential. If all or some of the variables must be aggregated, information about individual response rate, the extent and treatment of missing data, and tests of the collinearity of the aggregate data need to be made before proceeding with the analysis.
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10 MeSH Terms
Use of a faculty investment model to attain the goals of a college of nursing.
Minnick AF, Halstead L
(2001) J Prof Nurs 17: 74-80
MeSH Terms: Chicago, Faculty, Nursing, Financial Management, Humans, Investments, Middle Aged, Models, Organizational, Organizational Objectives, Schools, Nursing, Total Quality Management
Show Abstract · Added January 20, 2015
Driven by demands for fiscal prudence, new services, and an orderly transition as aging faculty approach retirement, a new model for administrative planning and decision making was tested. In its first year of using an investment model, a private, 600+ student, College of Nursing was able to achieve a labor savings of 10 percent, an enhancement of revenue of 3 percent, and a human capital pool equal to 12 percent of total full-time faculty equivalents. The model, which includes the integration of strategic planning, benchmarking, continuous quality improvement, and management by objectives, was accomplished by taking three investment steps. The steps included goal determination, market understanding, and resource allocation. Investment activity distribution and work determination frameworks were developed as a result of the commitment to the investment process. Suggestions for the future include the need to continue to reorient administrative and faculty thinking as definitions of the educational enterprise evolve.
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10 MeSH Terms